In February 2024, Hunan encountered two regional rainfall/snowfall and freezing events with low temperatures, one in northern Hunan from February 2 to 6 (hereinafter referred to as the“2.02”event), and the other across the whole province from February 21 to 26 (hereinafter referred to as the“2.21”event). Using conventional upper-air and surface weather observations, regional automatic weather station data, and NCEP reanalysis data, we conducted a comparative analysis of the circulation background, cooling mechanism, and water vapor transport characteristics of the two events. The results are as follows. (1) There are obvious differences in the circulation background between the two events. The“2.02”event occurred in the background with eastward movement of both the southern branch trough and westerly trough overlapping in phase. However, the“2.21”event occurred under the cold wave caused by the collapse of the blocking high, with the transition of rain and snow phases appearing multiple times due to the small influence on the southern branch trough. (2) There were the strong low-level frontal zone in both events. A rare north-south temperature gradient greater than 26 ℃ was observed in the“2.21”event, which may be an important indication of this extreme cold wave weather. (3) Temperature advection played an important role in the transition of rain and snow phases. In the“2.02”event, the strong cold advection intrusion in the middle level was driven by the westerly trough, causing a temperature decrease across the whole layer. In the“2.21”event, the continuous input of the ultra-low-level strong cold advection was one of the important cooling mechanisms. In addition, the strongest transport layer of warm advection corresponded to the negative center of vertical velocity, and the stronger vertical wind shear in the middle and lower troposphere resulted in stronger rain and snow intensity. (4) The Arabian Sea was the main source of water vapor for both events. Southwest warm and wet airflow in the middle troposphere moved with the low trough at 500 hPa or the small trough from it, with the highest contribution of specific humidity and water vapor flux to both events. The low troughs provided both favorable dynamical conditions and abundant water vapor for the occurrence of rain and snow weather. In the “2.21”event, the warm and wet air carried by three combined channels from the South China Sea channel, the Arabian Sea channel and the low latitude inland regions provided water vapor and warm layer conditions for the freezing area in the southern Hunan, which was an important reason for the severe freezing in this area.
High-quality three-dimensional wind field retrieval products from Doppler weather radars are essential data for studying and forecasting mesoscale weather systems. The existing 3D variational wind field retrieval method (3DVAR) mainly uses data from single or multiple radars to conduct the wind field retrieval of small regions. However, for wind field retrieval of large regions using multiple radars, challenges exist, such as high computational requirements and slow processing speeds, which obstruct operational applications. In this study, anan improved method (D-3DVAR) that can obtain high-quality large-scale wind field results is proposed by combining the dual-radar wind field retrieval method, based on the 3DVAR method, using 11 S-band Doppler weather radars and 27 X-band phased array weather radars in Guangdong Province. The optimization process consists of three steps. First, determine the wind field retrieval area based on the location of the weather system to reduce the number of radars; Second, reduce the number of radars by calculating the contribution ratio of the radar network in the dual-radar wind field retrieval; Third, during the dual-radar wind field retrieval process, only select the optimal two radial velocities for each grid point to conduct the wind field retrieval, while the remaining radial velocities do not participate in subsequent wind field retrieval. The results of wind field retrieval after each optimization step are recorded as Majorization 1-3. Taking a squall line process along the coastal area of Guangdong Province on 13 May 2022, as an example, wind field retrieval was performed on the radar network using D-3DVAR, and the retrieval results were compared and verified. The results show that the three-step optimized wind field retrieval method can obtain dual-Doppler radar wind field retrieval results for a large area of the Greater Bay Area, which can better cover the land area of the Greater Bay Area at an altitude of 2 km and most areas within the coastline at an altitude of 4 km. Compared to Majorization 1, the wind field retrieval program execution speed of Majorization 2 and 3 is increased by 3 times. The basic characteristics of Majorization 3 and Majorization 1 are consistent, with wind speed errors less than 1.7 m·s-1 and wind direction errors within 10°. However, the wind field retrieval result of Majorization 3 can better highlight the characteristics of strong updraft and vertical vortex in the wind field of mesoscale weather systems.
