Table of Content

28 June 2025, Volume 41 Issue 3 Previous Issue   

ARTICLES

Select

Development and variation characteristics of an evaluation system for winter comfortable climate in China ZHAO Shanshan, WANG Rong, LI Ying, YE Dianxiu 2025, 41 (3):  1-8.  doi: 10.3969/j.issn.1673-503X.2025.03.001 Abstract ( 44 )   PDF (2233KB) ( 18 )   Save Based on daily observation data from 2328 national meteorological stations in China during the winter (December of the previous year to February of the current year) from 1961 to 2020,an evaluation system for winter comfortable climate was developed.According to the connotation and characteristics of winter comfortable climate,13 indicators were selected from 7 aspects,such as temperature,precipitation,wind speed,and human comfortability,to quantitatively assess the winter comfortable climate and to analyze the spatial distribution and the characteristics of long-term change of winter comfortable climate in China.The results showed that winter comfortable climate in China are mainly distributed in southern Sichuan,Yunnan,Guangxi,Guangdong,Hainan,and Fujian,with favorable conditions observed in southern Yunnan,southern Guangxi,southern Guangdong,southern Fujian,and Hainan.From 1961 to 2020,the extent and frequency of winter comfortable climates have shown a significant increasing trend,especially after the 1990s,with February exhibiting the greatest expansion.Compared with 1961-1990,the period 1991-2020 show a northward expansion of winter comfortable climate and an overall improvement in climate conditions,with the obvious notable enhancements in February.By constructing an evaluation system for winter resort climate in China,we quantitatively discovered the spatial distributions of different levels of winter resort climate in winter and its various months.This provides a scientific reference for destination selection and the development and utilization of winter resort climate resources in various regions over China. References | Related Articles | Metrics

Select

Seasonal differences and attribution of climate warming in Shanxi Province WANG Wenchun, WANG Xiaoqiong 2025, 41 (3):  9-17.  doi: 10.3969/j.issn.1673-503X.2025.03.002 Abstract ( 55 )   PDF (8279KB) ( 28 )   Save Based on monthly temperature data from national meteorological observation stations,ERA5 reanalysis data,and aerosol optical depth data derived from satellite,this study analyzes the seasonal warming differences in Shanxi Province over the period 1961-2024 and identifies the possible causes of seasonal change in the maximum warming from winter to spring.The results indicate that:the rate of warming was highest in winter and significantly exceeded that of other seasons prior to the 1990s.Winter warming has slowed,while the rate of warming in spring has surpassed that of winter,making spring the season with the most rapid temperature increase since the mid-1990s.The pronounced rise in minimum temperature during the early period (1961-1990) was the primary driver of rapid winter warming,whereas in the recent period (1995-2024),both minimum and maximum temperatures contributed significantly to the accelerated warming in spring.The dominant factors affecting the warming change in winter and spring are different:an accelerating spring warming was driven by the persistent decline in soil moisture and its positive feedback,and the weakened winter warming was induced by the strengthened intensity of the winter Siberian High. References | Related Articles | Metrics

Select

A study on the temperature forecast correction method of the CMA-MESO model based on machine learning ZHANG Hui, CHEN Junming, WANG Yaqiang, MA Fenglian, ZHOU Yu, LU Yukun, LIU Tong, ZHANG Liangyu 2025, 41 (3):  18-28.  doi: 10.3969/j.issn.1673-503X.2025.03.003 Abstract ( 47 )   PDF (6207KB) ( 28 )   Save To improve the accuracy of temperature forecasts in Xiong'an New Area and the upstream Baoding region,this study utilizes forecast products from the CMA-MESO mesoscale weather model and surface observation data.Three machine learning methods-Linear Regression,Long Short-Term Memory Fully Convolutional Network(LSTM-FCN),and Light Gradient Boosting Machine(LightGBM) are applied.Four forecast correction schemes are designed,focusing on station classification and feature selection.The results show that models using regionally divided stations outperform those using all stations collectively,and LightGBM delivers the best performance among all schemes.Specifically,when composite feature factors are constructed by combining observed data from 48 hours prior to the forecast start time and forecast or observed variables from 4·k hours before the forecast time(within the 0-36 h lead time:for lead times 0-12 h,actual observations from the 0-12 h period before the forecast time are used,with k ranging from 0-12; for lead times 13-36 h,forecast data from 12 h before the forecast time are used,with k fixed at 12),the predictive performance of LightGBM is further improved.For all 37 forecast lead times,the accuracy is improved over the original CMA-MESO model forecasts.Particularly in plateau regions with elevations above 1000 meters,the RMSE improvement exceeds 30%.Moreover,these methods continue to demonstrate strong adaptability under transitional weather conditions.In terms of overall forecasting performance,LightGBM proves to be the best,achieving a root mean square error(RMSE)of 1.86 ℃,a mean absolute error(MAE)of 1.42 ℃,and an accuracy of 75%,representing improvements of 36.5%,38.9%,and 44.4% respectively compared to the CMA-MESO forecast. References | Related Articles | Metrics

