Volume 51,Issue 3,2023 Table of Contents
2023, 51(3):309-318.
DOI: 10.19517/j.1671-6345.20220418
Abstract:
Due to the differences in the system design of aerosol lidar, climate conditions in the observation site, parameters selection in retrieval and other factors, the quality of retrieved aerosol optical properties from each measurement is inconsistent, and its reliability is difficult to evaluate, which greatly affects the operational application in meteorology, environmental protection, and other fields. In order to solve this problem, we analyze the factors that affect the quality reliability of retrieved aerosol optical properties and develop a set of quality reliability assessment algorithms. A scientific and reasonable scoring combined with a weight allocation method is used to evaluate the quality reliability of retrieved aerosol optical properties from each measurement. This study mainly discusses the quality reliability assessment of retrieved aerosol optical properties of polarization Mie scattering lidar. The 532 nm polarization Mie scattering lidars of the Meteorological Observation Centre, China Meteorological Administration, are taken as examples to verify and analyze the proposed quality reliability assessment algorithm. The results show that the algorithm can effectively distinguish the quality reliability of retrieved aerosol optical properties from each measurement of each lidar in different observation scenarios and possesses the ability to provide the reliability assessment for the operational application of aerosol lidar.
Due to the differences in the system design of aerosol lidar, climate conditions in the observation site, parameters selection in retrieval and other factors, the quality of retrieved aerosol optical properties from each measurement is inconsistent, and its reliability is difficult to evaluate, which greatly affects the operational application in meteorology, environmental protection, and other fields. In order to solve this problem, we analyze the factors that affect the quality reliability of retrieved aerosol optical properties and develop a set of quality reliability assessment algorithms. A scientific and reasonable scoring combined with a weight allocation method is used to evaluate the quality reliability of retrieved aerosol optical properties from each measurement. This study mainly discusses the quality reliability assessment of retrieved aerosol optical properties of polarization Mie scattering lidar. The 532 nm polarization Mie scattering lidars of the Meteorological Observation Centre, China Meteorological Administration, are taken as examples to verify and analyze the proposed quality reliability assessment algorithm. The results show that the algorithm can effectively distinguish the quality reliability of retrieved aerosol optical properties from each measurement of each lidar in different observation scenarios and possesses the ability to provide the reliability assessment for the operational application of aerosol lidar.
2023, 51(3):319-330.
DOI: 10.19517/j.1671-6345.20220370
Abstract:
High-resolution weather radar data can reveal the fine structure of detected weather targets and are essential for catastrophic weather analysis, forecasting and warning. Improving weather radar reflectivity data resolution can enhance the monitoring and warning capability of existing operational weather radar for small-and-medium-scale strong convective disastrous weather. In this paper, based on an attention back-projection network (ABPN), the super-resolution reconstruction algorithm is proposed to improve the resolution of weather radar reflectivity data without radar hardware modification. The attentional back-projection network is accomplished by adding long and short skip connections in the deep back-projection network (DBPN) and channel attention mechanism to refine and reconstruct structural features in critical regions. By testing the superresolution reconstruction on real weather processes, it is demonstrated that the ABPN algorithm has significant advantages in radar echo reconstruction quality and subjective visual evaluation, especially in terms of echo details and edge structure features of weather radar.
High-resolution weather radar data can reveal the fine structure of detected weather targets and are essential for catastrophic weather analysis, forecasting and warning. Improving weather radar reflectivity data resolution can enhance the monitoring and warning capability of existing operational weather radar for small-and-medium-scale strong convective disastrous weather. In this paper, based on an attention back-projection network (ABPN), the super-resolution reconstruction algorithm is proposed to improve the resolution of weather radar reflectivity data without radar hardware modification. The attentional back-projection network is accomplished by adding long and short skip connections in the deep back-projection network (DBPN) and channel attention mechanism to refine and reconstruct structural features in critical regions. By testing the superresolution reconstruction on real weather processes, it is demonstrated that the ABPN algorithm has significant advantages in radar echo reconstruction quality and subjective visual evaluation, especially in terms of echo details and edge structure features of weather radar.
2023, 51(3):331-337.
