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.

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.

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.

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.

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.

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.

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.

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 PM_2.5 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 PM_2.5 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.

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.

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.

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.

Abstract:Area rainfall plays a crucial role in flood prevention within river basins.However,deterministic forecasts from single models often fail to capture the full range of possibilities,leading to uncertainties in area rainfall predictions.To address this issue,we employ the China Meteorological Administration-Regional Ensemble Prediction System to study ensemble forecasted area rainfall in the Haihe River basin.We evaluate and analyze the applicability of ensemble area rainfall forecasts from May to August of 2020 to 2022,utilizing high-resolution observed grid data.Subsequently,we develop ensemble area rainfall products and span forecasts based on our findings.Our analysis reveals several key insights:(1) The ensemble mean forecast of area rainfall in the Haihe River basin exhibits lower absolute error compared to the control forecast,with larger spatial distribution errors observed in the southern regions,followed by the central and northern regions.(2) Fuzzy scores indicate that the ensemble mean area rainfall forecasts for light and moderate rain closely align with observations,while forecasts for rainstorms require further consideration of ensemble extremes.(3) The ensemble mean demonstrates higher TS and Bias scores for light rain across all forecast times,with more improvements in moderate rain and higher categories during later forecast periods.(4) Probability forecasts suggest that CMA-REPS performs better for lower rainfall predictions in the central rivers of the Haihe River basin,while scores for the southern rivers are lower than those for the central rivers.We develop ensemble forecast area rainfall products and span forecast products and test them on two flood-causing rainstorm events in the Haihe River basin.Results indicate:(1) Ensemble members show a higher probability of predicting 24-hour intense area rainfall equivalent to observed magnitude,serving as warnings for extreme rainstorms.(2) Ensemble mean forecasts within 24 hours exhibit better scores,while 75％ quantile products are more significant for heavy precipitation process within 24 to 48 hours.(3) The ensemble forecast mixed percentile and span forecast products offer valuable references for heavy area rainfall.Additionally,by analyzing the probability forecast curve over time,we derive hourly area rainfall forecast products closer to observations.

Abstract:The Microwave Temperature Sounder (MWTS),an essential sensor onboard China's second-generation polar-orbiting meteorological satellites (FY-3),measures the vertical structure of atmospheric temperature profilesusing oxygen absorption in the 50-60 GHz frequency range.Since 2008,MWTS and its improved instruments have been deployed on FY-3A satellite (2008),FY-3B satellite (2010),FY-3C satellite (2013),and FY-3D satellite (2017),accumulating over a decade of observational data.While many researchers have utilized historical data from MSU and AMSU to study upper atmospheric trends,long-term datasets of high-altitude brightness temperatures incorporating data from domestic satellites remain scarce.The reliability of these domestic satellite datasets is crucial for constructingsuch long-term records.Therefore,this study assesses the quality of the FY-3 MWTS data by comparing them with synchronous observations from other instruments,such as METOP-A and Suomi-NPP.Our analysis shows that the average biases in the middle and upper tropospheric channels (53.596 GHz) between FY-3A/B/C/D and other instruments have been significantly reduced post-calibration,from -1.667 9/-1.215 6/-2.266 4/-0.019 4 K to -0.009 7/0.007 7/0.008 6/0.055 4 K,respectively.The standard deviations have also improved,reducing from 0.474 2/0.470 4/0.373 6/0.442 0 to 0.164 6/0.208 0/0.287 5/0.241 6,respectively.For the lower stratospheric channels (57.290 GHz),the average biases were reduced from 0.236 4/0.567 5/-3.933 3/0.218 8 K to -0.101 3/-0.222 0/0.053 3/-0.033 2 K,respectively,and the standard deviations from 0.875 0,1.344 0,0.230 8,1.074 2 to 0.690 6,0.783 4,0.277 4,0.178 1,respectively.These results indicate a steady improvement in the detection performance of MWTS onboard FY-3A/B/C/D satellites.The recalibrated datasets effectively address issues such as abnormal data jumps during satellite orbits,radiation response decay in remote sensing instruments,and calibration differences between various satellites.The deviations between recalibrated data and references are within ±0.1 K in both tropospheric and stratospheric channels.Furthermore,we conducted a differential analysis between the recalibrated FY-3D MWTS data and the long-term dataset from the NOAA Satellite Applications and Research Center (STAR).The monthly mean brightness temperature time series in the middle and upper tropospheresshows a minimal difference of 0.002 4 K/a in the trend of brightness temperature change.The brightness temperature distributions of both datasets are similar,decreasing gradually from the equator to the poles,influenced by underlying surface types.The maximum difference in brightness temperature change trends is within ±0.5 K/a.In the lower troposphere,the monthly mean brightness temperature time series shows a 0.0144 K/a difference in the trend.The brightness temperature distributions of both datasets are similar,increasing gradually from the equator to the poles,and are almost unaffected by underlying surface types.The maximum difference in brightness temperature change trends is within ±0.5 K/a.Therefore,the recalibrated FY-3D data post-2020 can be combined with the STAR dataset for analyzing temperature changes in the middle and upper atmosphere.This study supports climate change research based on long-term historical data from domestic satellites.