Volume 50,Issue 4,2022 Table of Contents
2022, 50(4):467-475.
DOI: 10.19517/j.1671-6345.20210376
Abstract:
Based on the realtime operational data, positioning data and observation data of the domestic marine meteorological drifting buoys, an operational assessment method with Effective-Lifetime (EL), File Receiving rate (FR), Data to Reporting rate (DR) and Data Availability (DA) as the main indicators is established. The evaluation results of buoy deployment in the western Pacific Ocean in 2017 show that the buoy drifting speed is a key indicator to reflect the effective life of the instrument. The EL of the four sets of buoys are 193.8 h, 837.8 h, 330.8 h and 2766.9 h, and the FR and DR during the effective lifetime are 79.86% and 98.74%, 97.37% and 99.88%, 94.65% and 100%, 65.45% and 89.66%, respectively. TheDA is 98.90%, 99.68%, 98.31%, and 60.14%, as verified by the buoy operational state parameter impact analysis and quality control algorithm. The buoy solar charging module can increase the working life of the buoy to some extent, but it cannot stop the power loss. The predicted results of the power supply voltage change trend show that the buoy’s working life is from 5550 to 8400 h, which meets the design index.
Based on the realtime operational data, positioning data and observation data of the domestic marine meteorological drifting buoys, an operational assessment method with Effective-Lifetime (EL), File Receiving rate (FR), Data to Reporting rate (DR) and Data Availability (DA) as the main indicators is established. The evaluation results of buoy deployment in the western Pacific Ocean in 2017 show that the buoy drifting speed is a key indicator to reflect the effective life of the instrument. The EL of the four sets of buoys are 193.8 h, 837.8 h, 330.8 h and 2766.9 h, and the FR and DR during the effective lifetime are 79.86% and 98.74%, 97.37% and 99.88%, 94.65% and 100%, 65.45% and 89.66%, respectively. TheDA is 98.90%, 99.68%, 98.31%, and 60.14%, as verified by the buoy operational state parameter impact analysis and quality control algorithm. The buoy solar charging module can increase the working life of the buoy to some extent, but it cannot stop the power loss. The predicted results of the power supply voltage change trend show that the buoy’s working life is from 5550 to 8400 h, which meets the design index.
2022, 50(4):476-484.
DOI: 10.19517/j.1671-6345.20210267
Abstract:
The precipitation estimation ability of the integrated multi-satellite retrievals for Global Precipitation Measurement (GPM/IMERG) is refined and evaluated in the study for Meiyu, typhoon and squall line precipitation, using the measurements from C-band dual-polarization radar from the Nanjing University of Information Science & Technology (NUIST-CDP). The ground-based gauges are used to calibrate the radar data. The main conclusions are: (1) IMERG overestimates the cumulative precipitation estimated by NUISTCDP during Meiyu precipitation. (2) During typhoon precipitation, when the cumulative precipitation estimated by NUIST-CDP is large, IMERG greatly underestimates the precipitation of NUIST-CDP. (3) IMERG performs poorly during squall line precipitation because it hardly observes heavy precipitation.
The precipitation estimation ability of the integrated multi-satellite retrievals for Global Precipitation Measurement (GPM/IMERG) is refined and evaluated in the study for Meiyu, typhoon and squall line precipitation, using the measurements from C-band dual-polarization radar from the Nanjing University of Information Science & Technology (NUIST-CDP). The ground-based gauges are used to calibrate the radar data. The main conclusions are: (1) IMERG overestimates the cumulative precipitation estimated by NUISTCDP during Meiyu precipitation. (2) During typhoon precipitation, when the cumulative precipitation estimated by NUIST-CDP is large, IMERG greatly underestimates the precipitation of NUIST-CDP. (3) IMERG performs poorly during squall line precipitation because it hardly observes heavy precipitation.
2022, 50(4):485-493.
DOI: 10.19517/j.1671-6345.20210334
Abstract:
This paper compares and verifies the atmosphere temperature profiles in the Winter Olympic Venue by different observation data, including ground microwave radiometer and Geostationary Interferometric Infrared Sounder (GIIRS) on FY-4A. For verification, we select the temperature profile data of FY-4A GIIRS from January to December 2020. We also compare the temperature profile data in three different atmospheric conditions: clear sky, air pollution, and dust storm, which will influence the Winter Olympic Games. The statistical result shows that GIIRS and ground microwave radiometer observation products have good accuracy in clear sky conditions. The average correlation coefficient is 0.97. The lower atmosphere (under 500 hPa) shows better accuracy than the higher atmosphere. Air pollution has a certain impact on the accuracy of vertical atmosphere detection. The value of PM2.5 has no obvious influence on the detection value. The value of PM10, especially during sand storms, has a huge impact on the vertical atmosphere detection of FY-4A GIIRS. After double comparison, we discover that satellite detection can be an important observation data source complementing radiosonde instruments and microwave radiometers. The advantages of FY-4A GIIRS are wide and frequent observation, average and high special resolution, and its accuracy detection in most types of atmospheric conditions. However, the cloud and heavy PM10 pollution will highly impact GIIRS. The ground microwave radiometer can get vertical atmosphere parameters frequently in a fixed location. It shows high accuracy with the detection of radiosonde instruments. Moreover, those detection methods can provide vertical atmosphere temperature data with good quality for the weather forecast to the Winter Olympic Venue.
