Frozen soil is the essential component of terrestrial cryosphere.Soil freeze-thaw process （SFT） affects soil structure， soil hydrothermal transfer， and biogeochemical processes， thereby influencing local and global weather and climate through land-atmosphere interaction.Therefore， it is of importance to explore SFT for human activities in frozen soil regions and for studying weather and climate change for local and remote regions.This paper reviews the effects and physical mechanisms of gravel and soil organic matter （SOM） on soil thermal and hydrological parameters and SFT， and summaries achievements in parameterizations of SFT， with focuses on soil thermal conductivity， hydraulic parameters， water-heat coupled parameterization， and freeze-thaw fronts.Gravel （SOM） has higher （lower） thermal conductivity and lower （higher） heat capacity， and thus they have different effects on the soil heat transfer and vertical distribution of soil temperature.Additionally， the existences of gravel and SOM change soil porosity， matrix capillary and adsorption， thereby affecting the transfer and vertical distribution of soil water content.Previous studies show that： （1） the Johansen scheme and its derivatives are widely incorporated into land models to calculate soil thermal conductivity.In consideration of the effect of gravel and SOM on soil thermal conductivity， the Balland-Arp scheme， a derivative of the Johansen scheme， better describes soil thermal conductivity during SFT.The thermal-hydro-deformation interaction thermal conductivity scheme comprehensively describes the water-heat coupling and frost heave impacts， resulting in more accurate simulation of characteristics of soil thermal conductivity in the drastic phase transition.（2） Supercooled water parameterization scheme can depict the existence of liquid water below 0 °C in soil.Variable freezing threshold parameterization depicts that water phase transition to ice happens below 0 °C.Taking account of the impedance of soil ice to liquid water infiltration improves model performance in simulating the hydrological process in frozen soil.（3） The water-heat coupled scheme is proposed to capture the synergistic changes of both thermal and hydraulic processes in soil， especially the interaction between water and heat.These schemes describe complex physical mechanisms during SFT in detail， and therefore can reduce model biases in simulating the transfer and vertical distribution of heat and water in soil.（4） Most numerical models with an isothermal framework assume that phase change of soil water/ice occurs in the middle of each soil layer and the entire model layer is either frozen or thawed， resulting in serious misestimates of the freeze-thaw depth in soil.To solve this problem， the freeze-thaw front parameterization scheme is developed and incorporated into models.Despite great progress in simulating SFT， there are still some deficiencies.Saline soil lowers freezing point of soil water， but this has not been considered in most current numerical models； although the impact of SOM on soil thermal and hydraulic conductivities has been taken into account， the content of SOM and its vertical distribution is not realistically associated with the growth of vegetation roots； the entire soil depth is not sufficient deep and the assumption of zero heat flux through bottom of soil in numerical models is not the case in the reality.Therefore developments of parameterization schemes to simulate the transfer and distribution of soil salt， to depict the root growth and vertical distribution of SOM， to take account of the influence of deep soil layers and real bottom boundary conditions are among the possible improvements in the future land models to improve the simulation of SFT.

We bias-corrected and assessed summer precipitation data over the Qinghai-Xizang Plateau （QXP） based on 18 models from the Coupled Model Intercomparison Project Phase 6 （CMIP6）.Our assessment of CMIP6 data， conducted for the period 1979-2014， centered on the performance of both the ensemble and individual models.We evaluated the CMIP6 data before and after bias correction， according to considering mean precipitation and extreme precipitation.The results highlight the correction method's dependence on ERA5 reanalysis data quality over the QXP.Although corrected mean summer precipitation over the QXP shows improvement in bias and bias rate， it exhibits inferior interannual time-varying characteristics compared to pre-corrected data.Most of the models were able to better simulate the spatial variability characteristics of mean precipitation over the QXP， gradually increasing from northwest to southeast from 1979 to 2014.Pre-correction precipitation data overestimates precipitation over the QXP with a bias rate of 60.4%， while corrected data is relatively underestimated with a deviation rate of -13.9%.The mean bias of the corrected data from ERA5 is only 0.003 mm·d^-1， with a spatial correlation as high as 0.999.Spatial trend analysis of observed data indicates a slight increase in summer precipitation over most of the TP from 1979 to 2014， with a significant decreasing trend only along the eastern edge.Both pre- and post-corrected data generally capture this spatial distribution， though pattern correlation coefficients of most individual uncorrected CMIP6 models do not exceed 0.5.Comparing with the interannual variability of the precipitation data obtained from observations， the pre-corrected data overestimate the precipitation on the QXP， while the post-corrected data are underestimated in comparison with the observation results.Extreme precipitation is selected by determining the 95% thresholds， a revealing a spatial distribution similar to the mean annual precipitation， increasing from northwest to southeast.This feature is well captured by some models， such as MRI-ESM2-0 （The Meteorological Research Institute Earth System Model version 2.0） and ACCESS-CM2 （Australian Community Climate and Earth System Simulator Climate Model Version 2.0）.Earth System Simulator Climate Model Version 2）， the spatial correlation coefficients are 0.851 and 0.821， respectively， compared with the observations， but the spatial correlation of the corrected data decreases from 0.861 to 0.730， failing to accurately characterize the stepwise increase of extreme precipitation on the QXP.The deviation distribution of the corrected extreme precipitation data is similar to pre-correction data， with lower areas concentrated in the southern hinterland and eastern part of the QXP.The analysis of extreme precipitation contribution shows that both the observation results and the CMIP6 precipitation data indicate that the trend of extreme precipitation contribution is not obvious during 1979-2014.Among individual models， EC-Earth3-Veg （European Community Earth-Vegetation model version 3） and EC-Earth3 （European Community Earth Model version 3） and CanESM5 （The Canadian Earth System Model version 5） ranked high in several parameters， showing better simulation capability， while IPSL-CM6A-LR （Institute Pierre-Simon Laplace Climate Model 6A Low Resolution） ranked high in the mean precipitation deviation and extreme precipitation deviation.

Based on NCEP/NCAR reanalysis data and the daily precipitation data from 105 meteorological stations in the central and eastern Qinghai-Xizang Plateau from 1982 to 2020， we investigate the spatiotemporal anomalous characteristics and major falling areas of warm season extreme precipitation and typical circulation of large-scale extreme precipitation in the central and eastern Qinghai-Xizang Plateau.The results show that： （1） Total precipitation of central and eastern Tibetan Plateau in the warm season shows statistically significant increasing at the rate of 10.7 mm·（10a）^-1 （P<0.05） during 1982 -2020， but there are obvious interdecadal trend shifts in the late 1990s and late 2000s.The increase in extreme precipitation of central and eastern Qinghai-Xizang Plateau is most prominent after 2009， and the climate tendency rate is of 4~5 times greater than that of during 1982 -2020.In terms of the distribution of spatial climate tendency rates， the trend of extreme precipitation in the southern Qinghai-Xizang Plateau is opposite to that in the central and northern Qinghai-Xizang Plateau in the three periods.The increase of extreme precipitation in the northern Qinghai-Xizang Plateau is the most prominent during 1998 -2009， and the extreme precipitation in the southern Qinghai-Xizang Plateau experiences the interdecadal trend shifts of significant increase， significant decrease and significant increase.（2） The small-scale extreme precipitation in central and eastern Qinghai-Xizang Plateau shows statistically significant decreasing trend （P<0.1）， while the large-scale extreme precipitation exhibits statistically significant increasing trend （P<0.05） during 1982 -2020.According to the locations of precipitation center， the level 4 large-scale extreme precipitation can be divided into three types， that is， northeast type （A type）， southern type （B type） and southeastern type （C type）.（3） The difference of location and intensity of the West Pacific Subtropical High is the main factor， which leads to the difference of water vapor sources and the locations of large-scale extreme precipitation falling areas.When the A-type large-scale extreme precipitation occurs， the West Pacific Subtropical High is anomaly weaker and eastward， which leads to the water vapor mainly transported from the Pacific Ocean and the westerlies.When the B-type occurs， the West Pacific Subtropical High is anomaly stronger and extending westward and southward， consequently， the water vapor mainly transported from the Indian Ocean and the Bay of Bengal.When the C-type occurs， the West Pacific Subtropical High is anomaly stronger， extending from the westward and northward， resulting in the water vapor mainly transported from the northwest Pacific Ocean， the South China Sea and the Bay of Bengal.

