Abstract:Using the mesoscale WRF model driven by global forecast field from China's self-devel-oped global numerical weather prediction system CMA-GFS,global atmospheric/land surface reanalysis system CMA-RA,and the U.S.global numerical weather prediction system NCEP-GFS,we obtain three mesoscale forecast fields,namely,CMA-GFS-WRF,CMA-RA-WRF,and NCEP-GFS-WRF.The effects of the three initial fields and their mesoscale forecast fields on the typhoon central pressure,near-central maximum wind speed,spiral cloud bands,precipitation and cold air intrusion process are analyzed.The results show that the central pressure intensity of CMA-GFS is in the best agreement with observations,and its mesoscale forecast field CMA-GFS-WRF also reproduces the typhoon sub-center structure better.The central pressure intensity of CMA-RA is obviously weaker than that of the observations.Although the central pressure intensity of its mesoscale forecast field CMA-RA-WRF prediction has improved,it is still the weakest.NCEP-GFS overall has a better forecasting ability for maximum wind speed than CMA-GFS,while CMA-RA has the weakest forecasting ability for maximum wind speed,and the WRF model fore-casts by the three initial fields did not show any significant improvement in the maximum wind speed fore-casts.CMA-GFS-WRF simulates a wider range of spiral cloud bands,with westerly locations,a large range of strong centers,and a denser structure of cumulonimbus mixed clouds,followed by NCEP-GFS-WRF,and CMA-RA-WRF simulates the smallest range of strong echoes.In terms of the temporal evolu-tion of the regional mean precipitation,the mesoscale forecast results of the three initial fields have a 2-3 h lag in the precipitation peak.The comprehensive analysis of the whole precipitation process shows that the precipitation time series simulated by NCEP-GFS-WRF is closer to observation,followed by CMA-RA-WRF.The rainstorm range of CMA-GFS-WRF is obviously larger,which may be related to the simulated longer maintenance of the warm-core structure of the typhoon and the simulated slower intrusion of the cold air.

Abstract:Using meteorological observation data at Beiji Village meteorological observatory from 1961 to 2021,this study analyzed the climate characteristics in Beiji Village,divided the climate sea-sons,calculated the climate comfort index,analyzed the variations of climate comfort,discussed the im-pact of climate change on tourism in Beiji Village,and provided a theoretical basis for understanding sci-entific issues such as climate change in high latitude areas and its impact on ecotourism.The results showed that the average annual temperature in Beiji Village was-3.3℃,with the highest average tem-perature of 19.4℃and the lowest average temperature of-28.3℃,and the temperature difference was 47.7℃.The annual average precipitation in Beiji Village was 457.4 mm,with precipitation days of 115.9 days,precipitation intensity of 3.3 mm/d,and average maximum daily precipitation of 41.9 mm.Beiji Village was classified as a perennial summer-less area,while spring start date was May 16th and the spring length was 58 days;the start date of autumn was July 13th,and the length of autumn was 58 days;the winter started on September 9th and lasted for 249 days.However,since the 1990s,33%of the years in Beiji Village had a summer,while the longest duration was 18 days.Beiji Village was shifting from"long winter without a summer"to"long winter with a summer".The annual average climate comfort level of Beiji Village was the cool level(level 7).Winter climate comfort level was the cold level(level 8).Non-winter climate comfort level was the comfortable level(level 5).Under the background of cli-mate warming,the comfort level of Beiji Village changed.Before 1982,the winter climate comfort level was the severe cold level(level 9),and after 1983,it was mainly the cold level(level 8).Before 1986,the non-winter climate comfort level was the slightly cool level(level 6),and after 1986,the comfort level was mainly the comfortable level(level 5).

