Abstract:Using the ozone data of five national control points in southern Jiangsu Province from 2019 to 2021,the observation data of national meteorological stations in the same period and the ERA5 reanalysis data,this article analyzes the spatio-temporal distribution characteristics of ozone pollution in southern Jiangsu and its relationship with relevant meteorological elements,and,meanwhile,classifies the weather conditions causing ozone pollution.The results show that the diurnal variation difference of ozone concentration among five cities of southern Jiangsu mainly occurs in the daytime,and the annual ozone concentration distribution has two peaks.When the temperature is 30-35℃,the sunshine time exceeds 10 hours,the relative humidity is 30%-60%,the wind speed is 1-3 m/s and the wind direction is prevailing southerly,the ozone excess pollution rate can reach its maximum value.The over-standard ozone pollution rate in Suzhou is significantly lower than that in the other four cities.When analyzing the excessive ozone pollution in the entire area of southern Jiangsu,except for Suzhou,60%of the backward trajectory in the Suzhou area mainly passes through the ocean to the east.In addition,the higher total cloud cover and lower total radiation in Suzhou are not conducive to the formation of ozone through photo-chemical reactions.There are three major types of synoptic situation for ozone pollution in southern Jiangsu,namely,the northwest airflow behind the trough pattern(69%),the short wave trough pattern(17%)and the subtropical high control pattern(14%).The main transmission paths in the backward trajectory of Nanjing and Suzhou under the control of the northwest airflow behind the trough are the northeast trans-port from the Yangtze River area in Anhui Province and the northwest transport from the vicinity of Hang-zhou Bay,respectively.

Abstract:Using micro-climate data from winter wheat fields and ground meteorological observation data in Qihe County,Jiyang District and Shenxian County in the Northwest-Shandong plain from 2019 to 2022,this paper investigates the vertical distribution characteristics of air temperatures in winter wheat field during the late growth stages of winter wheat under late-frost and dry-hot wind conditions.Moreover,the differences in the temperatures at 150 cm height between the farmland station and the ground meteoro-logical station are compared.The prediction models of maximum and minimum temperature in different weather types and different field altitudes during key growth stages of winter wheat are constructed.The results are as follows:(1)During late-frost events,the closer the field air temperature is to the ground vertically,the lower the minimum temperature is;the earlier the temperature drops to 0 ℃,the longer the duration of below-freezing temperature is.Compared to the temperature observation at the ground weather station,the minimum temperatures recorded at farmland station are lower.The onset time of cool-ing and the time of dropping to 0 ℃ come early,and then the duration of below-freezing temperatures stays longer.(2)During dry-hot wind events,the closer the farmland field temperature is to the ground vertically,the higher the maximum air temperature,and the earlier it reaches 33 ℃,a longer duration of temperature above 33℃ will be.The maximum temperatures recorded at the field stations are higher than those at the ground observation stations.The warming onset time and the time of reaching temperatures above 33 ℃ occur earlier,and then the duration of high temperatures above 33 ℃ is longer.(3)By utili-zing meteorological elements such as air temperature,air humidity and wind speed from the ground obser-vation stations,the minimum and maximum temperature prediction models for the key growth stages of winter wheat in the farmland fields are established.The prediction accuracy of these models varies in the three counties(districts)of the Northwest-Shandong Plain,with the forecast in Qihe performing better than in Shenxian,and the forecast accuracy in Jiyang being the lowest.The minimum temperature model in Qihe has coefficients of determination(R2)above 0.904.For farmland fields,the prediction perform-ance of the maximum temperature model is better than that of the minimum temperature model.The accu-racy of the minimum and maximum temperature prediction models for cloudy and clear days is higher than that for days with partly cloudy skies.