The China Meteorological Forcing Dataset（0.1°×0.1°） from 1979 -2018 was used as atmospheric forcing data to drive CLM5.0 （Community Land Model version 5.0） to simulate soil temperature and moisture changes in the Qinghai-Xizang Plateau region from 1979 to 2018.Divide the soil freeze-thaw process into two stages： freezing period and thawing period.By comparing and validating CLM5.0 simulation with site observation data， assimilation data （GLDAS-Noah）， and satellite remote sensing data （MODIS soil temperature data and ESA CCI-COMBINED soil moisture data） in two stages， this study explores the applicability of CLM5.0 simulation of soil temperature and moisture in the Qinghai-Xizang Plateau.The results indicate that： （1） CLM5.0 can accurately describe the dynamic changes in soil temperature and moisture at stations on the Qinghai-Xizang Plateau.The soil temperature and moisture simulated by CLM5.0 have consistent variation characteristics with the observed data and are numerically close.The accuracy of CLM5.0 simulation is higher than that of GLDAS Noah.CLM5.0 provides a more accurate description of soil temperature at the stations.（2） CLM5.0 can accurately describe the soil temperature and moisture characteristics during the freeze-thaw process in the Qinghai-Xizang Plateau.CLM5.0 simulated soil temperature and moisture show a significant positive correlation with MODIS and ESA CCI-COMBINED remote sensing data on the Qinghai-Xizang Plateau， with correlation coefficients mostly above 0.9.CLM5.0 has relatively better simulation ability for soil temperature in Qinghai-Xizang Plateau areas.CLM5.0 has better simulation ability for soil moisture during thawing periods than during freezing periods.CLM5.0 overestimates the soil temperature of the Qinghai-Xizang Plateau as a whole， with an average deviation mostly between 0~4 ℃.The average deviation of soil moisture simulated by CLM5.0 is mostly between -0.1~0.1 m³·m^-3， and the average deviation of soil moisture during thawing period is relatively small.（3） The soil temperature and moisture data from CLM5.0 simulation， GLDAS-Noah， MODIS， and ESA CCI-COMBINED remote sensing all have similar spatial distribution characteristics， with higher similarity in the spatial distribution characteristics of soil temperature.CLM5.0 has higher spatial resolution and more precise soil stratification， which can better describe the details of soil temperature and moisture.（4） The CLM5.0 simulation data shows an overall warming and drying trend in the Qinghai-Xizang Plateau， while the MODIS and ESA CCI-COMBINED remote sensing data show an overall warming and moistening trend.The trend of soil temperature changes simulated by CLM5.0 is relatively accurate， while there is a greater deviation in the trend of soil moisture changes.

From 22:00 on September 6， 2023 to 04:00 （Beijing Time） on September 7， Xiahe County in Gansu Province experienced severe convective weather， with short-term heavy rainfall in some areas， causing flash floods in Guoning Village， Xiahe County， resulting in casualties.In this study， the characteristics of Radar Quantitative Precipitation Estimation （Radar-QPE）， FengYun 4B Quantitative Precipitation Estimation （FY4B-QPE）， and CMA Multi-source Precipitation Analysis （CMPA） precipitation products were contrastive analyzed based on meteorological station observations.These precipitation data were used to drive the hydrodynamic hydrological model and evaluate the effect of different precipitation data in the flash flood simulation.The results showed that： （1） Among the 12-hour cumulative precipitation amounts， CMPA demonstrated higher accuracy in terms of the position of large value areas and differences in local precipitation levels； Radar-QPE was closer to AWS （Automatic Weather Station） in terms of cumulative precipitation level but showed significant differences in spatial distribution； FY4B-QPE overestimated the cumulative precipitation level by 33.8%.（2） In terms of hourly distribution， CMPA was most similar to AWS in terms of temporal evolution， spatial distribution， and precipitation level； Radar-QPE's peak values were smaller， and the peak times were lagged， with negative deviations in precipitation being dominant； FY4B-QPE's peak values and peak times were consistent with reality， but there were deviations in the start and end times of precipitation， with positive deviations in precipitation being dominant.（3） In the hydrological simulation study， CMPA， Radar-QPE， and FY4B-QPE all overestimated water levels， but the timing of water level peaks was more consistent with AWS.CMPA performed best in terms of RMSE （Root Mean Square Error）， NSE （Nash Efficiency Coefficient）， and Bias （Relative Deviation）， followed by Radar-QPE， and FY4B-QPE performed relatively poorly.Although existing site-observed precipitation cannot fully meet the needs of research and early warning for small and medium scale mountain floods， the high precision of CMPA data could effectively supplement the deficiencies of traditional meteorological observation stations to some extent.Meanwhile， the algorithms and accuracy of Radar-QPE and FY4B-QPE needed to be further improved and enhanced.

Purposes Methods Extreme weather and climate events have been exhibiting an intensification under global warming.This intensified extremity thus augments the damaging impacts on both society and the economy.In the Northern Drought-prone Belt （NDPB）， extreme drought events are becoming more frequent and more intense with a broader distribution.In this study， by using statistical analysis and composite analysis， characteristics of the main factors affecting prolonged spring-summer extreme drought events in NDPB are analyzed based on the meteorological drought composite index， precipitation and near-surface air temperature data observed by meteorological stations， reanalysis dataset， sea surface temperature， snow cover， and the sea ice concentration data.Findings Conclusions Results show that the main circulation factors are as follows： the eastward propagating wave trains from Baffin Bay in March， a “positive-negative-positive-negative-positive-negative” geopotential height anomaly from the south of Hudson Bay to the east of Lake Baikal in May， an eastward wave train near the 60°N latitude， the Silk Road wave train and the eastward， weak Western Pacific Subtropical High in June； the main external forcing factors are listed below： the phase transition from La Ni?a to El Ni?o， warmer sea surface temperature over the Indian Ocean basin and the central North Atlantic； the shrinking snow cover in the mid-to-high latitudes of Eurasia and between 40°N and 60°N of North America， a snow cover reversal from abnormally high to abnormally low over the Qinghai-Tibet Plateau， a “negative-positive” sea ice concentration anomaly with less near Baffin Bay and Davis Strait but more near Greenland Sea， and a “positive-negative-positive” sea ice concentration anomaly from the Barents Sea to the Kara Sea.

