Volume 51,Issue 2,2023 Table of Contents
2023, 51(2):167-174.
DOI: 10.19517/j.1671-6345.20210555
Abstract:
The Galion lidar is a lidar equipment using the second generation technology. It has the ability to scan all sky and all angles. At present, it is the only three-dimensional scanning equipment on the market. Based on the observation data of Shenzhen 356 m gradient tower and Xilinhot 100 m gradient tower, this paper analyzes the detection performance of Galion Lidar and draws the following conclusions: in PPI mode, the correlation coefficient of wind speed measured by the Galion lidar and gradient tower in Shenzhen is 0.85; the correlation coefficient of wind direction is 0.9; the correlation coefficient of wind speed and wind direction measured by the Galion lidar and gradient tower in Xilinhot is 0.9 and 0.95, respectively; in addition, the correlation of lidar detection results at all angles is good, indicating that the lidar has good detection performance in PPI mode.
The Galion lidar is a lidar equipment using the second generation technology. It has the ability to scan all sky and all angles. At present, it is the only three-dimensional scanning equipment on the market. Based on the observation data of Shenzhen 356 m gradient tower and Xilinhot 100 m gradient tower, this paper analyzes the detection performance of Galion Lidar and draws the following conclusions: in PPI mode, the correlation coefficient of wind speed measured by the Galion lidar and gradient tower in Shenzhen is 0.85; the correlation coefficient of wind direction is 0.9; the correlation coefficient of wind speed and wind direction measured by the Galion lidar and gradient tower in Xilinhot is 0.9 and 0.95, respectively; in addition, the correlation of lidar detection results at all angles is good, indicating that the lidar has good detection performance in PPI mode.
2023, 51(2):175-182.
DOI: 10.19517/j.1671-6345.20220196
Abstract:
The influence of atmospheric background data on liquid water path retrieval results is discussed based on the airborne GVR and BP neural network algorithm. It provides a basis for reasonably selecting training samples to obtain more accurate liquid water observation data and is beneficial to understand the detection scope of the retrieval algorithm. Multiple historical sounding data are selected and classified by historical data time series length, season, and region. Different training sample sets are established to train BP neural networks to obtain the corresponding retrieval equations. The sample test set is selected to calculate the retrieval accuracy of each type of retrieval equations. The influence of atmospheric background data difference on liquid water path retrieval results is analyzed by retrieval accuracy comparison. The results show that the spatial and temporal differences in the atmospheric background of the training samples influence the retrieval results. The effect of atmospheric background differences on the retrieval error can be reduced by increasing the length of historical-sounding data. However, it does not work when the time series length reaches a certain extent. Seasonal classification can reduce the impact of atmospheric background differences on retrieval error, but data classification reduces the sample size in practice. For the historical data of a certain time series length, classification according to the season cannot effectively improve the retrieval accuracy of the liquid water path.
The influence of atmospheric background data on liquid water path retrieval results is discussed based on the airborne GVR and BP neural network algorithm. It provides a basis for reasonably selecting training samples to obtain more accurate liquid water observation data and is beneficial to understand the detection scope of the retrieval algorithm. Multiple historical sounding data are selected and classified by historical data time series length, season, and region. Different training sample sets are established to train BP neural networks to obtain the corresponding retrieval equations. The sample test set is selected to calculate the retrieval accuracy of each type of retrieval equations. The influence of atmospheric background data difference on liquid water path retrieval results is analyzed by retrieval accuracy comparison. The results show that the spatial and temporal differences in the atmospheric background of the training samples influence the retrieval results. The effect of atmospheric background differences on the retrieval error can be reduced by increasing the length of historical-sounding data. However, it does not work when the time series length reaches a certain extent. Seasonal classification can reduce the impact of atmospheric background differences on retrieval error, but data classification reduces the sample size in practice. For the historical data of a certain time series length, classification according to the season cannot effectively improve the retrieval accuracy of the liquid water path.
2023, 51(2):183-191.
DOI: 10.19517/j.1671-6345.20220181
Abstract:
Taking seven national weather stations in Hebei Province as an example, the mixed layer height, ventilation capacity and atmospheric selfcleaning ability index are calculated using ERA5 cloud data and measured cloud data from 1979 to 2013, and a preliminarily assessment of ERA5 reanalysis cloud data is conducted through comparing the results by two sets of data calculated. ERA5 cloud cover is used to calculate the atmospheric self-cleaning capacity index from March 2013 to February 2021, and the relationship between it and PM2.5 concentration is analyzed. The results are as follows: (1) The monthly average relative errors between the mixed layer height, ventilation capacity, and atmospheric self-cleaning ability index calculated by using two sets of cloud data approximately accord with the normal distribution, the highest frequency occurring in 0-5%; the monthly relative error of the mixed layer height > ventilation capacity > atmospheric self-cleaning ability index; and the correlation is opposite. The relative errors (correlation coefficients) of autumn and winter are mostly lower (higher) in spring and summer. The monthly mean relative errors of Xingtai, Shijiazhuang and Baoding are significantly smaller than those of other stations. (2) The annual average relative error of the atmospheric self-cleaning ability index is the smallest, followed by ventilation capacity. The fitting degree and deviation of the annual values in the south-central stations are also more ideal. (3) From March 2013 to February 2021, the monthly average atmospheric self-cleaning ability index and PM2.5 concentration are inversely correlated at all stations. The correlativeness is more obvious in the central and southern stations.
