Volume 49,Issue 3,2021 Table of Contents
1 Application of Cluster Analysis in Hydrometeor Identification Based on X-Band Dual-Polarized Radar
2021, 49(3):315-321.
Abstract:
XBand DualPolarized radar has great advantages in precipitation hydrometeor identification. At present, the commonly used method is the fuzzy logic algorithm, which has better recognition ability. This method mainly depends on the membership function of the hydrometeor but it needs to adjust the suitable membership function for the aging problem of different radar sets. To solve this problem, this paper proposes the method of cluster analysis for precipitation phasestate recognition. After the phasestate recognition, the distribution of different radar parameters can be counted as the suitable membership function for the radar. The cluster analysis method performs well in the hydrometeor identification experiment, but there are still some problems. Some hydrometeor cannot be identified without the introduction of temperature, which is described.
XBand DualPolarized radar has great advantages in precipitation hydrometeor identification. At present, the commonly used method is the fuzzy logic algorithm, which has better recognition ability. This method mainly depends on the membership function of the hydrometeor but it needs to adjust the suitable membership function for the aging problem of different radar sets. To solve this problem, this paper proposes the method of cluster analysis for precipitation phasestate recognition. After the phasestate recognition, the distribution of different radar parameters can be counted as the suitable membership function for the radar. The cluster analysis method performs well in the hydrometeor identification experiment, but there are still some problems. Some hydrometeor cannot be identified without the introduction of temperature, which is described.
2021, 49(3):322-327.
Abstract:
The Lidar visibility meter is an effective means to detect atmospheric visibility, but its return signals are weak and easy to be interfered by various noises. In order to improve the accuracy of visibility inversion, the suppressing background noise and extracting useful signals from it are very important. The empirical mode decomposition algorithm is used to decompose and reconstruct the return signals, which achieves good denoising effect. The simulation results show that the empirical mode decomposition algorithm improves the output signal noise rate of return signals effectively and reduces the root mean square error. By processing several groups of measured data under different weather conditions, such as sunny, cloudy, and fog days, the inversion results are compared with the measurement results of atmospheric transmittance LT31, which further verifies the effectiveness of the algorithm.
The Lidar visibility meter is an effective means to detect atmospheric visibility, but its return signals are weak and easy to be interfered by various noises. In order to improve the accuracy of visibility inversion, the suppressing background noise and extracting useful signals from it are very important. The empirical mode decomposition algorithm is used to decompose and reconstruct the return signals, which achieves good denoising effect. The simulation results show that the empirical mode decomposition algorithm improves the output signal noise rate of return signals effectively and reduces the root mean square error. By processing several groups of measured data under different weather conditions, such as sunny, cloudy, and fog days, the inversion results are compared with the measurement results of atmospheric transmittance LT31, which further verifies the effectiveness of the algorithm.
2021, 49(3):328-335.
Abstract:
Piezoelectric ultrasonic windspeed sensors have higher accuracy and reliability than traditional mechanical wind instruments. However, in practical application, the outdoor climatic environment in some areas is complicated, and it will affect the radiated sound field emitted by the ultrasonic transducer in severe weather. The COMSOL finite element analysis software is used to simulate the sound field distribution of the piezoelectric transducer in the radiusspherical region. The boundary conditions of the transducer and air coupling are used to simulate the heavy rains and sandstorms in severe weather conditions, and the sound pressure and sound pressure level of the transducer sound field are compared in several cases. The results show that heavy rains have little effect on the ultrasonic radiation sound field. With the increase of dust concentration, the attenuation of ultrasonic signal becomes more obvious. The simulation results provide a reference and basis for the technical improvement of ultrasonic wind speed sensors in severe weather.
Piezoelectric ultrasonic windspeed sensors have higher accuracy and reliability than traditional mechanical wind instruments. However, in practical application, the outdoor climatic environment in some areas is complicated, and it will affect the radiated sound field emitted by the ultrasonic transducer in severe weather. The COMSOL finite element analysis software is used to simulate the sound field distribution of the piezoelectric transducer in the radiusspherical region. The boundary conditions of the transducer and air coupling are used to simulate the heavy rains and sandstorms in severe weather conditions, and the sound pressure and sound pressure level of the transducer sound field are compared in several cases. The results show that heavy rains have little effect on the ultrasonic radiation sound field. With the increase of dust concentration, the attenuation of ultrasonic signal becomes more obvious. The simulation results provide a reference and basis for the technical improvement of ultrasonic wind speed sensors in severe weather.
2021, 49(3):336-341.
Abstract:
In order to determine the position of the fixed point of the new jig fastening piece and ensure that the blockage ratio is reduced to the minimum and the wind cup group is also in the optimal uniform field, on the basis of testing the optimal uniformity region of the test wind field, the threedimensional model of the threecup anemometer is established by using CAD, and the maximum frontal area in the rotation process of the threecup anemometer was calculated. Finally, the blockage effect test experiment is carried out to verify it. The results show that the error of the traditional estimation is corrected by calculating the frontal area based on CAD, and the blockage ratio of the optimized test wind field is 0.04, which is reduced by 42%, and the indicated wind speed of the test wind field and the indicated wind speed of the free wind field are almost the same.
In order to determine the position of the fixed point of the new jig fastening piece and ensure that the blockage ratio is reduced to the minimum and the wind cup group is also in the optimal uniform field, on the basis of testing the optimal uniformity region of the test wind field, the threedimensional model of the threecup anemometer is established by using CAD, and the maximum frontal area in the rotation process of the threecup anemometer was calculated. Finally, the blockage effect test experiment is carried out to verify it. The results show that the error of the traditional estimation is corrected by calculating the frontal area based on CAD, and the blockage ratio of the optimized test wind field is 0.04, which is reduced by 42%, and the indicated wind speed of the test wind field and the indicated wind speed of the free wind field are almost the same.
2021, 49(3):342-347.
Abstract:
The FY4 geostationary meteorological satellite gets its orbit determination and prediction through ranging the distances from different ground stations to the satellite, so the coordinates of each station site are one of main factors which influence the accuracy of the orbit determination. The satelliteground distance is the distance from the antenna phase center of a ground station to that of the satellite in general, but the antenna phase center of the FY4 ranging station antenna cannot be used to determine the starting reference point of the ranging distance and site coordinate measuring point. On the basis of the theory of the Cassegrain antenna, the following are discussed: where the starting point of ranging is and how to fix the point of coordinates to measure in the condition of the special structure of the antenna. The correction algorithm is given from coordinate measurement point to the ranging start point. Taking the FY4B antenna for an example, the result of correction is analyzed according to the actual condition that five ground stations follow the satellites distributed in seven different sites of space. Finally, suggestions are provided for practical application.
The FY4 geostationary meteorological satellite gets its orbit determination and prediction through ranging the distances from different ground stations to the satellite, so the coordinates of each station site are one of main factors which influence the accuracy of the orbit determination. The satelliteground distance is the distance from the antenna phase center of a ground station to that of the satellite in general, but the antenna phase center of the FY4 ranging station antenna cannot be used to determine the starting reference point of the ranging distance and site coordinate measuring point. On the basis of the theory of the Cassegrain antenna, the following are discussed: where the starting point of ranging is and how to fix the point of coordinates to measure in the condition of the special structure of the antenna. The correction algorithm is given from coordinate measurement point to the ranging start point. Taking the FY4B antenna for an example, the result of correction is analyzed according to the actual condition that five ground stations follow the satellites distributed in seven different sites of space. Finally, suggestions are provided for practical application.
