The Qinghai-Xizang Plateau Vortex is a mesoscale low-pressure vortex system generated within the boundary layer of the Qinghai-Xizang plateau in summer， which not only has an important influence on the weather patterns and precipitation dynamics across the plateau， but also profoundly impacts the surrounding regions.In this study， the database of the plateau vortex obtained from an objective analysis method， along with ERA5-land reanalysis data， was utilized to conduct a comprehensive statistical and analytical investigation of the vortex's activity from 1950 to 2021.Various analytical methods， including correlation analysis， regression analysis， Bayesian time series analysis algorithm， and probability statistics were used.Furthermore， the intensity and path of the plateau vortex during the years 1950 and 2021 were specifically examined to identify the areas most sensitive to its activity during this time span.Results reveal a noteworthy increasing trend （at a 95% confidence level） in both the annual number and duration of the plateau vortex， with climate tendency rates of 0.16·a-1 and 1.25 h·a-1， respectively.However， the growing trend for the total number and duration of the plateau vortex during the active period （May to August） is not statistically significant.The sensitive areas that affect the activity of the plateau vortex are located on the north side of the northern Qinghai-Xizang Plateau and near the Hoh Xil Mountains， corresponding to the main mountains in the central and western Qinghai-Xizang Plateau.Furthermore， the study investigates the relationship between land surface parameters and the vortex's characteristics， showing positive correlations between latent heat， surface longwave radiation， and surface soil moisture （0~7 cm） with the number and duration of the plateau vortex.Conversely， sensible heat exhibits a negative correlation， it is further found that the plateau vortex is relatively consistent with precipitation when the time scale of the study is inter-annual， while on the daily scale， the sensible heat is positively correlated with the number， duration， and intensity of the plateau vortex mainly in the sensitive areas and to the east of the sensitive areas， with the most significant correlation being in the months of May and June.In conclusion， the results derived from this study provide a solid theoretical foundation for further exploration of the land-atmosphere interaction mechanism in the identified sensitive area.Moreover， these findings lay a critical foundation for enhancing numerical simulations and data assimilation studies of the Qinghai-Xizang Plateau Vortex.
Observed soil moisture and precipitation as well as GLDAS and CMFD reanalysis data are used to analyze the spatial and temporal distribution and variation trend in the Loess Plateau region.Regression analysis， Granger causality test and singular value decomposition （SVD） are used to study the relationship between soil moisture and precipitation， and to analyze the temporal scale and spatial range of the influence of initial soil moisture on subsequent precipitation.The results show that the explained variance of the regression analysis of soil moisture and subsequent 1~2 months precipitation on the Loess Plateau is relatively high， with larger values in the summer and fall seasons （July， August， September， and October）.That the correlation between soil moisture and the subsequent 21 days of precipitation in different regions of the Loess Plateau （zones I， II， and III） is more frequent and concentrated than that in the whole region.This indicates that soil moisture on the Loess Plateau is heterogeneous so that a larger lagged precipitation time scale is just suitable for analysis at larger spatial scales.The Granger causality test shows that the initial soil moisture in the fall （October and November） across the Loess Plateau has a significant effect on the precipitation in the following 1 or 2 months， and the soil moisture in August also has a significant effect on the precipitation in October in Area III， which is consistent with the results of the regression analysis.The result of the SVD decomposition shows that from 1979 to 2014， when soils in the central， northern， and eastern parts of the Loess Plateau are wetter in July， the precipitation in the western and northern margins of the plateau is accordingly more in August.A wetter soil in the eastern part of the plateau in September means more precipitation in the western part of the plateau， as well as some parts of the northern and southern parts of the plateau， in October.The significant correlation between soil moisture and precipitation has fewer overlapping regions， suggesting spatial and temporal asymmetry in the influence of soil moisture on precipitation on the Loess Plateau.
Qinghai Lake is not only the largest lake in China but also an important part of the national ecological security strategy.Under the background of global warming， the water level of Qinghai Lake changes rapidly， which has great effects on the surrounding traffic facilities， residents' safety and the development of animal husbandry， etc.Therefore， it is necessary to study the water level evolution characteristics of Qinghai Lake and its water balance under climate change.Based on the hydrological data of Buha River hydrology station and Xiashe hydrology station， meteorological data of Gangcha meteorological station and CMFD， and water balance equation， this paper first analyzes the inter-annual and intra-year water level evolution characteristics of Qinghai Lake from 1956 to 2020， and the water balance components， such as runoff into the lake （ ）， precipitation （P） and evaporation （E）.The second reveals that the changes in water level values calculated in the same months are synchronized with the changes in ， P， and E.Finally， the ridge regression method is employed to quantitatively calculate the contribution rates of ， P， and E to the water level change of Qinghai Lake based on calculations made for December.The results show that the annual average water level declined at a rate of 0.8 m·（10a）-1 from 1956 to 2004， of which the main reason for the decrease between 1979 and 2004 was that E exceeded the sum of P and .However， from 2004 to 2020， the water level increased at a rate of 1.9 m·（10a）-1， of which the main reason for the increase between 2004 and 2018 was the increase of P and .Qinghai Lake exhibits evident intra-annual variations， with the water level starting to rise in May and reaching its peak in September， which aligns with the monthly variations of ， P， and E.Furthermore， the impact of the current year's P， ， and E changes on the annual water level change for the same months of September to December is greater than that of the previous year.Specifically， the contributions of the current year's P， ， and E changes to the water level change calculated based on December data are 10%， 70%， and 20%， respectively.