El Ni?o-Southern Oscillation （ENSO） is the most prominent interannual climate mode over the tropical Pacific， which is characterized by a periodic and phase-locked evolution of sea surface temperature anomalies （SSTA）.From the perspective of ENSO cycle， this study objectively classified the SSTA evolution of ENSO from 1961 to 2021 into two results using K-means clustering method （KMA）： 3 or 5 types of ENSO cycle.When it is classified into 3 types， the basic characteristics of ENSO cycle are warm-developing， warm-decaying， and cold-persistence.When it is classified into 5 types， the discrepancies of intensity and zonal distribution of the development and decay processes between super-strong and normal events are highlighted.To further explain these discrepancies， this study employed a KMA considering the Principal Component Analysis （Empirical Orthogonal Function）.Based on the two EOF leading modes which reflects the zonal symmetric and asymmetric development modes， the zonally symmetric and asymmetric development processes of the ENSO cycle are divided.Combined with the KMA clustering analysis， it is further found that zonally asymmetric development mode together with the zonally consistent development mode jointly lead to the zonal asymmetric development speed of ENSO cycle.Reconstruction of the zonally homogeneous and asymmetric evolution modes of ENSO reveals that wind and thermocline thickness anomalies may be key factors controlling the zonal asymmetric evolution of SSTA.This study objectively classified different types of ENSO evolution， providing reference for climate dynamics and impacts of ENSO diversity.

Atmospheric rivers significantly impact the ocean-land-ice-atmosphere interaction around Antarctica.However， the shortage of in situ observations limits people’s understanding， bringing considerable uncertainty in numerical simulation results and products.This study utilized ship-borne radiosonde data collected during the 37^th Chinese Antarctic Expedition to evaluate four kinds of state-of-the-art atmospheric reanalysis datasets （ERA5， CFSv2， JRA-55， and MERRA-2） during an atmospheric river event in the Southern Ocean.All reanalysis provide acceptable descriptions of integrated water vapor transport （IVT） compared with the observation， even during the atmospheric river events.However， all reanalyses overestimated the humidity and underestimated the wind speed across the entire atmospheric column （from surface to 300 hPa）.Moreover， all reanalyses， except for ERA5， failed to capture the variation in the covariance term between humidity and wind speed in the vertical direction； the latter contributes to a considerable bias in the IVT of reanalyses.The ERA5 demonstrates superior performance during the observation period， especially in humidity and low-level jet profiles when the atmospheric river arrives at the observation site.In this study， ERA5 seems to be the best atmospheric reanalysis for studying atmospheric rivers in the Southern Ocean.

In order to solve the problem of the traditional remote sensing drought index focuses on the monitoring of a single response factor and lacks a complete analysis of drought.In this paper， we selected TVDI， RVI， PDI， and GVMI daily products estimated from remote sensing data as independent variables， and MCI calculated from meteorological data at the adjacent moments of satellite transit as dependent variables， and uses the Random Forest Regression （RFR） model to construct a integrated remote sensing drought monitoring model.The results show that the accuracy of RFR model is better than that of the Ordinary Least Squares （OLS） model in bothtraining data and test data.The R value of the RFR training data is 0.97， the RMSE is 0.33， the R value of the RFR test data is 0.90， and the RMSE is 0.53.The R value of the OLS training data is 0.78， the RMSE value is 0.73， the R value of the OLS test data is 0.76， and the RMSE value is 0.79.The comparisons of RFR and OLS model in R and RMSE show that the RFR model is superior than the OLS model in the characterization of regional drought.In the application of drought monitoring in Southwest China in 2022， the RFR results are consistent with the spatiotemporal distribution of the MCI index， which can better characterize the spatial and temporal dynamics of the regional drought， reflecting the practicality of the RFR model in the actual drought monitoring process.However， the accuracy of RFR model is related to the number of regional stations and the spatial distribution of stations， and the accuracy of the RFR model is higher in areas with a large number of stations and uniform distribution of stations.

The inland arid zone of northwestern China has two climate regimes， monsoon-dominated and westerly-dominated， and is also an area of monsoon-westerly interaction.The study of climate and environment in this region is of great theoretical and practical significance， and it is also a frontier issue that has attracted much attention in global change research.This paper summarized the research progress on the definition of the monsoon zone， the westerly belt and their boundary zones， the progress on the climatic impacts of these two circulations and their interactions as indicated by instrumental measurements and proxies.Future research needs to focus on the westerly-dominated climate regime and its interaction with the monsoon， spatial definition， and driving mechanisms at high resolution and large spatial and temporal scales.These studies can promote research on the response to global change and its dynamic mechanism， and provide scientific support and theoretical basis for regional desertification management and national ecological security guarantee in arid northwestern China.

As one of the most sensitive natural elements in response to climate change， snow cover has a significant effect on the Earth's surface radiation balance and water cycle.The global snow cover area is approximately 46×10⁶ km² and 98% of the snow cover distributed in the Northern Hemisphere.Due to its distinctive radiative properties （high surface albedo） and thermal characteristics （low thermal conductivity）， changes in snow cover play a crucial role in the energy balance and water cycle between land and the atmosphere.In the context of global warming， the snow cover in the Northern Hemisphere has been decreasing in recent decades， especially in the spring.Therefore， the capabilities of CMIP6 （Coupled Model Intercomparison Project Phase 6） data to simulate the snow cover area were evaluated based on observational data and the future changes in snow cover were also assessed using a multi-model average in this study.By using the snow cover products from the National Oceanic and Atmospheric Administration/National Climatic Data Center （NOAA/NCDC） as reference data， the Taylor skill scoring， relative deviation， and other methods were applied to evaluate the spring snow cover （SCF） data in the Northern Hemisphere from the International Coupled Model Comparison Project Phase 6 （CMIP6） during 1982 -2014.The ensemble average of the top three models was further selected to predict the spatiotemporal variation characteristics of SCF under different emission scenarios from 2015 to 2099， providing insights into the modeling capabilities of CMIP6 and future changes in SCF.During the historical period （1982 -2014）， SCF was characterized by high coverage at high latitudes and low coverage at low latitudes， with high-altitude regions such as Tibetan Plateau and eastern Asia having higher snow coverage than those at the same latitudes.Overall， 68.37% of the regions in the Northern Hemisphere showed a decreasing trend in SCF， while 31.63% of the regions showed an increasing trend in SCF.Most CMIP6 models overestimated SCF in the Tibetan Plateau region compared to the reference data.In addition， most models simulated larger areas with a decreasing trend in SCF than those evaluated by the reference data and underestimated SCF in March， April， and May.Various models exhibited differing abilities to simulate SCF， with NorESM2-MM， CESM2， BBC-CSM2-MR， NorESM2-LM， and CESM2-WACCM demonstrating superior capabilities.The Multi-Model Ensemble Mean （MME） consistently outperformed individual models， closely aligning with observational data.There were significant differences in the ability of the CMIP6 models to simulate the spatial distribution， inter-annual variation trends， and intra-annual variations of SCF in the Northern Hemisphere.At the end of the 21st-century （2067 -2099）， SCF in the Northern Hemisphere exhibited a decreasing trend in most areas， which intensifies with increasing emission intensity.The changes in SCF were relatively consistent under different emission scenarios before 2040.SCF maintains a steady state under the SSP1-2.6 scenario， showed a slight decreasing trend under the SSP2-4.5 scenario， and showed a significant decreasing trend under the SSP5-8.5 scenario after 2040.