Taking seven national weather stations in Hebei Province as an example, the mixed layer height, ventilation capacity and atmospheric selfcleaning ability index are calculated using ERA5 cloud data and measured cloud data from 1979 to 2013, and a preliminarily assessment of ERA5 reanalysis cloud data is conducted through comparing the results by two sets of data calculated. ERA5 cloud cover is used to calculate the atmospheric self-cleaning capacity index from March 2013 to February 2021, and the relationship between it and PM2.5 concentration is analyzed. The results are as follows: (1) The monthly average relative errors between the mixed layer height, ventilation capacity, and atmospheric self-cleaning ability index calculated by using two sets of cloud data approximately accord with the normal distribution, the highest frequency occurring in 0-5%; the monthly relative error of the mixed layer height > ventilation capacity > atmospheric self-cleaning ability index; and the correlation is opposite. The relative errors (correlation coefficients) of autumn and winter are mostly lower (higher) in spring and summer. The monthly mean relative errors of Xingtai, Shijiazhuang and Baoding are significantly smaller than those of other stations. (2) The annual average relative error of the atmospheric self-cleaning ability index is the smallest, followed by ventilation capacity. The fitting degree and deviation of the annual values in the south-central stations are also more ideal. (3) From March 2013 to February 2021, the monthly average atmospheric self-cleaning ability index and PM2.5 concentration are inversely correlated at all stations. The correlativeness is more obvious in the central and southern stations.
2023, 51(2):192-198.
DOI: 10.19517/j.1671-6345.20210491
Abstract:
With the wide application of higher-precision meteorological grid data in meteorological operations, the demand for using high-precision grid data to provide refined meteorological services for the public is growing. Due to the large data file of the meteorological grid, the rendering efficiency over time is slow on the front-end network page. In order to solve this problem, a visualization scheme based on the tile pyramid model for fast transmission and rendering of grid data is proposed. This scheme involves tile cutting, data compression, data interpolation and rendering, and realizes the dynamic visualization process of meteorological grid data under the B/S framework based on HTML5. The China 1km multi-source gridded products are used to complete the research relying on the WeChat mini program. The experimental results show that the visualization display efficiency of 100 megabyte meteorological grid data is improved to the second level or even millisecond level. The solution of this system can be applied well in all kinds of spatial grid data based on the browser.
With the wide application of higher-precision meteorological grid data in meteorological operations, the demand for using high-precision grid data to provide refined meteorological services for the public is growing. Due to the large data file of the meteorological grid, the rendering efficiency over time is slow on the front-end network page. In order to solve this problem, a visualization scheme based on the tile pyramid model for fast transmission and rendering of grid data is proposed. This scheme involves tile cutting, data compression, data interpolation and rendering, and realizes the dynamic visualization process of meteorological grid data under the B/S framework based on HTML5. The China 1km multi-source gridded products are used to complete the research relying on the WeChat mini program. The experimental results show that the visualization display efficiency of 100 megabyte meteorological grid data is improved to the second level or even millisecond level. The solution of this system can be applied well in all kinds of spatial grid data based on the browser.
2023, 51(2):199-207.
DOI: 10.19517/j.1671-6345.20220160
Abstract:
Modernizing meteorology is a long-term comprehensive work and a dynamic development process. In order to continuously, objectively evaluate the development level of meteorological modernization capability in real-time, relying on the framework of the meteorological integrated real-time monitoring system, and based on Okhttp and Jexl3 technology, which features synchronous efficient request, high stability communication mechanism and custom rule engine, a dynamic evaluation method of modern information network capability for multi-source meteorological monitoring big data is proposed. Rely on our self-designed the developed intelligent algorithm framework for data statistics, mining, and comparative analysis, this method can efficiently collect real-time monitoring data and metrics of national and provincial meteorological services and solve the problems of unscientific artificial statistical evaluation methods, inconsistent evaluation standards, delayed evaluation and distortion of evaluation results in the past. Since 2021, this method has been applied to realize the automatic collection and real-time evaluation of the meteorological modernization information network capability metrics from the national and provincial levels. It shortens the acquisition time to the second level, which provides an operation-datamation solution for the high-quality development of the meteorological information network.
Modernizing meteorology is a long-term comprehensive work and a dynamic development process. In order to continuously, objectively evaluate the development level of meteorological modernization capability in real-time, relying on the framework of the meteorological integrated real-time monitoring system, and based on Okhttp and Jexl3 technology, which features synchronous efficient request, high stability communication mechanism and custom rule engine, a dynamic evaluation method of modern information network capability for multi-source meteorological monitoring big data is proposed. Rely on our self-designed the developed intelligent algorithm framework for data statistics, mining, and comparative analysis, this method can efficiently collect real-time monitoring data and metrics of national and provincial meteorological services and solve the problems of unscientific artificial statistical evaluation methods, inconsistent evaluation standards, delayed evaluation and distortion of evaluation results in the past. Since 2021, this method has been applied to realize the automatic collection and real-time evaluation of the meteorological modernization information network capability metrics from the national and provincial levels. It shortens the acquisition time to the second level, which provides an operation-datamation solution for the high-quality development of the meteorological information network.
2023, 51(2):208-214.
