Abstract:The global warming trend has been increasingly significant since the 1980s.It appears that the warming has been accelerating since a decade ago.In 2023 and 2024,the global high temperature record was broken twice.In 2024,the temperature has risen by more than 1.55 ℃ as compared to the pre-industrial period.UN Secretary-General António Guterres proposed that the era of global warming has ended and the era of global boiling has arrived.With the intensification of climate change,the occurrence of extreme weather and climate events is becoming more and more frequent.According to statistics from relevant UN agencies,the economic losses caused by extreme weather and climate from 2000 to 2019 have been doubled compared to the previous 20 years.Effective tackling to the challenges of intensified climate change and extreme events requires revolutionary progress in climate science.Several landmark achievements in climate research have received top awards such as the Nobel Prize.The World Climate Research Programme has listed seven major scientific challenges and established the latest strategic and implementation plans to promote climate research and effectively address the challenges.
The China National Climate Research Committee (also the China National Committee for the World Climate Research Programme,CNC-WCRP) was established in 1985.It is one of the earliest established WCRP national committees in the world.CNC-WCRP has vigorously promoted exchanges and cooperation in climate research at home and internationally,and it has become an important bridge connecting international and domestic climate change research.The China Climate Research Committee,through expert recommendations and strict reviews,selected the major progress of climate research in China in 2024.
1) Characteristics and causes of interdecadal extreme warming in Northeast Asia transition Zone (Cai et al.,2024),a one-sentence comment:reveals that the substantial warming of the Northeast Asian climate transition zone since the 1980s is not entirely caused by external forcing,while the Pacific and Atlantic decadal oscillations play a significant role.
2) Aerosol climate effect caused by changes in aerosol absorbency and underlying surface albedo (Chen et al.,2024),a one-sentence comment:combining multi-source data to reveal the influence of surface albedo on the direct radiation effects of aerosols in recent 20 years,thus demonstrating the complexity of quantifying the direct radiation effects of aerosols.
3) Human activities have led to more variable global precipitation in the past hundred years (Zhang W et al.,2024),a one-sentence comment:the most abundant data are used to demonstrate the enhancement of global precipitation variability at different time scales.
4) Traditional Meiyu has been suspended by global warming (Yin et al.,2024),a one-sentence comment:for the first time,a three-dimensional index was constructed to characterize traditional Meiyu and it was found that the characteristics of traditional Meiyu features,such as misty rain and mildew rain,are gradually moving away due to global warming.
5) The pattern of global precipitation system tends to flatten in the past two decades (Zhang and Wang,2024),one sentence comment:in the past 20 years,the spatial morphology of precipitation systems on a global scale tends to flatten due to the enhancement of atmospheric stability and the increase of water vapor transport (manifested as a trend of limited vertical development and enhanced horizontal expansion).
6) The coupling process of water-heat-carbon on land surface and its key mechanisms in the Qinghai-Xizang Plateau (Deng et al.,2024;Meng et al.,2024;Sheng et al.,2024;Wang et al.,2024),a one-sentence comment:the key characteristics and mechanisms of the surface water-heat-carbon coupling are revealed using the observational data of the Qinghai-Xizang Plateau.
7) Effects of SST anomalies in the mid-latitude North Pacific Ocean on summer climate in ENSO and non-ENSO states (Tao et al.,2024a,2024b),a one-sentence comment:the mid-latitude North Pacific SST anomaly has a significant effect on subsequent summer climate (regardless of whether ENSO events occur).
8) Finding the increasing trend of salinity difference between Atlantic Ocean and Pacific Ocean (Lu Y et al.,2024),a one-sentence comment:the analysis of 0—2 000 m ocean observational data reveals that seawater salinity has generally increased in the Atlantic Ocean and decreased in the Pacific Ocean in the past half century.
9) Deeptime ocean circulation and ENSO (Li et al.,2024;Yuan et al.,2024),a one-sentence comment:using coupled climate models to simulate the deeptime North Atlantic overturning circulation and ENSO,presenting rich pictures of the processes and mechanisms.
10) Development and application of artificial intelligence (AI) global subseasonal-seasonal climate prediction system (Lu B et al.,2024),a one-sentence comment:a large artificial intelligence model for global subseasonal-seasonal climate prediction with physical information is constructed.