Plant diversity significantly affects the structure and function of ecosystems and plays a crucial role in soil organic carbon sequestration.In the past， the effects of plant diversity on soil organic carbon were mostly carried out under artificial plant diversity control， indicating that high plant diversity significantly promoted soil organic carbon accumulation.However， in natural grassland ecosystem， the research on the effect of plant diversity on soil organic carbon is relatively weak.In this study， 15 typical alpine meadows in the northeastern part of the Qinghai-Xizang Plateau were selected as sample sites.By measuring plant above-ground and subsurface biomass， soil pH value， soil microbial biomass carbon and nitrogen， soil organic carbon， granular organic carbon， mineral-bound organic carbon， total nitrogen and total phosphorus， etc.， the effects of plant diversity on soil organic carbon sequestration under natural conditions were explored.It provides theoretical basis for the change of soil carbon storage and scientific management of grassland.The results showed that plant diversity significantly increased plant coverage and aboveground biomass （P < 0.01）， but had no significant effect on underground biomass in different soil layers （0~20 cm and 20~40 cm）.In 0~20 cm and 20~40 cm soil layers， the increase of plant diversity significantly increased soil microbial biomass carbon and organic carbon contents （P<0.05）， but had no effect on microbial biomass nitrogen in different soil layers.According to the classification of soil organic carbon， there was a significant positive correlation between plant diversity and soil mineral bound organic carbon content （P<0.01）， but no correlation with soil particulate organic carbon content.In conclusion， in the alpine meadow of the Qinghai-Xizang Plateau， higher plant diversity under natural conditions has a significant promoting effect on soil organic carbon content， which is mainly reflected in the increase of mineral binding organic carbon content.This study provides new insights and theoretical basis for the relationship between plant diversity and soil carbon pool in grassland ecosystem.

Photosynthetically Active Radiation （PAR） spectrum， in visible light， is the wavelength range sensitive to plants and can be absorbed by them for photosynthesis.The characteristics of ground PAR spectrum directly affect the growth， development， morphology， physiological metabolism， yield， and adaptability of plants.In order to further understand the distribution characteristics of PAR in high-altitude areas of Xizang， this study utilized the International High-Precision Solar Spectroradiometer to conduct field observations of the PAR spectrum characteristics in the Mt.Everest， Shigatse， Lhasa， and Nyingchi regions of the Qinghai-Xizang Plateau from 2021 to 2022.The observations found that during the winter and summer solstices on the Qinghai-Xizang Plateau， the variation in PAR was significant.The peak monochromatic radiation illuminance of PAR at Mt.Everest during the summer solstice ［1251 mW·（m²·nm）^-1］ to the winter solstice ［1935 mW·（m²·nm）^-1］ fluctuated by up to 684 mW·（m²·nm）^-1.The winter solstice integrated value of PAR spectrum at Mt.Everest （309.86 W·m^-2） was 41.61% lower than the AM0 standard spectrum integrated value of PAR （530.67 W·m^-2）， and 28% lower than the AM1.5 standard spectrum integrated value of PAR （429.83 W·m^-2）.During the summer solstice， the PAR spectra at Mt.Everest， Shigatse， and Lhasa in Xizang all exceeded the AM1.5 standard spectrum at noon and were close to the AM0 standard spectrum.In Shigatse， Xizang， during the spring equinox and autumn equinox， the peak PAR spectra were 1699 mW·（m²·nm）^-1 and 1696 mW·（m²·nm）^-1 respectively， with peak values being nearly identical.This similarity is due to the same local solar altitude angle at noon （e.g.， 59.84 radians in Shigatse） during the equinoxes at the same observation point on the Tibetan Plateau， assuming other factors affecting the spectrum are the same.Comparison of observations between the Qinghai-Xizang Plateau and low-altitude areas such as Beijing， Anhui's Lu'an， and Henan's Puyang revealed that on a clear day near the winter solstice （November 20， 2021）， the integrated value of PAR spectrum at high-altitude Mt.Everest （309.86 W·m^-2 was 17.19% higher than that in low-altitude Lu'an， Anhui （264.41 W·m^-2）； on a clear day near the summer solstice （June 3， 2021）， the integrated value of PAR spectrum at high-altitude Mt.Everest （487.41 W·m^-2） was 23.66% higher than that in low-altitude Beijing （394.15 W·m^-2）； near the autumn equinox （September 19， 2021）， the integrated value of PAR spectrum in low-altitude Beijing （315.23 W·m^-2） was only 71.24% of that at high-altitude Mt.Everest （442.49 W·m^-2）； near the spring equinox （March 19， 2021）， the integrated value of PAR spectrum in high-altitude Shigatse （413.34 W·m^-2） was 64.75% higher than that in low-altitude Puyang， Henan （261.82 W·m^-2）.The results indicate that the integrated value of PAR spectrum is positively correlated with altitude， with higher altitudes corresponding to larger integrated values.Additionally， through observations of PAR spectra on clear days throughout the year， it was found that there are certain temporal variations in spectral radiation illuminance.Specifically， the spectral radiation illuminance is lowest at the winter solstice， then increases daily until reaching its peak the following year after the spring equinox， decreases daily after the summer solstice， reaches its lowest point again at the winter solstice after the autumn equinox， with the spectral radiation illuminance characteristics being basically the same during the spring equinox and autumn equinox.

The summer precipitation in eastern China has significant interdecadal variaitons， which can impact the spatiotemporal variability of drought and floods as well as people’s living.Hence， it is important to understand and predict the interdecadal variations of summer precipitation in eastern China.The Coupled Model Intercomparison Project Phase 6（CMIP6） can help to understand the changes in climatic factors and predict their future changes.What is the capability of CMIP6 models in simulating the interdecadal variations of summer precipitation in eastern China？ What are the potential reasons？ In order to understand the above questions， this study evaluated the capability of CMIP6 models in simulating the interdecadal variations of summer precipitation in eastern China， using the CN05.1 observational data， ERA5 reanalysis data， NOAA sea surface temperature （SST） data and the output of historical experiments from 30 CMIP6 models.The results indicate that during 1961 -2014， the summer precpitation over eastern China underwent two notable interdecadal variations， which occurred in the mid-1970s and early-1990s.During these two interdecadal variations， the simutaneously enhanced/weakened Western Pacific Subtropical High （WPSH） and South Asian High（SAH） as well as the interdecadal change in tropical Pacific SSTs induce changes in the winds and divergence at the 850-hPa and 200-hPa pressure levels over southern China （18°N -30°N， 105°E -122°E）.The associated interdecadal changes in water vapor flux， meridional circulation and atmospheric stability in lower troposphere led to interdecadal changes in summer precipitation in eastern China.Although the CMIP6 models can well simulate the climatology of summer precipitation in eastern China， only 5 out of 30 models have relatively good capability in simulating the aforementioned two interdecadal variations in summer precipitation， which have taylor scores larger than 0.7， while the other models have relatively poor skill.In addition， the best multi-model ensemble （BMME） means show better skills in simulating these two interdecadal variations in summer precipitation than individual models.This is because the BMME can well simulate the simultaneous change in WPSH and SAH as well as the change in tropical Pacific SSTs， which leads to a good simulation of the meridional circulation over eastern China， resulting in a good simulation of the summer precipitation anomalies south of the Yangtze River.

