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2026,49(2): 217-227, DOI: 10.13878/j.cnki.dqkxxb.20260107005
Abstract:
In late July 2025, Beijing experienced a prolonged and disastrous rainstorm event (hereafter referred to as the “25.7” event), which caused severe economic losses and casualties.Using high-resolution precipitation observations from national and regional meteorological stations in Beijing during 1961—2025, this study examines the refined characteristics of this extreme rainfall event and investigates the associated large-scale anomalous circulation background and moisture transport mechanisms.The results show that the “25.7” event occurred against a background of anomalously wet summer conditions and an earlier-than-normal onset of the rainy season in Beijing, with a marked increase in regional heavy precipitation events since 2010.During the event, the citywide mean accumulated precipitation reached 211.1 mm.The Miyun station recorded its highest rainfall since 1961 (366.6 mm), while a local maximum of 574.3 mm was observed at the Langfangyu station.Notably, the duration of continuous precipitation over Beijing reached 147 h, exceeding the historical record set during the “63.8” event in 1963.At the Miyun station, heavy rainfall persisted for approximately 106 h, with rainfall intensity exceeding 20 mm·h-1 for 42 h.Compared with other major rainstorm events since 2010, the “25.7” event ranks among the most extreme in terms of mean rainfall amount, duration and local maxima.Circulation analyses reveal that during the summer of 2025, the 500 hPa geopotential height anomaly field over the mid-high latitudes of Eurasia exhibited a pronounced “negative-positive-negative” teleconnection wave train, whose energy dispersion and persistent intensification provided a favorable large-scale background for extreme precipitation.Concurrently, the western Pacific subtropical high (WPSH) was stronger and positioned farther north than climatology, with its western ridge line remaining north of 35°N in late July.Together with a significantly enhanced East Asian summer monsoon, these conditions established an efficient moisture transport pathway toward northern China.During the “25.7” event, a deep trough was located near Lake Baikal at 500 hPa level, placing the Beijing-Tianjin-Hebei region ahead of the trough.The northern boundary of the WPSH extended anomalously to approximately 40°N, and a strong southeasterly low-level jet developed between the WPSH and the low-pressure system to its north.In addition, Typhoons Francisco and Co-may further intensified and sustained the moisture transport along the southeastern pathway toward Beijing.The combined effects of these circulation features ultimately led to this record-breaking, long-lasting, and extreme rainfall event.
In late July 2025, Beijing experienced a prolonged and disastrous rainstorm event (hereafter referred to as the “25.7” event), which caused severe economic losses and casualties.Using high-resolution precipitation observations from national and regional meteorological stations in Beijing during 1961—2025, this study examines the refined characteristics of this extreme rainfall event and investigates the associated large-scale anomalous circulation background and moisture transport mechanisms.The results show that the “25.7” event occurred against a background of anomalously wet summer conditions and an earlier-than-normal onset of the rainy season in Beijing, with a marked increase in regional heavy precipitation events since 2010.During the event, the citywide mean accumulated precipitation reached 211.1 mm.The Miyun station recorded its highest rainfall since 1961 (366.6 mm), while a local maximum of 574.3 mm was observed at the Langfangyu station.Notably, the duration of continuous precipitation over Beijing reached 147 h, exceeding the historical record set during the “63.8” event in 1963.At the Miyun station, heavy rainfall persisted for approximately 106 h, with rainfall intensity exceeding 20 mm·h-1 for 42 h.Compared with other major rainstorm events since 2010, the “25.7” event ranks among the most extreme in terms of mean rainfall amount, duration and local maxima.Circulation analyses reveal that during the summer of 2025, the 500 hPa geopotential height anomaly field over the mid-high latitudes of Eurasia exhibited a pronounced “negative-positive-negative” teleconnection wave train, whose energy dispersion and persistent intensification provided a favorable large-scale background for extreme precipitation.Concurrently, the western Pacific subtropical high (WPSH) was stronger and positioned farther north than climatology, with its western ridge line remaining north of 35°N in late July.Together with a significantly enhanced East Asian summer monsoon, these conditions established an efficient moisture transport pathway toward northern China.During the “25.7” event, a deep trough was located near Lake Baikal at 500 hPa level, placing the Beijing-Tianjin-Hebei region ahead of the trough.The northern boundary of the WPSH extended anomalously to approximately 40°N, and a strong southeasterly low-level jet developed between the WPSH and the low-pressure system to its north.In addition, Typhoons Francisco and Co-may further intensified and sustained the moisture transport along the southeastern pathway toward Beijing.The combined effects of these circulation features ultimately led to this record-breaking, long-lasting, and extreme rainfall event.
2026,49(2): 228-242, DOI: 10.13878/j.cnki.dqkxxb.20250307003
Abstract:
Under ongoing global warming,the climate system has exhibited increasingly frequent and unevenly distributed extreme weather and climate events worldwide.In particular,extreme precipitation events over the North China Plain (NCP) have shown a pronounced increase in sub-daily and hourly extremes since 2000.Extraordinary persistent heavy rainfall events (PHREs),often accompanied by record-breaking flash heavy rainfall (FHR),have repeatedly affected the Beijing-Tianjin-Hebei urban agglomeration,resulting in severe casualties,environmental damage,economic losses,and public concern,partly due to limitations in accurately predicting FHRs embedded within PHREs.Originating from complex interactions among multiscale atmospheric systems and the coupling between mesoscale or storm-scale structures and intense weather phenomena,FHRs remain a major challenge in meteorology.Compared with isolated FHRs occurring during individual rainstorms,those embedded within PHREs—characterized by varying intensities,durations,and spatial distributions—are generally more destructive.Previous studies have emphasized the dominant roles of meridional and zonal synoptic patterns in PHREs.However,the characteristics of FHRs during PHREs have often been obscured by based on daily-mean datasets,with primary focus on planetary- and synoptic-scale systems.In this study,the record-breaking extreme rainfall event in late July 2023 (hereafter referred to as the “23.7” event),which produced an average accumulated precipitation exceeding 300 mm over Beijing and a maximum hourly rainfall exceeding 111 mm,is comprehensively examined.
Using multi-source precipitation observations,reanalysis dataset,and historical PHREs over the NCP during the past 60 years,we investigate the synoptic characteristics and unbalanced flow features of the “23.7” event across different FHR stages.Diagnostic analyses include calculations of characteristic thermal and moisture variables,statistical comparisons,and dynamic approximations to separate ageostrophic and unbalanced flows.Comparative studies indicate that the “23.7” event is historically rare,persisting for approximately 83 h,with several rain gauge stations recording cumulative precipitation exceeding 800 mm.Quantitative analyses reveal that anomalies in 850 hPa moisture flux,lower-level warm and humid centers,vertical velocity,and convergence between southeasterly flows and topography were approximately 3—4,4—5,1.5,and 3 times larger,respectively,than those in historical PHREs.Further comparisons with two other extreme PHREs occurring after 2010 show that the “23.7” event was characterized by exceptionally persistent southeasterly moisture transport and convergence.Analyses of ageostrophic and unbalanced winds derived from geostrophic and nonlinear balance approximations demonstrate that unbalanced flows in the lower and middle troposphere better correspond to the spatial locations and intensity evolution of rainfall centers during the two major FHR stages over the central and northern Taihang Mountains.These findings are further supported by S-band and X-band radar observations,which reveal the evolution of mesoscale convective systems responsible for the two FHR episodes during the “23.7” event.This study provides a quantitative and comparative assessment of FHR processes embedded within an extreme PHRE and highlights the importance of unbalanced flows in modulating rainfall intensity and distribution.Future work should incorporate higher-resolution,multi-source observations to further elucidate the physical mechanisms governing FHRs across multiple temporal and spatial scales,with the goal of improving early-warning and forecasting of extreme rainfall during PHREs.
Under ongoing global warming,the climate system has exhibited increasingly frequent and unevenly distributed extreme weather and climate events worldwide.In particular,extreme precipitation events over the North China Plain (NCP) have shown a pronounced increase in sub-daily and hourly extremes since 2000.Extraordinary persistent heavy rainfall events (PHREs),often accompanied by record-breaking flash heavy rainfall (FHR),have repeatedly affected the Beijing-Tianjin-Hebei urban agglomeration,resulting in severe casualties,environmental damage,economic losses,and public concern,partly due to limitations in accurately predicting FHRs embedded within PHREs.Originating from complex interactions among multiscale atmospheric systems and the coupling between mesoscale or storm-scale structures and intense weather phenomena,FHRs remain a major challenge in meteorology.Compared with isolated FHRs occurring during individual rainstorms,those embedded within PHREs—characterized by varying intensities,durations,and spatial distributions—are generally more destructive.Previous studies have emphasized the dominant roles of meridional and zonal synoptic patterns in PHREs.However,the characteristics of FHRs during PHREs have often been obscured by based on daily-mean datasets,with primary focus on planetary- and synoptic-scale systems.In this study,the record-breaking extreme rainfall event in late July 2023 (hereafter referred to as the “23.7” event),which produced an average accumulated precipitation exceeding 300 mm over Beijing and a maximum hourly rainfall exceeding 111 mm,is comprehensively examined.
Using multi-source precipitation observations,reanalysis dataset,and historical PHREs over the NCP during the past 60 years,we investigate the synoptic characteristics and unbalanced flow features of the “23.7” event across different FHR stages.Diagnostic analyses include calculations of characteristic thermal and moisture variables,statistical comparisons,and dynamic approximations to separate ageostrophic and unbalanced flows.Comparative studies indicate that the “23.7” event is historically rare,persisting for approximately 83 h,with several rain gauge stations recording cumulative precipitation exceeding 800 mm.Quantitative analyses reveal that anomalies in 850 hPa moisture flux,lower-level warm and humid centers,vertical velocity,and convergence between southeasterly flows and topography were approximately 3—4,4—5,1.5,and 3 times larger,respectively,than those in historical PHREs.Further comparisons with two other extreme PHREs occurring after 2010 show that the “23.7” event was characterized by exceptionally persistent southeasterly moisture transport and convergence.Analyses of ageostrophic and unbalanced winds derived from geostrophic and nonlinear balance approximations demonstrate that unbalanced flows in the lower and middle troposphere better correspond to the spatial locations and intensity evolution of rainfall centers during the two major FHR stages over the central and northern Taihang Mountains.These findings are further supported by S-band and X-band radar observations,which reveal the evolution of mesoscale convective systems responsible for the two FHR episodes during the “23.7” event.This study provides a quantitative and comparative assessment of FHR processes embedded within an extreme PHRE and highlights the importance of unbalanced flows in modulating rainfall intensity and distribution.Future work should incorporate higher-resolution,multi-source observations to further elucidate the physical mechanisms governing FHRs across multiple temporal and spatial scales,with the goal of improving early-warning and forecasting of extreme rainfall during PHREs.
2026,49(2): 243-257, DOI: 10.13878/j.cnki.dqkxxb.20250223001
Abstract:
The Amazon Rainforest,the world's largest tropical rainforest,has experienced increasingly frequent wildfires and intensified deforestation over the past two decades.Aerosols and greenhouse gases emitted by these fires not only pose serious risks to human health and ecosystems but also influence the global climate system through radiative forcing,land-atmospheric interactions,and biogeochemical processes.Using the Community Earth System Model (CESM),this study investigates the impacts of Amazon wildfire aerosols on the tropical Pacific climate and the El Niño-Southern Oscillation (ENSO).The results show that Amazon wildfire aerosols induce pronounced climatic responses in the tropics.Aerosol radiative effects generate significant cooling in the eastern equatorial Pacific and the subtropical South Atlantic,which spreads across the tropical oceans.The enhanced cooling in the equatorial Pacific strengthens the zonal sea surface temperature gradient,intensifying easterly trade winds over the central and western equatorial Pacific.This dynamical adjustment increases sea surface height and deepens the thermocline in the western and central Pacific,thereby strengthening subsurface ocean circulation across the equatorial Pacific.Concurrently,tropical cooling suppresses precipitation in the western equatorial Pacific,particularly along the southern branch of the Intertropical Convergence Zone (ITCZ).Changes in the mean state of the tropical Pacific climate further modulate ENSO characteristics,leading to a prolonged ENSO period,an increased occurrence of multi-year ENSO events,a higher frequency and intensity of extreme El Niño events,and enhanced ENSO asymmetry.The increase in multi-year events advances ENSO onset timing and results in extended development phases and slower growth rates,partly attributable to strengthened nonlinear damping processes.Amazon wildfire aerosols also modulate the global climate impacts of ENSO.ENSO-related precipitation anomalies are weakened over the tropical Pacific and Atlantic but intensified over the tropical Indian Ocean.Correspondingly,the Pacific-North America (PNA) and Pacific-Japan (PJ) teleconnection patterns are weakened.Finally,when considered in the context of global warming,the results suggest that although aerosol emissions from Amazon wildfires may temporarily offset warming through radiative cooling,the long-term effects of vegetation loss and enhanced greenhouse gas emissions are likely to exacerbate global warming.These findings demonstrate that Amazon wildfire aerosols are not merely a byproduct of climate change but an active regulator of tropical climate variability and ENSO,with important implications for future climate change projections and ENSO prediction.
The Amazon Rainforest,the world's largest tropical rainforest,has experienced increasingly frequent wildfires and intensified deforestation over the past two decades.Aerosols and greenhouse gases emitted by these fires not only pose serious risks to human health and ecosystems but also influence the global climate system through radiative forcing,land-atmospheric interactions,and biogeochemical processes.Using the Community Earth System Model (CESM),this study investigates the impacts of Amazon wildfire aerosols on the tropical Pacific climate and the El Niño-Southern Oscillation (ENSO).The results show that Amazon wildfire aerosols induce pronounced climatic responses in the tropics.Aerosol radiative effects generate significant cooling in the eastern equatorial Pacific and the subtropical South Atlantic,which spreads across the tropical oceans.The enhanced cooling in the equatorial Pacific strengthens the zonal sea surface temperature gradient,intensifying easterly trade winds over the central and western equatorial Pacific.This dynamical adjustment increases sea surface height and deepens the thermocline in the western and central Pacific,thereby strengthening subsurface ocean circulation across the equatorial Pacific.Concurrently,tropical cooling suppresses precipitation in the western equatorial Pacific,particularly along the southern branch of the Intertropical Convergence Zone (ITCZ).Changes in the mean state of the tropical Pacific climate further modulate ENSO characteristics,leading to a prolonged ENSO period,an increased occurrence of multi-year ENSO events,a higher frequency and intensity of extreme El Niño events,and enhanced ENSO asymmetry.The increase in multi-year events advances ENSO onset timing and results in extended development phases and slower growth rates,partly attributable to strengthened nonlinear damping processes.Amazon wildfire aerosols also modulate the global climate impacts of ENSO.ENSO-related precipitation anomalies are weakened over the tropical Pacific and Atlantic but intensified over the tropical Indian Ocean.Correspondingly,the Pacific-North America (PNA) and Pacific-Japan (PJ) teleconnection patterns are weakened.Finally,when considered in the context of global warming,the results suggest that although aerosol emissions from Amazon wildfires may temporarily offset warming through radiative cooling,the long-term effects of vegetation loss and enhanced greenhouse gas emissions are likely to exacerbate global warming.These findings demonstrate that Amazon wildfire aerosols are not merely a byproduct of climate change but an active regulator of tropical climate variability and ENSO,with important implications for future climate change projections and ENSO prediction.
2026,49(2): 258-271, DOI: 10.13878/j.cnki.dqkxxb.20250401002
Abstract:
The western North Pacific anomalous circulation (WNPAC),manifested as large-scale anticyclonic or cyclonic circulation anomalies over the western North Pacific during boreal summer,is a key component of the East Asian summer monsoon system.It exerts substantial influence on regional precipitation,flood-drought variability,and tropical cyclone activity in East Asia.In particular,an anomalous anticyclonic circulation enhances southwesterly moisture transport into eastern China,increasing the likelihood of excessive rainfall over the Yangtze River basin,whereas an anomalous cyclonic circulation tends to suppress moisture transport and alter rainfall distributions.Consequently,understanding and predicting summer WNPAC variability is of both scientific and societal importance.
A robust trans-seasonal linkage has long been recognized between the El Niño-Southern Oscillation (ENSO) in the winter and the WNPAC in the following summer.El Niño decay years are generally associated with an anomalous anticyclonic circulation over the western North Pacific,while La Niña decay years tend to be accompanied by an anomalous cyclonic circulation.This ENSO-WNPAC linkage constitutes a fundamental source of seasonal predictability for the East Asian summer climate.However,its strength exhibits pronounced decadal variability,and the key factors governing this nonstationary under internal climate variability remain insufficiently understood,partly due to the limited length of observational records.
To address this issue,this study investigates the internally driven modulation of the ENSO-WNPAC relationship using two independent large-ensemble simulations:FGOALS-LE and CESM-LE.These ensembles,conducted under identical external forcing but with different initial conditions,allow robust isolation of internal variability.By examining inter-member differences in the correlation between preceding-winter ENSO and summer WNPAC,we identify the dominant factors controlling variations in the trans-seasonal linkage and diagnose the associated physical mechanisms.Particular attention is paid to differences in ENSO evolution characteristics,especially the relative occurrence frequencies of distinct ENSO decay types,as well as the role of sea surface temperature (SST) anomaly structures.
Both large-ensemble datasets consistently show that variations in the relative frequencies of ENSO decay types are the primary determinant of the ENSO-WNPAC relationship strength.Ensemble members exhibiting a stronger ENSO-WNPAC correlation are characterized by a higher proportion of slowly decaying ENSO events and a lower proportion of persistent ENSO events,whereas members with a weaker correlation display the opposite pattern.In contrast,the frequency of rapidly decaying ENSO events does not differ significantly between strong- and weak-correlation members,indicating that this ENSO category plays a limited role in modulating the linkage.These results demonstrate that the statistical composition of ENSO decay pathways,rather than ENSO amplitude alone,is central to shaping the stability of the winter ENSO-summer WNPAC connection.
Further analyses suggest that differences in ENSO decay rate are closely linked to variations in the meridional scale of ENSO-related SST anomalies.Broader versus narrower meridional SST anomaly structures are associated with distinct ENSO decay behaviors,which influence the persistence of tropical ocean-atmosphere anomalies into the subsequent summer and modulate the circulation response over the western North Pacific.This mechanism provides a dynamical link between SST spatial structure,ENSO temporal evolution,and the strength of ENSO teleconnections.
These findings advance understanding of why the ENSO-WNPAC relationship varies under identical external forcing and underscore the critical role of internal variability in modulating ENSO event-type composition and teleconnection strength.The results further imply that skillful seasonal prediction of East Asian summer climate depends not only on ENSO occurrence but also on accurate representation of ENSO decay pathway and SST anomaly structures,with important implications for operational climate prediction systems.
The western North Pacific anomalous circulation (WNPAC),manifested as large-scale anticyclonic or cyclonic circulation anomalies over the western North Pacific during boreal summer,is a key component of the East Asian summer monsoon system.It exerts substantial influence on regional precipitation,flood-drought variability,and tropical cyclone activity in East Asia.In particular,an anomalous anticyclonic circulation enhances southwesterly moisture transport into eastern China,increasing the likelihood of excessive rainfall over the Yangtze River basin,whereas an anomalous cyclonic circulation tends to suppress moisture transport and alter rainfall distributions.Consequently,understanding and predicting summer WNPAC variability is of both scientific and societal importance.
A robust trans-seasonal linkage has long been recognized between the El Niño-Southern Oscillation (ENSO) in the winter and the WNPAC in the following summer.El Niño decay years are generally associated with an anomalous anticyclonic circulation over the western North Pacific,while La Niña decay years tend to be accompanied by an anomalous cyclonic circulation.This ENSO-WNPAC linkage constitutes a fundamental source of seasonal predictability for the East Asian summer climate.However,its strength exhibits pronounced decadal variability,and the key factors governing this nonstationary under internal climate variability remain insufficiently understood,partly due to the limited length of observational records.
To address this issue,this study investigates the internally driven modulation of the ENSO-WNPAC relationship using two independent large-ensemble simulations:FGOALS-LE and CESM-LE.These ensembles,conducted under identical external forcing but with different initial conditions,allow robust isolation of internal variability.By examining inter-member differences in the correlation between preceding-winter ENSO and summer WNPAC,we identify the dominant factors controlling variations in the trans-seasonal linkage and diagnose the associated physical mechanisms.Particular attention is paid to differences in ENSO evolution characteristics,especially the relative occurrence frequencies of distinct ENSO decay types,as well as the role of sea surface temperature (SST) anomaly structures.
Both large-ensemble datasets consistently show that variations in the relative frequencies of ENSO decay types are the primary determinant of the ENSO-WNPAC relationship strength.Ensemble members exhibiting a stronger ENSO-WNPAC correlation are characterized by a higher proportion of slowly decaying ENSO events and a lower proportion of persistent ENSO events,whereas members with a weaker correlation display the opposite pattern.In contrast,the frequency of rapidly decaying ENSO events does not differ significantly between strong- and weak-correlation members,indicating that this ENSO category plays a limited role in modulating the linkage.These results demonstrate that the statistical composition of ENSO decay pathways,rather than ENSO amplitude alone,is central to shaping the stability of the winter ENSO-summer WNPAC connection.
Further analyses suggest that differences in ENSO decay rate are closely linked to variations in the meridional scale of ENSO-related SST anomalies.Broader versus narrower meridional SST anomaly structures are associated with distinct ENSO decay behaviors,which influence the persistence of tropical ocean-atmosphere anomalies into the subsequent summer and modulate the circulation response over the western North Pacific.This mechanism provides a dynamical link between SST spatial structure,ENSO temporal evolution,and the strength of ENSO teleconnections.
These findings advance understanding of why the ENSO-WNPAC relationship varies under identical external forcing and underscore the critical role of internal variability in modulating ENSO event-type composition and teleconnection strength.The results further imply that skillful seasonal prediction of East Asian summer climate depends not only on ENSO occurrence but also on accurate representation of ENSO decay pathway and SST anomaly structures,with important implications for operational climate prediction systems.
2026,49(2): 272-284, DOI: 10.13878/j.cnki.dqkxxb.20250214001
Abstract:
During May and June 2024,India experienced a severe,widespread,and persistent heatwave event,with some regions enduring more than 50 consecutive days of extreme heat.The event resulted in at least 46 reported fatalities in May alone and is considered the longest heatwave recorded to date.Understanding the characteristics and driving mechanisms of this extreme event is therefore critical for improving early warning systems and enhancing societal resilience for future heat extremes.This study provides a comprehensive analysis of the spatiotemporal characteristics of the May-June 2024 heatwave over India and investigates its underlying meteorological drivers.Heatwaves are identified using the excess heat factor (EHF) index,and their features are quantified using four indices:heatwave number,frequency,duration,and amplitude.To diagnose the causal mechanisms,a multi-parameter approach is employed,examining large-scale and regional atmospheric fields,including 500 hPa geopotential height,850 hPa wind patterns,zonal- and meridional-mean vertical circulation,surface radiation components (downward and upward shortwave radiation),surface energy fluxes (sensible and latent heat),and near-surface variables such as 2 m air temperature and relative humidity.
The results reveal a strong coupling between large-scale atmospheric circulation anomalies and local land-atmosphere processes.First,the subtropical high-pressure ridge,identified by the 588 dagpm contour,established over southern India unusually early in early May and subsequently expanded northward through late May and June.This anomalous persistence induced sustained subsidence,clear-sky conditions,and enhanced solar heating,contributing to the exceptional duration of the heatwave.Second,anomalous circulation patterns played a critical role:dry continental air intrusions from Central Asia increased heat stress over northern India in early May,while the convergence of warm,moist air from the Bay of Bengal and the Arabian Sea produced oppressive humid heat conditions western and southern regions by mid-May.In June,topographic modulation of pre-monsoon flow along the southern flank of the Qinghai-Xizang Plateau further shaped the heatwave evolution.Third,surface energy balance analysis highlights key amplifying mechanisms.Over northern India,enhanced downward shortwave radiation combined with reduced upward shortwave radiation resulted in substantial net surface energy accumulation.Concurrently,suppressed latent heat flux and increased sensible heat flux limited evaporative cooling,directly elevating near-surface air temperatures.While low humidity in northern India intensified thermal aridity,higher humidity in southern regions amplified perceived heat stress despite slightly lower air temperatures.
Overall,the extreme and prolonged heatwave during May-June 2024 resulted from the compound effects of 1) an anomalously strong and persistent subtropical high,2) circulation-driven transport of dry continental air and altered moisture pathways,3) suppression of monsoon onset under unfavorable multi-level wind anomalies,and 4) land-atmosphere feedbacks associated with surface energy partitioning and soil moisture deficits.This study advances the understanding of heatwave dynamics in South Asia and underscores the need to integrate circulation anomalies,moisture transport,and surface processes in heatwave prediction and impact assessment frameworks.