Abstract:Using minute-resolution precipitation data from Zhengzhou National Basic Meteorological Observing Station between April and October in 1955-2021,this article studies the autocorrelation of precipitation data and the sensitivity of precipitation events and change in intervals between them.Based on the establishment of a reasonable rainfall interval of 120 min,the evolution law of precipitation events under different durations in Zhengzhou is analyzed.The results show that:(1)From 1955 to 2021,there are about 4150 rainfall events with the precipitation mainly below 5 mm,the duration shorter than 3 h,and intensity lower than 2.0 mm·h-1.The break intervals between two rainfall events less than 6 h ac-count for 10.58％.(2)The precipitation duration in Zhengzhou exhibits a significant decreasing trend at a rate of-0.99 d/decade,while the average annual precipitation intensity and the annual maximum pre-cipitation intensity of the rainfall events are on the growing sides at rates of 0.15 mm·h-1/decade and 3.01 mm·h-1/decade,respectively.(3)The average annual precipitation intensity presents a distinct increasing trend,indicating that the precipitation structure in Zhengzhou has shifted towards extremely heavy precipitation from 1955 to 2021,especially since the 1990s.(4)Since the 1990s,short-duration heavy precipitation has become more frequent.For the rainfall events lasting for 1-3 h from 1991 to 2021,the precipitation frequency,amount,annual average intensity,and annual maximum intensity all show the trends of increasing significantly.

Abstract:Against the backdrop of global warming and accelerated urbanization,regional thermal environment is one of the important factors affecting urban ecological livability.Reasonable urban plan-ning can minimize meteorological disasters such as high temperatures and heat waves caused by regional thermal environment,and it is also one of the scientific issues that need to be solved in urban planning,construction and development.In this research,employing the WRF V4.2,we conduct comparative tests,analyze the simulated impact of urban planning on a high temperature process in Xiongan New Area on July 10,2016,and study the response of regional thermal environment to urban construction plan-ning.The research results show that:(1)Introducing high spatial-resolution land-use data to simulate the temperature in Xiongan New Area can accurately reflect the temperature changes inside the region.The absolute value of average relative error of temperatures is 1.68℃,and the stations with the absolute val-ue of average relative error≤2℃account for 76%.(2)The urban planning of Xiongan New Area mainly affects the daytime temperature.After the planning implementation,except for the slight increase of tem-perature in the starting area,Rongcheng group,and Zan'gang group,the 24 h mean temperature in most parts of the New Area is reduced by 1-2℃.(3)The urban and rural planning scheme of"one main,five auxiliary,and multiple nodes"in Xiongan New Area is good for degrading the high temperature and thermal environment in the region.The impact of high temperature in the entire region is shortened by 1-2 h,with 45.93%of the New Area showing a decrease in normalized thermal field intensity.Especial-ly,the growth in the water area of Baiyangdian Lake has effectively alleviated the urban heat island effect in Xiongan New Area.

Abstract:By using the radiosonde data and the ambient air quality data in Chengdu from 2015 to 2018 as well as the weather research and forecast(WRF)model,this article analyzes the characteristics of temperature inversion structure and its influences on air pollution during typical heavy pollution proces-ses in Chengdu.The results show that the dominant pollutants in Chengdu are PM2.5 and O3 throughout the whole year.During the typical PM2.5 pollution processes,the frequency of temperature inversion rea-ches 90％,and most belongs to the type Ⅱ multi-layer inversion(the surface-based inversion overlaid with the lower troposphere inversion),accounting for 60.96％.The superposition of multi-layer inversion makes it more difficult for air pollutants to disperse than under general inversion,and contributes more to the increased possibility of moderate and heavy pollution.During the typical O3 pollution processes,the frequency of temperature inversion is 41％,and most are the surface-based inversion and mainly appears in the period of mild pollution,taking up 64.75％.The surface-based inversion in the early stage of pollu-tion process restricts the diffusion of O3 and its precursors near the surface,but it is not the key meteoro-logical factor that causes heavy O3 pollution.

Abstract:This study aims to clarify the response of the growth period and yield of early rice in the Pearl River Delta region to changes in climate factors with different sowing dates,and to provide a scien-tific reference for the rational arrangement of early rice sowing dates to achieve high yields in the region.Based on the staged sowing experiment at the Guangdong Agricultural Meteorological Experimental Station from 2018 to 2021,the response characteristics of yield components,including the length of growth peri-od,yield,effective panicle number,grain number per panicle,seed setting rate,and thousand grain weight of the conventional early rice variety"Yefengzhan"to climate factors under different sowing dates are studied by means of correlation coefficient and variation coefficient,etc.The results show that:(1)With the delay of sowing dates,the average temperature during the growing season of early rice increases,the growth period is shortened,and the variation range of the growth period is smaller than that of the so-wing dates.The yield of early rice is positively correlated to the average temperature during the rice-grow-ing season,effective accumulated temperature ≥ 10 ℃ and accumulated sunshine hours,but negatively correlated to precipitation.Among them,sunshine hour is the major climatic factor affecting early rice yield in the Pearl River Delta region.(2)The high-to-low order of the influence of sowing dates on rice yield components is:effective number of ears≥number of grains per ear ≥ seed setting rate≥thousand grain weight.As the sowing date is delayed,the number of effective ears tends to increase,while the number of grains per ear tends to decrease.The setting rate and thousand grain weight tend to increase first and then decrease.(3)The second and third sowing dates of the experimental year are relatively high-yielding for early rice,and the third sowing date has the least impact on yield fluctuation.The suit-able sowing date for early rice should be postponed appropriately.It is recommended that the sowing date of early rice in the Pearl River Delta region be arranged in the mid-March.