South China （SC） is one of the regions with the most annual precipitation in China.Under the background of global warming， there had been significant changes in precipitation at regional and scale levels， the area of dry- and wet-season precipitation was expanding， and regional extreme precipitation events showed a significant upward trend in SC， but the changes and impacts of different types of precipitation were not the same.To better understand how different types of precipitation in SC respond to global warming， this paper investigated the characteristics of convective precipitation （CP） and large-scale precipitation （LSP） in SC based on ERA5 reanalysis precipitation dataset from 1960 to 2022 using linear correlation， trend analysis and wavelet analysis.The results showed that： （1） SC was dominated by LSP in winter while CP in other seasons.（2） CP and LSP in SC showed an increasing trend in winter， but most of CP showed a decreasing trend in other seasons.CP in SC had a relatively significant 2~4 years cycle from the 1980s to the beginning of the 21st century in winter， as well as there was an interdecadal characteristic of shifting from more to less in the 1990s to the beginning of the 21st century in spring， but the significant cyclical variations were mainly found in the period before the 1990s in autumn.In all seasons except winter， the changes in LSP were consistent with CP.（3） The total precipitation （TP） from April to October in Guangdong and Guangxi was mainly CP （CP accounts for about 65% of TP）， with the largest proportion in August （71.8% in Guangdong and 69.0% in Guangxi）.On the other hand， the proportion of CP in the first rainy season （up to 80% in May） was significantly higher than in the second rainy season in Hainan.Additionally， the proportion of CP remained at about 50% even in autumn and winter.（4） The diurnal variation intensity of CP and LSP was strongest in Hainan while the intensity of CP was the weakest in Guangxi.The peak periods of the strongest precipitation in Guangdong， Guangxi， and Hainan occured respectively from 13:00 to 17:00 （Beijing time， the sameas followed）， 15:00 to 17:00， and 14:00 to 16:00.The LSP peaked between 09:00 and 17:00 in Guangdong， and it started to strengthen from 04:00 and weakened in the afternoon， with the strongest period around 10:00 in Guangxi， for Hainan， the strongest period was 12:00 -17:00 before August， but 15:00 -16:00 after late September.In conclusion， the characteristics of precipitation varied with different seasons and types.Therefore， it was necessary to continue considering the impact of different types of precipitation in future research.

Based on the daily minimum temperature station data provided by the National Meteorological Information Centre from 1980 to 2022， the month-by-month reanalysis data of the NCEP/NCAR， and the monthly Sea Surface Temperature （SST） data from the NOAA， by using EOF， simple linear regression and T-N wave flux methods， the main anomalous spatial and temporal characteristics of winter cold wave frequency in the southern China are studied， and the influence mechanisms of atmospheric circulation and winter Atlantic Sea Surface Temperature Anomaly （SSTA） on it are also analyzed.The results show that： （1） The large value areas of winter cold wave frequency are mainly located in the eastern and central of the southern China， with an approximately "inverse C" distribution.There are three main frequency anomalous modes， namely， regionally consistent anomaly， north-south antiphase anomaly and tripole anomaly patterns according to the EOF analysis， among which the regionally consistent anomaly reflects the overall anomalous spatial and temporal characteristics of the winter cold wave frequency in the southern China.（2） The negative phase of the North Atlantic Oscillation （NAO）， the strong Caspian Sea - Tibetan Plateau ridge and the East Asian Trough located to the north and to the east， the weak in the north and strong in the south of the Siberian High， the strong temperate jet and the weak subtropical jet are the key circulation systems affect the winter cold wave frequency in the southern China.The cold air pool is located in the Western Siberia.The high and low level circulation systems cooperate together to make the cold air from Western Siberia move southward to the vicinity of the Caspian Sea， and then transport eastward along the northern side of the Tibetan Plateau， then move southward into the southern China along the eastern side of the Tibetan Plateau， resulting in the increase of the winter cold wave frequency in the whole southern China.（3）In winter， the “+”“-”“+” tripolar SSTA in the North Atlantic can stimulate the -NAO atmospheric circulation anomalies through the exchange of heat fluxes between air and sea and the Rossby wave energy anomalies.The Rossby wave energy propagates from the North Atlantic to East Asia along the south and north two paths， and stimulates the corresponding anomalous waves， which enhance the key circulation systems in the north and south affecting the cold wave frequency in the southern China.When the North Atlantic SSTA exhibits an inverse "C" anomaly in spring， and there is a trend of developing into a “+”“-”“+” tripolar pattern in summer and autumn， the winter cold wave frequency in the southern China can be predicted to more.

In this study， the improvements of lake dynamic module parameters in the literature were added to WRF-Lake （WRF4.4.1） at first， then six microphysical schemes， five cumulus convection schemes and two boundary layer schemes were selected.A total of 60 WRF-Lake simulations with different parameterization schemes were carried out from July 5 to 13， 2008 in the Nam Co Lake area.Sensitivity experiments were conducted to comparatively analyze the effects of different parameterization scheme combinations on atmospheric boundary layer variables.The "ranking method" was employed to comprehensively evaluate the simulation capabilities of different parameterization schemes in the summer atmospheric boundary layer over Nam Co Lake.The results indicated that the model captures the overall spatial and temporal distribution characteristics of the summer average two-meter temperature in Nam Co.However， the simulated values of the two-meter temperature over the lake were higher than the land surface data.Due to the selection of cumulus convection parameterization schemes and the impact of model performance， there was significant differentiation in the simulation effects of precipitation among experimental groups， leading to varying degrees of overestimation of daily precipitation.The daily average variations of latent heat fluxes showed the best correlation with observational values， while sensible heat and wind direction exhibited relatively good performance， and wind speed showed the least satisfactory results.Overall， comprehensive analysis of the simulation capabilities of each experimental group for the summer atmospheric boundary layer over Nam Co Lake revealed that Scheme 58 （SBU-Tiedtke-MYNN3） performed the best in simulations of 2 m temperature， daily precipitation， 10 m wind fields， and surface heat fluxes.The RMSE value for two-meter temperature and daily precipitation was 2.33 °C and 10.48 mm， respectively.The correlation coefficient for the daily average variation of 10 m wind speed was -0.41， and the ratio of standard deviations was 0.94.The correlation coefficient for the daily average variation of 10 m wind direction was 0.59， and the ratio of standard deviations was 0.73.The correlation coefficient for the daily average variation of sensible heat flux was 0.94， and the ratio of standard deviations was 1.89.The correlation coefficient for the daily average variation of latent heat flux was 0.89， and the ratio of standard deviations was 0.91.Therefore， it is recommended to use the aforementioned grid parameterization scheme for simulating the summer atmospheric boundary layer over the region of Lake Nam Co.