The major research progresses in 2024 as selected by the China Climate Research Committee involves many aspects of the earth's climate system,and most of the results are completed by the cooperation.At the same time,the research results have important value for building better forecasting methods to support efficient disaster prevention and reduction.Based on these research achievements and the author's research,this artical proposed that hot spots and emphases of future climate research mainly include,global warming acceleration,intensifying climate extremes,new era of the Arctic and Qinghai-Xizang Plateau,the interaction of the three oceans,paleoclimate studies serving for present climate change research,climate prediction and AI,and the increasing risk in coastal urban agglomerations to climate change.

Abstract:The middle-upper atmosphere has been identified as a frontier scientific research area in the World Weather and Climate Research Program due to its significant impact on tropospheric weather and climate.Moreover,as a transitional space from aviation to space,it has been regarded as the new “high frontier” for national defense security.In China,due to insufficient observational data and a lack of comprehensive middle-upper atmospheric models,our understanding of variations in the middle-upper atmospheric environment and their weather/climate disaster effects is not sufficiently profound.To deepen our understanding of the mid-to-upper atmosphere,the major project “Variations in the middle and upper atmospheric environment and their impacts on weather and climate disasters” was granted by the National Natural Science Foundation of China.This project aims to conduct the following research:1)Develop new technologies and methods for observing the composition of the middle-upper atmosphere,carry out integrated “sky-to-ground” multi-element collaborative observations,and obtain multi-temporal and multi-spatial scale observations of the middle-upper atmosphere.2)Study the impact of cross-atmospheric layer interactions and multi-source disturbances on the middle-upper atmosphere,quantify the influences and contributions of external forcing factors and internal variability on the variations in the middle-upper atmosphere.3)Improve the physical and chemical processes of the middle-upper atmosphere in the model,and establish a data assimilation system for the middle-upper atmosphere.4)Investigate the impacts and mechanisms of variations in the middle-upper atmosphere on extreme weather and climate,particularly in East Asia,assess their disaster effects and risks.The expected results will provide new insights for extreme weather forecasting and early warning,and offering important technological support and decision-making basis for disaster prevention,mitigation,climate change response,and even national defense security.This article briefly introduces the research background,content,and key scientific issues of the project as well as recent main achievements of this project.

Abstract:Drought,as one of the leading and most severe meteorological disasters globally,occurs frequently in China.Between 2001 and 2020,approximately 48％ of the crop area affected by meteorological disasters in China were due to drought (Li et al.,2021).Heatwaves are believed to be increasing under global warming,while droughts exhibit more regionalized patterns.The simultaneous occurrence of drought and heatwave has become more frequent,mainly due to increase in high temperature events driven by global warming.High temperature and soil moisture deficit can reinforce each other,likely leading to more frequent,longer-lasting,and stronger extreme events,known as compound drought and heatwave events (CDHEs).CDHEs have more severe and persistent impact on agriculture and ecological environment through the positive feedback between drought and high temperature.This work provides a brief review of research progress on drought,heatwave,and CDHE events in China.First,the various definitions of drought,heatwave,and CDHE are summarized.The influencing factors,including sea surface temperature (SST) and sea ice,land surface conditions,atmospheric circulation patterns,and the underlying physical processes,are then reviewed.
Northeast China (NEC) is a typical region where drought,heatwave,and CDHE events often occur.Previous studies have identified several factors that influence these events in NEC.As an example,we integrate the effects of sea-land-ice-air system on NEC drought,heatwave,and CDHE events based on prior research,constructing a simplified physical framework.The key mechanisms can be briefly depicted as follows:
Local anomalous anticyclone plays a central role in drought,heatwave,and CDHE events.These local circulation anomalies can be induced by Rossby wave train in the upper atmosphere,which are influenced by climate variations in the upstream,including the North Atlantic Oscillation (NAO),Atlantic Multidecadal Oscillation (AMO),North Atlantic SST,polar sea ice,and soil temperature in Central Asia.Additionally,phenomena like El Niño and Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO) can significantly affect the drought,heatwave,CDHE events in NEC.
Despite the identification of several local,regional,remote natural climate systems contributing to drought,heatwave,CDHE events in China,a comprehensive understanding of the synergistic physical and dynamical mechanisms behind these events remains lacking.These processes are complicated by the interplay between regional SST,sea ice,land surface conditions,and atmospheric dynamics.In addition to natural climate systems,anthropogenic activity are proposed to significantly drive the increasing frequency and intensity of drought,heatwave,CDHE events in China.However,the relative contribution of natural climate variation and anthropogenic forcing remain unclear and require further investigation.
