Data from rain Drop Size Distributions gathered on five sites in Africa as well as those of the pilot site in Kourou (French Guyana, South America), located in different climatic zones, and collected by two types of d...Data from rain Drop Size Distributions gathered on five sites in Africa as well as those of the pilot site in Kourou (French Guyana, South America), located in different climatic zones, and collected by two types of disdrometer (the impact JW RD-69 disdrometer and the Optical Spectro-Pluviometer, OSP) are used to study the consistency of the reflectivity factor-rain rate at the ground (Z-R) relationship variability. The results clearly confirm that the relationship Z-R knows a large spatial variability, from a type of precipitation to another and within the same precipitation regardless the type of disdrometer used for DSD measurements. Base on the similarity of the relations reflectivity factor-rain rate and ratio median volume diameter over the total number of drops-rain rate, the variability of the Z-R coefficients (A, b) through the simultaneously implication of the size and number of drops which characterize the DSD was exhibited. It was shown that the relationships A-α and b-β designed to understand the involvement of parameters D0 and NT of DSD in the variability of the relationship Z-R are similar regardless the types of disdrometer used. However, the relations A-α in the Sahelian region appear to deviate from those of Guinean, equatorial and Soudanian zones. The plausible reasons were discussed.展开更多
Seasonal variations of rainfall microphysics in East China are investigated using data from the observations of a twodimensional video disdrometer and a vertically pointing micro rain radar. The precipitation and rain...Seasonal variations of rainfall microphysics in East China are investigated using data from the observations of a twodimensional video disdrometer and a vertically pointing micro rain radar. The precipitation and rain drop size distribution(DSD) characteristics are revealed for different rain types and seasons. Summer rainfall is dominated by convective rain,while during the other seasons the contribution of stratiform rain to rainfall amount is equal to or even larger than that of convective rain. The mean mass-weighted diameter versus the generalized intercept parameter pairs of convective rain are plotted roughly around the "maritime" cluster, indicating a maritime nature of convective precipitation throughout the year in East China. The localized rainfall estimators, i.e., rainfall kinetic energy–rain rate, shape–slope, and radar reflectivity–rain rate relations are further derived. DSD variability is believed to be a major source of diversity of the aforementioned derived estimators. These newly derived relations would certainly improve the accuracy of rainfall kinetic energy estimation, DSD retrieval, and quantitative precipitation estimation in this specific region.展开更多
To analyze the effects of gas cannons on clouds and precipitation,multisource observational data,including those from National Centers for Environmental Prediction(NCEP)reanalysis,Hangzhou and Huzhou new-generation we...To analyze the effects of gas cannons on clouds and precipitation,multisource observational data,including those from National Centers for Environmental Prediction(NCEP)reanalysis,Hangzhou and Huzhou new-generation weather radars,laser disdrometer,ground-based automatic weather station,wind profiler radar,and Lin'an C-band dualpolarization radar,were adopted in this study.Based on the variational dual-Doppler wind retrieval method and the polarimetric variables obtained by the dual-polarization radar,we analyzed the microphysical processes and the variations in the macro-and microphysical quantities in clouds from the perspective of the synoptic background before precipitation enhancement,the polarization echo characteristics before,during and after enhancement,and the evolution of the fine three-dimensional kinematic structure and the microphysical structure.The results show that the precipitation enhancement operation promoted the development of radar echoes and prolonged their duration,and both the horizontal and vertical wind speeds increased.The dual-polarization radar echo showed that the diameter of the precipitation particles increased,and the concentration of raindrops increased after precipitation enhancement.The raindrops were lifted to a height corresponding to 0 to-20℃due to vertical updrafts.Based on the disdrometer data during precipitation enhancement,the concentration of small raindrops(lgN_(w))showed a significant increase,and the mass-weighted diameter D_(m)value decreased,indicating that the precipitation enhancement operation played a certain“lubricating”effect.After the precipitation enhancement,the concentration of raindrops did not change much compared with that during the enhancement process,while the Dm increased,corresponding to an increase in rain intensity.The results suggest the positive effect of gas cannons on precipitation enhancement.展开更多
