The Coupled Model Intercomparison Project （CMIP） provides reliable scientific data for predicting ecology， hydrology and climate under the backdrop of global change.However， there are large biases in current climate models， especially on the Qinghai-Xizang Plateau （QXP）.In this study， we employed Detrended Quantile Mapping （DQM） and Quantile Delta Mapping （QDM） methods to correct and evaluate the precipitation and temperature data of eight CMIP6 models with better simulation performance， utilizing the China Meteorological Forcing Dataset （CMFD）.The results showed that Both methods had corrected the simulation biases of the models， and the correction effects for temperature and precipitation data over the QXP were relatively consistent between the two methods.Then， based on the corrected multi-model ensemble mean （MME） results from QDM method， we analyzed the spatial and temporal variation characteristics of extreme high temperature events， low temperature events， atmospheric dryness and precipitation over the QXP in the early 21^st century （2015 -2057） and later 21^st century （2058-2100）.Under different emission scenarios in the future， extreme high temperature events strengthen， especially in the southeast of the QXP.Extreme high temperature events enhance with the increase of radiation.Extreme low temperature events decrease， with no occurrence in the later 21^st century under high emission scenarios （SSP370 and SSP585）.Under different emission scenarios， precipitation and saturated vapor pressure difference both exhibit a significant increasing trend on the QXP.With global warming， the increase of precipitation does not mitigate atmospheric drought.The atmospheric dryness increases significantly under the future scenarios， especially in summer， at 1.3 to 2 times compared to annual average.

As a unique alpine peat swamp wetland situated on the Tibetan Plateau， climate change in the Zoige ecological region not only impacts its own fragile ecological environment， but also exerts influence over the climate dynamics of the upper reaches of the Yellow River.Moreover， it plays crucial role in the climate stabilization of the western China.To investigate the simulation ability of the current high-resolution climate models in this area and to project the possible changes of the climate in this area in the future， this paper uses the four high-resolution climate models in the Coupled Model Intercomparison Program Phase 6 （CMIP6）， AWI-CM-1-1-MR， EC-Earth3， EC-Earth3-CC， MPI-ESM1-2-HR， and MPI-ESM1-2-HR， compared with the CN05.1 observation dataset provided by the National Climate Center， to evaluate the simulation capability of CMIP6 high-resolution models on the temperature and precipitation of the Zoige ecological region， and to make future temperature and precipitation projection under four different Shared Socioeconomic Pathway （SSP） scenarios.The results show that all the high-resolution CMIP6 models can simulate the distribution pattern and trend of temperature in the Zoige ecological region， but all of them have the underestimation of temperature， especially in the western Zoige ecological region， where the correlation coefficient of multi-model ensemble （MME） with the annual average time series of the observed data is 0.75， and the MME is lower than the multi-year average of the observed data by 0.75 ℃.For the precipitation simulation， there is an obvious simulation overestimation in all models as well as MME， with an overestimation of 1.45 mm·d^-1 in MME， and the correlation coefficient between MME and the observed data is 0.21 for the less satisfactory simulation of precipitation trend compared with the temperature.In 2100， the SSP scenarios with low to high emission concentrations of SSP1-2.6， SSP2-4.5， SSP3-7.0， and SSP5-8.5 scenarios are expected to have warming increases of about 1.8， 3.2， 5.2 and 5.8 °C， respectively， relative to the historical baseline period； the precipitation in the Zoige ecological region is expected to increase the most in the low SSP1-2.6 scenario compared with the historical period.The increase in 2100 was about 0.4 mm·d^-1 compared to the historical period， while the medium to high concentration SSP2-4.5， SSP3-7.0 and SSP5-8.5 scenarios showed a slight increase and smaller difference in precipitation changes by the end of the 21st century， with increases ranging from 0.1 mm·d^-1 to 0.2 mm·d^-1.The results of the study can provide scientific basis for water resource management and climate change adaptation research in the upper reaches of the Yellow River， and are also of great significance to the ecological protection of Zoige wetland.

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.

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.