This paper compares and verifies the atmosphere temperature profiles in the Winter Olympic Venue by different observation data, including ground microwave radiometer and Geostationary Interferometric Infrared Sounder (GIIRS) on FY-4A. For verification, we select the temperature profile data of FY-4A GIIRS from January to December 2020. We also compare the temperature profile data in three different atmospheric conditions: clear sky, air pollution, and dust storm, which will influence the Winter Olympic Games. The statistical result shows that GIIRS and ground microwave radiometer observation products have good accuracy in clear sky conditions. The average correlation coefficient is 0.97. The lower atmosphere (under 500 hPa) shows better accuracy than the higher atmosphere. Air pollution has a certain impact on the accuracy of vertical atmosphere detection. The value of PM2.5 has no obvious influence on the detection value. The value of PM10, especially during sand storms, has a huge impact on the vertical atmosphere detection of FY-4A GIIRS. After double comparison, we discover that satellite detection can be an important observation data source complementing radiosonde instruments and microwave radiometers. The advantages of FY-4A GIIRS are wide and frequent observation, average and high special resolution, and its accuracy detection in most types of atmospheric conditions. However, the cloud and heavy PM10 pollution will highly impact GIIRS. The ground microwave radiometer can get vertical atmosphere parameters frequently in a fixed location. It shows high accuracy with the detection of radiosonde instruments. Moreover, those detection methods can provide vertical atmosphere temperature data with good quality for the weather forecast to the Winter Olympic Venue.
2022, 50(4):494-499.
DOI: 10.19517/j.1671-6345.20210235
Abstract:
Based on the analysis of the Atmospheric Observing System Operations and Monitoring, 2418 sets of national automatic weather stations produced 9172 automatic station fault maintenance records from 2015 and 2020. This paper analyzes and evaluates the fault maintenance of automatic stations and statistically researches the average fault index (MFI) of automatic stations, average fault-free working time (MTBF) and average fault repair time (MTTR). The results show that: (1) There are more faults in June, July and August, which are mainly concentrated in the collector, communication transmission equipment and power supply equipment. Natural damage accounts for the largest proportion of failure causes. (2) As for the faults of the collector, the failure rates caused by natural damage, lightning strikes, and power supply are higher. (3) In the south, faults caused by power supply and communication are more common, while in the north, faults caused by communication and natural damage are more common. The corresponding maintenance suggestions are put forward according to the fault locations and fault causes.
Based on the analysis of the Atmospheric Observing System Operations and Monitoring, 2418 sets of national automatic weather stations produced 9172 automatic station fault maintenance records from 2015 and 2020. This paper analyzes and evaluates the fault maintenance of automatic stations and statistically researches the average fault index (MFI) of automatic stations, average fault-free working time (MTBF) and average fault repair time (MTTR). The results show that: (1) There are more faults in June, July and August, which are mainly concentrated in the collector, communication transmission equipment and power supply equipment. Natural damage accounts for the largest proportion of failure causes. (2) As for the faults of the collector, the failure rates caused by natural damage, lightning strikes, and power supply are higher. (3) In the south, faults caused by power supply and communication are more common, while in the north, faults caused by communication and natural damage are more common. The corresponding maintenance suggestions are put forward according to the fault locations and fault causes.
2022, 50(4):500-505.
DOI: 10.19517/j.1671-6345.20210542
Abstract:
The key parameters of the radar system and subsystem cannot be measured with the fixed test platform of weather radar. But they can be measured manually with a portable mobile test platform. So an automatic intelligent measure system is designed in this paper. Based on the weather radar mobile test support platform, the system is composed of four parts: the software system, embedded computer system, measuring instrument functional components, and test adapter interface. Based on the architecture of standard bus and synthetic instruments, the system is designed by combining the highly integrated RF transceiver hardware platform and the open extensible software platform with secondary development capability. The automatic one-click measure and calibration of radar parameters and intelligent fault location of radar are realized through the automatic control of instrument and radar, automatic acquisition and processing of measurement data, automatic generation of measure report, intelligent fault location based on logical judgment and other technologies. The results show that the system can improve the efficiency of radar measure, calibration and fault diagnosis.
