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2024,47(4): 521-532, DOI: 10.13878/j.cnki.dqkxxb.20240319001
Abstract:
El Niño significantly influences precipitation in eastern China,and it has been demonstrated that the diversity of El Niño characteristics leads to inconsistent impacts.Traditional identification of El Niño diversity focuses only on difference in spatial distributions of anomalous features,overlooking the temporal discrepancies among types.This leaves it unclear whether these time-scale differences change El Niño's influence.Therefore,utilizing high-resolution grid data of precipitation in China from 1961 to 2022,this study revisited the El Niño influence on precipitation in eastern China based on a newly proposed classification method that considers both spatial and temporal characteristics.We identified historical El Niño events into two primary spatiotemporal types:the low-frequency eastern-Pacific (LF-EP) type,characterized by a long lifecycle and located in the tropical eastern Pacific,and the quasi-biennial central-Pacific (QB-CP) type,with a shorter lifecycle and located relatively west.In the evolution of LF-EP-type events,the LF mode is dominant,while the QB mode is relatively weak.In QB-CP-type events,the LF mode is in the phase transition stage,while the QB mode is dominant.Composite analysis results indicate these two different spatiotemporal types of El Niño have distinct impacts on the evolution of precipitation anomalies in eastern China.LF-EP-type events have a stable influence on precipitation in eastern China,with a nearly four-season-lasting anomaly starting from autumn of the development year to summer of the decay year,resulting in above-normal rainfall south of the Yangtze River.Moreover,the center of the anomalous rain belt migrates northward starting in the spring of development year.In contrast,QB-CP-type events exhibit more frequent changes in precipitation anomaly characteristics.During summer and autumn of the development year,rainfall is generally less south of the Yangtze River,contrary to LF-EP-type events.Positive precipitation anomalies begin to emerge south of the Yangtze River in winter and show a gradual southward retreat,culminating in a “positive-negative-positive” distribution across North China,the Yangtze River basin,and South China by the decay year's summer.
This study also compared large-scale moisture transport differences between the two spatiotemporal types of El Niño to investigate the potential mechanisms behind their differing impacts.The results show that the difference in the zonal positioning of SST anomalies is a key factor leading to distinct atmospheric circulation responses.Due to the shift in the latitudinal position of SST and convective anomalies,the positions of anticyclonic circulation anomalies in the Northwest Pacific Ocean vary among different types of El Niño in summer and autumn,resulting in different moisture transports towards eastern China.In winter,the different types of El Niño induce a similar anomalous Walker circulation,whose sinking branch in the maritime continent region leads to relatively consistent anticyclonic water vapor transport towards eastern China.However,the related circulation anomaly dominated by the LF ENSO mode persists significantly longer due to its longer lifecycle.That is to say,the differences in persistence and phase transition timing between the two types of spatiotemporal events result in changes in the timescale of their impact on precipitation in eastern China.Additionally,during the spring and summer of the decay year,LF-EP El Niño can also indirectly develop anticyclonic water vapor transport in the Northwest Pacific to maintain its influence on precipitation in eastern China through the Indo-western Pacific Ocean “capacitor” effect and through the nonlinear interaction with the tropical Pacific annual cycle.
El Niño significantly influences precipitation in eastern China,and it has been demonstrated that the diversity of El Niño characteristics leads to inconsistent impacts.Traditional identification of El Niño diversity focuses only on difference in spatial distributions of anomalous features,overlooking the temporal discrepancies among types.This leaves it unclear whether these time-scale differences change El Niño's influence.Therefore,utilizing high-resolution grid data of precipitation in China from 1961 to 2022,this study revisited the El Niño influence on precipitation in eastern China based on a newly proposed classification method that considers both spatial and temporal characteristics.We identified historical El Niño events into two primary spatiotemporal types:the low-frequency eastern-Pacific (LF-EP) type,characterized by a long lifecycle and located in the tropical eastern Pacific,and the quasi-biennial central-Pacific (QB-CP) type,with a shorter lifecycle and located relatively west.In the evolution of LF-EP-type events,the LF mode is dominant,while the QB mode is relatively weak.In QB-CP-type events,the LF mode is in the phase transition stage,while the QB mode is dominant.Composite analysis results indicate these two different spatiotemporal types of El Niño have distinct impacts on the evolution of precipitation anomalies in eastern China.LF-EP-type events have a stable influence on precipitation in eastern China,with a nearly four-season-lasting anomaly starting from autumn of the development year to summer of the decay year,resulting in above-normal rainfall south of the Yangtze River.Moreover,the center of the anomalous rain belt migrates northward starting in the spring of development year.In contrast,QB-CP-type events exhibit more frequent changes in precipitation anomaly characteristics.During summer and autumn of the development year,rainfall is generally less south of the Yangtze River,contrary to LF-EP-type events.Positive precipitation anomalies begin to emerge south of the Yangtze River in winter and show a gradual southward retreat,culminating in a “positive-negative-positive” distribution across North China,the Yangtze River basin,and South China by the decay year's summer.
This study also compared large-scale moisture transport differences between the two spatiotemporal types of El Niño to investigate the potential mechanisms behind their differing impacts.The results show that the difference in the zonal positioning of SST anomalies is a key factor leading to distinct atmospheric circulation responses.Due to the shift in the latitudinal position of SST and convective anomalies,the positions of anticyclonic circulation anomalies in the Northwest Pacific Ocean vary among different types of El Niño in summer and autumn,resulting in different moisture transports towards eastern China.In winter,the different types of El Niño induce a similar anomalous Walker circulation,whose sinking branch in the maritime continent region leads to relatively consistent anticyclonic water vapor transport towards eastern China.However,the related circulation anomaly dominated by the LF ENSO mode persists significantly longer due to its longer lifecycle.That is to say,the differences in persistence and phase transition timing between the two types of spatiotemporal events result in changes in the timescale of their impact on precipitation in eastern China.Additionally,during the spring and summer of the decay year,LF-EP El Niño can also indirectly develop anticyclonic water vapor transport in the Northwest Pacific to maintain its influence on precipitation in eastern China through the Indo-western Pacific Ocean “capacitor” effect and through the nonlinear interaction with the tropical Pacific annual cycle.
