ISSN 1000-0526
CN 11-2282/P
CN 11-2282/P
Volume 46,Issue 5,2020 Table of Contents
ZHENG Yongguang
,
LAN Yu
,
CAO Yancha
,
ZHANG Xiaoling
,
CHEN Chuanlei
,
ZHU Wenjian
,
ZHANG Xiaowen
,
GUAN Liang
,
SHENG Jie
,
TANG Wenyuan
,
ZHOU Xiaomin
,
YANG Bo
,
ZHANG Tao
,
FANG Chong
2020, 46(5):589-602.
DOI: 10.7519/j.issn.1000-0526.2020.05.001
Abstract:
Based on multi-source observations with high spatio-temporal resolution, we present in detail the synoptic situation, environmental conditions, triggering and evolution characteristics of the convective storm, and formation and demise mechanisms of the EF4 tornado in Kaiyuan, Liaoning Province on the afternoon of 3 July 2019 in this paper. The Kaiyuan tornado occurred under the 500 hPa northwesterly airflow and the 850 hPa shear line in the southwest side of a cold vortex over Northeast China, and in the strong warm and moist southwesterly airflow at the surface. Except for the low relative humidity in the middle and lower troposphere and the higher lifting condensation level which were unfavorable for the tornado, other favorable environmental conditions for mesocyclonic tornado were all satisfied. However, winds of the Shenyang wind-profiling radar and radial velocity of Shenyang weather radar both show that the enhanced 0-1 km vertical wind shear had a mesoscale feature indicating that the coupling between the boundary layer jet and the mid-level jet formed strong vertical wind shear favorable for the EF4 tornado. The Kaiyuan tornado was generated by an isolated supercell with typical supercell radar echo features, an intense mesocyclone and tornadic vortex signature, etc. The strom was triggered by both a dryline and a convergence line of gust front to the east of the dryline. The rainfall produced in the front of the storm first made the atmosphere rapidly saturated over Kaiyuan and its vicinity. When the hook echo part at the back of the storm moved to Kaiyuan and its vicinity, the significantly improved low-level moisture condition was good for the less strong downdraft of the storm to generate the cold pool with suitable intensity. So the storm, with the suitable cold pool, strong warm and moist boundary-layer air inflow, strong low-level and mid-level vertical wind shear, and intense updraft, produced the EF4 tornado in Kaiyuan. The temperature distribution from automatic weather stations shows that the temperature differences between cold pool of the storm and the ambient atmosphere were 2-4℃, favorable for Kaiyuan tornadogenesis. While the strong downdraft of the storm produced the intense cold pool with the temperature difference up to 7℃ from the environmental atmosphere, it destroyed the maintenance of vertical vorticity near the ground and then caused the demise of the Kaiyuan tornado.
Based on multi-source observations with high spatio-temporal resolution, we present in detail the synoptic situation, environmental conditions, triggering and evolution characteristics of the convective storm, and formation and demise mechanisms of the EF4 tornado in Kaiyuan, Liaoning Province on the afternoon of 3 July 2019 in this paper. The Kaiyuan tornado occurred under the 500 hPa northwesterly airflow and the 850 hPa shear line in the southwest side of a cold vortex over Northeast China, and in the strong warm and moist southwesterly airflow at the surface. Except for the low relative humidity in the middle and lower troposphere and the higher lifting condensation level which were unfavorable for the tornado, other favorable environmental conditions for mesocyclonic tornado were all satisfied. However, winds of the Shenyang wind-profiling radar and radial velocity of Shenyang weather radar both show that the enhanced 0-1 km vertical wind shear had a mesoscale feature indicating that the coupling between the boundary layer jet and the mid-level jet formed strong vertical wind shear favorable for the EF4 tornado. The Kaiyuan tornado was generated by an isolated supercell with typical supercell radar echo features, an intense mesocyclone and tornadic vortex signature, etc. The strom was triggered by both a dryline and a convergence line of gust front to the east of the dryline. The rainfall produced in the front of the storm first made the atmosphere rapidly saturated over Kaiyuan and its vicinity. When the hook echo part at the back of the storm moved to Kaiyuan and its vicinity, the significantly improved low-level moisture condition was good for the less strong downdraft of the storm to generate the cold pool with suitable intensity. So the storm, with the suitable cold pool, strong warm and moist boundary-layer air inflow, strong low-level and mid-level vertical wind shear, and intense updraft, produced the EF4 tornado in Kaiyuan. The temperature distribution from automatic weather stations shows that the temperature differences between cold pool of the storm and the ambient atmosphere were 2-4℃, favorable for Kaiyuan tornadogenesis. While the strong downdraft of the storm produced the intense cold pool with the temperature difference up to 7℃ from the environmental atmosphere, it destroyed the maintenance of vertical vorticity near the ground and then caused the demise of the Kaiyuan tornado.