To gain an in-depth understanding of the asymmetric structure of the Southwest Vortex producing rainstorms, the rainstorm process in the Sichuan Basin on 30 June 2013 was investigated in this study. This rainstorm was caused by the slowly moving Southwest Vortex, and had the most significant impact in the past decade. Based on WRF numerical simulation and other data, the asymmetric structure characteristics and causes in the mature stage of the Southwest Vortex rainstorm were analyzed by using a dynamic composite method that followed the vortex center, combined with vorticity equation diagnosis, divergence equation diagnosis, and wind field decomposition. The results are as follows. (1) The Southwest Vortex exhibited convergent airflows which rotated into the center and gradually weakened at low altitudes, while divergent airflows rotated at high altitudes. The precipitation, positive vorticity, low-level convergence, and vertical ascending motion of the Southwest Vortex exhibited significant asymmetric distribution characteristics. The front side of the vortex exhibited significant positive vorticity, and prominent convergence ascending motion, leading to heavy rainfall. While on the rear side of the vortex, the positive and negative vorticity coexisted, with weaker convergence and ascending motion, accompanied by weaker rainfall. (2) The asymmetric distribution of the Southwest Vortex was related to the impact of subtropical high in front of the vortex. The maintenance of subtropical high favors the formation of the asymmetric structure of the Southwest Vortex, which was conducive to the formation of the gradually increasing potential height gradient and the enhancement of the low-level jet in front of the southeastward vortex. The spatial distribution led to negative evolutions of the Laplace term of potential height and the Laplace term of kinetic energy, which produced a sustained low-level negative non-equilibrium dynamic forcing effect. Then the negative non-equilibrium dynamic forcing promoted the development of low-level convergence, and vertical ascending motion, and led to heavy rainfall. In addition, the positive vorticity was generated through low-level convergence and vertical ascending motion in front of the vortex, forming asymmetric distribution characteristics of rainfall, positive vorticity, low-level convergence, and vertical ascending motion associated with the Southwest Vortex.
The Tropical Cyclone (TC) Rainfall Climatology and Persistence Model (R-CLIPER) is a statistical parametric model for TC precipitation based on observations of North Atlantic TCs or global TCs. It boasts simple inputs and quick calculations, enabling climate-scale TC precipitation simulations, thus providing technical support for TC precipitation forecasting and risk assessments. This study focuses on TCs in the Western North Pacific region and performs localization of the R-CLIPER model. Firstly, based on precipitation data from Tropical Rainfall Measuring Mission (TRMM) satellite and Fengyun satellite (FY2C/2E) precipitation data, the radial average profiles of precipitation from TCs of 6 different intensity levels (i.e., super typhoon, strong typhoon, typhoon, severe tropical storm, tropical storm, tropical depression) are extracted. Secondly, combined with the R-CLIPER model framework, a globally optimal parameterization fitting method for TC precipitation profiles is developed. Two models are constructed, including the R-CLIPER for the Western North Pacific Ocean based on TRMM data/FY data, namely TRMM-R-CLIPER-WNP (Model 1) and FY-R-CLIPER-WNP (Model 2). Finally, based on the 62 tropical cyclones in the Northwest Pacific from 2012 to 2013 and the 26 cyclones that affected Zhejiang from 2009 to 2021 the models are evaluated in terms of fitting error and precipitation falling area. The results are as follows. (1) The TC rainfall profiles derived from TRMM data are relatively sharp near the maximum rainfall, while those from FY2C/2E satellite data are smoother and more detailed due to its higher spatial resolution. (2) The RMSE of TRMM parameterized profiles is 0.28 mm·h-1, and that of FY2C/2E profiles is 0.51 mm·h-1. (3) Based on the ground-based station data evaluation, when the rainfall threshold is less than 3 mm·h-1, the ETS score of Model 1 is better than that of Model 2. But when the threshold is greater than 3 mm·h-1, Model 2 is better. Both models perform better when the TC is centered over the sea than over land, indicating higher accuracy of TC central rainfall intensity prediction over the ocean than over land. In conclusion, using the parameterized fitting method, the accuracy of the R-CLIPER model in simulating TC precipitation in the Northwest Pacific region can be improved by 5.5%. Additionally, it was revealed that the error in TC precipitation simulations is influenced by factors such as model data sources, model framework, and parameterization schemes.