Abstract:Based on ERA5 reanalysis data and the hourly precipitation data of 107 ground meteoro-logical observation stations in Xiaogan City from 2016 to 2022,the weather classification of extreme flash rain(EFR)in Xiaogan City is carried out,and the environmental circulation parameters and their anom-aly characteristics are analyzed.The results show that:(1)The EFR events in Xiaogan City occurred from May to August,most in June,followed by July and August.The average number of stations and rainfall intensity of EFR events increased with time.EFR in Xiaogan City is prone to occur at 06-12 and 23-01 the next day.The windward slope of Dabie Mountain and Dahong Mountain,the transition zone between the two mountains,and the dense area of lakes and rivers are densely populated with EFR sta-tions.(2)There are four weather types of EFR events in Xiaogan City EFR event:vortex shear type,frontal cyclone type,upper trough front type and weak forcing type.The favorable weather situation of EFR in Xiaogan City is that the upper air is a divergence area,the southwest jet around the strong sub-tropical high is in the convergence of wind speed in Xiaogan City,the east or north cold airflow forms a stable shear line with the southwest warm and humid jet,and the mesoscale low vortex moves to the vicin-ity of Xiaogan City or the cold shear is located in Suizhou City.(3)Xiaogan City EFR is closely related to water vapor content,water vapor convergence and low-level convergence,high-level divergence,and low-level vertical velocity anomalies.Abnormally abundant water vapor content and water vapor saturation in the boundary layer are necessary conditions for the generation of large-scale EFR.(4)The average PW of EFR events in Xiaogan City is 68 mm,and PW<54 mm is not conducive to the occurrence of EFR events.The average specific humidity at 850 hPa is 16 g·kg-1.The average LCL is 960 hPa,the aver-age CAPE is 2300 J·kg-1,the average K index,LI index and △T85 are 38,-4 and 23℃,and the av-erage vertical wind shear of 0-6 km is 9 m·s-1,which are favorable environmental parameters of EFR in Xiaogan City.

Abstract:In order to adapt to climate change,full rational use of agricultural climate resources,and make the development plan of Camellia oleifera planting in Hunan Province scientifically,based on high-resolution historical meteorological data from 1961 to 2020 and BCC-CSM2-MR model forecast data from 2021 to 2050,using the baseline period of 1961-1990,the high-yield climatic regionalization index of Camellia oleifera was used to analyze the spatial-temporal features,geocentric changes and displace-ments of Camellia oleifera climatic suitability in Hunan Province.The results showed that climatic suita-bility for high-yield Camellia oleifera showed decreasing trend.The most-suitable area decreased from northwest to southeast,while the suitable area expanded from north to south,the sub-suitable area devel-oped around the Dongting Lake region,and the unsuitable area remained relatively stable.Compared with the baseline period,the ratio of the most-suitable area decreased by 18.0%during 1991-2020,while the ratio of suitable,sub-suitable,and unsuitable areas increased by 9.9%,7.3%,and 0.8%,respec-tively.The most-suitable and suitable areas migrated to higher altitudes,while the sub-suitable and un-suitable areas migrated to lower altitudes.The ratio of the most-suitable area decreased by 20.7%during 2021-2050,while the ratio of suitable,sub-suitable,and unsuitable areas increased by 16.1%,3.1%,and 1.5%,respectively.The suitable areas migrated to higher altitudes,while the sub-suitable and un-suitable areas migrated to lower altitudes.Compared with the period of 1991-2020,the ratio of the most-suitable area and sub-suitable area decreased by 2.7%and 4.2%during 2021-2050,while the ratio of suitable and unsuitable areas increased by 6.2%and 0.7%,respectively.The most-suitable areas slightly migrated to lower altitudes,while the suitable and sub-suitable areas migrated to higher altitudes,and the unsuitable areas position remains basically unchanged.Under the background of future climate warming,the number of low temperature days during the flowering period and precipitation days during the young fruit period showed a decreased trend.The number of high temperature days during the peak period of oil conversion and accumulation increased,and the overall climatic suitability decreased.Air temperature was the main meteorological factor that would have a negative impact on high-yield of Camellia oleifera in the future.