ZHANG Tao
,
GUAN Liang
,
ZHENG Yongguang
,
CHEN Chuanlei
,
CAI Kuizhi
,
LI Deqin
,
CUI Shengquan
,
WU Yun
,
ZHANG Xiaoling
,
YANG Bo
,
LAN Yu
2020, 46(5):603-617.
DOI: 10.7519/j.issn.1000-0526.2020.05.002
Abstract:
On July 3, 2019, a violent tornado, which was recorded by video in detail, occurred in Kaiyuan City, Tieling, Liaoning Province. Based on the detailed damage survey and video data, this paper presents the lifecycle, occurrence time, path, disaster width and intensity distribution of the tornado. It is found that the weakening or strengthening of the tornado intensity was significantly related to the underlying surface conditions of dense high buildings and open field areas. According to the comprehensive assessment, the maximum intensity of this tornado is Level 4 (equivalent to EF4 in the United States), but the distribution range of the Level 4 disaster was very small, and the disaster distribution width and the range of Level 4 disaster were significantly smaller than the EF4 tornado in Funing, Jiangsu Province in 2016. The main structure of residential buildings with reinforced concrete frame structure remained almost intact after striking of the tornado with EF3 intensity at least, while the defense ability of largescale steel frame plant to tornado disaster was far worse than that of residential buildings. The areas through which the powerfull tornado passed are mostly wilderness and factories. Fewer people were affected and there were good views when the tornado occurred, which is an important reason why the tornado did not cause more serious disasters. Due to the complexity of underlying surface conditions and disaster mechanism, there must be some uncertainty in the estimation of the tornado strength.
On July 3, 2019, a violent tornado, which was recorded by video in detail, occurred in Kaiyuan City, Tieling, Liaoning Province. Based on the detailed damage survey and video data, this paper presents the lifecycle, occurrence time, path, disaster width and intensity distribution of the tornado. It is found that the weakening or strengthening of the tornado intensity was significantly related to the underlying surface conditions of dense high buildings and open field areas. According to the comprehensive assessment, the maximum intensity of this tornado is Level 4 (equivalent to EF4 in the United States), but the distribution range of the Level 4 disaster was very small, and the disaster distribution width and the range of Level 4 disaster were significantly smaller than the EF4 tornado in Funing, Jiangsu Province in 2016. The main structure of residential buildings with reinforced concrete frame structure remained almost intact after striking of the tornado with EF3 intensity at least, while the defense ability of largescale steel frame plant to tornado disaster was far worse than that of residential buildings. The areas through which the powerfull tornado passed are mostly wilderness and factories. Fewer people were affected and there were good views when the tornado occurred, which is an important reason why the tornado did not cause more serious disasters. Due to the complexity of underlying surface conditions and disaster mechanism, there must be some uncertainty in the estimation of the tornado strength.
2020, 46(5):618-628.
DOI: 10.7519/j.issn.1000-0526.2020.05.003
Abstract:
The historical severe convections from 2006 to 2015 in the warm season were classified into three types, namely hail, thunderstorm gale and short-term heavy rain, occurring at the national meteorological automatic stations in Henan Province. The physical parameters and their 15 d moving average values are calculated based on ECMWF reanalysis data, indicating the environmental characteristics such as vapor, thermal and dynamical conditions, and then the monthly characteristics are comparatively analyzed with the key parameters to classify convections selected, considering the influence of monthly change and the variety of climate background. The results showed that the frequency of short-time severe precipitation is the highest while that of hail is the lowest. All kinds of severe precipitation mainly occur in the afternoon (14:00 BT-20:00 BT). The inter-monthly variation of parameters is so prominent that the different parameter thresholds are advisable in the potential forecast monthly. The parameter deviations from the moving climate mean are also valuable for the classification and obviously vary in the different environmental conditions. The monthly characteristics of most parameters for the short-time severe precipitation are significantly distinct from the hail, such as the larger indices of precipitable water, ground dew point temperature, K index, 0℃ and -20℃ level heights, stronger vertical wind shear, convergence and positive vorticity in the lower level, and the less temperature difference between 850 and 500 hPa and CAPE. Most parameters for hail are similar to those of thunderstorm gale with less precipitable water and ground dew point temperature, lower 0 ℃ and -20 ℃ level heights, and stronger convergence and positive vorticity in the upper level, especially in July and August.