Select

Evaluation and correction of CMA-MESO predictability of low temperature event at airports CHEN Hao, HE Xiaofeng, TANG Xian 2025, 41 (3):  29-35.  doi: 10.3969/j.issn.1673-503X.2025.03.004 Abstract ( 29 )   PDF (3743KB) ( 6 )   Save Based on Meteorological Terminal Aviation Routine Weather Report (METAR),meteorological station observation data,and numerical model products for 13 airports in Northeast China in 2021,this study analyzes and evaluates the performance of CMA-MESO temperature forecasts at airports prone to high-impact low temperature events,and examines the predictability of the high-impact low-temperature interval.The results indicate that the temperature forecasts for most airports are higher than the observations except for ZYDQ,the absolute error and root mean square error of airports in the northern,eastern,and high-altitude areas are significantly larger than those in plain areas; the temperature error,absolute error and root mean square error have obvious diurnal and seasonal variations with the largest forecast errors occurring at 06:00-07:00.When the forecasts of airport temperature are above 0 ℃,they are close to observations; when below 0 ℃,the forecasts are more clustered.After applying the cumulative probability density function correction method to the airport temperature forecast error for ZBES,ZYMH,and ZYLD airports,the hit rates for low temperature events increased by 56%,14%,and 9%,respectively. References | Related Articles | Metrics

Select

Application of the XGBoost method in wind power forecasting Duan Yunxia, Li Zhongxian, Li Deqin 2025, 41 (3):  36-43.  doi: 10.3969/j.issn.1673-503X.2025.03.005 Abstract ( 51 )   PDF (3807KB) ( 14 )   Save Using the wind power observation and training data from the 2014 Global Energy Forecasting Competition (GEFCom2014),a study on the application of the XGBoost machine learning method in wind power forecasting was conducted.To assess the potential influence of variable distribution on machine learning models,wind power forecasting models were developed using zonal wind and meridional wind,as well as wind speed and wind direction as feature variables.Forecast experiments show that although the distributions of actual observed wind power and numerically forecasted wind speed generally follow the wind power curve,the high degree of dispersion is a major factor contributing to the uncertainty in wind power forecasts.While the correlation between zonal/meridional winds and wind power is not high,models trained with these features using XGBoost still achieve good forecasting performance comparable to those built directly with wind speed and wind direction.The forecast results of the models tend to underestimate wind power peaks and overestimate low power values,which may be attributed to errors in numerically forecasted wind speed. References | Related Articles | Metrics

Select

Evaluation and validation of gridded wind field analysis products in Heilongjiang Province LIU Songtao, GAO Mengzhu, QI Duo, WANG Chengwei, SHI Muzhen 2025, 41 (3):  44-51.  doi: 10.3969/j.issn.1673-503X.2025.03.006 Abstract ( 31 )   PDF (1816KB) ( 6 )   Save Using hourly ground observation data from 910 stations in Heilongjiang Province from 00:00 on 1 January 2020 to 00:00 on 25 December 2024 as the benchmark,the national-level hourly 10 m wind gridded live analysis product with a 5km resolution was evaluated by utilizing tools such as the METEVA validation tool and bilinear interpolation methods.The results indicate that this product exhibits low mean error,absolute error,and root mean square error within Heilongjiang Province,maintaining good consistency.Overall,the product demonstrates good applicability in Heilongjiang Province.In terms of spatial error distribution,the accuracy is relatively lower in the western plains and southeastern mountainous regions,while in the other regions,the accuracy for errors within ±2 m·s-1 exceeds 85%.This may be attributed to the complex topography in the southeastern mountains and the significant variations in underlying surface properties of the western plains.From the perspective of annual variations,wind speed (wind force grade) generally exhibits negative deviations,particularly pronounced from April to May,while it performs relatively better in winter,with wind vectors displaying similar characteristics.The wind direction tests show better results in spring compared to summer.In terms of diurnal variations,the negative deviation of wind speed is larger during the daytime (08:00-18:00) and smaller at night.The smallest error is observed for winds of grade 0-1,while the negative deviation increase with winds for grade ≥2,and the diurnal variation amplitude becomes significantly larger with winds for grade ≥ 7. References | Related Articles | Metrics