During May and June 2024,India experienced a severe,widespread,and persistent heatwave event,with some regions enduring more than 50 consecutive days of extreme heat.The event resulted in at least 46 reported fatalities in May alone and is considered the longest heatwave recorded to date.Understanding the characteristics and driving mechanisms of this extreme event is therefore critical for improving early warning systems and enhancing societal resilience for future heat extremes.This study provides a comprehensive analysis of the spatiotemporal characteristics of the May-June 2024 heatwave over India and investigates its underlying meteorological drivers.Heatwaves are identified using the excess heat factor (EHF) index,and their features are quantified using four indices:heatwave number,frequency,duration,and amplitude.To diagnose the causal mechanisms,a multi-parameter approach is employed,examining large-scale and regional atmospheric fields,including 500 hPa geopotential height,850 hPa wind patterns,zonal- and meridional-mean vertical circulation,surface radiation components (downward and upward shortwave radiation),surface energy fluxes (sensible and latent heat),and near-surface variables such as 2 m air temperature and relative humidity.
The results reveal a strong coupling between large-scale atmospheric circulation anomalies and local land-atmosphere processes.First,the subtropical high-pressure ridge,identified by the 588 dagpm contour,established over southern India unusually early in early May and subsequently expanded northward through late May and June.This anomalous persistence induced sustained subsidence,clear-sky conditions,and enhanced solar heating,contributing to the exceptional duration of the heatwave.Second,anomalous circulation patterns played a critical role:dry continental air intrusions from Central Asia increased heat stress over northern India in early May,while the convergence of warm,moist air from the Bay of Bengal and the Arabian Sea produced oppressive humid heat conditions western and southern regions by mid-May.In June,topographic modulation of pre-monsoon flow along the southern flank of the Qinghai-Xizang Plateau further shaped the heatwave evolution.Third,surface energy balance analysis highlights key amplifying mechanisms.Over northern India,enhanced downward shortwave radiation combined with reduced upward shortwave radiation resulted in substantial net surface energy accumulation.Concurrently,suppressed latent heat flux and increased sensible heat flux limited evaporative cooling,directly elevating near-surface air temperatures.While low humidity in northern India intensified thermal aridity,higher humidity in southern regions amplified perceived heat stress despite slightly lower air temperatures.
Overall,the extreme and prolonged heatwave during May-June 2024 resulted from the compound effects of 1) an anomalously strong and persistent subtropical high,2) circulation-driven transport of dry continental air and altered moisture pathways,3) suppression of monsoon onset under unfavorable multi-level wind anomalies,and 4) land-atmosphere feedbacks associated with surface energy partitioning and soil moisture deficits.This study advances the understanding of heatwave dynamics in South Asia and underscores the need to integrate circulation anomalies,moisture transport,and surface processes in heatwave prediction and impact assessment frameworks.
2026,49(2): 285-296, DOI: 10.13878/j.cnki.dqkxxb.20241023002
Abstract:
Persistent heavy rainfall (PHR) during South China's pre-summer rainy season (April-June) is a major driver of severe flooding and related socioeconomic losses.While intraseasonal oscillations such as the Madden-Julian Oscillation (MJO) are known modulators,the influence and mechanisms of higher-frequency tropical quasi-biweekly oscillations (QBWOs;10—30-day periods) on the intensity and persistence of PHR events remain insufficiently understood.Improving the quantitative assessment of QBWOs over the South China Sea (SCS) and elucidating their coupled ocean-atmosphere processes is essential for enhancing subseasonal predictability.This study systematically investigates the physical mechanisms through which QBWOs over the tropical SCS modulate the occurrence and persistence of PHR in South China.Multiple high-resolution daily datasets covering a climatologically significant period are analyzed,including 1) precipitation observations from the China Meteorological Administration station network;2) atmospheric fields (winds,geopotential height,vertical velocity,and specific humidity) from the NCEP-DOE Reanalysis 2;and 3) sea surface temperature (SST) from the NOAA daily optimum interpolation SST (OISST) dataset.QBWO signals are isolated using a Lanczos bandpass filter (10—30 days),and composite and lead-lag analyses are employed to diagnose coupled variability.Results show that quasi-biweekly convective oscillations over the SCS influence PHR anomalies by modulating low-frequency water vapor transport and vertical motion over South China.On the quasi-biweekly timescale,a negative air-sea feedback emerges,linking SCS convection and SST.Low-frequency cold SST anomalies suppress convection,induce local anticyclonic anomalies and subsidence,and inhibit regional ascent.Subsequently,enhanced solar radiation,reduced upward sensible heat flux,warm-water accumulation driven by southerly winds leads to a transition from cold to warm SST anomalies.During this warming phase,thermally driven direct circulation strengthens,promoting ascent and cyclonic circulation over South China and enhancing water vapor transport,ultimately supporting the development of intense and persistent rainfall.When warm SST anomalies peak,convection over the SCS is re-energized,local cyclones form,and the vertical circulation undergoes a phase reversal,creating conditions less favorable for precipitation over South China.
These findings demonstrate that the QBWO over the SCS constitutes a fundamental mode of variability governing the persistence of heavy rainfall during South China's pre-summer rainy season.The identified QBWO-coupled mode and the characteristic SST transition from suppressed to enhanced convection provide valuable predictors for extended-range (10—30-day) forecasts.Monitoring the phase and amplitude of the SCS QBWO—particularly early signs of SST warming during the suppressed convection phase—may significantly improve early-warning lead times for PHR events.
Persistent heavy rainfall (PHR) during South China's pre-summer rainy season (April-June) is a major driver of severe flooding and related socioeconomic losses.While intraseasonal oscillations such as the Madden-Julian Oscillation (MJO) are known modulators,the influence and mechanisms of higher-frequency tropical quasi-biweekly oscillations (QBWOs;10—30-day periods) on the intensity and persistence of PHR events remain insufficiently understood.Improving the quantitative assessment of QBWOs over the South China Sea (SCS) and elucidating their coupled ocean-atmosphere processes is essential for enhancing subseasonal predictability.This study systematically investigates the physical mechanisms through which QBWOs over the tropical SCS modulate the occurrence and persistence of PHR in South China.Multiple high-resolution daily datasets covering a climatologically significant period are analyzed,including 1) precipitation observations from the China Meteorological Administration station network;2) atmospheric fields (winds,geopotential height,vertical velocity,and specific humidity) from the NCEP-DOE Reanalysis 2;and 3) sea surface temperature (SST) from the NOAA daily optimum interpolation SST (OISST) dataset.QBWO signals are isolated using a Lanczos bandpass filter (10—30 days),and composite and lead-lag analyses are employed to diagnose coupled variability.Results show that quasi-biweekly convective oscillations over the SCS influence PHR anomalies by modulating low-frequency water vapor transport and vertical motion over South China.On the quasi-biweekly timescale,a negative air-sea feedback emerges,linking SCS convection and SST.Low-frequency cold SST anomalies suppress convection,induce local anticyclonic anomalies and subsidence,and inhibit regional ascent.Subsequently,enhanced solar radiation,reduced upward sensible heat flux,warm-water accumulation driven by southerly winds leads to a transition from cold to warm SST anomalies.During this warming phase,thermally driven direct circulation strengthens,promoting ascent and cyclonic circulation over South China and enhancing water vapor transport,ultimately supporting the development of intense and persistent rainfall.When warm SST anomalies peak,convection over the SCS is re-energized,local cyclones form,and the vertical circulation undergoes a phase reversal,creating conditions less favorable for precipitation over South China.
These findings demonstrate that the QBWO over the SCS constitutes a fundamental mode of variability governing the persistence of heavy rainfall during South China's pre-summer rainy season.The identified QBWO-coupled mode and the characteristic SST transition from suppressed to enhanced convection provide valuable predictors for extended-range (10—30-day) forecasts.Monitoring the phase and amplitude of the SCS QBWO—particularly early signs of SST warming during the suppressed convection phase—may significantly improve early-warning lead times for PHR events.
2026,49(2): 297-310, DOI: 10.13878/j.cnki.dqkxxb.20250909001
Abstract:
Based on daily precipitation records from 177 national meteorological stations in the Huang-Huai region from 1961 to 2024, this study systematically examines the spatiotemporal evolution and interrelationships of precipitation amount, precipitation concentration degree (PCD), and precipitation concentration period (PCP) across 12 summer and autumn solar terms.The main findings are as follows: 1) From 1961 to 2024, the regional mean annual precipitation was 620.9 mm, exhibiting a weak upward trend (1.43 mm·(10 a)-1).The multiyear mean PCD was 0.41, indicating increasingly concentrated precipitation (0.004 (10 a)-1).The PCP mainly occurred during the Minor Heat solar term and showed a tendency toward earlier timing (-0.84°·(10 a)-1). From 1961 to 1992, precipitation, PCD, and PCP all decreased, whereas from 1993 to 2024, precipitation and PCD increased and PCP was delayed.This interdecadal shift may be linked to changes in intensity of the East Asian summer monsoon and adjustments in the location of the western Pacific subtropical high.2) Regional precipitation exhibited a unimodal intra-annual pattern, with 65.47% of the total precipitation occurring between the Summer Solstice and the End of Heat, peaking during Minor Heat (105.3 mm).Trends during individual solar terms differ markedly: the Summer Solstice experienced the strongest increase (4.24 mm·(10 a)-1), while Major Heat and Beginning of Autumn showed the most pronounced decreases (-1.98 mm·(10 a)-1 and -1.29 mm·(10 a)-1, respectively).3) Spatially, PCD increased from southwest to northeast.Low PCD values in the mountainous regions of western Henan likely reflect the influence of more uniformly distributed orographic precipitation, whereas high values over the Jiaodong Peninsula may be associated with its proximity to the subtropical high and strong land-sea thermal contrasts.In low-precipitation years, PCD values were relatively high (mean 0.45), indicating more concentrated precipitation, while high-precipitation years exhibited lower PCD (mean 0.39).During wet years, PCP advanced progressively from south to north, following the sequence Summer Solstice-Minor Heat-Major Heat, consistent with the northward seasonal progression of the subtropical high.4) On an annual scale, PCD exhibited a weak negative correlation with regional mean precipitation, although 95.48% of stations showed positive correlations, highlighting the contrast between local extreme events and regional averages.PCP showed a weak positive correlation with regional annual precipitation.At the solar-term scale, PCD increased significantly with precipitation during the main flood season (Minor Heat to Beginning of Autumn).Increased precipitation during autumn solar terms (End of Heat, White Dew, Autumn Equinox, Cold Dew) was significantly associated with delayed PCP, particularly during 1993—2024.
Based on daily precipitation records from 177 national meteorological stations in the Huang-Huai region from 1961 to 2024, this study systematically examines the spatiotemporal evolution and interrelationships of precipitation amount, precipitation concentration degree (PCD), and precipitation concentration period (PCP) across 12 summer and autumn solar terms.The main findings are as follows: 1) From 1961 to 2024, the regional mean annual precipitation was 620.9 mm, exhibiting a weak upward trend (1.43 mm·(10 a)-1).The multiyear mean PCD was 0.41, indicating increasingly concentrated precipitation (0.004 (10 a)-1).The PCP mainly occurred during the Minor Heat solar term and showed a tendency toward earlier timing (-0.84°·(10 a)-1). From 1961 to 1992, precipitation, PCD, and PCP all decreased, whereas from 1993 to 2024, precipitation and PCD increased and PCP was delayed.This interdecadal shift may be linked to changes in intensity of the East Asian summer monsoon and adjustments in the location of the western Pacific subtropical high.2) Regional precipitation exhibited a unimodal intra-annual pattern, with 65.47% of the total precipitation occurring between the Summer Solstice and the End of Heat, peaking during Minor Heat (105.3 mm).Trends during individual solar terms differ markedly: the Summer Solstice experienced the strongest increase (4.24 mm·(10 a)-1), while Major Heat and Beginning of Autumn showed the most pronounced decreases (-1.98 mm·(10 a)-1 and -1.29 mm·(10 a)-1, respectively).3) Spatially, PCD increased from southwest to northeast.Low PCD values in the mountainous regions of western Henan likely reflect the influence of more uniformly distributed orographic precipitation, whereas high values over the Jiaodong Peninsula may be associated with its proximity to the subtropical high and strong land-sea thermal contrasts.In low-precipitation years, PCD values were relatively high (mean 0.45), indicating more concentrated precipitation, while high-precipitation years exhibited lower PCD (mean 0.39).During wet years, PCP advanced progressively from south to north, following the sequence Summer Solstice-Minor Heat-Major Heat, consistent with the northward seasonal progression of the subtropical high.4) On an annual scale, PCD exhibited a weak negative correlation with regional mean precipitation, although 95.48% of stations showed positive correlations, highlighting the contrast between local extreme events and regional averages.PCP showed a weak positive correlation with regional annual precipitation.At the solar-term scale, PCD increased significantly with precipitation during the main flood season (Minor Heat to Beginning of Autumn).Increased precipitation during autumn solar terms (End of Heat, White Dew, Autumn Equinox, Cold Dew) was significantly associated with delayed PCP, particularly during 1993—2024.
REN Yeting, WANG Zhiyi, ZHANG Zhiwei, SHI Baolong, WANG Jingjie, WU Tianbei, LI Mengjun, WANG Jinyan
2026,49(2): 311-323, DOI: 10.13878/j.cnki.dqkxxb.20241226001
Abstract:
Large-scale development of wind power represents a key pathway for decarbonizing the power sector, contributing significantly to energy conservation, emission reduction, environmental improvement, and climate change mitigation.Accurate wind resource assessment is critical for ensuring the successful development and profitability of wind farms, providing the basis for estimating regional wind energy potential and identifying suitable sites.In recent years, reanalysis datasets have been widely used in wind energy assessments due to their high spatiotemporal resolution, broad geographical coverage, and long-term continuity, which help overcome the limitations of conventional observational networks.However, while previous studies have identified notable regional differences in the applicability of various reanalysis-based wind fields, comparative evaluations of the latest products remain limited.In particular, the performance of China's first-generation global atmospheric and land reanalysis (CRA-40), the Japan Meteorological Agency's third global atmospheric reanalysis (JRA-3Q), and ERA5 from the European Centre for Medium-Range Weather Forecasts in reproducing wind power density (WPD),a key indicator of wind energy potential,has not been sufficiently assessed.To address this gap, this study employs the gridded observational dataset CN05.1 from the National Climate Center of China and divides mainland China into eight subregions (Northwest, North, Northeast, East, Central, South, Southwest, and West China) to systematically evaluate the performance of CRA-40, JRA-3Q, and ERA5 in capturing the spatial and temporal characteristics of WPD.The results indicate that (1) CRA-40 most accurately reproduces the spatial distribution of WPD in the N, NEC, EC, SC and SW regions, with the PCCs exceeding 0.7; ERA5 performs best in CC, while JRA-3Q performs better in NWC and W.CRA-40 also better captures WPD spatial trend patterns.(2) Temporal variability of WPD is best reproduced by CRA-40 in the N, NEC, EC, CC, and SC regions, by ERA5 in SW, and JRA-3Q in NWC and W.With the exception of NWC, CRA-40 most effectively reproduces the annual WPD trend.(3) In terms of quantitative consistency, CRA-40 shows the strongest correlation with observations, followed by JRA-3Q, with CCs generally reaching 0.8 in NEC, EC, and CC.In NWC and W, CRA-40 outperforms the other products by 0.1—0.2.CRA-40 also exhibits smaller RMSE and BIAS.Overall, CRA-40 demonstrates clear advantages in regions where wind projects are concentrated (e.g., N, NEC, EC, CC, SC, and SW), whereas JRA-3Q is more suitable for NWC and W.These findings offer important guidance for wind resource assessment, site selection, and the application of reanalysis datasets in terrestrial China.They can support the further development of wind power, accelerate decarbonization of the power sector, and promote the transition to clean energy.Future research should explore integrating multiple reanalysis datasets or applying higher-resolution surface wind products to improve the accuracy of wind resource assessments.
Large-scale development of wind power represents a key pathway for decarbonizing the power sector, contributing significantly to energy conservation, emission reduction, environmental improvement, and climate change mitigation.Accurate wind resource assessment is critical for ensuring the successful development and profitability of wind farms, providing the basis for estimating regional wind energy potential and identifying suitable sites.In recent years, reanalysis datasets have been widely used in wind energy assessments due to their high spatiotemporal resolution, broad geographical coverage, and long-term continuity, which help overcome the limitations of conventional observational networks.However, while previous studies have identified notable regional differences in the applicability of various reanalysis-based wind fields, comparative evaluations of the latest products remain limited.In particular, the performance of China's first-generation global atmospheric and land reanalysis (CRA-40), the Japan Meteorological Agency's third global atmospheric reanalysis (JRA-3Q), and ERA5 from the European Centre for Medium-Range Weather Forecasts in reproducing wind power density (WPD),a key indicator of wind energy potential,has not been sufficiently assessed.To address this gap, this study employs the gridded observational dataset CN05.1 from the National Climate Center of China and divides mainland China into eight subregions (Northwest, North, Northeast, East, Central, South, Southwest, and West China) to systematically evaluate the performance of CRA-40, JRA-3Q, and ERA5 in capturing the spatial and temporal characteristics of WPD.The results indicate that (1) CRA-40 most accurately reproduces the spatial distribution of WPD in the N, NEC, EC, SC and SW regions, with the PCCs exceeding 0.7; ERA5 performs best in CC, while JRA-3Q performs better in NWC and W.CRA-40 also better captures WPD spatial trend patterns.(2) Temporal variability of WPD is best reproduced by CRA-40 in the N, NEC, EC, CC, and SC regions, by ERA5 in SW, and JRA-3Q in NWC and W.With the exception of NWC, CRA-40 most effectively reproduces the annual WPD trend.(3) In terms of quantitative consistency, CRA-40 shows the strongest correlation with observations, followed by JRA-3Q, with CCs generally reaching 0.8 in NEC, EC, and CC.In NWC and W, CRA-40 outperforms the other products by 0.1—0.2.CRA-40 also exhibits smaller RMSE and BIAS.Overall, CRA-40 demonstrates clear advantages in regions where wind projects are concentrated (e.g., N, NEC, EC, CC, SC, and SW), whereas JRA-3Q is more suitable for NWC and W.These findings offer important guidance for wind resource assessment, site selection, and the application of reanalysis datasets in terrestrial China.They can support the further development of wind power, accelerate decarbonization of the power sector, and promote the transition to clean energy.Future research should explore integrating multiple reanalysis datasets or applying higher-resolution surface wind products to improve the accuracy of wind resource assessments.
2026,49(2): 324-335, DOI: 10.13878/j.cnki.dqkxxb.20240910002
Abstract:
Assessing data quality is essential for the effective application of new atmospheric observation instruments and is critical for ensuring the accuracy and reliability of meteorological datasets.With the rapid development of China's ground-based remote-sensing vertical observation network, millimeter-wave cloud radar (MMCR) has been widely deployed in operational meteorology.Although the co-location of MMCR and radiosonde systems provide favorable conditions for data quality evaluation, comprehensive multi-stations using long-term datasets remain limited.
This study evaluates the quality of MMCR products from seven stations in Sichuan Province using MMCR measurements, L-band radiosonde profiles, and surface precipitation data collected from 2023 to 2024.Cloud layers retrieved from radiosonde profiles serve as the reference, with adjustments made to account for radiosonde horizontal drift and precipitation-induced signal attenuation.Overall, the MMCR demonstrates strong consistency with radiosonde observations in detecting cloud occurrence and vertical structure, with agreement rates exceeding 65% at all stations.In high-altitude plateau regions, the MMCR more effectively penetrates thin cloud layers, capturing finer vertical structures and yielding a notably higher frequency of multi-layer cloud detections compared with radiosonde retrievals.
Analysis of cloud-height retrievals indicates that MMCR-derived cloud-base heights (CBH) exhibit higher accuracy than cloud-top heights (CTH) at all stations.This discrepancy is attributed to attenuation of millimeter-wave signals by atmospheric water vapor, which weakens returns from higher altitudes.Consequently, cloud-height error characteristics differ between plateau and basin regions.For example, large CTH errors occur at low-altitude basin stations (Wenjiang, Yibin, Dachuan), whereas the smallest mean CTH error (-0.27 km) is found at the high-altitude Ganzi station.When evaluated in 1 km altitude basins, the MMCR performs best for CBH is between 1 and 3 km and CTH between 8 and 9 km, with reduced accuracy when CBH exceeds 6 km or CTH is below 2 km.Environmental influences were further examined by calculating vertically integrated temperature and relative humidity from radiosonde profiles up to the observed cloud heights and correlating these with cloud-height errors.Both temperature and humidity significantly affect MMCR retrieval accuracy.A strong negative correlation is found between temperature and cloud-height error, with warmer conditions corresponding to larger negative CBH and CTH biases.In addition, increasing relative humidity leads to increasingly negative CTH errors, especially when integrated relative humidity exceeds approximately 60%.Under such conditions, CTH errors in basin regions show a pronounced negative bias, suggesting that an RH (relative humidity) threshold near 60% may serve as a useful indicator of potential CTH underestimation.
In summary, this study incorporates atmospheric temperature and humidity profiles to assess the applicability and performance of MMCR across diverse environments and cloud conditions.Nonetheless, uncertainties associated with radiosonde-based cloud retrieval algorithms may influence the evaluation.Future work will integrate additional observation sources—such as satellite and lidar measurements—to further validate MMCR cloud retrievals and enhance data quality assessments.
Assessing data quality is essential for the effective application of new atmospheric observation instruments and is critical for ensuring the accuracy and reliability of meteorological datasets.With the rapid development of China's ground-based remote-sensing vertical observation network, millimeter-wave cloud radar (MMCR) has been widely deployed in operational meteorology.Although the co-location of MMCR and radiosonde systems provide favorable conditions for data quality evaluation, comprehensive multi-stations using long-term datasets remain limited.
This study evaluates the quality of MMCR products from seven stations in Sichuan Province using MMCR measurements, L-band radiosonde profiles, and surface precipitation data collected from 2023 to 2024.Cloud layers retrieved from radiosonde profiles serve as the reference, with adjustments made to account for radiosonde horizontal drift and precipitation-induced signal attenuation.Overall, the MMCR demonstrates strong consistency with radiosonde observations in detecting cloud occurrence and vertical structure, with agreement rates exceeding 65% at all stations.In high-altitude plateau regions, the MMCR more effectively penetrates thin cloud layers, capturing finer vertical structures and yielding a notably higher frequency of multi-layer cloud detections compared with radiosonde retrievals.
Analysis of cloud-height retrievals indicates that MMCR-derived cloud-base heights (CBH) exhibit higher accuracy than cloud-top heights (CTH) at all stations.This discrepancy is attributed to attenuation of millimeter-wave signals by atmospheric water vapor, which weakens returns from higher altitudes.Consequently, cloud-height error characteristics differ between plateau and basin regions.For example, large CTH errors occur at low-altitude basin stations (Wenjiang, Yibin, Dachuan), whereas the smallest mean CTH error (-0.27 km) is found at the high-altitude Ganzi station.When evaluated in 1 km altitude basins, the MMCR performs best for CBH is between 1 and 3 km and CTH between 8 and 9 km, with reduced accuracy when CBH exceeds 6 km or CTH is below 2 km.Environmental influences were further examined by calculating vertically integrated temperature and relative humidity from radiosonde profiles up to the observed cloud heights and correlating these with cloud-height errors.Both temperature and humidity significantly affect MMCR retrieval accuracy.A strong negative correlation is found between temperature and cloud-height error, with warmer conditions corresponding to larger negative CBH and CTH biases.In addition, increasing relative humidity leads to increasingly negative CTH errors, especially when integrated relative humidity exceeds approximately 60%.Under such conditions, CTH errors in basin regions show a pronounced negative bias, suggesting that an RH (relative humidity) threshold near 60% may serve as a useful indicator of potential CTH underestimation.
In summary, this study incorporates atmospheric temperature and humidity profiles to assess the applicability and performance of MMCR across diverse environments and cloud conditions.Nonetheless, uncertainties associated with radiosonde-based cloud retrieval algorithms may influence the evaluation.Future work will integrate additional observation sources—such as satellite and lidar measurements—to further validate MMCR cloud retrievals and enhance data quality assessments.
2026,49(2): 336-348, DOI: 10.13878/j.cnki.dqkxxb.20250530001
Abstract:
Doppler radar is the only operational observing system capable of providing frequent,high-resolution measurements of the three-dimensional structure of convective storms.The effective assimilation of radar observations into numerical weather prediction (NWP) models is therefore critical for improving explicit convective-scale forecasts.The China Meteorological Administration Beijing version (CMA-BJ v3.0) system,an operational hourly rapid cycling assimilation and forecasting system developed by the Institute of Urban Meteorology,currently assimilates national radar reflectivity mosaics.This study investigates the assimilation of national CINRAD/SA radar radial velocity observations within CMA-BJ v3.0,with the objective of operational implementation.