Although the impact of drought,heatwave,CDHE events is growing rapidly,predictive skills remain limited.Numerical weather forecast based on state-of-the-art models have a skill horizon of only about one week.These limitations arise from our incomplete understanding of the underlying physical processes and the imperfect representation of the real world by current numerical models.The first step in improving prediction skills is to systematically enhance our understanding of the physical processes driving extreme climate events.Developing effective dynamical-statistical methods,including deep-learning techniques,is essential for improving the predictability of drought,heatwave,CDHE events over various timescales,addressing the urgent need to prevent disasters and reduce damages under global warming.

Abstract:In recent decades,the Northern Hemisphere has experienced frequent temperature extremes that have significantly influenced human well-being,socioeconomic stability,and ecological systems.Among these,concurrent cold extremes have concurrently occurred across multiple regions and have drawn increasing attention,often linked to variations in jet stream dynamics.Despite growing interest,most studies have focused on individual events,leaving a limited understanding of the mechanisms driving concurrent temperature extremes across regions.This study focused on the characteristics and possible mechanisms of concurrent cold extremes in East Asia and North America during winter from 1979 to 2021,using the Climate Prediction Center minimum surface air temperature dataset and the NCEP/NCAR reanalysis dataset.Cold extremes were defined as daily minimum temperatures falling below the 10th percentile at each grid point,and their frequencies were analyzed across different time scales.The East Asia (73°—145°E,4°—53°N)and North America (160°—12°W,25°—75°N)were selected as the dominant study regions.The results show that concurrent cold extremes between East Asia and North America predominantly occurred on a pentad time scale.While the frequency of such events has shown a decreasing trend since 2000,significant concurrent cold extremes continue to occur on smaller time scales.Synchronicity between the two regions was confirmed through lead-lag correlation coefficients analysis,highlighting a robust connection.Further analysis of the atmospheric circulations and thermodynamic conditions during concurrent cold extremes identified key mechanisms.Zonal circulation patterns showed enhanced jet streams over the western Pacific Ocean and the West Atlantic Ocean,accompanied by negative geopotential height anomalies.These anomalies formed a Rossby wave-4 pattern,facilitating cold air advection from high latitudes to low latitudes.Meridional circulation analysis supported this,demonstrating the role of jet stream variations in transporting cold air masses.From a thermodynamic perspective,meridional temperature advection and non-adiabatic cooling emerged as the two most significant contributors to concurrent cold extremes in East Asia and North America.These findings provide new insights into the dynamics of concurrent cold extremes in the Northern Hemisphere and highlight the critical role of jet stream variability.Regional differences in temperature impacts between East Asia and North America were noted and need further investigation.Additionally,the resemblance of geopotential height anomalies to a Rossby wave-4 pattern suggests a need for further exploration of the underlying wave dynamics.This study advances the understanding of concurrent temperature extremes and their linkage to atmospheric circulation,offering a foundation for future research and prediction efforts.

Abstract:Remote sensing precipitation products provide near real-time,multi-temporal,and spatially resolved precipitation data,which are essential for accurate meteorological drought monitoring.However,their accuracy is often compromised by complex terrain and extreme climate conditions.Machine learning-based data fusion methods offer a novel solution to for enhancing the precision of remote sensing precipitation products,particularly in challenging environments.This study focuses on the source region of the Yellow River,a data-scarce area with complex topography,to develop a high-resolution gridded precipitation dataset and evaluate its utility in drought monitoring.
Using the Random Forest (RF) model,a long-term (1983—2018) high-accuracy precipitation dataset was generated by fusing multiple remote sensing precipitation products.The fused dataset was applied to identify meteorological drought events using the Standardized Precipitation Index (SPI) and run theory.Temporal and spatial characteristics of drought events were analyzed to assess dataset’s capability to capture drought dynamics.Key findings include:1) The fused precipitation dataset outperformed three individual remote sensing precipitation products (PERSIANN-CDR,MSWEP v2.0,and CHIRPS v2.0) at the station scale,exhibiting higher correlation coefficients (CC),lower root mean square errors (RMSE),reduced relative bias,and improved Kling-Gupta efficiency (KGE).The dataset accurately captured both monthly and inter annual variations,demonstrating its adaptability to the Yellow River source region.2) Precipitation and SPI values across four temporal scales (SPI1,SPI3,SPI6,and SPI12) exhibited statistically significant increasing trends (P<0.05),indicating increased precipitation and a reduction meteorological drought severity over the past 36 years.3) An abrupt change in precipitation occurred in 2006.Prior to this point,the region experienced more frequent and severe droughts with longer durations,higher intensities,and greater extremes.After 2006,drought characteristics became milder.Spatially,the northwest of the source region experienced longer and more severe droughts,while the southeast exhibited higher drought intensity and extremes.