DOI: 10.19517/j.1671-6345.20220325
Abstract:
In order to generate highquality radar echo images in complex environments and reduce the phenomenon of target information loss and relative imaging error, a radar echo image generation method based on small and mediumscale strong convection weather is proposed. The Fourier interpolation method, which can retain the radar echo characteristics to the maximum extent, is used to form the 3D regular grid data of radar echo with uniform spatial resolution. Based on the improved variational Bayesian theory, the radar echo image of small-and-medium-scale convective weather radar is super-resolved and generated. The experimental results show that the radar echo range of the medium-small scale strong convection weather radar processed by this method is highly similar to the original image. The radar echo information can be retained to the maximum extent. This method can generate clear radar echo images; there is no lack of target information; and the relative imaging error is very small.
In order to generate highquality radar echo images in complex environments and reduce the phenomenon of target information loss and relative imaging error, a radar echo image generation method based on small and mediumscale strong convection weather is proposed. The Fourier interpolation method, which can retain the radar echo characteristics to the maximum extent, is used to form the 3D regular grid data of radar echo with uniform spatial resolution. Based on the improved variational Bayesian theory, the radar echo image of small-and-medium-scale convective weather radar is super-resolved and generated. The experimental results show that the radar echo range of the medium-small scale strong convection weather radar processed by this method is highly similar to the original image. The radar echo information can be retained to the maximum extent. This method can generate clear radar echo images; there is no lack of target information; and the relative imaging error is very small.
2023, 51(3):338-345.
Abstract:
To address the problem of large bias in the quantitative estimation of heavy precipitation by traditional methods using weather radar, the thesis uses the 1-hour cumulative rainfall as the estimation object, a new model for radar precipitation estimation based on radar mosaic data and XGBoost (eXtreme Gradient Boosting) algorithm. The model is designed with the radar combined reflectance factor of the previous hour as the input factor, and further employs several rejection strategies of anomalous samples to effectively remove some of the noise from the modelling samples, thus better constructing a non-linear mapping relationship between the radar combined reflectance and the estimated object. The root mean square error (RMSE) is 6.04 mm, the mean absolute error (MAE) is 3.50 mm, and the forecast bias (BIAS) is 1.05 for the 320,000 independently tested samples; compared to the Z-R(300,1.4) relational method currently used on operational systems, the RMSE and MAE of the former decrease by 20.6% and 10.3% respectively, while the BIAS indicators show a significant underestimation of precipitation magnitude by the latter. For samples with hourly rainfall intensity greater than 10 mm, further statistical results show that the new scheme’s RMSE, MAE and TS scores are substantially better than the Z-R (300,1.4) relational method for practical operational applications.
To address the problem of large bias in the quantitative estimation of heavy precipitation by traditional methods using weather radar, the thesis uses the 1-hour cumulative rainfall as the estimation object, a new model for radar precipitation estimation based on radar mosaic data and XGBoost (eXtreme Gradient Boosting) algorithm. The model is designed with the radar combined reflectance factor of the previous hour as the input factor, and further employs several rejection strategies of anomalous samples to effectively remove some of the noise from the modelling samples, thus better constructing a non-linear mapping relationship between the radar combined reflectance and the estimated object. The root mean square error (RMSE) is 6.04 mm, the mean absolute error (MAE) is 3.50 mm, and the forecast bias (BIAS) is 1.05 for the 320,000 independently tested samples; compared to the Z-R(300,1.4) relational method currently used on operational systems, the RMSE and MAE of the former decrease by 20.6% and 10.3% respectively, while the BIAS indicators show a significant underestimation of precipitation magnitude by the latter. For samples with hourly rainfall intensity greater than 10 mm, further statistical results show that the new scheme’s RMSE, MAE and TS scores are substantially better than the Z-R (300,1.4) relational method for practical operational applications.
2023, 51(3):346-355.