Select

Analysis on wind field forecast performance under complex terrains of the Sub-hundred-meter Numerical Forecast System of Inner Mongolia YAO Xiaojuan, SUN Xin, ZHU Feng, LIU Linchun, JI Yanxia, LIU Ke, SUN Zhezhong 2025, 41 (3):  52-60.  doi: 10.3969/j.issn.1673-503X.2025.03.007 Abstract ( 27 )   PDF (4451KB) ( 5 )   Save To meet the demand for high-precision weather forecasting services under complex terrains for the 14th National Winter Games,the Sub-hundred-meter Numerical Forecast System of Inner Mongolia (SNFS) was developed by integrating large eddy simulation technology and high-resolution terrain data,specifically for the outdoor competition areas of the 14th National Winter Games.This paper uses the observational data from the competition area stations as references,and evaluates the wind field forecasting performance of the SNFS system in the three competition areas based on wind speed forecast evaluation indicators and assessment scores.The results indicate that there is a systematic overestimation of wind speed forecast in the Zhalantun and Kharchin competition areas,while an underestimation in the Liangcheng competition area.For stations at lower elevations,the forecast and observed wind speed deviations are mainly positive; with increasing station elevation,the wind speed deviations turn to negative and become more dispersed.The forecast for Zhalantun and Kharchin competition areas tend to overestimate the wind weaker than Grade 6 and underestimated the wind stronger than or equal to Grade 6 in different lead times; while the Liangcheng competition area consistently underestimates the wind,and the Zhalantun competition area shows a significant advantage in forecast score.Further analysis of an individual case of strong wind weather in the Zhalantun competition area shows that,the forecast wind direction is generally consistent with the observed wind direction,and the trend of wind speed change.The SNFS system can characterize the local flow field characteristics and has good forecasting capability for wind fields under complex terrains. References | Related Articles | Metrics

Select

Study on the impact of adverse weather fonditions on expressway traffic safety in Liaoning Province ZHANG Mengmeng, ZHANG Weiqi, ZHANG Kai, LIN Yi, WANG Han, LI Jianing, LYU Jiaxin, ZHAO Yu 2025, 41 (3):  61-67.  doi: 10.3969/j.issn.1673-503X.2025.03.008 Abstract ( 54 )   PDF (2991KB) ( 21 )   Save Based on the data of expressway traffic accidents,traffic blocking from 2018 to 2022 and meteorological observations from 1971 to 2022 in Liaoning Province,this study analyzes the adverse impacts of different meteorological factors on traffic safety in Liaoning Province.The results show that rainfall is the primary weather factor leading to the accident of Liaoning expressway,and the correlation coefficient between the number of rainfall days and the number of accidents is 0.78.The accident-prone seasons are summer and autumn,and the time period is 9:00-10:00.Low-visibility events and snowfall are the main meteorological factors that lead to traffic jams on expressways.The main blocking season is winter,and the period is 18:00-23:00.The number and mean distribution of high-impact weather days in Liaoning Province show certain regional differences.The adverse weather accident-prone section of Jingha Expressway (532-552 km) is mainly affected by rainfall and low-visibility events.The number of low-visibility event is high and the average visibility is low.The number of rainfall days is high and the precipitation is heavy.The number of rainfall and snowfall days showed a decreasing trend,and the number of low-visibility days showed a significant decreasing trend before 1986,and then increased significantly. References | Related Articles | Metrics

Select

A case study on the heavy precipitation caused by a quasi-stationary mesoscale convective system SUN Xin, LIU Hongjun, WANG Guoliang 2025, 41 (3):  68-75.  doi: 10.3969/j.issn.1673-503X.2025.03.009 Abstract ( 37 )   PDF (11383KB) ( 21 )   Save A heavy precipitation process in the Hetao area of Inner Mongolia on 13 August 2022 was studied using radar,surface observations,sounding data and ERA5 reanalysis data in this paper.The results indicate that the precipitation was mainly caused by a quasi-static mesoscale convective system,which was characterized by the continuous formation of east-west linear convections in the south of the Yin Mountain and the movement to the northeast,resulting in long-lasting heavy precipitation in the Hetao area.The subtropical high extended westward to inland,forming a persistent southerly airflow in the southern Hetao area.This low-level water vapor could be continuously transported from the south or southeast channels to the Hetao area,forming a stable water vapor supply.The blocking effect of the Yin Mountains caused the water vapor to accumulate on the southern slopes of the mountain,leading to high convective available potential energy,which was conducive to the initiation and development of deep convection.Deflected by the trend of the Yin mountain,the easterly airflow turned to a northeasterly airflow.The convergence line formed by the northeasterly airflow and the southerly airflow provided uplifting for the initial convection.After the convection triggered,the northward diffusion of the cold pool was constrained by the mountains,which strengthened the cold pool and enhanced the cold pool to lift the southerly airflow with moisture,resulting in subsequent convections.Due to the stable water vapor transport of the southerly airflow,after the convection generated by the convergence in the southern mountain moving to the northeast,the warm and humid airflow could continue to be lifted by the cold pool,which is generated by the previous convection and trigger new convections,thereby generating the quasi-stationary organized mesoscale convective system and ultimately resulting in heavy rainfall. References | Related Articles | Metrics