This study examines observational data of the lower atmosphere during the summer seasons at the Antarctic Zhongshan Station from November 2018 to February 2019 and December 2019.It explores the profile characteristics and diurnal variations of meteorological elements， as well as inversions and jets at the station.The wind analysis reveals that the station experiences predominant winds from the east to northeast directions.Wind speeds increase sharply with altitude， peaking at approximately 1.2 kilometers in the morning and 0.8 kilometers in the afternoon， with lower speeds observed later in the day， possibly due to the development of downslope winds and enhanced turbulent mixing from thermal convection.Low-level jets are mostly concentrated in the speed range of 8~12 m·s^-1 and at altitudes between 800~1600 m， with multiple layers of jets identified.Temperature observations show the presence of a superadiabatic layer near the surface， with potential temperature gradually rising above this layer up to 3000 m， indicating a stable atmospheric structure.Further analysis of inversion layers demonstrates significant diurnal variations， with thicker and closer-to-ground layers in the morning and thinner but more intense layers in the afternoon， influenced by solar radiation and turbulence intensity.Multiple inversion layers corresponding to multiple jets are also observed， highlighting the connection between inversions and wind shear induced by jets.Humidity analysis indicates a decrease in specific humidity with altitude， particularly pronounced below 250 m.Specific humidity levels are lower in the afternoon compared to the morning up to 250 m.The study of humidity stratification reveals that the heights of maximum gradient changes in specific humidity coincide with the heights of inversion layers and low-level jets.

During November-December of 2022， the climate of Beijing-Tianjin-Hebei （BTH） showed significant cold and warm transition， and the average air temperature difference between November and December was 10.6 °C， ranked first with 1971 and 1980 since 1961.Based on NCEP/NCAR reanalysis and multiple climate index data， the possible causes of the air temperature transition in November and December 2022 in BTH was explored from the perspective of the interdecadal influence of atmospheric circulation transition， ENSO and AO on variation of temperature anomalies.The results show that the weak strength of the Ural Mountains Blocking High and the Siberian High， as well as the strong strength of the Western Pacific Subtropical high led to the abnormally warm climate in the BTH region in November.But the turning of the atmospheric circulation in December， the strengthening of the Ural Blocking high， the deepening of the East Asia Great trough， the strengthening of the Siberian high， and the northerly air flow in BTH， resulting in the abnormally cold December.The temperature anomaly difference of these two months showed obvious interdecadal changes， positive in 1961-1985， negative in 1986 -2003， and positive again in 2004 -2022.Compared to the cold and warm transition events in 1971， 1980， and 2005， there were interdecadal changes observed in atmospheric circulation transitions.The weak cold air activity in the north and the southern warm air flow influenced by the strengthening of the Western Pacific subtropical high acted together to cause the warm November of 2022 and 2005.However， the weak cold air activity in the north was mainly influence factor for warm November 1971 and 1980.The combination of significant Arctic warming and a significantly stronger Siberian high led to unusually cold Decembers in 2022 and 2005.The correlation between ENSO and November temperature in the BTH， as well as the correlation between AO and December temperature， exhibited a significant increase during the 2000s.In the context of La Nin ̃a， AO transitioned from a positive phase in November to a negative phase in December， resulting in a high likelihood of temperature inversion.Given that 2022 was the year of La Niña and influenced by an AO shift， a cold to warm transition event occurred in the BTH from November to December.

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.

Soil water-heat dynamics are pivotal in influencing regional hydrological processes.Understanding the dynamics of soil thermal and moisture changes during freezing and thawing processes is essential for assessing water balance in high-altitude regions.This study utilizes meteorological and soil water-heat observational data from a typical shallow mountainous catchment in the Qilian Mountains to simulate the water-heat dynamics of subalpine shrub meadow soil using the SHAW model， analyzing the changes in water balance during the soil freezing and thawing process.The results indicate that the SHAW model effectively simulates the temporal and vertical variations in soil temperature and moisture in subalpine shrub meadow soils.The findings demonstrates that the Nash-Sutcliffe Efficiency （NSE） for simulated soil temperature at various depths exceeded 0.88， with ae correlation coefficient （R） greater than 0.97and a Root Mean Square Error （RMSE） less than 1.89 ℃.For soil moisture， the correlation coefficient （R） was greater than 0.94， NSE was greater than 0.88.and the RMSE was less than 0.05 m³·m⁻³.Overall， the simulation of soil temperature is more accurate than that of soil moisture， especially in deeper soil layers.The soil freezing and thawing periods， delineated by temperature profiles， revealed a distinct unidirectional freezing and thawing characteristic of the subalpine shrub meadow soil， with the longest duration in the complete freezing period and the shortest in the freezing period.The trends in temperature and moisture across the soil profile exhibit a "U" shape， indicating higher soil temperatures and moisture during the thawing period compared to the freezing period， with significant fluctuations in surface soil moisture and relative stability at deeper layers.The water balance characteristics are significantly varied across different soil freezing and thawing periods.During the freezing period， the precipitation input is 4.28 mm， with the main expenditure of water is deep percolation at 9.06 mm.In the complete freezing period， the precipitation input is 28.69 mm， with the main expenditure of water is surface runoff at 17.90 mm.During the thawing period and the complete thawing period， the precipitation input is 106.29 mm and 207.31 mm respectively， with the major water output through evapotranspiration， where plant transpiration accounted for 78.11% and 71.54% respectively.The soil moisture shows a negative balance during the freezing and complete thawing periods， indicating a net loss of moisture.Conversely， the soil moisture exhibits a positive balance during the complete freezing and thawing periods， signifying a net increase in moisture.This study may provide empirical data and theoretical support for the formation and transformation of water resources in the Qilian Mountain region.