Considering the spatiotemporal variability of raindrop spectra is an effective way to improve radar quantitative precipitation estimation （QPE）.When using radar to estimate precipitation， the difference of raindrop spectrum is mainly manifested by the formulas of Z-R relation.Using the method of tile partitioning QPE （QPE_TP）， the precipitation estimation area is divided into tile partitions， the Z-R relationship is dynamically fitted using radar and automatic station data to carry out QPE within each tile.The QPE_TP effect was evaluated by utilizing six weather cases.From the evaluation indexes of QPE， the capability of QPE is significantly improved compared with the traditional fixed Z-R relationship and the global dynamic Z-R relationship.The QPE results are basically consistent with the heavy precipitation center， and the bias evaluation indexes are the least.The results show that the QPE_TP method is an effective way to improve radar QPE.

Using the observation data of 10 m surface wind speed at 173 meteorological stations in Northwest China from 1979 to 2020 and the ERA-5 reanalysis data， this study investigated the interdecadal variation characteristics of annual and seasonal surface wind speed in Northwest China and displayed the background circulation changes of interdecadal variation in 2003/2004.There are significant regional differences in the trend distribution of surface wind speed during 1979 -2020.The stations of the wind speed with increasing trend were mainly located in central and eastern Gansu， Shaanxi， southwest and northeastern parts of Xinjiang.The others stations generally showed the negative trends of wind speed.The number of the stations with decreasing trends of surface wind speed were obvious larger than that with decreasing trends.The average surface wind speed in the stations with decreasing （increasing） trends were larger （smaller） than that in whole northwest China.The distribution of the annual and four-season leading mode of surface wind speed were generally opposite to the trend distribution from 1979 to 2020.All the PC1s experienced the decadal shift around 2000.The second mode showed positive anomalies over the Ningxia Province and southern Shaanxi Province and negative over others regions.The PC2s both witnessed the decadal shifts in 1987/1988 and 2003/2004.Numerical studies investigated the decadal shift of surface wind speed northwest China in 1987/1988.Therefore， this study focuses on analyzing the possible circulation background of the decadal shift of northwest wind speed in 2003/2004.The composite difference of 500 hPa and 200 hPa geopotential heights between 2004 -2020 and 1988 -2003 presents the meridional dipole mode of Central Asia-Northern Europe in spring， the "Silk Road Pattern" in summer and autumn， the "Scandinavian" mode in winter， and the negative phase of the Arctic Oscillation in annual field.The circulation changes in four seasons and annual averages have their own characteristics.It needs further studies of the physical process of the influences of these circulation factors on the decadal shift of the surface wind speed in northwest China in 2003/2004.

Tropospheric ozone is an important air pollutant and greenhouse gas.It is harmful to human health and seriously harm the ecological environment.In this study， we use ozonesondes data from WOUDC （World Ozone and Ultraviolet Radiation Data Centre） during 2007 -2018 to evaluate tropospheric ozone column products from GOME-2A （Global Ozone Monitoring Experiment 2 aboard METOP-A） and Ozone Monitoring Instrument （OMI） satellite， as well as tropospheric ozone products from Updated Tropospheric Chemistry Reanalysis （TCR-2）.The results of the analysis show that in the equatorial American， subtropical， western European and Canadian regions， the correlation coefficients between GOME-2A and ozonesondes observations are up to 0.56， and the absolute values of the relative percentage deviations do not exceed 15%； in the eastern US.and western European regions， the correlation coefficients between OMI and ozonesondes observations are 0.65~0.72， and the standardized root-mean-square errors are 0.47~0.56； for the whole Northern Hemisphere region， the correlation coefficients between the TCR-2 tropospheric ozone column content and ozonesondes observations are 0.41~0.95， with standardized root-mean-square errors （RMSEs） of 0.18~0.48， which are better than the other two satellite data.Furthermore， the results indicate that the TCR-2 tropospheric ozone column trend is consistent with the trend direction of the ozonesondes observations.Through a more robust data assessment， it is evident that tropospheric ozone columns have increased in the equatorial Americas， Western Europe and China.Conversely， there has been a decrease in tropospheric ozone columns in the Arctic， Canada and the eastern United States.

This study aims to investigate the microphysical structure and hydrometeor conversion processes of convective clouds in the Yushu region of the Tibetan Plateau （referred to as the Plateau）.Using the WRF mesoscale numerical forecast model combined with observational data from the Yushu region in Qinghai during the summer of 2019， we analyzed a summer convective precipitation event in the Yushu area.The results show： （1） The 24-hour cumulative precipitation simulated by WRF is similar to the observed precipitation at the Yushu station.The spatial and temporal distribution of simulated precipitation echoes is generally consistent with Ka-band millimeter-wave cloud radar detection results， indicating the reliability of the simulation results.（2） Particles of different phases in precipitation clouds show distinct vertical distribution structures.The maximum centers of solid hydrometeors are all at relatively high altitudes， with cloud ice's maximum center being the highest at around 200 hPa.The maximum center of liquid hydrometeors is at 500 hPa.Water vapor's maximum center is at the lowest height， below 500 hPa， and its maximum value appears earlier than other particles.（3） In cloud microphysical conversion processes， cloud water makes the largest contribution to precipitation.Water vapor forms snow， graupel， and other hydrometeors through deposition.Ice-phase particles transform into graupel and snow particles through processes such as aggregation， Bergeron process， collection， and collision-coalescence.As they descend， ice-phase particles melt and combine with cloud water， accelerating the conversion of cloud water to rainwater.

Numerical models have risen to prominence as indispensable tools for the in-depth study of the water cycle and these extreme hydrological phenomena， gaining widespread application across the globe.To delve into the spatiotemporal evolution patterns of global terrestrial water circulation against the backdrop of climate change and to decipher the intricate feedback mechanisms among atmospheric， land， and hydrological systems， the exploration of coupled atmospheric-land-hydrological models has emerged as a pivotal area of focus in the international research landscape dedicated to atmospheric and hydrological studies.This paper embarks on its journey by meticulously reviewing and delineating the evolution of coupled models， shedding light on the distinct advantages of the Weather Research and Forecasting Model Hydrological （WRF-Hydro） modeling system.It methodically dissects the primary sensitivity parameters of the WRF-Hydro model， while extensively covering its applications in analyzing surface runoff， soil moisture， the energy-water cycle， and the intertwined atmospheric and hydrological processes.The discourse culminates in a forward-looking exploration of the future directions in the development of the WRF-Hydro coupled model.Emphasizing strategic advancements， the paper advocates for a concerted effort towards the creation of robust scale conversion schemes， the refinement of parameterization methods， and the execution of high-resolution simulations.These simulations are crucial for accurately mapping the spatial and temporal dynamics of atmospheric and hydrological variables within basins， thereby significantly enhancing the model's capacity to intricately depict the interactions among atmospheric conditions， land surface phenomena， and hydrological processes.This comprehensive approach underlines the imperative to deepen our understanding and improve our modeling capabilities， aiming at a more effective prediction and management of the impacts arising from climate change and extreme hydrometeorological events.