The effects of various precipitation types,such as snow,rain,sleet,hail and freezing rain,on regional hydrology,ecology,snow and ice surfaces differ significantly.Due to limited observations,however,few studies into p...The effects of various precipitation types,such as snow,rain,sleet,hail and freezing rain,on regional hydrology,ecology,snow and ice surfaces differ significantly.Due to limited observations,however,few studies into precipitation types have been conducted in the Arctic.Based on the high-resolution precipitation records from an OTT Parsivel^(2) disdrometer in Utqiaġvik,Alaska,this study analysed variations in precipitation types in the Alaskan Arctic from 15 May to 16 October,2019.Results show that rain and snow were the dominant precipitation types during the measurement period,accounting for 92%of the total precipitation.In addition,freezing rain,sleet,and hail were also observed(2,4 and 11 times,respectively),accounting for the rest part of the total precipitation.The records from a neighbouring U.S.Climate Reference Network(USCRN)station equipped with T-200B rain gauges support the results of disdrometer.Further analysis revealed that Global Precipitation Measurement(GPM)satellite data could well characterise the observed precipitation changes in Utqiaġvik.Combined with satellite data and station observations,the spatiotemporal variations in precipitation were verified in various reanalysis datasets,and the results indicated that ECMWF Reanalysis v5(ERA5)could better describe the observed precipitation time series in Utqiaġvik and the spatial distribution of data in the Alaskan Arctic.Modern-Era Retrospective analysis for Research and Applications,Version 2(MERRA-2)overestimated the amount and frequency of precipitation.Japanese 55-year Reanalysis(JRA-55)could better simulate heavy precipitation events and the spatial distribution of the precipitation phase,but it overestimated summer snowfall.展开更多
During the April-June raining season,warm-sector heavy rainfall(WR) and frontal heavy rainfall(FR) often occur in the south of China,causing natural disasters.In this study,the microphysical characteristics of WR and ...During the April-June raining season,warm-sector heavy rainfall(WR) and frontal heavy rainfall(FR) often occur in the south of China,causing natural disasters.In this study,the microphysical characteristics of WR and FR events from 2016 to 2022 are analyzed by using 2-dimensional video disdrometer(2DVD) data in the south of China.The microphysical characteristics of WR and FR events are quite different.Compared with FR events,WR events have higher concentration of D<5.3 mm(especially D <1 mm),leading to higher rain rates.The mean values of Dmand lgNwof WR events are higher than that of FR events.The microphysical characteristics in different rain rate classes(C1:R~5-20 mm h-1,C2:R~20-50 mm h-1,C3:R~50-100 mm h^(-1),and C4:R> 100 mm h^(-1)) for WR and FR events are also different.Raindrops from C3 contribute the most to the precipitation of WR events,and raindrops from C2 contribute the most to the precipitation of FR events.For C2 and C3,compared with FR events,WR events have higher concentration of D <1 mm and D~3-4.5 mm.Moreover,the shape and slope(μ-A) relationships and the radar reflectivity and rain rate(Z-R) relationships of WR and FR events are quite different in each rain rate class.The investigation of the difference in microphysical characteristics between WR and FR events provide useful information for radar-based quantitative precipitation estimation and numerical prediction.展开更多
Freezing rain(FZR)presents significant risks to energy,transportation,and agriculture,leading to substantial economiclossesandcasualties,particularlyinsouthwestern,central,andeasternChina,withonlyoccasionaloccurrences...Freezing rain(FZR)presents significant risks to energy,transportation,and agriculture,leading to substantial economiclossesandcasualties,particularlyinsouthwestern,central,andeasternChina,withonlyoccasionaloccurrences in northern China.This study investigates an extreme,large-scale FZR event that occurred during 8–9 November 2021 in Heilongjiang Province of Northeast China,marking the region’s most intense FZR since 1958.Surface station observations revealed distinct characteristics of the FZR,and the stations were classified into three types by using the k-means clustering:stations with continuous FZR(FZR_Con),stations with FZR of mixed hydrometeor types(FZR_Mix),and stations with FZR transitioning to rain(FZR_Rain).Vertical atmospheric temperature and humidity profiles significantly influenced the raindrop size distribution(DSD)for the three station types.All three station types exhibited an inversion layer in the upper atmosphere,though they