Climate and land-use change are important drivers of variation in carbon storage within terrestrial ecosystems.Investigating the effects of climate and land-use change on carbon storage has practical implications for proposing adaptive management strategies for carbon sequestration in a changing environment.In this study， the InVEST model and the PLUS model were used to evaluate the spatial and temporal dynamics of carbon storage in the water conservation area of the Yellow River under the dual influence of climate and land-use change.The results showed that the land-use in the water conservation area of the Yellow River was dominated by grassland and forest from 1980 to 2020， accounting for 80 % of the total area of the basin， with an increasing trend in the area of forest land， grassland， watershed and construction land， and a decreasing trend in the area of other land-uses.The types of land-use transfer include unused land to grassland， grassland to forest land and cultivated land.From 1980 to 2020， the carbon storage in the water conservation area of the Yellow River showed an overall growth trend.The growth area of carbon storage was mainly located in the western and central regions， increasing by 573.5×10⁶ t， which was closely related to climate warming and humidification and ecological restoration.The urban expansion areas in the central and northern regions are the main areas of carbon storage reduction.In the future， under different land-use scenarios， the area of forest and grassland in the ecological protection scenario will increase significantly.From 2030 to 2050， under SSP119 and SSP245 scenarios， carbon storage will increase by 294.83×10⁶ t and 79.56×10⁶ t， respectively， under natural development scenarios， and carbon storage will increase by 364.8×10⁶ t and 151.95×10⁶ t， respectively， under ecological protection scenarios.Low emission and ecological protection scenarios are favorable for carbon storage increase.In the future， the increase in carbon storage will mainly come from grassland， conversion of unused land into forest and cropland， and conversion of unused land into grassland.The decrease in carbon storage is mainly related to the conversion of forest land into grassland and cropland.It can be seen that protecting forest and grass is an important measure to improve the carbon storage of regional ecosystem.The results can provide a scientific basis for adjusting the land-use structure and carbon sequestration of the ecosystem in the water conservation area of the Yellow River.

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.

Differential reflectivity （Z_DR） is a crucial polarimetric parameter reflecting the morphology of cloud and precipitation particles.However， the quality of Z_DR is highly susceptible to decline due to hardware equipment and environmental influences.Analyzing biases in the measurement of Z_DR and conducting corrections are key for the effective application of dual-polarization radar data.In this study， an analysis of the biases in Z_DR is conducted， and corrective strategies are proposed based on data collected from light rain events by eight X-band dual-polarization radars in Beijing during July 2023.An adopted radial-by-radial accumulation method is employed to investigate factors and magnitudes influencing Z_DR.Furthermore， the system bias of Z_DR of full volume scans is corrected by using extensive raindrop spectrometer data during the corresponding period.The median value of Z_DR computed via the T-matrix method of raindrop spectrometer data serves as the reference for the correction process.The following conclusions are drawn： （1） Lightning rods exert a significant influence on X-band radar’s Z_DR in Beijing， with impact extending from 10° to 25° azimuth angles and average amplitude ranging from 0.16 dB to 1.21 dB.（2） Z_DR data obtained from Mentougou and Huairou radars are not only affected by lightning rods but also by nearby iron towers and signal towers， with smaller azimuth angles of impact compared to lightning rods.（3） Partial beam blockage significantly affects Z_DR， introducing notable systematic biases.For Fangshan X-band radar， partial beam blockage contributes to an increase of 1.19 dB in differential Z_DR.（4） The proposed method for system bias correction demonstrates effective mitigation of unreasonable Z_DR values attributed to factors such as lightning rods and beam blockage across all elevation angles and radial distances.