Abstract:In order to study the simulation effectiveness of various models on peanut growth and de-velopment,and identify the best simulation method,the five models of crop development stages,piece-wise linear model(LM),Wang-Engel model(WE),effective accumulated temperature model(EM),active accumulated temperature model(AM),and clock model(CM)were chosen,based on 26-year peanut development stage data on four agrometeorological observation stations in Zhengyang,Zhumadian,Fangcheng,and Yellow River Floodplain.The simulation performance of four main stages of peanut de-velopment,emergence,blooming,needling,and maturity fitted by the five models were compared with 18-year observation data which were randomly selected,using the metrics of root mean square error(RMSE),normalized root mean square error(NRMSE),and mean absolute error(MAE),and the performance was evaluated using the data from the remaining eight years.The results were as follows.(1)The accumulated temperature indexes of different models varied significantly,and the accumulated temperature of the whole period showed the AM>WE>EM>LM pattern.(2)The WE model fitted the de-velopmental stages relatively well.The mean values of RMSE,NRMSE,and MAE were 5.25 d,2.41%,and 3.87 d,respectively,at four stages of development,all lower than other four models.The fitting of the same model on different development stage was better for emergence stage than for blosso-ming stage,and better for blossoming stage than for needling stage and maturity stage.(3)The results of model validation were similar to the fitting results,also showing that the WE model had the lowest average RMSE(4.91 d),NRMSE(2.32%),and MAE(3.97 d).The verification of various development sta-ges revealed that the effect was better in the emergence stage,followed by blossoming stages,while rela-tively worse in the needling and maturity stages.In conclusion,the WE model is suitable for simulating the growth and development process of peanuts in Henan Province.

Abstract:In order to study the climate-adapted sowing date for winter wheat and help to achieve a high and stable yield,based on the daily temperature data of 21 national weather stations in North of the Huaihe River(Huaibei region)of Anhui Province from 1981 to 2020,four critical dates of vigorous seedling,start date of strong seedling,end date of strong seedling and weak seedling were determined by calculating the active cumulative temperatures before the final day of stably passing 0℃.The spatiotem-poral evolution characteristics of the mean value,climate tendency and 80%guarantee rate of the four critical dates were analyzed.The results showed that the mean values of the final day of stably passing 0℃were earlier in the north and later in the south,with a difference of 16 days between the north and south.The mean values in the east-west direction were basically consistent,and the climatic tendency rate ranged from 0.04 d/10a to 4.27 d/10a,with the largest in Sixian County and the smallest in Hua-iyuan County.The mean values of the critical dates of vigorous seedling,start date of strong seedling,end date of strong seedling and weak seedling from north to south were October 7-18,October 10-21,October 14-25,and October 19-30,respectively.The climate tendency rate difference of the above four values are relatively minor,ranged from 0.50 d/10a to 2.50 d/10a.The stations with delayed trend passing the p=0.01 significance level test were mainly located in Linquan,Yingshang and Fengtai in the southwestern part of Huaibei region,Lingbi and Sixian in the eastern part,and Bozhou and Guoyang in the northwest part.The delayed trend in nearly half of other regions was not significant.Based on the 80%guarantee of four types of critical dates,the climate-adapted sowing date of winter wheat was ana-lyzed.The results showed that the optimum sowing date was early in the north and late in the south.The optimum sowing date to ensure strong seedlings in the north,middle and south of Huaibei(along the Huaihe River)was October 10-13,October 13-16,and October 15-19,respectively.Sowing before October 7,October 10 and October 13 in the three sub-regions had a high probability of vigorous seed-lings.Sowing after October 18,October 21 and October 24 in the three sub-regions had a high probability of late weak seedlings.

Abstract:With the advancement of air pollution control efforts in China,particulate matter pollution has gradually decreased,while ozone pollution has become increasingly severe.The formation mechanism of ozone is complex,and the impact of lightning activity on ozone formation remains unclear.To investi-gate the influence of lightning activity on near-surface ozone concentration,the relationship between light-ning and ozone concentration is analyzed based on lightning monitoring data and ozone concentration data from 2013 to 2022.By typical processes of high ozone concentration and high-frequency lightning,the occurrence and development mechanisms of ozone pollution episodes are explored.The results show that between 2013 and 2022,a total of 140698 lightning events occurred in Huai'an urban area,with an an-nual average of 14069.8 events/year.The lightning density at the selected ozone monitoring stations ranged from 2.8 to 4.2 events/(km2·a).The hourly ozone concentration in Huai'an urban area mostly ranged between 33 and 138 μg/m3.The median ozone concentration on lightning days was higher than that on non-lightning days,with the Beijing South Road station in the old urban area showing the largest average ozone concentration change,reaching 21.7%.Lightning consistently caused an increase in ozone concentration within two hours of its occurrence,showing a strengthening trend.The average increase in ozone concentration ranged from 1 to 142 μg/m3,with an average growth rate exceeding 25%.The num-ber of lightning strikes was positively correlated with ozone concentration.Cloud-to-ground lightning showed a strong correlation with ozone concentration both during and 1-2 hours after the lightning event.The relatively high nighttime ozone values may result from the transport of ozone produced by strong tropo-sphere thunderstorms through downdrafts,creating a superimposed effect on the high near-surface ozone concentrations.In the Yangtze River Delta region,when the 8-hour average ozone concentration is around 25%below the exceeding threshold,if lightning occurs,the ozone exceeding warning can be considered two hours in advance with reference to the analysis results from Huai'an urban area.