DOI: 10.19517/j.1671-6345.20220126
Abstract:
With the rapid development of information technology, the cyber security situation is becoming more and more severe. The meteorological department has organized network attack and defence exercises to test and improve the capability of the service security protection system with practical standards. In the drill, the attacking team penetrates the real network and information system of important operational units. Each unit acts as the defender to carry out real-time monitoring and emergency response. Because of the information imbalance between the two sides, the defence is often in a passive situation by using traditional defence means. In order to improve the network defence capability, this paper studies the application of camouflage deception and attack trapping technology in the actual scenario of cyber security in meteorological departments. By adopting a honeypot-based deception trapping platform, an active defence system is constructed to realize the monitoring, analysis and early warning of abnormal network traffic, and trap and trace the source of attackers. Through actual combat tests, the application of deception trapping technology has effectively improved the cyber security defence capability and ensured meteorological operational systems stable and reliable.
With the rapid development of information technology, the cyber security situation is becoming more and more severe. The meteorological department has organized network attack and defence exercises to test and improve the capability of the service security protection system with practical standards. In the drill, the attacking team penetrates the real network and information system of important operational units. Each unit acts as the defender to carry out real-time monitoring and emergency response. Because of the information imbalance between the two sides, the defence is often in a passive situation by using traditional defence means. In order to improve the network defence capability, this paper studies the application of camouflage deception and attack trapping technology in the actual scenario of cyber security in meteorological departments. By adopting a honeypot-based deception trapping platform, an active defence system is constructed to realize the monitoring, analysis and early warning of abnormal network traffic, and trap and trace the source of attackers. Through actual combat tests, the application of deception trapping technology has effectively improved the cyber security defence capability and ensured meteorological operational systems stable and reliable.
SHEN Chendi
,
LAN Haibo
,
GUO Jie
,
SONG Yingying
,
WANG Ran
,
ZHAO Dapeng
,
LYU Fei
,
CHANG Zhanlai
2023, 51(2):215-221.
DOI: 10.19517/j.1671-6345.20210545
Abstract:
The traditional data service system, which is developed in the form of central control and large integrated single architecture, has poor service experience due to its difficulty in adding new functions and long version update cycles. This paper puts forward the construction idea of the meteorological service support system based on the micro-service architecture, which subdivides and atomizes the system functions and encapsulates the services. At the same time, according to different service characteristics, different mature technologies are used for different operation segments, and finally, the unit installation is carried out. Thus, under the premise of perfect realization of various design goals, the system further has the characteristics of agile development, continuous function update and release, and hot service update. At the same time, the system performance is greatly improved by using distributed deployment, elastic expansion and other technology applications.
The traditional data service system, which is developed in the form of central control and large integrated single architecture, has poor service experience due to its difficulty in adding new functions and long version update cycles. This paper puts forward the construction idea of the meteorological service support system based on the micro-service architecture, which subdivides and atomizes the system functions and encapsulates the services. At the same time, according to different service characteristics, different mature technologies are used for different operation segments, and finally, the unit installation is carried out. Thus, under the premise of perfect realization of various design goals, the system further has the characteristics of agile development, continuous function update and release, and hot service update. At the same time, the system performance is greatly improved by using distributed deployment, elastic expansion and other technology applications.
2023, 51(2):222-232.
DOI: 10.19517/j.1671-6345.20220125
Abstract:
Based on the data of the ground automatic station, Doppler weather radar, satellite hourly TBB data and NCEP reanalysis data, two strong convective weather processes (the process of 21-22 and the process of 26-27) in late March 2020 are compared and analyzed. The results show that: (1) The two strong convective weather processes had good coordination of dynamical, thermal and water vapour conditions. The circulation configuration of high-level divergence and low-level convergence was conducive to upward movement. The strong development of thermal unstable stratification, coupled with favourable water vapour conditions, triggered by systems such as the upper trough and the surface convergence line, led to the occurrence of mixed strong convection weather. (2) The two strong convective weather processes were divided into two stages, namely, warm advection forced strong convection and baroclinic frontogenesis. The accumulation of unstable energy was obvious in the forced phase of warm advection, and it was released to a certain extent before the beginning of the baroclinic frontogenesis phase. The dynamical conditions and water vapour convergence in the baroclinic frontogenesis stage of the two processes were stronger than those in the warm advection stage. (3) Hail, thunderstorms, gale and short-term strong precipitation occurred in the two strong convection weather processes. In the first process, the southwest jet developed more vigorously, the intensity of the warm advection centre was stronger, the vertical extension height was thicker, and the thermal conditions were better, mainly thunderstorms, gales and hail. In the second process, the cold air was stronger, and the significant upward movement lasted longer, with a more abundant water vapour supply, mainly short-term strong precipitation. (4) Hail occurred in 19:00-20:00 in Guanzhuang Town, Yuanling County, Huaihua, in both processes. The radar echoes all reflected the typical hail echo characteristics. The maximum reflectivity factor of the “21-22 process” was larger than that of the “26-27 process”, the intensity of the mesocyclone was stronger, the vertical cumulative liquid water content (VIL) jump was more obvious, and the value was larger, the expansion height of the mesocyclone was higher, and the upper air divergence was stronger, so the diameter of the hail was larger.