From 2 to 6 October 2021， Shanxi experienced the most intense continuous precipitation in autumn in meteorological records.Based on the precipitation observation data of automatic meteorological stations， ERA5 reanalysis data and NCEP GDAS reanalysis data， this study analyzed the circulation situation， low-level jet and water vapor transportation characteristics and water vapor sources of the extreme precipitation.The results indicated that the continuous extreme precipitation process had obvious phased characteristics.In the first stage （from 2nd to 3rd October）， the precipitation occurred in the warm area in front of the cold front and mainly in southern Shanxi.There were obvious convective precipitation characteristics which showed high and strongly fluctuant precipitation intensity.The precipitation of the second stage （from 4th to 6th October） was stable one behind the front which showed low precipitation intensity and long duration， resulting in continuous rainstorm in central and southern Shanxi.The circulation analysis revealed that the abnormally north-located and strong Western Pacific subtropical high and the abnormally south-located and strong West Siberian cut-off vortex constituted a favorable circulation background.During the whole precipitation process， compared with other rainstorm process， the abnormally north-located and strong low-level jet at 700 hPa remained stable which played an important role in the strengthening of low-level convergence， the intense development of vertical upward movement and the continuous water vapor supply.And it was the key to the formation of extreme precipitation.The low-level jet at 850 hPa existed a shorter time but played an important role in the transportation of warm wet air and the construction of unstable layer in southeast Shanxi in the first stage.The main water vapor input level of the heavy rainfall area increased gradually during the precipitation， with the first stage mainly around 850 hPa and the second stage mainly around 700 hPa， which was corresponding to the evolution of the weather situation.The sources of the water vapor in this extreme precipitation were mainly from the South China Sea， the East China Sea and the Yellow Sea， and the transportation path was southeast path， obviously different from other heavy rainfalls which main water vapor sources were mostly from the Bay of Bengal， the Arabian Sea and the South China Sea and the transportation path was southwest path.

The Qinling-Daba Mountains （Qinba Mountains） are referred to as the‘Central Water Tower’of China.They constitute the main transitional zone between the north and south and play a crucial regulatory role in the evolution of the natural environment.However， the current understanding of the contributions and causes of water vapor sources in the Qinba Mountains remains unclear， significantly impeding the comprehension of the underlying mechanisms that influence the geographical division between the north and south of China.In this study， we simulate the vapor trajectory in summer of years with high and low precipitation from 1970 to 2020 using the HYSPLIT model， and calculates the anomalies of vapor and wind using Eulerian method.The characteristics of vapor transport pathways and source contributions at different vertical levels from June to August over the Qinba Mountains were systematically analyzed.The results showed that： （1）The main summer water vapor channels in the Qinba Mountains are： the local channel， the Eurasian channel， the Western Pacific channel， the South China Sea channel and the Indian Ocean channel.（2）In terms of channel strength， the main vapor channels at the lower levels in high precipitation years are the local and South China Sea channels； that at the middle and upper levels are the Eurasian channel and the Indian Ocean channel.In the low precipitation year， the main channel at all levels is the Eurasian channel.（3）In terms of source contributions， the main source at the lower level in high precipitation years is the local and the South China Sea， that at the lower level in low years is the local， South China Sea and western Pacific.The main source at the middle and upper levels is the north Indian Ocean.（4）The anomalous characteristics of anticyclones and cyclonic circulation in the southeast have a significant impact on the difference in water vapor transport between high and low precipitation years.This study provides preliminary insights into the vapor transport characteristics during summer over the Qinba Mountains， thereby advancing our understanding of the underlying mechanisms of the Central Water Tower phenomenon and the geographic differentiation role of the Qinba Mountain region.

The phenomenon of near-surface energy budget imbalance is widespread， especially in the complex underlying surface such as mountain lakes.Due to the heterogeneity of the surface， the energy closure is poor， and the influence of the energy storage term between the atmosphere of the high canopy vegetation in the mountain on the energy closure is often ignored.This paper is based on the gradient tower meteorological data， radiation observation data and turbulence observation data of the eddy covariance system of Mount Emei Atmosphere and Environment Comprehensive Observation Experimental Station of Chengdu University of Information Technology （hereinafter referred to as "Mount Emei Station"） from June 2022 to October 2022.The Ogive function was used to analyze the average time suitable for the turbulent flux calculation at the forest station， and the soil heat flux and energy storage between vegetation and atmosphere were calculated， and the changes of near-surface energy balance after considering the storage terms between vegetation and atmosphere were analyzed.The results show that extending the average time to calculate turbulent flux to 60 minutes can capture larger turbulent vortices at some moments to a certain extent， but the energy balance ratio is lower than the average time of 30 minutes， so it is considered that the average time of 30 minutes is still suitable for the calculation of turbulent flux at Emei Mountain Station.The energy storage item of vegetation atmosphere improves the energy balance ratio by about 3.65%.Considering that this item has the effect of improving energy closure in most of the time， the energy storage item of photosynthesis contributes the most to improving energy closure， followed by the heat storage item of vegetation canopy， followed by the sensible heat storage item， and the latent heat storage item contributes the least.All the energy storage items in the atmosphere of high canopy vegetation have obvious single-peak diurnal variation characteristics.The peak value of heat storage items in vegetation canopy can reach up to 26 W·m^-2， and the energy balance ratio can be increased by 1.57% when the heat storage items in vegetation canopy are considered.The peak value of the photosynthetic storage term can reach about 8 W·m^-2， and the average daily storage capacity is about 141.6 W·m^-2， which is the main energy storage term.Considering the photosynthetic storage term， the energy balance ratio can be improved by 1.65%， accounting for 45% of the overall effect.The peak value of sensible heat storage term is about 5 W·m^-2， the magnitude of latent heat storage term is very small， and the effect on energy closure is also small.Vegetation-atmosphere storage terms cannot be ignored except latent heat storage terms which are very small.When considering the energy storage between vegetation and atmosphere， the energy closure problem still exists.Therefore， in addition to the energy storage term， the influence of large-scale vortices induced by the underlying mountain surface on the near-surface energy budget also needs to be further studied.