The key parameters of the radar system and subsystem cannot be measured with the fixed test platform of weather radar. But they can be measured manually with a portable mobile test platform. So an automatic intelligent measure system is designed in this paper. Based on the weather radar mobile test support platform, the system is composed of four parts: the software system, embedded computer system, measuring instrument functional components, and test adapter interface. Based on the architecture of standard bus and synthetic instruments, the system is designed by combining the highly integrated RF transceiver hardware platform and the open extensible software platform with secondary development capability. The automatic one-click measure and calibration of radar parameters and intelligent fault location of radar are realized through the automatic control of instrument and radar, automatic acquisition and processing of measurement data, automatic generation of measure report, intelligent fault location based on logical judgment and other technologies. The results show that the system can improve the efficiency of radar measure, calibration and fault diagnosis.
2022, 50(4):506-511.
DOI: 10.19517/j.1671-6345.20210379
Abstract:
The portable radar maintenance and test platform is an intelligent mobile technical support platform that integrates the functions of radar system performance parameter testing, fault diagnosis and maintenance protection, etc. The hardware system of the platform adopts the general test instrument based on the embedded chassis design architecture. The article for the general test instrument on board clock can not meet the radar system on the test instrument clock requirements. This paper proposes a highly stable clock source design suitable for the portable radar maintenance and test platform. Design solutions include the high stability thermostat crystal, FPGA, crystal power control module and power filter circuit module. The actual test results show that the high stability clock source design parameters achieve the output frequency stability of ±0.5×10-6
The portable radar maintenance and test platform is an intelligent mobile technical support platform that integrates the functions of radar system performance parameter testing, fault diagnosis and maintenance protection, etc. The hardware system of the platform adopts the general test instrument based on the embedded chassis design architecture. The article for the general test instrument on board clock can not meet the radar system on the test instrument clock requirements. This paper proposes a highly stable clock source design suitable for the portable radar maintenance and test platform. Design solutions include the high stability thermostat crystal, FPGA, crystal power control module and power filter circuit module. The actual test results show that the high stability clock source design parameters achieve the output frequency stability of ±0.5×10-6
2022, 50(4):512-525.
DOI: 10.19517/j.1671-6345.20210385
Abstract:
Based on the ground automatic station data, doppler weather radar data, satellite hourly TBB data and NCEP reanalysis data, we analyze the occurrence and maintenance mechanism of two short-term rainstorms in Hunan under the control of subtropical high in 2018. The results show that: (1) Under the condition of abundant water vapour and sufficient unstable energy and uplift, the short-term rainstorm weather can also be triggered in the anticyclone circulation in the strong subtropical high ridge. Its large-scale circulation characteristics are quite different from the typical rainstorm process in Hunan. (2) Before the occurrence of convective precipitation, the unstable energy was significantly enhanced. The humidification in the middle and lower layers was obvious, providing energy and water vapour conditions for the rainstorm. (3) The two processes were respectively affected by the disturbance of the outer cloud system of the tropical cyclone on the south side of the subtropical high and the intrusion of weak cold air. There was weak disturbance or weak shear forming at 925 hPa, cooperating with the ground mesoscale convergence line. Near-surface dynamic uplift triggered convective precipitation. Affected by solar radiation during the day, it could freely touch heat convection. Topographic uplift was also an important trigger mechanism. Thermal convection occurred on the windward slope, accounting for 84%. (4) The radar echoes of two short-term rainstorms were obvious precipitation echoes with a low centroid and high efficiency. The environmental wind and its vertical wind shear were small, which was not conducive to the organized development of convective storms. However, the thunderstorm monomer moved slowly, which was conducive to long-term heavy precipitation in the same area.
Based on the ground automatic station data, doppler weather radar data, satellite hourly TBB data and NCEP reanalysis data, we analyze the occurrence and maintenance mechanism of two short-term rainstorms in Hunan under the control of subtropical high in 2018. The results show that: (1) Under the condition of abundant water vapour and sufficient unstable energy and uplift, the short-term rainstorm weather can also be triggered in the anticyclone circulation in the strong subtropical high ridge. Its large-scale circulation characteristics are quite different from the typical rainstorm process in Hunan. (2) Before the occurrence of convective precipitation, the unstable energy was significantly enhanced. The humidification in the middle and lower layers was obvious, providing energy and water vapour conditions for the rainstorm. (3) The two processes were respectively affected by the disturbance of the outer cloud system of the tropical cyclone on the south side of the subtropical high and the intrusion of weak cold air. There was weak disturbance or weak shear forming at 925 hPa, cooperating with the ground mesoscale convergence line. Near-surface dynamic uplift triggered convective precipitation. Affected by solar radiation during the day, it could freely touch heat convection. Topographic uplift was also an important trigger mechanism. Thermal convection occurred on the windward slope, accounting for 84%. (4) The radar echoes of two short-term rainstorms were obvious precipitation echoes with a low centroid and high efficiency. The environmental wind and its vertical wind shear were small, which was not conducive to the organized development of convective storms. However, the thunderstorm monomer moved slowly, which was conducive to long-term heavy precipitation in the same area.