2024,47(4): 533-540, DOI: 10.13878/j.cnki.dqkxxb.20240107009
Abstract:
Drought poses a significant threat to economic and agricultural development,impacting physical health and daily life.With global warming,heatwaves,and droughts,extreme events are occurring with increasing frequency,exacerbating disaster risks.The middle-lower Yangtze Plain,one of China's most densely populated,economically developed,urbanized regions,experienced the most severe heatwave and drought-compound extreme event since 1961 in 2022.This event significantly impacted energy supply,agricultural production,and the ecosystem.This study analyzes precipitation and evaporation characteristics during the flood season from 2000 to 2022,exploring the mechanism and evolution of the 2022 extreme drought event in the middle-lower Yangtze Plain.A comparison with the high-temperature and drought events in 2013 provides a deeper understanding of the relationship between high temperatures and extreme drought in this region.The hydrological drought index,net precipitation(precipitation minus evapotranspiration,P-E) is used to analyze the drought conditions.Using ERA5 and ERA5-LAND reanalysis data,changes in P-E are decomposed into dynamic,thermodynamic,and transient eddy componentsby analyzing the moisture flux budget.Surface temperature during the 2022 flood season increased by nearly 1 ℃ compared to the 20-year average(2000—2019),with temperatures rising over 2 ℃ from July to August.Precipitation during the flood season decreased by 37％ and by 45％ from July to August,respectively,compared to the average for the same period.Net precipitation analysis indicates that the drought was primarily caused by decreased precipitation in the early flood season(May—June) of 2022.Moisture flux budget decomposition shows that changes in transient eddy and mean circulation were major contributorsto the early drought.In the mid-period(July—August),high temperatures enhanced surface evapotranspiration,especially in bare soil,worsening the drought.The thermodynamic contributionfrom increased specific humidity,driven by temperature rise,was the greatest factorin drought intensification.In the later period(September-October),high temperatures further altered the average circulation,with the dynamic component extending the drought duration.In contrast,the 2013 high-temperature and drought event was initially dominated by thermodynamic contributions,with mean circulation and transient eddy changes intensifying the mid-period droughtand only thermodynamic contributions remaining later,resulting in shorter duration and weaker drought severity.This analysis of the 2022 heatwave and drought compound extreme event development and evolution in the middle-lower Yangtze Plain provides a reference for predicting and warning about high-temperature and drought extreme events in humid areas.In-depth research on these development and evolution events can improve regional drought event prediction and duration forecasting.
Drought poses a significant threat to economic and agricultural development,impacting physical health and daily life.With global warming,heatwaves,and droughts,extreme events are occurring with increasing frequency,exacerbating disaster risks.The middle-lower Yangtze Plain,one of China's most densely populated,economically developed,urbanized regions,experienced the most severe heatwave and drought-compound extreme event since 1961 in 2022.This event significantly impacted energy supply,agricultural production,and the ecosystem.This study analyzes precipitation and evaporation characteristics during the flood season from 2000 to 2022,exploring the mechanism and evolution of the 2022 extreme drought event in the middle-lower Yangtze Plain.A comparison with the high-temperature and drought events in 2013 provides a deeper understanding of the relationship between high temperatures and extreme drought in this region.The hydrological drought index,net precipitation(precipitation minus evapotranspiration,P-E) is used to analyze the drought conditions.Using ERA5 and ERA5-LAND reanalysis data,changes in P-E are decomposed into dynamic,thermodynamic,and transient eddy componentsby analyzing the moisture flux budget.Surface temperature during the 2022 flood season increased by nearly 1 ℃ compared to the 20-year average(2000—2019),with temperatures rising over 2 ℃ from July to August.Precipitation during the flood season decreased by 37％ and by 45％ from July to August,respectively,compared to the average for the same period.Net precipitation analysis indicates that the drought was primarily caused by decreased precipitation in the early flood season(May—June) of 2022.Moisture flux budget decomposition shows that changes in transient eddy and mean circulation were major contributorsto the early drought.In the mid-period(July—August),high temperatures enhanced surface evapotranspiration,especially in bare soil,worsening the drought.The thermodynamic contributionfrom increased specific humidity,driven by temperature rise,was the greatest factorin drought intensification.In the later period(September-October),high temperatures further altered the average circulation,with the dynamic component extending the drought duration.In contrast,the 2013 high-temperature and drought event was initially dominated by thermodynamic contributions,with mean circulation and transient eddy changes intensifying the mid-period droughtand only thermodynamic contributions remaining later,resulting in shorter duration and weaker drought severity.This analysis of the 2022 heatwave and drought compound extreme event development and evolution in the middle-lower Yangtze Plain provides a reference for predicting and warning about high-temperature and drought extreme events in humid areas.In-depth research on these development and evolution events can improve regional drought event prediction and duration forecasting.
2024,47(4): 541-556, DOI: 10.13878/j.cnki.dqkxxb.20230910002
Abstract:
In July-August 2021,the evolution of the rain belt in eastern China deviated significantly from the typical northward progression of the climatological monsoon.The center of positive precipitation anomalies was located in Jianghuai-North China region in July and shifted southward to the Central China region in August.These regions experienced the highest and second-highest average precipitation anomalies on record since 1979,respectively.The inter-month differences in precipitation anomalies were primarily associated with the northeast (southwest) displacement of the western Pacific subtropical high (WPSH),the northward (southward) shift of the East Asian subtropical westerly jet,and the continuous eastward extension of the South Asia high (SAH) in July (August) 2021.The active tropical convection and enhanced warming of the North Atlantic Ocean were key factors influencing the southward shift of the precipitation center.In July 2021,the Madden-Julian Oscillation (MJO) was active over the Maritime Continent,intensifying tropical convection and triggering the northward propagation of a Pacific-Japan-like wave train.This caused the WPSH to shift northeastward,promoting water vapor convergence in the Jianghuai-North China region and resulting in increased precipitation.In August,the MJO reactivation over the tropical Indian Ocean strengthened local meridional circulation,leading to anomalous downward motion from southern China to the northwest Pacific Ocean.This favored the southward and westward extensions of the WPSH.Additionally,anomalously warm North Atlantic Sea surface temperature (SST) in August 2021 simulated the southeastward propagation of Rossby waves in the upper troposphere,intensifying the SAH and causing the East Asian subtropical westerly jet to strengthen and shift southward.Consequently,warm and moist air from the tropical western Pacific converged in Central China,shifting the precipitation center southward in August.The Climate Forecast System,version 2 (CFSv2,reported in June),accurately predicted positive precipitation anomalies for July 2021 in most parts of the Jianghuai-North China.However,it incorrectly predicted negative precipitation anomalies for August in southern China.The model successfully reproduced the northward movement of the WPSH and the influence of tropical convective activity on the Maritime Continent during July precipitation in the Jianghuai-North China.However,it failed to predict the effects of tropical Indian Ocean convection and anomalously warm North Atlantic SSTs in August 2021.Consequently,the model could not replicate the southward and strengthened deviation of the East Asian subtropical westerly jet or the intensified and eastward deviation of the SAH,leading to inaccurate precipitation predictions for Central China in August.The extreme precipitation anomalies in eastern China during midsummer 2021 were significantly influenced by the frequency and intensity of typhoons.Additionally,the predictive efficiency of dynamic models for the inter-monthly evolution of midsummer precipitation was limited.Developing an effective prediction model that integrates dynamic and statistical approaches is necessary to improve monthly-to-seasonal climate predictions in the future.