To address the modal aliasing phenomenon in traditional Empirical Mode Decomposition （EMD） algorithms， the Complementary Ensemble Empirical Mode Decomposition （CEEMD） and Mirror Extension algorithm were introduced to improve the shortcomings in EMD algorithm decomposition.This article selects case data from turbulence observations in the artificial forest area of Mount Si'e.Firstly， the differences between the two methods are compared and analyzed to clarify the advantages of the CEEMD algorithm； Then， case data of stable and unstable layers at different heights were selected， and the Hilbert Huang transformation method was applied to analyze the turbulent characteristics of the wind speed U and temperature T series under this case， exploring the application of the Hilbert Huang transformation method.The results indicate that the algorithm decomposition of CEEMD is more detailed， the mode aliasing defect of the modal function is better suppressed， the modal energy distribution is more focused， the Hilbert marginal spectrum has more energy spikes， and the energy distribution is clearer.Different modal functions have their own characteristic frequencies， and the decomposed modal functions contain motion of different scales， including turbulent motion in the inertial sub region with a slope of -2/3， and low-frequency large-scale modes corresponding to the energy containing region.The marginal spectral energy peaks obtained from CEEMD decomposition well reflect the energy containing characteristics of each modal function.Individual case analysis shows that the CEEMD algorithm can act as a typical binary filter.After CEEMD decomposition， there are gust fluctuations of about 3~6 minutes in the various modal functions of the U-wind in the turbulence signal of this case.The turbulence characteristics vary at different heights and stable layers.The Hilbert marginal spectral amplitude is higher in the unstable layer at noon compared to the stable layer at night， and the three-dimensional wind speed is better mixed at various heights.Moreover， due to the effect of the canopy， there is a crushing effect on large-scale turbulent vortices at lower altitudes， and the marginal spectrum exhibits low frequency small and high frequency large characteristics compared to other altitudes.In this case， the temperature T is different from the three-dimensional wind speed performance： turbulent vortices at different altitudes are better mixed under stable layer structures， while under unstable layer structures， the marginal spectrum amplitude at lower altitudes is higher due to differences in thermal absorption at different altitudes， and decreases with increasing altitude.Overall， this comparative analysis highlights the superior capabilities of the CEEMD algorithm in handling complex turbulence data， ensuring a more precise and insightful examination of atmospheric phenomena.