This study provides critical insights into precipitation and drought dynamics in the source region of the Yellow River,supporting efforts in meteorological drought early warning,water resource management,and regional climate adaptation.The observed increasing precipitation trend and alleviation of drought conditions are vital for developing sustainable development strategies and disaster mitigation plans.
The research underscores the potential of integrating remote sensing products with machine learning techniques to improve the accuracy and applicability of climate datasets,especially in regions with limited ground-based observations and complex topography.The fused dataset not only demonstrated enhanced accuracy but also provided a robust foundation for analyzing the spatiotemporal evolution of meteorological drought events.Future work could extend this approach to other regions and incorporate additional hydrometeorological variables for more comprehensive drought assessments.

Abstract:In the context of global warming,the frequency of compound extreme weather and climate events has increased,posing significant challenges to environmental stability and societal resilience.Understanding the mechanisms driving these events is crucial for improving their prediction and mitigation.This study examines Compound Extreme Heat-Precipitation Events (CEHPE) in Northwest China,a region frequently impacted by such phenomena.The study aims to elucidate the weather-scale dynamics underpinning CEHPE and distinguish them from isolated heatwave events to enhance our understanding of these processes.
CEHPEs are defined as the occurrence of heavy precipitation within 3 days after the end of a heatwave,excluding instances of heavy precipitation during the heatwave itself.Heatwaves are identified when the DMT exceeds the 90th percentile for at least three consecutive days during summer (June-August).This percentile is calculated for each grid cell and each date using a 31-day sliding window based on 30-year baseline period (1961—1990).Heavy precipitation events are defined as daily precipitation exceeding the 95th percentile of precipitation on rainy days (≥0.1 mm/d).
The results reveal that CEHPE are triggered by a quasi-barotropic wave train propagating southeastward from upstream regions.When an anticyclonic circulation center approaches the key region (95°-105°E,35°-40°N),anomalous descent leads to adiabatic warming,raising lower tropospheric air temperatures.Simultaneously,reduced cloud cover enhances downward shortwave radiation,heating the surface.The heated surface emits more longwave radiation,further warming the lower troposphere and initiating a heatwave.During the heatwave,surface thermal forcing generates a low-level cyclonic circulation anomaly,which directs moisture from the southeast into the key region.The resulting increase in moisture and air temperature enhances atmospheric instability.
At the end of the heatwave,when the quasi-barotropic anticyclonic anomaly moves eastward and is succeeded by a cyclonic circulation anomaly,the key region lies west of the upper-level ridge and east of the upper-level trough.This configuration promotes upper-level divergence,lower-level convergence,and rapid convective development,culminating in extreme precipitation and completing the CEHPE cycle.
Mere heatwave events share similar intensity and formation mechanisms with CEHPE.However,in these cases,the quasi-barotropic anticyclonic anomaly expands and weakens but remains centered over the key region,suppressing the development of low-level cyclonic circulation anomalies.Consequently,weaker low-level convergence,moisture transport,and atmospheric instability prevent heavy precipitation.Furthermore,the local weakening of the anomalous anticyclone inhibits the approach of upstream cyclonic circulation anomalies,further reducing the likelihood of precipitation.
This study elucidates the mechanisms underlying CEHPE in Northwest China and highlights their distinct differences from isolated heatwaves.However,the external forcings contributing to these differences remain unclear and merit further investigation.