2021, 49(3):348-354.
Abstract:
Meteorological satellites are an important national infrastructure, which have been heavily invested and have a huge potential benefit nationalwide. The evaluation of socialeconomic benefits becomes more important since it answers the significant questions of why should more public resources located in meteorological satellite systems, and how valuable is their applications. A framework of benefit evaluation for meteorological satellites is established. This framework contains two parts: one is the contribution of meteorological satellite data to meteorological services, and the other is the benefit directly from the application of satellite data and products. To be specific, a contribution rate is adopted from the related researches and reports in the first part, while the other part covers all the benefits of direct satellite data applications which are quantitatively or qualitatively evaluated. The preliminary evaluation of the total benefits from meteorological satellite application is from 33.55×109 to 84.66×109 RMB in 2012 in China. Further comparison to those of the United States (US) and the European Union (EU) reveals that the benefits of China and US are relatively close, while both are much smaller than that of EU. However, the costbenefit ratio of China is higher than that of EU. The difference in the methods and scales of evaluation is the main cause. Thus, a consensus in the methods of evaluation should be reached among all the operational meteorological systems as soon as possible. It will better guide the development of the Chinese Fengyun meteorological satellite system and improve its efficiency.
Meteorological satellites are an important national infrastructure, which have been heavily invested and have a huge potential benefit nationalwide. The evaluation of socialeconomic benefits becomes more important since it answers the significant questions of why should more public resources located in meteorological satellite systems, and how valuable is their applications. A framework of benefit evaluation for meteorological satellites is established. This framework contains two parts: one is the contribution of meteorological satellite data to meteorological services, and the other is the benefit directly from the application of satellite data and products. To be specific, a contribution rate is adopted from the related researches and reports in the first part, while the other part covers all the benefits of direct satellite data applications which are quantitatively or qualitatively evaluated. The preliminary evaluation of the total benefits from meteorological satellite application is from 33.55×109 to 84.66×109 RMB in 2012 in China. Further comparison to those of the United States (US) and the European Union (EU) reveals that the benefits of China and US are relatively close, while both are much smaller than that of EU. However, the costbenefit ratio of China is higher than that of EU. The difference in the methods and scales of evaluation is the main cause. Thus, a consensus in the methods of evaluation should be reached among all the operational meteorological systems as soon as possible. It will better guide the development of the Chinese Fengyun meteorological satellite system and improve its efficiency.
2021, 49(3):355-361.
Abstract:
This study conducts the spatial interpolation analysis of the temperature and precipitation of 38 years across the country, and selects the optimal model to generate a 1 km grid dataset to provide support for the researches on vegetation distribution, climate change and environmental ecology in mainland China. Based on the daily temperature data and precipitation data from 839 meteorological stations of the National Meteorological Center, using longitude, latitude and altitude as the three variables interpolated by the ANUSPLIN software, the square root pretreatment of precipitation is carried out, and with the thin disk smooth spline method of the thirdorder spline, the 1 km grid interpolation dataset of monthly average temperature and monthly cumulative precipitation in mainland China from 1980 to 2017 is obtained. The square root of Generalized CrossValidation and RootMeanSquare Error (RMSE) of this dataset have the characteristics of annual periodicity and obvious seasonal variation. The frequency distribution of the Mean Bias Error (MBE) of each station is close to the normal distribution, and the spatial distribution of the Mean Absolute Error (MAE) is also consistent with the changing characteristics of the climate of mainland China. The dataset is relatively new in accuracy and time series and is available for public download, which can provide information support for the study of the national terrestrial ecosystem.
This study conducts the spatial interpolation analysis of the temperature and precipitation of 38 years across the country, and selects the optimal model to generate a 1 km grid dataset to provide support for the researches on vegetation distribution, climate change and environmental ecology in mainland China. Based on the daily temperature data and precipitation data from 839 meteorological stations of the National Meteorological Center, using longitude, latitude and altitude as the three variables interpolated by the ANUSPLIN software, the square root pretreatment of precipitation is carried out, and with the thin disk smooth spline method of the thirdorder spline, the 1 km grid interpolation dataset of monthly average temperature and monthly cumulative precipitation in mainland China from 1980 to 2017 is obtained. The square root of Generalized CrossValidation and RootMeanSquare Error (RMSE) of this dataset have the characteristics of annual periodicity and obvious seasonal variation. The frequency distribution of the Mean Bias Error (MBE) of each station is close to the normal distribution, and the spatial distribution of the Mean Absolute Error (MAE) is also consistent with the changing characteristics of the climate of mainland China. The dataset is relatively new in accuracy and time series and is available for public download, which can provide information support for the study of the national terrestrial ecosystem.
2021, 49(3):362-371.
Abstract:
Based on the mesoscale WRF (Weather Research and Forecast) model, NCEP/NCAR reanalysis data and conventional meteorological observation data, the main moving process of the Kunming QuasiStationary Front （KQSF） from 22 to 24 January 2016 is simulated and sensitive tests are conducted to study the influencing factors of the KQSF movement. The results show that the WRF model successfully simulates the moving process of KQSF and the position of the front westward. When the height of the terrain increases by 1.2 times, the speed of the Kunming quasistatic front moving westward slows down, and the time for the front to cross the highest terrain near 103 °E is delayed by 9 to 12 hours, and the position of the front reaching the westernmost side is farther east than that of the unmodified terrain. The terrain is simulated by increasing 100 m, 200 m, 300 m, 400 m and 500 m, and decreasing 100 m, 200 m, 300 m, 400 m and 500 m. From the difference of the position of KQSF, the longer the simulation integral time is, the greater the difference of the front position is when the terrain height is changed. When the terrain is increased, the front is located to the east of 103°E of the relatively high terrain, which is blocked by the terrain, and the difference of the front position is relatively small. When the terrain height is reduced, the difference of the front position every 100 m is relatively large. It shows that the topography has a great influence on the moving speed of KQSF. When the temperature of the warm mass is increased by 2 ℃, the moving speed of the KQSF westward is faster. By strengthening the dynamic force field of the heating mass, the speed of KQSF westward is slowed down. From the simulation results of topography and heating mass sensitivity test, it can be seen that the factors affecting the moving speed of the Kunming quasistatic front are the topography and confrontation of cold and warm air masses, the heating masses play a relatively small role compared with topography.