Abstract:Based on daily precipitation data from 38 meteorological stations across Xizang Autono-mous Region during the summer months(June to August)from 1981 to 2023,the temporal and spatial variations of light and moderate rainfall amount,rainy days and rain intensity at different altitudes in Xi-zang are analyzed.The results show that the summer light and moderate rainfall amount,rain days and rainfall intensity at different altitudes in Xizang show significant interannual and interdecadal changes,and their trends all show a decrease in low-altitude areas but an increase in mid-and high-altitude areas.The climate tendency rates of rainfall amount,rainy days and rainfall intensity for light and moderate rainfall in different altitude regions of Xizang are-1.6-2.2 mm·(decade)-1 and-2.7-6.5 mm·(decade)-1,-0.6-0.7 d·(decade)-1 and-0.1-0.3 d·(decade)-1,-0.5-0.8 mm·(d·1000 years)-1 and-0.1-0.2 mm·(d·decade)-1,respectively.The light and moderate rainfall amount,rainy days and rainfall intensity in Xizang are generally distributed in the pattern of higher in the central and eastern part but lower in the western part,which is positively correlated to altitudes.The meteoro-logical stations having the upward trends are mainly located in the high-altitude areas of central Xizang,while the stations with the downward trends are situated in the low-and mid-altitude areas of the central and eastern Xizang.Among the 38 meteorological stations,the variation trend of light rain is primarily driven by changes in the number of rainy days at 13 stations and by changes in rainfall intensity at 25 sta-tions.For moderate rainfall,the variation trend is mainly influenced by changes in the number of rain days at 6 stations and by rainfall intensity at 32 stations.

Abstract:Using the daily hail data and elevation data of 876 surface weather modification operation sites in 9 cities or prefectures in Guizhou Province from 2007 to 2023,the spatio-temporal distribution characteristics of the number of hail days in the province and its correlation with elevation are analyzed.Further,7 indicators such as the number of hail days,terrain elevation and operation site distribution are selected as the evaluation indexes of three factors of hail risk zoning,i.e.,hazard-causing factor risk,hazard-forming environment sensitivity and disaster prevention and mitigation capability.Based on Ana-lytic Hierarchy Process(AHP),Geographic Information Systems(GIS)and other methods,the hail risk zoning in Guizhou is analyzed and studied.The results show that during the recent 17 years,the number of hail days in Guizhou has generally shown a fluctuating upward trend year by year.The distribution characteristics of hail in this province show obvious monthly and daily variations.The monthly variation of hail is unimodal,following a relatively standard parabola.The time period of hail events is mainly con-centrated in March to May each year,accounting for 73.4％of the total number of days with hail.The daily distribution of hail is dominated by the afternoon and night type[15:00,23:00),accounting for as high as 83％,followed by the night and morning type[23:00,07:00),taking up 12％,and then the morning and afternoon type[07:00,15:00),being 5％.The number of hail days in Guizhou varies greatly among regions,mainly showing a decrease trend from southwest to northeast.This is consistent with the terrain of Guizhou,which is high in the west and low in the east.Further research reveals that there is a very significant positive correlation between the number of hail days and the elevations of Guizhou,with the correlation coefficient reaching 0.608.Moreover,the risk of hail disasters in the northwestern and southwestern regions of Guizhou is relatively high,and the degree of hail risk is decrea-sing from west to east.