This study aims to improve the accuracy of simulating soil hydrothermal processes on the Qinghai-Xizang Plateau by introducing a novel soil stratification method combined with an integrated freeze-thaw gravel parameterization scheme.The region's unique topography and complex climate pose challenges for conventional numerical models in achieving precise simulations.The proposed scheme incorporates freeze-thaw parameterization， gravel parameterization， and refined vertical soil discretization， offering a more comprehensive representation of the soil characteristics and terrain complexity specific to the Qinghai-Xizang Plateau.To evaluate the effectiveness of the scheme， the BCC-CSM atmospheric circulation model， provided by the National Earth System Modeling Center， was used for testing.The results demonstrate that integrating freeze-thaw and gravel parameterization significantly improves the representation of soil hydrothermal distributions， especially during the winter and at greater soil depths.By refining the soil stratification to 20 and 30 layers， the simulations of soil temperature and moisture have been further enhanced.The 30-layer stratification yields the most accurate outcomes， followed closely by the 20-layer configuration.This approach notably reduces bias and root mean square error in soil temperature simulations， particularly in the central and western regions of the Qinghai-Xizang Plateau， with better performance in winter compared to summer.While soil moisture simulation accuracy lags behind temperature results， the stratification refinement reduces errors， particularly in shallow soil layers.The enhanced stratification also improves the correlation between simulated values and CRA data， strengthening the alignment between simulation and observation， especially in the central and western parts of the plateau.This research provides new insights into soil hydrothermal processes on the Qinghai-Xizang Plateau and offers critical methodology and technical support for future climate simulations and predictions.Moreover， the proposed integrated scheme holds significant potential for simulating soil hydrothermal processes in other plateau regions and may be applied across a wide range of fields.

Based on the hourly precipitation and 10 m wind speed data from the European Centre for Medium-Range Weather Forecasts （ECMWF） Fifth Generation Atmospheric Reanalysis dataset from 1979 to 2023， spatiotemporal changes and its corresponding clustering characteristics of compound precipitation and wind speed extremes （PWEs）， and the circulation characteristics in different periods in China were studied by using compound extreme events definition， trend analysis， spatial statistical analysis， and composite analysis.The results showed that PWEs in China were generally more frequent in the east than in the west.Among the PWEs in each subregion， the highest value was found in East China， where the mean value of the frequency and the days were the most in the range of 4~8 times and 4~8 d， and the corresponding area share reached 78.9% and 71.5%， respectively.The overall trend of PWEs from 1979 to 2023 had been decreasing， with the rate of change from 2011 to 2023 being 2.3 times and 3.4 times that of 1979 to 2010.The trend of PWEs from 1979 to 2010 showed an increasing trend in the central and eastern region of Eastern China， the central region of Southwest， and the northern region of Northwest， and the fastest decrease in Central China.From 2011 to 2023， positive trend values were mainly concentrated in the central region of China， and the Eastern China was the region of the fastest growth with rates of 0.96 times and 1.12 d per decade.In contrast， Southern China exhibited a decrease at rates of 0.81 times·（10a）^-1 and -0.77 d·（10a）^-1.The hot spot areas were concentrated on the west side of the Hu Line and coast region from 1979 to 2010， and the distribution of hot spot areas from 2011 to 2023 were consistent with the positive distribution of trend change.In addition， PWEs are the result of the combined effects of the high， middle， and low-level atmospheric layers.The enhancement of atmospheric high-level divergence and the weakening of the jet belt promote the upward movement of the atmosphere and the westward extension of the west Pacific subtropical high.The anomalous easterly wind in the middle atmosphere is conducive to the entry of water vapor from the periphery of the Northwest Pacific subtropical high into the inland regionof China， and the anomalous southeast wind in the low-level atmosphere further promotes the transport of water vapor to the inland region of China.The atmospheric circulation characteristics after 2010 also showed the development of PWEs events towards inland region of China.

The Three River Headwaters （TRH） region， known as the “Water Tower of China”， is a crucial freshwater source and an ecological barrier in China.Changes in precipitation concentration， seasonal precipitation amount， frequency， and intensity is a key process of water cycle in the context of global warming， holding significant implications for vegetation growth and water resource management in the TRH region.In this study， utilizing the CN05.1 daily precipitation gridded dataset from 1961 to 2020 prepared by the China Meteorological Administration， the Precipitation Concentration Index （PCI） were calculated， and the evolving patterns of precipitation concentration and intra-annual distribution in the TRH region were clarified.The climatology， relative interannual variability， long-term trends， and anomalies of annual and seasonal precipitation amount， frequency， and intensity were investigated.The results find that： （1） Precipitation in the TRH region exhibits a certain degree of concentration with PCI of 17.5.PCI increased from southeast to northwest， suggesting an increased precipitation concentration.Over the past 60 years， PCI has declined at a rate of -1.71% per decade， indicating a trend towards more evenly distributed monthly precipitation throughout the year.It’s noteworthy that the reduction in the proportion of precipitation during the growing season may have ramifications for agricultural production and ecosystem maintenance in the TRH region.（2） Over the past six decades， there has been a significant overall increase in precipitation amount and intensity during different seasons.However， precipitation frequency decreased during summer while increasing in other seasons.Enhanced precipitation intensity has predominantly contributed to the rise in precipitation amount during spring， summer， and autumn， while increased precipitation frequency has played a dominant role in elevating precipitation amount during winter.The increase rate in humidity during winter and spring was higher than that during summer and autumn.In spring， precipitation amount and intensity increased by 8.09% and 6.94% per decade respectively， while winter saw snowfall amount and frequency grow by 7.27% and 4.4% per decade.Also noteworthy is the distribution of droughts and floods in parts of the Yangtze River source area tends towards extreme， exacerbating the ecosystem vulnerability.（3） The regional average precipitation amount， frequency， and intensity in the TRH region have shown an increase of 1.36 mm， 0.024%， and 0.0056 mm·d^-1 per year over the past 60 years.The cumulative anomalies of precipitation amount， frequency， and intensity in the last 60 years were negative， with abrupt changes occurring in 2003， 1989， and 2003， respectively.There has been a significant decrease in precipitation frequency during the rainy season， coupled with a substantial increase in precipitation intensity.In contrast， both precipitation frequency and intensity during the dry season have experienced significant increases.These changes have been particularly pronounced in the past decade.This study can serve as a valuable reference for research concerning soil erosion， agricultural production， water resource management， and climate change in the TRH region.

Based on the hourly precipitation data of 3454 stations with dense space in Sichuan Province and the high-precision grid elevation data， the characteristics of precipitation in flood season in 7 regions of Sichuan Province in recent 10 years were analyzed.The results showed that： （1） There were 3 maximum centers of rainfall in flood season in Sichuan Province： Ya 'an in the southwest of the basin， Anxian in the northwest of the basin and Yanbian in the south of Panxi area.Anxian was the center of heavy rainstorm， and the rainfall in flood season was mainly contributed by the weather process of R ₂₄ ≥100 mm.（2） Affected by the trend of the mountains and the steepness of the terrain， the morphology and isoline gradient of the large value area around the basin had obvious differences.And the larger the accumulated rainfall in flood season， the more the sites were concentrated on the windward slope of the mountains.（3） The degree of night rain gradually weakened from southwest to northeast， among which Panzhihua was the most significant area of night rain in flood season.（4）The daily distribution of R ₂₄ ≥25 mm heavy rainfall was closely related to topography， and the heavy rainfall stations were only distributed in the steep transition zone between the western basin and the plateau.In addition， the percentage of stations with hourly rain intensity ≥50 mm·h^-1 in the rainstorm days in the northwest of the basin was the highest.（5） Compared with persistent heavy rain， the site distribution of persistent heavy rain was more significantly affected by the windward slope topography.