Based on the data of the ground automatic station, Doppler weather radar, satellite hourly TBB data and NCEP reanalysis data, two strong convective weather processes (the process of 21-22 and the process of 26-27) in late March 2020 are compared and analyzed. The results show that: (1) The two strong convective weather processes had good coordination of dynamical, thermal and water vapour conditions. The circulation configuration of high-level divergence and low-level convergence was conducive to upward movement. The strong development of thermal unstable stratification, coupled with favourable water vapour conditions, triggered by systems such as the upper trough and the surface convergence line, led to the occurrence of mixed strong convection weather. (2) The two strong convective weather processes were divided into two stages, namely, warm advection forced strong convection and baroclinic frontogenesis. The accumulation of unstable energy was obvious in the forced phase of warm advection, and it was released to a certain extent before the beginning of the baroclinic frontogenesis phase. The dynamical conditions and water vapour convergence in the baroclinic frontogenesis stage of the two processes were stronger than those in the warm advection stage. (3) Hail, thunderstorms, gale and short-term strong precipitation occurred in the two strong convection weather processes. In the first process, the southwest jet developed more vigorously, the intensity of the warm advection centre was stronger, the vertical extension height was thicker, and the thermal conditions were better, mainly thunderstorms, gales and hail. In the second process, the cold air was stronger, and the significant upward movement lasted longer, with a more abundant water vapour supply, mainly short-term strong precipitation. (4) Hail occurred in 19:00-20:00 in Guanzhuang Town, Yuanling County, Huaihua, in both processes. The radar echoes all reflected the typical hail echo characteristics. The maximum reflectivity factor of the “21-22 process” was larger than that of the “26-27 process”, the intensity of the mesocyclone was stronger, the vertical cumulative liquid water content (VIL) jump was more obvious, and the value was larger, the expansion height of the mesocyclone was higher, and the upper air divergence was stronger, so the diameter of the hail was larger.
WANG Xiaoqing
,
DONG Xiaobo
,
YAN Fei
,
FU Jiao
,
WANG Shuyi
,
XUE Xuewu
,
ZHANG Jiannan
,
SUN Xiaoshen
,
CUI Yi
2023, 51(2):233-244.
DOI: 10.19517/j.1671-6345.20220124
Abstract:
In order to better understand the macro and micro structure characteristics of snow clouds, the vertical structure and evolution of a frontal snowfall process on February 14, 2019, are examined using the dataset of Micro Rain Radar (MRR) and Ka-band Cloud Radar (CR) combined with aircraft observation at Huangsi national meteorological station in the south-central part of Hebei Province. The results are as follows: During the initial stage of snowfall, there was a double-layer cloud structure with a dry layer in the middle. The cloud top and base height of the medium cloud were about 4100 m and 3600 m, respectively. The height of the low cloud top and bottom were 3100 m and 200 m, respectively. The growth of particles below 3000 m in the lower cloud was mainly due to the process of rime attachment. During the snowfall development stage, the upper and lower layers of cloud were connected, and the amount of snowfall on the ground was larger in the period with stronger radar echo intensity. The snowfall process in this period was mainly dominated by condensation and aggregation growth. During the late stage of snowfall, the maximum echo intensity and the cloud top height decreased. The echo intensity, doppler velocity and spectral width increased with the decreasing height below 3000 m. Aircraft observation results show that due to the thin water cloud, it was unsuitable for catalytic operation at the bottom of the inversion layer during the late snowfall period. Ice and snow particles were mainly located in the middle and upper part of the cloud and grew bigger during the falling process as the height decreased, which is consistent with radar observation. The correlation coefficient between millimetre wave cloud radar/MRR reflectance and the effective diameter of precipitation particles were 0.89 and 0.83, respectively. Radar reflectivity factors were mainly dominated by largescale particles such as ice and snow crystal particles.
In order to better understand the macro and micro structure characteristics of snow clouds, the vertical structure and evolution of a frontal snowfall process on February 14, 2019, are examined using the dataset of Micro Rain Radar (MRR) and Ka-band Cloud Radar (CR) combined with aircraft observation at Huangsi national meteorological station in the south-central part of Hebei Province. The results are as follows: During the initial stage of snowfall, there was a double-layer cloud structure with a dry layer in the middle. The cloud top and base height of the medium cloud were about 4100 m and 3600 m, respectively. The height of the low cloud top and bottom were 3100 m and 200 m, respectively. The growth of particles below 3000 m in the lower cloud was mainly due to the process of rime attachment. During the snowfall development stage, the upper and lower layers of cloud were connected, and the amount of snowfall on the ground was larger in the period with stronger radar echo intensity. The snowfall process in this period was mainly dominated by condensation and aggregation growth. During the late stage of snowfall, the maximum echo intensity and the cloud top height decreased. The echo intensity, doppler velocity and spectral width increased with the decreasing height below 3000 m. Aircraft observation results show that due to the thin water cloud, it was unsuitable for catalytic operation at the bottom of the inversion layer during the late snowfall period. Ice and snow particles were mainly located in the middle and upper part of the cloud and grew bigger during the falling process as the height decreased, which is consistent with radar observation. The correlation coefficient between millimetre wave cloud radar/MRR reflectance and the effective diameter of precipitation particles were 0.89 and 0.83, respectively. Radar reflectivity factors were mainly dominated by largescale particles such as ice and snow crystal particles.
2023, 51(2):245-253.