The Source Area of the Yellow River is located in the northeastern part of the Qinghai-Xizang Plateau， and the meteorological stations are sparsely distributed in this basin， the study of the applicability of various precipitation data products has an important values in promoting the hydrological modeling in the basin.Based on the China Meteorological Assimilation Datasets for SWAT model Version1.1 （CMADS V1.1）， the Tropical Rainfall Measurement Mission （TRMM） precipitation datasets （3B42 Version7） and the Soil and Water Assessment Tool （SWAT） driven by these precipitation data， respectively， and the SWAT-CUP （SWAT Calibration and Uncertainty Program） and SUFI-2 （Sequential Uncertainty Fitting2） algorithm 27 sensitivity parameters were rate in simulating the variation of multi-year monthly average runoff， the simulated results were compared with the observations to evaluate the accuracy of CMADS and TRMM 3B42 precipitation data products and the applicability of SWAT model were evaluated in the Source Area of the Yellow River source area.The results show that： （1） The distribution of all three precipitation datasets showed an increasing trend from the west to the east， and TRMM 3B42 was in better agreement with the measured precipitation than CMADS data set in terms of annual and monthly variation.（2） The sensitivity analysis of the parameters showed that the sensitivity degree of SCS （Soil Conservation Service） runoff curve number， groundwater lagging coefficient， and soil evaporation compensation coefficient were stronger than that of the others.（3） The simulated runoff by using the CMADS and TRMM 3B42 precipitation datasets had better results than that by using the measured precipitation data， with the correlation coefficients R 2 of 0.93， 0.92 and 0.88 for the rate period at the three hydrological stations， respectively， while the results of the TRMM 3B42 simulation were the next best， with the coefficients of correlation （R） of the rate-period and validation-period of above 0.80， and the Nash-Sutcliffe efficiency coefficient （NSE） of the simulations is above 0.50.This research demonstrates the applicability of CMADS datasets and SWAT model for runoff simulation in high-altitude areas with complex landscape types and sensitive to climate change， and provides a replacement solution for improving the hydrological models in areas where there are sparely meteorological stations.
Clouds play an important role in the Earth-atmosphere system.To deeply analyze the cloud characteristics in the Loess Plateau region （LP）， the macro and micro physical characteristics of clouds were analyzed by using the CloudSat-CALIPSO data from 2007 to 2016 in four regions of the Loess Plateau， namely， semi-humid， semi-arid， arid， and cold arid.The findings indicate that： （1） In the LP， the annual average frequency of clouds exceeds 55%， with the highest frequency in spring and summer， and relatively lower in autumn and winter.The frequency of clouds in semi-humid region is higher than that in other regions.However， the months with the highest frequency of cloud occurrence in the other three regions are earlier than those in the semi-humid region.（2） The frequency of single-layer clouds is the highest in all regions， accounting for over 60% of the total cloud amount， with double-layer clouds being the main type among multi-layer clouds， accounting for about 25% of the total cloud amount.The seasonal variation of cloud height in each region shows that it is greater in spring and summer than in autumn and winter， and that it is greater in semi-humid region than in other regions in all seasons.The seasonal variation of cloud geometric thickness is not significant in all regions， which is between 1 km and 4 km， with mainly thin clouds， and 78.13% of the cloud geometric thickness is less than 2 km.（3） The annual average value of cloud liquid water content in all regions reaches more than 220.5 mg·m-3， about 6.5 times of the annual average ice water content.It is mainly distributed in the altitude below 8.5 km， and the liquid water content gradually increases as the altitude decreases， in which the cloud liquid water content in the semi-humid region is larger than that in other regions.The ice water content in each region is small throughout the year， mainly distributed in the altitude layer below 16.5 km.（4） The values of the effective radius of liquid droplets in each region are mainly concentrated in the range of 12~16 μm， with a maximum of about 24 μm in the spring in the semi-arid region； the maximum value of the effective radius of ice particles occurs in the summer in the semi-humid region.The values of droplet number concentration in all regions were concentrated at 60~80 cm3， which were smaller than the mean value of ice particle number concentration， with peaks occurring in the summer in all regions， and the peak of ice particle number concentration occurring in the spring in the semi-humid and semi-arid regions.The results of this study can help to understand the cloud characteristics of the Loess Plateau and provide a reference basis for the simulation of cloud characteristics in the Loess Plateau by regional climate models.