In July-August 2021,the evolution of the rain belt in eastern China deviated significantly from the typical northward progression of the climatological monsoon.The center of positive precipitation anomalies was located in Jianghuai-North China region in July and shifted southward to the Central China region in August.These regions experienced the highest and second-highest average precipitation anomalies on record since 1979,respectively.The inter-month differences in precipitation anomalies were primarily associated with the northeast (southwest) displacement of the western Pacific subtropical high (WPSH),the northward (southward) shift of the East Asian subtropical westerly jet,and the continuous eastward extension of the South Asia high (SAH) in July (August) 2021.The active tropical convection and enhanced warming of the North Atlantic Ocean were key factors influencing the southward shift of the precipitation center.In July 2021,the Madden-Julian Oscillation (MJO) was active over the Maritime Continent,intensifying tropical convection and triggering the northward propagation of a Pacific-Japan-like wave train.This caused the WPSH to shift northeastward,promoting water vapor convergence in the Jianghuai-North China region and resulting in increased precipitation.In August,the MJO reactivation over the tropical Indian Ocean strengthened local meridional circulation,leading to anomalous downward motion from southern China to the northwest Pacific Ocean.This favored the southward and westward extensions of the WPSH.Additionally,anomalously warm North Atlantic Sea surface temperature (SST) in August 2021 simulated the southeastward propagation of Rossby waves in the upper troposphere,intensifying the SAH and causing the East Asian subtropical westerly jet to strengthen and shift southward.Consequently,warm and moist air from the tropical western Pacific converged in Central China,shifting the precipitation center southward in August.The Climate Forecast System,version 2 (CFSv2,reported in June),accurately predicted positive precipitation anomalies for July 2021 in most parts of the Jianghuai-North China.However,it incorrectly predicted negative precipitation anomalies for August in southern China.The model successfully reproduced the northward movement of the WPSH and the influence of tropical convective activity on the Maritime Continent during July precipitation in the Jianghuai-North China.However,it failed to predict the effects of tropical Indian Ocean convection and anomalously warm North Atlantic SSTs in August 2021.Consequently,the model could not replicate the southward and strengthened deviation of the East Asian subtropical westerly jet or the intensified and eastward deviation of the SAH,leading to inaccurate precipitation predictions for Central China in August.The extreme precipitation anomalies in eastern China during midsummer 2021 were significantly influenced by the frequency and intensity of typhoons.Additionally,the predictive efficiency of dynamic models for the inter-monthly evolution of midsummer precipitation was limited.Developing an effective prediction model that integrates dynamic and statistical approaches is necessary to improve monthly-to-seasonal climate predictions in the future.
2024,47(4): 557-569, DOI: 10.13878/j.cnki.dqkxxb.20230911002
Abstract:
The lower reaches of the Yangtze River (28°—33°N,116°—123°E) are economically developed and prone to frequent summer (June-August) flooding disasters.Studying the variability of summer precipitation in this region is of great significance.In recent decades,summer precipitation in this area has increased significantly.This study quantitatively analyzes the factors influencing this trend using precipitation term decomposition,based on observed summer precipitation from 1961 to 2020,TC best track datasets,and hourly mean reanalysis data from the European Centre for Medium-Range Weather Forecasts Reanalysis Version 5 (ERA5).The results show that:(1) From 1961 to 2020,the average annual precipitation increase reaches 3.54 mm/year (passing the 95％ significance test),with a growth rate of 38.1％.The variance contribution of the linear trend accounts for 20.7％ of the total variance of summer precipitation.The increasing trend of daily precipitation reached 0.04 mm/day (passing the 95％ significance test),which is the primary for the significant increase in summer precipitation in this region.(2) Precipitation term decomposition reveals that the variability of summer precipitation is influenced by vertical velocity,horizontal motion,water vapor,and evaporation.Among these,significant upward trends in water vapor and vertical velocity contribute to the increase in daily precipitation by 0.039 mm/day (passing the 99％ significance test) and 0.019 mm/day (passing the 95％ significance test),respectively.This is primarily related to the increased vertical gradient of water vapor and the enhancement of vertical rise velocity.(3) The temperature of the lower atmosphere has risen due to the ground warming,while the upper atmosphere has cooled due to the phase change of the Asia-Pacific Oscillation (from a positive phase to a negative phase).The ability of the atmosphere to retain moisture is directly proportional to temperature.The intensified temperature difference between the upper and lower levels of the atmosphere increases the vertical gradient of water vapor,providing abundant moisture for increased precipitation.Additionally,abnormal positive vorticity in the upper atmosphere (200 hPa) and abnormal negative vorticity in the lower atmosphere (850 hPa) indicate that large-scale circulation does not favor the strengthening of upward motion.However,the anomalous convergence in the lower atmosphere,combined with increased instability energy due to mesoscale system variations,offers favorable dynamic and thermodynamic conditions for enhanced vertical rise velocity and increased convective precipitation in the summer.Previous studies have lacked quantitative analysis of the dynamic and thermodynamic factors affecting summer precipitation trends in the lower reaches of the Yangtze River.This paper quantifies the contributions of water vapor and vertical velocity variability to the summer precipitation trend,providing a theoretical basis for understanding precipitation changes in the context of global warming.
The lower reaches of the Yangtze River (28°—33°N,116°—123°E) are economically developed and prone to frequent summer (June-August) flooding disasters.Studying the variability of summer precipitation in this region is of great significance.In recent decades,summer precipitation in this area has increased significantly.This study quantitatively analyzes the factors influencing this trend using precipitation term decomposition,based on observed summer precipitation from 1961 to 2020,TC best track datasets,and hourly mean reanalysis data from the European Centre for Medium-Range Weather Forecasts Reanalysis Version 5 (ERA5).The results show that:(1) From 1961 to 2020,the average annual precipitation increase reaches 3.54 mm/year (passing the 95％ significance test),with a growth rate of 38.1％.The variance contribution of the linear trend accounts for 20.7％ of the total variance of summer precipitation.The increasing trend of daily precipitation reached 0.04 mm/day (passing the 95％ significance test),which is the primary for the significant increase in summer precipitation in this region.(2) Precipitation term decomposition reveals that the variability of summer precipitation is influenced by vertical velocity,horizontal motion,water vapor,and evaporation.Among these,significant upward trends in water vapor and vertical velocity contribute to the increase in daily precipitation by 0.039 mm/day (passing the 99％ significance test) and 0.019 mm/day (passing the 95％ significance test),respectively.This is primarily related to the increased vertical gradient of water vapor and the enhancement of vertical rise velocity.(3) The temperature of the lower atmosphere has risen due to the ground warming,while the upper atmosphere has cooled due to the phase change of the Asia-Pacific Oscillation (from a positive phase to a negative phase).The ability of the atmosphere to retain moisture is directly proportional to temperature.The intensified temperature difference between the upper and lower levels of the atmosphere increases the vertical gradient of water vapor,providing abundant moisture for increased precipitation.Additionally,abnormal positive vorticity in the upper atmosphere (200 hPa) and abnormal negative vorticity in the lower atmosphere (850 hPa) indicate that large-scale circulation does not favor the strengthening of upward motion.However,the anomalous convergence in the lower atmosphere,combined with increased instability energy due to mesoscale system variations,offers favorable dynamic and thermodynamic conditions for enhanced vertical rise velocity and increased convective precipitation in the summer.Previous studies have lacked quantitative analysis of the dynamic and thermodynamic factors affecting summer precipitation trends in the lower reaches of the Yangtze River.This paper quantifies the contributions of water vapor and vertical velocity variability to the summer precipitation trend,providing a theoretical basis for understanding precipitation changes in the context of global warming.