Abstract:In order to quantitatively evaluate the sterile-type of rice cold damage and carry out risk assessment,using data from 50 meteorological stations,10 rice observation stations,and corresponding disaster statistics in Jilin province from 1981 to 2019,the sterile-type cold damage intensity index of rice was constructed by synthesizing the cold damage intensity and effective days,and matching the sensitive growth period with the low temperature weather process,based on the GB/T 34967-2017"Grade of Rice Cold Damage in Northern China",and the risk assessment of sterile-type cold damage of rice was carried out by using the natural disaster risk theory.The results showed that the sterile-type cold damage intensity index of rice can identify the situation of sterile-type cold damage of rice at flowering and booting stages well,and had a good applicability in Jilin province.The stations with higher intensity of the ster-ile-type cold damage of rice during the flowering and booting stages were mainly located in the eastern part of Jilin province,and the intensity of the sterile-type cold damage of rice during the flowering stage was stronger than that during the booting stage.From 1981 to 2019,the occurrence intensity and station ratio of sterile-type cold damage of rice in Jilin province showed a decreasing trend.The range of cold damage was mainly local,followed by regional,and large-scale cold damage was less.The hazard and exposure of the sterile-type cold damage of rice were mainly high in the east,and the vulnerability was basically distributed in a pattern of high in the west and low in the east.The comprehensive high-risk area was mainly located in the east.

Abstract:Climate livability has become one of the important factors in high-quality urban settlement planning and adaptation to climate change.The climate background and problems of Lixian residential group of noise-resettled housing in the Airport Economic zone of Beijing Daxing International Airport were analyzed based on long-term climate observation data.Then the CFD software was driven by the observa-tion data of the weather station around the residential group,to simulate the typical wind and thermal en-vironment in summer and winter of the architectural design schemes,and the simulation results were eval-uated.The results showed that the wind speed in the downwind direction of the residential group was lower than that in the upwind direction.Wind speed in the leeward side of buildings and in enclosed buildings was generally less than 0.5 m·s-1.In summer,the wind speed in the three-dimensional space below 10 m both open space and inside ventilation corridors of residential group was about 40%higher than that in the regions with concentration of buildings,and temperature in the large open spaces,streets was gen-erally lower than that in the leeward side of buildings,between buildings and in enclosed buildings.In winter,the temperature in the regions with concentration of buildings was higher than that of the open space and streets,and the surface temperature of the buildings was about 5.0℃higher than the air tem-perature.Moreover,the effect of wind on the air temperature could extend to the downwind direction.Considering the influence of ventilation and cooling in summer,wind protection and warmth retention in winter,and the impact of buildings on surrounding outdoor air temperature,some microclimate livable strategies such as the maintenance of open space,public space selection and green forms around build-ings were proposed,and the microclimate livability guide maps were drawn using urban environmental cli-mate technology.