The daily precipitation data of Kunming Station for nearly 30 years from 1991 to 2020 were used to calculate the beginning and ending periods of Kunming rainy season （May-October）， further determine the length of the rainy season in Kunming.Additionally， statistical yearbook data for Yunnan Province and Kunming City were used， including year-end total population， urban built-up area， urbanization rate， per capita GDP， and other urban development factors， to determine the urban development process in Kunming.This process divided Kunming's urban development into a slow period （1991 -2003） and a fast period （2004 -2020）.The characteristics and differences in the length of the rainy season in Kunming City during these two periods were then analyzed and compared.Various analytical methods， including statistical analysis， wavelet analysis， and Mann-Kendall （M-K） mutation test， were employed to systematically analyze the temporal changes in the length of the rainy season in Kunming City.Additionally， the grey correlation analysis method was used to assess the correlation between the length of the rainy season and urban development in Kunming City.The results indicate that from 1991 to 2020， the start date of Kunming City's rainy season gradually became later， while the end date gradually became earlier， resulting in an overall trend of the rainy season getting shorter.Wavelet coefficient analysis revealed that there was no obvious regularity in the variation of the rainy season's length on time scales below 8 years， but on a 17-year time scale， there was a noticeable cycle of short-long-short-long-short variations， The rainy seasons from 2003 to 2008 and from 2014 to 2017 were relatively long， while the rainy seasons from 1991 to 2002， 2009 to 2012， and 2018 to 2020 were relatively short.The unclosed contour lines from 2018 to 2020 indicate a further trend of shortening.The M-K test showed that the length of the rainy season in Kunming City experienced four abrupt changes between 1991 and 2020， Occurring in 2002， 2008， 2012 and 2017.Regarding the relationship between Kunming's urban development and the length of the rainy season， the variation trend of the rainy season length during the slow urban development period remained relatively stable.However， after 2004， during the rapid urban development period， there was a significant reduction in the length of the rainy season in Kunming City， Extreme volatility became more pronounced as the urban development process accelerated.The SPSS （Statistical Product and Service Solutions） was used to predict the duration of rainy season in the next 10 years in Kunming City， The results show that the rainy season will continue to be shorter in the next 10 years in Kunming.When the grey correlation resolution was set at 0.5， four factors representing the urban development process had varying degrees of influence on the length of the rainy season in Kunming City， with correlation coefficients all exceeding 0.70， the results show that there is a significant correlation between the urban development and the length of rainy season in Kunming.Among these factors， the most influential one was the year-end total population， while the least influential was per capita GDP， with grey correlation coefficients of 0.88 and 0.70， respectively， signifying a high and significant correlation.The order of correlation coefficients for the four factors is as follows： year-end total population > urbanization rate > urban built-up area > per capita GDP.
Based on multi-source data， this article identifies and reconstructs a severe drought event in the modern Tarim Basin.The results show that in the early 20th century， especially in 1917 and 1918， an arc-shaped drought zone formed along the northwest to southwest edge of the basin.The temperature in the Kashgar and Yarkant River basins decreased， precipitation reduced， and the river flow at the north and south edges of the basin reached its lowest level in nearly a hundred years， resulting in severe drought.The drought zone overlapped with the population distribution and irrigation hotspots within the basin， intensifying the conflict between humans and water， and causing severe canalization of water bodies.At the same time， some water systems within the basin disintegrated， water bodies dried up， the desert expanded， endangering rivers， lakes， marshes， and vegetation.Some animal populations became extinct due to the degradation of their habitats.The climatic background of this drought event may be related to the suppression of warm and moist westerlies caused by the North Atlantic Oscillation （NAO）， and the strengthening of the Arctic cold and dry air masses.
Using the precipitable atmospheric water vapor （PWV） data of 17 ground-based GPS remote sensing stations， hourly and daily precipitation data of 14 meteorological stations in Tarim Basin and its surrounding areas from July 2018 to June 2022， this study analyzed the PWV distribution characteristics and its relationship with precipitation in the western （region A） and the eastern （region B） part of Tarim basin.The results show that： （1） The average annual PWV is largest in the northern and southwestern plain areas of the basin， and the average annual PWV is inversely proportional to the altitude at stations with over 1300 m， while that concentrated on 10~12 mm at stations with altitude below 1300 m.The average PWV value in summer is twice than that in spring and autumn at all GPS stations.（2） The monthly distribution of PWV in region A and region B presents a unimodal type， with the peaks occurred in August and in July， respectively.On the rain-day and no-rain day in region A， the both peak value of PWV occurred at 23:00 （Beijing Time， after the same）， While， the peak value of PWV occurred at 11:00 on rain-day and 17:00 on no-rain day in region B， respectively.（3） The peak of ΔPWV （PWV minus monhly mean PWV） at most stations occurred at 0~1 h before precipitation start time in region A， and within 1 h before and after precipitation in region B.In spring， the variation of PWV before the precipitation in region B is more severe than that in region A.In summer， there are more weather processes with σPWV （PWV divide monthly mean PWV） reached 1~1.8 times at 1 h and 5~6 h before the beginning of precipitation in region A and region B.In autumn and winter， The peak of σPWV are concentrated in 1.4~2.0 times and 1.6~2.4 times in region B， respectively.（4） At the end of precipitation in stations with altitude below 1400 m， the PWV value was concentrated in 10~20 mm during May to June and in 15~25 mm during July to August.In stations with altitude over 1400 m， the PWV value is increasing from 15~25 mm to 25~35 mm from May to August at the end of precipitation.