Strong convective weather dominated by thunderstorm strong winds appeared in Liaoning Province in the evening of 25th June 2022. Eighty-two automatic weather stations across the province recorded thunderstorm strong winds of magnitude 8 or above. Among them, the Ma Sanjia Station in the northern part of Shenyang City, Liaoning Province, recorded wind speeds of 13 on the Beaufort scale (39.1 m·s-1), resulting in severe damage. By utilizing the minute-level observational data from automatic weather stations in Liaoning Province on June 25 from 17:00 BT to 22:00 BT, as well as conventional radiosonde, dual-polarization radar, and data from the European Centre for Medium-Range Weather Forecasts ERA5 reanalysis, an analysis and study were conducted on the formation mechanism of this thunderstorm strong wind event. The results are as follows. (1) Liaoning is located at the southwest quadrant of the northeast cold vortex, where the cold dry air on the western side of the vortex converged with warm moist air in the northern part of Liaoning Province on the evening of the 25th. (2) The Shenyang sounding curve exhibits a low-level warm and dry layer, a mid-low-level moist layer, and a mid-high-level dry and cold layer with an "X" shaped pattern. Additionally, it features strong vertical wind shear, which creates favorable conditions for the occurrence of severe convective weather. (3) The evolution of radar echoes in this process is consistent with the evolution of classic bow echoes; isolated thunderstorms in the initial stage lead to locally strong winds. Subsequently, multiple individual storms gradually merge into a bow echo. The interaction of negative buoyancy, momentum transport, and cold pool density currents collectively results in widespread thunderstorm winds in the Shenyang urban area. (4) Along the leading edge of the bow echo, shallow low-level gamma scale cyclones are present. The rotation of low-level cyclones forms perturbation low pressure near the ground, enhancing the downdraft, while the cyclones interact with the strong inflow jet on the rear side, leading to locally strong thunderstorm winds.
To study the microphysical characteristics of warm-sector rainfall(WR)and frontal rainfall(FR)during the South China pre-flood season,the two-dimensional video raindrop spectrometer(2DVD)data,automatic station precipitation data,and ERA5 reanalysis data from four rainfall events were investigated in this study.The raindrop size distribution(DSD)parameters,the shape factor and slope factor(μ-A),and the relationship between radar reflectivity factor and rain intensity(Z-R)of FR events on June 17,2017,and April 6,2023,and WR events on June 22,2017 and May 11,2022 were analyzed.The results are as follows.(1)In both FR and WR events,convective precipitation dominates,which has a high concentration of each raindrop size(especially a diameter smaller than 1 mm)and a large raindrop diameter.Both the occurrence probability and precipitation contribution ratio of convective precipitation in WR events are higher than those in FR events.(2)During the convective development stage of precipitation in WR and FR events,the increase of rain intensity R usually lags be-hind that of radar reflectivity factor Z.The extreme values of R,mass-weighted diameter Dm,and generalized intercept parameter lgNw in WR are much larger than those in FR.(3)The value of Dm and lgNw is larger in WR events,showing that the distribution of convective precipita-tion in WR events is relatively dispersed,compared to the smaller Dm and lgNw in the stratiform precipitation of FR events.(4)The μ-A rela-tionships and Z-R relationships of FR and WR events differ significantly.Also,the Z-R relationships in this study are different from the classical Z-R relationship of continental convective precipitation.
In order to improve the understanding of the characteristics of thunderstorms in Guangxi and better study its forecasting methods,based on the 2022 VLF/LF 3D lightning data and SWAN radar 3D composite data,1 131 thunderstorm cases were identified and extracted by integrating SCIT(Storm Cell Identification and Tracking)and DBSCAN(Density Based Spatial Clustering of Applications with Noise),and thunderstorm feature data sets were constructed.Based on this data set,statistical analysis was carried out on the characteristics of thun-derstorms in Guangxi,such as the spatiotemporal distribution,movement direction,duration,movement speed,and movement distance.Then further analyze the distribution characteristics of radar reflectivity,vertically integrated liquid water(VIL),and echo height in thunderstorm environments.The results are as follows.(1)Thunderstorms in Guangxi are characterized by more in the south and less in the north,with the highest thunderstorm activity in the southern coastal areas.Thunderstorms occur most frequently in summer(June-August),account-ing for 65.3％,while they sharply decrease in winter(December-February),accounting for only 0.18％.Thunderstorms mainly occur from 11:00-19:00 BT during the day.(2)The thunderstorms speed was mainly concentrated in the range of 2～16 m·s-1,with the most frequent speed being 4～6 m·s-1.The movement distance was mainly within 100 km,with the most frequent distance being 10～20 km.The dominant movement directions of the thunderstorms were northeast,north,northwest,and east.There are certain differences in both speed and distance among thunderstorms moving in different directions.Specifically,thunderstorms moving eastward tend to be faster(8～16 m·s-1)and travel farther(10～40 km),those moving southward are generally slower(2～10 m·s-1)and travel shorter distances(0 to 30 km);thunderstorms mov-ing in other directions have speeds concentrated 4～12 m·s-1,though with varying peak ranges.(3)The initial flash in thunderstorms often oc-curs in areas with reflectivity greater than 45 dBz and VIL less than 30 kg·m-2.Lightning after the initial flash is primarily occurs in the 45～65 dBz strong echo region and is highly correlated with VIL in the range of 0.1～40 kg·m-2.The strong echo core which threshold greater than 45 dBz with top height exceeds 6 km can be used as one of the reference indicators for lightning occurrence.