Quality control (QC) procedures were applied prior to assimilation,including the removal of radial velocity observations in clear-air regions.A one-month set of cycling assimilation experiments was conducted using the CMA-BJ v3.0 configuration,and quantitative verification was performed.In the RV_qc experiment,radial velocity observations after QC were assimilated;in the RV_ctrl experiment,radial velocity observations before QC were assimilated;and the GTS experiment,only conventional observations were assimilated.The RV_qc experiment produced higher TS scores for precipitation forecasts and lower RMSEs for wind forecasts than the other two experiments.In contrast,the RV_ctrl experiment yielded lower TS scores than the GTS experiment and exhibited the highest BIAS among the three experiments,highlighting the importance of strict quality control.Based on these results,only QC-processed radial velocity were used in subsequent experiments.
To further assess the added value of radial velocity assimilation,two additional experiments were conducted.In the RV+Mosaics experiment,radial velocity observations were assimilated together with radar reflectivity mosaics and conventional observations,while in the Mosaics experiment,only reflectivity mosaics and conventional observations were assimilated.Two representative convective cases were analyzed.The results demonstrate that radial velocity assimilation improves the intensity,spatial extent,and location of precipitation forecasts.The RV+Mosaics experiment better captures the low-level convergence structure associated with convection.Accordingly,TS scores for precipitation forecasts in RV+Mosaics are higher than those in Mosaics at nearly all rainfall thresholds,while BIAS scores remain comparable.At the 25 mm threshold,TS scores in RV+Mosaics increase by approximately 4% during both the 0—3 h and 3—6 h forecast periods.Wind forecast errors are also reduced.At 925 hPa,RMSEs of upper-level wind forecasts decrease by 5.6% at 6 h lead time and 4.6% at 9 h lead time.For 10 m wind speed,RMSE is reduced by 1.5% at 6 h forecast.
Overall,the results demonstrate that assimilation of national CINRAD/SA radar radial velocity observations has a positive impact on both precipitation and wind forecasts in the operational CMA-BJ v3.0 system.Because this study targets operational implementation,strict quality control procedures were applied.The assimilation of radial velocity observations in clear-air region within an operational framework warrants further investigation.
Doppler radar is the only operational observing system capable of providing frequent,high-resolution measurements of the three-dimensional structure of convective storms.The effective assimilation of radar observations into numerical weather prediction (NWP) models is therefore critical for improving explicit convective-scale forecasts.The China Meteorological Administration Beijing version (CMA-BJ v3.0) system,an operational hourly rapid cycling assimilation and forecasting system developed by the Institute of Urban Meteorology,currently assimilates national radar reflectivity mosaics.This study investigates the assimilation of national CINRAD/SA radar radial velocity observations within CMA-BJ v3.0,with the objective of operational implementation.
Quality control (QC) procedures were applied prior to assimilation,including the removal of radial velocity observations in clear-air regions.A one-month set of cycling assimilation experiments was conducted using the CMA-BJ v3.0 configuration,and quantitative verification was performed.In the RV_qc experiment,radial velocity observations after QC were assimilated;in the RV_ctrl experiment,radial velocity observations before QC were assimilated;and the GTS experiment,only conventional observations were assimilated.The RV_qc experiment produced higher TS scores for precipitation forecasts and lower RMSEs for wind forecasts than the other two experiments.In contrast,the RV_ctrl experiment yielded lower TS scores than the GTS experiment and exhibited the highest BIAS among the three experiments,highlighting the importance of strict quality control.Based on these results,only QC-processed radial velocity were used in subsequent experiments.
To further assess the added value of radial velocity assimilation,two additional experiments were conducted.In the RV+Mosaics experiment,radial velocity observations were assimilated together with radar reflectivity mosaics and conventional observations,while in the Mosaics experiment,only reflectivity mosaics and conventional observations were assimilated.Two representative convective cases were analyzed.The results demonstrate that radial velocity assimilation improves the intensity,spatial extent,and location of precipitation forecasts.The RV+Mosaics experiment better captures the low-level convergence structure associated with convection.Accordingly,TS scores for precipitation forecasts in RV+Mosaics are higher than those in Mosaics at nearly all rainfall thresholds,while BIAS scores remain comparable.At the 25 mm threshold,TS scores in RV+Mosaics increase by approximately 4% during both the 0—3 h and 3—6 h forecast periods.Wind forecast errors are also reduced.At 925 hPa,RMSEs of upper-level wind forecasts decrease by 5.6% at 6 h lead time and 4.6% at 9 h lead time.For 10 m wind speed,RMSE is reduced by 1.5% at 6 h forecast.
Overall,the results demonstrate that assimilation of national CINRAD/SA radar radial velocity observations has a positive impact on both precipitation and wind forecasts in the operational CMA-BJ v3.0 system.Because this study targets operational implementation,strict quality control procedures were applied.The assimilation of radial velocity observations in clear-air region within an operational framework warrants further investigation.
2026,49(2): 349-358, DOI: 10.13878/j.cnki.dqkxxb.20250114001
Abstract:
To address the limitations of global numerical models in forecasting the location and intensity of heavy precipitation in complex terrain regions,this study applies a terrain correction method originally developed for the southwest center WRF ADAS real-time modeling system (SWCWARMS,abbreviated as SWC) to the European Centre for Medium-Range Weather Forecasts (ECMWF) global numerical forecast model (hereafter referred to as the EC model).Through a series of sensitivity experiments—including topographic nullification and altitude resetting—this method adjusts the EC model's terrain data and three-hourly forecasted meteorological fields (wind,precipitation,and relative humidity) initialized at 08:00 BST each day.The procedure quantitatively estimates the increase or decrease in precipitation induced by topographic effects,thereby enhancing the EC model's precipitation forecasts in mountainous regions.To evaluate the effectiveness of this method,the corrected EC precipitation forecasts were applied to the topographic transition zone along the eastern slope of the Tibetan Plateau in Sichuan during the flood seasons (June-August) of 2021—2022.A total of 31 heavy precipitation events were analyzed through daily verification and statistical assessment.The results demonstrate that the threat score (TS) for various precipitation intensities improved substantially after terrain correction.Relative to the uncorrected EC model forecasts,TS scores for heavy rain,rainstorm,and torrential rain increased by 11％,126％,and 267％,respectively.Concurrently,forecast hit rates improved markedly—reaching 45.5％,20％,and 8％,for heavy rain,rainstorm,and torrential rain,respectively—while false negative rates decreased to 54.5％,80％,and 92％.In addition,false positive rates for heavy rain and torrential rain declined to 50.5％ and 84.5％,respectively.The bias scores also approached unity,indicating a significant reduction in systematic forecast bias.Overall,the results confirm that the proposed terrain correction method effectively enhances the accuracy and reliability of global numerical precipitation forecasts in regions of complex topography.This approach provides valuable technical support for improving operational weather forecasting over the plateau—basin transitional zones of Southwest China.
To address the limitations of global numerical models in forecasting the location and intensity of heavy precipitation in complex terrain regions,this study applies a terrain correction method originally developed for the southwest center WRF ADAS real-time modeling system (SWCWARMS,abbreviated as SWC) to the European Centre for Medium-Range Weather Forecasts (ECMWF) global numerical forecast model (hereafter referred to as the EC model).Through a series of sensitivity experiments—including topographic nullification and altitude resetting—this method adjusts the EC model's terrain data and three-hourly forecasted meteorological fields (wind,precipitation,and relative humidity) initialized at 08:00 BST each day.The procedure quantitatively estimates the increase or decrease in precipitation induced by topographic effects,thereby enhancing the EC model's precipitation forecasts in mountainous regions.To evaluate the effectiveness of this method,the corrected EC precipitation forecasts were applied to the topographic transition zone along the eastern slope of the Tibetan Plateau in Sichuan during the flood seasons (June-August) of 2021—2022.A total of 31 heavy precipitation events were analyzed through daily verification and statistical assessment.The results demonstrate that the threat score (TS) for various precipitation intensities improved substantially after terrain correction.Relative to the uncorrected EC model forecasts,TS scores for heavy rain,rainstorm,and torrential rain increased by 11％,126％,and 267％,respectively.Concurrently,forecast hit rates improved markedly—reaching 45.5％,20％,and 8％,for heavy rain,rainstorm,and torrential rain,respectively—while false negative rates decreased to 54.5％,80％,and 92％.In addition,false positive rates for heavy rain and torrential rain declined to 50.5％ and 84.5％,respectively.The bias scores also approached unity,indicating a significant reduction in systematic forecast bias.Overall,the results confirm that the proposed terrain correction method effectively enhances the accuracy and reliability of global numerical precipitation forecasts in regions of complex topography.This approach provides valuable technical support for improving operational weather forecasting over the plateau—basin transitional zones of Southwest China.
2026,49(2): 359-369, DOI: 10.13878/j.cnki.dqkxxb.20250102001
Abstract:
As a key component of the East Asian summer monsoon system, the Meiyu front is frequently associated with severe weather events, including heavy precipitation.Understanding its structural evolution and disturbance characteristics is crucial for improving precipitation forecasts during the Meiyu period.This study investigates a persistent heavy rainfall event that occurred from 27 June to 1 July 2020.Utilizing ERA5 reanalysis data, daily gridded precipitation observations from Chinese meteorological stations, and hourly merged precipitation products over China, we analyze the structural disturbances of the Meiyu front and their relationship with precipitation.Results show that during this prolonged rainfall event, the Meiyu rainband exhibited pronounced north-south oscillations, accompanied by corresponding changes in the frontal shear structure.The front evolved from a warm-shear-induced northward lifting to a rapid southward retreat driven by cold-shear frontogenesis, eventually developing into a quasi-stationary shear front.Precipitation mainly occurred in the warm sector south of the 850 hPa frontal zone, characterized by deep convective activity.Both the intensity and spatial extent of precipitation were strongly influenced by the frontal shear type, with the warm-shear regime producing broader and more intense rainfall.The low-level frontogenesis region served as a reliable precursor for precipitation in the subsequent hour, and different frontogenesis types exhibited distinct vertical structural features modulated by diabatic heating and deformation effects.
During the evolution of the frontal system, the deformation and diabatic heating terms were the dominant contributors to frontogenesis.Under the influence of diabatic heating, warm-shear frontogenesis displayed a slight southward tilt with height, whereas cold-shear frontogenesis, affected by both deformation and heating, tilted northward.In contrast, the quasi-stationary frontogenesis maintained a vertically coherent structure throughout the troposphere.The deformation term was primarily governed by stretching deformation, while diabatic heating was concentrated on the warm side of the frontal zone, coinciding with the main precipitation area.This heating generated a pronounced thermal contrast across the front, further enhancing frontogenesis and sustaining the heavy rainfall process.
As a key component of the East Asian summer monsoon system, the Meiyu front is frequently associated with severe weather events, including heavy precipitation.Understanding its structural evolution and disturbance characteristics is crucial for improving precipitation forecasts during the Meiyu period.This study investigates a persistent heavy rainfall event that occurred from 27 June to 1 July 2020.Utilizing ERA5 reanalysis data, daily gridded precipitation observations from Chinese meteorological stations, and hourly merged precipitation products over China, we analyze the structural disturbances of the Meiyu front and their relationship with precipitation.Results show that during this prolonged rainfall event, the Meiyu rainband exhibited pronounced north-south oscillations, accompanied by corresponding changes in the frontal shear structure.The front evolved from a warm-shear-induced northward lifting to a rapid southward retreat driven by cold-shear frontogenesis, eventually developing into a quasi-stationary shear front.Precipitation mainly occurred in the warm sector south of the 850 hPa frontal zone, characterized by deep convective activity.Both the intensity and spatial extent of precipitation were strongly influenced by the frontal shear type, with the warm-shear regime producing broader and more intense rainfall.The low-level frontogenesis region served as a reliable precursor for precipitation in the subsequent hour, and different frontogenesis types exhibited distinct vertical structural features modulated by diabatic heating and deformation effects.
During the evolution of the frontal system, the deformation and diabatic heating terms were the dominant contributors to frontogenesis.Under the influence of diabatic heating, warm-shear frontogenesis displayed a slight southward tilt with height, whereas cold-shear frontogenesis, affected by both deformation and heating, tilted northward.In contrast, the quasi-stationary frontogenesis maintained a vertically coherent structure throughout the troposphere.The deformation term was primarily governed by stretching deformation, while diabatic heating was concentrated on the warm side of the frontal zone, coinciding with the main precipitation area.This heating generated a pronounced thermal contrast across the front, further enhancing frontogenesis and sustaining the heavy rainfall process.
2026,49(2): 370-383, DOI: 10.13878/j.cnki.dqkxxb.20241212001
Abstract:
Meteorological satellites are essential tools for acquiring atmospheric information, offering wide spatial coverage, high observation frequency, and high data accuracy.They play a critical role in weather forecasting and climate research.In addition to integrated operational meteorological satellites, specialized meteorological satellites form an important component of the global observing system, designed to meet requirements for monitoring specific variables, regions, or temporal windows.To address operational needs, dedicated precipitation-measuring satellites such as TRMM, GPM-CO and FY-3G have been developed.These missions directly retrieve vertical profiles of raindrop size distribution within precipitation systems, enabling more accurate depiction of precipitation structure and evolution.Satellites equipped with active sensors for cloud profiling—including CloudSat, CALIPSO and EarthCARE—have significantly advanced understanding of cloud three-dimensional structure and microphysical properties.The wind-profiling satellite Aeolus has greatly improved knowledge of global atmospheric dynamics.For specialized temporal and regional observations, early-morning-orbit satellites (e.g., FY-3E) and highly elliptical orbit satellites (e.g., Arktika-M) have been introduced, providing unique measurements during local dawn and in high-latitude regions, respectively.To enhance temporal resolution for specific variables, constellations of small satellites—such as COSMIC and TROPICS—have been deployed as effective complements to integrated operational systems.
Specialized meteorological satellites offer high-precision, targeted observations and therefore have broad prospects for future development.Their data applications, however, are relatively complex, highlighting the need for advances in on-board data processing and dissemination to reduce barriers for various users.Furthermore, the relationship between specialized and integrated meteorological satellites must be carefully considered through coordinated payload and orbit design to maximize overall system benefits.The rapid growth of the commercial satellite sector is also transforming the industry model toward service-oriented operations, contributing to a more mature satellite ecosystem.
This paper summarizes the development of representative specialized meteorological satellites worldwide and discusses emerging trends and implications to support future meteorological satellite development.
Meteorological satellites are essential tools for acquiring atmospheric information, offering wide spatial coverage, high observation frequency, and high data accuracy.They play a critical role in weather forecasting and climate research.In addition to integrated operational meteorological satellites, specialized meteorological satellites form an important component of the global observing system, designed to meet requirements for monitoring specific variables, regions, or temporal windows.To address operational needs, dedicated precipitation-measuring satellites such as TRMM, GPM-CO and FY-3G have been developed.These missions directly retrieve vertical profiles of raindrop size distribution within precipitation systems, enabling more accurate depiction of precipitation structure and evolution.Satellites equipped with active sensors for cloud profiling—including CloudSat, CALIPSO and EarthCARE—have significantly advanced understanding of cloud three-dimensional structure and microphysical properties.The wind-profiling satellite Aeolus has greatly improved knowledge of global atmospheric dynamics.For specialized temporal and regional observations, early-morning-orbit satellites (e.g., FY-3E) and highly elliptical orbit satellites (e.g., Arktika-M) have been introduced, providing unique measurements during local dawn and in high-latitude regions, respectively.To enhance temporal resolution for specific variables, constellations of small satellites—such as COSMIC and TROPICS—have been deployed as effective complements to integrated operational systems.
Specialized meteorological satellites offer high-precision, targeted observations and therefore have broad prospects for future development.Their data applications, however, are relatively complex, highlighting the need for advances in on-board data processing and dissemination to reduce barriers for various users.Furthermore, the relationship between specialized and integrated meteorological satellites must be carefully considered through coordinated payload and orbit design to maximize overall system benefits.The rapid growth of the commercial satellite sector is also transforming the industry model toward service-oriented operations, contributing to a more mature satellite ecosystem.
This paper summarizes the development of representative specialized meteorological satellites worldwide and discusses emerging trends and implications to support future meteorological satellite development.
2026,49(2): 384-392, DOI: 10.13878/j.cnki.dqkxxb.20241202002
Abstract:
Nitrogen oxides(NOx), including nitrous oxide (N2O), nitric oxide (NO), and nitrogen dioxide (NO2), are major atmospheric pollutants with important implications for climate change, air quality, and human health.These gases also play critical roles in the soil nitrogen cycle and interact closely with environmental factors.Among these factors, light is known to influence soil nitrogen oxide emissions; however, the underlying mechanisms remain insufficiently understood.This study investigates the effects of light exposure on soil nitrogen oxide emissions, focusing on different light treatments, crop species, and soil conditions.A meta-analysis of 28 published studies comprising 170 experimental datasets was conducted to quantify the impacts of ultraviolet-B (UV-B) radiation, shading, and high light intensity on nitrogen oxide fluxes and cumulative emissions.The results show that light exposure significantly affects soil nitrogen oxide emissions.Daytime light exposure and high light intensity increased N2O and NO emission fluxes by 57.28％ and 116.19％, respectively.In contrast, the effect on NO2 fluxes was less pronounced, with an increase of only 21.25％.UV-B radiation and shading exhibited contrasting influences on N2O accumulation: UV-B reduced N2O emissions by 6.85％, while shading increased them by 77.23％.Crop species also responded differently to light treatments.UV-B radiation inhibited N2O emissions in soybean but enhanced emissions in rice and wheat.Shading markedly increased N2O emission, particularly in rice and wheat,where the largest increases were observed.Light treatments also affected soil physicochemical properties.UV-B radiation and shading reduced soil temperature, whereas daytime exposure and high light intensity increased it.UV-B radiation decreased soil respiration and ammonium nitrogen content while increasing nitrate nitrogen levels.Analysis of soil microbial communities showed that UV-B significantly increased the gene copy numbers of ammonifying and ammonia-oxidizing bacteria, whiles its effects on denitrifying bacteria varied across studies.Overall,this study highlights the complex and multifaceted influence of light on soil nitrogen cyclingand nitrogen oxide emissions.The findings improve our understanding of how light regimes shape soil biogeochemical processes and provide a scientific basis for predicting nitrogen oxide emissionsunder changing environmental conditions.
Nitrogen oxides(NOx), including nitrous oxide (N2O), nitric oxide (NO), and nitrogen dioxide (NO2), are major atmospheric pollutants with important implications for climate change, air quality, and human health.These gases also play critical roles in the soil nitrogen cycle and interact closely with environmental factors.Among these factors, light is known to influence soil nitrogen oxide emissions; however, the underlying mechanisms remain insufficiently understood.This study investigates the effects of light exposure on soil nitrogen oxide emissions, focusing on different light treatments, crop species, and soil conditions.A meta-analysis of 28 published studies comprising 170 experimental datasets was conducted to quantify the impacts of ultraviolet-B (UV-B) radiation, shading, and high light intensity on nitrogen oxide fluxes and cumulative emissions.The results show that light exposure significantly affects soil nitrogen oxide emissions.Daytime light exposure and high light intensity increased N2O and NO emission fluxes by 57.28％ and 116.19％, respectively.In contrast, the effect on NO2 fluxes was less pronounced, with an increase of only 21.25％.UV-B radiation and shading exhibited contrasting influences on N2O accumulation: UV-B reduced N2O emissions by 6.85％, while shading increased them by 77.23％.Crop species also responded differently to light treatments.UV-B radiation inhibited N2O emissions in soybean but enhanced emissions in rice and wheat.Shading markedly increased N2O emission, particularly in rice and wheat,where the largest increases were observed.Light treatments also affected soil physicochemical properties.UV-B radiation and shading reduced soil temperature, whereas daytime exposure and high light intensity increased it.UV-B radiation decreased soil respiration and ammonium nitrogen content while increasing nitrate nitrogen levels.Analysis of soil microbial communities showed that UV-B significantly increased the gene copy numbers of ammonifying and ammonia-oxidizing bacteria, whiles its effects on denitrifying bacteria varied across studies.Overall,this study highlights the complex and multifaceted influence of light on soil nitrogen cyclingand nitrogen oxide emissions.The findings improve our understanding of how light regimes shape soil biogeochemical processes and provide a scientific basis for predicting nitrogen oxide emissionsunder changing environmental conditions.
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在线获得:June 12, 2025, DOI: 10.13878/j.cnki.dqkxxb.20241218001
Abstract:
In this paper, a regression reconstruction method of photovoltaic power based on convolutional neural network and spatial weights of satellite cloud map is investigated. In order to more comprehensively and accurately reflect the effects of direct sunlight and solar scattering on PV power, this paper proposes a method of assigning weights to satellite cloud maps, and constructs a novel PV power regression reconstruction method accordingly. The model firstly processes the satellite cloud map to enhance the difference between cloud and background, and then the correlation coefficients between PV power at different azimuths and satellite cloud maps at different spatial locations are calculated using historical power and cloud map data. Finally, a convolutional neural network model is used to establish the mapping relationship between satellite cloud maps and PV power taking into account the spatial weights to realize the regression reconstruction of PV power. The experimental results show that the proposed model fully considers the effects of direct sunlight and solar scattering through the weighting process, and demonstrates good accuracy. This study provides a useful reference for the regression reconstruction of PV power based on satellite cloud maps.
In this paper, a regression reconstruction method of photovoltaic power based on convolutional neural network and spatial weights of satellite cloud map is investigated. In order to more comprehensively and accurately reflect the effects of direct sunlight and solar scattering on PV power, this paper proposes a method of assigning weights to satellite cloud maps, and constructs a novel PV power regression reconstruction method accordingly. The model firstly processes the satellite cloud map to enhance the difference between cloud and background, and then the correlation coefficients between PV power at different azimuths and satellite cloud maps at different spatial locations are calculated using historical power and cloud map data. Finally, a convolutional neural network model is used to establish the mapping relationship between satellite cloud maps and PV power taking into account the spatial weights to realize the regression reconstruction of PV power. The experimental results show that the proposed model fully considers the effects of direct sunlight and solar scattering through the weighting process, and demonstrates good accuracy. This study provides a useful reference for the regression reconstruction of PV power based on satellite cloud maps.
在线获得:May 21, 2024, DOI: 10.13878/j.cnki.dqkxxb.20231129002
Abstract:
Lakes played an important role in regulating local climate and air quality. The impact of urban lakes on urban local atmospheric boundary layer circulation and atmospheric pollutant transport mechanisms was an important issue in current urban air quality research. This study analyzed the diurnal variation characteristics of near-surface atmospheric pollutant concentrations at lakeside stations in urban Nanjing in summer, and compared them with observations from non-lakeside urban stations relatively far away from the lake. The results showed that for NO2, which was mainly emitted near the ground, the average concentration in lakeside stations was about 1.64±0.29 μg·m-3 higher than that in non-lakeside city stations during the day, and was about 0.51±1.39 μg·m-3 lower at night. O3, which was mainly generated and transported in the middle and high levels of the boundary layer, showed the opposite trend: that is, the average concentration of lakeside stations during the day was about 9.57±2.19 μg·m-3 lower than that of non-lakeside city stations, while it was about 1.24±4.68 μg·m-3 higher at night; No similar concentration differences were found in PM2.5. We further used a two-dimensional land surface process model to conduct numerical experiments on the sensitivity of lake land use to lake-urban land distribution and different emission scenarios. The simulation results showed that the difference in thermal properties between lake surfaces and land surfaces in urban areas affects low-altitude atmospheric circulation. and vertical thermal stability, and further affected the diffusion and transmission process of urban near-surface air pollution concentration. Affected by the existence of the lake, the thermal stability of the vertical atmosphere above the lake and lakeside area during the day was higher than that over the non-lakeside area, and the vertical diffusion of the lower atmosphere was weaker, resulting in higher concentrations of pollutants mainly emitted near the surface in the lakeside area. The concentration of pollutants mainly emitted and generated at mid- and high-altitudes was low, while the situation was opposite at night. The simulation results were consistent with the observed data trends and qualitatively consistent with the WRF-Chem simulation results.