The historical severe convections from 2006 to 2015 in the warm season were classified into three types, namely hail, thunderstorm gale and short-term heavy rain, occurring at the national meteorological automatic stations in Henan Province. The physical parameters and their 15 d moving average values are calculated based on ECMWF reanalysis data, indicating the environmental characteristics such as vapor, thermal and dynamical conditions, and then the monthly characteristics are comparatively analyzed with the key parameters to classify convections selected, considering the influence of monthly change and the variety of climate background. The results showed that the frequency of short-time severe precipitation is the highest while that of hail is the lowest. All kinds of severe precipitation mainly occur in the afternoon (14:00 BT-20:00 BT). The inter-monthly variation of parameters is so prominent that the different parameter thresholds are advisable in the potential forecast monthly. The parameter deviations from the moving climate mean are also valuable for the classification and obviously vary in the different environmental conditions. The monthly characteristics of most parameters for the short-time severe precipitation are significantly distinct from the hail, such as the larger indices of precipitable water, ground dew point temperature, K index, 0℃ and -20℃ level heights, stronger vertical wind shear, convergence and positive vorticity in the lower level, and the less temperature difference between 850 and 500 hPa and CAPE. Most parameters for hail are similar to those of thunderstorm gale with less precipitable water and ground dew point temperature, lower 0 ℃ and -20 ℃ level heights, and stronger convergence and positive vorticity in the upper level, especially in July and August.
2020, 46(5):629-642.
DOI: 10.7519/j.issn.1000-0526.2020.05.004
Abstract:
Based on the data of dual polarization Doppler radar, wind-profiling radar, disdrometer, dual-Doppler radar retrieval, automatic weather stations and FNL reanalysis data, this paper analyzes the mesoscale characteristics of warm-sector torrential rain in southeastern coast of Fujian Province on 7 May 2018. The results show that this torrential rain process occurred inside the strong ultra-low-level southwest jet. The pulsation feature of ultra-low-level jet was obvious. Sudden enhancement of the jet favored the low-level disturbance, which caused significant low-level convergence. Deep southwest jet led to high consistency of convective echo pattern and echo moving direction, causing multiple severe convective systems to pass the same area repeatedly (a train effect), which was an important reason for the severe rainfall to last such a long time. There existed both wind speed and direction convergence inside the strong echo in horizontal direction. In vertical direction, there was significant wave-like motion in the echo band with the ascending motion in the front of the strong echo. This could guide echo to move northeastward. At the same time, there was significant compensatory secondary circulation in 〖JP2〗southeast of the strong echo, maintaining low-level convergence and the upstream.〖JP〗 In addition, high concentration of small raindrops with a few large raindrops was the main cloud microphysical characteristics of this warm-sector torrential rain.
Based on the data of dual polarization Doppler radar, wind-profiling radar, disdrometer, dual-Doppler radar retrieval, automatic weather stations and FNL reanalysis data, this paper analyzes the mesoscale characteristics of warm-sector torrential rain in southeastern coast of Fujian Province on 7 May 2018. The results show that this torrential rain process occurred inside the strong ultra-low-level southwest jet. The pulsation feature of ultra-low-level jet was obvious. Sudden enhancement of the jet favored the low-level disturbance, which caused significant low-level convergence. Deep southwest jet led to high consistency of convective echo pattern and echo moving direction, causing multiple severe convective systems to pass the same area repeatedly (a train effect), which was an important reason for the severe rainfall to last such a long time. There existed both wind speed and direction convergence inside the strong echo in horizontal direction. In vertical direction, there was significant wave-like motion in the echo band with the ascending motion in the front of the strong echo. This could guide echo to move northeastward. At the same time, there was significant compensatory secondary circulation in 〖JP2〗southeast of the strong echo, maintaining low-level convergence and the upstream.〖JP〗 In addition, high concentration of small raindrops with a few large raindrops was the main cloud microphysical characteristics of this warm-sector torrential rain.
2020, 46(5):643-654.