Abstract:Based on the hourly observation data and high-altitude situation field of 359 national sta-tions from April to September of 2000-2019,the NCEP reanalysis data and the best typhoon track data of Joint Typhoon Warning Center(JTWC)over the years,this paper studies the characteristics of warm-sector rainstorms in the middle and lower reaches of the Yangtze River.The results show that:(1)The warm-sector rainstorms occur 10.4 times a year on average in the middle and lower reaches of the Yangtze River,mostly in the period from June to August.The daily maximum precipitation at a single station is 53-226 mm,and the rainfall duration is shorter than 9 h.The precipitation amount from large to small is from the warm shear type,south wind convergence type and subtropical high edge type of rainstorms.(2)The diurnal variation characteristics of warm-sector rainstorm are obvious.The warm-shear-type rain-storm mostly starts in the early morning,and the probability of short-time heavy precipitation and extreme hourly rainfall intensity is the largest.The rainstorms of southerly convergence type and the subtropical high edge type mostly start after noon,and the latter usually lasts for no more than 3 h.(3)In terms of spatial distribution,the warm-sector rainstorms mainly occur in the area south of the Yangtze River,and a single station experiences no more than 5 times of rainstorms in the study period,and the rainstorm peak time arrives in June.The four rainstorm centers are located in western Hunan,the junction of Hu-nan and Jiangxi,northeastern Jiangxi,and the southern parts of Jiangsu and Anhui.(4)The main main-tenance mechanism of the warm-shear warm-sector rainstorm is that the low-level jet transports water va-por and unstable energy to the convergence zone of shear lines.The coupling of the high-level and low-level jets strengthens the convective instability of the atmosphere.Triggered by the boundary layer or the ground convergence line,heavy precipitation occurs.The rainstorm of southerly wind convergence type occurs when the convergence of the low-level southerly wind causes water vapor to accumulate in the rain-storm area,and the intrusion of dry-cold air in the middle layer cooperates with the terrain effect and the ground meso-scale convergence line,triggering the occurrence of severe rainfalls.The rainstorm of sub-tropical high edge type is mainly caused by the release of unstable energy that comes from the afternoon thermal convection.This kind of rainstorms mostly occurs in southern Anhui and the Dabie Mountains.

Abstract:Based on Gaussian distribution and SVM models,this article conducts research on hail identification indicators and algorithms based on seven inversion products from the FY-2G satellite.Using data from 368 sets of FY-2G satellite inversion products for both hail and non-hail spots in 30 hail days in Guizhou Province from 2020 to 2022,and Gaussian distribution,we obtain quantitative hail iden-tification indicators.L-SVM,RBF-SVM,and S-SVM models are established to conduct hail identifica-tion research.The results show that quantitative hail identification indicators can be established for six in-version products based on Gaussian distribution,namely,cloud top height,cloud top temperature,supercooled layer thickness,optical thickness,liquid water path and black body brightness temperature.The SVM models based on the three kernel functions can effectively identify hail for both hail and non-hail spots,with accuracy rates exceeding 70%.Among them,the RBF-SVM model has the highest accu-racy rates for the total sample and non-hail spot samples,at 87.50%and 91.85%,respectively.The S-SVM model performs best for hail spot identification(89.13%).

Abstract:Based on county-level rainstorm disaster data from 2016 to 2022 in Hunan Province,a comprehensive loss evaluation index is constructed by objective methods,which is then classified into four levels.Thirteen explanatory variables are selected by considering disaster-causing factors,environmental factors,disaster-exposed entities and disaster prevention and mitigation capabilities.The comprehensive loss assessment model is developed using Bayesian optimized XGBoost.The results show that:(1)In the comprehensive loss evaluation index,the population loss factor has the highest weight,followed by hous-ing loss and agricultural damage area.(2)The Bayesian optimized XGBoost model demonstrates a good performance,achieving accuracies of 0.86 and 0.83 for the training and testing samples,respectively.(3)The explanatory variables related to disaster-causing factors are the most crucial factors influencing the identification of loss levels,which have the greatest impact(83.11%)on the assessment of severe loss.Particularly,the increase in both the average process rainfall and maximum process rainfall can raise the probability of a sample being classified as a severe loss level.This model is applied and tested for the rainstorm event in Hunan Province from June 1 to 5,2022.Districts and counties that experienced casualties are classified as the severe loss level.The assessment results align well with the collected dis-aster data.

