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.

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.

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.

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.

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.

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.

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.

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.

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.

High-precision and long time-series soil moisture （SM） data are crucial for quantifying the land-atmosphere interactions on the Qinghai-Xizang Plateau （QXP）.However， most of current studies on the Tibetan Plateau mainly focus on retrieving surface SM based on the satellite data， with relative lack of studies on estimating rootzone SM （RZSM）.Based on data collected from five SM observation networks on the QXP （i.e.， Shiquanhe， Pali， Naqu， upper reaches of Heihe River， and Maqu）， this paper systematically evaluates the applicability of the exponential filter model for estimating RZSM （i.e.， 10， 20， 40 cm） in different climatic and land areas of the QXP.In addition， we explore the impacts of different environmental factors （e.g.， soil properties， climate， and vegetation） on the estimated key model parameter， i.e.， characteristic time length T.Moreover， the reliability of regional-scale T-value obtained using three methods （i.e.， using the median value of optimal T-value obtained for each observation network or the whole Qinghai-Xizang Plateau， or the random forest model） for estimating RZSM on the QXP was assessed.The results showed that： （1） With the increase of soil depth， the correlation between rootzone and surface SM decreased while its spatial heterogeneity increased.This results in a decrease in the accuracy of the exponential filter model， but the obtained T-value and its spatial heterogeneity increased.（2） Spatially， with the increase of precipitation and SM content， the correlation between rootzone and surface SM increased while its spatial heterogeneity decreased.This leads to an increase in the accuracy of the exponential filter model， while the difference in accuracy of the model applied to different sites shows a decreasing trend.（3） Soil properties， especially the sand content， are the main factors controlling the spatial distribution of T-value on the QXP.（4） The different methods for obtaining regional-scale T-value have little influence on the accuracy of the exponential filter model in estimating the RZSM on the QXP.Specifically， both the commonly used methods， such as using the median value of optimal T-value or the random forest model， can obtain reasonable regional-scale T-value and achieve consistent and accurate RZSM estimations.These findings are expected to promote the use of the exponential filter model to accurately obtain the RZSM on the TP using satellite-based surface SM data.

Henan Province is the main producing area of winter wheat in China， and it is also susceptible to dry-hot wind.At present， the research and forecast of dry-hot wind both are on the weather scale， it is of great significance to study whether the dry-hot wind is predictable from the perspective of climate.This study analyzed the relationship between dry-hot wind days in Henan Province and preceding sea surface temperatures （SST） from 1980 to 2022， as well as potential influencing pathways， based on the dry-hot wind data from Henan Province， NCEP/NCAR reanalysis data， and SST data from the Hadley Centre.The results show that： （1） The mean annual dry-hot wind days in northern， northwestern and central Henan Province is more than that in other regions.The probability of dry-hot wind occurrence in the day gradually increases from south to north， and from late May to early June.The average number of dry-hot wind days in the province has a significant increasing trend.（2） There is a close correlation between the number of dry-hot wind days in Henan and the March-April SST in the northeastern Atlantic-western Mediterranean （key region） on both decadal and interannual scales.The correlations between the above two and the 500 hPa geopotential height during dry-hot wind periods， before and after detrending， indicate significant positive correlation areas in mid-latitude East Asia， located from northern Xinjiang to north of the Lake Baikal， and significant negative correlation areas located from northeastern China to the Japanese archipelago， respectively.Correlations with 850 hPa wind fields show anticyclonic and cyclonic distributions in these significant correlation areas， respectively.There is significant correlation of northerly wind in the rear of cyclone， That is， in years with high SST in the key region in March-April， the dry-hot wind weather in Henan Province was formed under the influence of the Mongolian high pressure ridge and the East Asian trough.The correlations between the key region SST index and the circulation fields exhibits a more obvious zonal teleconnection wave-train from the northeastern Atlantic across Eurasia to northeastern Asia in the middle-latitudes.（3） When the western Pacific subtropical high （WPSH） shifts southward （northward）， the dry-hot wind days are more （fewer）， while the high （low） SST in the key region in March-April can lead to a southward （northward） shift of the WPSH.（4） The differences of meridional mean vortex at 30°N-55°N during dry-hot wind period between years with more dry-hot wind days and years with less days， years with key region high SST index in March-April and years with low SST index， composites of 500 hPa quasi-geostrophic stream function anomalies and wave activity flux during dry-hot wind period in years with high and low SST index all show that there is a zonal wave-train from the northeastern Atlantic to the western Pacific.This indicates that March-April SST in the key region can generate a similar wave train during subsequent dry-hot wind periods， propagating across the Eurasian continent to northeastern Asia， with the circulation pattern in high SST years causing dry-hot wind weather in Henan Province.