DOI: 10.7519/j.issn.1000-0526.2020.05.005
Abstract:
Two line convections hit Beijing Area successively and caused shorttime heavy rainfalls, gales and small hails on 7 July 2017. In this paper, the two cases were compared based on the high spatiotemporal resolution observations and the Variational Doppler Radar Analysis System (VDRAS) dataset. Both of the line convections were formed on the mountains in Zhangjiakou, located to the northwest of Beijing, and developed at the foothills and on the plains. However, they had different boundary layer conditions, as the second one developed on the cold mass caused by the first one. The results are shown as follows. The first line convection developed into a squall line benefited from both dynamic and thermodynamic conditions of the foothills and the plains, which includes the hot and humid environment in the boundary layer, the convergence line generated by the outflows of the cold pool and the lowlevel environmental southerly wind. At its mature phase, the squall line had the strongest convergence from surface to the height of 1.5 km and an approximately vertical updraft. The second line convection developed into an elevated convection on the cold mass caused by the previous one. The area of strong echo (≥45 dBz) maintained, though the updraft tilted and had a certain decrease. The thermodynamic conditions seemed to be no longer beneficial due to the wide and strong cold mass caused by the first one. The outflows from the two lines formed a convergence line, and the convergence line intensified especially when the cold mass of the second one met the cold mass caused by the first one, which offered dynamic conditions for the second one. The unstable layer above the boundary layer provided convective energy for the elevated convection. Besides, the rebuilt of convective available potential energy (CAPE) after the first convection is possible as warm advection and positive water vapour transport did exist in Beijing Area. Above all, both dynamic and thermodynamic conditions should be 〖JP2〗considered in nowcasting of convective storms, where VDRAS could play a positive role.
Two line convections hit Beijing Area successively and caused shorttime heavy rainfalls, gales and small hails on 7 July 2017. In this paper, the two cases were compared based on the high spatiotemporal resolution observations and the Variational Doppler Radar Analysis System (VDRAS) dataset. Both of the line convections were formed on the mountains in Zhangjiakou, located to the northwest of Beijing, and developed at the foothills and on the plains. However, they had different boundary layer conditions, as the second one developed on the cold mass caused by the first one. The results are shown as follows. The first line convection developed into a squall line benefited from both dynamic and thermodynamic conditions of the foothills and the plains, which includes the hot and humid environment in the boundary layer, the convergence line generated by the outflows of the cold pool and the lowlevel environmental southerly wind. At its mature phase, the squall line had the strongest convergence from surface to the height of 1.5 km and an approximately vertical updraft. The second line convection developed into an elevated convection on the cold mass caused by the previous one. The area of strong echo (≥45 dBz) maintained, though the updraft tilted and had a certain decrease. The thermodynamic conditions seemed to be no longer beneficial due to the wide and strong cold mass caused by the first one. The outflows from the two lines formed a convergence line, and the convergence line intensified especially when the cold mass of the second one met the cold mass caused by the first one, which offered dynamic conditions for the second one. The unstable layer above the boundary layer provided convective energy for the elevated convection. Besides, the rebuilt of convective available potential energy (CAPE) after the first convection is possible as warm advection and positive water vapour transport did exist in Beijing Area. Above all, both dynamic and thermodynamic conditions should be 〖JP2〗considered in nowcasting of convective storms, where VDRAS could play a positive role.
2020, 46(5):655-665.
DOI: 10.7519/j.issn.1000-0526.2020.05.006
Abstract:
To explore the applicability of terrain-considered spatial interpolation method in complex underlying surface region, the interpolation tests using regional automatic weather station observation data of monthly accumulated precipitation and average temperature in Chongqing in 2017 were designed by Cokriging, PRISM and IDW interpolation methods. The results showed that when a large number of samples are used, for average temperature, Cokriging and IDW have similar interpolation errors, which are lager than PRISM’s. For accumulated precipitation, two terrain-considered methods have similar errors and both are slightly lower than IDW. The accuracy of all three methods would decrease when using fewer observation samples, but PRISM has the lowest decrement rate in average temperature interpolation and highest decrement rate in precipitation interpolation. PRISM and Cokriging have the lowest errors for temperature and precipitation respectively when using small amounts of samples. Further analysis shows that PRISM can reduce the temperature interpolation error of complex terrain region significantly, but since the errors of accumulated precipitation are mainly based on precipitation intensity, the terrain-considered interpolation method may not have obvious advantage.
To explore the applicability of terrain-considered spatial interpolation method in complex underlying surface region, the interpolation tests using regional automatic weather station observation data of monthly accumulated precipitation and average temperature in Chongqing in 2017 were designed by Cokriging, PRISM and IDW interpolation methods. The results showed that when a large number of samples are used, for average temperature, Cokriging and IDW have similar interpolation errors, which are lager than PRISM’s. For accumulated precipitation, two terrain-considered methods have similar errors and both are slightly lower than IDW. The accuracy of all three methods would decrease when using fewer observation samples, but PRISM has the lowest decrement rate in average temperature interpolation and highest decrement rate in precipitation interpolation. PRISM and Cokriging have the lowest errors for temperature and precipitation respectively when using small amounts of samples. Further analysis shows that PRISM can reduce the temperature interpolation error of complex terrain region significantly, but since the errors of accumulated precipitation are mainly based on precipitation intensity, the terrain-considered interpolation method may not have obvious advantage.