2024,47(4): 570-580, DOI: 10.13878/j.cnki.dqkxxb.20230518003
Abstract:
The interaction between mid-high latitudes in the atmosphere of the Northern and Southern Hemispheres is closely related to cross-hemisphere weather and climate systems,such as monsoons.Due to the involvement of large-scale circulation and global energy changes,the correlation pathway and mechanism have garnered extensive attention from scholars.The inter-hemispheric air mass oscillation (IHO) index is defined as the difference in atmospheric mass between the Northern and Southern Hemispheres,reflecting changes in global atmospheric circulation caused by the exchange of atmospheric mass between the hemispheres.Using ERA5 reanalysis data post-1979,the winter IHO showed a significant positive correlation with the East Asian winter monsoon anomaly (correlation coefficient r=0.49).The historical output data of the CMIP6 models further verified this relationship,showing a positive correlation in 96.7％ of the models,with a correlation coefficient of 0.35 in the MPI-ESM1-2-HR model,statistically significant at the 95％ confidence level.Using ERA5 reanalysis data and the historical experimental data of the MPI-ESM1-2-HR model,we verified the influence of IHO anomalies on the interannual variation of the East Asian winter monsoon and the underlying physical processes.The results indicate that the IHO is closely related to the East Asian winter monsoon through the redistribution of global air mass.During a positive IHO phase,atmospheric mass accumulates abnormally deposited in northern Eurasia and decreases in the middle and low latitudes,significantly increasing the sea-land pressure difference in East Asia and strengthening winter winds,and vice versa.Additionally,the combined difference in surface pressure between high and low IHO years shows that the Antarctic air mass anomaly contributes most of the negative anomalies in the Southern Hemisphere,indicating that the Antarctic air mass oscillation is the main driver of the North-South air mass oscillation.In the MPI-ESM1-2-HR model,the IHO significantly impacts winter surface air temperature in China,particularly in Central China,with a correlation coefficient of -0.29 between winter surface air temperature and the IHO index in Central China.Analysis of the MPI-ESM1-2-HR model reveals that the correlation coefficient between the IHO and the average temperature of the upper troposphere in the Antarctic region is -0.32 (passing the 90％ significance test),indicating that the temperature of the upper troposphere in the Antarctic region significantly drives the interannual variation of the IHO.Ozone is identified as the primary factor affecting temperature changes in the Antarctic region.The mean temperature of the upper troposphere and ozone content in the Antarctic region are significantly positively correlated (r=0.33,passing the 95％ significance test),indicating that ozone changes play a dominant role in the temperature of the Antarctic troposphere.The temperature in the upper Antarctic troposphere is inversely correlated with that in the lower stratosphere of the equator (10°S—10°N) at 100—70 hPa,with a correlation coefficient of -0.38 (passing the 95％ significance test).This suggests that the temperature at the bottom of the tropical stratosphere influences the temperature of the Antarctic troposphere through residual circulation,regulating the interannual oscillation of the Antarctic air mass and causing the imbalance between the hemispheres.When the tropical stratosphere temperature rises,the ozone and temperature in the upper Antarctic troposphere decrease,leading to significant negative temperatures and geopotential anomalies over Antarctica.The decrease in air temperature over Antarctica reduces internal energy,increases the polar vortex,and contracts the atmospheric column,reducing total energy and atmospheric mass in the Antarctic region,thereby increasing the atmospheric mass difference between the hemispheres,and vice versa.
The interaction between mid-high latitudes in the atmosphere of the Northern and Southern Hemispheres is closely related to cross-hemisphere weather and climate systems,such as monsoons.Due to the involvement of large-scale circulation and global energy changes,the correlation pathway and mechanism have garnered extensive attention from scholars.The inter-hemispheric air mass oscillation (IHO) index is defined as the difference in atmospheric mass between the Northern and Southern Hemispheres,reflecting changes in global atmospheric circulation caused by the exchange of atmospheric mass between the hemispheres.Using ERA5 reanalysis data post-1979,the winter IHO showed a significant positive correlation with the East Asian winter monsoon anomaly (correlation coefficient r=0.49).The historical output data of the CMIP6 models further verified this relationship,showing a positive correlation in 96.7％ of the models,with a correlation coefficient of 0.35 in the MPI-ESM1-2-HR model,statistically significant at the 95％ confidence level.Using ERA5 reanalysis data and the historical experimental data of the MPI-ESM1-2-HR model,we verified the influence of IHO anomalies on the interannual variation of the East Asian winter monsoon and the underlying physical processes.The results indicate that the IHO is closely related to the East Asian winter monsoon through the redistribution of global air mass.During a positive IHO phase,atmospheric mass accumulates abnormally deposited in northern Eurasia and decreases in the middle and low latitudes,significantly increasing the sea-land pressure difference in East Asia and strengthening winter winds,and vice versa.Additionally,the combined difference in surface pressure between high and low IHO years shows that the Antarctic air mass anomaly contributes most of the negative anomalies in the Southern Hemisphere,indicating that the Antarctic air mass oscillation is the main driver of the North-South air mass oscillation.In the MPI-ESM1-2-HR model,the IHO significantly impacts winter surface air temperature in China,particularly in Central China,with a correlation coefficient of -0.29 between winter surface air temperature and the IHO index in Central China.Analysis of the MPI-ESM1-2-HR model reveals that the correlation coefficient between the IHO and the average temperature of the upper troposphere in the Antarctic region is -0.32 (passing the 90％ significance test),indicating that the temperature of the upper troposphere in the Antarctic region significantly drives the interannual variation of the IHO.Ozone is identified as the primary factor affecting temperature changes in the Antarctic region.The mean temperature of the upper troposphere and ozone content in the Antarctic region are significantly positively correlated (r=0.33,passing the 95％ significance test),indicating that ozone changes play a dominant role in the temperature of the Antarctic troposphere.The temperature in the upper Antarctic troposphere is inversely correlated with that in the lower stratosphere of the equator (10°S—10°N) at 100—70 hPa,with a correlation coefficient of -0.38 (passing the 95％ significance test).This suggests that the temperature at the bottom of the tropical stratosphere influences the temperature of the Antarctic troposphere through residual circulation,regulating the interannual oscillation of the Antarctic air mass and causing the imbalance between the hemispheres.When the tropical stratosphere temperature rises,the ozone and temperature in the upper Antarctic troposphere decrease,leading to significant negative temperatures and geopotential anomalies over Antarctica.The decrease in air temperature over Antarctica reduces internal energy,increases the polar vortex,and contracts the atmospheric column,reducing total energy and atmospheric mass in the Antarctic region,thereby increasing the atmospheric mass difference between the hemispheres,and vice versa.