DOI: 10.19517/j.1671-6345.20220470
Abstract:
Aiming at the characteristics of complex terrain and the variety of radar types in Sichuan Province, this paper designs an algorithm for evaluating the quality of single or dual-polarization weather radar data over a long period of time. The algorithm qualitatively evaluates whether the weather radar data have the error of Empty Echo, electromagnetic interference or ground object clutters, and quantitatively evaluates the data quality of reflectivity factor (Zh), differential reflectivity (Zdr), coefficient of correlation (CC), differential phase shift (φdp) and ground object clutter (GC). By evaluating the data quality of 12 new-generation weather radars in Sichuan Province from May to September 2022, the following results are obtained: (1) The weather radar in Sichuan Province is affected by electromagnetic interference, which seriously affects the data quality. More than 74% of the Yibin and Guangyuan radar data have electromagnetic interference echoes. The data of Yibin and Leshan radar stations have many error data of “Empty Echo”. More than 77.9% of the Guangyuan radar data have ground object echo interference that is caused by wind turbines. (2) If the radar performance is normal, the mean value of the ground object clutter coefficient GC does not change much. The standard deviation of GC coefficient can effectively reflect the problem of radar data, especially the problem of “Empty Echo” data. (3) The standard deviation of Zh in the 12 weather radars in Sichuan Province is generally small, and the standard deviation of Zh in Ya’an, Kangding and Guangyuan stations is better than that of others. (4) The quality of Zdr and CC data of 3 dual-polarization weather radars in Sichuan Province is optimum, but the data quality of φdp is poor.
Aiming at the characteristics of complex terrain and the variety of radar types in Sichuan Province, this paper designs an algorithm for evaluating the quality of single or dual-polarization weather radar data over a long period of time. The algorithm qualitatively evaluates whether the weather radar data have the error of Empty Echo, electromagnetic interference or ground object clutters, and quantitatively evaluates the data quality of reflectivity factor (Zh), differential reflectivity (Zdr), coefficient of correlation (CC), differential phase shift (φdp) and ground object clutter (GC). By evaluating the data quality of 12 new-generation weather radars in Sichuan Province from May to September 2022, the following results are obtained: (1) The weather radar in Sichuan Province is affected by electromagnetic interference, which seriously affects the data quality. More than 74% of the Yibin and Guangyuan radar data have electromagnetic interference echoes. The data of Yibin and Leshan radar stations have many error data of “Empty Echo”. More than 77.9% of the Guangyuan radar data have ground object echo interference that is caused by wind turbines. (2) If the radar performance is normal, the mean value of the ground object clutter coefficient GC does not change much. The standard deviation of GC coefficient can effectively reflect the problem of radar data, especially the problem of “Empty Echo” data. (3) The standard deviation of Zh in the 12 weather radars in Sichuan Province is generally small, and the standard deviation of Zh in Ya’an, Kangding and Guangyuan stations is better than that of others. (4) The quality of Zdr and CC data of 3 dual-polarization weather radars in Sichuan Province is optimum, but the data quality of φdp is poor.
2023, 51(3):356-365.
DOI: 10.19517/j.1671-6345.20220381
Abstract:
Phased-array weather radars have a significant advantage over new-generation weather radars in terms of spatial and temporal resolution. With the improvement of detection capability, the amount of phased-array radars data grows sharply, thus raising data transmission and storage problems. Existing weather radar data compression algorithms may reduce the amount of data transmitted and stored, and yet common data compression algorithms fail to consider the characteristics of phased-array radars sufficiently. This paper proposes a space-time predictive phased-array radar data compression algorithm (PARDC) to compress the redundancy associated with phased-array radar data using radial prediction to achieve efficient lossless compression. The algorithm performance of PARDC is evaluated using CHARTOR radar data, with experimental results showing that PARDC improves the compression rate performance by approximately 24% over the common compression algorithm.
Phased-array weather radars have a significant advantage over new-generation weather radars in terms of spatial and temporal resolution. With the improvement of detection capability, the amount of phased-array radars data grows sharply, thus raising data transmission and storage problems. Existing weather radar data compression algorithms may reduce the amount of data transmitted and stored, and yet common data compression algorithms fail to consider the characteristics of phased-array radars sufficiently. This paper proposes a space-time predictive phased-array radar data compression algorithm (PARDC) to compress the redundancy associated with phased-array radar data using radial prediction to achieve efficient lossless compression. The algorithm performance of PARDC is evaluated using CHARTOR radar data, with experimental results showing that PARDC improves the compression rate performance by approximately 24% over the common compression algorithm.
2023, 51(3):366-373.
DOI: 10.19517/j.1671-6345.20220427
Abstract:
The fault prediction and diagnosis of the new generation weather radar have always been a technical challenge for radar operation and maintenance. The delayed response to some severe faults will lead to aggravated damage to the corresponding components of the radar. In this paper, based on the combination of artificial intelligence technology and radar data characteristics, a SA radar transmitter system fault warning and determination method based on the adaptive threshold is proposed. An algorithm framework for transmitter fault online monitoring based on a reconstruction model is established. The algorithm framework can identify anomalies and warn early when radar transmitter failures occur. The actual operation records are used for calculation and analysis, verifying the method’s effectiveness.