Based on the hourly ground precipitation observations from the national and regional stations in Guizhou Province from 2016 to 2020, the spatial and temporal characteristics of heavy precipitation in the typical terrains of Guizhou were analyzed in this study. For typical terrains, the Beipan River was selected as the typical representative of Guizhou's valley terrain, while Leigong Mountain and Fanjing Mountain were chosen as the typical representatives of Guizhou's high mountain terrain. The three-hour precipitation forecast datasets during 2019-2020 provided by the European Centre for Medium-Range Weather Forecasts (ECMWF) were used, and a frequency matching method was applied to objectively correct the heavy precipitation forecast in the above three regions. The results are as follows. (1) Heavy precipitation in the three regions mostly occurs in June. The heavy precipitation frequency increases in Beipan River and Leigong Mountain year by year, while the increase in Fanjing Mountain is not significant. The heavy precipitation in the two mountainous regions mainly occurs during the night and early morning. While two heavy precipitation peaks are found in the Beipan River basin, one in the afternoon and one at night. (2) The distribution of heavy precipitation in the three areas is somewhat related to the terrain. The frequent and concentrated areas of heavy precipitation in the Beipan River are mainly located in the low-lying areas in the northern part of the basin, with that being in the south of Leigong Mountain and on the eastern side of Fanjing Mountain. Considering the slope of the terrain, the distribution of rainfall shows similar characteristics. In the regions of Beipan River and Fanjing Mountain with slopes less than 20°-30°, and the regions in Leigong Mountain with slopes less than 40°-50°, the frequency of heavy precipitation increases with the slope. While in other regions, the frequency of heavy precipitation decreases with the slope. (3) Objective corrections of heavy precipitation in these regions are applied using the frequency matching method. It is found that the frequency adjustment method has a certain effect in reducing the over-forecast of precipitation when the precipitation amount is less than 8.2 mm in Beipan River, less than 10.3 mm in Leigong Mountain, and less than 7.3 mm in Fanjing Mountain. When precipitation is greater than the above thresholds, the frequency matching method can significantly improve the levels of the predicted precipitation. After the correction, the overall performance of heavy precipitation prediction in the three regions has improved. A noticeable increase in the frequency of heavy precipitation prediction and comparable spatial distributions between the predictions and observations can be found, with the best improvement observed in the Beipan River.
To explore the influence of the lightning detection station layout on lightning location accuracy, the magnetic field waveform observation data from the natural lightning observation test base at Jiuxian Mountain in Fujian Province were used and ten return strokes of cloud-to-ground flashes from different orientations and distances both inside and outside of the detection network were selected. Using the time of arrival (TOA) method and the positioning results by 10 (or 9) stations as the references, we compared and analyzed the discrepancies of location results under different combinations of 5 to 8 stations. The possible reasons for the discrepancies in the location results were also explored. The results show that lightning location is closely related to the number of stations and the layout of the stations. For the same number of stations, large differences in the location results can be found for different station layouts, but with the increase in the number of stations, the differences caused by different station layouts gradually decrease. For the location with the same number and layout of stations, there are also significant differences in the localization deviations for lightning from different orientations and distances. The deviation of lightning localization outside of the network is significantly larger than that inside the network. The positions of lightning outside the network often show a "band-like distribution", and the farther the lightning is away from the network, the more obvious the deviation of this "band-like distribution" is. This is due to the narrow spatial region formed by the intersection of hyperbolas.