Lakes played an important role in regulating local climate and air quality. The impact of urban lakes on urban local atmospheric boundary layer circulation and atmospheric pollutant transport mechanisms was an important issue in current urban air quality research. This study analyzed the diurnal variation characteristics of near-surface atmospheric pollutant concentrations at lakeside stations in urban Nanjing in summer, and compared them with observations from non-lakeside urban stations relatively far away from the lake. The results showed that for NO2, which was mainly emitted near the ground, the average concentration in lakeside stations was about 1.64±0.29 μg·m-3 higher than that in non-lakeside city stations during the day, and was about 0.51±1.39 μg·m-3 lower at night. O3, which was mainly generated and transported in the middle and high levels of the boundary layer, showed the opposite trend: that is, the average concentration of lakeside stations during the day was about 9.57±2.19 μg·m-3 lower than that of non-lakeside city stations, while it was about 1.24±4.68 μg·m-3 higher at night; No similar concentration differences were found in PM2.5. We further used a two-dimensional land surface process model to conduct numerical experiments on the sensitivity of lake land use to lake-urban land distribution and different emission scenarios. The simulation results showed that the difference in thermal properties between lake surfaces and land surfaces in urban areas affects low-altitude atmospheric circulation. and vertical thermal stability, and further affected the diffusion and transmission process of urban near-surface air pollution concentration. Affected by the existence of the lake, the thermal stability of the vertical atmosphere above the lake and lakeside area during the day was higher than that over the non-lakeside area, and the vertical diffusion of the lower atmosphere was weaker, resulting in higher concentrations of pollutants mainly emitted near the surface in the lakeside area. The concentration of pollutants mainly emitted and generated at mid- and high-altitudes was low, while the situation was opposite at night. The simulation results were consistent with the observed data trends and qualitatively consistent with the WRF-Chem simulation results.
在线获得:May 21, 2024, DOI: DOI: 10.13878/j.cnki.dqkxxb.20230518003
Abstract:
Based on the reanalysis data of ERA5 and the historical output data of MPI-ESM1-2-HR model in CMIP6, the relationship between the inter-hemispheric atmospheric mass oscillation (IHO) and East Asian winter monsoon (EAWM) and its effect on winter temperature in China are verified. The results of reanalysis and model indicate that there is a significant positive correlation between winter IHO and East Asian winter monsoon. The IHO is closely related to the EAWM through the redistribution of global atmospheric mass. When the IHO is positive phase, the atmospheric mass accumulates abnormally in the northern part of Eurasia, but loses abnormally in the middle and low latitudes, which makes the ocean-land pressure difference in East Asia increase significantly, and the EAWM intensification. At the same time, it also significant cooling the winter surface temperature in central China, and vice versa. Further analysis shows that the temperature in the tropical lower stratosphere can affect the atmospheric temperature in the Antarctic troposphere by regulating the meridional distribution of ozone content through the residual circulation, thus playing a major driving role in the interannual variation of IHO.
Based on the reanalysis data of ERA5 and the historical output data of MPI-ESM1-2-HR model in CMIP6, the relationship between the inter-hemispheric atmospheric mass oscillation (IHO) and East Asian winter monsoon (EAWM) and its effect on winter temperature in China are verified. The results of reanalysis and model indicate that there is a significant positive correlation between winter IHO and East Asian winter monsoon. The IHO is closely related to the EAWM through the redistribution of global atmospheric mass. When the IHO is positive phase, the atmospheric mass accumulates abnormally in the northern part of Eurasia, but loses abnormally in the middle and low latitudes, which makes the ocean-land pressure difference in East Asia increase significantly, and the EAWM intensification. At the same time, it also significant cooling the winter surface temperature in central China, and vice versa. Further analysis shows that the temperature in the tropical lower stratosphere can affect the atmospheric temperature in the Antarctic troposphere by regulating the meridional distribution of ozone content through the residual circulation, thus playing a major driving role in the interannual variation of IHO.
在线获得:March 06, 2024, DOI: 10.13878/j.cnki.dqkxxb.20240212001
Abstract:
In the field of artificial precipitation enhancement, aircraft observation is still the only effective ways to directly obtain the phase state of cloud particles. Because the liquid supercooled water content in the cloud is an important parameter to judge the microphysical structure characteristics of the cloud system, based on the layered vertical detection data of Par-ticle Measurement System (PMS) in the Sanjiangyuan National Nature Reserve, we analyzed the microphysical charac-teristics of a typical layered cloud system in this area in spring. The results show that: (1) the typical stratiform cloud system in spring cloud system is mainly composed of three layers, the uppermost Cs (cirrostratus) is ice-phase cloud, and the AS (altostratus) in upper layer (high-level cloud) and the lower layer are mixed clouds. Moreover, the high super-cooled water area is mainly distributed in the middle, upper and lower parts of the low-level As, where the cloud particle concentration and supercooled water content are the highest, with obvious regional characteristics. (2) The liquid cloud particles in the As layer are concentrated in the median diameter range of 3.5 ~ 27.5 μm, and the cloud particles larger than 30.5 μm are ice-phase. In the middle and upper part of the low As layer, there is an obvious growth phenomenon in the high supercooled water area, and there is obvious ice crystals effect in the middle and lower part. (3) In the low su-percooled water area, the average content ratio of supercooled water is 90.8±10.9%, and the middle to lower parts (95.6±5.6%) is significantly higher than the middle and upper parts (79.8±12.1%). The accurate understanding and judgment of the microphysical structure of the layered cloud system in Sanjiangyuan will provide a reliable observation basis for the catalysis of artificial precipitation enhancement in this area.
In the field of artificial precipitation enhancement, aircraft observation is still the only effective ways to directly obtain the phase state of cloud particles. Because the liquid supercooled water content in the cloud is an important parameter to judge the microphysical structure characteristics of the cloud system, based on the layered vertical detection data of Par-ticle Measurement System (PMS) in the Sanjiangyuan National Nature Reserve, we analyzed the microphysical charac-teristics of a typical layered cloud system in this area in spring. The results show that: (1) the typical stratiform cloud system in spring cloud system is mainly composed of three layers, the uppermost Cs (cirrostratus) is ice-phase cloud, and the AS (altostratus) in upper layer (high-level cloud) and the lower layer are mixed clouds. Moreover, the high super-cooled water area is mainly distributed in the middle, upper and lower parts of the low-level As, where the cloud particle concentration and supercooled water content are the highest, with obvious regional characteristics. (2) The liquid cloud particles in the As layer are concentrated in the median diameter range of 3.5 ~ 27.5 μm, and the cloud particles larger than 30.5 μm are ice-phase. In the middle and upper part of the low As layer, there is an obvious growth phenomenon in the high supercooled water area, and there is obvious ice crystals effect in the middle and lower part. (3) In the low su-percooled water area, the average content ratio of supercooled water is 90.8±10.9%, and the middle to lower parts (95.6±5.6%) is significantly higher than the middle and upper parts (79.8±12.1%). The accurate understanding and judgment of the microphysical structure of the layered cloud system in Sanjiangyuan will provide a reliable observation basis for the catalysis of artificial precipitation enhancement in this area.
Zhou Xiaotian, Zhang Qianru, Guo Qingyan, Chen Yiling, Zhou Xuesong, Li Changjun, Feng Yong, Zhang Ping
在线获得:November 17, 2023, DOI: 10.13878/j.cnki.dqkxxb.20221130001
Abstract:
As the most basic physical quantity for studying on climate evolution, the integrity and accuracy of daily temperature series are of great significance for climate analysis and assessment. In recent years, with the deployment of a large number of unmanned ground intensified automatic weather stations, missing data with double random characteristics such as random distribution of stations and random lengths of series, which poses significant obstacles to climate analysis and operational applications. In view of the shortcomings of the existing methods for meteorological data interpolation, a new twice interpolation method of daily temperature data based on dynamic time warping (DTW) is proposed in this paper. The method adopts a real-time interpolation strategy, which mainly includes: (1) The method decomposes the temperature observation time series into a fitted straight line and a residual curved line by using univariate linear regression equation, and recomposes new temperature series by combining the two lines; (2) The method provides the definition and interpolation conditions of temperature interpolation areas; (3)The method proposes a new model for calculating the distance between stations by DTW . The collecting temperature data from Shandong Province in 2021 is used to test the method, and the test results show that the method can meet the interpolation needs of daily temperature data with double random characteristics, and the combination method of DTW distance and twice interpolation in the interpolation process can achieve a better effect than any of the other combination based on site geographical proximity relationships; the method is sensitive to terrain, and the interpolation effect in plain or hilly area is better than that in mountainous area.
As the most basic physical quantity for studying on climate evolution, the integrity and accuracy of daily temperature series are of great significance for climate analysis and assessment. In recent years, with the deployment of a large number of unmanned ground intensified automatic weather stations, missing data with double random characteristics such as random distribution of stations and random lengths of series, which poses significant obstacles to climate analysis and operational applications. In view of the shortcomings of the existing methods for meteorological data interpolation, a new twice interpolation method of daily temperature data based on dynamic time warping (DTW) is proposed in this paper. The method adopts a real-time interpolation strategy, which mainly includes: (1) The method decomposes the temperature observation time series into a fitted straight line and a residual curved line by using univariate linear regression equation, and recomposes new temperature series by combining the two lines; (2) The method provides the definition and interpolation conditions of temperature interpolation areas; (3)The method proposes a new model for calculating the distance between stations by DTW . The collecting temperature data from Shandong Province in 2021 is used to test the method, and the test results show that the method can meet the interpolation needs of daily temperature data with double random characteristics, and the combination method of DTW distance and twice interpolation in the interpolation process can achieve a better effect than any of the other combination based on site geographical proximity relationships; the method is sensitive to terrain, and the interpolation effect in plain or hilly area is better than that in mountainous area.
在线获得:November 01, 2023, DOI: 10.13878/j.cnki.dqkxxb.20231016001
Abstract:
Based on the hourly maximum wind speed data of Shanghai automatic stations and real-time gale disaster data provided by Shanghai Emergency Response Coordination Center from 2008 to 2019,?characteristics of spatiotemporal distributions and correlations between urban gales and disasters are analyzed in order to explore the impacts of strong winds in Shanghai. The results are as follows: (1) The gales and disasters present significant seasonal variations with force 8 gale days, maximum wind speeds, and disasters all exhibiting a summer single peak pattern. Summer gale days account for 41% of the year, and gale disasters account for over 80% of the year. The inter-annual fluctuations of disasters are significant, mainly influenced by extreme weathers. (2)The gales and disasters show significant differences between urban and suburban areas: Ⅰ) Wind speeds in downtown areas are much lower due to the impact of urbanization. Ⅱ) The density of disaster cases ranks the highest in central city (up to 37 cases/km2) and relatively high in regional centers and sub-centers. It is also found that the number of disasters in each region is positively correlated with its population and GDP. III) The housing related damages are relatively prominent in downtown and its surrounding regions, but the least significant in Chongming District. (3) The disastrous gale weather in Shanghai can be divided into four categories: Jiang-huai cyclone gales, thunderstorm gales, tropical cyclone gales and cold air gales, with thunderstorm gales the most frequent and tropical cyclone gales the most severe. (4) Trees and vehicles are the most common disaster-bearing bodies of strong wind disasters in Shanghai, followed by power lines and rain shelters. Gales cause disasters with obvious chain reactions. The study on the characteristics and impacts of urban gales are of great significance for the gale risk warning development and disaster prevention and mitigation.
Based on the hourly maximum wind speed data of Shanghai automatic stations and real-time gale disaster data provided by Shanghai Emergency Response Coordination Center from 2008 to 2019,?characteristics of spatiotemporal distributions and correlations between urban gales and disasters are analyzed in order to explore the impacts of strong winds in Shanghai. The results are as follows: (1) The gales and disasters present significant seasonal variations with force 8 gale days, maximum wind speeds, and disasters all exhibiting a summer single peak pattern. Summer gale days account for 41% of the year, and gale disasters account for over 80% of the year. The inter-annual fluctuations of disasters are significant, mainly influenced by extreme weathers. (2)The gales and disasters show significant differences between urban and suburban areas: Ⅰ) Wind speeds in downtown areas are much lower due to the impact of urbanization. Ⅱ) The density of disaster cases ranks the highest in central city (up to 37 cases/km2) and relatively high in regional centers and sub-centers. It is also found that the number of disasters in each region is positively correlated with its population and GDP. III) The housing related damages are relatively prominent in downtown and its surrounding regions, but the least significant in Chongming District. (3) The disastrous gale weather in Shanghai can be divided into four categories: Jiang-huai cyclone gales, thunderstorm gales, tropical cyclone gales and cold air gales, with thunderstorm gales the most frequent and tropical cyclone gales the most severe. (4) Trees and vehicles are the most common disaster-bearing bodies of strong wind disasters in Shanghai, followed by power lines and rain shelters. Gales cause disasters with obvious chain reactions. The study on the characteristics and impacts of urban gales are of great significance for the gale risk warning development and disaster prevention and mitigation.
在线获得:May 08, 2023, DOI: 10.13878/j.cnki.dqkxxb.20230501007
Abstract:
From March to April in 2023, 9 dust weather processes occurred in China.The processes from 19 to 24 March and from 9 to 13 April reached the level of strong sandstorm and sandstorm respectively, bringing adverse impacts on population health, ecological envi-ronment and transportation.The anomalous Eurasian atmospheric circulations showed a zonal distribution from the late winter to early spring, the Siberian high and the East Asian trough were weak, and the area around Mongolia was controlled by the high pressure anom-aly, which resulted in the continuous warm surface air temperature and soil temperature in the dust source area (the second highest since 1980).In addition, the lower troposphere also lacked water vapor transporting to the sand source, resulting in significantly less precipita-tion in the winter and spring of 2023 (the lowest in history since 1980).The continuous warm and dry climate conditions in winter and spring resulted in a large number of dry and loose gravel in the dust source area from February to March in 2023, which provided ex-tremely favorable dust source conditions for the occurrence of sandstorms.The synoptic disturbance systems that triggered the sandstorms in March 19—24 and April 9—13 were both Mongolian cyclones.However, the two Mongolian cyclones and their configuration with the rear cold high were different, which directly caused the differences in the intensity, path and duration of the two sandstorms.From 19 to 24 March, the dust process reached the level of strong sandstorm, causing PM10 concentrations in Beijing and Harbin to exceed 2000 and 3600 μg·m?3 respectively.The sandstorm from 9 to 13 April not only affected Northeast and North China, but also caused a significant increase in PM10 concentration in cities south of the Yangtze River, such as Hangzhou and Fuzhou.Moreover, the research emphases of dust events from the aspects of climate cumulative effect and synoptic disturbance mechanism are analyzed, and the necessity and key points of conducting subseasonal-seasonal and interdecadal prediction of dust events are discussed.Furthermore, severe sandstorms in 2021 and 2023 also raise the scientific question, "Have dust events entered a new period of activity?".To answer this question, it is neces-sary to study the interdecadal mechanism and prediction of dust change, and also to predict the future change of dust event trend to a cer-tain extent.
From March to April in 2023, 9 dust weather processes occurred in China.The processes from 19 to 24 March and from 9 to 13 April reached the level of strong sandstorm and sandstorm respectively, bringing adverse impacts on population health, ecological envi-ronment and transportation.The anomalous Eurasian atmospheric circulations showed a zonal distribution from the late winter to early spring, the Siberian high and the East Asian trough were weak, and the area around Mongolia was controlled by the high pressure anom-aly, which resulted in the continuous warm surface air temperature and soil temperature in the dust source area (the second highest since 1980).In addition, the lower troposphere also lacked water vapor transporting to the sand source, resulting in significantly less precipita-tion in the winter and spring of 2023 (the lowest in history since 1980).The continuous warm and dry climate conditions in winter and spring resulted in a large number of dry and loose gravel in the dust source area from February to March in 2023, which provided ex-tremely favorable dust source conditions for the occurrence of sandstorms.The synoptic disturbance systems that triggered the sandstorms in March 19—24 and April 9—13 were both Mongolian cyclones.However, the two Mongolian cyclones and their configuration with the rear cold high were different, which directly caused the differences in the intensity, path and duration of the two sandstorms.From 19 to 24 March, the dust process reached the level of strong sandstorm, causing PM10 concentrations in Beijing and Harbin to exceed 2000 and 3600 μg·m?3 respectively.The sandstorm from 9 to 13 April not only affected Northeast and North China, but also caused a significant increase in PM10 concentration in cities south of the Yangtze River, such as Hangzhou and Fuzhou.Moreover, the research emphases of dust events from the aspects of climate cumulative effect and synoptic disturbance mechanism are analyzed, and the necessity and key points of conducting subseasonal-seasonal and interdecadal prediction of dust events are discussed.Furthermore, severe sandstorms in 2021 and 2023 also raise the scientific question, "Have dust events entered a new period of activity?".To answer this question, it is neces-sary to study the interdecadal mechanism and prediction of dust change, and also to predict the future change of dust event trend to a cer-tain extent.
在线获得:April 06, 2023, DOI: 10.13878/j.cnki.dqkxxb.20220805002
Abstract:
Southeast Asia has a complex topography and a large population. The response of extreme precipitation events to global warming is sensitive and its future evolutionary characteristics are widely valued. In this study, 26 global climate models (GCMs) are used to present projected change in precipitation extremes over Southeast Asia at the end of 21st century based on the Coupled Model Intercomparison Project phase 6 (CMIP6) simulations. The thermodynamic and dynamic contributions to future changes in precipitation are analyzed by decomposition of moisture budget equation. The multi-model ensemble medians show that, compared with the historical reference period (1985—2014), the frequency and intensity of climatological precipitation and precipitation extremes in most of Southeast Asia are obviously increased at the end of 21st century (2070—2099) under SSP2-4.5 and SSP5-8.5 scenarios. The variation of precipitation extremes shows significant spatial differences under the global warming. Precipitation extremes with short duration and high intensity will occur in the Kalimantan. In southern Sumatra, the total precipitation of wet days (PRCPTOT) tends to decrease significantly and the occurrence of consecutive dry days (CDD) become more frequent. Except for heavy precipitation days (R10mm), the change of extreme precipitation indices with more pronounced magnitudes under SSP5-8.5 scenario than SSP2-4.5 scenario. The contribution rate of heavy precipitation (R95pTOT) increased by 22% (41%) under SSP2-4.5 (SSP5-8.5) scenario. Quantitative analysis of moisture budget equation shows that, thermodynamic and dynamic effects mainly result in the precipitation climatological changes at the end of 21st century. Compared with the large-scale circulation changes, the thermodynamic component with higher inter-model consistency is the main contribution term. Under SSP2-4.5 (SSP5-8.5) scenario, the contribution of thermodynamic effects accounts for 65% (64%) of the P-E (precipitation minus evaporation) changes. However, the dynamic effects show a counteracting trend to the changes of P-E, which contributes 35% (36%). Moisture convergence caused by atmospheric specific humidity changes is considered as the dominating factor of projected precipitation increase.
Southeast Asia has a complex topography and a large population. The response of extreme precipitation events to global warming is sensitive and its future evolutionary characteristics are widely valued. In this study, 26 global climate models (GCMs) are used to present projected change in precipitation extremes over Southeast Asia at the end of 21st century based on the Coupled Model Intercomparison Project phase 6 (CMIP6) simulations. The thermodynamic and dynamic contributions to future changes in precipitation are analyzed by decomposition of moisture budget equation. The multi-model ensemble medians show that, compared with the historical reference period (1985—2014), the frequency and intensity of climatological precipitation and precipitation extremes in most of Southeast Asia are obviously increased at the end of 21st century (2070—2099) under SSP2-4.5 and SSP5-8.5 scenarios. The variation of precipitation extremes shows significant spatial differences under the global warming. Precipitation extremes with short duration and high intensity will occur in the Kalimantan. In southern Sumatra, the total precipitation of wet days (PRCPTOT) tends to decrease significantly and the occurrence of consecutive dry days (CDD) become more frequent. Except for heavy precipitation days (R10mm), the change of extreme precipitation indices with more pronounced magnitudes under SSP5-8.5 scenario than SSP2-4.5 scenario. The contribution rate of heavy precipitation (R95pTOT) increased by 22% (41%) under SSP2-4.5 (SSP5-8.5) scenario. Quantitative analysis of moisture budget equation shows that, thermodynamic and dynamic effects mainly result in the precipitation climatological changes at the end of 21st century. Compared with the large-scale circulation changes, the thermodynamic component with higher inter-model consistency is the main contribution term. Under SSP2-4.5 (SSP5-8.5) scenario, the contribution of thermodynamic effects accounts for 65% (64%) of the P-E (precipitation minus evaporation) changes. However, the dynamic effects show a counteracting trend to the changes of P-E, which contributes 35% (36%). Moisture convergence caused by atmospheric specific humidity changes is considered as the dominating factor of projected precipitation increase.
在线获得:April 06, 2023, DOI: 10.13878/j.cnki.dqkxxb.20220715001
Abstract:
Based on the dataset of precipitation phenomenon instrument in Zhengzhou, the dual polarization radars, the conventional observation and the China’s First Generation Global Atmosphere and Land Reanalysis data, the microphysical characteristics of “7·20” extremely heavy rainfall in Zhengzhou were analyzed. The extremely heavy rainfall was affected by multiscale weather systems, providing favorable environmental conditions for the formation of complex microphysical characteristics. The results showed that the raindrop size distributions changed significantly with time, and values of the raindrop size distribution parameters were widely distributed, covering the distribution area from continental convective precipitation to maritime convective precipitation. The number density of small drops was much higher than that of common convective precipitation in East Asia and the average value in South China in summer, and a large number of large drops also existed, leading to the higher precipitation efficiency during the strongest precipitation period from 16:00 to 17:00 on the 20th July. The low-centroid structure of convective storm was observed by dual polarization radar, showing the typical characteristics of warm cloud. The intense warm-rain processes below the 0℃ layer played an important role in the formation of the extremely heavy rainfall because of the melting of lots of ice particles and high efficiency for the growth of raindrops.
Based on the dataset of precipitation phenomenon instrument in Zhengzhou, the dual polarization radars, the conventional observation and the China’s First Generation Global Atmosphere and Land Reanalysis data, the microphysical characteristics of “7·20” extremely heavy rainfall in Zhengzhou were analyzed. The extremely heavy rainfall was affected by multiscale weather systems, providing favorable environmental conditions for the formation of complex microphysical characteristics. The results showed that the raindrop size distributions changed significantly with time, and values of the raindrop size distribution parameters were widely distributed, covering the distribution area from continental convective precipitation to maritime convective precipitation. The number density of small drops was much higher than that of common convective precipitation in East Asia and the average value in South China in summer, and a large number of large drops also existed, leading to the higher precipitation efficiency during the strongest precipitation period from 16:00 to 17:00 on the 20th July. The low-centroid structure of convective storm was observed by dual polarization radar, showing the typical characteristics of warm cloud. The intense warm-rain processes below the 0℃ layer played an important role in the formation of the extremely heavy rainfall because of the melting of lots of ice particles and high efficiency for the growth of raindrops.
在线获得:April 06, 2023, DOI: 10.13878/j.cnki.dqkxxb.20220715002
Abstract:
In order to understand the causes of summer precipitation anomalies in North China and improve climate monitoring and prediction technology, based on the summer precipitation data in North China and NCEP/NCAR (National Centers for Environmental Prediction/National Center for Atmospheric Research) reanalysis data from 1961 to 2021, using the methods of correlation, synthesis and circulation anomaly reconstruction, the circulation background of summer (June -August) precipitation anomaly in North China and the relationship between East Asian subtropical summer monsoon, North China dynamic rise index and summer precipitation in North China are analyzed. The results show that: (1) the circulation conditions of abnormal precipitation in North China in summer are that the high ridge of Ural Mountain at 500hPa in summer is stronger, the Baikal Lake trough is deeper, the subtropical high in the Northwest Pacific is north by west near the Korean Peninsula, and North China is in the circulation situation of "high in the East and low in the west", so the dynamic rising conditions are favorable. At the same time, the 850hPa Indian monsoon is stronger, the East Asian subtropical summer monsoon is significantly stronger, and the water vapor source in North China is sufficient. (2) The East Asian subtropical summer monsoon index and North China dynamic rise index defined in this paper have a good indication of summer precipitation anomalies in North China. When the two indexes are stronger, the summer precipitation in North China is abnormally more. If both indexes are weak, the summer precipitation in North China is abnormally less. If the two indexes are inconsistent, the summer precipitation in North China is basically normal. (3) The abnormally more or less summer rainfall in North China is the result of the synergy of the East Asian subtropical summer monsoon and the dynamic upward movement in North China. The subtropical summer monsoon in East Asia is stronger (the dynamic upward movement in North China is stronger), the Baikal trough in the 500hPa layer is deepened, the subtropical high in the Northwest Pacific is north by west, and North China is under the control of the circulation of "high in the East and low in the West", so the dynamic upward conditions are favorable. At the same time, the Indian summer monsoon at 850hPa and the subtropical summer monsoon in East Asia are relatively strong, which will strengthen the water vapor transmission of the west wind in the tropical Indian Ocean and the south wind in the subtropical region of East Asia, and the water vapor source in North China is sufficient. The above situation will cause abnormally more summer precipitation in North China. On the contrary, the summer precipitation in North China will be abnormally less. (4) From April to May in the early stage, the Baikal trough in the 500hPa layer deepened, the subtropical high in the Northwest Pacific was northerly, and the southerly wind in East Asia in the 850hPa layer was significantly stronger, which can be used as a climate monitoring and prediction index for the abnormally more summer precipitation in North China.