Based on the mesoscale WRF (Weather Research and Forecast) model, NCEP/NCAR reanalysis data and conventional meteorological observation data, the main moving process of the Kunming QuasiStationary Front （KQSF） from 22 to 24 January 2016 is simulated and sensitive tests are conducted to study the influencing factors of the KQSF movement. The results show that the WRF model successfully simulates the moving process of KQSF and the position of the front westward. When the height of the terrain increases by 1.2 times, the speed of the Kunming quasistatic front moving westward slows down, and the time for the front to cross the highest terrain near 103 °E is delayed by 9 to 12 hours, and the position of the front reaching the westernmost side is farther east than that of the unmodified terrain. The terrain is simulated by increasing 100 m, 200 m, 300 m, 400 m and 500 m, and decreasing 100 m, 200 m, 300 m, 400 m and 500 m. From the difference of the position of KQSF, the longer the simulation integral time is, the greater the difference of the front position is when the terrain height is changed. When the terrain is increased, the front is located to the east of 103°E of the relatively high terrain, which is blocked by the terrain, and the difference of the front position is relatively small. When the terrain height is reduced, the difference of the front position every 100 m is relatively large. It shows that the topography has a great influence on the moving speed of KQSF. When the temperature of the warm mass is increased by 2 ℃, the moving speed of the KQSF westward is faster. By strengthening the dynamic force field of the heating mass, the speed of KQSF westward is slowed down. From the simulation results of topography and heating mass sensitivity test, it can be seen that the factors affecting the moving speed of the Kunming quasistatic front are the topography and confrontation of cold and warm air masses, the heating masses play a relatively small role compared with topography.
2021, 49(3):372-379.
Abstract:
Based on the GPM (Global Precipitation Measurement mission) data from March to September in 2014-2018, the temporal and spatial distribution of the deep convective system and precipitation characteristics of the Tibetan Plateau region are studied. The results show that the deep convective systems in the main area of the Tibetan Plateau (25°-40°N, 70°-105°E) were mainly concentrated in the central, eastern and southern regions. The convective intensity was relatively small compared with other regions of the East Asian monsoon region, while the systems with relatively large convective intensity were mostly distributed in the eastern region of the Plateau. The deep convection systems mainly occurred in summer. In July and August, the frequency peaks and the convection were strong. The main activity area had the characteristics of extending southward, westward, and then retreating eastward. The deep convective activities mainly developed in the afternoon and showed a unimodal distribution. The precipitation intensity produced by the deep convective system of the plateau was relatively weak, mainly concentrated below 5 mm/h, and the precipitation produced by it also mainly was induced by weak convective activities with a low echo top height and small area.
Based on the GPM (Global Precipitation Measurement mission) data from March to September in 2014-2018, the temporal and spatial distribution of the deep convective system and precipitation characteristics of the Tibetan Plateau region are studied. The results show that the deep convective systems in the main area of the Tibetan Plateau (25°-40°N, 70°-105°E) were mainly concentrated in the central, eastern and southern regions. The convective intensity was relatively small compared with other regions of the East Asian monsoon region, while the systems with relatively large convective intensity were mostly distributed in the eastern region of the Plateau. The deep convection systems mainly occurred in summer. In July and August, the frequency peaks and the convection were strong. The main activity area had the characteristics of extending southward, westward, and then retreating eastward. The deep convective activities mainly developed in the afternoon and showed a unimodal distribution. The precipitation intensity produced by the deep convective system of the plateau was relatively weak, mainly concentrated below 5 mm/h, and the precipitation produced by it also mainly was induced by weak convective activities with a low echo top height and small area.
2021, 49(3):380-387.
Abstract:
Based on the precipitation data from 86 observational stations in Guangdong Province and the NCEP reanalysis data from 1981 to 2019, and the MICAPS radiosonde data from 2005 to 2020, the temporal and spatial distribution, synoptic circulation and the radiosonde characteristics of winter rainstorm events in Guangdong are studied. The results show: (1) The winter rainstorms in Guangdong show ununiform distributions in different areas. Generally, more rainstorms occur in north and east than in south and west, and there are 0.25 winter rainstorms that occur in Guangdong per year on average. The rainstorm events occurring at less than 10 stations account for 65.6% of total rainstorm events in winter, indicating that the winter rainstorm events usually occur in small regions. (2) Winter rainstorms occurring in February take the largest percentage, while rainstorms in December are the least. Convection is usually found along with the rainstorms in February. Rainstorm events occurred between 1981 and 1990, 2011 and 2019 are more than those of other two decades in Guangdong. (3) Most winter rainstorms occur in steady atmospheric stratification with moderate K index and Δ〖WTBX〗T〖WTBZ〗, low CAPE, 〖JP2〗high SI and IQ index. (4) The main influencing systems include the eastward moving south westerly trough at 500 hPa, steady southerly airflows and cold shear line at 850 hPa, and the southward moving cold front at ground. Dominant background synoptic circulation that brings winter rainstorms can be classified into 4 patterns, including the shear linecold front pattern, the southerly airflowcold front pattern, the southerly airflowtransformed cold high ridge pattern, and the southerly airflowsouthwest depression pattern. 〖JP〗
Based on the precipitation data from 86 observational stations in Guangdong Province and the NCEP reanalysis data from 1981 to 2019, and the MICAPS radiosonde data from 2005 to 2020, the temporal and spatial distribution, synoptic circulation and the radiosonde characteristics of winter rainstorm events in Guangdong are studied. The results show: (1) The winter rainstorms in Guangdong show ununiform distributions in different areas. Generally, more rainstorms occur in north and east than in south and west, and there are 0.25 winter rainstorms that occur in Guangdong per year on average. The rainstorm events occurring at less than 10 stations account for 65.6% of total rainstorm events in winter, indicating that the winter rainstorm events usually occur in small regions. (2) Winter rainstorms occurring in February take the largest percentage, while rainstorms in December are the least. Convection is usually found along with the rainstorms in February. Rainstorm events occurred between 1981 and 1990, 2011 and 2019 are more than those of other two decades in Guangdong. (3) Most winter rainstorms occur in steady atmospheric stratification with moderate K index and Δ〖WTBX〗T〖WTBZ〗, low CAPE, 〖JP2〗high SI and IQ index. (4) The main influencing systems include the eastward moving south westerly trough at 500 hPa, steady southerly airflows and cold shear line at 850 hPa, and the southward moving cold front at ground. Dominant background synoptic circulation that brings winter rainstorms can be classified into 4 patterns, including the shear linecold front pattern, the southerly airflowcold front pattern, the southerly airflowtransformed cold high ridge pattern, and the southerly airflowsouthwest depression pattern. 〖JP〗
2021, 49(3):388-398.
Abstract:
Based on the monthly data of ground temperature at a depth of 0 cm as well as other meteorological elements of 17 meteorological observation stations from 1980 to 2018 in Hainan Island, the changes in ground temperature and their relationship with meteorological elements are analyzed by the mathematical statistic method. The results show that the annual ground temperature of Hainan Island showed an increasing trend, and the ground temperature rising in autumn had the greatest contribution, and that in spring was the second. The MK test confirms that the annual and spring, autumn ground temperature had significantly increasing trends with the significant mutation around the midtolate 1990s. The annual ground temperature was low in the central and high in the south parts. In most regions, ground temperature had increasing trends. Among the relationships with ground temperature, the air temperature had a significant positive drive to ground temperature. The decrease of sunshine duration and the increase of precipitation caused slow ground temperature warming trends. The effect of wind speed on ground temperature was more complicated, and different in different seasons.
