ISSN 1000-0526
CN 11-2282/P
CN 11-2282/P
Volume 44,Issue 7,2018 Table of Contents
2018, 44(7):857-868.
DOI: 10.7519/j.issn.10000526.2018.07.001
Abstract:
The initial soil water content and temperature significantly influence numerical weather forecasts. The Optimal Interpolation (OI) technique takes into account observation and forecast errors in an objective statistical way and can produce the analyzed soil water content and temperature. The OI_EC and OI_MF, which were developed from the original OI technique, have been used in the operational systems in European Centre for MediumRange Weather Forecasts and in MétéoFrance, but not in the GRAPES_Meso of China. So, we tried to apply the two OI techniques in the GRAPES_Meso. The experiment results of the two seasons in summer and winter show that the accuracy of the simulated 2 m temperature is improved by the use of the two OI techniques, and there is no obvious change in precipitation simulation results. Comparing the results of two OI techniques, we find that the OI_EC coefficients are more reasonable, and the OI_MF method is not suitable for simulating in the low vegetation coverage area.
The initial soil water content and temperature significantly influence numerical weather forecasts. The Optimal Interpolation (OI) technique takes into account observation and forecast errors in an objective statistical way and can produce the analyzed soil water content and temperature. The OI_EC and OI_MF, which were developed from the original OI technique, have been used in the operational systems in European Centre for MediumRange Weather Forecasts and in MétéoFrance, but not in the GRAPES_Meso of China. So, we tried to apply the two OI techniques in the GRAPES_Meso. The experiment results of the two seasons in summer and winter show that the accuracy of the simulated 2 m temperature is improved by the use of the two OI techniques, and there is no obvious change in precipitation simulation results. Comparing the results of two OI techniques, we find that the OI_EC coefficients are more reasonable, and the OI_MF method is not suitable for simulating in the low vegetation coverage area.
2018, 44(7):869-881.
DOI: 10.7519/j.issn.10000526.2018.07.002
Abstract:
Affected by northward cyclone, a rarelyseen severe rainstorm hit the BeijingTianjinHebei Region on 20 July 2016, resulting in a new extremum of daily mean precipitation amount in this region in the past 50 years. Using the FY2F satellite data with 6 min interval and 5 km horizontal resolution, radar data and AWS (automatic weather station) data collected every 10 min, NCEP 1°×1° reanalysis data with 6 h interval as well as the methods of multiple data overlay analysis, TBB gradient computation, retrieval of radar lowlevel wind etc., this paper analyzes the cloud image characteristics of cyclonic rainstorm cloud system in northern China and the organization, dynamic and thermodynamic structures of multiscale systems (synoptic scale and mesoα, mesoβ, mesoγ scale convective systems). Two mesoγ scale convective systems (MγCSs), which contribute to the severe rainstorms in the urban areas of Beijing and Tianjin are taken as examples to analyze the relationship between multiscale ambient configuration and the severe torrential rain events. The results are as follows. (1) The thermodynamic and vapor configurations of different parts of the comma cloud system are: the vortex center (Zone D) coincides with the center of the cyclonic circulation and is a lowvalue zone of the 700 hPa pseudoequivalent temperature (θse). The west side of the tail cloud zone is a dry, cold and cloudless zone. The smooth zone at the edge of the cloud zone corresponds to the energy front zone. The head of the cloud system (Zones A and B) corresponds to the θse highenergy zone of the 700 hPa and the jet stream core of the 850 hPa, while the Zones A and B correspond to northeast and southeast jets, respectively. In the jet zone, the θse of 700 hPa is as high as 78℃, the 850 hPa specific humidity is 18 g·kg-1, the maximum jet core wind speed is 30 m·s-1, and the entire precipitable water amount is 70 mm. (2) The comma cloud system has two MαCSs and one MβCS embeded in the head, which are the major contributors to the severe torrential rains, but the rain intensity is only 20-30 mm·h-1. However the MγCS in Beijing (MγCSBJ) and MγCS in Tianjin (MγCSTJ) both caused extremely heavy precipitation with the intensity getting to 40-70 mm·h-1. The two MγCSs are generated and maintained under different multiscale background conditions: (a) MγCSBJ is located in the vortex center (Zone D), which is the left front convective instability zone of the lowlevel jet, combined with the wind direction convergence line formed by the northerly wind and the east wind. The convergence line appears about 1.5 h earlier than the convective system. (b) MγCSTJ is located in the edge zone between the cloud head and the vortex center. It occurs in the highgradient energy frontal zone of θse and matches the surface wind speed convergence line. (3) The development of MγCSTJ is closely related to the largevalue zone of TBB gradient in the MβCS edge. MγCSTJ has a deep mesocyclone inside, with the axis tilting to northwest, and the maximum rain intensity occurs at the moment when the rotation speed is the fastest.