Anthropogenic aerosols have an important impact on summer heavy precipitation,but their impact and associated mechanisms are still greatly uncertain.In this study,the WRF-Chem including the aerosol-meteorology interactions was used to investigate the effects and possible mechanisms of aerosol direct,indirect,and total effects on a heavy rainfall event that occurred in Beijing during August 12-13,2020.The results are as follows.(1)In the first stage of the precipitation(15:00-18:00 BT on August 12),due to the aerosol effects on solar radiation and cloud nuclei,the aerosol direct,indirect,and total effects all decrease the hourly precipitation intensity in the Beijing urban ar-ea,with a maximum reduction of 6 mm·h-1,1 mm·h-1,and 4 mm·h-1,respectively.(2)In the second stage(20:00 BT on August 12 to 04:00 BT on August 13),both aerosol direct and indirect effects decrease the hourly precipitation intensity,with a maximum reduction of about 4 mnvh-1.The aerosol total effect has little impact on the hourly precipitation intensity but delays the precipitation time.Generally,the aerosol direct effect enhances the warm cloud process while weakening the cold cloud process,thus decreasing the precipitation and advancing the strong precipitation process in the second precipitation stage.The aerosol indirect effect decreases the effective radius of rain,thereby reduc-ing the merging process and precipitation,and delaying the onset of heavy precipitation during the second precipitation stage.The aerosol to-tal effect on precipitation is a nonlinear result of both aerosol direct and indirect effects,with the direct effect dominating in the first stage of precipitation and the indirect effect dominating in the second stage of precipitation.
The assessment of lightning disaster-causing hazards is the key to risk survey of lightning disasters. Following the technical route of the national meteorological disasters comprehensive risk survey since 2020, and based on the lightning location data from 2010 to 2020, lightning disaster data from 2000 to 2020, digital elevation data, and soil conductivity data in Anhui Province, a model diagram of disaster-causing hazard zoning was constructed according to"Specification for meteorological disasters investigation and risk assessment: Lightning". The Analytic Hierarchy Process was used to determine the weight of each index, and the lightning disaster-causing hazard index was then calculated. The zoning of lightning disaster-causing hazards in Anhui Province was completed by combining with GIS technology. The results are as follows. (1) The distributions of lightning strike density and lightning peak current amplitude are closely related to the topography. The altitude and terrain have a positive driving effect on the lightning disaster-causing hazard. (2) The high and relatively high sensitivity of lightning disaster-pregnant areas are mainly located in mountainous regions, along the Yangtze River, and parts of the Huai River basin. (3) The areas of high lightning disasters are mainly located in most regions along the Yangtze River and southern mountainous regions in Anhui Province. The areas of relatively high lightning disasters are mainly located in the southern mountainous region, between the Yangtze River and Huai River, and parts of the Jiangnan region. The areas of low and relatively low lightning disasters are mainly located in the plain and hilly areas in the northern Anhui region and the Jiang-huai region. By comparing the zoning results with historical disaster data, it is found that the distribution of lightning disaster-causing hazard zoning agrees well with the true distribution of disaster, which can provide a reference for future lightning disaster prevention in Anhui Province.
An extreme freezing weather occurred in Hubei during the early of February in 2024,which accompanying freezing rain,ice pel-lets,and snow occurred and the intensity of freezing rain ranks first since 1981.Based on conventional meteorological observations,dual-po-larization radar,and reanalysis data,the characteristics of observation and the cause of extreme freezing rain process are analyzed to provide reference for accurate forecasting and refined warning services of complex freezing weather processes.The results are as follow.(1)This pro-cess occurred under the combined influence of the subtropical trough and the subtropical high,with the long-term convergence of the cold air from the east route,forming a typical circulation pattern where the southwest warm and moist air flows are superimposed on the low-level cold air,and a"cold-warm-cold"temperature sandwich structure conducive to the occurrence of freezing rain is formed in the vertical direc-tion.The abnormally strong water vapor flux at 700 hPa,the abnormally high temperature at 700-800 hPa,and the abnormally low tempera-ture at 925 hPa are the main reasons for the extreme intensity of the freezing rain.(2)The analysis of the relationship between precipitation phase and vertical temperature and humidity layer structure indicates that the cloud top height,the melting layer,and the thickness and strength of the low-level cold pad are the key factors determining the precipitation phase.In this process in Hubei Province,both freezing rain and ice pellets are melting mechanism precipitation,with ice pellets having a higher cloud top height,weaker melting layer thickness and strength,and stronger low-level cold pad thickness and strength than freezing rain.(3)The dual-polarization radar characteristics of this extreme freezing rain are manifested as strong echoes mainly concentrated near the 2～3 km height of the melting layer,with a clear 0℃layer bright band feature,and echo intensity of 30～45 dBZ,the strongest reaching 50 dBZ,in and below the melting layer,the correlation coeffi-cient remains at 0.7～0.95,with a clear gradient high value area,the differential reflectivity is positive,with a strength of 1～3 dB,up to 4 dB at most,which is not significantly different from rainfall,but differs significantly from the negative value of pure snow.