In order to understand the causes of summer precipitation anomalies in North China and improve climate monitoring and prediction technology, based on the summer precipitation data in North China and NCEP/NCAR (National Centers for Environmental Prediction/National Center for Atmospheric Research) reanalysis data from 1961 to 2021, using the methods of correlation, synthesis and circulation anomaly reconstruction, the circulation background of summer (June -August) precipitation anomaly in North China and the relationship between East Asian subtropical summer monsoon, North China dynamic rise index and summer precipitation in North China are analyzed. The results show that: (1) the circulation conditions of abnormal precipitation in North China in summer are that the high ridge of Ural Mountain at 500hPa in summer is stronger, the Baikal Lake trough is deeper, the subtropical high in the Northwest Pacific is north by west near the Korean Peninsula, and North China is in the circulation situation of "high in the East and low in the west", so the dynamic rising conditions are favorable. At the same time, the 850hPa Indian monsoon is stronger, the East Asian subtropical summer monsoon is significantly stronger, and the water vapor source in North China is sufficient. (2) The East Asian subtropical summer monsoon index and North China dynamic rise index defined in this paper have a good indication of summer precipitation anomalies in North China. When the two indexes are stronger, the summer precipitation in North China is abnormally more. If both indexes are weak, the summer precipitation in North China is abnormally less. If the two indexes are inconsistent, the summer precipitation in North China is basically normal. (3) The abnormally more or less summer rainfall in North China is the result of the synergy of the East Asian subtropical summer monsoon and the dynamic upward movement in North China. The subtropical summer monsoon in East Asia is stronger (the dynamic upward movement in North China is stronger), the Baikal trough in the 500hPa layer is deepened, the subtropical high in the Northwest Pacific is north by west, and North China is under the control of the circulation of "high in the East and low in the West", so the dynamic upward conditions are favorable. At the same time, the Indian summer monsoon at 850hPa and the subtropical summer monsoon in East Asia are relatively strong, which will strengthen the water vapor transmission of the west wind in the tropical Indian Ocean and the south wind in the subtropical region of East Asia, and the water vapor source in North China is sufficient. The above situation will cause abnormally more summer precipitation in North China. On the contrary, the summer precipitation in North China will be abnormally less. (4) From April to May in the early stage, the Baikal trough in the 500hPa layer deepened, the subtropical high in the Northwest Pacific was northerly, and the southerly wind in East Asia in the 850hPa layer was significantly stronger, which can be used as a climate monitoring and prediction index for the abnormally more summer precipitation in North China.
在线获得:April 06, 2023, DOI: 10.13878/j.cnki.dqkxxb.20221212001
Abstract:
During the Dragon-boat precipitation period in 2022 (from May 21 to June 21), the average precipitation in South China is 472.5 mm, which is the second largest in the same period in history, it is the third largest in Guangdong，Guangxi is the largest in the same period since there are meteorological records history in 1951. Under its influence, River basin flood occurs in the Pearl River basin, and catastrophic floods occurs in the Beijiang River basin. Using the daily precipitation data of 192 national meteorological observation stations in South China, NCEP/NCAR atmospheric circulation，atmospheric outward long wave radiation(OLR) data and NOAA monthly scale SST reanalysis data, the characteristics of South China Dragon-boat precipitation anomaly in 2022 and its relationship with atmospheric circulation and sea surface temperature are studied by using correlation and composite analysis methods. The results show that the East Asia Trough and the Northeast Cold Vortex are significantly strengthened, the cold air affecting South China is strong. The Western Pacific Subtropical High and the South Branch Trough are both relatively strong, and there is significant water vapor convergence in South China during the Dragon-boat precipitation period in 2022. The atmospheric response to the La Nina event is obvious in 2022, and the Walker circulation is enhanced. The convection in South China strengthened obviously. An abnormal anticyclone circulation was in the east of the Philippines. The Western Pacific Subtropical High becomes stronger, the southwest wind on its northwest side is stronger. Water vapor transmission to South China has increased significantly, Water vapor transmission to South China increased significantly. the significant enhancement of water vapor transport to South China. A significant upward movement at the same time in South China. The abnormality of atmospheric circulation and SST lead to the extreme Dragon-boat precipitation in South China in 2022.
During the Dragon-boat precipitation period in 2022 (from May 21 to June 21), the average precipitation in South China is 472.5 mm, which is the second largest in the same period in history, it is the third largest in Guangdong，Guangxi is the largest in the same period since there are meteorological records history in 1951. Under its influence, River basin flood occurs in the Pearl River basin, and catastrophic floods occurs in the Beijiang River basin. Using the daily precipitation data of 192 national meteorological observation stations in South China, NCEP/NCAR atmospheric circulation，atmospheric outward long wave radiation(OLR) data and NOAA monthly scale SST reanalysis data, the characteristics of South China Dragon-boat precipitation anomaly in 2022 and its relationship with atmospheric circulation and sea surface temperature are studied by using correlation and composite analysis methods. The results show that the East Asia Trough and the Northeast Cold Vortex are significantly strengthened, the cold air affecting South China is strong. The Western Pacific Subtropical High and the South Branch Trough are both relatively strong, and there is significant water vapor convergence in South China during the Dragon-boat precipitation period in 2022. The atmospheric response to the La Nina event is obvious in 2022, and the Walker circulation is enhanced. The convection in South China strengthened obviously. An abnormal anticyclone circulation was in the east of the Philippines. The Western Pacific Subtropical High becomes stronger, the southwest wind on its northwest side is stronger. Water vapor transmission to South China has increased significantly, Water vapor transmission to South China increased significantly. the significant enhancement of water vapor transport to South China. A significant upward movement at the same time in South China. The abnormality of atmospheric circulation and SST lead to the extreme Dragon-boat precipitation in South China in 2022.
在线获得:March 22, 2023, DOI: 10.13878/j.cnki.dqkxxb.20221025001
Abstract:
Based on the observational and reanalysis data during 1979—2020, this study investigated the basic features of the month-to-month reversal of air temperature anomalies in Northeast Asia in early summer (May to June) on the interannual timescales, as well as the effects of soil moisture anomalies in eastern Europe and the possible physical processes. The results show that the predominant mode of the intermonthly variation of air temperature anomalies in Northeast Asia in early summer is the reversal mode, that is warmer (colder) in May and colder (warmer) in June; and its formation is directly derived from the reversal of circulation anomalies over Northeast Asia. Further analysis indicates that the lower soil moisture in eastern Europe in May tends to lead to a warmer May and colder June in Northeast Asia. With the possible physical processes as following: lower soil moisture in May leads to local soil temperature and lower troposphere warming, which in turn causes a weakening (enhancement) of the lower tropospheric meridional temperature gradient and baroclinicity in the Mediterranean region (northern Europe). Correspondingly, high-frequency transient wave activity weakens (enhances) and facilitates the formation of an anomalous high over central and eastern Europe and hence Rossby wave source via transient vorticity forcing. The associated Rossby wave travels eastward along the polar front jet, resulting in a barotropic anomalous high over Northeast Asia and resultant surface warming. The soil moisture anomalies can persist until June but weaken in intensity. Similarly, it favors the formation of an anomalous high and Rossby wave source, but their center shifts westward to western Europe. The related Rossby wave activity leads to a barotropic anomalous low and hence cooling over Northeast Asia. There are obvious differences in the activity characteristics of Rossby waves (wave source, activity centers, and propagation pathway) associated with the soil moisture anomalies in eastern Europe in May and June, which are closely related to the difference in atmospheric climatology over northern Eurasia. When the soil moisture in eastern Europe is high in May, the above physical processes are roughly reversed.
Based on the observational and reanalysis data during 1979—2020, this study investigated the basic features of the month-to-month reversal of air temperature anomalies in Northeast Asia in early summer (May to June) on the interannual timescales, as well as the effects of soil moisture anomalies in eastern Europe and the possible physical processes. The results show that the predominant mode of the intermonthly variation of air temperature anomalies in Northeast Asia in early summer is the reversal mode, that is warmer (colder) in May and colder (warmer) in June; and its formation is directly derived from the reversal of circulation anomalies over Northeast Asia. Further analysis indicates that the lower soil moisture in eastern Europe in May tends to lead to a warmer May and colder June in Northeast Asia. With the possible physical processes as following: lower soil moisture in May leads to local soil temperature and lower troposphere warming, which in turn causes a weakening (enhancement) of the lower tropospheric meridional temperature gradient and baroclinicity in the Mediterranean region (northern Europe). Correspondingly, high-frequency transient wave activity weakens (enhances) and facilitates the formation of an anomalous high over central and eastern Europe and hence Rossby wave source via transient vorticity forcing. The associated Rossby wave travels eastward along the polar front jet, resulting in a barotropic anomalous high over Northeast Asia and resultant surface warming. The soil moisture anomalies can persist until June but weaken in intensity. Similarly, it favors the formation of an anomalous high and Rossby wave source, but their center shifts westward to western Europe. The related Rossby wave activity leads to a barotropic anomalous low and hence cooling over Northeast Asia. There are obvious differences in the activity characteristics of Rossby waves (wave source, activity centers, and propagation pathway) associated with the soil moisture anomalies in eastern Europe in May and June, which are closely related to the difference in atmospheric climatology over northern Eurasia. When the soil moisture in eastern Europe is high in May, the above physical processes are roughly reversed.
在线获得:February 17, 2023, DOI: 10.13878/j.cnki.dqkxxb.20220324001
Abstract:
Based on the daily observations collected by National Meteorological Information Centre since 1919, the homogenized daily maximum and minimum temperature series during the period of 1912-2019 were established for Baoding in Hebei Province. Firstly, the error data due to manual observation or recording, instrument malfunctions and digital inputs were removed by quality control. Then, the missing observations were interpolated by standardized series method using the homogenized daily temperature data in Tianjin over century-long scale. Lastly, several significant breakpoints caused by changes in interpolation, station relocation and instrument manufacturers were detected by penalized maximal t test (PMT) with annual and monthly reference series constructed by two means, and adjusted by Quantile Matching (QM) adjustment with daily reference series from Berkeley Earth-daily data. It was found that the characteristics of inter-annual, decadal and trend changes were consistent with those fromBerkeley Earth-monthly、CRUTS4.03 and GHCNV3. And the characteristics of warming change induced by the rapid urban development in Baoding region have well been reflected, simultaneously compared with the whole Beijing-Tianjin-Hebei region. In addition, the warming change of annual and seasonal temperature extremes in Baoding have also increased significantly since 1912, the warming trends of annual and autumn lowest minimum temperature (TNn) were 0.340℃/10a and 0.404℃/10a (95% significance level), respectively, and the corresponding diurnal temperature range (DTR) are -0.118℃/10a and -0.215℃/10a (95% significance level).
Based on the daily observations collected by National Meteorological Information Centre since 1919, the homogenized daily maximum and minimum temperature series during the period of 1912-2019 were established for Baoding in Hebei Province. Firstly, the error data due to manual observation or recording, instrument malfunctions and digital inputs were removed by quality control. Then, the missing observations were interpolated by standardized series method using the homogenized daily temperature data in Tianjin over century-long scale. Lastly, several significant breakpoints caused by changes in interpolation, station relocation and instrument manufacturers were detected by penalized maximal t test (PMT) with annual and monthly reference series constructed by two means, and adjusted by Quantile Matching (QM) adjustment with daily reference series from Berkeley Earth-daily data. It was found that the characteristics of inter-annual, decadal and trend changes were consistent with those fromBerkeley Earth-monthly、CRUTS4.03 and GHCNV3. And the characteristics of warming change induced by the rapid urban development in Baoding region have well been reflected, simultaneously compared with the whole Beijing-Tianjin-Hebei region. In addition, the warming change of annual and seasonal temperature extremes in Baoding have also increased significantly since 1912, the warming trends of annual and autumn lowest minimum temperature (TNn) were 0.340℃/10a and 0.404℃/10a (95% significance level), respectively, and the corresponding diurnal temperature range (DTR) are -0.118℃/10a and -0.215℃/10a (95% significance level).
在线获得:December 06, 2022, DOI: 10.13878/j.cnki.dqkxxb. 20210324001
Abstract:
A Rapid Refresh Hybrid system was constructed based on the Weather Research and Forecasting(WRF) Model,WRF Hybrid Data Assimilation system and Ensemble Transform Kalman Filter(ETKF),with assimilating both Wind Profile Radar Detection(WPRD) data and Microwave Radiometer(MWR) data.Experiments were performed for the study of the impact of 4 important parameters on the system,which are 2 tuning factors of static background error, localization scale and ensemble weighting factor,and contrast research was carried on to the results of Hybrid and 3DVAR schemes.Some encouraged conclusions were given as follows:Tuning these 4 parameters could improve performance of the Rapid Refresh Hybrid system.The analysis and forecast of Hybrid with pa-rameters not tuned were better than those of 3DVAR, and the results of Hybrid with parameters tuned were the best.
A Rapid Refresh Hybrid system was constructed based on the Weather Research and Forecasting(WRF) Model,WRF Hybrid Data Assimilation system and Ensemble Transform Kalman Filter(ETKF),with assimilating both Wind Profile Radar Detection(WPRD) data and Microwave Radiometer(MWR) data.Experiments were performed for the study of the impact of 4 important parameters on the system,which are 2 tuning factors of static background error, localization scale and ensemble weighting factor,and contrast research was carried on to the results of Hybrid and 3DVAR schemes.Some encouraged conclusions were given as follows:Tuning these 4 parameters could improve performance of the Rapid Refresh Hybrid system.The analysis and forecast of Hybrid with pa-rameters not tuned were better than those of 3DVAR, and the results of Hybrid with parameters tuned were the best.
在线获得:December 06, 2022, DOI: 10.13878/j.cnki.dqkxxb. 20220306001
Abstract:
Based on the Global Ensemble Prediction System in China Meteorological Administration (CMA-GEPS), the extreme Meiyu process over China in 2020 was evaluated. Results show that, during the Meiyu season, a strong and stable western Pacific subtropical high (WPSH) and a gradually strengthened East Asian summer monsoon provide favorable dynamic and moisture conditions for strong rainfall. For the western Pacific subtropical high, CMA-GEPS could skillfully forecast the evolution trend of WPSH index with 7-9 leading days; the CMA-GEPS prediction skills of WPSH strength and area are about the same level as the results from the NCEP ensemble prediction system, and the WPSH strength presents the weaker bias compared with the observation; the prediction skills of ridge line and western boundary index with CMA-GEPS are comparable with the results from ECMWF ensemble prediction system, and the forecasting bias is mainly attributed to the more southward location of ridge line and more eastward center position of western boundary. For the East Asian summer monsoon, CMA-GEPS could skillfully predict the index with 9 leading days, which was two days earlier than the control forecast. The CMA-GEPS control forecasting bias is mainly attributed to the weaker precipitation intensity and more southward location of strong rainfall belt, and also the control forecasting fails to predict the heavy rain in some regions in the middle and lower reaches of Yangtze river. With the time-spatial weight probability (TSWP) neighborhood scheme, the prediction skills related to the heavy rain with CMA-GEPS are improved obviously, and the scheme reduced the occurrence of precipitation missing report. The results of precipitation probability prediction were verified by observation and Brier Scores, which show that: the TSWP neighborhood scheme is superior to the original single point ensemble probability forecast method and the control forecast, and also has a well application values for the heavy storm prediction in the Meiyu period.
Based on the Global Ensemble Prediction System in China Meteorological Administration (CMA-GEPS), the extreme Meiyu process over China in 2020 was evaluated. Results show that, during the Meiyu season, a strong and stable western Pacific subtropical high (WPSH) and a gradually strengthened East Asian summer monsoon provide favorable dynamic and moisture conditions for strong rainfall. For the western Pacific subtropical high, CMA-GEPS could skillfully forecast the evolution trend of WPSH index with 7-9 leading days; the CMA-GEPS prediction skills of WPSH strength and area are about the same level as the results from the NCEP ensemble prediction system, and the WPSH strength presents the weaker bias compared with the observation; the prediction skills of ridge line and western boundary index with CMA-GEPS are comparable with the results from ECMWF ensemble prediction system, and the forecasting bias is mainly attributed to the more southward location of ridge line and more eastward center position of western boundary. For the East Asian summer monsoon, CMA-GEPS could skillfully predict the index with 9 leading days, which was two days earlier than the control forecast. The CMA-GEPS control forecasting bias is mainly attributed to the weaker precipitation intensity and more southward location of strong rainfall belt, and also the control forecasting fails to predict the heavy rain in some regions in the middle and lower reaches of Yangtze river. With the time-spatial weight probability (TSWP) neighborhood scheme, the prediction skills related to the heavy rain with CMA-GEPS are improved obviously, and the scheme reduced the occurrence of precipitation missing report. The results of precipitation probability prediction were verified by observation and Brier Scores, which show that: the TSWP neighborhood scheme is superior to the original single point ensemble probability forecast method and the control forecast, and also has a well application values for the heavy storm prediction in the Meiyu period.
在线获得:September 15, 2022, DOI: :10.13878/j.cnki.dqkxxb. 20211121001
Abstract:
At present, a Regional Ensemble Prediction System has been developed by Kelamayi Meteorological Bureau. The system has only adopted initial condition perturbation of Ensemble Transform Kalman Filter(ETKF), and the system is lack of spread. In order to improve the skill of this Ensemble Prediction System, the model perturbation method of Stochastic Physics Parameterization Tendency(SPPT) is adopted and tested. This paper conducted sensitivity test on critical parameter of SPPT and parameter setting of SPPT is determined. Ensemble forecast experiment test is conducted and compared for both ETKF scheme and ETKF-SPPT scheme. The results show that the ETKF method can generate initial condition perturbation with dynamic structure, but the spread will saturated within short forecast lead time and will decrease due to the constraint of identical LBC for all members. With SPPT model perturbation method adopted, the ensemble spread can significantly improved. Ensemble verification scores indicate that the reliability of ETKF without model perturbation is small, and the root mean square error(RMSE) is relatively large, while add model perturbation to initial condition perturbation will improve the probabilistic forecast skill with larger forecast reliability and smaller(RMSE) . The results of gale forecast show that the adoption of model perturbation method can significantly improve the ensemble forecast that it has more accurate forecast on the magnitude and time period of local gale.
At present, a Regional Ensemble Prediction System has been developed by Kelamayi Meteorological Bureau. The system has only adopted initial condition perturbation of Ensemble Transform Kalman Filter(ETKF), and the system is lack of spread. In order to improve the skill of this Ensemble Prediction System, the model perturbation method of Stochastic Physics Parameterization Tendency(SPPT) is adopted and tested. This paper conducted sensitivity test on critical parameter of SPPT and parameter setting of SPPT is determined. Ensemble forecast experiment test is conducted and compared for both ETKF scheme and ETKF-SPPT scheme. The results show that the ETKF method can generate initial condition perturbation with dynamic structure, but the spread will saturated within short forecast lead time and will decrease due to the constraint of identical LBC for all members. With SPPT model perturbation method adopted, the ensemble spread can significantly improved. Ensemble verification scores indicate that the reliability of ETKF without model perturbation is small, and the root mean square error(RMSE) is relatively large, while add model perturbation to initial condition perturbation will improve the probabilistic forecast skill with larger forecast reliability and smaller(RMSE) . The results of gale forecast show that the adoption of model perturbation method can significantly improve the ensemble forecast that it has more accurate forecast on the magnitude and time period of local gale.
在线获得:September 07, 2022, DOI: :10.13878/j.cnki.dqkxxb. 20211228001
Abstract:
As an important part of the cryosphere, snow cover has an important impact on atmospheric circulation and the hydrologic cycle. 98% of the seasonal snow in the world is located in the northern hemisphere. Eurasia continent is the main snow area in the Northern Hemisphere. China has a vast territory with nearly 50 degrees latitude across from north to south, and snow is widely distributed, which is important for studying spatial and temporal dynamics of snow cover. This paper proposes a trend extraction method based on empirical mode decomposition (EMD) based on the Snow Cover (SNC) data of FY-3 meteorological satellite and discusses the temporal and spatial characteristics and variation trends of Snow Cover in China during the past decade (2010-2019). The results show that: 1) China"s Snow Cover Frequency (SCF) has significant seasonal characteristics, which increases first and then decreases, and reaches the maximum SCF in February and March each year. The inter-annual SCF in northeast China has a significant trend of decline, but there is little change in other regions. 2) Snow Cover Rate (SCR) in Inner Mongolia and Xinjiang has decreased by 1.6% and 1.5% in the last decade, respectively. SCR in other areas has not changed significantly. SCR in main snow covered areas changed from increase to decrease in 2016.This study is of great significance to understand the spatial and temporal dynamics of typical snow cover areas in China and to further explore the relationship between snow cover and air temperature, precipitation, and other influential factors. At the same time, relevant results are obtained from the data of the Wind Cloud Meteorological Satellite, and the application of the observation data of the FY-3 satellite is strengthened.
As an important part of the cryosphere, snow cover has an important impact on atmospheric circulation and the hydrologic cycle. 98% of the seasonal snow in the world is located in the northern hemisphere. Eurasia continent is the main snow area in the Northern Hemisphere. China has a vast territory with nearly 50 degrees latitude across from north to south, and snow is widely distributed, which is important for studying spatial and temporal dynamics of snow cover. This paper proposes a trend extraction method based on empirical mode decomposition (EMD) based on the Snow Cover (SNC) data of FY-3 meteorological satellite and discusses the temporal and spatial characteristics and variation trends of Snow Cover in China during the past decade (2010-2019). The results show that: 1) China"s Snow Cover Frequency (SCF) has significant seasonal characteristics, which increases first and then decreases, and reaches the maximum SCF in February and March each year. The inter-annual SCF in northeast China has a significant trend of decline, but there is little change in other regions. 2) Snow Cover Rate (SCR) in Inner Mongolia and Xinjiang has decreased by 1.6% and 1.5% in the last decade, respectively. SCR in other areas has not changed significantly. SCR in main snow covered areas changed from increase to decrease in 2016.This study is of great significance to understand the spatial and temporal dynamics of typical snow cover areas in China and to further explore the relationship between snow cover and air temperature, precipitation, and other influential factors. At the same time, relevant results are obtained from the data of the Wind Cloud Meteorological Satellite, and the application of the observation data of the FY-3 satellite is strengthened.
在线获得:September 01, 2022, DOI: :10.13878/j.cnki.dqkxxb. 20220623001
Abstract:
The observational stability, observational ability, and rationality of both base data and products of millimeter cloud radar (MCR for short) installed at Shanghai Meteorological Service during “The study and experiment of vertical integrated meteorological observation technology in mega-cities” (MCME for short) have been evaluated using observations from ground-based Lidar distrometer, micro-rain radar, radiosonde, FY-4A’s products as well as surface rain gage. The results show that: the observational stability of MCR is considerably high that only one-time software failure happened during the MCME and the data acquisition rate is larger than 95%. The minimal detectable reflectivity of MCR is generally distributed within -40 to -20 dBZ and has an exponential distribution in the vertical direction which fits well with the theory. The minimal detectable reflectivity of MCR changes little (smaller than 2 dB for heights lower than 9 km) during the MCME. A false “No Cloud” region will be seen in the MCR’s observation when the rain rate is larger than 4-5 mm/h. Although the raw data of the two MCRs have certain differences, the pattern of reflectivity in the time-height cross-section is highly reasonable indicated by the comparisons between the reflectivity from MCR’s observation, the reflectivity calculated with Lidar distrometer’s observation, and the reflectivity from micro-rain radar’s observation. The cloud top height and cloud base height retrieved by MCR are also evaluated by the cloud top/base height calculated by radiosonde and cloud top height retrieved by FY-4A satellite, and the results show certainly a degree of consistency among the three observations. The inconsistency of reflectivity due to the merge of multiple pulses with different pulse widths used in MCR’s base data processing and the false “clear sky area” due to the strong attenuation are two obvious issues that may have significant impacts on the operational usage of MCR. The advice on how to improve the current MCR from the perspective of the demand for the development of the Shanghai Meteorological Service has been given at the end of the paper.