DOI: 10.19517/j.1671-6345.20220110
Abstract:
Using Ningbo S-band dual-polarization radar data, NCEP reanalysis data, conventional observation data, and field hail survey data, the weather background and evolution characteristics of dual-polarization radar echo of a severe hailstorm disaster process in the central-northern of Zhejiang Province on 21 March 2020 is analyzed. The results show that: (1) The circulation situation of this hailstorm process which lasted about 4 hours, belonged to the type of low-level warm advection forcing. Hailstorms A and B first moved in the form of strong convective cells and strengthened into supercells, respectively, when moving from west to east. (2) At the typical hailing stages, there existed the obvious three-body scattering spike (TBSS). The extension height of the strong echo (>50 dBz) on the vertical profile exceeded -20 ℃, while the weak echo of the low layer and the hanging echo of the middle-high layer were obvious. On the vertical profile of radial velocity, the lower layer of the hailstorm converged, and the divergent layer was superimposed on it, which made the hailstorm blocks continue to form and grow. (3) The ZDR hail signal appeared in the hail area, and the corresponding ZH was greater than 65 dBz, ZDR was between -2.0 and 0 dB, and CC was between 0.80 and 0.98. When combined ZH, ZDR and CC to comprehensively judge that there were hail particles in the cloud, and CC<0.9, the “hole” area of KDP could also be used as one of the basis for judging heavy hails. (4) HCL products better reflected the distribution and evolution of hails in the air. According to the hail colour scale at low elevation, combined with the height of the zero-degree layer and the value of temperature decline rate under hail clouds, the falling area and size of a hail could be better judged.
Using Ningbo S-band dual-polarization radar data, NCEP reanalysis data, conventional observation data, and field hail survey data, the weather background and evolution characteristics of dual-polarization radar echo of a severe hailstorm disaster process in the central-northern of Zhejiang Province on 21 March 2020 is analyzed. The results show that: (1) The circulation situation of this hailstorm process which lasted about 4 hours, belonged to the type of low-level warm advection forcing. Hailstorms A and B first moved in the form of strong convective cells and strengthened into supercells, respectively, when moving from west to east. (2) At the typical hailing stages, there existed the obvious three-body scattering spike (TBSS). The extension height of the strong echo (>50 dBz) on the vertical profile exceeded -20 ℃, while the weak echo of the low layer and the hanging echo of the middle-high layer were obvious. On the vertical profile of radial velocity, the lower layer of the hailstorm converged, and the divergent layer was superimposed on it, which made the hailstorm blocks continue to form and grow. (3) The ZDR hail signal appeared in the hail area, and the corresponding ZH was greater than 65 dBz, ZDR was between -2.0 and 0 dB, and CC was between 0.80 and 0.98. When combined ZH, ZDR and CC to comprehensively judge that there were hail particles in the cloud, and CC<0.9, the “hole” area of KDP could also be used as one of the basis for judging heavy hails. (4) HCL products better reflected the distribution and evolution of hails in the air. According to the hail colour scale at low elevation, combined with the height of the zero-degree layer and the value of temperature decline rate under hail clouds, the falling area and size of a hail could be better judged.
2023, 51(2):254-261.
DOI: 10.19517/j.1671-6345.20220129
Abstract:
The temporal and spatial distribution characteristics of 79 hail processes causing major disasters in 2012-2021 are statistically analyzed by using hail data, radiosonde observation data, ground observation data and EC thin grid data, the characteristics and thresholds of key environmental parameters of hails in different regions, sizes and months are summarized. The results show that: (1) Hails in Shandong have obvious spatial and temporal distribution characteristics, and mainly appear in central and north Shandong. The number of hail days varies greatly from year to year, with a maximum of 14 days and a minimum of 5 days. Hails mainly occur in late spring and early summer, accounting for 65% of hail days in the year and 65% of hail days in the year. Hails frequently occur from 14:00 to 20:00, accounting for 63.3% of the total hail. (2) The average annual occurrence frequency of large hails is the most in central Shandong Province, but the probability of large hails is greater in the peninsula region. Large hails mainly appear in May and June, accounting for 68.6% of the annual number of large hail days. (3) Hails in Shandong have large convective effective potential energy, deep (0 to 6 km) vertical wind shear with medium or above intensity, significant conditional unstable stratification and suitable characteristic layer height/thickness. (4) Different regions, different sizes and key months have certain differences in the characteristics of physical parameters and potential prediction thresholds. Compared with hail falling in coastal areas and in inland areas, hail falling in June and May, large and small hails, it is mainly reflected in the obvious larger convective effective potential energy, smaller dry and warm cap index, greater deep vertical shear, slightly higher lifting condensation height, and thinner thickness of -20 ℃ to 0 ℃ layer.
The temporal and spatial distribution characteristics of 79 hail processes causing major disasters in 2012-2021 are statistically analyzed by using hail data, radiosonde observation data, ground observation data and EC thin grid data, the characteristics and thresholds of key environmental parameters of hails in different regions, sizes and months are summarized. The results show that: (1) Hails in Shandong have obvious spatial and temporal distribution characteristics, and mainly appear in central and north Shandong. The number of hail days varies greatly from year to year, with a maximum of 14 days and a minimum of 5 days. Hails mainly occur in late spring and early summer, accounting for 65% of hail days in the year and 65% of hail days in the year. Hails frequently occur from 14:00 to 20:00, accounting for 63.3% of the total hail. (2) The average annual occurrence frequency of large hails is the most in central Shandong Province, but the probability of large hails is greater in the peninsula region. Large hails mainly appear in May and June, accounting for 68.6% of the annual number of large hail days. (3) Hails in Shandong have large convective effective potential energy, deep (0 to 6 km) vertical wind shear with medium or above intensity, significant conditional unstable stratification and suitable characteristic layer height/thickness. (4) Different regions, different sizes and key months have certain differences in the characteristics of physical parameters and potential prediction thresholds. Compared with hail falling in coastal areas and in inland areas, hail falling in June and May, large and small hails, it is mainly reflected in the obvious larger convective effective potential energy, smaller dry and warm cap index, greater deep vertical shear, slightly higher lifting condensation height, and thinner thickness of -20 ℃ to 0 ℃ layer.