As the main mechanism of extratropical cyclogenesis， moist baroclinic instability plays a central role in the study of cyclone thermodynamics， which can be further divided into four categories： dry baroclinic instability， moist instability， diabatic Rossby wave and Type C cyclogenesis （tropopause intrusion）.The '7·20' heavy rainstorm was caused by the eastward movement of a Yellow River cyclone into North China after its rapid formation on July 18， 2016.Compared with the mature stage of the cyclone， the mechanism of the initial stage is still unclear.This article uses ERA5 reanalysis data and WRF model to study the moist baroclinic instability of the cyclogenesis event numerically.The results show that mid-lower troposphere presented diabatic Rossby wave pattern， that is， the eastward movement of the system was mainly driven by the cycle of vertical motion and diabatic effect.The vertical motion on which the wave relied was more provided by vorticity advection.The PV sink and the ageostrophic wind in the upper layer delayed the eastward movement of the tropopause intrusion PV， maintaining the phase difference between upper and lower layers.Finally， a PV column formed throughout the troposphere in front of dry intrusion.Using piecewise PV inversion， several sensitivity runs are designed to remove unbalanced circulation， tropopause dry intrusion PV and lower-level diabatic-produced PV from the initial field， respectively.Combined with the analysis of generalized omega equation， it shows that the baroclinic wave in this process must be coupled with the diabatic process with the help of sufficient water vapor to develop strongly.The cyclogenesis was suppressed when the latent heat was turned off.Dry baroclinic instability cannot explain this process.The removal of initial unbalanced field did not affect the baroclinic instability but will delay development of the system.Limited by humidity and mesoscale circulation structure， the active area of lower-level unbalanced flow was controlled by dry baroclinic dynamics.In this case， the gradient of was too small to organize eastward diabatic Rossby wave by relying only on the initial lower-level PV.Nor can strong lower-level diabatic heating generate as in Type C cyclogenesis by tropopause intrusion.For this Yellow River cyclogenesis case， it is required the initial lower-level PV anomaly to be strong enough to counteract the suppression of the cooling subsidence in front of dry intrusion； on the other hand， it is also required that the dry intrusion， in an appropriate initial phase difference with the lower system， strengthened the ascending motion east of the low-level PV in form of vorticity advection through vertical penetration， so as to promote the eastward momentum of diabatic Rossby wave to enter north China with more saturated environment.None of dry baroclinic instability， diabatic Rossby wave and Type C cyclogenesis could independently explain this cyclogenesis event， which was an initial optimal perturbation growth under the combined effect of diabatic Rossby wave and tropopause dry intrusion.
Using daily 700 hPa geopotential height charts from October 2013 to October 2022， Southwest Vortex （SWV） annual data， European Centre for Medium-Range Weather Forecasts （ECMWF） ERA5 reanalysis data， and precipitation data from stations in Shaanxi Province， a statistical and diagnostic analysis was conducted on individual cases of heavy rain induced by the Southwest Vortex in southern Shaanxi.The results reveal the following insights： （1） Over the course of 10 years， there were a total of 119 days with heavy rain， among which 38 days were associated with heavy rain caused by the Southwest Vortex， accounting for about one-third （32%） of the total heavy rain days.These events were mostly observed from May to September， with the highest frequency in June.Statistically， the precipitation tended to start at night and end during the day.（2） The Southwest Vortex influencing southern Shaanxi originates primarily from the basin vortex， and typically， its movement eastward by 12 to 24 hours can lead to heavy rain in the region.The heavy rain area associated with the Southwest Vortex is mainly located in the northeast quadrant of the 700 hPa vortex center， to the south of the shear line， in the area with a large gradient of potential pseudo-equivalent potential temperature， at the intersection of the 500 hPa westerly trough and the outer southwest flow of the subtropical high， corresponding to the region of strong divergence at the 200 hPa level.（3） The study of the vertical structure of the Southwest Vortex indicates that the strong convergence center at 700 hPa is located to the east of the positive vorticity center.This region corresponds well with the heavy rainfall area.Strong divergence under high-altitude jet streams leads to air quality adjustment， lower-level convergence， and frontal genesis.（4） There are three moisture transport channels： one comes from the warm sea surface of the western Bay of Bengal， the second originates from the warm sea surface in the eastern Bay of Bengal， and the third derives from the South China Sea.During heavy rain periods， the cyclonic-like vorticity， divergence， moisture flux divergence generated by the terrain in the Qinba Mountain region combined with the systematic vorticity， divergence， and moisture flux divergence， enhancing the lower-level convergence.This is also an important factor contributing to the formation of heavy rain induced by the Southwest Vortex in southern Shaanxi.