Abstract:On September 7,extreme torrential rainstorms struckthe Greater Bay Area(GBA),including Hong Kong,Macau,and parts of Guangdong Province near the Peal River Estuary in South China.This event resulted in historical accumulated precipitation exceeding 800 mm within 24 hours in Hong Kong,causing severe social and economic losses.Operational numerical forecast models showed limited skill in predicting the intensity and location of this extreme rainfall.Using multi-source meteorological observations,this study analyzed the precipitation characteristics,convection initiation,organization,and underlying causes of the extreme precipitation through circulation diagnostics,thermodynamic analysis,and vorticity budgeting.The rainfall was primarily associated with remnant vortex of the decayed typhoon Haikui.Synoptic analysis revealed that the typhoon vortex decayed rapidly after landfall in Fujian Province,South China.Due to weak mid-level environmental steering,the westward-moving remnant vortex stagnated over the GBA,north of the Pearl River Estuary,from the morning of September 7 until early evening on September 8.On the night of September 7,an enhanced easterly boundary layer jet combined with southwesterly monsoon airflowfrom the South China Sea,forming an intensified southeast jets tronger than predicted in numerical models.This southeast jet injected large amounts of moist,unstable air into the remnant vortex circulation over the GBA,triggering excessive precipitation.Significant low-level convergence and frontogenesis provided favorable conditions for mesoscale lifting.Late on September 7,a mesoscale jet pulse with boundary-layer wind speeds exceeding 20 m/s was detected by a wind profiler in Shenzhen.The mesoscale convergence and frontogenesis near the jet exit intensified convection initiation and precipitation.Revival of the remnant vortex in the boundary layer was closely linked to latent heat gradients below the mid-level maximum heating center.Weather radar observations revealed that from 14:00 BST on September 7,convection and precipitation intensified,forming a quasi-linear convective belt composed of rapidly growing discrete convective cells along the west shore of the GBA.A secondary,weaker convective line formed along the east shore,organized along the boundary between shallow easterly airflow and southwesterly monsoon winds.These two linear mesoscale convective systems (MCS) merged near Hong Kong’s southern coast,persisting for over 12 hours.A series of northward-moving convective cells repeatedly passed over Hong Kong and Shenzhen along similar tracks,inducing localized extreme rainfall.A maximum rainfall intensity of 158 mm/h was recorded in Hong Kong.After 14:00 BST on September 8,the remnant vortex of Haikui gradually moved westward toward Guangxi Province,leading to weakened rainfall in the GBA.Observation of raindrop size distributions showed that the precipitation had characteristics typical of maritime convection,with significant increases in raindrop size during periods of enhanced rainfall.This increased precipitation efficiency in the deep moist layer.The convection exhibited a low echo centroid structure withstorm tops exceeding 8 km,facilitating rapid growth of raindrops through coalescence during descent.Embedded β- and γ-mesoscale vortices within the linear MCS contributed to the extreme rainfall intensity.These vortices,identified using Doppler radar observations in Shenzhen,warrant further investigations.

Abstract:Sea surface temperature (SST) is a crucial indicator of heat exchange between the ocean and atmosphere.As one of the most important ocean environmental parameters describing the thermal state of the ocean surface,it is widely used in research and applications such as upper ocean processes,air-sea heat exchange,numerical simulation and forecasting of the ocean-atmosphere system.In-situ observation is one of the most direct and accurate ways to obtain SST,primarily through conventional observation systems such as offshore buoys,coastal stations,and ships.In-situ SST observations serve as the foundation for all other sea temperature data products.Whether it is gridded SST data products,satellite-retrieved SST products,multi-source merged products,or reanalysis data,these SST data products all rely on ship and buoy observation data as the basic support.
Therefore,focusing on ships and buoys as the two primary observation methods for SST,this work collected SST observation data from multiple sources such as ICOADS,GTS,CFSR_OBS,GDAS_OBS,and offshore China.Through decoding,extraction,duplicate checking,standardization,and other steps,a relatively complete and long-term sequence of global SST observation dataset was integrated.Besides the traditional quality control techniques for gross errors,the quality control scheme developed for this dataset also includes a technical approach leveraging model analysis fields for observation data quality control.Specifically,using ERA5 reanalysis data,a unified quality control process was applied to the data.The quality control scheme formulated can remove large variations or anomalies in SST.The final products,the “Global Ship-Based SST Observation Dataset from 1900 to 2023” and the “Global Buoy-Based SST Observation Dataset from 1976 to 2023,” can provide fundamental data support for subsequent SST data evaluation,multi-source SST data merging,and global climate change analysis.This paper further evaluates the data characteristic differences,and the main conclusions are as follows:
After the 1990s,the number of buoy observation records far exceeded those of ship observations.After 2011,buoy observation records reached more than ten times the number of ship observations.The large number of buoy observation records is mainly due to continuous observations over time.However,buoy data have much lower spatial and temporal coverage than ship observations,with poor representation of global or large-scale SST,making it impractical to study global SST trends solely using buoy data.
The quality control results indicate that buoy observation data have a higher accuracy rate and better quality than ship observation data.Error comparison analysis between ships,buoys,and ERA5 reanalysis data also shows that buoy observation data have smaller errors.Therefore,buoy data can be used as a high-precision data source to correct or evaluate other data sources.Ship data has a positive systematic bias relative to buoy data,with an average daily bias of approximately 0.2 ℃.