Wind profiling radar is a remote sensing device that boasts high spatiotemporal resolution and good consistency with sounding data， capable of probing the vertical distribution of atmospheric wind fields.Dali Airport， situated at the western edge of the Yunnan-Guizhou Plateau， on the southeastern rim of the Hengduan Mountains， is a typical plateau airport characterized by pronounced local circulation， where wind significantly impacts aviation safety.By statistically analyzing the vertical distribution of wind fields and the characteristics of wind shear using Dali Airport's wind profiling radar observations from 2016 to 2022， this study aims to enhance our understanding of the vertical structural features of wind fields over complex underlying surfaces and assess the impact of wind shear on aviation safety at civil airports.Key findings include： （1） Horizontal wind speeds are higher in winter and spring， with wind speed frequency contours resembling a trumpet shape （narrow below， wide above）.In summer， the contours exhibit a relatively straight and smooth S-shape， with similar wind speed distributions between the lower and upper layers.Autumn serves as a transitional period between summer and winter， necessitating attention to wind shear near 1000 meters and the impact of strong winds in winter and spring on flight safety.（2） The prevailing wind direction at higher altitudes throughout the year is westerly， while it shifts to southerly near the surface.At around 500 meters， a change in wind direction occurs with increasing altitude.Given the airport runway orientation， the impact of varying crosswind components on takeoffs and landings must be considered.（3） The mean zonal wind speed exceeds the mean meridional wind speed.Daily variations in wind fields are influenced by solar radiation， with 13:00 （UTC， the same as after） and 00:00 marking crucial time nodes for zonal wind speed changes， and 07:00 and 02:00 for meridional wind speed changes.（4） Vertical velocities are greater in spring and winter， with more dispersed frequency distributions， while they are smaller and more concentrated in summer and autumn.The frequency of downdrafts exceeds that of updrafts， exhibiting pronounced diurnal variations.（5） Spring sees a higher frequency and intensity of vertical wind shear events， with more occurrences of severe levels， followed by autumn and winter.Significant differences exist in the multi-year average frequency of wind shear across various altitude levels， with a hotspot for wind shear occurring between 840 and 900 meters.Taking 1000 meters as the boundary， notable differences are observed in wind shear indices between the upper and lower layers.

The accurate estimation of rainfall is always a topic of concern， given its pivotal role in accurately predicting rainfall-related disasters.This study proposed a multi-source rainfall assimilation technology based on a broad learning system （BLS） to improve the accuracy of rainfall estimation.Yunnan Province， located in China's low-latitude plateau， was chosen as the geographical area of interest to establish a multi-source rainfall assimilation model within this region.In particular， the model utilizes five satellite-derived rainfall datasets （3B42V7， IMERG， GSMaP， CMORPH， PERSIANN） and the latitude and longitude information as the source data， and the ground-based rainfall gauge data serves as the reference data.The time span of all the datasets is from April 2014 to December 2017.A leave-one-year-out cross-validation （LOYOCV） method was applied to verify the performance of the established assimilation model， where statistical indicators including Pearson’s correlation coefficient （CC）， root-mean square error （RMSE）， mean absolute error （MAE）， Nash efficiency coefficient （NSE） and Kling-Gupta efficiency （KGE） were used to quantify the accuracy of assimilation rainfall at different spatiotemporal scales.Concurrently， assimilation models based on support vector machine （SVM） and deep neural network （DNN） were established to highlight the accuracy and efficiency of the BLS， respectively.Additionally， the effectiveness of the latitude and longitude information within the proposed assimilation model was examined.The results show that the daily average statistical index of assimilation rainfall based on BLS is better than that of the other five satellite-based products in LOYOCV.At the temporal scale， the proposed assimilation technique effectively reflects the temporal variations observed in gauge-recorded rainfall.Moreover， it can accurately estimate the rainfall amounts during rainstorms in Yunnan Province throughout 2017.It is worth noting that the rainfall data generated through the BLS method outperforms the CMORPH product （the most accurate one among the five satellite-derived rainfall products） in both rainy and dry seasons （May to October and November to April of next year， respectively）.At the spatial scale， BLS-based rainfall results in most areas of Yunnan Province showed higher CC and NSE as well as smaller RMSE and MAE than the satellite-based products.The evaluation of the assimilation models based on BLS， SVM， and DNN highlights that the BLS exhibits superior functional mapping capabilities compared to SVM and demands fewer computational resources than DNN.It is reasonable to conclude that the multi-source rainfall assimilation approach utilizing the BLS while incorporating latitude and longitude information can enhance the precision of rainfall estimates in Yunnan Province.The proposed method presents practical significance in multi-source rainfall data assimilation.