To prepare for the heavy rainfall resulting from future climate change in the upper reaches of the Yangtze River， this paper analyzed daily precipitation data from 687 meteorological stations in the region between 1990 and 2014， as well as simulation results from 24 global climate models （GCMs） provided by the Coupled Model Intercomparison Project Phase 6 （CMIP6）.The spatio-temporal characteristics and uncertainties of the mean annual rainstorm volume， rainstorm days and rainstorm intensity in the upper reaches of the Yangtze River during 2021 -2099 under different Shared Socioeconomic Pathways （SSPs） scenarios are studied.The results show： （1） Compared to the reference period of 1995 -2014， the mean annual volume， days and intensity of rainstorm in the upper reaches of the Yangtze River are projected to increase and strengthen during the whole projection period of 2021 -2099 and the end of the 21st century （2080 -2099） under the SSP1-2.6， SSP2-4.5， and SSP5-8.5 scenarios.The largest increase is observed under the SSP5-8.5 scenario.The predicted direction is consistent and the certainty of the projection among models increases with higher emissions.The distribution of rainstorm volume， days and intensity during 2021 -2099 is similar under SSP1-2.6 and SSP2-4.5 scenarios， but differs from that of the SSP5-8.5 scenario.By the end of the 21st century， the distribution of volume and days of rainstorm is similar under the three scenarios.However， the distribution of rainstorm intensity under the SSP5-8.5 scenario differs from that under the SSP1-2.6 and SSP2-4.5 scenarios.（2） Relative to the reference period， the rainstorm volume in the upper reaches of the Yangtze River increases by 3.5 mm·（10a）-1， 5.4 mm·（10a）-1 and 14.7 mm·（10a）-1 under SSP1-2.6， SSP2-4.5， SSP5-8.5， respectively.The rainstorm days increases by 0.045 d·（10a）-1， 0.07 d·（10a）-1 and 0.18 d·（10a）-1 under the three scenarios， respectively.The rainstorm intensity increases by 0.37 mm·d-1·（10a）-1， 0.78 mm·d-1·（10a）-1 and 1.94 mm·d-1·（10a）-1 under the three scenarios， respectively.All of the trends pass the 99% confidence test and the same-sign rate test.The period with a high level of prediction certainty is expected to occur in the late 21st century under the SSP5-8.5 scenario.（3） The analysis of the three scenarios indicates an increasing trend in the volume， days and intensity of rainstorm throughout the whole prediction period.The region of southeast Tibet has experienced the highest growth rate in terms of volume and days of rainstorms.The region with the largest increasing trend of rainstorm intensity under the SSP1-2.6 scenario is in northern Sichuan， while under the SSP2-4.5 and SSP5-8.5 scenarios， it is in northern Yunnan.（4） During the early 21st century（2021 -2040）， there is no significant change in the volume， days or intensity of rainstorm in the upper reaches of the Yangtze River， as compared to the reference period， under the three scenarios.While during the middle（2041 -2060）and the end of the 21st century， the volume， days and intensity of rainstorm increase significantly under the SSP2-4.5 and SSP5-8.5 scenarios.This effect is particularly pronounced during the end period of the 21st century under the SSP5-8.5 scenario， as well as the consistency of predicted direction among modes is the highest.
We conducted a comprehensive analysis on the causes of prolonged maintenance and widespread precipitation after the landfall of Typhoon Chaba， using the best track data from the Shanghai Typhoon Research Institute of the China Meteorological Administration， the FNL 0.25°×0.25° reanalysis data and the NOAA 0.5°×0.5° global daily precipitation data.The results show that the main moisture source of the remnant of Chaba in the first phase （3-4 July） was the southerly low-level jet， and the second phase （5-6 July） it was mainly the combination of the southerly low-level jet and the boundary layer easterly jet， which resulted in a rare entire atmosphere precipitable water of 75 mm.The vertical wind shear and water vapor convergence formed by the coupling of the double low-level jets provided favorable dynamic conditions for the occurrence and maintenance of heavy rainfall.A cold pool was formed near the surface to the west of the vortex with the intrusion of cold air， which caused the Chaba remnant to gradually degenerate into an extratropical cyclone with a significant increase in baroclinic kinetic energy.In the view of potential divergence diagnosis， we found that as the Chaba remnant kept moving northward to approach the subtropical westerly jet， the vertical wind shear at high and low levels increased.The cold air carried by the high-altitude cold vortex turns the Chaba residual vortex to baroclinic system.The easterly wind jet in the boundary layer increased the instability of the layer below 850 hPa， which provided unstable energy conditions for the occurrence and maintenance of heavy rainfall.