The fault prediction and diagnosis of the new generation weather radar have always been a technical challenge for radar operation and maintenance. The delayed response to some severe faults will lead to aggravated damage to the corresponding components of the radar. In this paper, based on the combination of artificial intelligence technology and radar data characteristics, a SA radar transmitter system fault warning and determination method based on the adaptive threshold is proposed. An algorithm framework for transmitter fault online monitoring based on a reconstruction model is established. The algorithm framework can identify anomalies and warn early when radar transmitter failures occur. The actual operation records are used for calculation and analysis, verifying the method’s effectiveness.
2023, 51(3):374-380.
DOI: 10.19517/j.1671-6345.20220369
Abstract:
Using USB 3.0 hubs and synthesis instruments, highly integrated RF transceiver hardware, and combined with open and scalable software, the automatic testing of S-band, C-band, and X-band weather radars is realized. The system software adopts a “layered mode” architecture, which integrates the test process with the business model to realize standardized and automated testing. By comparing the measurement of the transmitter’s output pulse envelope and limit improvement factor, the integrated platform has higher test accuracy, no manual recording and calculation are required, and the judgment of radar performance is more accurate, which solves the limitations of a single radar system test platform and support platform, and improves the test efficiency and agility of the national multi-band weather radar system.
Using USB 3.0 hubs and synthesis instruments, highly integrated RF transceiver hardware, and combined with open and scalable software, the automatic testing of S-band, C-band, and X-band weather radars is realized. The system software adopts a “layered mode” architecture, which integrates the test process with the business model to realize standardized and automated testing. By comparing the measurement of the transmitter’s output pulse envelope and limit improvement factor, the integrated platform has higher test accuracy, no manual recording and calculation are required, and the judgment of radar performance is more accurate, which solves the limitations of a single radar system test platform and support platform, and improves the test efficiency and agility of the national multi-band weather radar system.
2023, 51(3):381-387.
Abstract:
The fault of the new generation of weather radar directly affects the data quality. The generation of abnormal products has a great impact on the shorttime approaching forecast and early warning. It is of certain practical significance to realize the realtime monitoring of radar abnormal products. This system uses the WinForm threelayer architecture and ORM model architecture through statistical texture analysis, grey image feature value analysis and other image processing technology to realize automatic recognition of radar abnormal products. The new generation of weather radar product fault monitoring and warning system can detect abnormal radar products in realtime, efficiently and accurately, and meet the functional requirements of severe convection weather warning and monitoring, weather radar fault warning service prediction, weather radar product availability service, and identify abnormal echoes from the data of a single radar product. It is of great significance for the quality control of weather radar networking products to avoid further influencing the multiradar networking puzzle.
The fault of the new generation of weather radar directly affects the data quality. The generation of abnormal products has a great impact on the shorttime approaching forecast and early warning. It is of certain practical significance to realize the realtime monitoring of radar abnormal products. This system uses the WinForm threelayer architecture and ORM model architecture through statistical texture analysis, grey image feature value analysis and other image processing technology to realize automatic recognition of radar abnormal products. The new generation of weather radar product fault monitoring and warning system can detect abnormal radar products in realtime, efficiently and accurately, and meet the functional requirements of severe convection weather warning and monitoring, weather radar fault warning service prediction, weather radar product availability service, and identify abnormal echoes from the data of a single radar product. It is of great significance for the quality control of weather radar networking products to avoid further influencing the multiradar networking puzzle.
2023, 51(3):388-396.