In order to investigate the four key meteorological factors affecting aviation safety and their regional variations in Yunnan， research employed daily and hourly ground observation data from 125 meteorological stations across Yunnan from 2010 to 2021， as well as airport ground observation data from Tengchong Tuofeng Airport during 2013 -2019.Initially， an analysis was conducted on the primary seasonal variations of key meteorological elements in Yunnan.Subsequently， a spatiotemporal evolution analysis was performed for short-duration heavy precipitation and strong wind events during typical seasons at 15 airports.Furthermore， select observational data from typical plateau mountain airports-Tengchong Tuofeng Airport， and compare it with observation data from the Tengchong meteorological station.Analyze the annual frequency of short-duration heavy precipitation events during summer and the daily occurrence periods of spring strong wind events.Ultimately， a complex interrelation analysis among the four categories of meteorological elements was undertaken， followed by an exploration of the spatial distribution patterns of safe and dangerous aviation days in the Yunnan region.The findings revealed the following outcomes： （1） Short-duration heavy precipitation was most pronounced during summer， with areas spanning from Baoshan through Lincang to Puer experiencing heightened occurrences.Spring was characterized by prominent strong wind occurrences， particularly in Ninglang and Kunming， both exhibiting an increasing trend in the frequency of windy days.Notably significant was the occurrence of low visibility during autumn， predominantly observed in the southwestern region of Yunnan， encompassing Lincang， Cangyuan， Puer， and Xishuangbanna， with an escalating tendency.The spatial distribution of low clouds remained relatively similar across all seasons， with higher occurrence frequencies and distribution areas noted during summer and autumn， as opposed to winter and spring.（2） The occurrence of short-duration heavy precipitation events in summer exhibited a distinct positive correlation with precipitation amount， and the timing of occurrences aligned well with the primary operational periods of the airports.Variances in springtime strong wind events were noticeable among airports， predominantly transpiring between 14:00 and 23:00 （Beijing time）.（3） The localized nature of weather systems results in frequency disparities in weather phenomena occurring at airport locations compared to their surrounding areas， while maintaining a correlation in their patterns of variability.（4） Notably elevated were the average numbers of safe aviation days in the northern region along the Dali-Kunming alignment， compared to the southern areas of Yunnan.The majority of Yunnan's locales exhibited a declining trend in safe aviation days， whereas dangerous days were concentrated along the eastern vicinity of Puer to the western border of Wenshan， presenting an increasing trend along the Diqing-Lijiang-Kunming westward direction.

During March 23 and March 26， 2020， an area along the international route from Kunming， Yunnan to Vientiane， Laos experienced severe weather conditions including hail， thunderstorm winds， and heavy precipitation.A severe convective weather process was simulated using the mesoscale numerical model WRFV4.2 （Weather Research and Forecasting Model） and FNL （Final Operational Global Analysis） data from the National Centers for Environmental Prediction （NCEP）.Hourly weather station data from the China Meteorological Administration was used to check the reliability of the simulation.Furthermore， a diagnostic analysis of various physical quantities output from the WRF model was performed to provide an aviation safety reference for the Kunming-Laos Vientiane route in Yunnan.The results show that： （1） the WRF model can better simulate temperature and precipitable water， but the simulated values of the near-surface wind field are large during the daytime.（2） The simulated output physical quantity field of the simulation can indicate the time and location of severe convective weather， which has certain spatial and temporal forecasting and warning functions and can be used to judge the impact of severe convective weather on flight and the degree of impact according to it.（3） The severe convection was mainly caused by the eastward movement of the Southern Branch Trough， with dry and cold air in the upper levels superimposed on the warm and moist air forming an unstable structure， triggered by the surface convergence lines.Convective available potential energy （CAPE） in the route area is large， and the water vapor conditions are abundant-the rising motion and sinking motion alternate below 9 km altitude， which can cause turbulence during flights.Additionally， the 0 ℃ layer is located at an altitude of about 3 km， which can cause ice to form on the airframe or encounter hail weather， causing a certain impact on flight safety.

On February 19-22， 2022， Yunnan province， located on the low latitude plateau， experienced a large-scale cooling， rainfall and snow weather process， leading to the cancellation， delay， and return of multiple flights at eight airports.Focusing on this high-impact weather， this paper employs rain gauge data， ERA5 reanalysis data， and wind profile radar data to investigate the circulation causes， features of the cold front activity， and their impacts on aviation.The results show that： （1） This low-temperature rain and snow weather was a large-scale cold surge process that happened under the joint influence of a cold front and the southern branch trough.Before February 21， mainly affected by the cold front， the temperature dropped sharply with mild precipitation.The primary impact on aviation was aircraft turbulence caused by strong wind shear and unstable stratification.Subsequently， with the westward of the southern branch trough， precipitation increased， and the adverse weathers， such as airport snow cover， low-level clouds， thunderstorms， and wind shear， imposed a significant impact on flights.（2） The main body of the cold front regime was located below 700 hPa.When the cold surge out broke， the cold air leading by low-level easterly winds rushed westward with a nose-shaped forehead.The strength and thickness of the low-level easterly winds correspond well with those of the cold air mass； the warm westerly wind in front of the front climbs along the front， forming a inversion layer over the cold air mass.（3） When the front strongly developed and moved westward， the high value belts of the frontogenesis function at 800 hPa could well indicate the position and intensity of the front lines.The convergence of easterly behind the front and warm westerly before the front caused a significant updraft over the frontogenesis area.Meanwhile， the Richardson numbers （R_i ） were small in the areas where the vertical temperature gradient was large below 650 hPa before the front and in the near-surface layer behind the front， suggesting the potential turbulence regions.（4） Wind profile radar data indicated that during the maintenance period of low-level easterly winds， the strengthening of westerly winds above 2 km had a certain indicative significance for precipitation.When the low-level easterly winds weakened and disappeared， the process ended.