In this paper， the gale events are defined firstly.Using ERA5 reanalysis data， the variation characteristics of the sea surface wind speed and the gale events from 1979 to 2021 were analyzed.The variation characteristics of sea surface wind speed and gale event in the South China Sea from 1979 to 2021 were analyzed using methods such as the empirical orthogonal decomposition.Specifically， the effects of tropical cyclones were distinguished.The results show that the distribution of wind speed in the South China Sea has obvious seasonal characteristics with the northeast wind in winter and in the summer， the wind direction turns to be southwest.Except for the northeast coastal areas， the mean wind speed in the spring time experienced a decreasing-increasing-decreasing character.While in the summer， it turns to a kind of increased-decreasing-increasing trend and the overall trend is decreasing.The consistent change of wind speed in the whole area of the South China Sea in the autumn shows a decreasing trend.In the winter， the wind speed in the southeast of the South China Sea is opposite to the rest aera， with a significant increase in wind speed except for the southwest.The frequency of the gale events that occur in the winter and in the autumn is higher than that in the spring and autumn， and the frequency of the gale events in the winter half year is higher than that in the summer half year.In the winter or winter half year， the frequency of the gale event has a significant increasing trend， especially in the area from the east of the Annamese Cordillera to area near the Taiwan Strait， through the central part of the South China Sea， in the northeast part of the South China Sea.The variation trend of the frequency of gale event in the winter and spring is opposite to that in the summer and autumn.The changes of the frequency of gale event in the summer half year combines the characteristics of the variation trends in the summer and autumn.Similarly， gale event that occur in the winter half year combines the variation trends of winter and spring.During the seasons affected by the South China Sea summer monsoon， such as summer， autumn， and the summer half year， tropical cyclones have a greater impact on the frequency of gale event which is different from the gale event that appearance in the winter， spring and winter half year.
Extreme weather and climate events caused by El Ni?o have significant impacts on socio-economic conditions and the safety of people’s lives and properties.Between 2014 and 2016， a super El Ni?o event occurred， leading to frequent extreme weather and climate events worldwide.This study focuses on the Indochina Peninsula region and explores the potential reasons for abnormally decreased precipitation in April 2016， against the backdrop of the super El Ni?o event.The research utilizes monthly observations and reanalysis data of sea temperatures， precipitation， wind fields， and specific humidity to investigate circulation patterns and abnormal moisture transport.The results indicate that in April 2016， the ICP experienced anomalous sinking currents due to the influence of a developing and robust Western North Pacific Anti-Cyclone and subtropical high-pressure systems.These conditions hindered moisture convergence necessary for precipitation formation.Furthermore， through dynamic diagnostic analysis， the study finds that the product of the Nino3.4 index and the zonal gradient of SST anomalies （GSSTA） between the equatorial East Indian Ocean and the equatorial Western Pacific Ocean effectively indicates the super El Ni?o event.Additionally， the modulation of nonlinear moisture advection over the ICP plays a vital role in the abnormally low precipitation in the region in April.During the 2015/2016 El Ni?o event， conflicting wind patterns emerged between the easterly winds on the southern side of the WNPAC and the anomalous westerly moisture transport guided by GSSTA.This conflict weakened the moisture transport from the Pacific Ocean and the Bay of Bengal to the ICP.Over the ICP， most of the moisture exhibited a pattern of being less in the south and more in the north， with higher levels in the east and lower in the west.This led to moisture divergence， which was unfavorable for precipitation formation.In summary， this study emphasizes the significant influence of a super El Ni?o event on extreme weather and climate events， particularly focusing on the abnormally decreased precipitation over the Indochina Peninsula in April 2016.By examining circulation patterns and moisture transport anomalies， the research contributes to understanding the underlying causes and dynamics of these events.The findings have implications for future weather predictions， climate change assessments， and the development of effective strategies to mitigate the impacts of extreme weather events in the Indochina Peninsula region.In April 2016， under the combined action of the Bay of Bengal anomalous anticyclonic and the Western North Pacific Anti-Cyclone， the Indochina Peninsula convection was suppressed， and the warm and wet air was transported to South China under the guidance of the anomalous south wind.
Many new-generation Doppler weather radars in China are located in mountainous areas with complex topography， and the problem of low elevation angle terrain occlusion is prominent.When estimating precipitation by radar in the occluded area， observations with higher elevation angles need to be used， and due to the micro-physical changes and horizontal motion of precipitation particles during their descent， the reflectivity factor at high locations of the same site is often very different from that near the surface， which will increase the estimation error when used directly for estimating surface precipitation.In this paper， we propose a method for the vertical revision of reflectivity factor.First， we establish the vertical reflectivity factor profiles （VPR） of different precipitation types in the unobstructed observation area， and then revise the observations above the height to be revised to the target height by determining the height threshold to be revised and the near-surface target height based on the vertical variation characteristics of the profiles.The comparison test results show that： the revised target reflectivity factor data are less different from the actual observed data values， and the consistency is improved； moreover， the data at low VPR are more accurate by considering the occlusion factor； since the VPR of different precipitation types are significantly different， the differentiation of precipitation types can avoid mis-correction.The proposed revision method is not only applicable to the beam blocking area， but also generally applicable to the revision of the observed data at high beam height at long distances.