Abstract:High-temperature stress is a major factor leading to cotton yield reduction in Hunan,and the design and promotion of a high-temperature weather index insurance are crucial for diversifying and transferring agricultural meteorological disaster risks and ensuring farmers'incomes.Based on field trial data of the"Xiangmian Early No.1"cotton variety from three counties(districts)between 2020 and 2022,the impact of high-temperature stress during the flowering and boll stages on cotton yield and its components is investigated,and a high-temperature weather index insurance model is constructed.The main research results are as follows:(1)Average temperature and maximum temperature during the flow-ering and bolling stages significantly affect the development period,shortening the flowering to boll-open-ing stage by an average of 8.5 days.High temperature also impacts yield components,with actual seed cotton yield per plant showing a downward trend.Specifically,in Huarong County,the 2022 yield de-creased by 22.9%and 19.4%compared to 2020 and 2021,respectively;in Li County,the 2022 yield decreased by 12.6%and 14.1%.compared to 2020 and 2021,respectively.(2)Average temperature(Tave),maximum temperature(Tmax),the number of days with average temperature≥30℃(DTave),and the number of days with maximum temperature≥35℃(DTmax)are all negatively correlated with the number of bolls and yield.The correlation coefficients between boll number and Tave,Tmax,and DTmax were-0.784,-0.771,and-0.701,respectively,all reaching a significant level(p≤0.05),which meant boll number decreased significantly with increase in the number of days with Tave,Tmax,Tmax≥35℃.(3)An Allometric high-temperature disaster loss compensation model based on the number of high-temperature days(DTmax)during the cotton flowering and boll stages was constructed.The pure pre-mium rates under different high-temperature levels ranged from 0.16%to 0.68%,with compensation standards ranging from 45.0 to 900.0 yuan/hm2.

Abstract:In order to understand the disaster-inducing process of low temperature and weak light,improve the ability of facility crops to cope with this disaster,and ensure the safety of national facility ag-riculture,a low-temperature and weak light simulation experiment lasting 10 days was carried out on solar greenhouse tomatoes during the seedling stage in Tianjin.A total of five temperature levels and two light levels were set to form five low temperature and weak light treatments with different intensities.They were T1(25℃/18℃,200 μmol·m-2·s-1),T2(22℃/15℃,200 μmol·m-2·s-1),T3(18℃/11℃,200 μmol·m-2·s-1),T4(15℃/8℃,200 μmol·m-2·s-1),and T5(12℃/5℃,200 μmol·m-2·s-1),and a normal temperature-light was set up to be the control group CK(25℃/18℃,800 μmol·m-2·s-1).The disaster-inducing process and its possible influencing mechanism of tomato seedlings were analyzed under different intensities of low temperature and weak light conditions.The results showed that the inhibition effect on tomato growth indicators increased as the intensity and du-ration of low temperature and weak light increased,and finally affected the yield and fruit quality of toma-to.However,different growth indicators of tomato had different sensitivities to low temperature and weak light.The sequence of different growth indicators responding to low temperature and weak light was:leaf photosynthesis,leaf area,leaf dry mass,stem dry mass,plant height,root dry mass.The sensitivity of different organs of tomato to low temperature and weak light was ranged as:leaf,stem,and root.Struc-tural equation model was applied to investigate the influence mechanism of low temperature and weak light on tomato growth and development,which was as follows.The temperature directly affected the growth of leaf area,while light directly affected the accumulation of leaf biomass,and then indirectly affected the expansion of leaf area,resulting in the reduction of biomass accumulation of stem and root,as well as growth rate,and thus finally reduced the yield and fruit quality.

Abstract:Based on the surface and upper-air observations from July to August of 2003-2022 as well as the ERA5 reanalysis data,the environmental characteristics of midsummer hail cases in Shanghai are analyzed.The results demonstrate that,in midsummer season,the atmosphere always shows moist and unstable stratification,and the occurrence of deep moist convections(DMCs)mainly depend on the triggering of meso-scale convergence lines.Although the three typical hail situations(subtropical high edge type,subtropical high control type and upper-air trough type)are different from each other,their common features are the large-value combination of CAPE and 0-6 km vertical wind shear(SHR6),the cold advection or cold tongue at 500 hPa,and the warm center or warm-wet advection at lower levels.In midsummer season,when hail occurs in Shanghai,the median WBZ is 4343 m,which is significantly higher than the median WBZ height threshold in other regions of China.The median temperature differ-ence between 850 hPa and 500 hPa is 26℃,and the 0-6 km vertical wind shear is weak.The Signifi-cant Hail Index(SHIP)has certain indicative value for hail forecasting,but the threshold applicable to the Shanghai area is significantly lower than the commonly used threshold,approximately 0.2.Compared with other convective weather conditions(thunderstorms and short-time severe precipitation)in the same period,the sounding of hail weather shows the characteristics of drier and colder middle layer,and larger potential instability.