This study conducts a comprehensive risk assessment of meteorological safety for aviation operations in Yunnan Province.Leveraging meticulously curated observational data from 124 county-level meteorological stations across the province， encompassing measurements of low clouds and reduced visibility， rainfall， strong winds， icing， and thunderstorms， the research delves into the primary meteorological elements influencing aviation safety during takeoff and landing in various regions of Yunnan.Employing a fuzzy comprehensive evaluation method and Arcgis spatial analysis tools， a zoning map is developed to delineate the levels of aviation weather safety risk in Yunnan Province.The analysis yields the following significant findings： （1） Regionally， the primary meteorological factors influencing aviation safety in Yunnan encompass icing in the northwest， rainfall and strong winds in the west， low clouds and reduced visibility， as well as rainfall and thunderstorms in the southwest.Furthermore， prevalent meteorological challenges include low clouds and reduced visibility along with rainfall in the southeast， while rainfall predominates in the southern part of the east.Overall conditions demonstrate relative favorability without significant influencing factors observed in other parts of northeastern， central and most of eastern Yunnan.（2） When assessing aviation operation meteorological safety days and dangerous days across different regions within Yunnan province， it is evident that meteorological conditions for aviation operations generally exhibit favorability across most areas.Relatively poorer meteorological conditions are primarily concentrated in specific areas such as the northwest， the southern edge of the west， the southwestern edge of the southwest， the southern edge of the southeast， the southern part of the east etc.（3） In terms of comprehensive assessment regarding meteorological risk associated with aviation operations within various regions across Yunnan province， a majority fall into safe or very safe categories.The relatively dangerous or very dangerous grades are only found to be distributed within specific areas such as central Diqing Prefecture in the northwest， the southwestern part of Lincang City in the southwest， Xishuangbanna Dai Autonomous Prefecture etc.Overall assessment indicates a favorable level for comprehensive meteorological risk associated with aviation operations throughout Yunnan province.

In an effort to elevate the precision of low-level wind shear forecasting， this paper amalgamates European Centre for Medium-Range Weather Forecasts （ECMWF） fifth-generation reanalysis data （ERA5） and National Centers for Environmental Prediction Final Operational Global Analysis （FNL） reanalysis data， high-resolution Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model （ASTER GDEM） terrain data， and real-time observational data from Lanzhou Zhongchuan Airport.It employs the Weather Research and Forecasting Model （WRF）， WRF integrated with Computational Fluid Dynamics （CFD）， and Long Short-Term Memory （LSTM） neural network methods to simulate and analyze two wind shear events at Lanzhou Zhongchuan Airport on April 15-16， 2021.The findings reveal that： （1） within grids smaller than 1 kilometer utilizing Large Eddy Simulation （LES）， the WRF model demonstrates superior performance in wind speed simulation for individual stations， yet it falls short when compared to the WRF model combined with Computational Fluid Dynamics （CFD） models in simulating near-surface horizontal wind field wind speeds； （2） concerning the simulation of two low-level wind shears encountered during aircraft landing， both Weather Research and Forecasting Model - Large Eddy Simulation （WRF-LES） and Weather Research and Forecasting Model - Computational Fluid Dynamics （WRF-CFD） models are capable of simulating the first wind shear， however， the second appears to be influenced by the potentially lower wind speed data input into the models， with neither model achieving the threshold for wind speed difference， necessitating further validation in future work； （3） under low wind speed conditions （6 meters per second）， the LSTM-based single-variable wind speed prediction model maintains an average absolute error of approximately 0.59 meters per second， effectively capturing the nonlinear relationship of wind speed changes under various terrain and circulation background conditions.Despite being constrained by WRF errors and incomplete observational elements， multi-variable wind speed prediction can achieve wind speed forecasting with higher computational efficiency and generalization capabilities while ensuring that the average absolute percentage error is less than 6.60%.This paper not only verifies the differences between WRF-CFD and WRF-LES coupling schemes in wind field and low-level wind shear forecasting but also explores the feasibility and accuracy of LSTM-based wind speed prediction， aspiring to offer new perspectives and methods for enhancing wind field simulation accuracy and reducing the time required for detailed wind field simulation.