Select

Accuracy assessment of FY-4A and FY-4B Quantitative Precipitation Estimation in Sichuan CHU Meng, WU Wei 2025, 41 (3):  76-84.  doi: 10.3969/j.issn.1673-503X.2025.03.010 Abstract ( 22 )   PDF (6169KB) ( 22 )   Save Using hourly precipitation data from ground stations in Sichuan Province from September 2022 to August 2023,the accuracy of Quantitative Precipitation Estimation (QPE) products from FengYun-4A (FY-4A) and FengYun-4B (FY-4B) satellites in Sichuan was compared by statistical and evaluation indicators.The results show that FY-4A and FY-4B QPE products perform better in regions with less precipitation,such as the plateau region,than in regions with more precipitation,like northeastern Sichuan and the plateau-basin transition zone.FY-4A tends to underestimate precipitation,while FY-4B tends to overestimate it,with FY-4A performing better overall than FY-4B.At the annual scale,the correlation coefficients between precipitation from FY-4A and FY-4B and that observed on the ground are 0.69 and 0.59,respectively.This indicates that FY-4A is closer to ground-based precipitation observations.At the seasonal and monthly scales,the correlation coefficients between the two satellite QPE products and the ground-observed precipitation are high in spring and October,and lower in winter.FY-4A performs better in spring and September-October,while FY-4B performs better in July-August.Except for the slight overestimation by FY-4B for precipitation below 2.0 mm·h-1,both QPE products mainly underestimate precipitation at other precipitation levels,with FY-4A underestimating more.As rainfall intensity increases,the underestimation worsens,and the root mean square error increases.FY-4A shows slightly better performance than FY-4B when there is no ground precipitation.Analysis of two heavy rainfall events in July 2023 indicates that both QPE products can indicate the approximate range of precipitation areas and reflect the timing of precipitation occurrence well,but both underestimate the amount of precipitation. References | Related Articles | Metrics

Select

Study on the variation characteristics of surface ozone and the impact of atmospheric circulation over Mt.Waliguan area NIE Hong, WANG Kai, ZHANG Xiaoyun, LIU Qingqing, SONG Chuangang, LUO Wenzhao, ZHENG Xiangdong, LIU Meng 2025, 41 (3):  85-92.  doi: 10.3969/j.issn.1673-503X.2025.03.011 Abstract ( 35 )   PDF (1682KB) ( 17 )   Save By using the daily averaged data of Mt.Waliguan during 2016-2022,this study analyzes the relationship of variation's characteristics of near surface ozone concentration and their relationships with multiple meteorological factors such as air temperature,wind direction and speed over Mt.waliguan area,and the influences of abnormal upper air circulation upon surface ozone,where it reveals the variation characteristics and the impact of atmospheric circulation over Mt.waliguan area.The result shows that the daily averaged concentration shows significant fluctuation throughout the year,reaching highest in summer and lowest in winter.In the meantime,the surface ozone has a positively and negatively correlation with temperature and relative humidity,the higher temperature and lower relative humidity cause the rising of surface ozone.The northeasterly wind of Mt.walugan is in favor of surface ozone's accumulation,thus resulting in higher concentration,meanwhile,the southwesterly wind will cause the rapid proliferation in the horizontal direction,which is difficult to form the higher concentration.In addition,when there is a "Foehn effect" in the atmosphere,will also trigger the rising of surface ozone.The upper air circulation patterns over Mt.waliguan also affects the concentration of surface ozone,when the 100 hPa circulation pattern belongs to the western type,the polar vortex is weak,and presence of the warm high or ridge over Mt.waliguan,and causes the rising of concentration of surface ozone; conversely,when the 100hpa circulation pattern belongs to the eastern type,the polar vortex is strong,the presence of low pressure and a trough of low pressure will cause the decreasing of surface ozone. References | Related Articles | Metrics