The Qaidam Basin is sensitive to the warming and humidification trend of climate change on the Qinghai-Xizang Plateau， and an ecologically vulnerable region.Evaluating its spatiotemporal patterns of precipitation is crucial for the rational utilization of water resources as well as ecological management.However， the scarcity and uneven distribution of meteorological stations within the basin poses a challenge to such analysis.This study was to explore an optimal method for precipitation interpolation in the basin in this context.Specifically， the Australian National University Spline （ANUSPLIN） model was used for the interpolation with different numbers of meteorological stations （9， 20， 40， 60， 80， 100， 120 140， 160 and 180 stations） within and around the basin and 9 kinds of thin disk smooth spline functions （various combinations of independent variables， covariates and spline times）.We screened the optimal number of interpolation stations and the optimal function by accuracy assessments using the data in 2019.The spatiotemporal patterns of precipitation in this region from 2000 to 2019 were then analyzed.The results showed that： （1） The ANUSPLIN model achieved the highest accuracy with 120 meteorological stations and the function of trivariate local thin disk smooth spline （TVPTPS4）.The root mean square error （RMSE）， expected true mean square error （RTMSE） and signal-to-noise ratio （SNR） were less than 0.6 mm， 0.3 mm and 0.25， respectively， which was the lowest among all combinations.（2） Precipitation in the Qaidam Basin had substantial differences in regional distribution and seasonality.Both annual precipitation and seasonal precipitation were abundant in the east and scarce in the west， while the precipitation in summer was the highest， accounting for 62.13% of the annual total value.（3） From 2000 to 2019， both the annual precipitation and seasonal precipitation in the basin showed an increasing trend.The precipitation in summer showed a significant increasing trend， with a maximum growth rate of 5.85 mm·a-1 （P<0.05）.The regions with significant trend accounted for approximately 42.36% of the total area of the basin.The results of this study demonstrate that the AUNSPLIN model can accurately reflect the distribution of precipitation in the Qaidam Basin， comparing with the ordinary Kriging and the inverse distance weighted methods.Obtaining an accurate precipitation patterns is of great theoretical and practical significance for the optimal management of water resources in the region.
Using the basic data from four C-band Doppler weather radars and ground observation data in Shanxi province， the statistical analysis of the V-shaped gap features observed in Shanxi from 2009 to 2017 was conducted.The correspondence between V-shaped gap observed by Doppler radar and hailfall was investigated， and the forecasting and warning indicators for hail using V-shaped gap features were summarized.Real-time operational applications were carried out from 2018 to 2022 to validate and refine forecasting and warning indicators of the V-shaped gap.The results indicate that hailfall begins after the appearance of V-shaped gap and ends before their disappearance.There is no significant correlation between the probability of hailfall and the initial height of V-shaped gap.When the corresponding updraft height of V-shaped gap is ≤4 km， hailfall does not occur.The ideal observation elevation angle for V-shaped gap ranges from 2.4°to 6.0°， with 2.4°being the optimal angle.The strongest phase of hailfall is characterized by a "butterfly-shaped" intense echo region.The predictive indicators and focal points during the initial stage of hail forecasting and early warning include： （1） the presence of a weak or marginally weak echo region when a V-shaped gap appears； （2） a length of the V-shaped gap along the radial direction > 30 km， or an initial length of the V-shaped gap along the radial direction <30 km and an updraft extending above 4 km； （3） average radial velocity showing low-level convergence and high-level divergence characteristics.Meeting these three criteria can predict the occurrence of hail.If a V-shaped gap is first observed at a 6.0° angle， a forecast can be made for the occurrence of large hailstones （with a diameter greater than 1 cm）， and an immediate forecasting and warning signal can be issued.The predictive indicators and focal points during the duration of hail include： （1） continuous decrease in the height of the strong echo center > 50 dBZ and echo top > 10 km； （2） a slanted weak echo region corresponding to the V-shaped gap， with high-level divergence and low-level convergence characteristics in the average radial velocity field； （3） stable maintenance of the weak echo region or marginally weak echo region； （4） continuous occurrence of hail can be predicted when the V-shaped gap is observed at a 0.5° angle， and an increase in hail intensity can be foreseen when the strong echo region exhibits a "butterfly" shape； （5） When the maximum vertical liquid water content exceeds 22 kg·m-2， the vertical liquid water content jump increment exceeds 26 kg·m-2， and the vertical liquid water content density exceeds 3.6 g·m-3， the probability of hail is high.