2022, 50(4):526-535.
DOI: 10.19517/j.1671-6345.20210394
Abstract:
Based on the winter temperature and NCEP reanalysis data and the realtime prediction data of the CFS model in Southwest China, the SVD diagnostic analysis is used to select the atmospheric circulation and early sea temperature and OLR factor fields in the key areas affecting the winter temperature in Southwest China, and to establish a combined statistical drop scale prediction model combining prediction and observation fields. The results of this statistical downscale forecast model for 1982-2017 show that the spatial correlation coefficient with the observation field is significantly higher than the original results of the CFS model, with the multi-year mean increasing from -0.06 to 0.38, up to 0.85. At the same time, this scale prediction model can better restore the spatial distribution of winter temperature in Southwest China.
Based on the winter temperature and NCEP reanalysis data and the realtime prediction data of the CFS model in Southwest China, the SVD diagnostic analysis is used to select the atmospheric circulation and early sea temperature and OLR factor fields in the key areas affecting the winter temperature in Southwest China, and to establish a combined statistical drop scale prediction model combining prediction and observation fields. The results of this statistical downscale forecast model for 1982-2017 show that the spatial correlation coefficient with the observation field is significantly higher than the original results of the CFS model, with the multi-year mean increasing from -0.06 to 0.38, up to 0.85. At the same time, this scale prediction model can better restore the spatial distribution of winter temperature in Southwest China.
2022, 50(4):536-544.
DOI: 10.19517/j.1671-6345.20210419
Abstract:
Advanced Geosynchronous Radiation Imager (AGRI) mounted on FY-4A significantly improved both temporal and spatial resolution compared with Visible and Infrared Spin-Scan Radiometer (VISSR) mounted on the Chinese first-generation geostationary meteorological satellite Fengyun-2. Based on FY-4A AGRI imager Infrared Difference Dust Index(IDDI) and a new improved day-night sand-dust remote sensing algorithm, this paper carries out continuous remote sensing monitoring of dust processes in the northern China and systematically analyzes the characteristics and affected areas of three typical sandstorms in 2021. The total impact area of the three typical sand-dust processes in the northern provinces of China reaches a minimum of more than 2.6 million square kilometres and a maximum of more than 3 million square kilometres. The dust storm from April 14 to 17 affected the largest area. The result shows that in 2021, the areas with high sand and dust occurrences were in the southern Xinjiang, north of the Hexi Corridor in Gansu, and western Inner Mongolia. Compared with the same period in 2019 and 2020, the occurrence of sand and dust storms in the northern China in 2021 had a higher frequency and a larger influence area. The results show that the new generation of FY-4A geostationary satellite has a more complete ability to monitor the interannual variation of dust processes in China.
Advanced Geosynchronous Radiation Imager (AGRI) mounted on FY-4A significantly improved both temporal and spatial resolution compared with Visible and Infrared Spin-Scan Radiometer (VISSR) mounted on the Chinese first-generation geostationary meteorological satellite Fengyun-2. Based on FY-4A AGRI imager Infrared Difference Dust Index(IDDI) and a new improved day-night sand-dust remote sensing algorithm, this paper carries out continuous remote sensing monitoring of dust processes in the northern China and systematically analyzes the characteristics and affected areas of three typical sandstorms in 2021. The total impact area of the three typical sand-dust processes in the northern provinces of China reaches a minimum of more than 2.6 million square kilometres and a maximum of more than 3 million square kilometres. The dust storm from April 14 to 17 affected the largest area. The result shows that in 2021, the areas with high sand and dust occurrences were in the southern Xinjiang, north of the Hexi Corridor in Gansu, and western Inner Mongolia. Compared with the same period in 2019 and 2020, the occurrence of sand and dust storms in the northern China in 2021 had a higher frequency and a larger influence area. The results show that the new generation of FY-4A geostationary satellite has a more complete ability to monitor the interannual variation of dust processes in China.
2022, 50(4):545-553.