The extreme heavy rainfall weather under the long-term influence of MCS can easily cause serious disasters such as flash floods in complex terrain areas. Detailed study of its characteristics and causes can help better understand and defend against similar disaster weather. In this paper, we use multi-source meteorological observation data to study the MCS evolution characteristics and mechanism of two rainstorm processes on 10-11 August 2020 (process 1) and 4-5 August 2021 (process 2) in the complex terrain area of the eastern slope of the Qinghai Tibet Plateau. The results are as follows. (1) The two processes are warm rainstorm weather processes under the influence of weak weather scale system, and the strong precipitation areas are located in the Pingba River valley to the west of Luochun Mountains. The terrain has a very obvious impact on the strong precipitation areas. Compared with process 2, process 1 has larger precipitation intensity, wider range and more concentrated distribution of precipitation areas. (2) The MCS that caused the two rainstorm both originated in the high altitude windward slope terrain in the west of Ya'an, and maintained development in the west side of Luochun Mountains, but the MCS of process 1 was larger in scale, intensity and duration. (3) The heavy precipitation in process 1 is mainly caused by a larger scale convective (mainly cumulus clouds) MCS with stable and less movement, while process 2 is caused by two successively developing mixed (cumulus layer cloud mixing) MCS passing through the same area. (4) The maintenance mechanism of MCS during the two processes is different. The main mechanism of Process 1 is the continuous formation of deep convective cells under the forced uplift of the Luochun Mountain terrain, which merge with the original MCS1_A and maintain it on the western side of Luochun Mountain for a long time, forming a quasi stationary backward established MCS echo zone; At the same time, the blocking effect of the terrain on the outflow of the cold pool and the bypass effect on the warm and humid air flow also promote the stability and less movement of MCS1_A to a certain extent. The main mechanism for maintaining MCS in process 2 is the feedback effect of high-altitude windward slope terrain.
Using CN05.1 and ECMWF Reanalysis v5 (ERA5) data, the characteristics of precipitation, water vapor content and precipitation conversion rate in eastern Southwest China (ESWC) during the summer of 1961-2020 were analyzed, and the influence of terrain distribution on the spatial distribution difference of precipitation conversion rate was preliminarily explored by means of synoptic analysis. Finally, the mesoscale numerical Weather Research and Forecasting Model (WRF4.0) was used to design terrain sensitivity tests to verify the effect of terrain on summer precipitation in the ESWC. The results are as follow. (1) In the summer of 1961-2020, the precipitation in the ESWC shows the characteristics of more precipitation in the east and less precipitation in the west, but there are two large value areas of water vapor content in the southeast and northwest of ESWC. The precipitation conversion rate in the large value area of water vapor is low, and the distribution of the strong precipitation area and the large value area of water vapor content are significantly different. By analyzing the situation of heavy precipitation areas in conjunction with horizontal wind fields and vertical velocity fields, it is found that topographic distribution is an important factor leading to this difference. (2) WRF model can well reflect the characteristics of summer precipitation in the ESWC. The terrain sensitivity test shows that the southwest to northeast mountain terrain distribution consisting of Dalou Mountain, Fangdou Mountain and Daba Mountain has a significant impact on the intensity of precipitation, and the decrease of terrain height will lead to a significant decrease of precipitation in the southeastern part of the region. (3) In particular, after reducing the topographic height of the region by half and to 0, respectively, the precipitation in the southeast of the region will decrease by 9.89% and 19.90% respectively on the monthly time scale. The change of topographic height will also cause the change of vertical velocity, horizontal wind field, water vapor transport and water vapor convergence, which will lead to the change of precipitation intensity. When the terrain height decreases, the upward motion and the southwest wind will weaken obviously, and the intensity of water vapor transport and water vapor convergence will decrease, which is not conducive to the formation of precipitation.
Based on the daily precipitation data of 2, 424 stations and conventional weather chart data in mainland China in 2021, a statistical analysis of the main heavy rain weather processes from April to October of that year was conducted. The main influencing systems and precipitation situations were outlined, and a comparative analysis of the number of heavy rain days and major heavy rain events from 2008 to 2021 from April to October was performed. The results show that from April to October 2021, China experienced a total of 199 heavy rain days and 32 major heavy rain events. The number of heavy rain days was 10 days more than the average for the previous 13 years (2008-2020), while the number of major heavy rain events remained the same as the average for the previous 13 years. Among them, there were 7 occurrences in July, 6 in May and August each, 5 in June, 4 in September, and 3 in October, with 1 occurrence in April. Among the 32 major heavy rain events, 5 were caused by the landing or influence of tropical cyclones. The northern heavy rain from July 18th to 22nd, including the "7.20" extreme heavy rain in Zhengzhou, was the most widely affected and economically damaging major heavy rain event, with Zhengzhou in Henan Province recording the country's largest daily precipitation of 552.5 mm on July 20th of that year. The maximum accumulated rainfall for a single event in the year reached 820 mm, also occurring in Zhengzhou, Henan Province (July 18th to 22nd) and was caused by the joint influence of a trough, shear line, and warm and humid airflow.