DOI: 10.19517/j.1671-6345.20220399
Abstract:
Based on the radar composite reflectivity factor data and thunderstorm gale observation data in North China from 2013 to 2017, a total of 27 strong squall line processes are identified, and their spatial and temporal distribution, development and movement characteristics are statistically analyzed. The results show that the most concentrated months of the strong squall lines are from late July to early August in North China, and the strongest hours are concentrated from 16:00 to 22:00. Most initial 40 dBz echo locations are near the junction of Shanxi, Inner Mongolia and Hebei. Most strong squall lines are formed in Beijing, Tianjin and Hebei. The area from eastern Shanxi Province to western Hebei Province is the concentrated area of the strong squall lines, with the longest length of more than 400 km and a maintenance duration of more than 7 hours. The strong squall lines with an initial echo time of 02:00-07:59 have the longest average formation duration, while those with an initial echo time of 14:00-19:59 have the shortest average formation duration. There is good correspondence between the longest length of the strong squall lines and their development and maintenance duration. The strong squall lines with an initial echo time of 14:00-19:59 move a short distance in the formation period but a long distance in the development period, while the strong squall lines with an initial echo time of 02:00-07:59 are opposite. Most of the strong squall lines move faster in the development period than in the formation period.
Based on the radar composite reflectivity factor data and thunderstorm gale observation data in North China from 2013 to 2017, a total of 27 strong squall line processes are identified, and their spatial and temporal distribution, development and movement characteristics are statistically analyzed. The results show that the most concentrated months of the strong squall lines are from late July to early August in North China, and the strongest hours are concentrated from 16:00 to 22:00. Most initial 40 dBz echo locations are near the junction of Shanxi, Inner Mongolia and Hebei. Most strong squall lines are formed in Beijing, Tianjin and Hebei. The area from eastern Shanxi Province to western Hebei Province is the concentrated area of the strong squall lines, with the longest length of more than 400 km and a maintenance duration of more than 7 hours. The strong squall lines with an initial echo time of 02:00-07:59 have the longest average formation duration, while those with an initial echo time of 14:00-19:59 have the shortest average formation duration. There is good correspondence between the longest length of the strong squall lines and their development and maintenance duration. The strong squall lines with an initial echo time of 14:00-19:59 move a short distance in the formation period but a long distance in the development period, while the strong squall lines with an initial echo time of 02:00-07:59 are opposite. Most of the strong squall lines move faster in the development period than in the formation period.
2023, 51(3):397-408.
DOI: 10.19517/j.1671-6345.20220415
Abstract:
Based on the detection data of CINRAD/SA-D dualpolarization weather radar in Jinan and the field survey data of tornado, the evolution process of radar echo, the structure of tornado cell, mesocyclone (M), tornadic vortex signature (TVS) and tornadic debris signature (TDS) of a class EF3 tornado storm in Gaotang, Liaocheng, Shandong Province, on July 11, 2021, are analyzed. The results show that: (1) The tornado, which was located about 200 km northeast of the surface cyclone centre, occurred under the weather situation of the common effect of the upper cold vortex and the surface cyclone. The two strong convective cells in the spiral convective cloud zone merged and developed into a supercell storm. The downdraft behind the supercell was strong, which together with the strong inflow, induced a strong tornado. (2) The top heights of mesocyclones in storms were mostly between 5 and 7 km; the average maximum shear of mesocyclone before the tornado was 19×10-3 s-1; during the tornado maintenance period, the average maximum shear value of mesocyclone reached 51×10-3 s-1. (3) The main characteristics of the dual polarization parameters of the bottom layer of the Gaotang tornado vortex were large horizontal polarization reflectivity factor, small or even negative ZDR and small CC; the temporal and spatial characteristics of TDS were that the bottom CC was less than 0.7, the area of the low CC value area increased significantly with time after the tornado formation, and the bottom CC value was the minimum, increased gradually with height; the area of the low-value area of CC was larger in the lower and top layers, and smaller in the middle layer; the maximum height of TDS gradually increased with time after the tornado formation, and the maximum height of TDS reached 4.8 km when the tornado was strongest, and then decreased gradually; after the tornado dissipating, the TDS characteristics above 1.5° disappeared quickly, and the TDS characteristics at 0.5° elevation continued to maintain for about 11 minutes.