Affected by northward cyclone, a rarelyseen severe rainstorm hit the BeijingTianjinHebei Region on 20 July 2016, resulting in a new extremum of daily mean precipitation amount in this region in the past 50 years. Using the FY2F satellite data with 6 min interval and 5 km horizontal resolution, radar data and AWS (automatic weather station) data collected every 10 min, NCEP 1°×1° reanalysis data with 6 h interval as well as the methods of multiple data overlay analysis, TBB gradient computation, retrieval of radar lowlevel wind etc., this paper analyzes the cloud image characteristics of cyclonic rainstorm cloud system in northern China and the organization, dynamic and thermodynamic structures of multiscale systems (synoptic scale and mesoα, mesoβ, mesoγ scale convective systems). Two mesoγ scale convective systems (MγCSs), which contribute to the severe rainstorms in the urban areas of Beijing and Tianjin are taken as examples to analyze the relationship between multiscale ambient configuration and the severe torrential rain events. The results are as follows. (1) The thermodynamic and vapor configurations of different parts of the comma cloud system are: the vortex center (Zone D) coincides with the center of the cyclonic circulation and is a lowvalue zone of the 700 hPa pseudoequivalent temperature (θse). The west side of the tail cloud zone is a dry, cold and cloudless zone. The smooth zone at the edge of the cloud zone corresponds to the energy front zone. The head of the cloud system (Zones A and B) corresponds to the θse highenergy zone of the 700 hPa and the jet stream core of the 850 hPa, while the Zones A and B correspond to northeast and southeast jets, respectively. In the jet zone, the θse of 700 hPa is as high as 78℃, the 850 hPa specific humidity is 18 g·kg-1, the maximum jet core wind speed is 30 m·s-1, and the entire precipitable water amount is 70 mm. (2) The comma cloud system has two MαCSs and one MβCS embeded in the head, which are the major contributors to the severe torrential rains, but the rain intensity is only 20-30 mm·h-1. However the MγCS in Beijing (MγCSBJ) and MγCS in Tianjin (MγCSTJ) both caused extremely heavy precipitation with the intensity getting to 40-70 mm·h-1. The two MγCSs are generated and maintained under different multiscale background conditions: (a) MγCSBJ is located in the vortex center (Zone D), which is the left front convective instability zone of the lowlevel jet, combined with the wind direction convergence line formed by the northerly wind and the east wind. The convergence line appears about 1.5 h earlier than the convective system. (b) MγCSTJ is located in the edge zone between the cloud head and the vortex center. It occurs in the highgradient energy frontal zone of θse and matches the surface wind speed convergence line. (3) The development of MγCSTJ is closely related to the largevalue zone of TBB gradient in the MβCS edge. MγCSTJ has a deep mesocyclone inside, with the axis tilting to northwest, and the maximum rain intensity occurs at the moment when the rotation speed is the fastest.
2018, 44(7):882-891.
DOI: 10.7519/j.issn.10000526.2018.07.003
Abstract:
Based on Global Precipitation Measurement (GPM) and 40 weather stations in Tianshan Mountains, a new error correction method (MERGE) is proposed and compared with the widely used geographical different analysis (GDA) method through crossvalidation. The results indicate that both GDA and MERGE methods can improve the accuracy of Tropical Rainfall Measuring Mission (TRMM) significantly. The MERGE method not only improve the spatial resolution of TRMM, but also has higher accuracy than GDA method on annual and monthly scales. The error of corrected TRMM data varies greatly in different months. It has larger error (MAE>3 mm) in the rainy season (April-October), but less error (MAE<3 mm) in the dry season (November-March). Besides, the MERGE method can effectively improve the error in high altitude area and less depends on the original TRMM data, with the R2=0.47. So, even in local areas where the TRMM data have poor performance, this method can also reduce the error effectively.