Based on the monthly data of ground temperature at a depth of 0 cm as well as other meteorological elements of 17 meteorological observation stations from 1980 to 2018 in Hainan Island, the changes in ground temperature and their relationship with meteorological elements are analyzed by the mathematical statistic method. The results show that the annual ground temperature of Hainan Island showed an increasing trend, and the ground temperature rising in autumn had the greatest contribution, and that in spring was the second. The MK test confirms that the annual and spring, autumn ground temperature had significantly increasing trends with the significant mutation around the midtolate 1990s. The annual ground temperature was low in the central and high in the south parts. In most regions, ground temperature had increasing trends. Among the relationships with ground temperature, the air temperature had a significant positive drive to ground temperature. The decrease of sunshine duration and the increase of precipitation caused slow ground temperature warming trends. The effect of wind speed on ground temperature was more complicated, and different in different seasons.
2021, 49(3):399-405.
Abstract:
Under the historical simulation during 1951-2005 and two different scenarios of greenhouse gas emission including RCP 8.5 and 4.5 over 2006-2099, the daily mean temperature, precipitation, westerly wind at 10 m and incident solar energy flux from the RegCM4 model are examined in this study in order to find out the comparison of temporal and spatial climate change in summer tourism resources between Guizhou and other regions in China over the 21 century. Results show that the increase of mean temperature in summer over Guizhou under two scenarios will be smaller that of the whole nation, and the warming amplitude after 2050 under RCP4.5 (low emission) scenario would be lower than that under RCP8.5 (high emission) scenario. There was no obvious change in other factors including precipitation, westerly wind at 10 m and incident solar energy flux. From the perspective of spatial distribution, the increase in summer mean temperature over Guizhou would be less than that in the northern and western regions in China during the 21st century under the two RCPs scenarios, though close to that in Yunnan. However, Yunnan would be dominated by the trend of increasing incident solar energy flux in summer, especially located in the highvalue center of rising under the RCP8.5 〖JP2〗(higher emission) in the midlate 21st century. Generally, Guizhou would continue keeping the advantage in summer tourism climate resources on account of the less increasing mean temperature and little changes in precipitation, westerly wind at 10 m and incident solar energy flux in the future. Moreover, environmental protection for emission reduction should be adopted to maintain and further expand the advantages of summer tourism resources in Guizhou.〖JP〗
Under the historical simulation during 1951-2005 and two different scenarios of greenhouse gas emission including RCP 8.5 and 4.5 over 2006-2099, the daily mean temperature, precipitation, westerly wind at 10 m and incident solar energy flux from the RegCM4 model are examined in this study in order to find out the comparison of temporal and spatial climate change in summer tourism resources between Guizhou and other regions in China over the 21 century. Results show that the increase of mean temperature in summer over Guizhou under two scenarios will be smaller that of the whole nation, and the warming amplitude after 2050 under RCP4.5 (low emission) scenario would be lower than that under RCP8.5 (high emission) scenario. There was no obvious change in other factors including precipitation, westerly wind at 10 m and incident solar energy flux. From the perspective of spatial distribution, the increase in summer mean temperature over Guizhou would be less than that in the northern and western regions in China during the 21st century under the two RCPs scenarios, though close to that in Yunnan. However, Yunnan would be dominated by the trend of increasing incident solar energy flux in summer, especially located in the highvalue center of rising under the RCP8.5 〖JP2〗(higher emission) in the midlate 21st century. Generally, Guizhou would continue keeping the advantage in summer tourism climate resources on account of the less increasing mean temperature and little changes in precipitation, westerly wind at 10 m and incident solar energy flux in the future. Moreover, environmental protection for emission reduction should be adopted to maintain and further expand the advantages of summer tourism resources in Guizhou.〖JP〗
2021, 49(3):406-418.
Abstract:
A training set is obtained by combining diagnostic predictors calculated from the ECMWF finemesh reanalysis (ECthin) fields with the shortduration heavy rain cases from 2011 to 2014 between May and September. Based on the box difference indexes of all predictors, a thresholding method is proposed to rudimentarily decrease false alarms. A new classbalanced training set is reconstructed by using the Kmeans clustering, and meanwhile, predictors with greater average weights are selected by the Relief algorithm. A forecast model for shortduration heavy rainfall in the Chongqing region centered by the Xgboost algorithm is established. The results suggest three points: (1) this model provides probabilistic and deterministic binary forecasts generated by the customized threshold; (2) the verification of the independent validation set in 2015 shows that the model achieves better classification performance in general and outperforms the ECthin hourly total precipitation reanalysis when the probability threshold is set to be 0.1, with TS score reaching 0.3. Two case studies show that this Xgboostbased model can predict the probability and area of potential shortduration heavy rain events with higher precision than the hourly ECthin, scoring TS between 0.2 to 0.4. (3) The TS scores of the Xgboost model on cases from recent years are greater than 0.1, outperforming the ECthin and rivalling daily forecast operation, which means that its products are well worth referring to.
A training set is obtained by combining diagnostic predictors calculated from the ECMWF finemesh reanalysis (ECthin) fields with the shortduration heavy rain cases from 2011 to 2014 between May and September. Based on the box difference indexes of all predictors, a thresholding method is proposed to rudimentarily decrease false alarms. A new classbalanced training set is reconstructed by using the Kmeans clustering, and meanwhile, predictors with greater average weights are selected by the Relief algorithm. A forecast model for shortduration heavy rainfall in the Chongqing region centered by the Xgboost algorithm is established. The results suggest three points: (1) this model provides probabilistic and deterministic binary forecasts generated by the customized threshold; (2) the verification of the independent validation set in 2015 shows that the model achieves better classification performance in general and outperforms the ECthin hourly total precipitation reanalysis when the probability threshold is set to be 0.1, with TS score reaching 0.3. Two case studies show that this Xgboostbased model can predict the probability and area of potential shortduration heavy rain events with higher precision than the hourly ECthin, scoring TS between 0.2 to 0.4. (3) The TS scores of the Xgboost model on cases from recent years are greater than 0.1, outperforming the ECthin and rivalling daily forecast operation, which means that its products are well worth referring to.
2021, 49(3):419-426.
Abstract:
A new precipitation correction forecast method for ECMWF is proposed by using Convolution Neural Network (CNN) and Random Forest Regression (RFR) models. In the new method, the grades of rainfall forecast values of stations are divided according to the ECMWF model, and then the high correlation factor matrix corresponding to different grades is calculated. The CNN model is used to train the comprehensive features of the high correlation matrix. Finally, the features highly correlated with the forecast stations and the factors by the ECMWF precipitation field interpolating to the forecast stations are served as the RFR forecast modeling inputs. The graded and nongraded 24 hour precipitation correction forecast experiments for 10 stations are conducted. The results show that the MAE and RMSE errors of the ECMWF model precipitation grading correction forecast method proposed in this paper are reduced by 20% and 15%, respectively, when compared with the forecast method of ECMWF rainfall forecast field interpolating to stations. Meanwhile, the TS (Threat Score) of 24 hour rainstorms at 10 stations is 0.32, which is significantly higher than that of the EC interpolation (0.19). In addition, compared with the traditional numerical prediction model product correction method using the same forecast model for the full sample (nongraded), the grading correction forecast method proposed in this paper shows a higher forecast sill in the overall forecast accuracy and the heavy rainfall forecast TS score.