Select

Preliminary study on water changes during abnormal drought in East Dongting Lake Wetland in summer 2022 CHEN Leishi, HAN Qinzhe, FAN Jiazhi, HE Bingwei, LI Wei, YAN Ruliu 2025, 41 (3):  93-100.  doi: 10.3969/j.issn.1673-503X.2025.03.012 Abstract ( 24 )   PDF (5247KB) ( 3 )   Save In the summer of 2022,abnormal high temperatures and drought in the Yangtze River Basin severely impacted China's natural environment.On 4 August,Dongting Lake had already entered the dry season,with the continuous exposure of lake bed,and disconnection even in the core area of the main lake body.In order to accurately monitor the spatiotemporal changes in the water of the East Dongting Lake wetland during this drought period,UAV sampling data and field survey data were used to evaluate the accuracy of three typical algorithms:MNDWI,AWEI,and CS-OTSU.Experimental results indicate that the CS-OTSU algorithm shows the highest mapping accuracy,user accuracy,overall classification accuracy and Kappa coefficient.It can accurately extract the dry flow of the main lake body and the exposed lake bed.The spatiotemporal change results of East Dongting Lake wetland water in August 2022 extracted by the CS-OTSU method show that the average water area decreased by 71.58% compared with the same period in 2021.The permanent water area decreased by 86.24%.From the beginning to the end of the month,more than half of the water body of the East Dongting Lake wetland had shrunk.Despite remaining stable,the water body boundary of the main flood channel was reflecting the severe impact of drought.The core area of the main lake dried up entirely,indicating the severe impact of this drought on the East Dongting Lake wetland. References | Related Articles | Metrics

BULLETINS

Select

Precipitation influence driving time forecast model based on Baidu Map ZHANG Yefang, FENG Zhenzhen, HUANG Huilin, LIU Bing 2025, 41 (3):  101-107.  doi: 10.3969/j.issn.1673-503X.2025.03.013 Abstract ( 21 )   PDF (1087KB) ( 8 )   Save This article aims to study the impact of precipitation on driving travel time and its forecasting model.The current road condition value,precipitation amount,historical road condition changing trend,and current driving navigation travel time are used as independent variables,and the increase rate of driving navigation travel time in the next hour is used as the dependent variable.A total of 13 142 pairs of meteorological and traffic data from January 2021 to December 2022 in the jurisdiction of Fuzhou City were collected through web crawlers to analyze the impact of precipitation on driving travel time.Multiple linear regression and random forest regression were used to develop two forecasting models,and the prediction effects of the two models were tested using the Fuzhou City jurisdiction from January to May 2023 as an example.The results indicate that precipitation has a non-linear positive impact on driving travel time.Within the rainfall intensity range of 0.0-0.7 mm·h-1,for every 1mm increase in rainfall,the average travel time increases by 0.33 times.Beyond 0.7 mm,for every 1mm increase in rainfall,the average travel time increases by 0.06 times.The rate of increase in travel time varies slightly across different time periods,with a higher increase during commuting hours.Whether using forecast precipitation data or actual precipitation data,the random forests have lower losses or biases in sample training and testing compared with the multiple linear regression models; and the accuracy of precipitation forecasts has a significant impact on travel time forecasting. References | Related Articles | Metrics

Select

Fuzzy assessment of regional lightning hazard risk based on improved analytic hierarchy process LIANG Jingfeng, LI Xiaolong, CHENG Xiangyang, ZHAO Jingbo, XU Junqing 2025, 41 (3):  108-115.  doi: 10.3969/j.issn.1673-503X.2025.03.014 Abstract ( 31 )   PDF (578KB) ( 14 )   Save In order to carry out regional lightning disaster risk assessment scientifically and effectively,a fuzzy comprehensive assessment scheme of regional lightning disaster risk based on improved analytic hierarchy process (IAHP) was proposed based on the analysis of domestic and international disaster loss assessment methods,especially the relevant technical standards and specifications of lightning disaster risk assessment.The improved three scale analytic hierarchy process is used to calculate weights of assessment index,avoiding the consistency test,and improving the convenience and accuracy of constructing judgment matrix.The membership degree of risk grade of assessment index was determined by using triangular arithmetic membership function; and the consistency of the membership degree determination methods of risk grade of different assessment indexes was realized.The evaluation results and risk grades were determined according to the maximum membership degree principle,which accounts for the fuzziness and uncertainty of lightning disaster and improves the scientific robustness of risk assessment.By implementing this methodology with lightning positioning data,radar meteorological observations,on-site field investigations,and regional planning documentation,a comprehensive lightning disaster risk assessment was carried for Hebei Baoding Lianchi High-tech Industrial Development Zone.The results are consistent with those obtained by using the current technical standards for lightning disaster risk assessment,which confirms the feasibility and reliability of the method. References | Related Articles | Metrics