Based on the detection data of CINRAD/SA-D dualpolarization weather radar in Jinan and the field survey data of tornado, the evolution process of radar echo, the structure of tornado cell, mesocyclone (M), tornadic vortex signature (TVS) and tornadic debris signature (TDS) of a class EF3 tornado storm in Gaotang, Liaocheng, Shandong Province, on July 11, 2021, are analyzed. The results show that: (1) The tornado, which was located about 200 km northeast of the surface cyclone centre, occurred under the weather situation of the common effect of the upper cold vortex and the surface cyclone. The two strong convective cells in the spiral convective cloud zone merged and developed into a supercell storm. The downdraft behind the supercell was strong, which together with the strong inflow, induced a strong tornado. (2) The top heights of mesocyclones in storms were mostly between 5 and 7 km; the average maximum shear of mesocyclone before the tornado was 19×10-3 s-1; during the tornado maintenance period, the average maximum shear value of mesocyclone reached 51×10-3 s-1. (3) The main characteristics of the dual polarization parameters of the bottom layer of the Gaotang tornado vortex were large horizontal polarization reflectivity factor, small or even negative ZDR and small CC; the temporal and spatial characteristics of TDS were that the bottom CC was less than 0.7, the area of the low CC value area increased significantly with time after the tornado formation, and the bottom CC value was the minimum, increased gradually with height; the area of the low-value area of CC was larger in the lower and top layers, and smaller in the middle layer; the maximum height of TDS gradually increased with time after the tornado formation, and the maximum height of TDS reached 4.8 km when the tornado was strongest, and then decreased gradually; after the tornado dissipating, the TDS characteristics above 1.5° disappeared quickly, and the TDS characteristics at 0.5° elevation continued to maintain for about 11 minutes.
2023, 51(3):409-418.
DOI: 10.19517/j.1671-6345.20220395
Abstract:
Based on the conventional meteorological data, ERA5 reanalysis data and Doppler radar data, a heavy hail weather process in northwestern Hebei Province on June 10, 2022, is analyzed. The results show that: (1) The hail occurred in the southeast quadrant of the cold vortex and the warm area in front of the low-level shear line. The convection was triggered by the local thermal factor and strengthened near the surface convergence line. (2) The hail process could be divided into three stages. The first two stages were formed by two different supercells, respectively. The identification results of hydrometeor were mainly dry hail particles. The radar echoes were characterized by high reflectivity, low differential reflectivity, high correlation coefficient and low differential phase. In the third stage, two supercells merged and formed. Besides hail, local flash rain also occurred. The flash rain was caused by large raindrops of larger diameter and more numerous. (3) The wind field retrieved by radar could be used to analyze the dynamic structure of convection cells, and the future moving direction and development trend of cells could be obtained by analyzing the dynamic structure of cells in different stages. In particular, the strength of updraft in the vertical profile had important indicative significance for the development trend of monomers.
Based on the conventional meteorological data, ERA5 reanalysis data and Doppler radar data, a heavy hail weather process in northwestern Hebei Province on June 10, 2022, is analyzed. The results show that: (1) The hail occurred in the southeast quadrant of the cold vortex and the warm area in front of the low-level shear line. The convection was triggered by the local thermal factor and strengthened near the surface convergence line. (2) The hail process could be divided into three stages. The first two stages were formed by two different supercells, respectively. The identification results of hydrometeor were mainly dry hail particles. The radar echoes were characterized by high reflectivity, low differential reflectivity, high correlation coefficient and low differential phase. In the third stage, two supercells merged and formed. Besides hail, local flash rain also occurred. The flash rain was caused by large raindrops of larger diameter and more numerous. (3) The wind field retrieved by radar could be used to analyze the dynamic structure of convection cells, and the future moving direction and development trend of cells could be obtained by analyzing the dynamic structure of cells in different stages. In particular, the strength of updraft in the vertical profile had important indicative significance for the development trend of monomers.
2023, 51(3):419-430.
DOI: 10.19517/j.1671-6345.20220396
Abstract:
Using the data of Guangzhou S-band dual-polarization radar and X-band phased array radar, we analyze the radar observation characteristics of a supercell on March 26, 2022. The results show that this supercell showed classical structural features such as hook echo, drape echo, and three-body scatter signature (TBSS). Other structures, such as low-level convergence, upper-level divergence, mesocyclone and anticyclones, contributed to the maintenance of the supercell. Analysis of the polarization features shows that the differential reflectivity (ZDR) arc appeared in the low layer of the supercell, and the high reflectivity corresponded to low ZDR, low correlation coefficient (CC) and high specific differential phase (KDP), which conformed to the characteristics of melting hail. The polarization characteristics of the ZDR ring, CC ring and TBSS were observed in the middle layer. The high-rise strong-echo regions corresponded to low ZDR, higher CC, and low KDP, helping to identify large hail. The ZDR and the KDP columns were observed in the vertical direction, and the maximum development height of the ZDR column reached 8 km. The KDP column could reflect changes in the region of the supercell containing large amounts of liquid water droplets, and the KDP foot could identify the region where the heavy precipitation was located. The faster scanning speed of X-band phased array radar could finely monitor the formation and evolution of supercell hook echo and mesocyclones. ZDR arc and melting hail features were also observed at low layers with patterns similar to those by S-band dual-polarization radar, but the effects of attenuation should be dealt with with caution.