Abstract:Based on the basic quality data of Shine-Muscat from Wuhan Academy of Agricultural Sciences and the daily meteorological data such as temperature,humidity,precipitation,and sunshine duration from 2019 to 2023,this study explored the impact of meteorological factors on four quality indi-ces,such as soluble solids,titratable acids,solid-acid ratio,and single grain weight,and established the relationship model between the meteorological factors and the quality indices.The results showed that the quality indices of Shine-Muscat are influenced by multiple meteorological factors.The key period in which meteorological conditions have influence on soluble solids,titratable acids and solid-acid ratio is July to August.The content of soluble solids has a significantly positive correlation with the average temperature,the mean maximum temperature,the effective accumulated temperature≥10℃in July-August,the aver-age temperature,the mean minimum temperature and the effective accumulated temperature≥10℃in August.The content of titratable acids is significantly positively correlated to the average relative humidity from July to the end of August and the hydrothermal coefficient in August.However,it has significantly negative correlations with the average temperature,average maximum temperature,diurnal temperature range and the effective accumulated temperature≥10℃in August and the average diurnal temperature range from April to September and July to August.The average diurnal temperature range,the average maximum temperature,the average relative humidity and the hydrothermal coefficient in August have the greatest influence on the solid-acid ratio.Moderately increasing the average diurnal temperature range and average temperature and reducing the relative humidity and hydrothermal coefficient during the grape rip-ening period are conducive to improving the solid-acid ratio.Suitable humidity,hydrothermal coefficient and saturated vapor pressure deficit in growing season(April-September)and ripening period(July-Sep-tember)of Shine-Muscat are beneficial to increase in the weight of single grapes.In addition,the climate quality evaluation model of the four quality indices has been established by means of stepwise regression(R2>0.9),which could provide reference for climate quality evaluation of Shine-Muscat in Wuhan re-gion.

Abstract:Based on the FY-4A satellite data and its retrieval products,the C-band Doppler radar data of Qiandongnan Prefecture and the reanalysis sounding data from Kaili Station,the characteristics of a hail weather process that happened in Qiandongnan Prefecture,Guizhou Province,on May 10,2021,are analyzed.Moreover,the feature identification of FY-4A satellite data and products in hail weather and the applying methods in hail monitoring and early warning are discussed.The results show that:(1)The hail cloud developed very rapidly this time,and hail fell two hours after the formation of the cloud cluster.Both hail events occurred in the area with temperatures below-20℃at the rear of the low-value center,and the radar echo intensity was greater than 50 dBZ,which has good indicative signifi-cance for the hail falling area.(2)The average cloud optical thickness was stably maintained above 40,with the maximum value exceeding 100.However,the average effective radius of the particles in the cloud did not exceed 25 μm both before and after the hail fall,indicating that the water content in the cloud was extremely abundant.(3)The microphysical structure characteristics of hail clouds indicate that the vertical development of hail clouds was deep,and the effective radius of cloud particles had little change with the decrease of temperature,remaining at 15-30 μm throughout the whole layer.The small-scale supercooled water droplets in the cloud could be lifted near the cloud top by strong updraft,and there was a certain amount of supercooled water at the cloud top of hail clouds.

Abstract:Based on the observation data of Xinyang meteorological station from 1981 to 2020,the photosynthesis potential productivity,photo-thermal potential productivity and climatic potential produc-tivity and their changing trends at different sowing stages of japonica rice are calculated by the step-by-step correction method.Moreover,the major meteorological elements that influence the climatic potential productivity in southern Henan Province are analyzed.The results show that with the delay of sowing date,the photosynthesis potential productivity of japonica rice presents a linear downward trend in south-ern Henan,and can decline by 405.3 kg/hm2 with a 10-day delay of sowing date,but the photo-thermal potential productivity and climatic potential productivity share the trend of rising-up first and then decli-ning.From 1981 to 2020,the potential productivities of photosynthesis,photo-thermal,and climate potential productivity all show a fluctuating decreasing trend with time in five different sowing periods,and their average regression rates are 828.8 kg/(hm2·decade),469.8 kg/(hm2·decade),and 491.7 kg/(hm2·decade),respectively.Precipitation and mean temperature are the major climatic fac-tors affecting the climatic potential productivity during the sowing period of japonica rice,and sunshine percentage is the main climatic factor for the climatic potential productivity durying the same sowing peri-od of japonica rice.