Based on the MODIS MCD19A2 aerosol dataset， the temporal and spatial distribution characteristics of the atmospheric aerosol optical thickness （AOD） and the influence of meteorological factors in the Qaidam Basin from 2001 to 2021 were investigated by using linear trend， Spearman correlation analysis， and ?ngstr?m exponential interpolation， and the results show that： （1） On the interannual scale， the AOD in the Qaidam Basin fluctuates upward， with an annual increase of 3.74% and an annual mean value of 0.110±0.002； on the seasonal scale， AOD has obvious seasonal changes， and its value from high to low is spring， summer， autumn and winter， respectively.AOD in spring and summer fluctuates， while AOD in autumn and winter has no obvious change.on the monthly scale， the AOD is in the shape of a single peak， and the peak value is in April.（2） In space， the high value area of AOD is located in the hinterland of Qaidam Basin， showing the distribution characteristics of high in the middle and low around， and the low value area is located in the high altitude areas such as Kunlun Mountain Range and Qilian Mountain Range and the area with high vegetation cover.（3） Meteorological factors have a certain influence on AOD， among which wind speed， temperature， relative humidity， cloudiness and precipitation are positively correlated with AOD， and wind speed and temperature have the greatest influence on AOD.
Studying the formation and evolution mechanism of heavy pollution haze events is beneficial to control the regional scale air quality and to formulate the prevention policies of severe haze pollution.Based on the WRF-CMAQ model and actual observation data， a severe haze event which occurred in Chengdu of Sichuan Basin from December 23， 2016 to January 7， 2017 was reproduced.The distribution of temporal and spatial variations of PM2.5 concentration and ventilation coefficient， the physical and chemical processes and the distribution of potential pollution source areas were analyzed to study the formation and evolution mechanism of this severe pollution haze event.Major results were as follows： （1） The environmental conditions of low temperature and low wind speed during the haze event created favorable conditions for the accumulation of pollutants.（2） The northerly airflow in the north of the basin， the southwesterly airflow in the south and the lower ventilation coefficient value （weak turbulent diffusion capability of atmosphere） were the main reasons for the accumulation of pollutants.The PM2.5 concentration in Chengdu reached the peak under the influence of the northeast airflow.The dissipation of pollutants was mainly because of the strengthening of the northerly airflow and the higher ventilation coefficient value （strong turbulent diffusion capability of atmosphere）.（3） The positive contribution of the aerosol process and emission sources in this haze event was strengthened.And the increase in PM2.5 was mainly at night （the negative contribution of the advection process and the weak diffusion process） and the magnitude of the increase was greater relative to the decrease， resulting in an overall gradual increase in PM2.5.（4） PSCF and CWT analysis showed that the airflows with high PM2.5 concentration in Chengdu mainly came from its northeast and southwest directions during this haze event， and the potential pollution source areas were generally distributed in a northeast-southwest band.
Wind farm wakes have a significant impact on momentum and turbulence fluxes within the atmospheric boundary layer， thereby influencing the local climate and environment.Mesoscale numerical models incorporating wind farm parameterizations are powerful tools for studying the climate and environmental impacts of wind farms.In this study， the wind speed and turbulence kinetic energy profiles of the Fitch wind farm parameterization scheme in the WRF mesoscale model are evaluated in the turbine and wake regions using high-resolution Large Eddy Simulations （LES） as “true values” and a method based on the relation derived from classical momentum theory is proposed to correct the grid-inflow wind speed.The method takes into account the blocking effect caused by the grid equivalent thrust and the corrected wind speed is closer to the free-stream wind speed.Results show that the difference between the grid-inflow wind speed from the original Fitch parameterization scheme and the LES is significant and sensitive to the model horizontal resolution.The Fitch-new parameterization with corrected grid-inflow wind speed reduces the relative error in absolute value between grid-inflow and free-stream wind speed to less than 1% across different horizontal resolutions （1000 m， 500 m， and 250 m）.The spatially averaged thrust and output power are consistent with LES results.The Fitch-new parameterization improves the simulated wind speed deficit in the wake zone of wind turbine， especially in the grid with turbine under high resolution.Although the simulated increase in turbulent kinetic energy and its vertical distribution in the wake zone is improved compared to the original Fitch scheme， there are certain issues that require further investigation.
Gansu-Yellow River basin is a natural-social-economic complex ecosystem intertwined with ecological and development issues.Soil conservation service （SCS） is an important safeguard for preventing soil erosion and promoting high-quality development in this region.Combining with the Revised Universal Soil Loss Equation（RULSE）， we obtained the annual SCS dataset for Gansu-Yellow River basin from the Standardized Vegetation Difference Vegetation Index， Land Cover Type product MCD12Q1， precipitation data， Digital Elevation Model data and the Harmonized World Soil Database version 1.1.The times span for this SCS dataset ranges from 2001 to 2015， with spatial coverage between 33°6′29″N -40°0′6″N and 97°23′38″E -108°42′38″E.This study offers a scientific basis for developing measures to improve SCS， and provides important data support for assessing ecological security and constructing ecological security pattern.The URL for obtaining the entity dataset is http： //www.ncdc.ac.cn/portal/metadata/a918f7ed-5988-44ea-80ad-ee14acab89aa.