Using the data of Guangzhou S-band dual-polarization radar and X-band phased array radar, we analyze the radar observation characteristics of a supercell on March 26, 2022. The results show that this supercell showed classical structural features such as hook echo, drape echo, and three-body scatter signature (TBSS). Other structures, such as low-level convergence, upper-level divergence, mesocyclone and anticyclones, contributed to the maintenance of the supercell. Analysis of the polarization features shows that the differential reflectivity (ZDR) arc appeared in the low layer of the supercell, and the high reflectivity corresponded to low ZDR, low correlation coefficient (CC) and high specific differential phase (KDP), which conformed to the characteristics of melting hail. The polarization characteristics of the ZDR ring, CC ring and TBSS were observed in the middle layer. The high-rise strong-echo regions corresponded to low ZDR, higher CC, and low KDP, helping to identify large hail. The ZDR and the KDP columns were observed in the vertical direction, and the maximum development height of the ZDR column reached 8 km. The KDP column could reflect changes in the region of the supercell containing large amounts of liquid water droplets, and the KDP foot could identify the region where the heavy precipitation was located. The faster scanning speed of X-band phased array radar could finely monitor the formation and evolution of supercell hook echo and mesocyclones. ZDR arc and melting hail features were also observed at low layers with patterns similar to those by S-band dual-polarization radar, but the effects of attenuation should be dealt with with caution.
2023, 51(3):431-440.
DOI: 10.19517/j.1671-6345.20220259
Abstract:
Using satellite data, radar data, lightning data and NCEP reanalysis data, taking a large-scale strong convective process in Hubei Province on March 16, 2022 as an example, the observation characteristics of convective systems at two different positions during the movement of the southwest vortex ars analyzed. The results show that the eastward movement of the southwest vortex in front of the trough was the main influence system of the strong convection. The wind and hail weather in eastern Hubei mainly occurred at the top of the low vortex and the warm shear line, while the cold shear line in the southern part of the low vortex induced the southern convection. In this case, the TBB gradually dropped below 220 K in the early stage of convective development, and the maximum local TBB variability could reach -30 ℃ in the next one. Most of the lightning strikes were close to the right side of the TBB≤220 K cumulus and the centre and edge of the large TBB variability area. The lightning on the right side of the convective system was a good indicator of the development and movement of the convective system. The area of cumulus clouds with TBB≤210 K reached the maximum in the mature stage, and the TBB variability decreased in the next hour. The dense lightning strikes were distributed in the middle of the cumulus cloud cluster and moved with the low TBB area. The vertical profile of the radar reflectivity factor presented a right-tilt structure, and the righttilt feature was more evident in the convective development stage. The lightning was located on the right front side of the convective system and was consistent with the strong echo of ≥45 dBz; the combined reflectivity area of ≥45 dBz and ≥50 dBz, and the echo top areas of ≥10 km and≥12 km were positively correlated with the evolution of convective systems. The positive and negative ground lightning peaks appeared 0 to 18 minutes earlier than wind and hail. The first peak value of negative ground lightning significantly impacted wind and hail, and the advance amount could reach 18 minutes.