A new precipitation correction forecast method for ECMWF is proposed by using Convolution Neural Network (CNN) and Random Forest Regression (RFR) models. In the new method, the grades of rainfall forecast values of stations are divided according to the ECMWF model, and then the high correlation factor matrix corresponding to different grades is calculated. The CNN model is used to train the comprehensive features of the high correlation matrix. Finally, the features highly correlated with the forecast stations and the factors by the ECMWF precipitation field interpolating to the forecast stations are served as the RFR forecast modeling inputs. The graded and nongraded 24 hour precipitation correction forecast experiments for 10 stations are conducted. The results show that the MAE and RMSE errors of the ECMWF model precipitation grading correction forecast method proposed in this paper are reduced by 20% and 15%, respectively, when compared with the forecast method of ECMWF rainfall forecast field interpolating to stations. Meanwhile, the TS (Threat Score) of 24 hour rainstorms at 10 stations is 0.32, which is significantly higher than that of the EC interpolation (0.19). In addition, compared with the traditional numerical prediction model product correction method using the same forecast model for the full sample (nongraded), the grading correction forecast method proposed in this paper shows a higher forecast sill in the overall forecast accuracy and the heavy rainfall forecast TS score.
2021, 49(3):427-436.
Abstract:
By using the besttrack datasets of tropical cyclones (TCs) provided by the China Meteorological Administration (CMA) and the ERA interim reanalysis data provided by the European Centre for MediumRange Weather Forecasts (ECMWF), the reasons for the difference between the tracks of typhoons Yagi and Rumbia that influenced Shandong when moving northward in 2018 are analyzed. It is found that: The differences between the tracks of typhoons Yagi and Rumbia are mainly related to the different distributions of the weather systems. Both typhoons were affected by the subtropical high and continental high successively, and Rumbia was also influenced by the upper trough that made a big angle change of the move direction. The steering airflow formed by the interaction between typhoon and highpressure systems were the main factors influencing the tracks of the two typhoons. The radiuses of the best steering airflow were within 5 latitudes of the TC center in both Yagi and Rumbia, but the height was different in different stages. The indicative function of the airflow at the middlelow levels was superior to that at the high levels before landing. After landing and before turning, the zonal airflow was better than the meridional, but the stability was little worse. After turning, without the meridional airflow of Rumbia, both the meridional and zonal airflow of Yagi and the zonal airflow of Rumbia had significant correlation across the whole level, and the middleupper levels were slightly better than the low levels. The airflow from 300 to 200 hPa can be used to forecast the turning of the typhoon 12 hours in advance. In addition, typhoons always move towards the direction of the positive vorticity advection nearby, and the stronger the positive vorticity advection is, the faster the typhoon moves.
By using the besttrack datasets of tropical cyclones (TCs) provided by the China Meteorological Administration (CMA) and the ERA interim reanalysis data provided by the European Centre for MediumRange Weather Forecasts (ECMWF), the reasons for the difference between the tracks of typhoons Yagi and Rumbia that influenced Shandong when moving northward in 2018 are analyzed. It is found that: The differences between the tracks of typhoons Yagi and Rumbia are mainly related to the different distributions of the weather systems. Both typhoons were affected by the subtropical high and continental high successively, and Rumbia was also influenced by the upper trough that made a big angle change of the move direction. The steering airflow formed by the interaction between typhoon and highpressure systems were the main factors influencing the tracks of the two typhoons. The radiuses of the best steering airflow were within 5 latitudes of the TC center in both Yagi and Rumbia, but the height was different in different stages. The indicative function of the airflow at the middlelow levels was superior to that at the high levels before landing. After landing and before turning, the zonal airflow was better than the meridional, but the stability was little worse. After turning, without the meridional airflow of Rumbia, both the meridional and zonal airflow of Yagi and the zonal airflow of Rumbia had significant correlation across the whole level, and the middleupper levels were slightly better than the low levels. The airflow from 300 to 200 hPa can be used to forecast the turning of the typhoon 12 hours in advance. In addition, typhoons always move towards the direction of the positive vorticity advection nearby, and the stronger the positive vorticity advection is, the faster the typhoon moves.
2021, 49(3):437-445.
Abstract:
Using the surface observation data, radar data, FY2G satellite cloud images and ECMWF_HR data, the extra torrential rain of Typhoon Lekima in Shandong in 2019 is analyzed. The results show that during the landfalling and northward moving process of Lekima, the cold air invaded into the center from west, southwest and south of the typhoon, which gradually weakened its warm center structure and during the extratropical transition period from 20:00 of 10 August to 08:00 of 11 August. The extra torrential rain in Shandong occurred during the period of 12 hours ahead and 6 hours later of the extratropical transition. Before the transition, the precipitation in Shandong was mainly caused by the interaction between the spiral cloud belt of the typhoon and the tail clouds of the low trough, but the precipitation during the transition was caused by the cold air intrusion which made the clouds outside of the typhoon develop into mesoscale convective convergence. Before the transition, the wind speed of 800 to 500 hPa in the troposphere was small, and that of 500 to 250 hPa was large. There were warm advection and ascending motion in the air layer, and the main precipitation came from convective precipitation in the warm zone. After the transition, the wind speed of 800 to 500 hPa was large, and that of 500 to 250 hPa was small. The ascending motion lain from 500 hPa to the ground, and the descending motion was above 500 hPa. The precipitation belonged mainly the convective precipitation near the baroclinefront area. When the cold advection appeared between 500 hPa to the ground, the wet layer became thinner and the precipitation tended to weaken. The heavy rain appeared in the energy front on the northwest direction of the typhoon center, which was consistent with the divergence convergence of water vapor flux at 850 hPa.
Using the surface observation data, radar data, FY2G satellite cloud images and ECMWF_HR data, the extra torrential rain of Typhoon Lekima in Shandong in 2019 is analyzed. The results show that during the landfalling and northward moving process of Lekima, the cold air invaded into the center from west, southwest and south of the typhoon, which gradually weakened its warm center structure and during the extratropical transition period from 20:00 of 10 August to 08:00 of 11 August. The extra torrential rain in Shandong occurred during the period of 12 hours ahead and 6 hours later of the extratropical transition. Before the transition, the precipitation in Shandong was mainly caused by the interaction between the spiral cloud belt of the typhoon and the tail clouds of the low trough, but the precipitation during the transition was caused by the cold air intrusion which made the clouds outside of the typhoon develop into mesoscale convective convergence. Before the transition, the wind speed of 800 to 500 hPa in the troposphere was small, and that of 500 to 250 hPa was large. There were warm advection and ascending motion in the air layer, and the main precipitation came from convective precipitation in the warm zone. After the transition, the wind speed of 800 to 500 hPa was large, and that of 500 to 250 hPa was small. The ascending motion lain from 500 hPa to the ground, and the descending motion was above 500 hPa. The precipitation belonged mainly the convective precipitation near the baroclinefront area. When the cold advection appeared between 500 hPa to the ground, the wet layer became thinner and the precipitation tended to weaken. The heavy rain appeared in the energy front on the northwest direction of the typhoon center, which was consistent with the divergence convergence of water vapor flux at 850 hPa.
2021, 49(3):446-454.