Based on Global Precipitation Measurement (GPM) and 40 weather stations in Tianshan Mountains, a new error correction method (MERGE) is proposed and compared with the widely used geographical different analysis (GDA) method through crossvalidation. The results indicate that both GDA and MERGE methods can improve the accuracy of Tropical Rainfall Measuring Mission (TRMM) significantly. The MERGE method not only improve the spatial resolution of TRMM, but also has higher accuracy than GDA method on annual and monthly scales. The error of corrected TRMM data varies greatly in different months. It has larger error (MAE>3 mm) in the rainy season (April-October), but less error (MAE<3 mm) in the dry season (November-March). Besides, the MERGE method can effectively improve the error in high altitude area and less depends on the original TRMM data, with the R2=0.47. So, even in local areas where the TRMM data have poor performance, this method can also reduce the error effectively.
2018, 44(7):892-901.
DOI: 10.7519/j.issn.10000526.2018.07.004
Abstract:
Based on meteorological data from 70 automatic weather stations and 365 traffic meteorological observation stations of Jiangsu Province, a heavy fog process that occurred in Jiangsu in 11-12 February 2016 is investigated. The results show this fog process features that the fog formed and intensified explosively. At most stations, the dense fog formed rapidly with the visibility dropping directly from 1000 m above, and there was multiple burst enhancement phenomena in some areas. Along with the opened sky at night, the longwave radiation cooling also strengthened, which was an important cause for the formation and explosive development of the wide range of heavy fog. Meanwhile, the prophase rainfall provided basic conditions for the formation of the heavy fog, and also was the direct cause of the enhanced evaporation and explosive increase of heavy fog at some sites after sunrise. In addition, strong inversion temperature provided stable atmospheric conditions for the explosive development of fog. The lowlevel jet near the top of inversion temperature promoted the maintenance and enhancing of the strong inversion, which played an important role in the explosive development of heavy fog.
Based on meteorological data from 70 automatic weather stations and 365 traffic meteorological observation stations of Jiangsu Province, a heavy fog process that occurred in Jiangsu in 11-12 February 2016 is investigated. The results show this fog process features that the fog formed and intensified explosively. At most stations, the dense fog formed rapidly with the visibility dropping directly from 1000 m above, and there was multiple burst enhancement phenomena in some areas. Along with the opened sky at night, the longwave radiation cooling also strengthened, which was an important cause for the formation and explosive development of the wide range of heavy fog. Meanwhile, the prophase rainfall provided basic conditions for the formation of the heavy fog, and also was the direct cause of the enhanced evaporation and explosive increase of heavy fog at some sites after sunrise. In addition, strong inversion temperature provided stable atmospheric conditions for the explosive development of fog. The lowlevel jet near the top of inversion temperature promoted the maintenance and enhancing of the strong inversion, which played an important role in the explosive development of heavy fog.
2018, 44(7):902-910.
DOI: 10.7519/j.issn.10000526.2018.07.005
Abstract:
This article focuses on the application of the 2013-2015 Beijing meteorological tower data and derivative data, combined with conventional and unconventional observation data, such as VDRAS, automatic weather stations and NCEP reanalysis data. According to the evolution of the boundary layer elements, shorttime heavy precipitation is divided into two types, one has the surface convergence line and the other has not. And we also focus on the evolution of the boundary layer elements of the two types shorttime rainfalls to find the forecasting signal before heavy rainfalls occur in summer, which could provide reference for the shorttime heavy rainfall forecasting. The results show that varivation of the elements of the meteorological power can not predict for the occurrence of the nonsurface convergence line type, but it has certain guiding significance to the shorttime severe rainfall of the surface convergence line type. Before such type of heavy rain occurs, the temperature and potential temperature begin to decrease obviously and decline rate gradually increases. The temperature change rate gradually increases to -0.35℃ per minute. The specific humidity increases significantly 3 h before the start of the heavy rainfall below 325 m. When it begins to rain, the specific humidity decreases about 3.5 g·kg-1 during 20 min before the rainfall begins. The lowlevel wind shear is up to the strong degree. But the specific humidity and lowlevel wind shear can show the signals at 10-20 min lead time. So the evolution of tower meteorological elements and the physical quantities have indicative meaning for the forecasting and warning of shorttime rainfall of surface convergence line type.