2023, 51(2):262-268.
DOI: 10.19517/j.1671-6345.20210433
Abstract:
Based on the Detrended Fluctuation Analysis (DFA) method, this paper focuses on the long-range correlation characteristics of wind speed time series observed by 103 wind measuring towers. The results show that: (1) The wind speed time series at different heights have almost consistent scale behaviour, regardless of the resolution. (2) For the 6-hour average wind speed series, the DFA index α has a numerical range basically of 0.55 to 0.91 for all 103 wind towers, showing strong long-range persistence. (3) For the 10-minute average wind speed series, taking the 24-hour scale as the boundary, the DFA curve shows two obvious independent scaling intervals: on the larger time scale, the numerical size of scaling index α is 0.80, while α is about 1.38 on the smaller time scale. This study quantifies the long-range persistence characteristics of wind speed using the nonlinear time series analysis method. It reveals the physical mechanism behind it, which is of great significance for building wind speed models and accurately predicting wind speed.
Based on the Detrended Fluctuation Analysis (DFA) method, this paper focuses on the long-range correlation characteristics of wind speed time series observed by 103 wind measuring towers. The results show that: (1) The wind speed time series at different heights have almost consistent scale behaviour, regardless of the resolution. (2) For the 6-hour average wind speed series, the DFA index α has a numerical range basically of 0.55 to 0.91 for all 103 wind towers, showing strong long-range persistence. (3) For the 10-minute average wind speed series, taking the 24-hour scale as the boundary, the DFA curve shows two obvious independent scaling intervals: on the larger time scale, the numerical size of scaling index α is 0.80, while α is about 1.38 on the smaller time scale. This study quantifies the long-range persistence characteristics of wind speed using the nonlinear time series analysis method. It reveals the physical mechanism behind it, which is of great significance for building wind speed models and accurately predicting wind speed.
2023, 51(2):269-278.
DOI: 10.19517/j.1671-6345.20220185
Abstract:
Based on the cases of rainstorms and flood disasters in Hebei Province from 1984 to 2014, the spatial and temporal distribution characteristics of damaged houses caused by rainstorms are analyzed. Taking houses as the disaster-bearing body, geographical elements such as land use type, topography and residential area are selected as zoning indicators. The disaster-inducing environment of rainstorm disasters in Hebei Province is divided based on the K-means clustering analysis method. The results show that the change in house losses caused by rainstorms from 1984 to 2014 is basically consistent with the total five-day precipitation. The frequency of damages to houses is generally higher in the north and fewer in the south. Among the environmental factors related to land use type, grassland is mainly distributed in Taihang-Yanshan Mountains, and woodland is mainly in Chengde, Southeast Zhangjiakou, Western Baoding and Shijiazhuang. The proportion of agricultural land in the southeast plain is above 0.8. The water range in the eastern coastal area, Zhangbei, Guyuan, and western Daqing River, account for a larger proportion. The topography of the northern plateau and Taihang Yanshan Mountains undulates greatly, and the regional standard deviation is more than 100 m. The density of residential areas increases gradually from northwest to southeast. In the plain, there are dense residential areas near the urban districts. Area Ⅰ is the coastal plain area, which is easily affected by strong precipitation. Area Ⅱ is the piedmont plain area. Its grassland and woodland increase. The proportion of agricultural land in Area Ⅳ (low mountain area in the West) is larger than that in Area Ⅲ (high mountain area in the north). Area Ⅴ is the inland plain area with less precipitation.
Based on the cases of rainstorms and flood disasters in Hebei Province from 1984 to 2014, the spatial and temporal distribution characteristics of damaged houses caused by rainstorms are analyzed. Taking houses as the disaster-bearing body, geographical elements such as land use type, topography and residential area are selected as zoning indicators. The disaster-inducing environment of rainstorm disasters in Hebei Province is divided based on the K-means clustering analysis method. The results show that the change in house losses caused by rainstorms from 1984 to 2014 is basically consistent with the total five-day precipitation. The frequency of damages to houses is generally higher in the north and fewer in the south. Among the environmental factors related to land use type, grassland is mainly distributed in Taihang-Yanshan Mountains, and woodland is mainly in Chengde, Southeast Zhangjiakou, Western Baoding and Shijiazhuang. The proportion of agricultural land in the southeast plain is above 0.8. The water range in the eastern coastal area, Zhangbei, Guyuan, and western Daqing River, account for a larger proportion. The topography of the northern plateau and Taihang Yanshan Mountains undulates greatly, and the regional standard deviation is more than 100 m. The density of residential areas increases gradually from northwest to southeast. In the plain, there are dense residential areas near the urban districts. Area Ⅰ is the coastal plain area, which is easily affected by strong precipitation. Area Ⅱ is the piedmont plain area. Its grassland and woodland increase. The proportion of agricultural land in Area Ⅳ (low mountain area in the West) is larger than that in Area Ⅲ (high mountain area in the north). Area Ⅴ is the inland plain area with less precipitation.
2023, 51(2):279-286.