Abstract:Based on hailfall information from 2006 to 2023 in the Five-hundred-meter Aperture Spherical Radio Telescope region(hereinafter referred to as the FAST region),combined with meteoro-logical observation data from soundings,radar,and satellite,twenty environmental physical parameters(characterizing water vapor conditions,thermodynamic and dynamic features,atmospheric instability,and characteristic height layers),as well as radar feature parameters and satellite TBB were used to ana-lyze the patterns of hail weather processes,key environmental physical parameters and their monitoring and warning thresholds in the FAST region.The results show that:(1)Hail in the FAST region primarily occurs in spring,mostly during the evening to nighttime hours.The duration of hail is 1-3 minutes,and the diameter of hail is less than 10 mm.The main path of hail clouds affecting the FAST region is from the northwest,with their primary source located in the southeast of Anshun City.(2)Among the selected similar physical parameters,T850-Td850,ΔT850-500,SWEAT,and SHR6 exhibit the smallest dispersion and can serve as key discriminative physical parameters for hail weather in the FAST region,providing important reference for potential forecasting operations.Specifically,the maximum threshold for T850-Td850 should not exceed 1.25℃(75th percentile),the minimum threshold for ΔT850-500,SWEAT,and SHR6 should not be lower than 22.63℃(25th percentile),170.03(25th percentile),and 22.88 m/s(25th percentile),respectively.Concurrently,WBZ and H-20℃need to fall within their 25th and 75th percentile ranges,specifically 3.55-3.86 km and 6.69-7.48 km.(3)For hail warning operations in the FAST region,radar physical parameters Zmax,VILmax,ET,H45 dBZ,H55 dBZ,and the ice-water ratio take the 25th percentile as their minimum thresholds,which are 60 dBZ,31.25 kg/m2,13.25 km,8.75 km,7.00 km,and 2.12,respectively.For satellite TBB,the 75th percentile(-44.9℃)is taken as the maximum threshold.

Abstract:Based on temporal and spatial climate series and DEM data set,using the physical model of vegetation biomass expressed by climate factors,this paper evaluated the temporal and spatial dynamics of vegetation climate production potential in Xiaoxing'an Mountains in the climate-sensitive area of boreal forest,and analyzed the variation patterns of climate production potential,and its coordination degree with terrain resources and regional differences.The results show that from 1971 to 2020,the climate pro-duction potential of the north and south regions of Xiaoxing'an Mountains has an increasing trend(except NPPR in the southern region),and the increase trend of the north region is more significant than that of the south region.The whole region climate production potential tendency rates are as follows,NPPT:21.267-30.730 kg·hm-2·a-1,NPPR:-2.569-10.783 kg·hm-2·a-1,NPPV:9.501-21.783 kg·hm-2·a-1,NPPB:9.502-24.231 kg·hm-2·a-1.From 1971 to 2020,NPPR was the highest in the north region except for 2017,while NPPR was the highest in nearly 80%years in the south region.Both NPPT and NPPV mutations occurred in the early 1990s in the north region,while NPPV lagged behind NPPT in the south region.NPPT,NPPR and NPPV in the two regions have a scale oscillation period of about 25-30 a,and the maximum peak value corresponds to 28 a.NPPT and NPPV were negatively correlated with elevation(P<0.05),NPPR was positively correlated with slope(P<0.05),and the correlation between climate production potential and slope direction was not significant.