Using satellite data, radar data, lightning data and NCEP reanalysis data, taking a large-scale strong convective process in Hubei Province on March 16, 2022 as an example, the observation characteristics of convective systems at two different positions during the movement of the southwest vortex ars analyzed. The results show that the eastward movement of the southwest vortex in front of the trough was the main influence system of the strong convection. The wind and hail weather in eastern Hubei mainly occurred at the top of the low vortex and the warm shear line, while the cold shear line in the southern part of the low vortex induced the southern convection. In this case, the TBB gradually dropped below 220 K in the early stage of convective development, and the maximum local TBB variability could reach -30 ℃ in the next one. Most of the lightning strikes were close to the right side of the TBB≤220 K cumulus and the centre and edge of the large TBB variability area. The lightning on the right side of the convective system was a good indicator of the development and movement of the convective system. The area of cumulus clouds with TBB≤210 K reached the maximum in the mature stage, and the TBB variability decreased in the next hour. The dense lightning strikes were distributed in the middle of the cumulus cloud cluster and moved with the low TBB area. The vertical profile of the radar reflectivity factor presented a right-tilt structure, and the righttilt feature was more evident in the convective development stage. The lightning was located on the right front side of the convective system and was consistent with the strong echo of ≥45 dBz; the combined reflectivity area of ≥45 dBz and ≥50 dBz, and the echo top areas of ≥10 km and≥12 km were positively correlated with the evolution of convective systems. The positive and negative ground lightning peaks appeared 0 to 18 minutes earlier than wind and hail. The first peak value of negative ground lightning significantly impacted wind and hail, and the advance amount could reach 18 minutes.
2023, 51(3):441-453.
DOI: 10.19517/j.1671-6345.20220410
Abstract:
Based on conventional observation data, encrypted data from automatic stations, radiosonde data, ERA5 reanalysis data, and Doppler weather radar data, a severe convective weather process affecting the coast of northern Zhejiang on April 30, 2021, is analyzed. The results show that: (1) This process occurred in the background of the highaltitude cold vortex and the strong northwest jet behind its trough. The lowaltitude shear line and the surface convergence line jointly provided the triggering conditions for uplift. (2) Appropriate CIN, relatively low LFC, and high CAPE were conducive to the formation of unstable stratification with cold upper and warm lower layers. Deep vertical wind shear combined with dry air entrainment in the middle layer further enabled the occurrence, maintenance, and development of severe convective weather. (3) The development of this gust front had gone through three stages. When the thunderstorm’s main body generated a gust front that developed strongly and caused strong winds on the ground, there were characteristics such as a rapid drop in the height of the strong echo centre, a strong inflow in the rear middle layer, a radial velocity divergence field, and velocity ambiguity. (4) The sinking of a strong cold air pile formed a dense area of pressure gradient and wind temperature and humidity shear, which could easily lead to thunderstorms and gale weather. The negative and positive temperature variation centres had certain indications for strong convection. (5) During the transit of gust fronts, there was often an abrupt increase in atmospheric pressure and wind speed, sudden change in wind direction, and sudden drop in temperature. Due to the limitations of radar observation distance, forecasters needed to analyze the potential in the early stage and jointly studied and judged the automatic station elements and radar information.
Based on conventional observation data, encrypted data from automatic stations, radiosonde data, ERA5 reanalysis data, and Doppler weather radar data, a severe convective weather process affecting the coast of northern Zhejiang on April 30, 2021, is analyzed. The results show that: (1) This process occurred in the background of the highaltitude cold vortex and the strong northwest jet behind its trough. The lowaltitude shear line and the surface convergence line jointly provided the triggering conditions for uplift. (2) Appropriate CIN, relatively low LFC, and high CAPE were conducive to the formation of unstable stratification with cold upper and warm lower layers. Deep vertical wind shear combined with dry air entrainment in the middle layer further enabled the occurrence, maintenance, and development of severe convective weather. (3) The development of this gust front had gone through three stages. When the thunderstorm’s main body generated a gust front that developed strongly and caused strong winds on the ground, there were characteristics such as a rapid drop in the height of the strong echo centre, a strong inflow in the rear middle layer, a radial velocity divergence field, and velocity ambiguity. (4) The sinking of a strong cold air pile formed a dense area of pressure gradient and wind temperature and humidity shear, which could easily lead to thunderstorms and gale weather. The negative and positive temperature variation centres had certain indications for strong convection. (5) During the transit of gust fronts, there was often an abrupt increase in atmospheric pressure and wind speed, sudden change in wind direction, and sudden drop in temperature. Due to the limitations of radar observation distance, forecasters needed to analyze the potential in the early stage and jointly studied and judged the automatic station elements and radar information.
External LinksChina Meteorological AdministrationCMA Meteorological Observation CentreChinese Academy of Meteorological SciencesBeijing Meteorological ServiceNational Satellite Meteorological Center
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Supported by:Beijing E-Tiller Technology Development Co., Ltd.
Supported by:Beijing E-Tiller Technology Development Co., Ltd.