After 1961,the number of global ship-based SST observations increased significantly.Between the 1970s and 1990s,the number of ship records showed phased high values.After the 1990s,the number of ship observations decreased and stabilized.During 1990—2023,the global SST trend shown by ship data was consistent with that of ERA5 data,showing a slow upward trend.Among them,the global SST observed by ships from 1998 to 2012 showed a “basically unchanged plateau period”, while before and after this period,SST showed a clear upward trend.Although ship data have a relatively smaller number of observation samples compared to buoys,their spatial and temporal coverage is relatively larger,providing a certain reference for global SST trend changes.Combining the accuracy of buoy observation data with the coverage of ship observation data in the future can better apply them to global change research.

Abstract:Since the launch of the FY-3A satellite in May 2008 and subsequent missions,including the FY-3G for precipitation and the FY-3F until 2023,the Fengyun-3 (FY-3) second-generation polar-orbiting satellite series has developed into a comprehensive observation network.This network now operates with early-morning,mid-morning,afternoon,and precipitation-dedicated satellites simultaneously in orbit,significantly enhancing the spatial and temporal resolution of satellite data and supporting advances in numerical weather prediction (NWP) in China.The Southwest China vortex (SWCV),a major weather system contributing to intense summer rainfall in China,forms over the complex terrain east of the Qinghai-Xizang Plateau at 700—850 hPa.This study analyzes a SWCV event from July 21 to 23,2022,which caused heavy rainfall near the Sichuan-Shanxi border,where several stations recorded over 100 mm of precipitation within 24 hours.As the vortex moved eastward,it generated a rainfall belt extending from Chongqing through Hubei,Henan,and Shandong provinces.
The research investigates the impact of clear-sky assimilation of FY-3 satellite microwave humidity data on forecasting the SWCV using the WRF model and WRFDA system.Clear-sky assimilation experiments with MWHS-2 observations from FY-3C and FY-3D satellites were conducted to assess optimal thinning distances for data assimilation.The findings show that applying inappropriate thinning distances minimizes observation errors,reduces computational costs and improves forecast accuracy.Specifically,a thinning distance of 30 km,approximating the resolution of the sub-satellite point,optimizes forecast performance by maintaining an effective balance between minimizing spatial correlations in the data and ensuring sufficient observational density to constrain the analysis field.This configuration enhances predictions of precipitation location and intensity while reducing false alarms for heavy rainfall events.
Results demonstrate that assimilating data from both FY-3C and FY-3D satellites provides superior forecasts compared to single satellite assimilation,as network data assimilation increases the quantity of high-quality observations,thereby refining initial conditions and improving short-term weather forecast accuracy.FY-3C-only data assimilation particularly enhances relative humidity forecasts,improving intensity predictions and yielding higher threat scores (TSs) for extreme rainfall.Conversely,while FY-3D-only assimilation enhances wind field forecasts,improving the spatial accuracy of precipitation predictions.The combined FY-3CD satellite data assimilation adjusts lower-quality data points,producing more stable forecasts.Future work will extend these efforts by incorporating additional Fengyun satellites for comprehensive network assimilation,aiming to further improve NWP accuracy and optimize the use of satellite observations.

Abstract:The complex topography and unique geographical location of Yunnan Province contribute to the frequent occurrence of short-term heavy precipitation,a severe convective weather phenomenon often associated with natural disasters.Using hourly precipitation data at a high spatial resolution of 0.062 5°×0.062 5° from the China Meteorological Administration Land Data Assimilation System (CLDAS) and ERA5 hourly reanalysis data from 2008 to 2022,this study analyzes 91 regional short-term heavy precipitation events and classifies them using K-means clustering.The three-dimensional weather system configuration and its thermal and dynamic characteristics are also examined.The results reveal the following:1) Short-term heavy precipitation is most frequent in southeastern Yunnan,with the highest intensity observed in southeastern,southwestern,and western region of the province.Peak intensity occurs between 2000 UTC and 2100 UTC,while peak frequency is observed from 1400 UTC to 1500 UTC.Inter-annual variability is significant,with extreme years experiencing precipitation exceeding 80 mm,compared to an average of 26 mm.2) The precipitation events can be categorized into three types:the westerly-small trough type,the upper-level long trough type,and the peripheral type of the subtropical high.The upper-level long trough type exhibits the highest intensity and frequency,occurring across the entire province.3) Favorable conditions for precipitation include dynamic,thermal,and moisture-related factors.At 200 hPa,strong divergence is observed in regions such as the southern side of the upper-level jet stream,located in front of a trough or on the western side of the subtropical high,coupled with upward motion at 500 hPa.This is combined with low-level shear lines,low vortices,and surface convergence zones in the middle and lower troposphere.Moisture convergence primarily originates from the Bay of Bengal,interacting with westerly airflow over Yunnan Province.The K-index exceeds 38 ℃ in these events.Among the three types,the upper-level long trough type features the strongest low-level fronts,cold air activity,and mid-and low-level shear lines and vortices centered over Yunnan.Its forward-tilting vertical structure creates strong thermal instability,resulting in enhanced upward motion,significant water vapor convergence across atmospheric layers,and the heaviest precipitation.