The observational stability, observational ability, and rationality of both base data and products of millimeter cloud radar (MCR for short) installed at Shanghai Meteorological Service during “The study and experiment of vertical integrated meteorological observation technology in mega-cities” (MCME for short) have been evaluated using observations from ground-based Lidar distrometer, micro-rain radar, radiosonde, FY-4A’s products as well as surface rain gage. The results show that: the observational stability of MCR is considerably high that only one-time software failure happened during the MCME and the data acquisition rate is larger than 95%. The minimal detectable reflectivity of MCR is generally distributed within -40 to -20 dBZ and has an exponential distribution in the vertical direction which fits well with the theory. The minimal detectable reflectivity of MCR changes little (smaller than 2 dB for heights lower than 9 km) during the MCME. A false “No Cloud” region will be seen in the MCR’s observation when the rain rate is larger than 4-5 mm/h. Although the raw data of the two MCRs have certain differences, the pattern of reflectivity in the time-height cross-section is highly reasonable indicated by the comparisons between the reflectivity from MCR’s observation, the reflectivity calculated with Lidar distrometer’s observation, and the reflectivity from micro-rain radar’s observation. The cloud top height and cloud base height retrieved by MCR are also evaluated by the cloud top/base height calculated by radiosonde and cloud top height retrieved by FY-4A satellite, and the results show certainly a degree of consistency among the three observations. The inconsistency of reflectivity due to the merge of multiple pulses with different pulse widths used in MCR’s base data processing and the false “clear sky area” due to the strong attenuation are two obvious issues that may have significant impacts on the operational usage of MCR. The advice on how to improve the current MCR from the perspective of the demand for the development of the Shanghai Meteorological Service has been given at the end of the paper.
在线获得:July 07, 2022, DOI: :10.13878/j.cnki.dqkxxb. 20220503001
Abstract:
Based on the satellite derived snow depth over the Tibetan Plateau (TP), daily rainfall data of 261 meteorological stations in South China (SC) and the ERA5 reanalysis dataset during 1979-2018, relationships between the TP winter snow depth and precipitation during the first rainy season (FRS) in SC have been investigated. Results show that: (1) Connections between snow depth over the western TP and precipitation during the FRS in SC are the most robust and the TP snow depth mainly affects frontal precipitation of the FSR, whereas it shows less impact on summer monsoonal rainfall. (2) Onset date of the FRS in above normal TP snow years is about 20 days earlier than that in below normal snow years, leading to more rainy days, longer of the FRS and more rainfall during the FRS. However, rainfall intensity during the FRS shows small difference between different types of the TP snow years. (3) The TP is colder in above normal snow year and the cooling effect stimulates an abnormal anticyclonic circulation over the TP. However, tripole anomaly patterns of 500 hPa geopotential height occur at East Asian coastal region. Configurations of the circulation facilitate cold air in middle-high latitude regions invade SC, which makes a colder SC. And the enhanced northwest Pacific subtropical high intensifies the low-level southerly flow and water vapor supplement. The front swings northward-southward in northern part of the SC during March-April. The FRS has been established once the dry cold northerly and the warm-wet southerly flow invade the SC in early April. In below normal TP snow years, both the cold northerly and warm southerly flow are weak and inactivity and the front in northern part of the SC is interrupted in early April. When the northerly and southerly flow invades the SC in mid-to-late April, the front is reverted and the FRS occurs later.
Based on the satellite derived snow depth over the Tibetan Plateau (TP), daily rainfall data of 261 meteorological stations in South China (SC) and the ERA5 reanalysis dataset during 1979-2018, relationships between the TP winter snow depth and precipitation during the first rainy season (FRS) in SC have been investigated. Results show that: (1) Connections between snow depth over the western TP and precipitation during the FRS in SC are the most robust and the TP snow depth mainly affects frontal precipitation of the FSR, whereas it shows less impact on summer monsoonal rainfall. (2) Onset date of the FRS in above normal TP snow years is about 20 days earlier than that in below normal snow years, leading to more rainy days, longer of the FRS and more rainfall during the FRS. However, rainfall intensity during the FRS shows small difference between different types of the TP snow years. (3) The TP is colder in above normal snow year and the cooling effect stimulates an abnormal anticyclonic circulation over the TP. However, tripole anomaly patterns of 500 hPa geopotential height occur at East Asian coastal region. Configurations of the circulation facilitate cold air in middle-high latitude regions invade SC, which makes a colder SC. And the enhanced northwest Pacific subtropical high intensifies the low-level southerly flow and water vapor supplement. The front swings northward-southward in northern part of the SC during March-April. The FRS has been established once the dry cold northerly and the warm-wet southerly flow invade the SC in early April. In below normal TP snow years, both the cold northerly and warm southerly flow are weak and inactivity and the front in northern part of the SC is interrupted in early April. When the northerly and southerly flow invades the SC in mid-to-late April, the front is reverted and the FRS occurs later.
在线获得:June 22, 2022, DOI: 10.13878/j.cnki.dqkxxb.20220406001
Abstract:
The key dynamic forcing factors and sources of water vapor influencing the remote heavy rainfall over North China produced by Typhoon Lekima on 10 August 2019 are investigated using the surface rain gauge data, ERA5 reanalysis data, and ECWMF ensemble forecasts data. Ensemble sensitivity analysis shows that low-level relative vorticity over the remote typhoon precipitation (TRP) area is the most significant dynamic factor facilitating TRP. The stronger low-level relative vorticity is closely associated with the enhancement of northerly winds in the north caused by the deepening of the low-level short-wave trough and jointly related to the strengthening low-level southerly winds between the TRP and typhoon precipitation (TP) area. The divergence term of relative vorticity is the crucial dynamic process that dominates the strengthening and weakening period of TRP. During the TRP enhancement phase, the positive vorticity is mainly contributed by the positive divergence term, while the negative divergence term leads to the decrease of relative vorticity and the weakening of TRP intensity. The water vapor in the TRP region at 500 hPa is mainly contributed by local area and Typhoon Lekima, while 60% of the water vapor at 700 hPa is contributed by Typhoon Lekima. 40% of the water vapor at 850 hPa is contributed by Typhoon Rosa, and the remaining 60% of water vapor is transported from Typhoon Lekima and the local area.
The key dynamic forcing factors and sources of water vapor influencing the remote heavy rainfall over North China produced by Typhoon Lekima on 10 August 2019 are investigated using the surface rain gauge data, ERA5 reanalysis data, and ECWMF ensemble forecasts data. Ensemble sensitivity analysis shows that low-level relative vorticity over the remote typhoon precipitation (TRP) area is the most significant dynamic factor facilitating TRP. The stronger low-level relative vorticity is closely associated with the enhancement of northerly winds in the north caused by the deepening of the low-level short-wave trough and jointly related to the strengthening low-level southerly winds between the TRP and typhoon precipitation (TP) area. The divergence term of relative vorticity is the crucial dynamic process that dominates the strengthening and weakening period of TRP. During the TRP enhancement phase, the positive vorticity is mainly contributed by the positive divergence term, while the negative divergence term leads to the decrease of relative vorticity and the weakening of TRP intensity. The water vapor in the TRP region at 500 hPa is mainly contributed by local area and Typhoon Lekima, while 60% of the water vapor at 700 hPa is contributed by Typhoon Lekima. 40% of the water vapor at 850 hPa is contributed by Typhoon Rosa, and the remaining 60% of water vapor is transported from Typhoon Lekima and the local area.
在线获得:June 06, 2022, DOI: 10.13878/j.cnki.dqkxxb.20220215001
Abstract:
In recent years, O3 pollution in Nanjing has gradually intensified. In order to understand the impact of surrounding cities on O3 in Nanjing, we simulated the air quality in the Yangtze River Delta(YRD) using the source-oriented WRF/CMAQ regional air quality model from March to October 2018.By tracking the emissions from 41 cities in the YRD and outside the YRD, the characteristics of the transportation of O3 in Nanjing were analyzed under different winds. The results show that from March to October 2018, Nanjing contributes 56.8% of local O3 on polluted days, and contributed 49.5% on polluted days. When pollution occurs, the contribution of surrounding cities to Nanjing increased from 36.4% to 46.3%, and the contribution from outside the YRD to Nanjing decreased from 6.8% to 4.7%. From the perspective of daily changes, Nanjing O3 accounts for more than 70% of the local contribution during the daytime, and at night, most of the transport contributions come from surrounding cities and areas outside the YRD (more than 95%) .On all O3 pollution days, the contribution in Jiangsu Province accounts for 73.1%, 10.8% in Zhejiang Province, 10.5% in Anhui Province and 0.95% in Shanghai. During the pollution period, the contribution ratio of O3 (O3N) produced by NOx as a precursor in Nanjing to O3 (O3V) produced by VOCs as a precursor was about 7:13; During all polluting periods, the proportion of southeast and northeast winds was 38.0% and 35.9% respectively, when the dominant wind direction is northeast, Nanjing has the highest concentration of non-background O3, and the contribution of upwind to Yangzhou reached 13.6%. When the dominant wind direction is southeast wind, the upwind to Changzhou (7.3%), Zhenjiang (7.0%) and Wuxi (6.5%) contributed more to Nanjing O3. Therefore, Nanjing O3 pollution control should consider the transportation of upwind to cities.
In recent years, O3 pollution in Nanjing has gradually intensified. In order to understand the impact of surrounding cities on O3 in Nanjing, we simulated the air quality in the Yangtze River Delta(YRD) using the source-oriented WRF/CMAQ regional air quality model from March to October 2018.By tracking the emissions from 41 cities in the YRD and outside the YRD, the characteristics of the transportation of O3 in Nanjing were analyzed under different winds. The results show that from March to October 2018, Nanjing contributes 56.8% of local O3 on polluted days, and contributed 49.5% on polluted days. When pollution occurs, the contribution of surrounding cities to Nanjing increased from 36.4% to 46.3%, and the contribution from outside the YRD to Nanjing decreased from 6.8% to 4.7%. From the perspective of daily changes, Nanjing O3 accounts for more than 70% of the local contribution during the daytime, and at night, most of the transport contributions come from surrounding cities and areas outside the YRD (more than 95%) .On all O3 pollution days, the contribution in Jiangsu Province accounts for 73.1%, 10.8% in Zhejiang Province, 10.5% in Anhui Province and 0.95% in Shanghai. During the pollution period, the contribution ratio of O3 (O3N) produced by NOx as a precursor in Nanjing to O3 (O3V) produced by VOCs as a precursor was about 7:13; During all polluting periods, the proportion of southeast and northeast winds was 38.0% and 35.9% respectively, when the dominant wind direction is northeast, Nanjing has the highest concentration of non-background O3, and the contribution of upwind to Yangzhou reached 13.6%. When the dominant wind direction is southeast wind, the upwind to Changzhou (7.3%), Zhenjiang (7.0%) and Wuxi (6.5%) contributed more to Nanjing O3. Therefore, Nanjing O3 pollution control should consider the transportation of upwind to cities.
在线获得:June 02, 2022, DOI: 10.13878/j.cnki.dqkxxb.20210811002
Abstract:
Based on the daily precipitation of 24 global climate models from the sixth phase of the Coupled Model Intercomparison Project 6 (CMIP6) multimodel simulations, the generalized extreme value distribution (GEV) is introduced to study the risks of precipitation extremes that expected to occur every 20, 50 and 100 years over China under 1.5/2°C global warming. Compared to the historical period (1995-2014), the changes in the probability risks of extreme precipitation under global warming of 1.5/2℃ present an overall increasing trend. Although their spatial distributions show similar characteristics, the additional half a degree global warming will lead to a higher risk. For example, extreme precipitation that occurred once every 50 years will become once about every 17/14years under the warming of 1.5/2°C, respectively, and extreme precipitation will become more frequent. There are regional differences in the responses of different regions to climate warming, among which the middle and upper reaches of the Yangtze and Yellow Rivers and the Qinghai-Tibet Plateau region in the Western China, and the middle and lower reaches of Yangtze and Yellow Rivers and its south in Eastern China, are highly sensitive response regions to climate change, and their probability ratios reach 3 or even 5 or more. Furthermore, the influence and contribution measures of location and scale parameters on the probability ratios are explored from a theoretical perspective based on the probability distributions, and are used to explore the influences of the climate means and variability changes on the risks of extreme precipitation. The results show that there are significant differences between Eastern China and Western China in the incremental changes of location and scale parameters, and in the rates of probability risk changes, which lead to differences of the factors that influencing the risk of extreme precipitation. In the Western China, although the changes in climate means and variabilities of extreme precipitation are small, the probability ratios increase significantly due to the high rates of probability risk changes. In contrast, the change rates are small, but the climate means and variabilities present a high increase, which also lead to an increase in the Eastern China. Moreover, compared to the location parameters, the increase risks in most of regions over China are mainly due to the changes of scale parameters of extreme precipitation in the future.
Based on the daily precipitation of 24 global climate models from the sixth phase of the Coupled Model Intercomparison Project 6 (CMIP6) multimodel simulations, the generalized extreme value distribution (GEV) is introduced to study the risks of precipitation extremes that expected to occur every 20, 50 and 100 years over China under 1.5/2°C global warming. Compared to the historical period (1995-2014), the changes in the probability risks of extreme precipitation under global warming of 1.5/2℃ present an overall increasing trend. Although their spatial distributions show similar characteristics, the additional half a degree global warming will lead to a higher risk. For example, extreme precipitation that occurred once every 50 years will become once about every 17/14years under the warming of 1.5/2°C, respectively, and extreme precipitation will become more frequent. There are regional differences in the responses of different regions to climate warming, among which the middle and upper reaches of the Yangtze and Yellow Rivers and the Qinghai-Tibet Plateau region in the Western China, and the middle and lower reaches of Yangtze and Yellow Rivers and its south in Eastern China, are highly sensitive response regions to climate change, and their probability ratios reach 3 or even 5 or more. Furthermore, the influence and contribution measures of location and scale parameters on the probability ratios are explored from a theoretical perspective based on the probability distributions, and are used to explore the influences of the climate means and variability changes on the risks of extreme precipitation. The results show that there are significant differences between Eastern China and Western China in the incremental changes of location and scale parameters, and in the rates of probability risk changes, which lead to differences of the factors that influencing the risk of extreme precipitation. In the Western China, although the changes in climate means and variabilities of extreme precipitation are small, the probability ratios increase significantly due to the high rates of probability risk changes. In contrast, the change rates are small, but the climate means and variabilities present a high increase, which also lead to an increase in the Eastern China. Moreover, compared to the location parameters, the increase risks in most of regions over China are mainly due to the changes of scale parameters of extreme precipitation in the future.
在线获得:May 23, 2022, DOI: :10.13878/j.cnki.dqkxxb. 20220503002
Abstract:
A wind profiler radar is a new type of Doppler wind radar designed to measure the horizontal wind vectors, and are able to provide wind profiles at various elevations with high temporal and spatial resolution. It plays an increasingly important role in China"s Meteorological business. However, the quality of wind profiler radar data varies widely consider-ing the different types of radars deployed in China. To better utilize these data in numerical weather prediction (NWP), this study assesses the data quality from five different types of wind profiler radars (i.e., CFL-06, GLC-24, TWP8-L, CFL-03 and CLC-11-D) at 20 stations in North China from June to September 2019. Results show that each type of profiler has strong detection ability, but different profilers have great differences in data acquisition rate and effective detection height. Without considering the influence of precipitation, the data quality of v-wind is better than that of u-wind for all types of profilers. In all air conditions, the quality of u-wind data from TWP8-L profiler is relatively the best, followed by CFL-03 radar, the quality of u-wind data from GLC-24 radar is the worst. The differences in v-wind data is not noticea-ble, while bias correction and quality control are necessary for u-wind data. The data quality of wind profile radar is quite sensitive to precipitation, which reduces the data acquisition rates at low levels and increases the data acquisition rates at the middle and high levels, with the maximum increase of 53%. The statistical results indicate precipitation is responsible for the large mean errors and root mean square errors (RMSEs) of u wind data. GLC-24 and CLC-11-D profilers are the most sensitive to precipitation. The RMSEs are increased by 5.5 m/s in precipitation regions as compared to non-precipitation regions. The u-wind and v-wind data in precipitation regions requires further quality control procedure.
A wind profiler radar is a new type of Doppler wind radar designed to measure the horizontal wind vectors, and are able to provide wind profiles at various elevations with high temporal and spatial resolution. It plays an increasingly important role in China"s Meteorological business. However, the quality of wind profiler radar data varies widely consider-ing the different types of radars deployed in China. To better utilize these data in numerical weather prediction (NWP), this study assesses the data quality from five different types of wind profiler radars (i.e., CFL-06, GLC-24, TWP8-L, CFL-03 and CLC-11-D) at 20 stations in North China from June to September 2019. Results show that each type of profiler has strong detection ability, but different profilers have great differences in data acquisition rate and effective detection height. Without considering the influence of precipitation, the data quality of v-wind is better than that of u-wind for all types of profilers. In all air conditions, the quality of u-wind data from TWP8-L profiler is relatively the best, followed by CFL-03 radar, the quality of u-wind data from GLC-24 radar is the worst. The differences in v-wind data is not noticea-ble, while bias correction and quality control are necessary for u-wind data. The data quality of wind profile radar is quite sensitive to precipitation, which reduces the data acquisition rates at low levels and increases the data acquisition rates at the middle and high levels, with the maximum increase of 53%. The statistical results indicate precipitation is responsible for the large mean errors and root mean square errors (RMSEs) of u wind data. GLC-24 and CLC-11-D profilers are the most sensitive to precipitation. The RMSEs are increased by 5.5 m/s in precipitation regions as compared to non-precipitation regions. The u-wind and v-wind data in precipitation regions requires further quality control procedure.
在线获得:May 06, 2022, DOI: :10.13878/j.cnki.dqkxxb. 20220207001
Abstract:
We proposed a novel method to predict the meteorological risk for important events, and successfully applied it to the 70th anniversary celebration of the People"s Republic of China. The method based on fine meteorological factors analysis, considered risk resources(weather risk) and vulnerability(impact on events), so that efficient measures can be taken in advance to make sure the success of the events. A risk matrix method was used to perform the analysis and prediction. Meteorological risk levels were evaluated and risk maps were drawn of major celebration events based on the investigation and analysis of meteorological factors that may affected the successful holding of the celebration events and the occurrence ratio of different meteorological events. For the 70th anniversary celebration of the People"s Republic of China, we recognized the major weather risks (from high to low) were precipitation/overcast and rain, day force eight wind, frog-haze, night force eight wind, high temperature and direct sunlight, thunder and lightning, low temperature, etc.. Risk control measures and countermeasures were put forward to the risk caused by different meteorological factors, which provided important reference for the scientific formulation and implementation of safety work plan and the successful development of activities. In the meteorological support work of major activities, a major change has been realized from considering only the occurrence probability of high impact weather to risk assessment based on weather impact and we got a good service effect for the events.
We proposed a novel method to predict the meteorological risk for important events, and successfully applied it to the 70th anniversary celebration of the People"s Republic of China. The method based on fine meteorological factors analysis, considered risk resources(weather risk) and vulnerability(impact on events), so that efficient measures can be taken in advance to make sure the success of the events. A risk matrix method was used to perform the analysis and prediction. Meteorological risk levels were evaluated and risk maps were drawn of major celebration events based on the investigation and analysis of meteorological factors that may affected the successful holding of the celebration events and the occurrence ratio of different meteorological events. For the 70th anniversary celebration of the People"s Republic of China, we recognized the major weather risks (from high to low) were precipitation/overcast and rain, day force eight wind, frog-haze, night force eight wind, high temperature and direct sunlight, thunder and lightning, low temperature, etc.. Risk control measures and countermeasures were put forward to the risk caused by different meteorological factors, which provided important reference for the scientific formulation and implementation of safety work plan and the successful development of activities. In the meteorological support work of major activities, a major change has been realized from considering only the occurrence probability of high impact weather to risk assessment based on weather impact and we got a good service effect for the events.
在线获得:May 06, 2022, DOI: :10.13878/j.cnki.dqkxxb. 20211230001
Abstract:
Nowadays, ensemble forecasting has become the main support for operational weather forecasting. However, due to the limitations and imperfections of the numerical model itself, the forecast results are generally systematically biased. In addition, different forecasting models usually have different physical parameterization schemes, initial conditions, etc., resulting in different forecasting capabilities. Therefore, how to eliminate systematic biases and how to make full and effective use of forecast information from different models to obtain more accurate weather forecasts has received extensive attention. In recent years, using statistical theory and forecasting diagnosis, multimodel ensemble forecasting technologies based on multiple ensemble prediction systems have been rapidly developed to effectively eliminate systematic biases and improve weather forecasting skills. For the three most basic surface meteorological variables (i.e., temperature, precipitation, wind), the widely used multimodel ensemble technologies such as ensemble mean (EM), bias-removed ensemble mean (BREM), superensemble (SUP), Bayesian model averaging(BMA), and ensemble model output statistics(EMOS) are first introduced from the perspective of deterministic forecasting and probabilistic forecasting. Finally, the issues that need to be paid attention to when using and developing multimodel ensemble technologies are discussed, including the consideration the number of participating models, the development of categorized precipitation and wind speed forecast models. Meanwhile, the combination of multimodel ensemble with machine learning deserves more investigation.
Nowadays, ensemble forecasting has become the main support for operational weather forecasting. However, due to the limitations and imperfections of the numerical model itself, the forecast results are generally systematically biased. In addition, different forecasting models usually have different physical parameterization schemes, initial conditions, etc., resulting in different forecasting capabilities. Therefore, how to eliminate systematic biases and how to make full and effective use of forecast information from different models to obtain more accurate weather forecasts has received extensive attention. In recent years, using statistical theory and forecasting diagnosis, multimodel ensemble forecasting technologies based on multiple ensemble prediction systems have been rapidly developed to effectively eliminate systematic biases and improve weather forecasting skills. For the three most basic surface meteorological variables (i.e., temperature, precipitation, wind), the widely used multimodel ensemble technologies such as ensemble mean (EM), bias-removed ensemble mean (BREM), superensemble (SUP), Bayesian model averaging(BMA), and ensemble model output statistics(EMOS) are first introduced from the perspective of deterministic forecasting and probabilistic forecasting. Finally, the issues that need to be paid attention to when using and developing multimodel ensemble technologies are discussed, including the consideration the number of participating models, the development of categorized precipitation and wind speed forecast models. Meanwhile, the combination of multimodel ensemble with machine learning deserves more investigation.
在线获得:March 23, 2022, DOI: 10.13878/j.cnki.dqkxxb. 20211229001
Abstract:
To study the differences and similarities between fine observation and conventional observation in fog microstructure, a systematic field observation of fog was conducted and lasted 58 days in Donghai, Lianyungang during the winter of 2020. Two fog monitors with different frequencies (5Hz and 1Hz) were applied simultaneously for measuring a radiation fog on December 28, 2020. Based on this observation, we found that compared with the 1Hz data, the 5Hz measurement observed more extreme values. In terms of the whole fog process, the results of the 5Hz fog droplet spectrometer averaged into 1Hz are less similar to the original results of 1Hz in the fog generation and dissipation stages, and more similar in the fog maturation and development stages. In terms of the spectral patterns, the spectral patterns of 5 Hz and 1 Hz are similar, while the main differences appear at the peak. The measurements of 5 Hz and 1 Hz can both reflect the relationship between the microphysics at different stages of this fog process, and the main differences appear at the fog generation stage. This may be due to the relatively small number of activation and condensation growth of new fog droplets observed at 5Hz at this stage.
To study the differences and similarities between fine observation and conventional observation in fog microstructure, a systematic field observation of fog was conducted and lasted 58 days in Donghai, Lianyungang during the winter of 2020. Two fog monitors with different frequencies (5Hz and 1Hz) were applied simultaneously for measuring a radiation fog on December 28, 2020. Based on this observation, we found that compared with the 1Hz data, the 5Hz measurement observed more extreme values. In terms of the whole fog process, the results of the 5Hz fog droplet spectrometer averaged into 1Hz are less similar to the original results of 1Hz in the fog generation and dissipation stages, and more similar in the fog maturation and development stages. In terms of the spectral patterns, the spectral patterns of 5 Hz and 1 Hz are similar, while the main differences appear at the peak. The measurements of 5 Hz and 1 Hz can both reflect the relationship between the microphysics at different stages of this fog process, and the main differences appear at the fog generation stage. This may be due to the relatively small number of activation and condensation growth of new fog droplets observed at 5Hz at this stage.