DOI: 10.19517/j.1671-6345.20210401
Abstract:
Based on the ERA5 reanalysis data, Doppler radar data and Beijing VDRAS data, a tornado with a supercell that occurred in Zhangjiakou on July 1, 2021, is analyzed. The results show that: (1) The tornado occured in the southeast quadrant of the cold vortex, the warm region in front of the shear line and near the surface convergence line. (2) The analysis of radar data shows that the tornado was generated on the south side of the supercell. During the tornado process, the height of more than 50 dBz was less than 6 km, and the strong core centre was less than 3 km, which was a convective system with a low centroid centre. In the wind field retrieved by radar, there was a closed cyclonic circulation at the lower level of 1 km. (3) The analysis of VDRAS data in Beijing shows that the strong convergence in the lower layer, divergence in the upper layer and the strong positive storm-relative helicity in the middle and lower layer provided favourable environmental conditions for the tornado occurrence. The vertical velocity distribution shows that there was strong upward movement and sinking velocity zone on both sides of the tornado. The vertical distribution of the disturbance temperature indicates that there was a negative centre below 4 km and a positive centre above 4 km.
Based on the ERA5 reanalysis data, Doppler radar data and Beijing VDRAS data, a tornado with a supercell that occurred in Zhangjiakou on July 1, 2021, is analyzed. The results show that: (1) The tornado occured in the southeast quadrant of the cold vortex, the warm region in front of the shear line and near the surface convergence line. (2) The analysis of radar data shows that the tornado was generated on the south side of the supercell. During the tornado process, the height of more than 50 dBz was less than 6 km, and the strong core centre was less than 3 km, which was a convective system with a low centroid centre. In the wind field retrieved by radar, there was a closed cyclonic circulation at the lower level of 1 km. (3) The analysis of VDRAS data in Beijing shows that the strong convergence in the lower layer, divergence in the upper layer and the strong positive storm-relative helicity in the middle and lower layer provided favourable environmental conditions for the tornado occurrence. The vertical velocity distribution shows that there was strong upward movement and sinking velocity zone on both sides of the tornado. The vertical distribution of the disturbance temperature indicates that there was a negative centre below 4 km and a positive centre above 4 km.
2022, 50(4):554-562.
DOI: 10.19517/j.1671-6345.20210271
Abstract:
By using raindrop spectrum data derived from DSG5 precipitation meter and ground hourly precipitation data, the characteristics of raindrop spectrum distribution and its relationship to Z-I on a summer typical precipitation process that occurred in Lhasa on July 8-9, 2018, are analyzed. The results show that the trend of hourly precipitation measured by DSG5 precipitation meter and tilting rain gauge is well consistent. The main contributor to the convective cloud precipitation is the raindrops of 2.0 to 3.0 mm, and that of mixed cloud precipitation is the raindrops of 1.0 to 2.0 mm. The concentration of the raindrop spectrum on the mixed cloud precipitation is one magnitude larger than that of the convective cloud. Whether the mixed cloud or the convective cloud, the rain intensity is closely related to the mass-weighted average diameter and number concentration of the raindrops. The raindrop spectrum of this precipitation is well accorded with the Γ distribution. Compared with other areas in the Qinghai-Tibet Plateau, the differences in the spectrum parameters indicate the spatial and temporal differences in the raindrop spectrum distribution. The trends of N0、μ and λ are opposite to the trend of rain intensity. The parameters of the Z-I relationship of mixed cloud precipitation are less than those of convective clouds. Using the standard Z-I relationship radar may underestimate the rain intensity of convective cloud precipitation in the plateau areas. When rain intensity is less than 2.3 mm·h-1, radar may underestimate that of mixed cloud precipitation. Otherwise, radar may overestimate precipitation.
By using raindrop spectrum data derived from DSG5 precipitation meter and ground hourly precipitation data, the characteristics of raindrop spectrum distribution and its relationship to Z-I on a summer typical precipitation process that occurred in Lhasa on July 8-9, 2018, are analyzed. The results show that the trend of hourly precipitation measured by DSG5 precipitation meter and tilting rain gauge is well consistent. The main contributor to the convective cloud precipitation is the raindrops of 2.0 to 3.0 mm, and that of mixed cloud precipitation is the raindrops of 1.0 to 2.0 mm. The concentration of the raindrop spectrum on the mixed cloud precipitation is one magnitude larger than that of the convective cloud. Whether the mixed cloud or the convective cloud, the rain intensity is closely related to the mass-weighted average diameter and number concentration of the raindrops. The raindrop spectrum of this precipitation is well accorded with the Γ distribution. Compared with other areas in the Qinghai-Tibet Plateau, the differences in the spectrum parameters indicate the spatial and temporal differences in the raindrop spectrum distribution. The trends of N0、μ and λ are opposite to the trend of rain intensity. The parameters of the Z-I relationship of mixed cloud precipitation are less than those of convective clouds. Using the standard Z-I relationship radar may underestimate the rain intensity of convective cloud precipitation in the plateau areas. When rain intensity is less than 2.3 mm·h-1, radar may underestimate that of mixed cloud precipitation. Otherwise, radar may overestimate precipitation.