Abstract:From March 19 to 25,2023,a mixed heavy pollution weather process with the strongest intensity and widest influence in the past three years occurred in Yangquan City,Shanxi Province.Through analyzing the air quality data,meteorological monitoring data,microwave radiometer data,and backward trajectory during this period,the backward trajectories are clustered by means of the binary K-means algorithm.The results show that:(1)This heavy pollution process is divided into three stages:from the haze stage to the sand-dust stage,and then to the sand-dust to haze stage.The first stage was the haze weather stage,affected by static-stable weather with low surface wind speed.The second stage was the stage of sand-dust weather,affected by the Mongolian cyclone that moved eastward and south-ward,causing the PM10 concentration to increase explosively.The third stage was the sand-dust to haze stage,which was affected by reflux weather.During this stage,the surface wind speed was reduced,the PM10 in the atmosphere gradually settled down as the result of gravity,making the PM2.5 gradually accu-mulate again.(2)The transport paths of pollutants during this heavy pollution process are divided into three categories.Spatially,the pollutant transport path in haze weather was first downward and then up-ward in the vertical direction.In terms of the pollutant transport speed,the moving speed of sand and dust was higher than that in the haze weather.(3)When the mixed pollution weather appeared in spring,the surface situation of haze weather was mostly saddle-shaped field,warm low-pressure type and high-pressure rear type,and the upper situation was mostly flat zonal circulation.The surface situation of sand-dust weather was mostly the high-pressure front(bottom)type,and the upper situation was mostly the meridional circulation with large gradient.(4)The concentrations of gaseous pollutants(SO2 and NO2)were greatly affected by the near-surface wind field,presenting different characteristics in the peri-od of dust and haze weather.(5)Below the height of 3.0 km,the temperature profile and water vapor density profile data in the boundary layer can make up for the lack of local conventional radiosonde data.Moreover,according to the temperature profile in the boundary layer,the ground inversion can be ob-served in advance.

Abstract:Based on the statistical data of lightning disasters in Beijing from 2000 to 2020 and the existing classification statistics of lightning disasters,we conduct statistical analysis of direct economic loss caused by lightning strike and economic loss after equivalent conversion of casualties section by sec-tion to obtain the classification standard of lightning disasters in Beijing.Following the new standard,the probabilities of all-level lightning disasters in Beijing are calculated.The results show that the"general"probability of a lightning disaster in Beijing is 59.20％,the"greater"probability is 28.00％,the"signifi-cant"probability is 9.36％,and the"extreme"probability is 3.44％.Compared with the existing classifi-cation standard,the new standard is of more significance in statistics.Analysis of the correlation between lightning disaster level and lightning current intensity suggests that there is a positive correlation between them.According to the weight analysis method,the intensity range of lightning current of each disaster level is given.The lightning current intensity of"general"disasters in Beijing is concentrated below 40 kA,the lightning current intensity of"larger"disasters is mainly concentrated between 40 kA and 60 kA,the lightning current intensity of"major"disasters is mainly concentrated between 60 kA and 100 kA,and the lightning current intensity of"extraordinary"disasters is concentrated between 100 kA and 200 kA.The lightning disaster levels are obtained by referring to the distribution of lightning current intensity in Bei-jing,which is closer to the classification standard of lightning disaster levels in Beijing.

Abstract:Based on multi-source observation data,which include conventional meteorological obser-vations,ERA5 reanalysis data,wind profile radar data,Doppler weather radar data and dual-polarization weather radar data,combined with hydrometeor phase identification techniques,this study analyzes the synoptic background,atmospheric thermodynamic and energy conditions,as well as the mesoscale dy-namic characteristics of a dry thunderstorm gale event that occurred behind a cold front in Tianjin on May 31,2022.The analysis results show that this dry thunderstorm gale event was an elevated thunderstorm process in spring.Before the thunderstorm,the 850 hPa shear line and the surface cold front had crossed Tianjin,and the low-level cold air had invaded.The unstable energy mainly came from the convective unstable stratification in the warm and humid air above the cold air.The fluctuation of the middle shallow trough was the primary trigger cause for the convection.The inverted-V temperature-humidity profile,the ambient temperature lapse rate closed to dry adiabatic lapse rate and the large downdraft convective avail-able potential energy all had strong instruction significance for this dry thunderstorm gale event.The dry air caught by the inflow from the back side into the storm accelerated the melting of ice particles,which lowered the temperature in the storm,and the airflow sank and reached the surface at an accelerated speed,causing the occurrence of the dry thunderstorm gale event.