Affected by global climate change， lakes on the Qinghai-Xizang Plateau have undergone drastic changes in recent years.Understanding the characteristics of lake evolution and their driving factors is of great significance for the protection of major engineering facilities along the lakeshore.Based on Landsat remote sensing images， area data， and water level observation data of Qinghai Lake and Lake Cuona， this study conducted a detailed investigation into the evolution of the two lakes and their minimum distances from the Qinghai-Xizang Railway.Furthermore， by integrating the China Meteorological Forcing Dataset （CMFD） with high spatiotemporal resolution ground meteorological elements and meteorological data from meteorological stations， the main meteorological factors influencing water level changes in the two lakes were revealed.The results show： （1） From 1956 to 2004， Qinghai Lake exhibited a shrinking trend.After reaching their lowest values in water level and area in 2004， Qinghai Lake began to gradually increase.During the period from 2004 to 2020， the annual average growth rate of water level was 0.20 m·a^-1， and the annual average growth rate of area was 19.20 km²·a^-1.The water level of Lake Cuona from 2000 to 2018 and the area from the 1970s to 2022 showed slight fluctuations.The maximum interannual fluctuation values of water level and area were 0.60 m and 9.98 km²， respectively.（2） From 1990 to 2022， the minimum distance between Qinghai Lake and the Qinghai-Xizang Railway first increased and then decreased.After 2004， the minimum distance between them decreased at a rate of 19.6 m·a^-1， reaching 74.3 m by 2022.The change trend in the minimum distance between Lake Cuona and the Qinghai-Xizang Railway from 2004 to 2022 was not significant， reaching 32.3 m by 2022.（3） The water level changes of Qinghai Lake are influenced by wind speed， annual precipitation， downward shortwave radiation， downward longwave radiation， and specific humidity， with contributions of 38%， 24%， 20%， 14%， and 4% respectively.The water level changes of Lake Cuona are mainly influenced by precipitation， with other meteorological factors showing no significant correlation with water level changes.

A heavy rainstorm process occurring simultaneously at the northern and southern piedmont of the Qinling Mountains from August 21 to 22， 2021 is compared and analyzed to explore the influence mechanism of the triggering conditions at the northern and sorthern piedmont of the Qinling Mountains by using the real-time meteorological observation data， FY-2G satellite cloud images， doppler radar data and ERA5 0.25°×0.25° hourly reanalysis data.The result shows that on the flow field of the northern piedmont of the Qinling Mountains， the westerly system forms a meso-scale cyclonic circulation in the lower troposphere under the special topography of the Qinling Mountains， which triggers heavy rainfall through thermal effects.Convective precipitation is short-lived and its intensity is weak.The enhancement of wet baroclinicity is a signal of the beginning of the rainstorm at the northern Qinling Mountains.The precipitation ends when the wet baroclinicity weakens and the specific humidity of the middle layer decreases.For the southern piedmont of the Qinling Mountains， the formation of mesoscale convergence lines in the lower tropospheric flow field under the effect of topography triggers the rainstorm.The condensation latent heat released by precipitation heats the lower atmosphere and establishes a convective instable structure， together with the cold intrusion in the middle and lower layers， which leads to the enhancement of the upward movement and the precipitation.Under the high temperature and humidity environment， the convective cloud organizes and develops rapidly to form the MCC， which has a high convective intensity， deep convective tropospheric junctions， and powerful hourly rainfall.The timing of the invasion and diffusion of cold air in the lower and middle layers to the ground represent the beginning and end of heavy rain at the sorthern Piedmont of the Qinling Mountains respectively.

The Yangtze River Delta in China is a typical rice planting area， and its carbon source and sink have significant impacts on regional climate and environment.This study systematically examines the relationship between NEE and various meteorological factors in the Yangtze River Delta region and reveals that NEE exhibits the strongest correlation with solar short-wave radiation （R=-0.68）， followed by a robust linear association with humidity-related parameters （saturated water vapor pressure difference， relative humidity）.Additionally， diurnal variations are evident in the correlations between NEE and solar radiation， temperature， humidity factor， wind speed， and friction velocity.Based on these analyses， this paper constructed a multi-layer perceptron （MLP） model for simulating rice undersurface NEE in the Yangtze River Delta using observed NEE data alongside meteorological observations.The simulation performance and spatiotemporal stability of this model are evaluated.Results demonstrate that the constructed MLP model effectively captures NEE patterns； it achieves an R value of 0.88 with respect to observed values within the training set while maintaining an RMSE of 5.34 μmol·m^-2·s^-1.Moreover， this MLP model performs well when predicting NEE in the Yangtze River Delta region as evidenced by high correlation coefficients （>0.78） between simulated results and observations at Dongtai and Shouxian stations-indicating good spatiotemporal stability of the model's predictions.Notably， this MLP model demonstrates superior performance when capturing daily variations in daytime mean NEE compared to nighttime mean values.The research results reveal the main meteorological factors affecting rice carbon cycling， provide support for understanding the spatiotemporal distribution characteristics of carbon cycling in rice planting areas of the Yangtze River Delta， and have important significance for accurately evaluating global and regional carbon flux.