In order to achieve further improvement in the forecast accuracy of station temperatures and enhance the forecast capability for extreme temperatures， this study establishes a 24-hour national station daily maximum （minimum） temperature forecast model for Jiangxi Province based on the LightGBM machine-learning algorithm and the MOS forecast framework by using the surface observation data of 91 national stations in Jiangxi Province and the upper-air and surface forecast data of the ECMWF model from 2017 to 2019.The results of the 2020 evaluation show that the LightGBM model daily maximum （minimum） temperature forecast is consistent with the observed trend， and the annual average forecast is better than that of three numerical models， ECMWF， CMA-SH9 and CMA-GFS， two machine learning products， RF and SVM， and subjective revision products.In terms of the spatial and temporal distribution of forecast errors， the model's daily maximum （minimum） temperature forecast errors in winter and spring are slightly larger than those in summer and autumn； the daily maximum temperature forecast errors show the spatial distribution characteristics of "larger in the south and smaller in the north， and larger in the periphery than in the centre"， while the opposite is true for the daily minimum temperatures.In terms of important weather processes， the LightGBM model has the best prediction effect among the seven products in the high temperature process； in the strong cold air process， the LightGBM model is still better than the three numerical model products and the other two machine-learning models， but the prediction effect of the daily minimum temperature is not as good as that of the subjective revision products.After a simple empirical correction for the low-temperature forecast error in the strong cold air process， the model low-temperature forecast effect is close to that of the subjective revision product.The model significance analysis shows that the recent surface observation features also contribute to the model construction， and the results can be used as a reference for model improvement and temperature forecast product development.At present， the LightGBM model temperature forecast products have been applied to meteorological operations in Jiangxi Province.

Based on the meteorological observational data over Qinghai-Xizang （Tibetan） Plateau and atmospheric reanalysis dataset during 1961 to 2020， the snowfall variation characteristics over the Qinghai-Xizang （Tibetan） Plateau and its related corresponding circulation system were analyzed in this paper.Main conclusions are drawn as following： the spatial distribution of snowfall shows a uniformity with less in the northwest and more in the southeast.The characteristics of interannual and interdecadal variability are very evident.The interannual variability of the snowfall over Qinghai-Xizang Plateau was strong.The first mode of Qinghai-Xizang （Tibetan） Plateau snowfall anomalies is regional uniformity.In terms of the key circulation systems that affect Qinghai-Xizang （Tibetan） Plateau snowfall， when the snowfall over Qinghai-Xizang （Tibetan） Tibetan Plateau is more， the upper troposphere corresponds to the positive phase of the southern Eurasian （SEA） teleconnection， characterized as positive anomalies over the southwestern Europe， the Arabian Sea， and the northeast Asia， and negative anomalies over the Middle East and the Qinghai-Xizang （Tibetan） Plateau， while the Middle East jet is stronger； the positive （negative） phase of North Atlantic Oscillation （NAO） is conducive to more （less） snowfall over Tibetan Plateau， via modulating the SEA teleconnection and key circulation systems such as the Middle East jet stream.

Wind is one of the most important meteorological conditions in previous Winter Olympics， and it is the primary factor that affects the mountain events for Beijing Winter Olympics.Understanding the fine distribution law of wind can provide important theoretical basis for track construction， wind forecast and prevention measures.Using hourly observation data from surface automatic weather stations at different altitudes in Yanqing mountain area of Beijing Winter Olympics from December 2017 to March 2022， this study investigated the characteristics of local wind field during winter and early spring （Mar， Paralympics period） under complex terrain， focusing on comparing the frequency of wind speeds and directions， as well as the diurnal and seasonal variations.Firstly， all stations were grouped into four categories using the K-Means clustering algorithm， and Groups 1 to 4 represent the low-elevation Yangqing suburb area， the northeastern foothills transition area， the southwestern transition area and the high-elevation mountain top area， respectively.Subsequently， fine-grained characteristic analysis was conducted on each group separately.Results show that： （1） The frequency of strong winds is closely related to the altitude， with higher altitudes generally having a higher frequency of strong winds.In Groups 1~2 （altitude below 1000 m）， the frequency of light winds （≤3.3 m·s^-1） exceeds 80%， while the proportion of strong winds （≥10.7 m·s^-1） is 0%.In Group 3 （above 1000 m）， the frequency of light winds decreases to below 75%， and strong winds occasionally occur for less than 1%.In Group 4 （above 1800 m）， there is a significant shift in the wind speed frequency distribution， with the frequency of strong winds increasing to above 10%， which is much higher during winter compared to early spring.（2） There are significant local variations in the distribution characteristics of wind directions.Group 4 is primarily dominated by large-scale winter monsoonal circulation， resulting in a prevailing northwesterly wind， with rare concurrence of other wind directions.Groups 1~3 are influenced by a combination of large-scale circulation， valley wind circulation and underlying surface conditions， leading to different frequencies for each wind direction.（3） The diurnal variation exhibits contrasting characteristics between high and low elevations.Groups 1~3 show lower wind speeds at night and higher wind speeds during the day， while Group 4 shows a reserved pattern and an obvious small wind “window period” in midday.Groups 1~3 exhibit distinct daily transitions in wind direction， occurring after sunrise and sunset， whereas Group 4 does not show any diurnal change.（4） From a seasonal perspective， there are significant local differences between early spring and winter.Compared to winter， Group 2 exhibits a daytime wind speed increase in early spring， and Group 3 exhibits a nighttime decrease， while Group 4 exhibits a significant decrease in wind speeds throughout the day.Wind directions in early spring are relatively more variable， with an evident increase in northeasterly winds in Group 1， a delay of about 3 hours in the transition of valley wind circulation in Group 2， and an increase in southwesterly winds in Groups 3~4.This study contributes to a deeper comprehension of the fine-scale spatiotemporal patterns of near-surface local wind fields within complex terrains， and can offer crucial background clues for Winter Olympics and small-scale mountainous meteorological monitoring and forecasting.

Based on autumn precipitation data from 1961 to 2021 in Shanxi Province， NCEP/NCAR reanalysis data， and sea surface temperature data， the spatial-temporal variation characteristics and cause diagnosis of autumn precipitation in Shanxi Province were analyzed and discussed by using EOF analysis， correlation analysis and regression analysis.The results show that the autumn precipitation in Shanxi Province was relatively high before the mid-1970s， but decreased afterwards， and began to increase again in the mid-2000s.Further exploration of the causes of this interdecadal variation from the perspective of atmospheric circulation reveals that， during periods of excessive precipitation， the 200 hPa latitudinal wind field is located in the north of the East Asian westerly jet， which is beneficial for enhancing the upward movement in Shanxi； The 500 hPa geopotential height field exhibits a significant “+-+” anomaly distribution in the Europe and Asia region， which is conducive to the southward eruption of high latitude cold air； The 850 hPa wind field is conducive to the transport of low latitude water vapor to Shanxi， and under such high and low altitude circulation configuration， it is conducive to an increase in precipitation in Shanxi.At the same time， there is a close relationship between autumn precipitation and sea surface temperature anomaly in Shanxi.When the sea surface temperature in the central North Pacific is higher and in the tropical Middle East Pacific is lower from March to May， the autumn precipitation in the southern part of Shanxi is prone to behigher.