This article focuses on the application of the 2013-2015 Beijing meteorological tower data and derivative data, combined with conventional and unconventional observation data, such as VDRAS, automatic weather stations and NCEP reanalysis data. According to the evolution of the boundary layer elements, shorttime heavy precipitation is divided into two types, one has the surface convergence line and the other has not. And we also focus on the evolution of the boundary layer elements of the two types shorttime rainfalls to find the forecasting signal before heavy rainfalls occur in summer, which could provide reference for the shorttime heavy rainfall forecasting. The results show that varivation of the elements of the meteorological power can not predict for the occurrence of the nonsurface convergence line type, but it has certain guiding significance to the shorttime severe rainfall of the surface convergence line type. Before such type of heavy rain occurs, the temperature and potential temperature begin to decrease obviously and decline rate gradually increases. The temperature change rate gradually increases to -0.35℃ per minute. The specific humidity increases significantly 3 h before the start of the heavy rainfall below 325 m. When it begins to rain, the specific humidity decreases about 3.5 g·kg-1 during 20 min before the rainfall begins. The lowlevel wind shear is up to the strong degree. But the specific humidity and lowlevel wind shear can show the signals at 10-20 min lead time. So the evolution of tower meteorological elements and the physical quantities have indicative meaning for the forecasting and warning of shorttime rainfall of surface convergence line type.
6 Research on Threshold and Regularity of Mixed Layer Thickness in Heavy Pollution Weather in Tianjin
2018, 44(7):911-920.
DOI: 10.7519/j.issn.10000526.2018.07.006
Abstract:
Based on ceilometers inversion data and simulation data, the dataset of mixed layer thickness in Tianjin were constructed, the data of PM2.5 mass concentration and visibility in Tianjin during 2009-2015 were collected, and the threshold and regularity of mixed layer thickness in heavy pollution weather in Tianjin were researched in this paper. The results show that the thickness of mixed layer kept increasing during 2000-2015, having a strong consistency with the increase of nocturnal boundary layer height and the increase of inversion base observed by meteorological tower. Statistics show that PM2.5 mass concentration has exponential relationship with the thickness of mixed layer. The lower the mixed layer thickness, the higher the PM2.5 mass concentration. The thresholds of mixed layer thickness can be 200 m, 400 m, 600 m and 800 m, which can be used as limits to determine the vertical diffusion of atmospheric pollution. When the thickness of mixed layer is less than 200 m, probability of heavy pollution weather is 52%, and probability of moderate haze is 46%. The negative correlation between PM2.5 average mass concentration and mixed layer thickness is not applicable to all pollution processes. For the transport of air pollution, the impact is from high altitude to ground surface. In the initial stage of pollution, the increase of mixed layer thickness is beneficial to pollutant transmission, causing the nearsurface PM2.5 mass concentration to increase, which need to be considered carefully when the threshold of mixed layer thickness is used.
Based on ceilometers inversion data and simulation data, the dataset of mixed layer thickness in Tianjin were constructed, the data of PM2.5 mass concentration and visibility in Tianjin during 2009-2015 were collected, and the threshold and regularity of mixed layer thickness in heavy pollution weather in Tianjin were researched in this paper. The results show that the thickness of mixed layer kept increasing during 2000-2015, having a strong consistency with the increase of nocturnal boundary layer height and the increase of inversion base observed by meteorological tower. Statistics show that PM2.5 mass concentration has exponential relationship with the thickness of mixed layer. The lower the mixed layer thickness, the higher the PM2.5 mass concentration. The thresholds of mixed layer thickness can be 200 m, 400 m, 600 m and 800 m, which can be used as limits to determine the vertical diffusion of atmospheric pollution. When the thickness of mixed layer is less than 200 m, probability of heavy pollution weather is 52%, and probability of moderate haze is 46%. The negative correlation between PM2.5 average mass concentration and mixed layer thickness is not applicable to all pollution processes. For the transport of air pollution, the impact is from high altitude to ground surface. In the initial stage of pollution, the increase of mixed layer thickness is beneficial to pollutant transmission, causing the nearsurface PM2.5 mass concentration to increase, which need to be considered carefully when the threshold of mixed layer thickness is used.
2018, 44(7):921-928.