Abstract:Using hourly observational data from weather stations and ERA5 reanalysis dataset in 2019-2023,employing climate comfort index and aggressive meteorological index(AMI)for health,the distribution characteristics of climatic health preservation resource in Zhejiang province are analyzed.Re-sults show that annual mean number of hours of climate with no thermal stress in Zhejiang province is about 4176.1 h,while number of hours of climate with significant heat stress and significant cold stress in Zhejiang province are 856.1 h and 35.3 h,respectively.In terms of spatial distribution,the occur-rence frequency of climate with no thermal stress is higher in the south and is lower in the north,higher in the coastal area and lower in the inland area,higher in the mountainous area and lower in the plain area.Number of hours of climate with no thermal stress in October and May are 584.1 h and 536.6 h,respec-tively,which are considered to be the most physically comfortable months for human body.Annual mean cumulative number of days of moderately strong aggressive weather for health(AMI>60)in Zhejiang province is 86.0 d,whereas number of days of highly strong aggressive weather for health(AMI>80)is 32.6 d.Under the effect of ocean climate,the AMI is relatively small and number of days of aggressive weather for health is relatively fewer in coastal area in the east Zhejiang province.Comprehensive analysis of both climate comfort index(seeking benefits)and aggressive meteorological index for health(avoiding harms)shows that there are abundant climatic health preservation resource in Zhejiang province,and the coastal area in the south Zhejiang province is the most suitable area to conduct climatic health preserva-tion activities.

Abstract:Based on the daily meteorological observation data in Hubei Province and the outputs of 14 global climate models from 2021 to 2100 under Phase 6 of the Coupled Model Intercomparison Project(CMIP6)and two shared socioeconomic pathways emission scenarios(medium:SSP2-4.5,high:SSP5-8.5),the temporal and spatial variations of climate comfort in 17 different regions of Hubei Province in future periods from 2021 to 2100 are projected.The results show that:(1)Under climatic conditions of baseline period from 1995 to 2014,the annual average comfort days in Hubei Province is about 180.7 d with the highest number in Spring and Autumn and the lowest in Winter and Summer.The average annual number of hot uncomfortable days is 105.0 d in Hubei Province.The average annual number of cold and uncomfortable days is 79.6 d.Overall,there are few extreme hot and cold days of Hubei Province,and the climate is generally comfortable.(2)The absolute deviation of the average days of each comfort level in the baseline period between CMIP6 model prediction and observation calculation is 0.2-5.3 d.This indicates that the downscaling data of CMIP6 model can satisfy the projection of the climatic comfort level in Hubei Province under the climate change scenarios.(3)Under future climate scenarios,the number of climatic comfort days in Hubei Province will decrease from 2021 to 2100,the number of thermal discomfort days will increase significantly,the number of cold discomfort days will decrease significantly,and the overall developing trend will change to thermal discomfort.By the end of the 21st century,under the SSP2-4.5 and SSP5-8.5 scenarios,the average annual comfort days in Hubei Province will decrease by 7.8 d and 14.8 d,the number of hot uncomfortable days will increase by 38.8 d and 61.4 d,and the number of cold uncomfortable days will decrease by 32.5 d and 49.6 d,respectively.Compared with the current climate conditions,and the number of summer comfort days will become less and less,and the number of comfort days in winter will increase.The most comfortable months will be February to April and October to December.

Abstract:Using the daily meteorological data of 97 stations in the Songhua River Basin during the winter of 1961-2021 and the NECP reanalysis data,we analyze the climatic characteristics and circula-tion background of northeast cold vortex and its impact on the climate of the Songhua River Basin in win-ter and each month by means of linear regression,moving average,correlation analysis and composite analysis.The results indicate that during the 61 years,the northeast cold vortex process accounts for 32.3%of the total number of days in winter.The longer the duration of the cold vortex process,the lower the frequency of its occurrence.The most active days of the northeast cold vortex are in January,and there is no significant change in the frequency of the northeast cold vortex in winter and each month,only a significant decrease in February.During the northeast cold vortex period,the average precipitation in the Songhua River Basin is higher than that in normal years and that without cold vortex process,and the average temperature is lower than in other time periods.More than 30%of regional cold waves,blizzards,and heavy snows occur during the northeast cold vortex period.Overall,there is a significant increase in the number of days of regional heavy snow and heavy snow during the winter and February cold vortex periods,while the trend of changes in the number and proportion of days of regional heavy snow and heavy snow in other months is not significant.In the active year of the northeast cold vortex in winter,the Eurasia has an east-west"-+-"anomalous distribution at 500 hPa.The Arctic Oscillation may affect the activity of the northeast cold vortex during the same period,and its negative phase is conducive to the generation of northeast cold vortex.