The short-time severe rainfall at the edge of the western Pacific subtropical high (referred to as the Subtropical High) is characterized by strong bursts, concentrated precipitation, and low predictability, often posing challenges for forecasting. Eight regional short-time severe rainfall events at the edge of subtropical high in Liaoning from May to October during 2021 and 2022 were examined. The synoptic situations of these events are divided into two categories according to the synoptic systems that cooperate with the subtropical high, which are the low trough at the edge of the subtropical high and the vortex at the edge of the subtropical high. Based on the European Center for Medium-Range Weather Forecasts (ECMWF) ERA5 reanalysis data, NCAR/NCEP GDAS data, conventional observation data, and HYSPLT4 model, the variation characteristics of the water vapor transport of the short-time heavy rainfall events during these two categories are studied. The changes in water vapor flux and the role of low-level jets were analyzed by investigating typical rainfall cases with the largest coverage of heavy precipitation and the most number of short-term heavy precipitation stations. The results are as follows. Under the upper-level trough and the cold vortex at the edge of the subtropical high, the water vapor over Liaoning mainly comes from the Central Eurasian continent, the eastern coast of China, the Inner Mongolian area, and North China. Despite the influence of similar synoptic systems, the water vapor transport pathways are significantly different, corresponding to differences in air mass sources, movement trajectories, and the way air mass obtains water vapor. The evolution of the high-value area of water vapor flux is consistent with the variation of the wind field at 850 hPa. During short-time heavy rainfall events, under the situation of low-level jet uplift and water vapor transport, the positions of the high-value area of water vapor convergence, strong updraft area, and water vapor transport pathways are closely related to the position of the low-level jet. The air mass from the Central Eurasian continent and the Inner Mongolian area contribute to 32% of the water vapor supply during the short-time severe rainfall events at the edge of the subtropical high in Liaoning.
The coupling factors of geological hazards such as rainfall are sufficient conditions for the occurrence of geological hazards. In this study, the distribution characteristics of Wuhan's geological disasters and their relationship with heavy rainfall by cluster analysis were investigated using multiple regression and other methods, based on Wuhan's geological disaster data, rainfall live grid data, and geological environment foundation during 2016-2022. Meanwhile, multi-source data fusion, machine learning, and other methods were employed to dynamically assess the vulnerability of geological disasters. The results are as follows. About 76.49% of geological disasters in Wuhan are induced by rainfall. The impact period of heavy rainfall on geological disasters in Wuhan is 13 days, and the possibility of geological disasters during the impact period is as high as 87.69%. A meteorological risk prediction model for geological disasters in Wuhan based on effective rainfall was established. This model can achieve a dynamic assessment of geological disaster-prone zoning by introducing the latest geological disaster occurrence, geological environment, and rainfall information. The 24-hour average accuracy rate can reach 79.51%. In the application of geological disaster prediction in 2022, the recognition rate reaches 90%, which shows good geological disaster prediction capabilities.
To improve the accuracy of quantitative precipitation products derived from regional satellite observations, the level 1 radiation observation products, level 2 cloud detection products, and level 2 quantitative precipitation estimation operational products from the FY-4B geostationary radiation imager AGRI (Advanced Geosynchronous Radiation Imager), and national rain gauge observations collected between June 1 and July 31, 2022, in China were utilized in this study. The random forest algorithm was employed to establish separate models for predicting the presence or absence of rainfall and estimating rainfall amounts during the day and at night. The importance of 15 channels from the AGRI level 1 radiation observations was evaluated, and suitable channels for determining and estimating ground rainfall during the day and night were selected. Judgment and retrieval models based on these optimal channels were then created. Finally, using the models based on their respective optimal channels, precipitation for August 2022 was estimated and compared with the FY-4B AGRI level 2 quantitative precipitation estimation operational products. The results are as follows: (1) Channels 7 and 8 in the mid-wave infrared range were of lower importance during the day, and the daytime judgment and retrieval models did not use these channels. However, the nighttime models employed all infrared channels, and the retrieval precipitation closely matched the national gauge observations. (2) The optimal channel judgment models for both day and night outperformed the FY-4B precipitation operational products in identifying whether precipitation occurred, particularly showing a significant improvement in hit rates. Nevertheless, rainfall retrieval from both optimal channel retrieval models tended to overestimate rainfall amounts, with daytime retrieval precipitation being more accurate than nighttime. (3) The errors of rainfall retrieval from both daytime and nighttime optimal channel models were both lower than those from the FY-4B precipitation operational products. Both the precipitation operational products and the two optimal channel model estimates tended to overestimate light rainfall and underestimate heavy rainfall, with the underestimation becoming more severe as precipitation intensity increased. (4) For the retrieval of different precipitation magnitudes using optimal channel models, improvements in root mean square errors were observed for nearly all levels of rainfall except for nighttime heavy rain, with the most significant accuracy enhancement seen in the small to moderate rainfall range.