Abstract:
By using the conventional and unconventional intensive observation data, FY satellite data and NCEP/NCAR reanalysis data (1°×1°), a heavy rainfall process happened in Hunan in the main flood season of 2019 is analyzed and its causes are discussed. The results show that: the influence systems of this rainfall process were complex and changeable, which were composed of the warm zone rainstorm, middle cold advection intrusion rainstorm, and frontal rainstorm. The highest rainfall effectiveness occurred when the cold air invaded, and the strongest hourly rainfall intensity and accumulated rainfall reached the peak; the subtropical high was obviously strong, 24 longitudes west than the same period of previous year, and there were multiple active shortwave troughs around. The upper cold vortex activity was obvious, and the cold vortex and cold trough were superimposed in the same phase. The bottom of trough developed southward to the south of 30°N, and the northerly airflow at the back of the trough guided the cold air to penetrate southward and intersect with the southwest airflow at the edge of the subtropical high, which was the largescale circulation background of continuous heavy rainfall. Frequent activities of medium and smallscale systems and the development and merger of multiple MCC (Mesoscale Convective Complex) directly caused the rainstorm. The radar echo map shows the characteristics of lowcentroid precipitation and high rainfall effectiveness. When heavy rainfall occurred, the spatial distribution of divergence field and vertical velocity corresponded well, and the strong rising center and the nondivergence layer were relatively obvious.
By using the conventional and unconventional intensive observation data, FY satellite data and NCEP/NCAR reanalysis data (1°×1°), a heavy rainfall process happened in Hunan in the main flood season of 2019 is analyzed and its causes are discussed. The results show that: the influence systems of this rainfall process were complex and changeable, which were composed of the warm zone rainstorm, middle cold advection intrusion rainstorm, and frontal rainstorm. The highest rainfall effectiveness occurred when the cold air invaded, and the strongest hourly rainfall intensity and accumulated rainfall reached the peak; the subtropical high was obviously strong, 24 longitudes west than the same period of previous year, and there were multiple active shortwave troughs around. The upper cold vortex activity was obvious, and the cold vortex and cold trough were superimposed in the same phase. The bottom of trough developed southward to the south of 30°N, and the northerly airflow at the back of the trough guided the cold air to penetrate southward and intersect with the southwest airflow at the edge of the subtropical high, which was the largescale circulation background of continuous heavy rainfall. Frequent activities of medium and smallscale systems and the development and merger of multiple MCC (Mesoscale Convective Complex) directly caused the rainstorm. The radar echo map shows the characteristics of lowcentroid precipitation and high rainfall effectiveness. When heavy rainfall occurred, the spatial distribution of divergence field and vertical velocity corresponded well, and the strong rising center and the nondivergence layer were relatively obvious.
2021, 49(3):455-463.
Abstract:
In this paper, a total of 41 flight detection results during 2009-2011 in Tongliao, Inner Mongolia are statistically analyzed, so as to discuss the microscopic characteristics of various types of clouds in a typical area in the northern China. The results show that average number concentrations of cloud droplets (〖WTBX〗N〖WTBZ〗c) in different types of clouds are: Stratocumulus (Sc) >Cumulus (Cu)>Altostratus (As)>Nimbostratus (Ns)>Altocumulus (Ac), in order of size.〖WTBX〗 N〖WTBZ〗c in precipitable clouds (Ns, As and Sc) generally spanned a large range, and the cumulative probability reduced relatively gentle. Average Liquid Water Contents (LWCs) in precipitable clouds (Sc, Ns and As) were larger than those in nonprecipitable clouds (Ac and Cu). Besides, LWCs〖WTBX〗 〖WTBZ〗in As and Ns were generally between 0.01 and 0.3 g·m-3. The characteristics of average mean diameter (〖WTBX〗D〖WTBZ〗m) for various types of clouds were similar to effective diameter (〖WTBX〗D〖WTBZ〗e), and the cloud types with larger 〖WTBX〗N〖WTBZ〗c have smaller droplet sizes. Average 〖WTBX〗D〖WTBZ〗e ranked: Ns>As>Ac>Cu>Sc. 〖WTBX〗D〖WTBZ〗e and 〖WTBX〗D〖WTBZ〗m of higher clouds (Ac, As and Ns) were generally larger than those in lower clouds (Cu and Sc).〖WTBZ〗 Precipitable clouds compared with nonprecipitable clouds had more big droplets, which is conducive to the formation of precipitation. Moreover, the statistical results show that the relative dispersion of various types of cloud droplet spectrum spread widely when 〖WTBX〗N〖WTBZ〗c was small. With the increasing of 〖WTBX〗N〖WTBZ〗c, the relative dispersion constringed to 0.3 to 0.6, and eventually all kinds of cloud relative dispersion slowly converged to about 0.4 at the high 〖WTBX〗N〖WTBZ〗c.
In this paper, a total of 41 flight detection results during 2009-2011 in Tongliao, Inner Mongolia are statistically analyzed, so as to discuss the microscopic characteristics of various types of clouds in a typical area in the northern China. The results show that average number concentrations of cloud droplets (〖WTBX〗N〖WTBZ〗c) in different types of clouds are: Stratocumulus (Sc) >Cumulus (Cu)>Altostratus (As)>Nimbostratus (Ns)>Altocumulus (Ac), in order of size.〖WTBX〗 N〖WTBZ〗c in precipitable clouds (Ns, As and Sc) generally spanned a large range, and the cumulative probability reduced relatively gentle. Average Liquid Water Contents (LWCs) in precipitable clouds (Sc, Ns and As) were larger than those in nonprecipitable clouds (Ac and Cu). Besides, LWCs〖WTBX〗 〖WTBZ〗in As and Ns were generally between 0.01 and 0.3 g·m-3. The characteristics of average mean diameter (〖WTBX〗D〖WTBZ〗m) for various types of clouds were similar to effective diameter (〖WTBX〗D〖WTBZ〗e), and the cloud types with larger 〖WTBX〗N〖WTBZ〗c have smaller droplet sizes. Average 〖WTBX〗D〖WTBZ〗e ranked: Ns>As>Ac>Cu>Sc. 〖WTBX〗D〖WTBZ〗e and 〖WTBX〗D〖WTBZ〗m of higher clouds (Ac, As and Ns) were generally larger than those in lower clouds (Cu and Sc).〖WTBZ〗 Precipitable clouds compared with nonprecipitable clouds had more big droplets, which is conducive to the formation of precipitation. Moreover, the statistical results show that the relative dispersion of various types of cloud droplet spectrum spread widely when 〖WTBX〗N〖WTBZ〗c was small. With the increasing of 〖WTBX〗N〖WTBZ〗c, the relative dispersion constringed to 0.3 to 0.6, and eventually all kinds of cloud relative dispersion slowly converged to about 0.4 at the high 〖WTBX〗N〖WTBZ〗c.
2021, 49(3):464-474.