2024,47(4): 581-591, DOI: 10.13878/j.cnki.dqkxxb.20230106001
Abstract:
In the context of global warming and rapid urbanization,Beijing,as the capital city,has undergone significant transformations in its urban landscape.These changes have brought about persistent environmental issues,particularly the urban heat island (UHI) effect.Based on daily temperature observation data from 1981 to 2020 collected from both urban and suburban stations in Beijing,this study employs methods such as linear regression,kriging interpolation,and correlation analysis to investigate the temperature change trends on monthly,seasonal,and annual scales over the past 40 years.Additionally,it explores the spatiotemporal characteristics of UHI intensity in Beijing and assesses the impact of various factors,including meteorological elements (such as extreme maximum temperatures and average wind speed),population density,and land use/cover types,on the UHI effect,ultimately revealing the underlying causes of Beijing's UHI phenomenon.The findings indicate that the temperature trends in both urban and suburban areas of Beijing have been consistent over the past four decades,with an overall upward trajectory.Notably,the temperature increase in urban areas has been more pronounced than in suburban areas,with UHI increasing at a “wave-like” rate of 0.1 ℃/(10 a) highlighting a significant upward trend in Beijing's UHI.Analyzing by seasons,the UHI effect in Beijing is most pronounced in winter,with an average intensity of 1.22 ℃,followed by autumn,while spring and summer exhibit the weakest UHI effect.Among these,the increase in UHI during autumn is the most significant,with a change rate of 0.13 ℃/(10 a).From a spatial perspective,the UHI effect in Beijing is expanding.The high-value UHI areas are concentrated in the six central urban districts.The UHI zone extends from the northwest towards the southeast,reaching the sub-center in Tongzhou district.The warming trend is particularly evident in Chaoyang and Tongzhou districts.Since the year 2000,there has been a noticeable increase in the winter UHI intensity in Beijing,with high-value areas in the Tongzhou sub-center seeing UHI intensities rising to 1.6 ℃.Furthermore,principal component analysis reveals that population density,construction land,and average atmospheric pressure are key factors promoting the formation of the UHI effect.Conversely,wind speed and cultivated land play crucial roles in mitigating the UHI effect.As the process of urbanization accelerates,balancing urban development with environmental ecology becomes a crucial aspect of urban planning.Effective measures to control the UHI effect include regulating population density,rationally planning urban land use in terms of scale,structure,and spatial layout,and increasing the area of green vegetation and other ecological lands to alleviate the UHI impact.By implementing such strategies,Beijing can mitigate the adverse effects of the UHI phenomenon and enhance the overall quality of life for its residents.In summary,addressing Beijing's UHI effect requires a comprehensive approach that involves controlling population density,strategically planning urban land use,and enhancing ecological conservation efforts.These measures aim to reduce the spread of the UHI effect and promote a sustainable urban environment,ultimately improving the living conditions and well-being of Beijing's inhabitants.
In the context of global warming and rapid urbanization,Beijing,as the capital city,has undergone significant transformations in its urban landscape.These changes have brought about persistent environmental issues,particularly the urban heat island (UHI) effect.Based on daily temperature observation data from 1981 to 2020 collected from both urban and suburban stations in Beijing,this study employs methods such as linear regression,kriging interpolation,and correlation analysis to investigate the temperature change trends on monthly,seasonal,and annual scales over the past 40 years.Additionally,it explores the spatiotemporal characteristics of UHI intensity in Beijing and assesses the impact of various factors,including meteorological elements (such as extreme maximum temperatures and average wind speed),population density,and land use/cover types,on the UHI effect,ultimately revealing the underlying causes of Beijing's UHI phenomenon.The findings indicate that the temperature trends in both urban and suburban areas of Beijing have been consistent over the past four decades,with an overall upward trajectory.Notably,the temperature increase in urban areas has been more pronounced than in suburban areas,with UHI increasing at a “wave-like” rate of 0.1 ℃/(10 a) highlighting a significant upward trend in Beijing's UHI.Analyzing by seasons,the UHI effect in Beijing is most pronounced in winter,with an average intensity of 1.22 ℃,followed by autumn,while spring and summer exhibit the weakest UHI effect.Among these,the increase in UHI during autumn is the most significant,with a change rate of 0.13 ℃/(10 a).From a spatial perspective,the UHI effect in Beijing is expanding.The high-value UHI areas are concentrated in the six central urban districts.The UHI zone extends from the northwest towards the southeast,reaching the sub-center in Tongzhou district.The warming trend is particularly evident in Chaoyang and Tongzhou districts.Since the year 2000,there has been a noticeable increase in the winter UHI intensity in Beijing,with high-value areas in the Tongzhou sub-center seeing UHI intensities rising to 1.6 ℃.Furthermore,principal component analysis reveals that population density,construction land,and average atmospheric pressure are key factors promoting the formation of the UHI effect.Conversely,wind speed and cultivated land play crucial roles in mitigating the UHI effect.As the process of urbanization accelerates,balancing urban development with environmental ecology becomes a crucial aspect of urban planning.Effective measures to control the UHI effect include regulating population density,rationally planning urban land use in terms of scale,structure,and spatial layout,and increasing the area of green vegetation and other ecological lands to alleviate the UHI impact.By implementing such strategies,Beijing can mitigate the adverse effects of the UHI phenomenon and enhance the overall quality of life for its residents.In summary,addressing Beijing's UHI effect requires a comprehensive approach that involves controlling population density,strategically planning urban land use,and enhancing ecological conservation efforts.These measures aim to reduce the spread of the UHI effect and promote a sustainable urban environment,ultimately improving the living conditions and well-being of Beijing's inhabitants.
2024,47(4): 592-603, DOI: 10.13878/j.cnki.dqkxxb.20230719001
Abstract:
Aerosol hygroscopicity is intricately linked to optical properties,activation potential,and lifespan.This study utilizes H-TDMA observational data from six sites across North China (Beijing,Xingtai,and Xinzhou) and the Yangtze River Delta (Baoshan,Dongtan in Shanghai,and Pukou in Nanjing) to investigate aerosol hygroscopicity characteristics and influencing factors in diverse environments.Urban sites include Beijing and Baoshan (Shanghai),while Xingtai and Pukou (Nanjing) represent suburban areas heavily impacted by human pollution.In contrast,Xinzhou and Dongtan (Shanghai) are less-affected suburban locales.The findings reveal that particle hygroscopicity at North China sites generally exceeds that at Yangtze River Delta sites.Specifically,the average hygroscopicity parameter of 40 nm nucleation mode particles at North China sites is approxiamtely 0.1 higher,and 200 nm accumulation mode particles are about 0.06 higher,representing a 5.6％ and 0.1％ increase,repectively,compared to the same particle sizes at Yangtze River Delta sites.This disparity is attributed to the dense presence of heavy industries in North China,limited atmospheric dispersion,and significant emissions and accumulation of gaseous precursors,which foster the formation of highly hygroscopic secondary aerosols,such as sulfates,under humid conditions.Overall,a significant divergence in aerosol hygroscopicity is observed across different emission backgrounds,with noticeable differences in hygroscopicity parameters between nucleation mode and accumulation mode particles across various North China sites.Urban site aerosols are heavily influenced by primary emissions and predominantly comprise hydrophobic substances,resulting in weak hygroscopicity and pronounced external mixing characteristics.Suburban sites heavily impacted by human pollution exhibit stronger hygroscopicity due to increased secondary aerosol formation.Conversely,less polluted suburban sites display intermediate hygroscopicity with a relatively higher internal mixing of particles.The marked variance in accumulation mode hygroscopicity at Yangtze River Delta sites is primarily attributed to the influence of marine aerosols,distinct from those at North China sites.Excluding Xingtai,particle hygroscopicity generally increases with particle size across other sites,indicating that larger particles typically contain more hygroscopic substances.Frequent new particle formation events at the Xingtai site result in stronger hygroscopicity of nucleation mode particles,with 40 nm particle hygroscopicity values around 0.38,significantly higher than at the other two sites in the same region.Substantial emissions of primary aerosols during morning and evening peak hours generally diminish aerosol hygroscopicity.Conversely,secondary aerosols generated by daytime photochemical reactions substantially enhance aerosol hygroscopicity,particularly evident at the three North China sites.These findings underscore the distinct differences in aerosol hygroscopicity across varying pollution environments,emphasizing the necessity for differentiation in simulations and studies addressing their impact on haze formation.The insights gleaned are of significant relevance for elucidating the mechanisms of air pollution formation and the radiative effects of aerosols.