formed through two distinct mechanisms:(1)the supercooled warm rain mechanism and(2)the melting mechanism.This study found that the massweighted mean diameters(D--m)were larger than those observed in FZR events in central China and in stratiform rain in northern and northwestern China.FZR_Mix,which formed through the supercooled warm rain mechanism,exhibited the largest D_(m) among the three types.In contrast,FZR_Con and FZR_Rain formed through the melting mechanism,involving the melting of ice crystals and snow particles.The drier refreezing layer in FZR_Rain,compared to FZR_Con,resulted in a lower normalized number concentration(N_(w))and a larger D_(m).Positive exponential relationships between D_(m) and R(precipitation rate),as well as N_(w) and R,across all FZR types,highlighting dominant role of microphysical processes such as collision and coalescence.Variations in the gamma distribution parameters—shape(μ)and slope(λ)—as well as in the radar Z–R relationships among the FZR types further underscore differences in the microphysical processes and regional precipitation characteristics.This study enhances our understanding of the macro-and microphysical properties of FZR formed through different mechanisms,providing valuable reference for improved radar-based precipitation estimation in mid-and high-latitude regions.展开更多
Raindrop size distribution(DSD)is crucial in the study of precipitation microphysics,but the parameters that characterize the DSD is not easy to be derived accurately.Wind profile radar(WPR)provides rich data with hig...Raindrop size distribution(DSD)is crucial in the study of precipitation microphysics,but the parameters that characterize the DSD is not easy to be derived accurately.Wind profile radar(WPR)provides rich data with high spatiotemporal resolution and low attenuation,and the previous studies using WPR power spectral distribution to extract DSD parameters demonstrate certain limitations.In this study,a WPR-based Gamma DSD parameter estimation network(WPR-DSDnet)combined with a neural network(NN)and a long short-term memory(LSTM)network is designed,and then a WPR-DSDnet-based model is trained to retrieve the Gamma DSD parameters including normalized intercept parameter(N_(w))and mass-weighted average diameter(D_(m))by means of the high-resolution WPR reflectivity factor and velocity spectral width as the inputs,and the spatiotemporal matching disdrometer data collected from 2017 to 2021 in Beijing as labels.Two precipitation cases are used to validate the performance of the model,and the results demonstrate that the model can retrieve the Gamma DSD parameters effectively,in which the ratio between the estimated and measured values of both lg N_(w)and D_(m)exceeds 99%.The estimation accuracy of lg N_(w)is slightly better than that of D_(m)due to smaller relative deviation of lg N_(w)although the absolute deviation between the estimated and true values of lg N_(w)is larger than that of D_(m),which are probably caused by the larger distribution range of lg N_(w).The vertical distributions of lg N_(w)closely aligns with variations in precipitation intensity,which hints it is a useful indicator for precipitation intensity change.On the other hand,the distribution of D_(m)is closely associated with the degree of convection,which is valuable for precipitation recognition and classification.The two parameters extracted by the deep learning-based model can facilitate further in-depth analysis on precipitation characteristics and mechanisms with WPR data.展开更多
In this study, significant rainfall microphysical variability is revealed for the extremely heavy rainfall event over Henan Province in July 2021(the “21·7” Henan EHR event) using a dense network of disdrometer...In this study, significant rainfall microphysical variability is revealed for the extremely heavy rainfall event over Henan Province in July 2021(the “21·7” Henan EHR event) using a dense network of disdrometers and two polarimetric radars.The broad distributions of specific drop size distribution(DSD) parameters are identified in heavy rainfall from the disdrometer observations, indicating obvious microphysical variability on the surface. A K-means clustering algorithm is adopted to objectively classify the disdrometer datasets into separate groups, and distinct DSD characteristics are found among these heavy rainfall groups. Combined with the supporting microphysical structures obtained through radar observations, comprehensive microphysical features of the DSD groups are derived. An extreme rainfall group is dominantly formed in the deep convection over the plain regions, where the high number of concentrations and large mean sizes of surface raindrops are underpinned by both active ice-phase processes and efficient warm-rain collision-coalescence processes in the vertical direction. Convection located near orographic regions is characterized by restricted ice-phase processes and high coalescence efficiency of liquid hydrometeors, causing the dominant DSD group to comprise negligible large raindrops. Multiple DSD groups can coexist within certain precipitation episodes at the disdrometer stations, indicating the potential microphysical variability during the passage of convective system on the plain regions.展开更多