2020, 46(5):666-674.
DOI: 10.7519/j.issn.1000-0526.2020.05.007
Abstract:
Climatic characteristics and changes of glaze days in China were analyzed with the daily glaze observational dataset at 2426 stations in China from 1954 to 2017. China’s glaze mainly occurs in Xinjiang and the parts east to 103°E of China. There are three major glaze zones: the area cross the borders of Shaanxi, Gansu and Ningxia provinces, the area of Henan and eastern Hubei provinces, and the area of Jiangxi, Hunan and Guizhou provinces, of which the third area is the central area, with 5-50 glaze days per year in average at every station. The 128 glaze days when glaze occurs in Mountain Emei at an altitude of 3 〖KG-*5〗047 meters are the most in China. In the glaze region south of the Yellow River, the glaze days at the stations with altitude more than 1 〖KG-*5〗000 meters are possibly more. The glaze occurs from September to May of next year, showing a peak pattern distribution with a beginning of glaze mainly from winter season when the cold air is the most active from January to mid-February. The probability of number of glaze days has obvious interdecadal variation characteristics, and it is significantly higher during the first 26 years than the latter 30 years during 1961-2016. From 1961 to 2016, the total number of glaze days in China is decreasing, and the area of glaze is significantly reduced since 1990 except for the main area of Guizhou and Hunan provinces.
Climatic characteristics and changes of glaze days in China were analyzed with the daily glaze observational dataset at 2426 stations in China from 1954 to 2017. China’s glaze mainly occurs in Xinjiang and the parts east to 103°E of China. There are three major glaze zones: the area cross the borders of Shaanxi, Gansu and Ningxia provinces, the area of Henan and eastern Hubei provinces, and the area of Jiangxi, Hunan and Guizhou provinces, of which the third area is the central area, with 5-50 glaze days per year in average at every station. The 128 glaze days when glaze occurs in Mountain Emei at an altitude of 3 〖KG-*5〗047 meters are the most in China. In the glaze region south of the Yellow River, the glaze days at the stations with altitude more than 1 〖KG-*5〗000 meters are possibly more. The glaze occurs from September to May of next year, showing a peak pattern distribution with a beginning of glaze mainly from winter season when the cold air is the most active from January to mid-February. The probability of number of glaze days has obvious interdecadal variation characteristics, and it is significantly higher during the first 26 years than the latter 30 years during 1961-2016. From 1961 to 2016, the total number of glaze days in China is decreasing, and the area of glaze is significantly reduced since 1990 except for the main area of Guizhou and Hunan provinces.
2020, 46(5):675-686.
DOI: 10.7519/j.issn.1000-0526.2020.05.008
Abstract:
Three serious PM2.5 pollution events which occurred in Shanghai on 29 October, 2-3 November and 7-8 November 2017 were investigated. They can be divided into two pollution types according to atmospheric circulation as follows. The pollution event on October 29 was transport pollution which features fast transportation and short period of pollution; the other two are static stability superimposed transport pollution which features slow transportation and long duration. By analyzing the weather conditions of the three pollution events, we found that the low wind speed, stable vertical stratification and descending motion made air pollutants difficult to disperse. The crosssections of the PM2.5 concentration, 〖JP2〗surface meteo〖JP〗rological elements and vertical circulation from Beijing to Shanghai showed that the pollution belt was distributed in a narrow strip from north to south on October 29, and the wind which was in the midlow level and the near surface layer contributed to the pollution transport in Shanghai; the two pollution events in November had longer durations and wider ranges, and the pollution transport channel of Shanghai was the near surface layer. Calculating the stable weather index and the transport intensity index of the three pollution events were also carried out to prove that the pollution on October 29 was caused by transportation and the other two were caused by the local accumulation and transportation. By using the FLEXPART model and the 〖JP2〗Regional Atmospheric Environmental Modeling System for Eastern China (RAEMS). It was found that the potential sources of the two pollution processes in November were all around Shanghai, and the sources were concentrated, with coutributions from Jiangsu, Zhejiang, and Anhui.