Using the daily maximum temperature datasets from 664 observational stations during the period of 1961-2022， this paper systematically analyzed the spatio-temporal distribution and variations of the extreme heat events as well as their start and end dates.The results showed that nearly 90% of the extreme heat events in China occurred in summer， of which 39.3% occurred in July.The extreme heat events increased significantly in the past 62 years in China， characterized by increasing days and maximum temperature of extreme heat events at over 90% of the stations.The average days and maximum temperature of extreme heat events increased by 2.1 d and 0.18 ℃ every 10 years in China， respectively.The increase of extreme heat events was more obvious in high altitude areas， with more than 90% stations showing a significant increasing trend in extreme heat days， and more than 87% stations showing a significant increasing trend in maximum temperature in Qinghai-Tibetan Plateau.The increasing trends of days and maximum temperature were up to 2.9 d·（10a）^-1 and 0.34 ℃·（10a）^-1 in Qinghai-Tibetan Plateau， respectively.The start and end dates of extreme heat events showed obvious advance and delay trend in most stations in China.The duration of extreme heat events increased more distinctly due to the reverse variations of the start and end dates， characterized by increasing duration of extreme heat events at over 90% of the stations in all regions.Southwest China was characterized by the fastest growth of extreme heat events in all regions， with the largest rate of 10.8 d·（10a）^-1.Persistent extreme heat events maintained for a long time posed a serious threat to people’s production and life， which occurred frequently in 21 century.Similar to the variation of extreme heat events， the persistent extreme heat events also showed a significant increasing trend in most stations in China.The persistent extreme heat events increased rapidly in South China and Southwest China.Specifically， the largest increase was observed in South China， with the trends up to 0.5 times·（10a）^-1 and 2.5 d·（10a）^-1， respectively.In addition， the increase of persistent extreme heat events was also obvious in Qinghai-Tibetan Plateau， with trends of frequencies and accumulated days up to 0.3 times·（10a）^-1 and 2.1 d·（10a）^-1， respectively.

Based on similar forecast method with step-by-step filter and Self-organizing map （SOM） neural network， a fusing analog forecast method is proposed.Using ECMWF model forecast products， ERA5 reanalysis data and station data， this method is used to carry out a 72-hour forecast of heavy precipitation in southeastern Gansu from 2021 to 2022， and the forecast effect is tested.The results show that the TS score of the fusing analog forecast method ranges from 4.5% to 9.1%， demonstrating a certain advantage compared to the forecast results of the ECMWF model.As the forecast lead time increases， the TS score of the heavy precipitation forecast shows a decreasing trend， with relatively higher TS scores forecasted at 08:00.Compared with the similar forecast method with step-by-step filter alone， the accuracy of the fusing analog forecast method is improved， and it can alleviate the problem of high false alarm rate to a certain extent.Specifically， the TS scores forecasted at 08:00 and 20:00 are increased by 1.31 % and 0.63 %， while the FAR is decreased by 2.39 % and 1.25 %.

The north slope of the Middle Kunlun Mountains contains different sub-surfaces such as oases， deserts and their transition zones， as well as deserts and plateau climates， with great ecological differences and climate variations from north to south.However， the poor natural environment of the mountainous areas and the lack of sufficient meteorological stations and unevenly distribution of them， which bringing certain challenges to the study of meteorological elements， and resulting in incomplete mastery of meteorological elements in the region.Therefore， it is necessary to perform a study on the meteorological elements of the North Slope of the Central Kunlun Mountains.This study utilized meteorological data from nine meteorological stations at different altitudes on the northern slopes of the Central Kunlun Mountains in a consecutive year （August 2022 to July 2023） to investigate the spatial and temporal characteristics of near-surface meteorological elements at the altitude of 1.5 m in the mountainous areas in response to the gradient.The results show that： （1） The wind direction changed significantly at different altitudes， the wind speed increased with increase of the elevation， the metrological station at 1738~3044 m above sea level was affected by the valley wind， and two dominant "twin peaks type" were observed for the daily change of wind speed； （2） The temperature lapse rate （TLR） on the north slope of the Central Kunlun Mountains is lower than the standard atmospheric temperature lapse rate， and the TLR_mean（mean temperature laspe rate）， TLR_max（max temperature laspe rate） and TLR_min（min temperature laspe rate） were -0.56 ℃·（100m）^-1， -0.60 ℃·（100m）^-1 and -0.47 ℃·（100m）^-1， respectively， with seasonal characteristics of steepness in summer and shallowness in winter； （3） There are several inversion temperature layers and inversion humidity layers at different altitudes， and the seasonal differences in the degree of inversion temperature and inversion humidity were large， which are manifested as the smallest intensity of inversion temperature and the larger intensity of inversion humidity in summer， the largest degree of inversion temperature and the smallest intensity of inversion humidity in winter， and the strongest inversion temperature and inversion humidity were found at the altitude between 1256 m and 1409 m； （4） The inverse temperature and inverse humidity under typical summer weather were greater on sunny days than that of on rainy days， and the maximum inverse temperature intensity on sunny days was equal to 4.32 times of the rainy days， while the range of variation of specific humidity on sunny days was greater than that on rainy days， and the intensity of inverse humidity was equal to 1.11 times of the rainy days； （5） The North Slope of the Middle Kunlun Mountains accounted for more than 86% of the total annual precipitation from April to September， the precipitation change gradient was more obvious with changes in altitude， and showed "increase - decrease - increase"trend， a obvious precipitation zone was found around 2800~3200 m.