DOI: 10.7519/j.issn.10000526.2018.07.007
Abstract:
The effects of traffic emission and heating in winter on the components of atmospheric aerosol were revealed by using the relation between the properties of aerosol and the aerosol absorption ngstrom exponent (AAE) as the indicator for the aerosol’s composition, based on a 37 d measurement campaign from 13 November to 19 December 2009 with the Aethalometer in the region of Beijing. The diurnal variation characteristics and the comparison analysis were studied on the 37 d average, clean, and foghaze conditions. The results showed that the AAE reached the minimum during traffic rushhours and increased at other times in the average and foghaze conditions. In clean condition, the AAE decreased gradually from nighttime to daytime, and an inflexion would turn with the advent of the traffic rushhours. The AAE was significantly higher in clean condition than in the two other conditions, and the difference became more significant at night. Combining the varied weather conditions, the paper demonstrated that significant emissions of brown carboncontaining aerosols in the region of Beijing in winter, especially during the night, and emissions of the fine particles during traffic rushhours, as well as the important impact on the components of aerosol in ambient atmosphere.
The effects of traffic emission and heating in winter on the components of atmospheric aerosol were revealed by using the relation between the properties of aerosol and the aerosol absorption ngstrom exponent (AAE) as the indicator for the aerosol’s composition, based on a 37 d measurement campaign from 13 November to 19 December 2009 with the Aethalometer in the region of Beijing. The diurnal variation characteristics and the comparison analysis were studied on the 37 d average, clean, and foghaze conditions. The results showed that the AAE reached the minimum during traffic rushhours and increased at other times in the average and foghaze conditions. In clean condition, the AAE decreased gradually from nighttime to daytime, and an inflexion would turn with the advent of the traffic rushhours. The AAE was significantly higher in clean condition than in the two other conditions, and the difference became more significant at night. Combining the varied weather conditions, the paper demonstrated that significant emissions of brown carboncontaining aerosols in the region of Beijing in winter, especially during the night, and emissions of the fine particles during traffic rushhours, as well as the important impact on the components of aerosol in ambient atmosphere.
2018, 44(7):929-935.
DOI: 10.7519/j.issn.10000526.2018.07.008
Abstract:
The impact of meteorological factors on particle size distribution and its characteristic over Guanzhong Basin (GZB) was studied by employing the particulate matter (PM) mass concentration data released by Xi’an Environmental Protection Bureau, the meteorological station data and the particle size distribution data measured by aerodynamic particle sizer (APS) and Scanning Mobility Particle Sizer Model 3034 (SMPS). The result showed that heavy haze frequently occurring in GZB is mainly caused by complex special terrain and high levels of particulate pollutants. Significant negative correlations were found between planetary boundary layer height (PBLH) and mass concentrations of PM with aerodynamic diameters <2.5 μm (PM2.5), suggesting that a higher PBLH is favorable for the diffusion of particulate pollutants. Changes in PM2.5 in response to wind speed and wind direction was simultaneously investigated, clearly showing that easterly (northwesterly) wind is associated with the import (export) of pollutants to (from) GBZ. Furthermore, high relative humidity significantly contributes to the maintenance of stable atmospheric boundary layers and the accumulation of particulate pollutants. When relative humidity (RH) is less then 80%, the particle number concentration with diameters ranging from 150 nm to 1.0 μm increases greatly with the increase of RH, which could result in a poor visibility. The number concentration of particles within different size ranges changes variously with RH, causing different impacts on visibility. The higher the RH, the larger the contribution of humidity to the visibility reduction.
The impact of meteorological factors on particle size distribution and its characteristic over Guanzhong Basin (GZB) was studied by employing the particulate matter (PM) mass concentration data released by Xi’an Environmental Protection Bureau, the meteorological station data and the particle size distribution data measured by aerodynamic particle sizer (APS) and Scanning Mobility Particle Sizer Model 3034 (SMPS). The result showed that heavy haze frequently occurring in GZB is mainly caused by complex special terrain and high levels of particulate pollutants. Significant negative correlations were found between planetary boundary layer height (PBLH) and mass concentrations of PM with aerodynamic diameters <2.5 μm (PM2.5), suggesting that a higher PBLH is favorable for the diffusion of particulate pollutants. Changes in PM2.5 in response to wind speed and wind direction was simultaneously investigated, clearly showing that easterly (northwesterly) wind is associated with the import (export) of pollutants to (from) GBZ. Furthermore, high relative humidity significantly contributes to the maintenance of stable atmospheric boundary layers and the accumulation of particulate pollutants. When relative humidity (RH) is less then 80%, the particle number concentration with diameters ranging from 150 nm to 1.0 μm increases greatly with the increase of RH, which could result in a poor visibility. The number concentration of particles within different size ranges changes variously with RH, causing different impacts on visibility. The higher the RH, the larger the contribution of humidity to the visibility reduction.