Three serious PM2.5 pollution events which occurred in Shanghai on 29 October, 2-3 November and 7-8 November 2017 were investigated. They can be divided into two pollution types according to atmospheric circulation as follows. The pollution event on October 29 was transport pollution which features fast transportation and short period of pollution; the other two are static stability superimposed transport pollution which features slow transportation and long duration. By analyzing the weather conditions of the three pollution events, we found that the low wind speed, stable vertical stratification and descending motion made air pollutants difficult to disperse. The crosssections of the PM2.5 concentration, 〖JP2〗surface meteo〖JP〗rological elements and vertical circulation from Beijing to Shanghai showed that the pollution belt was distributed in a narrow strip from north to south on October 29, and the wind which was in the midlow level and the near surface layer contributed to the pollution transport in Shanghai; the two pollution events in November had longer durations and wider ranges, and the pollution transport channel of Shanghai was the near surface layer. Calculating the stable weather index and the transport intensity index of the three pollution events were also carried out to prove that the pollution on October 29 was caused by transportation and the other two were caused by the local accumulation and transportation. By using the FLEXPART model and the 〖JP2〗Regional Atmospheric Environmental Modeling System for Eastern China (RAEMS). It was found that the potential sources of the two pollution processes in November were all around Shanghai, and the sources were concentrated, with coutributions from Jiangsu, Zhejiang, and Anhui.
2020, 46(5):687-694.
DOI: 10.7519/j.issn.1000-0526.2020.05.009
Abstract:
Using HYSPLIT (Hybrid Single Particle Lagrangian Integrated Trajectory) model and ERA_INTERIM data, this paper calculated the 72 h backward trajectories in February during 2013-2017 starting from the Beijing National Olympic Sports Center (hereinafter referred to as Sports Center). Combined with cluster analysis and pollutant concentration data in the Sports Center, the influence of different trajectory paths on the concentration of pollutants in the Sports Center was analyzed. Four different trajectory analysis methods were used to analyze the source characteristics of the pollutants in the Sports Center, and then its advantages, disadvantages and applicability were illustrated by examples. The results showed that the dominant airflow in the Sports Center is obvious in February, following the northwestern path with a probability of 55.85%. The cleaning path is northward airflow, and the pollution sources are a southward path and an eastward path, corresponding to the highest particulate matter concentration. By trajectory statistical method, the main sources of particulate matter at the Sports Center in February are Hebei Pro-vince, Shandong Peninsula, Yellow Sea Region, northern Xinjiang and Hexi Corridor. The PSCF and CWT methods are suitable for close-range pollution source identification. In the method of RTWC, the deterministic method is used to accurately identify the main pollutant sources of the Sports Center through iteration. The QTBA method introduces the concept of uncertainty, which is suitable for the identification of a wide range of deterministic sources of pollution, but at the same time it produces some false pollutant sources. However, the combination of the RTWC method and the QTBA method can eliminate the false pollution sources brought by the QTBA method.
Using HYSPLIT (Hybrid Single Particle Lagrangian Integrated Trajectory) model and ERA_INTERIM data, this paper calculated the 72 h backward trajectories in February during 2013-2017 starting from the Beijing National Olympic Sports Center (hereinafter referred to as Sports Center). Combined with cluster analysis and pollutant concentration data in the Sports Center, the influence of different trajectory paths on the concentration of pollutants in the Sports Center was analyzed. Four different trajectory analysis methods were used to analyze the source characteristics of the pollutants in the Sports Center, and then its advantages, disadvantages and applicability were illustrated by examples. The results showed that the dominant airflow in the Sports Center is obvious in February, following the northwestern path with a probability of 55.85%. The cleaning path is northward airflow, and the pollution sources are a southward path and an eastward path, corresponding to the highest particulate matter concentration. By trajectory statistical method, the main sources of particulate matter at the Sports Center in February are Hebei Pro-vince, Shandong Peninsula, Yellow Sea Region, northern Xinjiang and Hexi Corridor. The PSCF and CWT methods are suitable for close-range pollution source identification. In the method of RTWC, the deterministic method is used to accurately identify the main pollutant sources of the Sports Center through iteration. The QTBA method introduces the concept of uncertainty, which is suitable for the identification of a wide range of deterministic sources of pollution, but at the same time it produces some false pollutant sources. However, the combination of the RTWC method and the QTBA method can eliminate the false pollution sources brought by the QTBA method.
2020, 46(5):695-704.