The evolution of the microphysical properties of raindrops from Typhoon Mangkhut’s outer rainbands as the storm made landfall in South China in September 2018 was investigated.The observations by three two-dimensiona...The evolution of the microphysical properties of raindrops from Typhoon Mangkhut’s outer rainbands as the storm made landfall in South China in September 2018 was investigated.The observations by three two-dimensional video disdrometers deployed in central Guangdong Province were analyzed concurrently.It was found that the radial distribution of the median volume diameter(D_(0))and normalized intercept parameter(N_(w))varied in different stages,and that raindrops smaller than 3.0 mm contributed more than 99%of the total precipitation.Considering the characteristics of precipitation in the typhoon outer rainband,a modified stratiform rain(SR)-convective rain(CR)separator line is proposed based on D_(0) and N_(w) scatterplots.Meanwhile,an“S-C likelihood index”is introduced,which was used to classify three rain types(SR,CR,and mixed rain).The CR results were highly consistent with those of the improved typhoon precipitation classification method based on rain rate.By calculating effectively the radar reflectivity factor(Ze)in the Ku and Ka bands,D0-Ze and N_(w)-D_(0) empirical relations were thereby derived for improving the accuracy of rainfall retrieval.Among the four quantitative precipitation estimators using S-band dual-polarimetric radar parameters simulated by the T-matrix method,the estimator that adopted the specific differential phase and differential reflectivity was found to be the most effective for both SR and CR.展开更多
文摘Data from rain Drop Size Distributions gathered on five sites in Africa as well as those of the pilot site in Kourou (French Guyana, South America), located in different climatic zones, and collected by two types of disdrometer (the impact JW RD-69 disdrometer and the Optical Spectro-Pluviometer, OSP) are used to study the consistency of the reflectivity factor-rain rate at the ground (Z-R) relationship variability. The results clearly confirm that the relationship Z-R knows a large spatial variability, from a type of precipitation to another and within the same precipitation regardless the type of disdrometer used for DSD measurements. Base on the similarity of the relations reflectivity factor-rain rate and ratio median volume diameter over the total number of drops-rain rate, the variability of the Z-R coefficients (A, b) through the simultaneously implication of the size and number of drops which characterize the DSD was exhibited. It was shown that the relationships A-α and b-β designed to understand the involvement of parameters D0 and NT of DSD in the variability of the relationship Z-R are similar regardless the types of disdrometer used. However, the relations A-α in the Sahelian region appear to deviate from those of Guinean, equatorial and Soudanian zones. The plausible reasons were discussed.
基金primarily supported by the National Key Research and Development Program of China(Grant No.2017YFC1501703)the National Natural Science Foundation of China(Grant Nos.41875053,41475015 and 41322032)+1 种基金the National Fundamental Research 973 Program of China(Grant Nos.2013CB430101 and 2015CB452800)collected by a National 973 Project(Grant No.2013CB430101)
文摘Seasonal variations of rainfall microphysics in East China are investigated using data from the observations of a twodimensional video disdrometer and a vertically pointing micro rain radar. The precipitation and rain drop size distribution(DSD) characteristics are revealed for different rain types and seasons. Summer rainfall is dominated by convective rain,while during the other seasons the contribution of stratiform rain to rainfall amount is equal to or even larger than that of convective rain. The mean mass-weighted diameter versus the generalized intercept parameter pairs of convective rain are plotted roughly around the "maritime" cluster, indicating a maritime nature of convective precipitation throughout the year in East China. The localized rainfall estimators, i.e., rainfall kinetic energy–rain rate, shape–slope, and radar reflectivity–rain rate relations are further derived. DSD variability is believed to be a major source of diversity of the aforementioned derived estimators. These newly derived relations would certainly improve the accuracy of rainfall kinetic energy estimation, DSD retrieval, and quantitative precipitation estimation in this specific region.