Abstract:
Taking the urban landscape of Shijiazhuang as the research object, the Landsat remote sensing image data of 1987, 2004 and 2019 are selected, and the supervised classification method is used to distinguish the studied area into four types of landscapes: green land, water body, impervious surface, and unused land. The window algorithm and split window algorithm are used to invert land surface temperature (LST). From the perspective of landscape ecology, Fragstats4.2 is used to calculate the four types of landscape pattern indexes, and explore and analyze the landscape granularity and mobile window scale selection, using the ArcGIS spatial analysis method and statistical analysis method to analyze the four types of landscape correlation between pattern index and LST. The results show that, from 1987 to 2019, the green patch type area (CA), maximum patch area index (LPI) and aggregation index (AI) gradually decreased, and the CA, LPI and AI of impervious surface gradually increased. With the urbanization process, the area of green land gradually reduced and cracked, the advantage of green landscape was declining, the surface area of impervious land was gradually increasing and converging, and the advantage of impervious surface landscape was constantly strengthening, gradually forming an advantageous landscape. The Plaque percentage index (PLAND), LPI, AI and LST show a consistent and extremely significant correlation; green land and water are negatively correlated; impervious surface and unused land were positively correlated. The SPLIT index was the opposite, green lands and water bodies are positively correlated, and impervious surface and unused land are negatively correlated. The correlation coefficient of LST with PLAND and LPI is significantly higher than that with AI and SPLIT, indicating that the effect of a dominant landscape on the surface temperature is significantly greater than that of several more scattered or broken landscapes.
Taking the urban landscape of Shijiazhuang as the research object, the Landsat remote sensing image data of 1987, 2004 and 2019 are selected, and the supervised classification method is used to distinguish the studied area into four types of landscapes: green land, water body, impervious surface, and unused land. The window algorithm and split window algorithm are used to invert land surface temperature (LST). From the perspective of landscape ecology, Fragstats4.2 is used to calculate the four types of landscape pattern indexes, and explore and analyze the landscape granularity and mobile window scale selection, using the ArcGIS spatial analysis method and statistical analysis method to analyze the four types of landscape correlation between pattern index and LST. The results show that, from 1987 to 2019, the green patch type area (CA), maximum patch area index (LPI) and aggregation index (AI) gradually decreased, and the CA, LPI and AI of impervious surface gradually increased. With the urbanization process, the area of green land gradually reduced and cracked, the advantage of green landscape was declining, the surface area of impervious land was gradually increasing and converging, and the advantage of impervious surface landscape was constantly strengthening, gradually forming an advantageous landscape. The Plaque percentage index (PLAND), LPI, AI and LST show a consistent and extremely significant correlation; green land and water are negatively correlated; impervious surface and unused land were positively correlated. The SPLIT index was the opposite, green lands and water bodies are positively correlated, and impervious surface and unused land are negatively correlated. The correlation coefficient of LST with PLAND and LPI is significantly higher than that with AI and SPLIT, indicating that the effect of a dominant landscape on the surface temperature is significantly greater than that of several more scattered or broken landscapes.
2021, 49(3):475-482.
Abstract:
Climate conditions are one of the determinants whether an area is suitable for the growth and quality of tea plants. This study is to reveal the climate advantages of main producing areas of Banan Silver Needle Tea. Taking the Banan Silver Needle Tea producing area as an example, the climate feasibility of tea planting areas is analyzed based on the statistics of climate conditions and meteorological disasters. Considering the climate impacts on the growth and quality of tea plants as well as the analysis of main meteorological factors during the spring tea growing period, the climate suitability and climate quality grade of tea growing are quantitatively analyzed based on climate suitability theory and climate quality evaluation model. The results show that the Banan Silver Needle Tea producing area has superior heat conditions, no freezing damage in early spring, and can ensure the safe overwintering of tea trees and the early harvest and high yields of spring tea; the average climate suitability is calculated to be 0.75 during the spring tea growing period, which was counted from the picking period of one bud and one leaf, maintained at a relatively high level. The climate quality grade of spring tea is maintained between grade 2 and grade 1, leading to the result that the production of quality tea can be ensured since climate condition there is good for the quality ingredient accumulation of spring tea.
Climate conditions are one of the determinants whether an area is suitable for the growth and quality of tea plants. This study is to reveal the climate advantages of main producing areas of Banan Silver Needle Tea. Taking the Banan Silver Needle Tea producing area as an example, the climate feasibility of tea planting areas is analyzed based on the statistics of climate conditions and meteorological disasters. Considering the climate impacts on the growth and quality of tea plants as well as the analysis of main meteorological factors during the spring tea growing period, the climate suitability and climate quality grade of tea growing are quantitatively analyzed based on climate suitability theory and climate quality evaluation model. The results show that the Banan Silver Needle Tea producing area has superior heat conditions, no freezing damage in early spring, and can ensure the safe overwintering of tea trees and the early harvest and high yields of spring tea; the average climate suitability is calculated to be 0.75 during the spring tea growing period, which was counted from the picking period of one bud and one leaf, maintained at a relatively high level. The climate quality grade of spring tea is maintained between grade 2 and grade 1, leading to the result that the production of quality tea can be ensured since climate condition there is good for the quality ingredient accumulation of spring tea.
2021, 49(3):483-490.
Abstract:
According to the calculation demand of the carrying capacity of the overhead lines, this paper analyzes the monthly average, median, and quartile values, as well as the cutoff points of the abnormal values, by using the monthly extreme maximum temperature and the average wind speed at 14:00 of 94 meteorological stations in the southern Hebei power grid area from 1974 to 2018. Then the monthly high temperature analysis interval and the small wind speed analysis interval are determined and each high temperature analysis interval and the small wind speed analysis interval are grouped into meteorological parameter combinations. Based on the hourly temperature and wind speed data of 94 automatic stations in the southern Hebei power grid area from the station construction to 20 September in 2018, 〖JP2〗combined with the combination of meteorological parameters determined by the box plot method, the frequency of combination of various meteorological parameters and the meteorological risk of combination of parameters for the carrying capacity calculation of the southern Hebei power grid are analyzed month by month. The results show that the probability of combination of the maximum temperature and the minimum wind speed is very small, only 4, 1, 130 and 1 station in June, July, August and November. In general, the occurrence probability of combination of highrisk meteorological parameters is very small in 12 months, and the occurrence probability of combination of medium risk and lowrisk meteorological parameters is relatively high in summer. The comprehensive meteorological risk of combination of meteorological parameters is different in space. The risks of Cangzhou, Baoding and the Xiong’an new district are relatively low, while the risks of the Taihang Mountains and the plain in front of the mountain are relatively high. This study is helpful to understand the risk of power grid operation under highimpact weather conditions.〖JP〗
According to the calculation demand of the carrying capacity of the overhead lines, this paper analyzes the monthly average, median, and quartile values, as well as the cutoff points of the abnormal values, by using the monthly extreme maximum temperature and the average wind speed at 14:00 of 94 meteorological stations in the southern Hebei power grid area from 1974 to 2018. Then the monthly high temperature analysis interval and the small wind speed analysis interval are determined and each high temperature analysis interval and the small wind speed analysis interval are grouped into meteorological parameter combinations. Based on the hourly temperature and wind speed data of 94 automatic stations in the southern Hebei power grid area from the station construction to 20 September in 2018, 〖JP2〗combined with the combination of meteorological parameters determined by the box plot method, the frequency of combination of various meteorological parameters and the meteorological risk of combination of parameters for the carrying capacity calculation of the southern Hebei power grid are analyzed month by month. The results show that the probability of combination of the maximum temperature and the minimum wind speed is very small, only 4, 1, 130 and 1 station in June, July, August and November. In general, the occurrence probability of combination of highrisk meteorological parameters is very small in 12 months, and the occurrence probability of combination of medium risk and lowrisk meteorological parameters is relatively high in summer. The comprehensive meteorological risk of combination of meteorological parameters is different in space. The risks of Cangzhou, Baoding and the Xiong’an new district are relatively low, while the risks of the Taihang Mountains and the plain in front of the mountain are relatively high. This study is helpful to understand the risk of power grid operation under highimpact weather conditions.〖JP〗
2021, 49(3):491-497.