2018, 44(7):936-943.
DOI: 10.7519/j.issn.10000526.2018.07.009
Abstract:
This paper uses the conventional observation data collected from eight automatic weather stations in Lhasa in 2012-2016, and the related data of local industry, agriculture and residents’ living status, and assesses the spatiotemporal distribution of heat island effect in Lhasa and its relationship with landuse. The results show that the annual and seasonal changes of urban heat island in Lhasa are gradually increasing. The monthly variation of the urban heat island intensity is mainly concentrated in winter, followed by summer, and the heat island effects in spring and autumn are weak. The spatial distribution of the urban heat island is extremely uneven: high in the southwest and low in the northeast. Heat island area has expanded, and the center shifts southward from the economic development zone to the Liuwu Railway Station, with low value range located near the Tax Forest and the Lalu Wetland. The heat island intensity of Lhasa is positively correlated to population density, housing built area and reduced cultivated land area, and negatively correlated to afforestation area. It has no significant correlation with agricultural production.
This paper uses the conventional observation data collected from eight automatic weather stations in Lhasa in 2012-2016, and the related data of local industry, agriculture and residents’ living status, and assesses the spatiotemporal distribution of heat island effect in Lhasa and its relationship with landuse. The results show that the annual and seasonal changes of urban heat island in Lhasa are gradually increasing. The monthly variation of the urban heat island intensity is mainly concentrated in winter, followed by summer, and the heat island effects in spring and autumn are weak. The spatial distribution of the urban heat island is extremely uneven: high in the southwest and low in the northeast. Heat island area has expanded, and the center shifts southward from the economic development zone to the Liuwu Railway Station, with low value range located near the Tax Forest and the Lalu Wetland. The heat island intensity of Lhasa is positively correlated to population density, housing built area and reduced cultivated land area, and negatively correlated to afforestation area. It has no significant correlation with agricultural production.
2018, 44(7):944-951.
DOI: 10.7519/j.issn.10000526.2018.07.010
Abstract:
The computing method of rainstorm surface rainfall is studied based on the grid product of hourly quantitative precipitation estimation (QPE) of radar data and the automatic weather station (AWS) quality control rainfall data in Shanghai. The computing method is that the radar estimated rainfall of the AWS in rainstorm area, which was obtained from the radar QPE mean of 9 grid points around the AWS, is used to calculate the difference between the rainfall and the radar estimated rainfall of the AWS. The difference field is interpolated into the same grid point of radar precipitation estimation using Kriging interpolation method. The hourly rainfall of grid points is the sum of the residual interpolation data and the radar rainfall estimation of grid points. The average absolute error of QPE and measured rainfall of 24 typical rainstorm cases of all stations is reduced by 27% after correction. The average error of QPE and measured rainfall of main precipitation sections and process rainfall of national weather stations for two typical rainstorms are reduced by 33%-39% and 34%-59% respectively after correction. The value and graph of hourly and process surface rainfall and administrative district as well as water conservancy onesided rainfall of the 24 typical rainstorms from 2007 to 2015 are calculated and drawn according to the rainfall of grid points using above computing method. Finally, the automated computing inquiry system of rainstorm surface rainfall based on radar data is produced using the development tools of Visual Studio Microsoft 2012 and Microsoft Visual Studio software relying on NET Framework.4.0 Software development platform. This system will be used for realtime querying and calculation.
The computing method of rainstorm surface rainfall is studied based on the grid product of hourly quantitative precipitation estimation (QPE) of radar data and the automatic weather station (AWS) quality control rainfall data in Shanghai. The computing method is that the radar estimated rainfall of the AWS in rainstorm area, which was obtained from the radar QPE mean of 9 grid points around the AWS, is used to calculate the difference between the rainfall and the radar estimated rainfall of the AWS. The difference field is interpolated into the same grid point of radar precipitation estimation using Kriging interpolation method. The hourly rainfall of grid points is the sum of the residual interpolation data and the radar rainfall estimation of grid points. The average absolute error of QPE and measured rainfall of 24 typical rainstorm cases of all stations is reduced by 27% after correction. The average error of QPE and measured rainfall of main precipitation sections and process rainfall of national weather stations for two typical rainstorms are reduced by 33%-39% and 34%-59% respectively after correction. The value and graph of hourly and process surface rainfall and administrative district as well as water conservancy onesided rainfall of the 24 typical rainstorms from 2007 to 2015 are calculated and drawn according to the rainfall of grid points using above computing method. Finally, the automated computing inquiry system of rainstorm surface rainfall based on radar data is produced using the development tools of Visual Studio Microsoft 2012 and Microsoft Visual Studio software relying on NET Framework.4.0 Software development platform. This system will be used for realtime querying and calculation.