基金National Natural Science Foundation of China(41675029)Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX18_0998)+1 种基金Science and Technology Program of Huzhou(2021GZ14,2020GZ31)Science and Technology(Key)Program of Zhejiang Meteorological Service(2021ZD27)。
文摘To analyze the effects of gas cannons on clouds and precipitation,multisource observational data,including those from National Centers for Environmental Prediction(NCEP)reanalysis,Hangzhou and Huzhou new-generation weather radars,laser disdrometer,ground-based automatic weather station,wind profiler radar,and Lin'an C-band dualpolarization radar,were adopted in this study.Based on the variational dual-Doppler wind retrieval method and the polarimetric variables obtained by the dual-polarization radar,we analyzed the microphysical processes and the variations in the macro-and microphysical quantities in clouds from the perspective of the synoptic background before precipitation enhancement,the polarization echo characteristics before,during and after enhancement,and the evolution of the fine three-dimensional kinematic structure and the microphysical structure.The results show that the precipitation enhancement operation promoted the development of radar echoes and prolonged their duration,and both the horizontal and vertical wind speeds increased.The dual-polarization radar echo showed that the diameter of the precipitation particles increased,and the concentration of raindrops increased after precipitation enhancement.The raindrops were lifted to a height corresponding to 0 to-20℃due to vertical updrafts.Based on the disdrometer data during precipitation enhancement,the concentration of small raindrops(lgN_(w))showed a significant increase,and the mass-weighted diameter D_(m)value decreased,indicating that the precipitation enhancement operation played a certain“lubricating”effect.After the precipitation enhancement,the concentration of raindrops did not change much compared with that during the enhancement process,while the Dm increased,corresponding to an increase in rain intensity.The results suggest the positive effect of gas cannons on precipitation enhancement.
基金This study is funded by the National Key Research and Development Program of China(Grant no.2018YFC1406103)the National Nature Science Foundation of China(Grant no.NSFC 41971084).
文摘The effects of various precipitation types,such as snow,rain,sleet,hail and freezing rain,on regional hydrology,ecology,snow and ice surfaces differ significantly.Due to limited observations,however,few studies into precipitation types have been conducted in the Arctic.Based on the high-resolution precipitation records from an OTT Parsivel^(2) disdrometer in Utqiaġvik,Alaska,this study analysed variations in precipitation types in the Alaskan Arctic from 15 May to 16 October,2019.Results show that rain and snow were the dominant precipitation types during the measurement period,accounting for 92%of the total precipitation.In addition,freezing rain,sleet,and hail were also observed(2,4 and 11 times,respectively),accounting for the rest part of the total precipitation.The records from a neighbouring U.S.Climate Reference Network(USCRN)station equipped with T-200B rain gauges support the results of disdrometer.Further analysis revealed that Global Precipitation Measurement(GPM)satellite data could well characterise the observed precipitation changes in Utqiaġvik.Combined with satellite data and station observations,the spatiotemporal variations in precipitation were verified in various reanalysis datasets,and the results indicated that ECMWF Reanalysis v5(ERA5)could better describe the observed precipitation time series in Utqiaġvik and the spatial distribution of data in the Alaskan Arctic.Modern-Era Retrospective analysis for Research and Applications,Version 2(MERRA-2)overestimated the amount and frequency of precipitation.Japanese 55-year Reanalysis(JRA-55)could better simulate heavy precipitation events and the spatial distribution of the precipitation phase,but it overestimated summer snowfall.
基金National key research and development program of China(2022YFC3003902)National Natural Science Foundation of China(U2242203,42075086,41975138)Guangdong Basic and Applied Basic Research Foundation(2023A1515011971,2021A1515011415,2019A1515010814)。
文摘During the April-June raining season,warm-sector heavy rainfall(WR) and frontal heavy rainfall(FR) often occur in the south of China,causing natural disasters.In this study,the microphysical characteristics of WR and FR events from 2016 to 2022 are analyzed by using 2-dimensional video disdrometer(2DVD) data in the south of China.The microphysical characteristics of WR and FR events are quite different.Compared with FR events,WR events have higher concentration of D<5.3 mm(especially D <1 mm),leading to higher rain rates.The mean values of Dmand lgNwof WR events are higher than that of FR events.The microphysical characteristics in different rain rate classes(C1:R~5-20 mm h-1,C2:R~20-50 mm h-1,C3:R~50-100 mm h^(-1),and C4:R> 100 mm h^(-1)) for WR and FR events are also different.Raindrops from C3 contribute the most to the precipitation of WR events,and raindrops from C2 contribute the most to the precipitation of FR events.For C2 and C3,compared with FR events,WR events have higher concentration of D <1 mm and D~3-4.5 mm.Moreover,the shape and slope(μ-A) relationships and the radar reflectivity and rain rate(Z-R) relationships of WR and FR events are quite different in each rain rate class.The investigation of the difference in microphysical characteristics between WR and FR events provide useful information for radar-based quantitative precipitation estimation and numerical prediction.