DOI: 10.7519/j.issn.1000-0526.2020.05.010
Abstract:
The spatio-temporal distribution characteristics of haze and the climatic background were analyzed by using the daily haze abservations from 83 meteorological stations from 1964 to 2013 and the statistical method of linear regression.The results showed that haze days are significantly more in central and northern Jiangxi than in southern Jiangxi. The annual haze days more than 30 d appear in central Jiangxi, including Pingxiang, Yichun, Fuzhou and Shangrao, and also in northern Jiangxi, including central Jiujiang and northern Jingdezhen. The haze days are maximum in winter, followed by autumn and spring, and the minimum in summer. The central and northern parts of Pingxiang, Yichun and Yingtan and the central part of Nanchang and Jiujiang as well as the eastern part of Shangrao have more than 20 haze days per year. The haze days are the most in December, 〖JP2〗nearly 20% of annual haze days. The haze days in Jiangxi〖JP〗 Province present a significant increasing trend with the increase rate 11 d per decade from 1964 to 2013 and the climatic trend coefficient is 0.78, which has passed the significance test at 0.01 level. The correlation coefficient between the haze days and the mean wind speed and strong wind days is negative, but is positive between haze days and calm days in Jiangxi. In the past 50 years, the annual averaged wind days and stong wind days show a downward trend, while the calm days show an upward trend, which may cause the accumulation of pollutants in the air to form more haze weather. The correlation coefficient between haze days and precipitation days is mainly negative and the precipitation days show a decreasing trend in Jiangxi，with the rate of around -6.3 d·（10 a）-1. The correlation coefficient between 〖JP2〗haze days and temperature is positive and the temperature shows an increasing trend in Jiangxi， with the rate of around 0.15℃·（10 a）-1.
The spatio-temporal distribution characteristics of haze and the climatic background were analyzed by using the daily haze abservations from 83 meteorological stations from 1964 to 2013 and the statistical method of linear regression.The results showed that haze days are significantly more in central and northern Jiangxi than in southern Jiangxi. The annual haze days more than 30 d appear in central Jiangxi, including Pingxiang, Yichun, Fuzhou and Shangrao, and also in northern Jiangxi, including central Jiujiang and northern Jingdezhen. The haze days are maximum in winter, followed by autumn and spring, and the minimum in summer. The central and northern parts of Pingxiang, Yichun and Yingtan and the central part of Nanchang and Jiujiang as well as the eastern part of Shangrao have more than 20 haze days per year. The haze days are the most in December, 〖JP2〗nearly 20% of annual haze days. The haze days in Jiangxi〖JP〗 Province present a significant increasing trend with the increase rate 11 d per decade from 1964 to 2013 and the climatic trend coefficient is 0.78, which has passed the significance test at 0.01 level. The correlation coefficient between the haze days and the mean wind speed and strong wind days is negative, but is positive between haze days and calm days in Jiangxi. In the past 50 years, the annual averaged wind days and stong wind days show a downward trend, while the calm days show an upward trend, which may cause the accumulation of pollutants in the air to form more haze weather. The correlation coefficient between haze days and precipitation days is mainly negative and the precipitation days show a decreasing trend in Jiangxi，with the rate of around -6.3 d·（10 a）-1. The correlation coefficient between 〖JP2〗haze days and temperature is positive and the temperature shows an increasing trend in Jiangxi， with the rate of around 0.15℃·（10 a）-1.
2020, 46(5):705-715.
DOI: 10.7519/j.issn.1000-0526.2020.05.011
Abstract:
The heavy rainfall occurred on 16 July 2018 in Beijing resulted in a series of serious hazards such as urban water logging and collapse hazards. Starting with the analysis on the features of rain regime and its associated geological hazard situations, this paper mainly analyzes and summarizes the forecast and verification on the early warning of meteorological geological hazards for this kind of extremely intense rainfall. Based on the detailed information of geological hazards, this study further analyzes the causes of geological hazards in Beijing by combining the characteristics of rainfall intensity, soil moisture and the runoff evolution (derived from the CREST model driven by quantitative precipitation estimation data). The results indicate that the northern and western parts of Beijing are areas characterized by the mid- and high-risk susceptibility degree, the accumulated area-rainfall beyond 50 mm is prone to result in the occurrence of geological hazards and the occurrence time is during the next 15 h after the high peak of precipitation. Based on the rainfall intensity and precipitation duration, the threshold of critical rainfall of geological hazards can be derived as a reference for geological hazard meteorological forecast in the area. The simulation of hydrological process elements such as runoff, depth of overland flow, and soil moisture of hydrological model also has a good guiding significance for early warning of meteorological geological hazards in Beijing.