Abstract:This study leverages rotorcraft Unmanned Aerial Vehicle (UAV) observations from five stations near Yancheng city,Jiangsu Province,collected between July and October 2019,to analyze atmospheric boundary layer characteristics during summer convective weather.ERA5 analysis and L-band sounding observations were used to quantitatively evaluate biases and errors in temperature,humidity,and wind fields derived from UAV observations.At different vertical levels,the average temperature deviations between UAV and sounding observations ranged from -0.2 to 0.02 ℃,with observation errors between 0.44 and 0.59 ℃.Average humidity deviations between UAV observations and ERA5 reanalysis were 1.27％ to 7.14％,with corresponding observation errors of 7.14％ to 10.71％.Deviations in wind speed and direction were 0.40 to 1.34 m/s and -3.87° to 4.98°,respectively with errors of 1.24 to 1.62 m/s and 10.50° to 23.96°.The triangular cap method,used for error estimation assumes mutual independence of datasets,leading to inherent uncertainties in standard deviation calculations.Observational errors derived via this method depend on discrepancies between reference datasets;large discrepancies yield smaller observational errors,whereas smaller discrepancies increase the errors.Despite these limitations,the overall accuracy of UAV data aligns with the reference datasets,meeting requirements for boundary layer analysis.The boundary layer characteristics during three distinct convective weather scenarios were examined:1) In the case of weak synoptic-scale forcing,precipitation was driven caused by localized wind convergence and changes in inversion layer height prior to precipitation,as captured by UAV observations.Intense wind shear below the lifting condensation level was identified as a precursor to precipitation events;2) In the case of strong synoptic-scale forcing,precipitation was caused by large-scale low-level instability,evidenced by an unstable superadiabatic layer within the boundary layer.The boundary layer characteristics showed clear responses to synoptic-scale forcing;3) In the influence of a moving synoptic-scale weather system,rapid changes in meteorological variables within the boundary layer,such as increased wind speed near the surface,were attributed to the movement of a dominant synoptic-scale system.The planetary boundary layer depth dropped sharply due to the cold air intrusion.The study underscores that boundary layer variations reflect large-scale forcing in cases of strong synoptic-scale influences,while weak synoptic-scale forcing reveals localized precipitation mechanisms.These findings form the basis for improving numerical models and variational assimilation techniques for convective weather prediction.Future research will focus on developing error correction models,quality control methods,and sparsification techniques to enhance the integration assimilation of UAV observations into numerical weather prediction models,improving forecasts of localized convective events.