Abstract:
Based on the lightning location data of ADTD in Zhejiang Province from 2007 to 2018, the distribution and related parameters of multiple return strokes of cloudtoground (CG) lightning are analyzed. The results show that the number of multiple return stroke flashes accounts for 26.79% of the total CG number. The positive flashes are dominated by singlereturn stroke CG lightning flashes. The mean stroke number of positive CG and negative CG is 1.04 and 1.65, and the maximum stroke number is 5 and 21, respectively. The interannul variation features of multiple stroke CG lightning flashes and total CG lightning flashes are consistent. The daily changes of positive CG and negative CG show multimodal and unimodal distributions, respectively. The arithmetic mean current intensity of the positive multiple stroke lightning is 72.06 kA, and that of the negative is -36.89 kA. The average current for CG flashes of particular multiplicity has a tendency of decreasing with the stroke order. Furthermore, about 40% of multiple stroke CG flashes have at least one subsequent stroke, with the initial peak electric field stronger than that of the first return stroke. The current intensities of the first return stroke and flowing stroke of CG show a lognormal distribution, in which the stroke frequency is the highest when the current intensity is from 15 kA to 45 kA. The arithmetic mean interval stroke of positive CG lightning is 125.47 ms, and the negative is 138.14 ms. The geometric mean interval stroke of positive CG lightning is 56.73 ms, and the negative is 98.95 ms. The interval of stroke lightning also shows a lognormal distribution. The mean interval has a tendency of decreasing with the stroke order. The distribution of interval distance between first return stroke and flowing stroke shows a quasinormal distribution, and the strokes mostly occur within the range of 1 km.
Based on the lightning location data of ADTD in Zhejiang Province from 2007 to 2018, the distribution and related parameters of multiple return strokes of cloudtoground (CG) lightning are analyzed. The results show that the number of multiple return stroke flashes accounts for 26.79% of the total CG number. The positive flashes are dominated by singlereturn stroke CG lightning flashes. The mean stroke number of positive CG and negative CG is 1.04 and 1.65, and the maximum stroke number is 5 and 21, respectively. The interannul variation features of multiple stroke CG lightning flashes and total CG lightning flashes are consistent. The daily changes of positive CG and negative CG show multimodal and unimodal distributions, respectively. The arithmetic mean current intensity of the positive multiple stroke lightning is 72.06 kA, and that of the negative is -36.89 kA. The average current for CG flashes of particular multiplicity has a tendency of decreasing with the stroke order. Furthermore, about 40% of multiple stroke CG flashes have at least one subsequent stroke, with the initial peak electric field stronger than that of the first return stroke. The current intensities of the first return stroke and flowing stroke of CG show a lognormal distribution, in which the stroke frequency is the highest when the current intensity is from 15 kA to 45 kA. The arithmetic mean interval stroke of positive CG lightning is 125.47 ms, and the negative is 138.14 ms. The geometric mean interval stroke of positive CG lightning is 56.73 ms, and the negative is 98.95 ms. The interval of stroke lightning also shows a lognormal distribution. The mean interval has a tendency of decreasing with the stroke order. The distribution of interval distance between first return stroke and flowing stroke shows a quasinormal distribution, and the strokes mostly occur within the range of 1 km.
2021, 49(3):498-503.
Abstract:
Aiming at the problem of the use of graphite gaps with different spacings, according to its working principle and combined with the Thompson theory of gas discharge, we use the 1.2/50 μs open circuit voltage wave and 8/20 μs shortcircuit current wave to test different series of graphite clearance. It is concluded that: the voltage protection level as the clearance increases with the increase of the distance, and when the gap distance is greater than 2 mm, the voltage protection level is greater than 2.5 kV stipulated by the IEC. The residual pressure, flow passage and action response time of the graphite gap all increase with the increase of the graphite order, and the gap distance is negatively correlated with the residual pressure ratio. It is verified that the multiclearance structure of the graphite gap can effectively improve the flow capacity and reduce the flow continuation. Based on the phenomenon and theoretical analysis, the design method of switch type surge protector under the condition of reasonable gap distance is put forward, which has certain reference value in practical application.
Aiming at the problem of the use of graphite gaps with different spacings, according to its working principle and combined with the Thompson theory of gas discharge, we use the 1.2/50 μs open circuit voltage wave and 8/20 μs shortcircuit current wave to test different series of graphite clearance. It is concluded that: the voltage protection level as the clearance increases with the increase of the distance, and when the gap distance is greater than 2 mm, the voltage protection level is greater than 2.5 kV stipulated by the IEC. The residual pressure, flow passage and action response time of the graphite gap all increase with the increase of the graphite order, and the gap distance is negatively correlated with the residual pressure ratio. It is verified that the multiclearance structure of the graphite gap can effectively improve the flow capacity and reduce the flow continuation. Based on the phenomenon and theoretical analysis, the design method of switch type surge protector under the condition of reasonable gap distance is put forward, which has certain reference value in practical application.
2021, 49(3):504-508.
Abstract:
The Lingui National Meteorological Observatory of Guilin, Guangxi, observed an extreme high wind of 60.3 m/s at 21:13 on 21 March 2019. The data users doubted the authenticity of the wind speed observations. The observation data of Lingui Station, including main AWS and backup AWS, were analyzed, and the wind sensors were replaced for verification. According to the comprehensive analysis, it is concluded: (1) The observational data of Lingui Station’s main AWS and backup AWS had the same trend before and after the occurrence of the extreme wind. The changes in the observation elements conformed to the logical relationship between the elements, so the observation data of Lingui Station are credible. (2) The verification results show that there is still a good linear relationship between the frequency of the wind speed sensor and the wind speed. The wind speed value corrected according to the new linear relationship is closer to the true value of the extreme wind at Lingui Station. Based on the analysis and summary of the authenticity of the maximum wind speed observations at Lingui Station, the suggestions are put forward in three aspects: data quality control, observation data extreme value identification and correction application, as well as the equipment operation and maintenance measures.
The Lingui National Meteorological Observatory of Guilin, Guangxi, observed an extreme high wind of 60.3 m/s at 21:13 on 21 March 2019. The data users doubted the authenticity of the wind speed observations. The observation data of Lingui Station, including main AWS and backup AWS, were analyzed, and the wind sensors were replaced for verification. According to the comprehensive analysis, it is concluded: (1) The observational data of Lingui Station’s main AWS and backup AWS had the same trend before and after the occurrence of the extreme wind. The changes in the observation elements conformed to the logical relationship between the elements, so the observation data of Lingui Station are credible. (2) The verification results show that there is still a good linear relationship between the frequency of the wind speed sensor and the wind speed. The wind speed value corrected according to the new linear relationship is closer to the true value of the extreme wind at Lingui Station. Based on the analysis and summary of the authenticity of the maximum wind speed observations at Lingui Station, the suggestions are put forward in three aspects: data quality control, observation data extreme value identification and correction application, as well as the equipment operation and maintenance measures.
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.