2022, 50(4):563-573.
DOI: 10.19517/j.1671-6345.20210300
Abstract:
Based on the visibility, temperature, pressure, humidity, wind and atmospheric particulate concentration data in Chongqing, the characteristics and influencing factors of visibility in Chongqing are analyzed. The visibility forecast model is established using the neural network method, and the effects of introducing the PM2.5 concentration factor on the forecast model are analyzed and compared. The results show that the visibility distribution in Chongqing is low in the west, high in the east, and low along the Yangtze River. The average visibility during fog is lower than that during precipitation and much lower after removing the data of rain and fog days, indicating that low visibility is more affected by water vapour in the atmosphere. The proportion of fog increases significantly in winter, leading to a significant decrease in average visibility in winter. The precipitation increase in June and October is an important reason for the significant decrease in average visibility in these two months. The diurnal variation of visibility shows a single-peak pattern, and the periods of high fog and precipitation overlap with the areas of low average visibility, which is an important reason for the low visibility at night. Atmospheric humidity, temperature and particle concentration are all critical factors affecting visibility. When relative humidity is less than 70%, visibility decreases significantly with the increase of PM2.5, and when relative humidity is more than 70%, the influence of PM2.5 on visibility decreases. The prediction effect of introducing the PM2.5 concentration factor into the visibility objective forecast model is better than that of not introducing the PM2.5 concentration factor, especially the prediction effect in autumn and winter is significantly improved.
Based on the visibility, temperature, pressure, humidity, wind and atmospheric particulate concentration data in Chongqing, the characteristics and influencing factors of visibility in Chongqing are analyzed. The visibility forecast model is established using the neural network method, and the effects of introducing the PM2.5 concentration factor on the forecast model are analyzed and compared. The results show that the visibility distribution in Chongqing is low in the west, high in the east, and low along the Yangtze River. The average visibility during fog is lower than that during precipitation and much lower after removing the data of rain and fog days, indicating that low visibility is more affected by water vapour in the atmosphere. The proportion of fog increases significantly in winter, leading to a significant decrease in average visibility in winter. The precipitation increase in June and October is an important reason for the significant decrease in average visibility in these two months. The diurnal variation of visibility shows a single-peak pattern, and the periods of high fog and precipitation overlap with the areas of low average visibility, which is an important reason for the low visibility at night. Atmospheric humidity, temperature and particle concentration are all critical factors affecting visibility. When relative humidity is less than 70%, visibility decreases significantly with the increase of PM2.5, and when relative humidity is more than 70%, the influence of PM2.5 on visibility decreases. The prediction effect of introducing the PM2.5 concentration factor into the visibility objective forecast model is better than that of not introducing the PM2.5 concentration factor, especially the prediction effect in autumn and winter is significantly improved.
2022, 50(4):574-583.
DOI: 10.19517/j.1671-6345.20210384
Abstract:
Based on the observation from Automatic Weather Stations (AWS) and atmospheric environment monitoring stations, along with ERA5 reanalysis data between 2015 and 2020, the variation characteristics of main pollutants, as well as the relationship between synoptic pattern and meteorological elements in Yuncheng, a city of the eastern Fenwei Plain are comprehensively analyzed. The results show that the annual average concentrations of PM2.5, PM10, SO2, NO2, and CO in the city from 2015 to 2020 show a downward trend, while the annual average concentration of O3 shows an upward trend. The air quality in winter and summer is relatively poor, with PM2.5 and O3 as the major pollutant in winter and summer, respectively. There is a close relationship between the variation of Boundary Layer Height (BLH) and wind direction, wind speed and pollutant concentration in the eastern Fenwei Plain. In the winter, heavy PM2.5 pollution usually happens on the days with low BLH and relatively small northwesterly prevailing winds. In contrast, the heavy pollution in summer usually occurs on the days with tall BLH and relatively large south-easterly prevailing winds. Finally, using the Self-Organizing Map neural (SOM) network algorithm, the synoptic patterns are identified from geopotential height fields at the height of 925 hPa in winter and summer, and the relationship between the variation of pollutant concentration and meteorological elements under different synoptic patterns are elucidated. It is shown that the weather partterns characterized by weak northeasterly prevailing winds are found to be associated with heavy PM2.5 pollution, which is transported from the heavily polluted regions to Yuncheng, while O3 pollution in summer is linked to the synoptic pattern featured by heat low pressure and strong radiation, which is conductive to the gathering of O3 precursor.