Abstract:This study analyzes the characteristics of a widespread rainstorm event in Shandong Prov-ince from July 5 to 6,2022,which was triggered by the interaction between the residual vortex of Ty-phoon Chaba(2203)and a westerly trough,utilizing the China Meteorological Administration Tropical Cyclone Best Track Dataset,conventional meteorological observations,Fengyun-4 satellite imagery,Doppler weather radar,wind profile radar data,and hourly ERA5 data.The results indicate that the main precipitation period exhibited strong integrated water vapor flux convergence at approximately 3×10-5 kg·m-2·s-1 and high specific humidity values of 14-16 g·kg-1 at 850 hPa,providing favorable moisture conditions for the heavy rainfall.Prior to the extratropical transition of the residual vortex,the western Pacific contributed 80%of the moisture,with 46.67%originating from the ocean southeast of Ja-pan;following the transition,the primary moisture source shifted to the southwest,dominated by the northern Indian Ocean,which illustrates the important role of water vapor transported by the strengthening and northward movement of the jet stream in the residual vortex maintenance and rainstorm generation.Atmospheric instability caused by low-level cold air intrusion was the primary factor contributing to the strong precipitation after the residual vortex transition.The level distribution of frontogenesis function and the wind direction transition showed by wind profile radar had a strong correlation with the invasion of low-level cold air and the significant increase of hourly rainfall intensity at observation stations.The wind profile radar data effectively compensated for the limitations of satellite water vapor imagery in detecting low-level cold air invasions.

Abstract:This study utilizes near-surface observational data from meteorological stations around wind farms in Henan Province from 2020 to 2024.Based on an assessment of wind field characteristics across the province,wind profile models are applied to vertically extrapolate winter wind speeds near two wind farms in southern Henan.The extrapolation results are then corrected using a residual learning method.The results are as follows.(1)The wind fields near wind farms exhibit distinct seasonal fea-tures,closely related to station elevation.Wind speeds are weakest in summer and strongest in winter.In high-altitude regions,wind speed distribution shows a wider range.Regarding wind direction,low-alti-tude areas are dominated by southerly winds in spring and summer and by northeasterly winds in autumn and winter.At altitudes above 600 m,the seasonal prevailing wind directions become more complex,typically characterized by southeasterly and northwesterly winds.(2)Wind speeds at heights of around 100 meters were extrapolated using both the power law and the logarithmic law wind profile models.The results from the two models are similar,and both outperform the 100-meter wind speeds derived from nearby ERA5 grid data.(3)The residual learning method was employed to correct the vertically extrapo-lated wind speeds,leading to a significant improvement in model accuracy.This technical approach con-tributes to addressing the lack of vertical observational data for low-altitude wind fields in the vicinity of wind farms.

Abstract:Winter wheat yield estimation is crucial for ensuring food security.To enhance the effi-ciency and accuracy of yield prediction,this study integrates multi-source data from 2000 to 2021,inclu-ding county-level winter wheat yield,remote sensing data,meteorological data,and geographical coordi-nates in Henan Province,to analyze the correlation between characteristic variables and yield.By pro-gressively inputting feature variables in a time-series manner,the dynamic yield estimation performance of five models——Linear Regression,Random Forest,Gradient Boosting,LightGBM,and K-Nearest Neighbors——is compared and validated using 2021 data.The results indicate that winter wheat yield ex-hibits a significant positive correlation with NDVI and is strongly associated with geographical location and meteorological factors such as light,temperature,and water.All five models effectively estimated yield,with the LightGBM model(27 feature variables)performing the best(prediction period:May,R2=0.91,RMSE=435 kg·hm-2,NRMSE=7.0%,RE=6.5%).Based on this model,the prediction accuracy for the 2021 yield is significantly high(R2=0.97,RMSE=249 kg·hm-2,NRMSE=5.1%,RE=2.7%),and the spatial heterogeneity of relative errors is related to topographical factors and mixed pixels in remote sensing data.