Aerosol hygroscopicity is intricately linked to optical properties,activation potential,and lifespan.This study utilizes H-TDMA observational data from six sites across North China (Beijing,Xingtai,and Xinzhou) and the Yangtze River Delta (Baoshan,Dongtan in Shanghai,and Pukou in Nanjing) to investigate aerosol hygroscopicity characteristics and influencing factors in diverse environments.Urban sites include Beijing and Baoshan (Shanghai),while Xingtai and Pukou (Nanjing) represent suburban areas heavily impacted by human pollution.In contrast,Xinzhou and Dongtan (Shanghai) are less-affected suburban locales.The findings reveal that particle hygroscopicity at North China sites generally exceeds that at Yangtze River Delta sites.Specifically,the average hygroscopicity parameter of 40 nm nucleation mode particles at North China sites is approxiamtely 0.1 higher,and 200 nm accumulation mode particles are about 0.06 higher,representing a 5.6％ and 0.1％ increase,repectively,compared to the same particle sizes at Yangtze River Delta sites.This disparity is attributed to the dense presence of heavy industries in North China,limited atmospheric dispersion,and significant emissions and accumulation of gaseous precursors,which foster the formation of highly hygroscopic secondary aerosols,such as sulfates,under humid conditions.Overall,a significant divergence in aerosol hygroscopicity is observed across different emission backgrounds,with noticeable differences in hygroscopicity parameters between nucleation mode and accumulation mode particles across various North China sites.Urban site aerosols are heavily influenced by primary emissions and predominantly comprise hydrophobic substances,resulting in weak hygroscopicity and pronounced external mixing characteristics.Suburban sites heavily impacted by human pollution exhibit stronger hygroscopicity due to increased secondary aerosol formation.Conversely,less polluted suburban sites display intermediate hygroscopicity with a relatively higher internal mixing of particles.The marked variance in accumulation mode hygroscopicity at Yangtze River Delta sites is primarily attributed to the influence of marine aerosols,distinct from those at North China sites.Excluding Xingtai,particle hygroscopicity generally increases with particle size across other sites,indicating that larger particles typically contain more hygroscopic substances.Frequent new particle formation events at the Xingtai site result in stronger hygroscopicity of nucleation mode particles,with 40 nm particle hygroscopicity values around 0.38,significantly higher than at the other two sites in the same region.Substantial emissions of primary aerosols during morning and evening peak hours generally diminish aerosol hygroscopicity.Conversely,secondary aerosols generated by daytime photochemical reactions substantially enhance aerosol hygroscopicity,particularly evident at the three North China sites.These findings underscore the distinct differences in aerosol hygroscopicity across varying pollution environments,emphasizing the necessity for differentiation in simulations and studies addressing their impact on haze formation.The insights gleaned are of significant relevance for elucidating the mechanisms of air pollution formation and the radiative effects of aerosols.
2024,47(4): 604-619, DOI: 10.13878/j.cnki.dqkxxb.20230724001
Abstract:
Recent years have seen rapid industrialization and urbanization in China,leading to increased urban energy consumption and atmospheric pollutant emissions,posing severe air pollution challenges in some cities.The Fen River Valley,a critical area for air pollution prevention and control,experiences significant influences on pollutant dispersion within the atmospheric boundary layer due to its distinctive basin topography and the urban heat island effects of its large internal cities.This study employs the WRF-Chem model to investigate a severe pollution event in the Fen River Valley and Taiyuan City in January 2015.The study includes numerical simulations of the pollution process,observational validations,and terrain sensitivity experiments.It utilizes boundary layer height and wind speed to establish the Atmospheric Environment Capacity Index (AECI),quantifying the atmospheric dispersion capability.This index,along with the spatiotemporal distribution of PM2.5 concentrations,assesses the impact of surrounding terrain on local air pollution,providing a scientific basis for air pollution control policy formulation.Results show that atmospheric boundary layer circulation and pollutant transport in Taiyuan City and the surrounding Fen River Valley are influenced by weather systems,terrain,and urbanization.Terrain-induced circulation intensity significantly outweighs the urban heat island circulation in Taiyuan and markedly impacts its development.At night,mountainous terrain confines the boundary layer height within 200 to 400 m,while a weakened terrain sensitivity group shows only about 100 m.However,during the day,mountains compress the boundary layer height by more than 400 m in the sensitive group.Thus,to some extent,mountains limit urban atmospheric capacity,exacerbating the accumulation of near-surface air pollutants and deteriorating air quality.This is primarily evidenced by the experiment's terrain-sensitive group,where weakening the surrounding valley's topographic features in Taiyuan slows the PM2.5 concentration rise during the accumulation phase,aligning with the Fen River Valley dynamics.Terrain is identified as a primary factor affecting the distribution of atmospheric pollutants.The Fen River Valley's north-south orientation and its broader southern section influence regional atmospheric capacity,dictated by prevailing wind directions.When the dominant wind direction aligns with the valley's orientation,the increased wind speed due to the venturi effect enhances the valley's atmospheric capacity,facilitating pollutant dispersion and clearance.Conversely,when the dominant wind direction is perpendicular to the valley,mountainous terrain suppresses near-surface wind speeds and forms lower wind zones at the interface of the valley and mountains,significantly reducing the area's atmospheric capacity.This reduction strongly correlates with near-surface pollutant concentrations,with a correlation coefficient of 0.74;this correlation drops to 0.21 in the terrain-sensitive group,further underscoring the significant impact of terrain on air pollution processes.Overall,the surrounding mountains inhibit urban atmospheric capacity,particularly by accelerating the concentration increase during the pollutant accumulation phase.However,the specific mechanisms are complex and vary with different wind directions and diurnal cycles,suggesting that future research could further investigate the interactions between meteorological and topographical factors and propose more effective environmental management strategies.
Recent years have seen rapid industrialization and urbanization in China,leading to increased urban energy consumption and atmospheric pollutant emissions,posing severe air pollution challenges in some cities.The Fen River Valley,a critical area for air pollution prevention and control,experiences significant influences on pollutant dispersion within the atmospheric boundary layer due to its distinctive basin topography and the urban heat island effects of its large internal cities.This study employs the WRF-Chem model to investigate a severe pollution event in the Fen River Valley and Taiyuan City in January 2015.The study includes numerical simulations of the pollution process,observational validations,and terrain sensitivity experiments.It utilizes boundary layer height and wind speed to establish the Atmospheric Environment Capacity Index (AECI),quantifying the atmospheric dispersion capability.This index,along with the spatiotemporal distribution of PM2.5 concentrations,assesses the impact of surrounding terrain on local air pollution,providing a scientific basis for air pollution control policy formulation.Results show that atmospheric boundary layer circulation and pollutant transport in Taiyuan City and the surrounding Fen River Valley are influenced by weather systems,terrain,and urbanization.Terrain-induced circulation intensity significantly outweighs the urban heat island circulation in Taiyuan and markedly impacts its development.At night,mountainous terrain confines the boundary layer height within 200 to 400 m,while a weakened terrain sensitivity group shows only about 100 m.However,during the day,mountains compress the boundary layer height by more than 400 m in the sensitive group.Thus,to some extent,mountains limit urban atmospheric capacity,exacerbating the accumulation of near-surface air pollutants and deteriorating air quality.This is primarily evidenced by the experiment's terrain-sensitive group,where weakening the surrounding valley's topographic features in Taiyuan slows the PM2.5 concentration rise during the accumulation phase,aligning with the Fen River Valley dynamics.Terrain is identified as a primary factor affecting the distribution of atmospheric pollutants.The Fen River Valley's north-south orientation and its broader southern section influence regional atmospheric capacity,dictated by prevailing wind directions.When the dominant wind direction aligns with the valley's orientation,the increased wind speed due to the venturi effect enhances the valley's atmospheric capacity,facilitating pollutant dispersion and clearance.Conversely,when the dominant wind direction is perpendicular to the valley,mountainous terrain suppresses near-surface wind speeds and forms lower wind zones at the interface of the valley and mountains,significantly reducing the area's atmospheric capacity.This reduction strongly correlates with near-surface pollutant concentrations,with a correlation coefficient of 0.74;this correlation drops to 0.21 in the terrain-sensitive group,further underscoring the significant impact of terrain on air pollution processes.Overall,the surrounding mountains inhibit urban atmospheric capacity,particularly by accelerating the concentration increase during the pollutant accumulation phase.However,the specific mechanisms are complex and vary with different wind directions and diurnal cycles,suggesting that future research could further investigate the interactions between meteorological and topographical factors and propose more effective environmental management strategies.