Based on the observation from Automatic Weather Stations (AWS) and atmospheric environment monitoring stations, along with ERA5 reanalysis data between 2015 and 2020, the variation characteristics of main pollutants, as well as the relationship between synoptic pattern and meteorological elements in Yuncheng, a city of the eastern Fenwei Plain are comprehensively analyzed. The results show that the annual average concentrations of PM2.5, PM10, SO2, NO2, and CO in the city from 2015 to 2020 show a downward trend, while the annual average concentration of O3 shows an upward trend. The air quality in winter and summer is relatively poor, with PM2.5 and O3 as the major pollutant in winter and summer, respectively. There is a close relationship between the variation of Boundary Layer Height (BLH) and wind direction, wind speed and pollutant concentration in the eastern Fenwei Plain. In the winter, heavy PM2.5 pollution usually happens on the days with low BLH and relatively small northwesterly prevailing winds. In contrast, the heavy pollution in summer usually occurs on the days with tall BLH and relatively large south-easterly prevailing winds. Finally, using the Self-Organizing Map neural (SOM) network algorithm, the synoptic patterns are identified from geopotential height fields at the height of 925 hPa in winter and summer, and the relationship between the variation of pollutant concentration and meteorological elements under different synoptic patterns are elucidated. It is shown that the weather partterns characterized by weak northeasterly prevailing winds are found to be associated with heavy PM2.5 pollution, which is transported from the heavily polluted regions to Yuncheng, while O3 pollution in summer is linked to the synoptic pattern featured by heat low pressure and strong radiation, which is conductive to the gathering of O3 precursor.
JIANG Jiang
,
YE Caihua
,
LIU Meide
,
YOU Huanling
,
QIAO Yuan
,
XIA Jiangjiang
,
TONG Ying
,
ZHANG Yong
,
YAN Ting
,
LI Qiuhong
,
LIU Ting
,
ZHOU Xiaojie
,
ZENG Xiaofan
2022, 50(4):584-593.
DOI: 10.19517/j.1671-6345.20210422
Abstract:
This paper analyzes the relationship between mosquito density and meteorological conditions from 2009 to 2019 in Beijing and its 14 districts based on three machine learning methods. The result shows that the mosquito density fluctuates periodically from May to October each year. The average is between 0.35 to 2.54 per lamp·hour, and the peak appears in mid-July to mid-August, corresponding to the period of highest temperature and most precipitation in Beijing. We choose Multiple Regression, Support Vector Machine and Random Forest to predict the mosquito density for ten days with different input factors. RMSE and MAPE are used to test the prediction effect. It turns out that it is relatively better in areas where the mosquito density is stable, such as Pinggu, Mentougou, Daxing, Haidian and so on. In addition, among the three methods, the support Vector Machine Method has a very good prediction effect in late May 2019, while the prediction effect of Multiple Regression and the Random Forest is more stable from May to October 2019.
This paper analyzes the relationship between mosquito density and meteorological conditions from 2009 to 2019 in Beijing and its 14 districts based on three machine learning methods. The result shows that the mosquito density fluctuates periodically from May to October each year. The average is between 0.35 to 2.54 per lamp·hour, and the peak appears in mid-July to mid-August, corresponding to the period of highest temperature and most precipitation in Beijing. We choose Multiple Regression, Support Vector Machine and Random Forest to predict the mosquito density for ten days with different input factors. RMSE and MAPE are used to test the prediction effect. It turns out that it is relatively better in areas where the mosquito density is stable, such as Pinggu, Mentougou, Daxing, Haidian and so on. In addition, among the three methods, the support Vector Machine Method has a very good prediction effect in late May 2019, while the prediction effect of Multiple Regression and the Random Forest is more stable from May to October 2019.
2022, 50(4):594-599.
DOI: 10.19517/j.1671-6345.20210340
Abstract:
In recent years, the demand for mobile meteorological services has grown rapidly, and the auxiliary decisionmaking function of meteorological information has become more and more prominent in modern meteorological service systems. How to quickly establish a reliable, easy-to-expand, autonomous, and controllable mobile weather service system has become the core concern of meteorological departments at all levels. This paper introduces the overall design of building a refined mobile meteorological service system based on the Hybrid mode and realizes the display and interaction of meteorological information on mobile terminals through Hybrid, component-based development, MVC framework, HTML5 fusion and other key technologies. It embodies the technical advantages of the Hybrid development mode in the aspects of high function reuse and convenient iteration and upgrades. After iteratively upgrading for nearly five years, the system products have been widely applied in the meteorological departments, governments, and key industries at all levels in Shandong Province. It has played an essential role in meteorological services for social disaster prevention, mitigation and relief.