Accounting the carbon sequestration rate of terrestrial ecosystems: methods, progress and challenges
在线获得:March 14, 2022, DOI: 10.13878/j.cnki.dqkxxb. 20220303002
Abstract:
Global warming, caused by the rapid increase of atmospheric CO2 has become an urgent problem for sustainable development of human beings. Terrestrial ecosystems have played an important carbon sink role in the past decades by absorbing about 30% of the CO2 emitted by human activities. This paper reviewed the estimation methods of carbon sequestration rate of terrestrial ecosystems, including sampling inventory, flux monitoring, model simulation, remote sensing, etc., and analyzed the progresses and challenges of the current approaches for accounting terrestrial carbon sequestration. Sampling inventory and flux observations can provide direct measurement of plot-scale carbon sequestration rate, but there are many problems, such as limited observation samples and insufficient spatial representation. Model simulation methods can describe the terrestrial carbon cycles and simulate the state and change of carbon sequestration rates in terrestrial ecosystems. However, the approximating and simplifying processes in model, together with the uncertainties introduced by model-driven data, it is very challenging to accurately modeling the carbon sequestration rate of terrestrial ecosystems. Satellite remote sensing, holding the advantages of global coverage, fine resolution, and time-series observations, combined with machine learning methods, can provide a new approach for the estimation of the carbon sequestration rate of terrestrial ecosystems. So far, various accounting methods for carbon sequestration rates have not yet met the needs of monitoring carbon sequestration in terrestrial ecosystems due to the high spatial and temporal heterogeneity. In the future, it is extremely important to integrate various accounting approaches, such as ground observations, model simulations, and satellite remote sensing, to provide accurate estimation of terrestrial ecosystem carbon sinks at the regional and global scales.
Global warming, caused by the rapid increase of atmospheric CO2 has become an urgent problem for sustainable development of human beings. Terrestrial ecosystems have played an important carbon sink role in the past decades by absorbing about 30% of the CO2 emitted by human activities. This paper reviewed the estimation methods of carbon sequestration rate of terrestrial ecosystems, including sampling inventory, flux monitoring, model simulation, remote sensing, etc., and analyzed the progresses and challenges of the current approaches for accounting terrestrial carbon sequestration. Sampling inventory and flux observations can provide direct measurement of plot-scale carbon sequestration rate, but there are many problems, such as limited observation samples and insufficient spatial representation. Model simulation methods can describe the terrestrial carbon cycles and simulate the state and change of carbon sequestration rates in terrestrial ecosystems. However, the approximating and simplifying processes in model, together with the uncertainties introduced by model-driven data, it is very challenging to accurately modeling the carbon sequestration rate of terrestrial ecosystems. Satellite remote sensing, holding the advantages of global coverage, fine resolution, and time-series observations, combined with machine learning methods, can provide a new approach for the estimation of the carbon sequestration rate of terrestrial ecosystems. So far, various accounting methods for carbon sequestration rates have not yet met the needs of monitoring carbon sequestration in terrestrial ecosystems due to the high spatial and temporal heterogeneity. In the future, it is extremely important to integrate various accounting approaches, such as ground observations, model simulations, and satellite remote sensing, to provide accurate estimation of terrestrial ecosystem carbon sinks at the regional and global scales.
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2019,42(2): 161-173, DOI: 10.13878/j.cnki.dqkxxb.20170504012
Abstract:
The eyewall replacement cycle plays an important role in changes regarding typhoon intensity and inner-core structure.In this study,in order to investigate the influences of large-eddy simulation(LES) on eyewall replacement,two ideal numerical experiments were conducted,of which one was coupled with LES.The study results indicate that the typhoon intensity of the LES experiment was stronger with larger inflow in the boundary layers.It took the two typhoon approximately 20-22 hours to complete the entire eyewall replacement,but the typhoon in the LES experiment had a faster enclosing of the outer eyewall.At the same time,the intensity and updraft in the outer eyewall were also greater.After the eyewall replacement,the typhoon in the LES experiment continued to intensify,and its intensity became greater than it was before the eyewall replacement.Of more importance is that the LES can more effectively simulate the downdraft within the moat region which is at the outside of the inner eyewall.In addition,the downward motion can more effectively induce the formation and development of convections near the outer eyewall regions,and is in line with the observational features found by previous studies.
The eyewall replacement cycle plays an important role in changes regarding typhoon intensity and inner-core structure.In this study,in order to investigate the influences of large-eddy simulation(LES) on eyewall replacement,two ideal numerical experiments were conducted,of which one was coupled with LES.The study results indicate that the typhoon intensity of the LES experiment was stronger with larger inflow in the boundary layers.It took the two typhoon approximately 20-22 hours to complete the entire eyewall replacement,but the typhoon in the LES experiment had a faster enclosing of the outer eyewall.At the same time,the intensity and updraft in the outer eyewall were also greater.After the eyewall replacement,the typhoon in the LES experiment continued to intensify,and its intensity became greater than it was before the eyewall replacement.Of more importance is that the LES can more effectively simulate the downdraft within the moat region which is at the outside of the inner eyewall.In addition,the downward motion can more effectively induce the formation and development of convections near the outer eyewall regions,and is in line with the observational features found by previous studies.
2022,45(2): 280-291, DOI: 10.13878/j.cnki.dqkxxb.20200719017
Abstract:
Based on the sea surface temperature (SST) data from NOAA in USA, the asymmetric characteristics of interannual relationship between ENSO and Victoria mode (VM;EOF2 of North Pacific SST anomalies in winter (DJF)) were emphatically analyzed.Results show that the correlation between VM and ENSO is weak on the decadal scale, but strong on the interannual scale.VM has significant negative correlation with ENSO in the same year, and has strong positive correlation with ENSO in the following year.However, there is a certain asymmetry in the relationship between the positive/negative VM events and ENSO warm/cold phases on the interannual scale.The relationship between the positive VM events and the SST anomalies in the tropical central and eastern Pacific in the same winter is weak, but El Niño events often occur in the following year.In contrast, the negative VM events are usually accompanied by El Niño events in the same years, but there is no significant relationship between the negative VM events and the SST anomalies in the tropical central and eastern Pacific in the following winter and there are few ENSO events.It can be seen that the positive VM event seems to promote the occurrence and development of El Niño in the next year and can be used as one of the early prediction factors of ENSO, while the negative VM event cannot be used as the early prediction factor of ENSO.
Based on the sea surface temperature (SST) data from NOAA in USA, the asymmetric characteristics of interannual relationship between ENSO and Victoria mode (VM;EOF2 of North Pacific SST anomalies in winter (DJF)) were emphatically analyzed.Results show that the correlation between VM and ENSO is weak on the decadal scale, but strong on the interannual scale.VM has significant negative correlation with ENSO in the same year, and has strong positive correlation with ENSO in the following year.However, there is a certain asymmetry in the relationship between the positive/negative VM events and ENSO warm/cold phases on the interannual scale.The relationship between the positive VM events and the SST anomalies in the tropical central and eastern Pacific in the same winter is weak, but El Niño events often occur in the following year.In contrast, the negative VM events are usually accompanied by El Niño events in the same years, but there is no significant relationship between the negative VM events and the SST anomalies in the tropical central and eastern Pacific in the following winter and there are few ENSO events.It can be seen that the positive VM event seems to promote the occurrence and development of El Niño in the next year and can be used as one of the early prediction factors of ENSO, while the negative VM event cannot be used as the early prediction factor of ENSO.
Abstract:
Based on the hourly precipitation observed by automatic weather stations(AWS) in China and retrieved from CMORPH(CPC MORPHing technique) satellite data,the merged precipitation product at hourly/0.1°lat/0.1°lon temporal-spatial resolution in China is developed through the two-step merging algorithm of PDF(probability density function) and OI(optimal interpolation).In this paper,the quality of merged precipitation product is assessed from the points of temporal-spatial characteristics of error,accuracy at different precipitation rates and cumulative times,merging effect at three station network densities and monitoring capability of the heavy rainfall.Results indicate that:1)The merged precipitation product effectively uses the advantages of AWS observations and satellite product of CMORPH,so it is more reasonable both at the precipitation amount and spatial distribution;2)The regional mean bias and root-mean-square error of the merged precipitation product are decreased remarkably,and they have a little change with time;3)The relative bias of merged precipitation product is -1.675%,less than 15% and about 30% for the medium(1.0—2.5 mm/h),medium to large(1.0—8.0 mm/h) and heavy rainfall(≥8.0 mm/h),respectively,and the product quality is improved further with the cumulative time increases.The merged precipitation product can capture the precipitation process very well and have a definite advantage in the quantitatively rainfall monitoring.
Based on the hourly precipitation observed by automatic weather stations(AWS) in China and retrieved from CMORPH(CPC MORPHing technique) satellite data,the merged precipitation product at hourly/0.1°lat/0.1°lon temporal-spatial resolution in China is developed through the two-step merging algorithm of PDF(probability density function) and OI(optimal interpolation).In this paper,the quality of merged precipitation product is assessed from the points of temporal-spatial characteristics of error,accuracy at different precipitation rates and cumulative times,merging effect at three station network densities and monitoring capability of the heavy rainfall.Results indicate that:1)The merged precipitation product effectively uses the advantages of AWS observations and satellite product of CMORPH,so it is more reasonable both at the precipitation amount and spatial distribution;2)The regional mean bias and root-mean-square error of the merged precipitation product are decreased remarkably,and they have a little change with time;3)The relative bias of merged precipitation product is -1.675%,less than 15% and about 30% for the medium(1.0—2.5 mm/h),medium to large(1.0—8.0 mm/h) and heavy rainfall(≥8.0 mm/h),respectively,and the product quality is improved further with the cumulative time increases.The merged precipitation product can capture the precipitation process very well and have a definite advantage in the quantitatively rainfall monitoring.
2014,37(5): 642-652, DOI: 10.13878/j.cnki.dqkxxb.20121017006
Abstract:
In this paper,the Weather Research and Forecast Model(WRF) is coupled with Surface-Layer Scheme,Single-Layer Urban Canopy Model and Mingle-Layer Urban Canopy Model respectively to evaluate the simulation effect of various parameterizations on the weather conditions on 1 August 2007 in Nanjing.The best urban parameterization scheme is coupled into WRF to study the impact of land cover change on the Urban Heat Island(UHI) effect in Nanjing.Results show that the Mingle-Layer Urban Canopy Model shows the best simulation effect for surface temperature and 10m wind field.Urbanization makes surface air temperature increase over the region,especially at night and thus intensifies the UHI effect.After urbanization,the wind speed in the downtown area decreases obviously while the Urban Heat Circulation occurs more apparently.There also exists the downstream effect of UHI in Nanjing.
In this paper,the Weather Research and Forecast Model(WRF) is coupled with Surface-Layer Scheme,Single-Layer Urban Canopy Model and Mingle-Layer Urban Canopy Model respectively to evaluate the simulation effect of various parameterizations on the weather conditions on 1 August 2007 in Nanjing.The best urban parameterization scheme is coupled into WRF to study the impact of land cover change on the Urban Heat Island(UHI) effect in Nanjing.Results show that the Mingle-Layer Urban Canopy Model shows the best simulation effect for surface temperature and 10m wind field.Urbanization makes surface air temperature increase over the region,especially at night and thus intensifies the UHI effect.After urbanization,the wind speed in the downtown area decreases obviously while the Urban Heat Circulation occurs more apparently.There also exists the downstream effect of UHI in Nanjing.
Abstract:
Based on the multiple type observational data,this paper preliminarily analyses the meso scale convective systems(MCSs) and weather background producing an extremely heavy rain along the Mei yu front in Hubei and Anhui provinces during 29—30 June 2009,and investigates the multi scale structure features of the Mei yu frontal rainstorm system.Then the meso scale numerical model WRF with large domain and 9 km horizontal resolution is used to carry out a 3 domain nested fine simulation for the heavy rain process.Morlet wavelet transformation is carried out to do spatial band passing filter for the model outputs,and the meso 〖WTBX〗α, β〖WTB1〗 and 〖WTBX〗γ〖WTB1〗 scale systems are separated out,in such a way that the three dimensional spatial dynamic and thermodynamic characteristics of the meso scale systems with different scales are studied.The results are as follows.The extremely Mei yu frontal heavy rain is directly resulted from several MCSs with different scales,which are of different features on satellite cloud images and radar echoes.On meso 〖WTBX〗α, β〖WTB1〗 and 〖WTBX〗γ〖WTB1〗 scales,the Mei yu frontal heavy rain system has obvious different dynamic and thermodynamic structure features in horizontal and vertical directions.The meso 〖WTBX〗α〖WTB1〗 and 〖WTBX〗β〖WTB1〗 scale systems have obvious vertical circulation,while meso 〖WTBX〗γ〖WTB1〗 scale system has some features of inertial gravity waves and usually develops in meso 〖WTBX〗α〖WTB1〗 and 〖WTBX〗β〖WTB1〗 scale system.Lastly,a physic conceptual model is advanced for the typical Mei yu frontal rainstorm system.
Based on the multiple type observational data,this paper preliminarily analyses the meso scale convective systems(MCSs) and weather background producing an extremely heavy rain along the Mei yu front in Hubei and Anhui provinces during 29—30 June 2009,and investigates the multi scale structure features of the Mei yu frontal rainstorm system.Then the meso scale numerical model WRF with large domain and 9 km horizontal resolution is used to carry out a 3 domain nested fine simulation for the heavy rain process.Morlet wavelet transformation is carried out to do spatial band passing filter for the model outputs,and the meso 〖WTBX〗α, β〖WTB1〗 and 〖WTBX〗γ〖WTB1〗 scale systems are separated out,in such a way that the three dimensional spatial dynamic and thermodynamic characteristics of the meso scale systems with different scales are studied.The results are as follows.The extremely Mei yu frontal heavy rain is directly resulted from several MCSs with different scales,which are of different features on satellite cloud images and radar echoes.On meso 〖WTBX〗α, β〖WTB1〗 and 〖WTBX〗γ〖WTB1〗 scales,the Mei yu frontal heavy rain system has obvious different dynamic and thermodynamic structure features in horizontal and vertical directions.The meso 〖WTBX〗α〖WTB1〗 and 〖WTBX〗β〖WTB1〗 scale systems have obvious vertical circulation,while meso 〖WTBX〗γ〖WTB1〗 scale system has some features of inertial gravity waves and usually develops in meso 〖WTBX〗α〖WTB1〗 and 〖WTBX〗β〖WTB1〗 scale system.Lastly,a physic conceptual model is advanced for the typical Mei yu frontal rainstorm system.
2023,46(3): 332-344, DOI: 10.13878/j.cnki.dqkxxb.20230303001
Abstract:
The summer of 2022 exhibits significant characteristics of high temperature,low humidity,and rainfall in South China.Previous studies have focused on extreme events of high temperature and low rainfall in summer,whereas attention to near-ground relative humidity,which is closely related to human comfort and crop growth,has been relatively insufficient.In this study,we define events of positive temperature anomaly,negative precipitation anomaly,and negative relative humidity anomaly exceeding one time of the interannual standard deviation between 1959 and 2022 are as compound events of summer high temperature,low humidity,and rainfall.Monthly ERA5 atmospheric reanalysis data of 1959—2022 are used in this study.We study the effect of spring soil moisture on the compound events in summer by composite analysis and a dynamic adjustment approach based on constructed circulation analogs,and the physical mechanism is analyzed.The results show that:1) The hot spots of the coupling between spring soil moisture and summer climate in south China are basically consistent with the high variability of summer temperature,precipitation,and relative humidity in 2022.2) When the soil in the Yangtze River Basin and Huang-Huai area is dry in spring and the southeast area is wet,the compound events of drying and heat will occur in summer.3) The effect of spring soil moisture on summer climate variability is mainly realized by adjusting the distribution of local evapotranspiration and net radiation energy.The study of the compound extreme events of high temperature,low humidity,and rainfall is of great significance in effectively preventing all kinds of disasters and safety accidents caused by them,protecting people's lives and property,and maintaining social production order.
The summer of 2022 exhibits significant characteristics of high temperature,low humidity,and rainfall in South China.Previous studies have focused on extreme events of high temperature and low rainfall in summer,whereas attention to near-ground relative humidity,which is closely related to human comfort and crop growth,has been relatively insufficient.In this study,we define events of positive temperature anomaly,negative precipitation anomaly,and negative relative humidity anomaly exceeding one time of the interannual standard deviation between 1959 and 2022 are as compound events of summer high temperature,low humidity,and rainfall.Monthly ERA5 atmospheric reanalysis data of 1959—2022 are used in this study.We study the effect of spring soil moisture on the compound events in summer by composite analysis and a dynamic adjustment approach based on constructed circulation analogs,and the physical mechanism is analyzed.The results show that:1) The hot spots of the coupling between spring soil moisture and summer climate in south China are basically consistent with the high variability of summer temperature,precipitation,and relative humidity in 2022.2) When the soil in the Yangtze River Basin and Huang-Huai area is dry in spring and the southeast area is wet,the compound events of drying and heat will occur in summer.3) The effect of spring soil moisture on summer climate variability is mainly realized by adjusting the distribution of local evapotranspiration and net radiation energy.The study of the compound extreme events of high temperature,low humidity,and rainfall is of great significance in effectively preventing all kinds of disasters and safety accidents caused by them,protecting people's lives and property,and maintaining social production order.
2019,42(4): 631-640, DOI: 10.13878/j.cnki.dqkxxb.20170815015
Abstract:
Imperative quality control methods for Doppler radar data,such as ground clutter elimination,range folding elimination and velocity dealiasing,should be adopted before being used for quantitative analyses,due to the serious impacts originating from certain non-meteorological factors.In this study,in order to precisely identify the ground clutter and precipitous echo,an automatic algorithm based on the Support Vector Machine(SVM) is performed,based on the observational CINRAD/SA Doppler weather radar data in the areas of Anqing and Changzhou from June to August,2013,and the results are compared with the recognition effect based on the Artificial Neural Networks(ANNs) method.Statistical learning theory(SLT) is favorable for small samples,which focuses on the statistical law and nature of small-sample learning.As a new machine learning based on SLT,the basic principle of the SVM is to possess an optimal separating hyperplane which is able to satisfy the requirement of the classification accuracy by introducing the largest classification intervals on either side of the hyperplane.In the first step,the dataset used in the experiment will be establised by empirically distinguishing the ground clutter and precipitous points at each bin.Next,several characteristic parameters,which are used to quantify the possibility affected by the ground clutter,such as reflectivity vertical variation (GDBZ),reflectivity horizontal texture (TDBZ),velocity regional average (MDVE),and spectrum regional average (MDSW),will be derived from the reflectivity,radaial velocity,spectrum width and spatial variance information of the ground clutter and precipitous echo.The statistical results of the above characteristic parameters show the following:a large portion of these parameters vary in terms of ground clutter and precipitous echo,which indicates that the seven parameters (GDBZ,TDBZ,SPIN,SIGN,MDVE,MDSW and SDVE) contribute to the identifiable recognition of the ground clutter and precipitous echo.Based on the above conclusions,seven parameters,which are regarded as the trigger (the training factor of SVM) to establish the SVM's training model,can be randomly extracted from the database.Finally,the training model is used to automatically recognize the ground clutter and precipitation using the random data from the database.The recognition effect of the SVM method will be examined by comparing the model output with the empirical identifications,and the examination of the ANNs algorithm is the same as that of the SVM method.The comparison of the recognition effect between the SVM and ANNs methods reveals the following:(1) The statistically identifiable recognition parameter for the sSVM and ANNs methods appears to be steady,despite the fact that the Doppler radar data vary in shape and position between Anqing and Changzhou;(2) An identifying threshold must be determined for the ANNs method before the ground clutter and precipitous echo are identified,which will lead to a differently identifiable accuracy with the unlike threshold;and (3) Overall,the SVM method works better than the ANNs method in terms of radar echo identification.Moreover,the identifiable recognition accuracy of the latter increases significantly with the increasing total number of training samples,while the identifiable recognition accuracy of the former performs at a highly accurate level,which remains relatively stable with the changes in the training samples.In terms of the identification accuracy of the total samples (ground clutter and precipitous echo) and identification accuracy of the ground clutter echo,the SVM method presents better results than the ANNs method.As for the precipitous echo erroneous recognition,the ANNs method performs slightly better than the SVM,but both methods control the erroneous recognition rate at a low level.
Imperative quality control methods for Doppler radar data,such as ground clutter elimination,range folding elimination and velocity dealiasing,should be adopted before being used for quantitative analyses,due to the serious impacts originating from certain non-meteorological factors.In this study,in order to precisely identify the ground clutter and precipitous echo,an automatic algorithm based on the Support Vector Machine(SVM) is performed,based on the observational CINRAD/SA Doppler weather radar data in the areas of Anqing and Changzhou from June to August,2013,and the results are compared with the recognition effect based on the Artificial Neural Networks(ANNs) method.Statistical learning theory(SLT) is favorable for small samples,which focuses on the statistical law and nature of small-sample learning.As a new machine learning based on SLT,the basic principle of the SVM is to possess an optimal separating hyperplane which is able to satisfy the requirement of the classification accuracy by introducing the largest classification intervals on either side of the hyperplane.In the first step,the dataset used in the experiment will be establised by empirically distinguishing the ground clutter and precipitous points at each bin.Next,several characteristic parameters,which are used to quantify the possibility affected by the ground clutter,such as reflectivity vertical variation (GDBZ),reflectivity horizontal texture (TDBZ),velocity regional average (MDVE),and spectrum regional average (MDSW),will be derived from the reflectivity,radaial velocity,spectrum width and spatial variance information of the ground clutter and precipitous echo.The statistical results of the above characteristic parameters show the following:a large portion of these parameters vary in terms of ground clutter and precipitous echo,which indicates that the seven parameters (GDBZ,TDBZ,SPIN,SIGN,MDVE,MDSW and SDVE) contribute to the identifiable recognition of the ground clutter and precipitous echo.Based on the above conclusions,seven parameters,which are regarded as the trigger (the training factor of SVM) to establish the SVM's training model,can be randomly extracted from the database.Finally,the training model is used to automatically recognize the ground clutter and precipitation using the random data from the database.The recognition effect of the SVM method will be examined by comparing the model output with the empirical identifications,and the examination of the ANNs algorithm is the same as that of the SVM method.The comparison of the recognition effect between the SVM and ANNs methods reveals the following:(1) The statistically identifiable recognition parameter for the sSVM and ANNs methods appears to be steady,despite the fact that the Doppler radar data vary in shape and position between Anqing and Changzhou;(2) An identifying threshold must be determined for the ANNs method before the ground clutter and precipitous echo are identified,which will lead to a differently identifiable accuracy with the unlike threshold;and (3) Overall,the SVM method works better than the ANNs method in terms of radar echo identification.Moreover,the identifiable recognition accuracy of the latter increases significantly with the increasing total number of training samples,while the identifiable recognition accuracy of the former performs at a highly accurate level,which remains relatively stable with the changes in the training samples.In terms of the identification accuracy of the total samples (ground clutter and precipitous echo) and identification accuracy of the ground clutter echo,the SVM method presents better results than the ANNs method.As for the precipitous echo erroneous recognition,the ANNs method performs slightly better than the SVM,but both methods control the erroneous recognition rate at a low level.
Abstract:
Wind shear in the atmosphere is a serious threat to the safety of aircraft,especially the low-level wind shear which is an important factor affecting the aircraft taking off and landing.By using the Doppler radar velocity data to calculate the one-dimension tangential,one-dimensional radial and two-dimension composite shear,accurately judging the dangerous area of wind shear could provide timely warning for flight,taking off and landing.In this study,as the wind shear automatic identification product on the principal user processor(PUP) for Doppler radar applications has the shortcomings such as weak edge recognition and larger location errors,according to Doppler radar velocity distributions and taking advantage of least square fitting method,"fitting window" suitable for airborne radar parameters are chosen,and the several cases have been identified and analyzed.For the performance in wind shear's identification,location and edge discerning,the least square method could provide better reference of wind shear and warnings than PUP's identification products.
Wind shear in the atmosphere is a serious threat to the safety of aircraft,especially the low-level wind shear which is an important factor affecting the aircraft taking off and landing.By using the Doppler radar velocity data to calculate the one-dimension tangential,one-dimensional radial and two-dimension composite shear,accurately judging the dangerous area of wind shear could provide timely warning for flight,taking off and landing.In this study,as the wind shear automatic identification product on the principal user processor(PUP) for Doppler radar applications has the shortcomings such as weak edge recognition and larger location errors,according to Doppler radar velocity distributions and taking advantage of least square fitting method,"fitting window" suitable for airborne radar parameters are chosen,and the several cases have been identified and analyzed.For the performance in wind shear's identification,location and edge discerning,the least square method could provide better reference of wind shear and warnings than PUP's identification products.