Abstract:Cold front precipitation cloud systems are the primary target for ecological restoration through artificial precipitation enhancement in the Sanjiangyuan National Nature Reserve.However,the quantitative understanding of these cloud systems remains insufficient.Aircraft observations are currently the only method to directly obtain the phase state of cloud particles,making them a crucial component of cloud and precipitation physics studies.In this study,we analyzed the microphysical characteristics of a typical layered cloud system in the Sanjiangyuan region during spring,based on vertical detection data collected using the particle measurement system (PMS).To discriminate the phase state of cloud particles,the study adopted 2DC image gray projection data,identifying discriminate non-spherical cloud particles with sizes between 50 μm and 125 μm as ice crystals.The criteria for phase discrimination included: i) mean diameter N_2(>50)> 0.1 L^-1,and ii) the water content LWC_FSSP> 10^-3 g/m³.Flight observations revealed a three-layered stratiform cloud system during spring;i) cirrostratus (Cs) located at an altitude of about 7 400—7 800 m above sea level with a thickness of 300—400 m,consisting entirely of ice-phase clouds,ii) upper and lower layers of altostratus (As) positioned between 6 400—6 600 m above sea level,and 5 100—6 200 m above sea level,respectively.The results show that the high supercooled water regions were primarily distributed in the middle,upper,and lower parts of the low-level As layer.These regions exhibited the highest cloud particle concentrations and supercooled water contents,with distinct regional characteristics.The average cloud particle concentration As measured by FSSP in the studied region was significantly higher than that of stratiform clouds in inland northern China and higher than autumn observation in this region.This regional distinction is largely attributed to the abundant water vapor in the Sanjiangyuan region.The liquid cloud particles in the As layer were predominantly concentrated within a median diameter range of 3.5—27.5 μm,while particles exceeding 30.5 μm were primarily ice-phase.In the middle and upper parts of the low As layer,there was pronounced growth in the high supercooled water region,with ice crystal formation and growth predominantly occurring in the middle and lower parts.In the low supercooled water regions,the average supercooled water content ratio was (90.8％±10.9％).The ratio in the middle to lower parts (95.6％±5.6％) was significantly higher than in the middle and upper parts (79.8％±12.1％).As the primary precipitation-generating cloud layer,accretion growth in the lower As layer was the dominant mechanism for the generation of large-size ice particles.These findings underscore the importance of accurate characterization and understanding of the microphysical structure of the layered cloud system in Sanjiangyuan.Such insights provide a reliable observation basis for the optimizing artificial precipitation enhancement operations in the region.This study has significant practical significance for advancing the understanding of the microphysical characteristics of stratiform clouds in Sanjiangyuan and improving aircraft-based artificial precipitation operation technologies.

Abstract:This study investigates the macro- and micro-physical characteristics of a stratiform precipitation event in southern Hebei on April 4,2023,influenced by a combination of a high-altitude trough,the Yangtze-Huaihe cyclone,and a low-level jet stream.Leveraging data from the Luancheng Cloud Microphysics Superstation,aircraft observations,operational weather radar,and satellite imagery,the research provides a comprehensive analysis of the cloud microphysical and precipitation processes.The precipitation event,located north of the Yangtze-Huaihe cyclone,was driven by dynamic interactions between a low-level jet at 850 hPa,a high-altitude trough at 500 hPa,and a reversed trough at 700 hPa.These conditions created upper-level divergence and lower-level convergence across Hebei Province,facilitating the large-scale ascent of warm,moist air and the formation of a stratiform cloud system.Analysis of radar reflectivity and FY-4B satellite data,including cloud-top height and blackbody brightness temperature,indicated that the Yangtze-Huaihe cyclone reached its mature stage on April 4,displaying a typical “comma-shaped” cloud structure that moved northeastward over time.The stratiform cloud region north of the cyclone exhibited cloud-top brightness temperatures ranging from -10 ℃ to -25 ℃,within the “cloud seeding temperature window.” Cloud-top heights ranged from 8 to 11 km,indicating a deep and well-developed cloud system.During the precipitation development phase,the cloud system consisted primarily of ice-phase particles.Above 3.8 km,ice crystals dominated,originating from small ice crystals falling from the convective region and nucleated ice crystals in the stratiform cloud.These crystals underwent slow deposition growth as they descended.Between 1.8 and 3.8 km,the cloud radar reflectivity factor increased significantly,reflecting processes such as deposition growth,aggregation,and riming of ice crystals.Below 1.8 km,precipitation transitioned to rain as ice crystals melted upon exiting the cloud layer.In the dissipation phase,cloud-top and cloud-base heights decreased,and the ice crystal layer thinned.After 12:00 BST,a shift in high-altitude wind direction to the west dispersed upper-level ice crystals,inhibiting further deposition growth and reducing cloud-top height and ice crystal content.Deposition growth remained dominant above 3.8 km,while aggregation and rimming prevailed between 1.0 and 3.8 km,with fragmentation observed in the 2.8—3.8 km range.During this phase,relatively low liquid water content limited the precipitation process,diverging from the typical “seeding-supply mechanism”. This study provides valuable insights into the cloud microphysical processes associated with stratiform precipitation,offering a basis for monitoring and identifying conditions suitable for artificial weather modification.While the findings enhance understanding of weather modification conditions,they are based on a single case.Future studies should expand to multiple cases to refine the understanding of cloud structures and precipitation processes,ultimately improving the scientific foundation for artificial weather modification operations.