Abstract:Scab and stripe rust are common diseases in the main wheat planting area in Henan Prov-ince.The dynamic monitoring of scab and stripe rust is of great significance for disease prevention and control as well as high and stable yields of wheat.To investigate the application of China's high-resolu-tion satellites in the regional monitoring of scab and stripe rust,this study developed multiple vegetation indices based on GF-6 satellite data.Moreover,combined with meteorological factors including air tem-perature and relative humidity in March and April,remote sensing monitoring models for scab and stripe rust in winter wheat were established by Multiple Linear Regression(MLR)and Back Propagation Neural Network(BPNN),respectively.Additionally,monitoring research was conducted on the disease inci-dence rate of spikes(scab)and infected leaf rate(stripe rust)in winter wheat planting areas of southern Henan Province.The results showed that the incorporation of meteorological factors significantly enhanced monitoring accuracy for the disease incidence rate of spikes in scab.The coefficient of determination(R2)of the MLR and BPNN models increased from 0.42 and 0.39 to 0.67 and 0.82,respectively,while their root mean square errors(RMSEs)decreased from 3.99 and 4.16 to 3.03 and 2.21,respec-tively.The BPNN model exhibited superior performance compared to the MLR model.For the infected leaf rate in stripe rust,the integration of meteorological factors improved the monitoring accuracy of the MLR model,with R2 rising from 0.19 to 0.26 and RMSE decreasing from 18.56 to 17.79.However,no significant improvement was observed in the BPNN model.

Abstract:Based on the conventional surface observation data,sounding data and Final(FNL)rean-alysis data in Jiangxi Province from 2011 to 2022,417 regional haze weather processes are statistically analyzed in this paper.The characteristics of regional haze,such as high-and low-level synoptic situa-tion,surface wind speed,high-and low-level relative humidity,inversion and mixed layer height are ob-tained,and also compared with those of regional fog events.The results show that:(1)The Jiangxi re-gional haze events tend to occur in the winter December and January,more in the north and less in the south of the province.(2)The surface wind speeds during the regional haze processes are generally in the range of 1-3 m·s-1,and can reach 6 m·s-1 in cold frontal zones.Most of the relative humidity values below 925 hPa in the lower troposphere are below 75％,and those at 500 hPa in the upper air are less than 40％.(3)The regional haze processes are often accompanied by single-layer inversion,with high frequency of inversion appearing near the surface.The mixed layer is below the height of 800 m.(4)The surface situation is mainly composed of high pressure,low pressure and uniform pressure,of which the high-pressure bottom type is the most,followed by the cold frontal zone type.The upper air is mostly controlled by westerly or northwesterly winds.(5)Compared to regional fog,the surface wind speed con-ditions are similar in both fog and haze events,but the inversion intensity and low-level water vapor dur-ing regional haze processes are weaker.In addition,on the basis of these analyses,a synoptic conceptual model of regional haze weather of high pressure bottom type is established.

Abstract:Based on the precipitation data from 34 meteorological stations in Chongqing,NCEP/NCAR reanalysis data,and CFSv2 model products,this article investigates the spatio-temporal distribu-tion characteristics of precipitation during the flood season(May-September)and the atmospheric circu-lation patterns of typical anomalous precipitation years.Significant differences are identified in drought/flood-sensitive regions and key atmospheric circulation features influencing precipitation in these months.Consequently,monthly-specific statistical downscaling prediction models are established for precipitation prediction at the 34 stations in Chongqing during the flood season from May to September.These models incorporate the key precursor and concurrent predictors selected by the year-to-year increment approach.the average Ps score of the downscaling models from May to September in 2012-2020 can reach 74.2,representing a 13.1-point improvement over direct CFSv2 model outputs.This highlights the advantages of the downscaling models in predicting precipitation during the flood season in Chongqing.Furthermore,the downscaling models can basically predict the relatively high-value and low-value precipitation zones in both anomalously dry and wet years,thereby demonstrating a robust skill in reproducing regional distribu-tion characteristics of precipitation.