According to the classification of warm-sector rainstorm （the southwest vortex， the edge of subtropical high， the southwest jet， and the southeast wind types）， four rainstorm processes are selected under the different weather background in the west of Sichuan Basin （Chengdu area）.The wind profile characteristics of heavy precipitation in the initial and developmental stages are analyzed by using the new wind profiler radar data in different types of warm-sector rainstorms.The main results are as follows： （1） Wind profiler radar data can clearly show the meso-scale systems that exists in the troposphere and boundary layer.The evolution characteristics of wind field in different types of heavy precipitation are closely related to the interaction of the unique terrain of the Qinghai-Xizang Plateau and the Sichuan Basin with the regional circulation and weather system.Except for the edge of subtropical high warm-sector rainstorm， the northeast wind or easterly wind appeared before or during the typical process of the other three warm-sector rainstorms.（2） A large gradient of vertical velocity intuitively reflects the characteristics of short time and strong convection in these processes.There is a sudden change of vertical velocity at the beginning of heavy precipitation， that the downward vertical velocity is apparently weakened or even turned to the upward， which means the upward motion in the atmosphere is significantly enhanced.This abrupt change in vertical velocity has indicative significance for the prediction of heavy precipitation.（3） The extremum of vertical velocity will increase significantly before or during the heavy precipitation， accompanied by the decrease of the extreme layer height， due to the fall of precipitation particles.During the southwest vortex rainstorm， the change of the extremum of vertical velocity was basically ahead of the change of precipitation intensity by half hour to 1 hour.The extremum of horizontal wind speed and the extreme layer height change synchronously.Before the most of heavy precipitation processes， the meso-scale jet appeared in the mesosphere， accompanied by the decrease of the jet layer.（4） Low-level jet is involved in all four types of warm-sector rainstorm.In the process of the edge of subtropical high and the southwest vortex rainstorm， the precipitation could be predicted after 1 hour to 2 hours by the first increase of low-level jet index.The low-level jet could provide water vapor and turbulence during heavy precipitation.Therefore， in the process of the southeast wind and the southwest vortex rainstorm， the sudden increase of low-level jet index predicts the increasing intensity of precipitation.

Based on the observation data of Shijiazhuang S-band radar and X-band radar， along with information from raindrop spectrometer and ground rain gauge data， this investigation analyzes four quantitative precipitation estimation methods： R（Z _H）， R（Z _H， Z _DR）， R（K _DP） and R（K _DP， Z _DR） applied to two radar systems in Shijiazhuang area.Firstly， the T-matrix method is used to calculate dual polarization parameters using raindrop spectrum data， fitting various rain measurement equations； Subsequently to this， 13 precipitation cases are used to test different quantitative precipitation estimation methods， selecting surface rainfall data of Shijiazhuang area.These results reveal that the radar reflectivity factor calculated from raindrop spectrometer data is generally consistent with the radar measurement， with a slight overall overestimation of 5 dB.The precipitation estimation results using R（K _DP， Z _DR） from both two radars are superior， and the use of polarization parameter K _DP can significantly enhances the rainfall estimation.The addition of Z _DR does not substantially improve the rainfall measurement formula compared to the single parameter.The application of R（K _DP） and R（K _DP， Z _DR） methods demonstrates heightened accuracy in precipitation estimation with the X-band radar compared to the S-band radar.The utilization of X-band radar， distinguished by its high spatial-temporal resolution， further refines the precision of urban precipitation estimation.