ZHENG Hepeng, XIE Yanqiong, ZHANG Yun, YU Ting, HUANG Mengyu, TIAN Ping, BI Kai, DING Deping, YU Haoxiang, GE Panyan
2024,47(4): 620-628, DOI: 10.13878/j.cnki.dqkxxb.20230429001
Abstract:
Heavy fog significantly impacts modern transportation and public health.Thus,artificial fog dispersal crucial for disaster prevention and mitigation.Despite its importance,the mechanism underlying fog dispersal and the optimal particle size of dispersal catalyst remains uncertain.This study,conducted in a 15 000 cubic meter cloud chamber,explores the influence of different catalyst particle sizes on warm fog clearance.We found that catalyst A,with a particle size of 75 μm,effectively reduced the number concentration of fog droplets from 5 800 g/cm3 to 2 000 g/cm3 within 8 minutes and further to 1 000 g/cm3 within 10 minutes,while decreasing the liquid water content from 2.45 g/m3 to 0.2 g/m3.The mean volume diameter of the fog droplets increased from 6—8 μm to 10—20 μm,accelerating the fog clearance to 20％ of the time required for natural sedimentation.In contrast,Catalyst B (with a particle size of 100 μm) induced raindrop formation under heavy fog conditions,clearing the fog in 40％ of the time taken by natural sedimentation,albeit with slightly less effectiveness than catalyst A.
To determine the optimal catalyst particle size,we employed a gravitational continuous collision and growth model to evaluate the fog dispersal efficacy of different particle sizes,providing a theoretical basis for selecting the most effective size.Theoretical calculations suggest that for a droplet radius of 6 μm in a 25 m high cloud chamber,the collision efficiencies catalyst particles sized 50 μm and 100 μm are comparable (approximately 80％),requiring a catalyst mass of 3.52 kg.However,the dispersal for 50 μm radius particles is twice as long as for 100 μm particles.The study indicates that for droplets radii of 6—15 μm,catalyst particles in the 60—100 μm range are most effective.
Further analysis revealed that excessively small catalyst particles capture fewer fog droplets,require more time for fog dispersal,and consume less water during collisions.Conversely,overly large catalyst particles clear fog faster and have higher descent speed but are less effective in water consumption and droplet capture.Therefore,an optimal catalyst particle diameter of 40—80 μm is suggested.The findings presented here are based on a simplified gravitational continuous collision and growth model and do not consider factors such as vertical velocity and variations in liquid water content with height.Future studies should address these to refine the theoretical mechanisms of fog clearance and improve catalyst dosage calculations.
Heavy fog significantly impacts modern transportation and public health.Thus,artificial fog dispersal crucial for disaster prevention and mitigation.Despite its importance,the mechanism underlying fog dispersal and the optimal particle size of dispersal catalyst remains uncertain.This study,conducted in a 15 000 cubic meter cloud chamber,explores the influence of different catalyst particle sizes on warm fog clearance.We found that catalyst A,with a particle size of 75 μm,effectively reduced the number concentration of fog droplets from 5 800 g/cm3 to 2 000 g/cm3 within 8 minutes and further to 1 000 g/cm3 within 10 minutes,while decreasing the liquid water content from 2.45 g/m3 to 0.2 g/m3.The mean volume diameter of the fog droplets increased from 6—8 μm to 10—20 μm,accelerating the fog clearance to 20％ of the time required for natural sedimentation.In contrast,Catalyst B (with a particle size of 100 μm) induced raindrop formation under heavy fog conditions,clearing the fog in 40％ of the time taken by natural sedimentation,albeit with slightly less effectiveness than catalyst A.
To determine the optimal catalyst particle size,we employed a gravitational continuous collision and growth model to evaluate the fog dispersal efficacy of different particle sizes,providing a theoretical basis for selecting the most effective size.Theoretical calculations suggest that for a droplet radius of 6 μm in a 25 m high cloud chamber,the collision efficiencies catalyst particles sized 50 μm and 100 μm are comparable (approximately 80％),requiring a catalyst mass of 3.52 kg.However,the dispersal for 50 μm radius particles is twice as long as for 100 μm particles.The study indicates that for droplets radii of 6—15 μm,catalyst particles in the 60—100 μm range are most effective.
Further analysis revealed that excessively small catalyst particles capture fewer fog droplets,require more time for fog dispersal,and consume less water during collisions.Conversely,overly large catalyst particles clear fog faster and have higher descent speed but are less effective in water consumption and droplet capture.Therefore,an optimal catalyst particle diameter of 40—80 μm is suggested.The findings presented here are based on a simplified gravitational continuous collision and growth model and do not consider factors such as vertical velocity and variations in liquid water content with height.Future studies should address these to refine the theoretical mechanisms of fog clearance and improve catalyst dosage calculations.
2024,47(4): 629-642, DOI: 10.13878/j.cnki.dqkxxb.20240107001
Abstract:
This study investigates turbulence and cloud microphysical characteristics within the decoupled boundary layer,focusing on selected decoupling cases.High-frequency meteorological data and cloud microphysics data from stratocumulus-topped boundary layers,obtained during the POST (Physics of Stratocumulus Top) observation campaign,form the basis of our analysis.Results reveal that atmospheric static stability strengthens in the transition layer,inhibiting upward buoyancy work and rapidly depleting turbulent kinetic energy,leading to boundary layer decoupling.Maximum turbulent kinetic energy occurs within the cloud,driven primarily by cooling at the cloud top,enhanced downdraft from falling and sinking large cloud droplets,and latent heat release from condensation above the cloud base.Buoyancy and shear contributions augment turbulent kinetic energy in the near-surface layer,with shear playing a more prominent role,while within-cloud turbulent kinetic energy is mainly buoyancy-driven.Downward heat flux near the transition layer hinders upward heat transport and buoyancy enhancement,further promoting decoupling.Upward sensible heat flux within the cloud correlates with cloud top cooling and latent heat release from condensation in the lower cloud region.Increased moisture at the cloud top facilitates downward latent heat flux transport,amplifying water vapor content within the cloud,fostering positive feedback role in decoupled boundary layer cloud development.Cloud-top buoyancy reversal induces inhomogeneous mixing,leading to the appearance of adiabatic or super-adiabatic droplets and promoting condensation and coalescence growth.Additionally,enhanced moisture at the cloud top drives microphysical growth within the cloud.The cloud base exhibits homogeneous mixing characteristics due to entrainment.