基金Supported by the Hubei Provincial Natural Science Foundation and Meteorological Innovation and Development Project of China(2023AFD096,2022CFD122,and 2023AFD100)Science and Technology Development Fund of Hubei Meteorological Bureau(2023Y18)+3 种基金Qinghai Province 2023 Key R&D and Transformation Plan(2023-SF-111)Special Program for Innovation and Development of China Meteorological Administration(CXFZ2022J010)Natural Science Foundation of Wuhan(2024020901030454)CMA Meteorological Observation Centre Field Experiment Project in 2024(GCSYJH24-30)。
文摘Freezing rain(FZR)presents significant risks to energy,transportation,and agriculture,leading to substantial economiclossesandcasualties,particularlyinsouthwestern,central,andeasternChina,withonlyoccasionaloccurrences in northern China.This study investigates an extreme,large-scale FZR event that occurred during 8–9 November 2021 in Heilongjiang Province of Northeast China,marking the region’s most intense FZR since 1958.Surface station observations revealed distinct characteristics of the FZR,and the stations were classified into three types by using the k-means clustering:stations with continuous FZR(FZR_Con),stations with FZR of mixed hydrometeor types(FZR_Mix),and stations with FZR transitioning to rain(FZR_Rain).Vertical atmospheric temperature and humidity profiles significantly influenced the raindrop size distribution(DSD)for the three station types.All three station types exhibited an inversion layer in the upper atmosphere,though they formed through two distinct mechanisms:(1)the supercooled warm rain mechanism and(2)the melting mechanism.This study found that the massweighted mean diameters(D--m)were larger than those observed in FZR events in central China and in stratiform rain in northern and northwestern China.FZR_Mix,which formed through the supercooled warm rain mechanism,exhibited the largest D_(m) among the three types.In contrast,FZR_Con and FZR_Rain formed through the melting mechanism,involving the melting of ice crystals and snow particles.The drier refreezing layer in FZR_Rain,compared to FZR_Con,resulted in a lower normalized number concentration(N_(w))and a larger D_(m).Positive exponential relationships between D_(m) and R(precipitation rate),as well as N_(w) and R,across all FZR types,highlighting dominant role of microphysical processes such as collision and coalescence.Variations in the gamma distribution parameters—shape(μ)and slope(λ)—as well as in the radar Z–R relationships among the FZR types further underscore differences in the microphysical processes and regional precipitation characteristics.This study enhances our understanding of the macro-and microphysical properties of FZR formed through different mechanisms,providing valuable reference for improved radar-based precipitation estimation in mid-and high-latitude regions.
基金Supported by the Beijing Natural Science Foundation(8242029)Beijing Municipal Science and Technology Commission(Z221100005222016)+1 种基金Science&Technology Plan Project of Fujian Province(2021L3019)Open Grants of the State Key Laboratory of Severe Weather(2023LASW-B02)。
文摘Raindrop size distribution(DSD)is crucial in the study of precipitation microphysics,but the parameters that characterize the DSD is not easy to be derived accurately.Wind profile radar(WPR)provides rich data with high spatiotemporal resolution and low attenuation,and the previous studies using WPR power spectral distribution to extract DSD parameters demonstrate certain limitations.In this study,a WPR-based Gamma DSD parameter estimation network(WPR-DSDnet)combined with a neural network(NN)and a long short-term memory(LSTM)network is designed,and then a WPR-DSDnet-based model is trained to retrieve the Gamma DSD parameters including normalized intercept parameter(N_(w))and mass-weighted average diameter(D_(m))by means of the high-resolution WPR reflectivity factor and velocity spectral width as the inputs,and the spatiotemporal matching disdrometer data collected from 2017 to 2021 in Beijing as labels.Two precipitation cases are used to validate the performance of the model,and the results demonstrate that the model can retrieve the Gamma DSD parameters effectively,in which the ratio between the estimated and measured values of both lg N_(w)and D_(m)exceeds 99%.The estimation accuracy of lg N_(w)is slightly better than that of D_(m)due to smaller relative deviation of lg N_(w)although the absolute deviation between the estimated and true values of lg N_(w)is larger than that of D_(m),which are probably caused by the larger distribution range of lg N_(w).The vertical distributions of lg N_(w)closely aligns with variations in precipitation intensity,which hints it is a useful indicator for precipitation intensity change.On the other hand,the distribution of D_(m)is closely associated with the degree of convection,which is valuable for precipitation recognition and classification.The two parameters extracted by the deep learning-based model can facilitate further in-depth analysis on precipitation characteristics and mechanisms with WPR data.