The initial section of the Arctic Northeast Passage is located in the Yellow Sea and Bohai Sea of China. The severe weather types that may threaten the safety of shipping in this area are mainly strong winds and heavy precipitation. Among them the cold air gale accompanied by the cold wave process, as well as the disastrous weather such as strong wind and heavy precipitation caused by weather systems such as tropical cyclones and extratropical cyclones, have a great impact on shipping safety in this area. Based on the National Centers for Environmental Prediction (NCEP) global daily reanalysis data from 1991 to 2020, we analyze the energy propagation characteristics of the Rossby wave along the upper-level jet stream during the seaworthiness period (July to October) of the Arctic Northeast Passage and its impact on the weather in the initial section of the Arctic Northeast Passage, especially on heavy precipitation. The results are as follows. (1) The meridional wind along the 250 hPa westerly jet axis in the subtropical region of the Northern Hemisphere shows a zonal three-wave quasi-stationary Rossby wave pattern. (2) The atmospheric quasi-stationary Rossby wave source at 250 hPa is located in the Mediterranean region. The wave is excited here and propagates eastward along the jet stream. Although the wave energy is dissipated during the propagation process, continuous input of energy from the Mediterranean region maintains and strengthens the wave. (3) The absolute value of the correlation coefficient between the key area of the wave action flux divergence and the precipitation and wind speed in the initial section of the Arctic Northeast Passage is greater than 0.5. While the absolute value of the correlation coefficient between the key area wave action flux index and the precipitation and wind speed is close to 0.9, indicating a strong correlation, it shows that the energy of the Rossby wave is concentrated and strengthened when it propagates along the upper jet stream, significantly influencing the precipitation and wind speed in the initial section of the Northeast Passage of the Arctic, thus triggering disastrous weather such as heavy precipitation and strong winds. (4) When the Rossby wave disturbance is stronger, the downstream propagation energy is also stronger. The westerly jet is then strengthened, and the vertical upward motion is enhanced. This results in an abnormal increase in precipitation in the initial section of the Arctic Northeast Passage.
The Sichuan Basin is one of the most severely air-polluted regions in China. To study the scavenging effect of precipitation on PM2.5 and PM10 in Sichuan Basin, the PM2.5 and PM10 mass concentration data from 90 environmental monitoring stations and observation data from 17 ground meteorological stations in Sichuan Basin from 2016 to 2021 were used. First, the effects of precipitation on the spatial distribution of PM2.5 and PM10 in the Sichuan Basin were analyzed. Then, the influence of precipitation intensity and duration on PM2.5 and PM10 removal effects was revealed based on the removal rates of aerosol particle mass concentration changes before and after precipitation. Finally, by calculating the removal coefficients using the raindrop spectral distribution, raindrop sizes, and end-of-fall velocities, the removal effects of precipitation on four PM2.5 and PM10 pollution events in the Sichuan Basin were investigated. The results are as follows: (1) In the Sichuan Basin, precipitation affects the spatial distribution of PM2.5 and PM10. The greater the precipitation amounts and the longer the duration of precipitation, the greater the removal rates and the more significant the scavenging effect. (2) In cases of heavy rainfall, removal rates are not sensitive to increases in precipitation duration when it exceeds 6 hours. (3) When the raindrop diameter, the total number of raindrops, and the minute rain intensity peak, and the raindrop spectra broaden and intensify, rapid decreases of PM2.5 and PM10 mass concentrations occur. (4) The removal coefficients are indicative of variations in PM2.5 and PM10 mass concentrations. When the peak removal coefficients are above 10 h-1, the scavenging effect of precipitation on PM2.5 and PM10 is significant.