This study investigates turbulence and cloud microphysical characteristics within the decoupled boundary layer,focusing on selected decoupling cases.High-frequency meteorological data and cloud microphysics data from stratocumulus-topped boundary layers,obtained during the POST (Physics of Stratocumulus Top) observation campaign,form the basis of our analysis.Results reveal that atmospheric static stability strengthens in the transition layer,inhibiting upward buoyancy work and rapidly depleting turbulent kinetic energy,leading to boundary layer decoupling.Maximum turbulent kinetic energy occurs within the cloud,driven primarily by cooling at the cloud top,enhanced downdraft from falling and sinking large cloud droplets,and latent heat release from condensation above the cloud base.Buoyancy and shear contributions augment turbulent kinetic energy in the near-surface layer,with shear playing a more prominent role,while within-cloud turbulent kinetic energy is mainly buoyancy-driven.Downward heat flux near the transition layer hinders upward heat transport and buoyancy enhancement,further promoting decoupling.Upward sensible heat flux within the cloud correlates with cloud top cooling and latent heat release from condensation in the lower cloud region.Increased moisture at the cloud top facilitates downward latent heat flux transport,amplifying water vapor content within the cloud,fostering positive feedback role in decoupled boundary layer cloud development.Cloud-top buoyancy reversal induces inhomogeneous mixing,leading to the appearance of adiabatic or super-adiabatic droplets and promoting condensation and coalescence growth.Additionally,enhanced moisture at the cloud top drives microphysical growth within the cloud.The cloud base exhibits homogeneous mixing characteristics due to entrainment.
ZHANG Jing, WU Dongli, LIU Daxin, LIU Cong, ZHU Yongchao, ZHANG Quanjun, YANG Dasheng, ZHANG Shihao, JIN Lei
2024,47(4): 643-652, DOI: 10.13878/j.cnki.dqkxxb.20231116001
Abstract:
Chlorophyll fluorescence is a non-invasive technique used to study the photosynthetic activity of plants.Recently,solar-induced chlorophyll fluorescence (SIF) has been developed to measure chlorophyll fluorescence in plants.This study uses hourly meteorological observation data and ERA5 reanalysis atmospheric data.The growth of pasture in the Hulunbuir grassland during the growing season was continuously and stably observed using the orbital daylight-induced chlorophyll fluorescence observatory.The variational characteristics of SIF and its response to changes in meteorological conditions are analyzed.During the 2022 growing season,SIF measurements were conducted in the Hulunbuir Grassland using the DR-SIF01 orbital observation instrument.Compared to the normalized difference vegetation index (NDVI),the low-frequency components of SIF can characterize plant growth changes during the growing season,while high-frequency variations can more clearly monitor the physiological processes of intrinsic photosynthesis in plants,closely related to meteorological conditions.Notably,the relationship between soil water content and SIF is nonlinear.When continuous excessive precipitation leads to soil waterlogging,the physiological metabolism of grass is weakened,and photosynthesis slows down,resulting in low SIF.Conversely,adequate early precipitation resulting in moist soil and strong solar radiation can maintain SIF at a relatively high level,indicating vigorous plant photosynthesis.In the late-growing season,cool autumn rains significantly reduce plant photosynthesis,resulting in difficult recovery.The in-situ measurements of chlorophyll fluorescence conducted in this study contribute to a quantitative understanding of grass growth status.Combined with the revealed response of SIF to meteorological conditions,early warning for crop disasters and optimization of management measures can be further achieved.Although the in-situ chlorophyll fluorescence data used in this study are more accurate than satellite inversion data,there are still challenges,such as short observation periods and limited observation sites.The SIF variation characteristics and responses to meteorological conditions revealed in this paper are based on data from a single site during the 2022 growing season,which introduces uncertainties.Future studies should focus on the data assimilation of satellite inversion and in-situ observation to achieve quantitative descriptions and real-time monitoring of plant photosynthesis and carbon sources and sinks in the Hulunbuir grassland.Additionally,applying chlorophyll fluorescence and NDVI observation data to the parametrization of land surface models to improve the simulation of dynamic plants and related water balance,energy balance,and carbon absorption remains a key scientific problem worth exploring.
Chlorophyll fluorescence is a non-invasive technique used to study the photosynthetic activity of plants.Recently,solar-induced chlorophyll fluorescence (SIF) has been developed to measure chlorophyll fluorescence in plants.This study uses hourly meteorological observation data and ERA5 reanalysis atmospheric data.The growth of pasture in the Hulunbuir grassland during the growing season was continuously and stably observed using the orbital daylight-induced chlorophyll fluorescence observatory.The variational characteristics of SIF and its response to changes in meteorological conditions are analyzed.During the 2022 growing season,SIF measurements were conducted in the Hulunbuir Grassland using the DR-SIF01 orbital observation instrument.Compared to the normalized difference vegetation index (NDVI),the low-frequency components of SIF can characterize plant growth changes during the growing season,while high-frequency variations can more clearly monitor the physiological processes of intrinsic photosynthesis in plants,closely related to meteorological conditions.Notably,the relationship between soil water content and SIF is nonlinear.When continuous excessive precipitation leads to soil waterlogging,the physiological metabolism of grass is weakened,and photosynthesis slows down,resulting in low SIF.Conversely,adequate early precipitation resulting in moist soil and strong solar radiation can maintain SIF at a relatively high level,indicating vigorous plant photosynthesis.In the late-growing season,cool autumn rains significantly reduce plant photosynthesis,resulting in difficult recovery.The in-situ measurements of chlorophyll fluorescence conducted in this study contribute to a quantitative understanding of grass growth status.Combined with the revealed response of SIF to meteorological conditions,early warning for crop disasters and optimization of management measures can be further achieved.Although the in-situ chlorophyll fluorescence data used in this study are more accurate than satellite inversion data,there are still challenges,such as short observation periods and limited observation sites.The SIF variation characteristics and responses to meteorological conditions revealed in this paper are based on data from a single site during the 2022 growing season,which introduces uncertainties.Future studies should focus on the data assimilation of satellite inversion and in-situ observation to achieve quantitative descriptions and real-time monitoring of plant photosynthesis and carbon sources and sinks in the Hulunbuir grassland.Additionally,applying chlorophyll fluorescence and NDVI observation data to the parametrization of land surface models to improve the simulation of dynamic plants and related water balance,energy balance,and carbon absorption remains a key scientific problem worth exploring.
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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.
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℃.
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。
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.
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.
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
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Ranking List
- 1APPLICATION OF WAVELET TRANSFORMATION TO ANALYSIS OF MULTIPLE TIME SCALE CLIMATE CHANGE
- 2Major Achievements in Meteorology in Ancient China
- 3The impact of the Himalayan-Tibet Plateau on the monsoon region
- 4CMIP5 projected changes in mean and extreme climate in the Belt and Road region
- 5Discussion on calculation method of flowering date meeting of hybrid rice parents
- 6Quality assessment of hourly merged precipitation product over China
- 7Analysis and comparison of four kinds of circulation indices of Aleutian Low
- 8The differences in characteristics and applicability among three types of Rossby wave activity flux in atmospheric dynamics
- 9Multiscale structure features of a typical Meiyu frontal rainstorm process
- 10
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