2018, 44(7):952-960.
DOI: 10.7519/j.issn.10000526.2018.07.011
Abstract:
Lowlevel jet is important for predicting severe convective weather. At present, the identification of lowlevel jet is conducted mainly by handwork, which brings the problem of low efficiency, easily influenced by subjective factors. So, based on the wind field data of the sounding stations in MICAPS, we propose an automatic lowlevel jet identification and drawing algorithm in this paper. The algorithm is based on the definition of the lowlevel jet axis, and detects the lowlevel jet axis from several aspects in terms of wind speed, wind direction, sounding station distribution, and the central axis position. Then after the steps of transitive closure clustering, key points extracting, lowlevel jet axis merging and the axis smooth ing, the automatic identification and drawing of lowlevel jet are achieved. The test result shows that the jet axis, which is automatically drawn, has the characteristics of accurate position and natural shape. Besides, it could reflect the transport path of water vapor in jet, and adapt to the complex environment of lowlevel jet. In the 291 test data, the identification rate reaches 94.96% and false alarm is not found.
Lowlevel jet is important for predicting severe convective weather. At present, the identification of lowlevel jet is conducted mainly by handwork, which brings the problem of low efficiency, easily influenced by subjective factors. So, based on the wind field data of the sounding stations in MICAPS, we propose an automatic lowlevel jet identification and drawing algorithm in this paper. The algorithm is based on the definition of the lowlevel jet axis, and detects the lowlevel jet axis from several aspects in terms of wind speed, wind direction, sounding station distribution, and the central axis position. Then after the steps of transitive closure clustering, key points extracting, lowlevel jet axis merging and the axis smooth ing, the automatic identification and drawing of lowlevel jet are achieved. The test result shows that the jet axis, which is automatically drawn, has the characteristics of accurate position and natural shape. Besides, it could reflect the transport path of water vapor in jet, and adapt to the complex environment of lowlevel jet. In the 291 test data, the identification rate reaches 94.96% and false alarm is not found.
2018, 44(7):961-968.
DOI: 10.7519/j.issn.10000526.2018.07.012
Abstract:
Using standardization, intensification, intelligence concepts, this paper presents the design idea and overall structure of Ningxia Intelligent Integrated Meteorological Service Sharing Management Platform (NXIIMSSMP) based on the cloud deployment technology, and builds the Ningxia meteorological basic database, operational product database, service product database, as well as the automation generation system of operational products, intelligent production system of service products, intelligent publishing system of service information and information sharing and management system. The design of standardization system based on intensive data environments is given by means of storage standardization, standardization of data service interface, standardization of data resource management, and standardization of data processing process. Through the operation system intensification and data intensification, a datadriven intensive system is designed to form a unified data processing pipeline. The intelligent requirements are emphasized in NXIIMSSMP. Meanwhile, the intelligent data analys algorithm and system operation control are designed. In addition, we are exploring some methods of operational product automation processing, intelligent production of service products, and intelligent release in this system. The platform design concept is advanced. With frontier technology, concise procedural flow, complete function, and efficient operation, it fully embodies the requirements of standardization of data resources, intensive operation system and intelligent calculation. The development and construction of this platform would greatly promote the meteorological modernization process in Ningxia Hui Autonomous Region, and also the development of intelligent meteorology.