2023,46(6): 950-960, DOI: 10.13878/j.cnki.dqkxxb.20230313001
Abstract:
Northern China experienced four sandstorms or severe sandstorms in spring 2021, contrasting with just one event in the corresponding period of 2022. Utilizing air quality and multi-source meteorological data spanning 2015 to 2022, we applied the Lamb Jenkinson classification and Mann-Whitney U test methods to analyze similarities and differences in the sand source areas' conditions and meteorological factors during the spring of 2021 and 2022. Our findings reveal that the sand and dust weather (SDW) in northern China is frequently categorized into NW-N (cyclone type) and E-NE (high-pressure type), with the NW-N type leading to higher PM10 extreme values and a broader range of high concentrations. In terms of meteorological factors, synoptic conditions favorable for SDW in spring 2022 occur more frequently, with the differences in daily PM10 concentration predominantly associated with the NW-N type when compared to spring 2021. The frequency of NW-N type events and cyclone intensity remains comparable between the two periods, along with similar dynamic uplift conditions conducive to SDW are similar. Regarding sand source area conditions, the soil temperature in Mongolia's sand source area displayed a “cold before and warm after” pattern in the pre-winter of 2021, resulting in an early peak of snowmelt and other water content. In addition, a widespread decrease in precipitation and a relatively strong cyclone in Mongolia's sand source area in March contributed to the high incidence of sand and dust in spring 2021. Conversely, during the pre-winter of 2022, the soil temperature in Mongolia's sand source area followed a “warm before and cold after” trend, leading to a delayed peak of water content and soil moisture content during the snowmelt period. These conditions, characterized by thicker and moisture soil, were less conducive to sand formation. Therefore, the disparities in Mongolian sand source area conditions represent the primary factor behind the significant differences in SDW between the two periods.
Northern China experienced four sandstorms or severe sandstorms in spring 2021, contrasting with just one event in the corresponding period of 2022. Utilizing air quality and multi-source meteorological data spanning 2015 to 2022, we applied the Lamb Jenkinson classification and Mann-Whitney U test methods to analyze similarities and differences in the sand source areas' conditions and meteorological factors during the spring of 2021 and 2022. Our findings reveal that the sand and dust weather (SDW) in northern China is frequently categorized into NW-N (cyclone type) and E-NE (high-pressure type), with the NW-N type leading to higher PM10 extreme values and a broader range of high concentrations. In terms of meteorological factors, synoptic conditions favorable for SDW in spring 2022 occur more frequently, with the differences in daily PM10 concentration predominantly associated with the NW-N type when compared to spring 2021. The frequency of NW-N type events and cyclone intensity remains comparable between the two periods, along with similar dynamic uplift conditions conducive to SDW are similar. Regarding sand source area conditions, the soil temperature in Mongolia's sand source area displayed a “cold before and warm after” pattern in the pre-winter of 2021, resulting in an early peak of snowmelt and other water content. In addition, a widespread decrease in precipitation and a relatively strong cyclone in Mongolia's sand source area in March contributed to the high incidence of sand and dust in spring 2021. Conversely, during the pre-winter of 2022, the soil temperature in Mongolia's sand source area followed a “warm before and cold after” trend, leading to a delayed peak of water content and soil moisture content during the snowmelt period. These conditions, characterized by thicker and moisture soil, were less conducive to sand formation. Therefore, the disparities in Mongolian sand source area conditions represent the primary factor behind the significant differences in SDW between the two periods.
2021,44(1): 39-49, DOI: 10.13878/j.cnki.dqkxxb.20201113007
Abstract:
The Arctic climate,an important component of the global climate system,has moved into a new state over the past 20 years.Scientific questions and possible consequences related to these changes are now front in the midst of many important issues that the world needs to deal with in the future.These changes,including prominent atmospheric and oceanic warming and sea ice melting have been largely attributed to a combined effect of anthropogenic forcing and internal variability of the climate system.This review highlights some findings from a number of studies conducted by my research group in the past few years.The studies collectively suggest that the high latitude atmospheric circulation that is sensitive to tropical SST forcing related to the interdecadal Pacific oscillation (IPO) plays a vital role in driving the interannual and interdecadal variability of Arctic sea ice by affecting the atmospheric temperature,moisture,clouds and radiative fluxes over sea ice.In particular,the teleconnection excited by a SST cooling over the tropical Pacific is suggested to cause an enhanced melting from 2007 to 2012.In addition,it suggests that a similar internal process may also play a role to cause strong sea ice melting in summer 2020.Furthermore,the model evaluation focusing on CMIP5 models finds that most climate models have a limitation to replicate this IPO-related teleconnection,raising awareness on an urgent need to investigate the cause of this bias in models.Thus,this review is meant to offer priorities for future Arctic research so that more efforts are targeted on critical scientific questions raised in this study.
The Arctic climate,an important component of the global climate system,has moved into a new state over the past 20 years.Scientific questions and possible consequences related to these changes are now front in the midst of many important issues that the world needs to deal with in the future.These changes,including prominent atmospheric and oceanic warming and sea ice melting have been largely attributed to a combined effect of anthropogenic forcing and internal variability of the climate system.This review highlights some findings from a number of studies conducted by my research group in the past few years.The studies collectively suggest that the high latitude atmospheric circulation that is sensitive to tropical SST forcing related to the interdecadal Pacific oscillation (IPO) plays a vital role in driving the interannual and interdecadal variability of Arctic sea ice by affecting the atmospheric temperature,moisture,clouds and radiative fluxes over sea ice.In particular,the teleconnection excited by a SST cooling over the tropical Pacific is suggested to cause an enhanced melting from 2007 to 2012.In addition,it suggests that a similar internal process may also play a role to cause strong sea ice melting in summer 2020.Furthermore,the model evaluation focusing on CMIP5 models finds that most climate models have a limitation to replicate this IPO-related teleconnection,raising awareness on an urgent need to investigate the cause of this bias in models.Thus,this review is meant to offer priorities for future Arctic research so that more efforts are targeted on critical scientific questions raised in this study.
2016,39(6): 722-734, DOI: 10.13878/j.cnki.dqkxxb.20161028003
Abstract:
The present paper has mainly analysed the process and mechanisms of genesis and development of the 2014-2016 mega El Niño event.It is shown that the entire lifecycle of the event is about 2 years(from April 2014 to May 2016),with four stages identified for its evolutive process:(1)Early and continuous westerly wind bursts(December 2013 to April 2014).The continuous three westerly wind burstsnot only changed the state of the easterly trade wind prevailing tropical central and easterly in the Pacific for long period of time,but also changed the cold water state in this region for the most recent 12 years,thus leading to SST rise and warming.Until early spring 2014,the SSTA exceeded 0.5℃,marking the possible occurrence of a new El Niño event.(2)Alternative weakening period(June 2014 to August 2015).Six westerly wind bursts continued to occur,thus maintaining and enhancing the warming of the equatorial central and eastern Pacific,while at the same time overcoming two periods of SST warming decrease or barrier,so that the initial development of El Niño was not aborted,and even changed into the stage of strong El Niño.Correspondingly,in the sub layer of the equatorial central and eastern Pacific,six warm Kelvin waves were observed to propagate eastward.The heat contents of these oceanic waves not only maintained the continuous warming in the equatorial central and eastern Pacific,but also caused El Niño to change from CP to EP type.(3)Peak period of development (September 2015 to February 2016).Two stronger westerly wind bursts were observed,which corresponded to very vigorous convective activity on the equatorial central and eastern Pacific.Rapid warming occurred in the Niño3.4 region,with 3℃observed in November 2015,classified as the mega-El Niño event.(4)Accelerating weakening stage(March to May 2016).The intensity of the El Niño rapidly weakened from 2 to 0.5℃ in the Niño3.4 region,then accelerated the transition to the cold water phase.In July to August 2016,the SSTA in the Niño3.4 region already approached -0.5℃.This rapid phase shift is a manifestation of the theory of delayed oscillation.From the above results,it is concluded that the development and shift of warm and cold phases is observationally consistent with the mechanism derived from the paradigm of the current theory of recharge oscillation and/or delayed oscillation theory.This clearly demonstrates that the results of the El Niño theory effectively underpin the development of related operational prediction.
The present paper has mainly analysed the process and mechanisms of genesis and development of the 2014-2016 mega El Niño event.It is shown that the entire lifecycle of the event is about 2 years(from April 2014 to May 2016),with four stages identified for its evolutive process:(1)Early and continuous westerly wind bursts(December 2013 to April 2014).The continuous three westerly wind burstsnot only changed the state of the easterly trade wind prevailing tropical central and easterly in the Pacific for long period of time,but also changed the cold water state in this region for the most recent 12 years,thus leading to SST rise and warming.Until early spring 2014,the SSTA exceeded 0.5℃,marking the possible occurrence of a new El Niño event.(2)Alternative weakening period(June 2014 to August 2015).Six westerly wind bursts continued to occur,thus maintaining and enhancing the warming of the equatorial central and eastern Pacific,while at the same time overcoming two periods of SST warming decrease or barrier,so that the initial development of El Niño was not aborted,and even changed into the stage of strong El Niño.Correspondingly,in the sub layer of the equatorial central and eastern Pacific,six warm Kelvin waves were observed to propagate eastward.The heat contents of these oceanic waves not only maintained the continuous warming in the equatorial central and eastern Pacific,but also caused El Niño to change from CP to EP type.(3)Peak period of development (September 2015 to February 2016).Two stronger westerly wind bursts were observed,which corresponded to very vigorous convective activity on the equatorial central and eastern Pacific.Rapid warming occurred in the Niño3.4 region,with 3℃observed in November 2015,classified as the mega-El Niño event.(4)Accelerating weakening stage(March to May 2016).The intensity of the El Niño rapidly weakened from 2 to 0.5℃ in the Niño3.4 region,then accelerated the transition to the cold water phase.In July to August 2016,the SSTA in the Niño3.4 region already approached -0.5℃.This rapid phase shift is a manifestation of the theory of delayed oscillation.From the above results,it is concluded that the development and shift of warm and cold phases is observationally consistent with the mechanism derived from the paradigm of the current theory of recharge oscillation and/or delayed oscillation theory.This clearly demonstrates that the results of the El Niño theory effectively underpin the development of related operational prediction.
2015,38(1): 27-36, DOI: 10.13878/j.cnki.dqkxxb.20130626001
Abstract:
The high-resolution numerical simulations of Hurricane Bonnie(1998) are used to analyze its intensity and structure changes in relation to its associated inertial stability under the influence of intense vertical wind shear during three different stages of its life cycle.Results show that Bonnie has high asymmetry and experiences an eyewall displacement cycle during its rapid intensifying stage.During its rapid structure change stage,the development of high inertial stability is consistent with the change in hurricane inner core size.The inertially stable region,which is usually present inside the eyewall,provides resistance to radial motions,and plays an important role in reducing the influence of vertical wind shear.The inertially stable region reduces the Rossby radius of deformation,and concentrates the latent heating,which is beneficial to the enhancing of the hurricane.This is an important factor in the development of inner core region of the hurricane.
The high-resolution numerical simulations of Hurricane Bonnie(1998) are used to analyze its intensity and structure changes in relation to its associated inertial stability under the influence of intense vertical wind shear during three different stages of its life cycle.Results show that Bonnie has high asymmetry and experiences an eyewall displacement cycle during its rapid intensifying stage.During its rapid structure change stage,the development of high inertial stability is consistent with the change in hurricane inner core size.The inertially stable region,which is usually present inside the eyewall,provides resistance to radial motions,and plays an important role in reducing the influence of vertical wind shear.The inertially stable region reduces the Rossby radius of deformation,and concentrates the latent heating,which is beneficial to the enhancing of the hurricane.This is an important factor in the development of inner core region of the hurricane.
JIANG Tong, ZHAI Jianqing, LUO Yong, SU Buda, CHAO Qingchen, WANG Yanjun, WANG Guojie, HUANG Jinlong, XU Runhong, GAO Miaoni, MIAO Lijuan
2022,45(4): 502-511, DOI: 10.13878/j.cnki.dqkxxb.20220529013
Abstract:
The second working group of the IPCC Sixth Assessment Report (IPCC AR6 WGⅡ) focuses on the impact,risk,adaptation and vulnerability of climate change.The report quantitatively assesses the impact of climate change on natural and human systems with the latest data,detailed evidence and diverse methods.Compared to AR5,the following progress has been made:Firstly,The content clarifies that the impact of climate change is attributable to three categories:anthropogenic climate forcing,non-climate factor action and weather sensitivity identification,127 key risks from climate change will become widespread or irreversible,and limiting global warming to 1.5 ℃ can greatly reduce climate change loss and damage to natural and human systems,pointing to the importance of adapting to transition.Secondly,AR6 WGⅡ adopts the latest combination of SSPs and RCPS in terms of evaluation method,which is more comprehensive.Thirdly,AR6 WGⅡ has focus on risks and solutions,and on the basis of AR5 WGⅡ,it is clarified that under different future warming scenarios,the risk level of the key risks facing the five “reasons for concern (RFCs)” will be relied on lower to very high levels of global warming.Finally,AR6 WGⅡ clarifies the urgency of climate action,combining adaptation and mitigation to support sustainable development is essential for climate resilience development pathways,pointing to the importance of immediate action to address climate risks.
The second working group of the IPCC Sixth Assessment Report (IPCC AR6 WGⅡ) focuses on the impact,risk,adaptation and vulnerability of climate change.The report quantitatively assesses the impact of climate change on natural and human systems with the latest data,detailed evidence and diverse methods.Compared to AR5,the following progress has been made:Firstly,The content clarifies that the impact of climate change is attributable to three categories:anthropogenic climate forcing,non-climate factor action and weather sensitivity identification,127 key risks from climate change will become widespread or irreversible,and limiting global warming to 1.5 ℃ can greatly reduce climate change loss and damage to natural and human systems,pointing to the importance of adapting to transition.Secondly,AR6 WGⅡ adopts the latest combination of SSPs and RCPS in terms of evaluation method,which is more comprehensive.Thirdly,AR6 WGⅡ has focus on risks and solutions,and on the basis of AR5 WGⅡ,it is clarified that under different future warming scenarios,the risk level of the key risks facing the five “reasons for concern (RFCs)” will be relied on lower to very high levels of global warming.Finally,AR6 WGⅡ clarifies the urgency of climate action,combining adaptation and mitigation to support sustainable development is essential for climate resilience development pathways,pointing to the importance of immediate action to address climate risks.
Abstract:
利用IAEA\WMO\GNIP的降水稳定同位素资料，分析了中国降水稳定同位素的时空分布特征及其影响因素。结果表明，整体来看我国降水稳定同位素有明显的大陆效应和高度效应。各地大气降水线存在地域差异，内陆地区同一站点冬、夏半年也有明显差异，显示出水汽团特性的不同。不同地区降水稳定同位素（δ和过量氘）的季节变化特征明显不同，表明主要水汽来源存在季节性差异。通过对比长序列降水稳定同位素的年际变化与季风和ENSO指数的关系，发现ENSO与降水稳定同位素有显著的正相关，但不一定通过影响降水量来引起降水稳定同位素（stable isotope in precipitation, SIP）的变化。重点分析了我国降水量效应、温度效应的特点，指出沿海和西南等季风区主要受降水量的影响，北方非季风区温度效应起主要作用，交叉地带则两种效应都有影响。
利用IAEA\WMO\GNIP的降水稳定同位素资料，分析了中国降水稳定同位素的时空分布特征及其影响因素。结果表明，整体来看我国降水稳定同位素有明显的大陆效应和高度效应。各地大气降水线存在地域差异，内陆地区同一站点冬、夏半年也有明显差异，显示出水汽团特性的不同。不同地区降水稳定同位素（δ和过量氘）的季节变化特征明显不同，表明主要水汽来源存在季节性差异。通过对比长序列降水稳定同位素的年际变化与季风和ENSO指数的关系，发现ENSO与降水稳定同位素有显著的正相关，但不一定通过影响降水量来引起降水稳定同位素（stable isotope in precipitation, SIP）的变化。重点分析了我国降水量效应、温度效应的特点，指出沿海和西南等季风区主要受降水量的影响，北方非季风区温度效应起主要作用，交叉地带则两种效应都有影响。
2020,43(4): 663-672, DOI: 10.13878/j.cnki.dqkxxb.20190330001
Abstract:
In this paper,using conventional observation data,NCEP 1°×1° reanalysis data,FY-2G satellite hourly TBB data,radar and AWS data,the potential and triggering characteristics of short-term heavy precipitation in southeastern Shanxi Province on the night of July 13,2018 were analyzed.The results reveal that the strong southwest airflow around subtropical high provide abundant water vapor conditions for the short-term heavy precipitation process.In addition,the stratification structure of "dry and cold under warm and wet" and the temperature differential advection of "high-level cold advection and low-level warm advection" provides the energy conditions required for the development of strong convection.The formation and maintenance of ascending motion are conducive to the release and enhancement of unstable energy.The meso-β scale convergence line on the ground develops into a meso-β scale vortex,thereby stimulating the consolidation and strengthening of the mid-β scale convective cloud mass,which in turn stimulates the merging and strengthening of meso-βscale convective clouds.The meso-γscale convective monomer embedded in the meso-βscale band echo of ≥ 35 dBZ,under the guidance of the 500 hPa southwest airflow,forms a slowly moving,highly organized multi-cell linear echo,which was the direct cause of the formation of short-duration heavy rainfall.The short-term heavy precipitation is located between 5 880 gpm and 5 840 gpm on the 500 hPa map,between the 850 hPa and 700 hPa shear line,and overlaps with 850 hPa and 700 hPa wet tongue,ground trunk line and mesoscale convergence line (near the 10 km range),as well as the cold air inflow side of the convective cloud mass TBB gradient high value area and TBB ≤ -60℃.
In this paper,using conventional observation data,NCEP 1°×1° reanalysis data,FY-2G satellite hourly TBB data,radar and AWS data,the potential and triggering characteristics of short-term heavy precipitation in southeastern Shanxi Province on the night of July 13,2018 were analyzed.The results reveal that the strong southwest airflow around subtropical high provide abundant water vapor conditions for the short-term heavy precipitation process.In addition,the stratification structure of "dry and cold under warm and wet" and the temperature differential advection of "high-level cold advection and low-level warm advection" provides the energy conditions required for the development of strong convection.The formation and maintenance of ascending motion are conducive to the release and enhancement of unstable energy.The meso-β scale convergence line on the ground develops into a meso-β scale vortex,thereby stimulating the consolidation and strengthening of the mid-β scale convective cloud mass,which in turn stimulates the merging and strengthening of meso-βscale convective clouds.The meso-γscale convective monomer embedded in the meso-βscale band echo of ≥ 35 dBZ,under the guidance of the 500 hPa southwest airflow,forms a slowly moving,highly organized multi-cell linear echo,which was the direct cause of the formation of short-duration heavy rainfall.The short-term heavy precipitation is located between 5 880 gpm and 5 840 gpm on the 500 hPa map,between the 850 hPa and 700 hPa shear line,and overlaps with 850 hPa and 700 hPa wet tongue,ground trunk line and mesoscale convergence line (near the 10 km range),as well as the cold air inflow side of the convective cloud mass TBB gradient high value area and TBB ≤ -60℃.
2014,37(5): 653-664, DOI: 10.13878/j.cnki.dqkxxb.20111230001
Abstract:
Studies have shown that large-scale monsoon gyre activity is closely associated with tropical cyclogenesis over the western North Pacific.In this study,two cases of monsoon gyre activities in 2002 and 2009 were first examined.It was found that a monsoon gyre can be linked to the formation of one or more tropical cyclones,which usually occur near or to the east of the gyre center.Further analysis of the monsoon gyre activity during the period of 2000—2009 indicates that tropical cyclogenesis mainly occurs near or to the east of the gyre center,although the definition of a monsoon gyre depends on its duration and the circulation intensity.It is suggested that the tropical cyclogensis may be associated with the Rossby wave energy dispersion of monsoon gyres.
Studies have shown that large-scale monsoon gyre activity is closely associated with tropical cyclogenesis over the western North Pacific.In this study,two cases of monsoon gyre activities in 2002 and 2009 were first examined.It was found that a monsoon gyre can be linked to the formation of one or more tropical cyclones,which usually occur near or to the east of the gyre center.Further analysis of the monsoon gyre activity during the period of 2000—2009 indicates that tropical cyclogenesis mainly occurs near or to the east of the gyre center,although the definition of a monsoon gyre depends on its duration and the circulation intensity.It is suggested that the tropical cyclogensis may be associated with the Rossby wave energy dispersion of monsoon gyres.
Abstract:
A new atmospheric correction algorithm based on dark object method and the look up table developed from MODTRAN model was introduced for Landsat images in the paper.The infomation of the satellite remote sensing images was used to support the atmospheric correction.The algorithm was applied to the Landsat ETM+imagery and comparisons show that the influence on Landsat imagery caused by molecules,water vapor,ozone,and aerosol particles in the atmosphere was effectively reduced after the correction.The surface reflectivity was more precisely,which is beneficial for remote sensing information extraction and thematic interpretation.
A new atmospheric correction algorithm based on dark object method and the look up table developed from MODTRAN model was introduced for Landsat images in the paper.The infomation of the satellite remote sensing images was used to support the atmospheric correction.The algorithm was applied to the Landsat ETM+imagery and comparisons show that the influence on Landsat imagery caused by molecules,water vapor,ozone,and aerosol particles in the atmosphere was effectively reduced after the correction.The surface reflectivity was more precisely,which is beneficial for remote sensing information extraction and thematic interpretation.
Abstract:
超级单体风暴常伴随着冰雹、雷雨大风等强对流天气，最本质的特征是有一持久深厚的几千米尺度的涡旋———中气旋。利用2003-2009年福建龙岩新一代天气雷达观测到的32次超级单体风暴，分析了超级单体风暴中气旋的时空分布、结构特征以及旋转速度大小、中气旋顶和底的高度、伸长厚度以及切变值等特征量。结果表明：90%以上的超级单体中尺度气旋是与冰雹、雷雨大风、短时强降水等强对流天气相联系的。统计8次有详细灾情的雷雨大风或冰雹天气过程发现，中气旋强度不断加强，中气旋厚度加大，最强切变中心突降时将产生大风或冰雹等强对流天气
超级单体风暴常伴随着冰雹、雷雨大风等强对流天气，最本质的特征是有一持久深厚的几千米尺度的涡旋———中气旋。利用2003-2009年福建龙岩新一代天气雷达观测到的32次超级单体风暴，分析了超级单体风暴中气旋的时空分布、结构特征以及旋转速度大小、中气旋顶和底的高度、伸长厚度以及切变值等特征量。结果表明：90%以上的超级单体中尺度气旋是与冰雹、雷雨大风、短时强降水等强对流天气相联系的。统计8次有详细灾情的雷雨大风或冰雹天气过程发现，中气旋强度不断加强，中气旋厚度加大，最强切变中心突降时将产生大风或冰雹等强对流天气
2015,38(2): 184-194, DOI: 10.13878/j.cnki.dqkxxb.20140508002
Abstract:
The observed SST data and CMIP5 data are used to analyze climate state and interdecadal variation of sea surface temperature(SST) over Northwest Pacific(20—60°N,120°E—120°W).Results indicate that the selected 22 models can simulate the climate state perfectly.More importantly,the selected models can simulate the annual and interdecadal variations of SST over Northwest Pacific.Total standard deviation of SST simulted by the models is the largest in Kuroshio extension region.The majority of models have an ability to simulate the first EOF mode of SST.The SST over Northwest Pacific has a significant interdecadal oscillation phenomenon.SSTs simulated by the 13/22 models have obvious interdecadal oscillations.Meanwhile,the simulated deviation of SST climate state has a great effect on the periodic oscillation of SST,especially in Kuroshio extension region.
The observed SST data and CMIP5 data are used to analyze climate state and interdecadal variation of sea surface temperature(SST) over Northwest Pacific(20—60°N,120°E—120°W).Results indicate that the selected 22 models can simulate the climate state perfectly.More importantly,the selected models can simulate the annual and interdecadal variations of SST over Northwest Pacific.Total standard deviation of SST simulted by the models is the largest in Kuroshio extension region.The majority of models have an ability to simulate the first EOF mode of SST.The SST over Northwest Pacific has a significant interdecadal oscillation phenomenon.SSTs simulated by the 13/22 models have obvious interdecadal oscillations.Meanwhile,the simulated deviation of SST climate state has a great effect on the periodic oscillation of SST,especially in Kuroshio extension region.
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- 1CMIP5 projected changes in mean and extreme climate in the Belt and Road region
- 2APPLICATION OF WAVELET TRANSFORMATION TO ANALYSIS OF MULTIPLE TIME SCALE CLIMATE CHANGE
- 3Major Achievements in Meteorology in Ancient China
- 4The impact of the Himalayan-Tibet Plateau on the monsoon region
- 5Discussion on calculation method of flowering date meeting of hybrid rice parents
- 6Quality assessment of hourly merged precipitation product over China
- 7The differences in characteristics and applicability among three types of Rossby wave activity flux in atmospheric dynamics
- 8
- 9Analysis and comparison of four kinds of circulation indices of Aleutian Low
- 10A review on multi-scale drought processes and prediction under global change
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