DOI: 10.19517/j.1671-6345.20220065
Abstract:
Based on the observation data of 88 meteorological stations in Guangxi from 1961 to 2020, the temporal and spatial variation characteristics of the first day of cold dew wind, the first day of 50% and 80% guarantee rates, and the safe heading period of double cropping late rice in Guangxi are analyzed in combination with the data of rice development period. The results show that: (1) In terms of time, the first day of the cold dew wind in Guangxi shows a slight advance trend at a rate of 0.23 days per 10 years (P<0.05), showing an asymmetric W-shaped feature; in space, the first day of cold dew wind in Guangxi is characterized by a “ladder” distribution: early at high latitudes, late at low latitudes, early in mountainous areas and late on flat lands. (2) The first day of cold dew wind in Guangxi has four cycles of 22 years, 12 years, 8 years and 3 years, of which 22 years is the main cycle of the first day of cold dew wind in Guangxi, without obvious mutation. (3) The average full heading stage of double cropping late rice in Guangxi is delayed at a rate of 0.22 days per 10 years (P<0.05), and the frequency of encountering cold dew wind during heading and flowering is 21.9%. It is suggested that the sowing date of late rice should be adjusted appropriately to make its full heading date 3 to 7 days earlier. In order to avoid being affected by the sudden cold dew wind disaster, the middle late maturing varieties of late rice should be popularized carefully in the central and northern regions of Guangxi.
Based on the observation data of 88 meteorological stations in Guangxi from 1961 to 2020, the temporal and spatial variation characteristics of the first day of cold dew wind, the first day of 50% and 80% guarantee rates, and the safe heading period of double cropping late rice in Guangxi are analyzed in combination with the data of rice development period. The results show that: (1) In terms of time, the first day of the cold dew wind in Guangxi shows a slight advance trend at a rate of 0.23 days per 10 years (P<0.05), showing an asymmetric W-shaped feature; in space, the first day of cold dew wind in Guangxi is characterized by a “ladder” distribution: early at high latitudes, late at low latitudes, early in mountainous areas and late on flat lands. (2) The first day of cold dew wind in Guangxi has four cycles of 22 years, 12 years, 8 years and 3 years, of which 22 years is the main cycle of the first day of cold dew wind in Guangxi, without obvious mutation. (3) The average full heading stage of double cropping late rice in Guangxi is delayed at a rate of 0.22 days per 10 years (P<0.05), and the frequency of encountering cold dew wind during heading and flowering is 21.9%. It is suggested that the sowing date of late rice should be adjusted appropriately to make its full heading date 3 to 7 days earlier. In order to avoid being affected by the sudden cold dew wind disaster, the middle late maturing varieties of late rice should be popularized carefully in the central and northern regions of Guangxi.
2023, 51(2):287-294.
DOI: 10.19517/j.1671-6345.20220155
Abstract:
Lowtemperature frozen characteristics and their risk assessment can provide the theoretical basis for decision-making of rape planting layout. This article uses daily weather data from 66 national ground meteorological stations in Anhui Province from 1960 to 2017. Depending on the low-temperature strength, the lowtemperature freezing damage is divided into three levels: light, medium and heavy damage, and builds a low-temperature risk index. Matlab, ArcGIS 9.3 and wavelet analysis methods have been applied to analyze the multitime scale variation characteristics of rape low-temperature freezing damage in Anhui Province for nearly 57 years. Low-temperature freezing risk zoning of rape is carried out. The results show that: (1) The distribution characteristics of different levels of low-temperature freezing damage are basically similar during the wintering of rape in Anhui Province, rendering strip distribution characteristics from south to north. High-value areas for average annual total freezing damage occur in the Huaibei area, along the Huaihe area and the Dabie mountain area. (2) Mild, moderate, severe, and total freezing damages show a significant decline; the tendency rates are 1.0, 1.0, 1.1 and 3.2 days per 10 years, respectively, during the wintering of rape in nearly 57 years, which indicates that global warming is good for rape safety in a certain extent. (3) The light-weight risk area is located in the southern region of the Huoshan-Liu’an-Hefei-Quanjiao area, which has a lower latitude, and smaller low-temperature freezing risk index, and is suitable for large-scale planting. The study conclusions can be used as a basis for the development of rape planting layout and meteorological disaster defence countermeasures.
Lowtemperature frozen characteristics and their risk assessment can provide the theoretical basis for decision-making of rape planting layout. This article uses daily weather data from 66 national ground meteorological stations in Anhui Province from 1960 to 2017. Depending on the low-temperature strength, the lowtemperature freezing damage is divided into three levels: light, medium and heavy damage, and builds a low-temperature risk index. Matlab, ArcGIS 9.3 and wavelet analysis methods have been applied to analyze the multitime scale variation characteristics of rape low-temperature freezing damage in Anhui Province for nearly 57 years. Low-temperature freezing risk zoning of rape is carried out. The results show that: (1) The distribution characteristics of different levels of low-temperature freezing damage are basically similar during the wintering of rape in Anhui Province, rendering strip distribution characteristics from south to north. High-value areas for average annual total freezing damage occur in the Huaibei area, along the Huaihe area and the Dabie mountain area. (2) Mild, moderate, severe, and total freezing damages show a significant decline; the tendency rates are 1.0, 1.0, 1.1 and 3.2 days per 10 years, respectively, during the wintering of rape in nearly 57 years, which indicates that global warming is good for rape safety in a certain extent. (3) The light-weight risk area is located in the southern region of the Huoshan-Liu’an-Hefei-Quanjiao area, which has a lower latitude, and smaller low-temperature freezing risk index, and is suitable for large-scale planting. The study conclusions can be used as a basis for the development of rape planting layout and meteorological disaster defence countermeasures.
2023, 51(2):295-301.