Using standardization, intensification, intelligence concepts, this paper presents the design idea and overall structure of Ningxia Intelligent Integrated Meteorological Service Sharing Management Platform (NXIIMSSMP) based on the cloud deployment technology, and builds the Ningxia meteorological basic database, operational product database, service product database, as well as the automation generation system of operational products, intelligent production system of service products, intelligent publishing system of service information and information sharing and management system. The design of standardization system based on intensive data environments is given by means of storage standardization, standardization of data service interface, standardization of data resource management, and standardization of data processing process. Through the operation system intensification and data intensification, a datadriven intensive system is designed to form a unified data processing pipeline. The intelligent requirements are emphasized in NXIIMSSMP. Meanwhile, the intelligent data analys algorithm and system operation control are designed. In addition, we are exploring some methods of operational product automation processing, intelligent production of service products, and intelligent release in this system. The platform design concept is advanced. With frontier technology, concise procedural flow, complete function, and efficient operation, it fully embodies the requirements of standardization of data resources, intensive operation system and intelligent calculation. The development and construction of this platform would greatly promote the meteorological modernization process in Ningxia Hui Autonomous Region, and also the development of intelligent meteorology.
2018, 44(7):969-976.
DOI: 10.7519/j.issn.10000526.2018.07.013
Abstract:
The East Asian winter monsoon (EAWM) and Siberian high (SH) were both stronger than normal during the 2017/2018 winter, with significant intraseasonal variation. The geopotential height anomalies of midhigh latitude of Eurasia were mainly occupied by meridional circulation, with strong Ural high, and westward East Asian trough. The 2017/2018 winter was marked with frequent cold air processes, low temperature in northeasten China and abnormal warmer climate in Tibetan Plateau. Diagnostic analysis of possible mechanism for strong EAWM in 2017/2018 winter indicated that, subject to the modulation of warm phase of Pacific Decadal Oscillation (PDO), the influence of La Ni〖AKn~D〗a was comparatively weak. Meanwhile, the weak polar vortex of Northern Hemisphere, and continuously warm SST in north Atlantic, both associated with the strong EAWM in 2017/2018 winter.
The East Asian winter monsoon (EAWM) and Siberian high (SH) were both stronger than normal during the 2017/2018 winter, with significant intraseasonal variation. The geopotential height anomalies of midhigh latitude of Eurasia were mainly occupied by meridional circulation, with strong Ural high, and westward East Asian trough. The 2017/2018 winter was marked with frequent cold air processes, low temperature in northeasten China and abnormal warmer climate in Tibetan Plateau. Diagnostic analysis of possible mechanism for strong EAWM in 2017/2018 winter indicated that, subject to the modulation of warm phase of Pacific Decadal Oscillation (PDO), the influence of La Ni〖AKn~D〗a was comparatively weak. Meanwhile, the weak polar vortex of Northern Hemisphere, and continuously warm SST in north Atlantic, both associated with the strong EAWM in 2017/2018 winter.
2018, 44(7):977-984.
DOI: 10.7519/j.issn.10000526.2018.07.014
Abstract:
The main characteristics of the general atmospheric circulation in April 2018 are as follows. There were double polar vortex centers in the Northern Hemisphere, stronger than usual. The circulation in Eurasian middlehigh latitudes showed a fourwave pattern. The strength of Western Pacific subtropical high was a little weaker than in normal years while the south branch trough was stronger. The monthly mean temperature was 12.4℃, 1.4℃ higher than normal with the value of 11℃, and the monthly mean precipitation amount was 43.6 mm, which is less than normal by 2.5%. Three cold air processes happened in this month. The first cold air process was a nationwide strong cold air process, causing wide range of severe cooling, raining and snowing. There were five sanddust weather processes seen in northern China in April. In addition, three torrential rain processes happened in southern China. The middle and lower reaches of the Yangtze River Basin suffered severe rainstorm floods caused by the heavy rainfall event in 22-24 April 2018.
The main characteristics of the general atmospheric circulation in April 2018 are as follows. There were double polar vortex centers in the Northern Hemisphere, stronger than usual. The circulation in Eurasian middlehigh latitudes showed a fourwave pattern. The strength of Western Pacific subtropical high was a little weaker than in normal years while the south branch trough was stronger. The monthly mean temperature was 12.4℃, 1.4℃ higher than normal with the value of 11℃, and the monthly mean precipitation amount was 43.6 mm, which is less than normal by 2.5%. Three cold air processes happened in this month. The first cold air process was a nationwide strong cold air process, causing wide range of severe cooling, raining and snowing. There were five sanddust weather processes seen in northern China in April. In addition, three torrential rain processes happened in southern China. The middle and lower reaches of the Yangtze River Basin suffered severe rainstorm floods caused by the heavy rainfall event in 22-24 April 2018.
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ISSN:1000-0526 CN:11-2282/P