基金jointly supported by the National Natural Science Foundation of China (Grant Nos. 42025501, 42005009, 41875053, U2142203)the National Key Research and Development Program of China (Grant No. 2017YFC1501703)+1 种基金the Basic Research Fund of CAMS (Grant No. 2021Z003)the Open Research Program of the State Key Laboratory of Severe Weather (Grant No. 2020LASW-A01)。
文摘In this study, significant rainfall microphysical variability is revealed for the extremely heavy rainfall event over Henan Province in July 2021(the “21·7” Henan EHR event) using a dense network of disdrometers and two polarimetric radars.The broad distributions of specific drop size distribution(DSD) parameters are identified in heavy rainfall from the disdrometer observations, indicating obvious microphysical variability on the surface. A K-means clustering algorithm is adopted to objectively classify the disdrometer datasets into separate groups, and distinct DSD characteristics are found among these heavy rainfall groups. Combined with the supporting microphysical structures obtained through radar observations, comprehensive microphysical features of the DSD groups are derived. An extreme rainfall group is dominantly formed in the deep convection over the plain regions, where the high number of concentrations and large mean sizes of surface raindrops are underpinned by both active ice-phase processes and efficient warm-rain collision-coalescence processes in the vertical direction. Convection located near orographic regions is characterized by restricted ice-phase processes and high coalescence efficiency of liquid hydrometeors, causing the dominant DSD group to comprise negligible large raindrops. Multiple DSD groups can coexist within certain precipitation episodes at the disdrometer stations, indicating the potential microphysical variability during the passage of convective system on the plain regions.
基金Supported by the National Key Research and Development Program of China (2018YFC1507905)National Natural Science Foundation of China (41675136 and 41875170)+3 种基金National Undergraduate Innovation and Entrepreneurship Training Program (201910300040Z)Opening Project of Key Laboratory for Aerosol–Cloud–Precipitation of China Meteorological Administration (KDW1405)Natural Science Foundation of Guangdong Province of China-Major Basic Research and Cultivation Projects (2015A030308014)Guangxi Key Research and Development Program (AB20159013)
文摘The evolution of the microphysical properties of raindrops from Typhoon Mangkhut’s outer rainbands as the storm made landfall in South China in September 2018 was investigated.The observations by three two-dimensional video disdrometers deployed in central Guangdong Province were analyzed concurrently.It was found that the radial distribution of the median volume diameter(D_(0))and normalized intercept parameter(N_(w))varied in different stages,and that raindrops smaller than 3.0 mm contributed more than 99%of the total precipitation.Considering the characteristics of precipitation in the typhoon outer rainband,a modified stratiform rain(SR)-convective rain(CR)separator line is proposed based on D_(0) and N_(w) scatterplots.Meanwhile,an“S-C likelihood index”is introduced,which was used to classify three rain types(SR,CR,and mixed rain).The CR results were highly consistent with those of the improved typhoon precipitation classification method based on rain rate.By calculating effectively the radar reflectivity factor(Ze)in the Ku and Ka bands,D0-Ze and N_(w)-D_(0) empirical relations were thereby derived for improving the accuracy of rainfall retrieval.Among the four quantitative precipitation estimators using S-band dual-polarimetric radar parameters simulated by the T-matrix method,the estimator that adopted the specific differential phase and differential reflectivity was found to be the most effective for both SR and CR.