DOI: 10.19517/j.1671-6345.20220195
Abstract:
Based on the daily meteorological data of 35 meteorological observation stations during 1971-2020 in Dabie Mountains and DEM data, methods such as climatic statistical analysis, successive correction and trend surface interpolation are used, and the spatiotemporal distribution characteristics of the photosynthesis (YQ), photothermal (YT) and climatic potential productivity (YW) of tea, the contribution rate of climatic resources and their response to climate change are analyzed. The results show that YQ and YW of tea in Dabie Mountains show a decreasing trend, the rate of decline is 0.58 and 0.05 t·hm-2 per 10 years, YT show an increasing trend, the rate of increase is 0.36 t·hm-2 per 10 years. In spatial distribution, YQ increases with latitude, YT decreases with latitude and altitude, and YW decreases with latitude and increases with altitude. The contribution rates of solar radiation, temperature and precipitation to YW are 26%, 48% and 26%, respectively. The increase in temperature is offset by the decrease in solar radiation and precipitation, resulting in a general dynamic equilibrium trend. Under the background of climate change, the decreasing trend of YQ in the northern part of the Dabie Mountains is more obvious than that in the southern part. The increasing trend of YT in the southern part is more obvious than that in the northern part. The YW in the low-altitude area is increasing, and that in the high-altitude area is decreasing. The results of this study can provide the scientific basis for the tea industry in Dabie Mountains to make full use of climate resources, pursue advantages and avoid disadvantages efficiently, and optimize industrial layout rationally.
Based on the daily meteorological data of 35 meteorological observation stations during 1971-2020 in Dabie Mountains and DEM data, methods such as climatic statistical analysis, successive correction and trend surface interpolation are used, and the spatiotemporal distribution characteristics of the photosynthesis (YQ), photothermal (YT) and climatic potential productivity (YW) of tea, the contribution rate of climatic resources and their response to climate change are analyzed. The results show that YQ and YW of tea in Dabie Mountains show a decreasing trend, the rate of decline is 0.58 and 0.05 t·hm-2 per 10 years, YT show an increasing trend, the rate of increase is 0.36 t·hm-2 per 10 years. In spatial distribution, YQ increases with latitude, YT decreases with latitude and altitude, and YW decreases with latitude and increases with altitude. The contribution rates of solar radiation, temperature and precipitation to YW are 26%, 48% and 26%, respectively. The increase in temperature is offset by the decrease in solar radiation and precipitation, resulting in a general dynamic equilibrium trend. Under the background of climate change, the decreasing trend of YQ in the northern part of the Dabie Mountains is more obvious than that in the southern part. The increasing trend of YT in the southern part is more obvious than that in the northern part. The YW in the low-altitude area is increasing, and that in the high-altitude area is decreasing. The results of this study can provide the scientific basis for the tea industry in Dabie Mountains to make full use of climate resources, pursue advantages and avoid disadvantages efficiently, and optimize industrial layout rationally.
2023, 51(2):302-308.
DOI: 10.19517/j.1671-6345.20220123
Abstract:
The data used in this study includes cherry phenological observation data and temperature observation data in the cherry planting area for 2018-2020 and the temperature data of the national automatic meteorological observation station in 2006-2020 in Shijiazhuang. The research period is determined by adopting mathematical statistical methods, and the meteorological indicators of cherry fertility are delineated according to the GDD(Growing Degree Days) model. Subsequently, by referring to the “Crop Frost Damage Grade”, the daily minimum temperature, the daily average temperature and duration are selected as the elements of the low-temperature freezing injury index in this paper. The linear regression model between low-temperature freezing injury index and yield reduction rate is established. Compared to the four probability distribution models, including poisson distribution, information diffusion method, normal distribution and Weber distribution, the results show that the information diffusion method passes the chi-square goodness of fit test, and its RMSE value of the model is the minimum. Therefore, the information diffusion method is the most suitable low-temperature freezing injury index distribution model. The study finally determines the weather index insurance net premium rate under different trigger conditions of low-temperature freezing injury in Shijiazhuang. The maximum rate is 2.045%, and the minimum is 0.173%. At the same time, this study finds that in the case of a small amount of data, the distribution pattern of the information diffusion method model is more consistent with the real probability distribution pattern. And this model provides a theoretical model for the crop weather index insurance products, for which long-series observations have yet to be conducted.
The data used in this study includes cherry phenological observation data and temperature observation data in the cherry planting area for 2018-2020 and the temperature data of the national automatic meteorological observation station in 2006-2020 in Shijiazhuang. The research period is determined by adopting mathematical statistical methods, and the meteorological indicators of cherry fertility are delineated according to the GDD(Growing Degree Days) model. Subsequently, by referring to the “Crop Frost Damage Grade”, the daily minimum temperature, the daily average temperature and duration are selected as the elements of the low-temperature freezing injury index in this paper. The linear regression model between low-temperature freezing injury index and yield reduction rate is established. Compared to the four probability distribution models, including poisson distribution, information diffusion method, normal distribution and Weber distribution, the results show that the information diffusion method passes the chi-square goodness of fit test, and its RMSE value of the model is the minimum. Therefore, the information diffusion method is the most suitable low-temperature freezing injury index distribution model. The study finally determines the weather index insurance net premium rate under different trigger conditions of low-temperature freezing injury in Shijiazhuang. The maximum rate is 2.045%, and the minimum is 0.173%. At the same time, this study finds that in the case of a small amount of data, the distribution pattern of the information diffusion method model is more consistent with the real probability distribution pattern. And this model provides a theoretical model for the crop weather index insurance products, for which long-series observations have yet to be conducted.
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.