In recent years, the demand for mobile meteorological services has grown rapidly, and the auxiliary decisionmaking function of meteorological information has become more and more prominent in modern meteorological service systems. How to quickly establish a reliable, easy-to-expand, autonomous, and controllable mobile weather service system has become the core concern of meteorological departments at all levels. This paper introduces the overall design of building a refined mobile meteorological service system based on the Hybrid mode and realizes the display and interaction of meteorological information on mobile terminals through Hybrid, component-based development, MVC framework, HTML5 fusion and other key technologies. It embodies the technical advantages of the Hybrid development mode in the aspects of high function reuse and convenient iteration and upgrades. After iteratively upgrading for nearly five years, the system products have been widely applied in the meteorological departments, governments, and key industries at all levels in Shandong Province. It has played an essential role in meteorological services for social disaster prevention, mitigation and relief.
2022, 50(4):600-605.
DOI: 10.19517/j.1671-6345.20210459
Abstract:
Meteorological satellite data are the core cornerstone of remote sensing applications, and the remote sensing business platform is an essential technical means. Using the distributed NAS storage in the data centre of the Guangdong Meteorological Bureau, this paper sets up FY-3d and FY-4a data resource pools. Through data synchronization and user management technology, this paper designs the Guangdong Meteorological Satellite Data Resource Pool V1.0 for desktop business applications. Using two meteorological remote sensing application systems (SMART and SWAP), the technical personnel can quickly produce meteorological satellite remote sensing monitoring and evaluation products at all levels. Through the above “cloud + end” remote sensing business architecture, the difficult problem of not easy to obtain meteorological remote sensing data and the technical barriers of remote sensing application are effectively solved, which provides a certain application demonstration and reference value for promoting the integration of meteorological satellite remote sensing operation at the provincial, municipal and county levels.
Meteorological satellite data are the core cornerstone of remote sensing applications, and the remote sensing business platform is an essential technical means. Using the distributed NAS storage in the data centre of the Guangdong Meteorological Bureau, this paper sets up FY-3d and FY-4a data resource pools. Through data synchronization and user management technology, this paper designs the Guangdong Meteorological Satellite Data Resource Pool V1.0 for desktop business applications. Using two meteorological remote sensing application systems (SMART and SWAP), the technical personnel can quickly produce meteorological satellite remote sensing monitoring and evaluation products at all levels. Through the above “cloud + end” remote sensing business architecture, the difficult problem of not easy to obtain meteorological remote sensing data and the technical barriers of remote sensing application are effectively solved, which provides a certain application demonstration and reference value for promoting the integration of meteorological satellite remote sensing operation at the provincial, municipal and county levels.
2022, 50(4):606-610.
DOI: 10.19517/j.1671-6345.20210504
Abstract:
In the calibration process of the double tipping bucket rain sensor, for the rain gauge with different rain intensities in the opposite direction, it is necessary to adjust the positioning screw of the upper tipping bucket and the capacity adjustment screw of the metering tipping bucket respectively. At the same time, it is also necessary to record the turnover times of the upper tipping bucket and the metering tipping bucket. The rain gauge uses a passive pulse output. Each time the measuring bucket is flipped, it triggers the reed tube to produce a pulse. The signal can be collected by the single-chip microcomputer and recorded automatically. However, the turning times of the up-tipping bucket depend on manual observation and statistics. Because the tipping speed of the up-tipping bucket is fast, the manual counting is inaccurate, resulting in an inaccurate calibration. In addition, only one rain gauge can be manually recorded at a time, which cannot automatically record data in batches. In this paper, the optical fibre sensor is used to automatically count the number of tipping buckets under the condition of the rain gauge’s non-contact and non-interference operation to provide accurate calibration data.
In the calibration process of the double tipping bucket rain sensor, for the rain gauge with different rain intensities in the opposite direction, it is necessary to adjust the positioning screw of the upper tipping bucket and the capacity adjustment screw of the metering tipping bucket respectively. At the same time, it is also necessary to record the turnover times of the upper tipping bucket and the metering tipping bucket. The rain gauge uses a passive pulse output. Each time the measuring bucket is flipped, it triggers the reed tube to produce a pulse. The signal can be collected by the single-chip microcomputer and recorded automatically. However, the turning times of the up-tipping bucket depend on manual observation and statistics. Because the tipping speed of the up-tipping bucket is fast, the manual counting is inaccurate, resulting in an inaccurate calibration. In addition, only one rain gauge can be manually recorded at a time, which cannot automatically record data in batches. In this paper, the optical fibre sensor is used to automatically count the number of tipping buckets under the condition of the rain gauge’s non-contact and non-interference operation to provide accurate calibration data.
External LinksChina Meteorological AdministrationCMA Meteorological Observation CentreChinese Academy of Meteorological SciencesBeijing Meteorological ServiceNational Satellite Meteorological Center
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Supported by:Beijing E-Tiller Technology Development Co., Ltd.
Supported by:Beijing E-Tiller Technology Development Co., Ltd.