The heavy rainfall occurred on 16 July 2018 in Beijing resulted in a series of serious hazards such as urban water logging and collapse hazards. Starting with the analysis on the features of rain regime and its associated geological hazard situations, this paper mainly analyzes and summarizes the forecast and verification on the early warning of meteorological geological hazards for this kind of extremely intense rainfall. Based on the detailed information of geological hazards, this study further analyzes the causes of geological hazards in Beijing by combining the characteristics of rainfall intensity, soil moisture and the runoff evolution (derived from the CREST model driven by quantitative precipitation estimation data). The results indicate that the northern and western parts of Beijing are areas characterized by the mid- and high-risk susceptibility degree, the accumulated area-rainfall beyond 50 mm is prone to result in the occurrence of geological hazards and the occurrence time is during the next 15 h after the high peak of precipitation. Based on the rainfall intensity and precipitation duration, the threshold of critical rainfall of geological hazards can be derived as a reference for geological hazard meteorological forecast in the area. The simulation of hydrological process elements such as runoff, depth of overland flow, and soil moisture of hydrological model also has a good guiding significance for early warning of meteorological geological hazards in Beijing.
2020, 46(5):716-724.
DOI: 10.7519/j.issn.1000-0526.2020.05.012
Abstract:
This article analyzes the diurnal variation of road surface temperature in the different weather conditions for winter and summer in Beijing. Based on the 2012-2015 data of the road stations and the corresponding forecasting model outputs, the multiple linear regression statistical forecasting models 〖JP2〗are built to predict the road mini〖JP〗mum temperature in winter and the maximum temperature in summer with the different correlative factors from the selected 5 representative road stations. Then the best forecasting model is chosen to make an assessment for winters and summers from 2016 to 2017. The results show that there exists a significant diurnal variation for the road surface temperature, suggesting that the road surface temperature is obviously different under different kinds of weather conditions.〖JP〗 The road surface temperature is correlated to air temperature, atmospheric radiation and sunshine duration. In addition, the prediction accuracy of summer forecasting models for the various weather conditions is improved. Under the fair to cloudy condition, the errors of forecasting models could be controlled within the ± 2℃ in winter and ±3℃ in summer, but it is worse under the other weather conditions. The models show a better performence in terms of the minimum temperature forecast in winter compared to the maximum temperature forecast in summer.
This article analyzes the diurnal variation of road surface temperature in the different weather conditions for winter and summer in Beijing. Based on the 2012-2015 data of the road stations and the corresponding forecasting model outputs, the multiple linear regression statistical forecasting models 〖JP2〗are built to predict the road mini〖JP〗mum temperature in winter and the maximum temperature in summer with the different correlative factors from the selected 5 representative road stations. Then the best forecasting model is chosen to make an assessment for winters and summers from 2016 to 2017. The results show that there exists a significant diurnal variation for the road surface temperature, suggesting that the road surface temperature is obviously different under different kinds of weather conditions.〖JP〗 The road surface temperature is correlated to air temperature, atmospheric radiation and sunshine duration. In addition, the prediction accuracy of summer forecasting models for the various weather conditions is improved. Under the fair to cloudy condition, the errors of forecasting models could be controlled within the ± 2℃ in winter and ±3℃ in summer, but it is worse under the other weather conditions. The models show a better performence in terms of the minimum temperature forecast in winter compared to the maximum temperature forecast in summer.
2020, 46(5):725-732.
DOI: 10.7519/j.issn.1000-0526.2020.05.013
Abstract:
The main characteristics of the general atmospheric circulation in February 2020 are as follows. There were two polar vortex centers in the Northern Hemisphere and they were stronger than normal. The circulation at middlehigh latitudes of the Eurasian showed a threewave pattern, and the general circulation is of latitudinal type with small longitude. The Western Pacific subtropical high was stronger than that of the climatological normal, and the Bay of Bengal trough was more active than normal in late February. During this month, the frequency of cold air in China was less than that of average year, and there was one nationwide cold wave process. The monthly mean temperature was -0.1℃, higher than normal by 1.6℃. The monthly mean precipitation was 3.2 mm, 18% higher than normal. During the first half of February, continues foghaze weather appeared in the central and eastern part of China. Sanddust weather appeared in Northwest China firstly this year.
The main characteristics of the general atmospheric circulation in February 2020 are as follows. There were two polar vortex centers in the Northern Hemisphere and they were stronger than normal. The circulation at middlehigh latitudes of the Eurasian showed a threewave pattern, and the general circulation is of latitudinal type with small longitude. The Western Pacific subtropical high was stronger than that of the climatological normal, and the Bay of Bengal trough was more active than normal in late February. During this month, the frequency of cold air in China was less than that of average year, and there was one nationwide cold wave process. The monthly mean temperature was -0.1℃, higher than normal by 1.6℃. The monthly mean precipitation was 3.2 mm, 18% higher than normal. During the first half of February, continues foghaze weather appeared in the central and eastern part of China. Sanddust weather appeared in Northwest China firstly this year.
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ISSN:1000-0526 CN:11-2282/P