Volume 50,Issue 2,2022 Table of Contents
2022, 50(2):161-170.
DOI: 10.19517/j.1671-6345.20210009
Abstract:
Based on the continuous observation data of the ground-based dual-band all-sky imager (ASC200) from February to May 2019 at the National Integrated Meteorological Observation (Science) Testbed of the China Meteorological Administration in Changsha and the National Basic Weather Station in Baoshan, compared with manual and instrument measurement reference standards, the analysis aims to evaluate the detectability of ASC200 from the three aspects of visible cloud cover, infrared cloud cover and comprehensive cloud cover. The comparison results show that: Samples of comprehensive cloud cover with a difference within ±20% from manual reference standards account for 92.2% at Changsha and 79.4% at Baoshan of the total samples, respectively. Samples of comprehensive cloud cover at Changsha with a difference within ±20% from instrument measurement reference standard cloud cover account for 90.5%, and those with a difference within ±10% account for 86%. The results indicate: (1) Samples of ASC200 comprehensive cloud cover are in good consistency with manual and instrument measurement reference standards; (2) It is verified that the visible cloud observation system is weak in observation under haze or fog weather, and the infrared cloud observation system is weak in cirrus observation; (3) Under the conventional observation conditions with better visibility, the dualband cloud cover observation system is superior to the single band cloud cover observation system.
Based on the continuous observation data of the ground-based dual-band all-sky imager (ASC200) from February to May 2019 at the National Integrated Meteorological Observation (Science) Testbed of the China Meteorological Administration in Changsha and the National Basic Weather Station in Baoshan, compared with manual and instrument measurement reference standards, the analysis aims to evaluate the detectability of ASC200 from the three aspects of visible cloud cover, infrared cloud cover and comprehensive cloud cover. The comparison results show that: Samples of comprehensive cloud cover with a difference within ±20% from manual reference standards account for 92.2% at Changsha and 79.4% at Baoshan of the total samples, respectively. Samples of comprehensive cloud cover at Changsha with a difference within ±20% from instrument measurement reference standard cloud cover account for 90.5%, and those with a difference within ±10% account for 86%. The results indicate: (1) Samples of ASC200 comprehensive cloud cover are in good consistency with manual and instrument measurement reference standards; (2) It is verified that the visible cloud observation system is weak in observation under haze or fog weather, and the infrared cloud observation system is weak in cirrus observation; (3) Under the conventional observation conditions with better visibility, the dualband cloud cover observation system is superior to the single band cloud cover observation system.
2022, 50(2):171-178.
DOI: 10.19517/j.1671-6345.20210136
Abstract:
Based on the basic principle of upper wind sounding, a smoothing algorithm of upper wind used in routine operation for satellite navigation radiosonde system is presented. Firstly, the original upper wind is calculated in a geocentric coordinate system based on the second geodetic coordinate data provided by the Beidou-GPS dual-mode radiosonde. Then, the vector average method is adopted to smooth the original upper wind. Through comparative analysis with the RS92 radiosonde system launched on the same ball, the upper wind of the satellite navigation radiosonde system coincides with the RS92 radiosonde system under the condition that the moving average window is set to 34 s in the range of 0 to 32 km and 60 s above 32 km. The calculation result of this algorithm is basically the same as the 30 s moving average wind calculated in the local Cartesian coordinates coordinate system. However, its wind components’ confidence interval is slightly better below 32 km and obviously reduced above 32 km, and the error of the whole flight is more stable.
Based on the basic principle of upper wind sounding, a smoothing algorithm of upper wind used in routine operation for satellite navigation radiosonde system is presented. Firstly, the original upper wind is calculated in a geocentric coordinate system based on the second geodetic coordinate data provided by the Beidou-GPS dual-mode radiosonde. Then, the vector average method is adopted to smooth the original upper wind. Through comparative analysis with the RS92 radiosonde system launched on the same ball, the upper wind of the satellite navigation radiosonde system coincides with the RS92 radiosonde system under the condition that the moving average window is set to 34 s in the range of 0 to 32 km and 60 s above 32 km. The calculation result of this algorithm is basically the same as the 30 s moving average wind calculated in the local Cartesian coordinates coordinate system. However, its wind components’ confidence interval is slightly better below 32 km and obviously reduced above 32 km, and the error of the whole flight is more stable.
2022, 50(2):179-188.
DOI: 10.19517/j.1671-6345.20210209
Abstract:
In order to improve the operational application quality and efficiency of the monitoring data of the ADTD lightning monitoring system, the lightning monitoring data of the system in Hubei Province from 2006 to 2019 are used to statistically analyze the ground lightning distribution law near several high-rise buildings and the time-space distribution law of the whole province through the grid method, lightning case verification method and qualitative analysis method. The positioning accuracy is verified by lightning accidents. The results show that: (1) There is a deviation between the high-value areas of ground lightning return stroke times around four high-rise buildings in Hubei and the actual positions of highrise buildings, and the actual location of the buildings. The deviation distance ranges from 190 to 1548 m, and the deviation azimuth is not regular. (2) The positioning deviation data of four reference points of high-rise buildings and the actual lightning stroke points of lightning disaster accidents corresponding to the lightning monitoring system show that the average positioning error of the system in plain area is 539 m, the average positioning error in mountainous area is 1384 m, and the positioning error in mountainous area is significantly greater than that in plain area. (3) The temporal and spatial distribution characteristics of the system’s monitoring data are in good agreement with the precipitation characteristics of Hubei and the monitoring data of similar monitoring systems in surrounding provinces and cities of Hubei. The fitting degree between the cumulative probability characteristics of lightning current and the distribution regulation recommended by IEEE is high, indicating that the main parameters monitored by the system have a certain accuracy.
In order to improve the operational application quality and efficiency of the monitoring data of the ADTD lightning monitoring system, the lightning monitoring data of the system in Hubei Province from 2006 to 2019 are used to statistically analyze the ground lightning distribution law near several high-rise buildings and the time-space distribution law of the whole province through the grid method, lightning case verification method and qualitative analysis method. The positioning accuracy is verified by lightning accidents. The results show that: (1) There is a deviation between the high-value areas of ground lightning return stroke times around four high-rise buildings in Hubei and the actual positions of highrise buildings, and the actual location of the buildings. The deviation distance ranges from 190 to 1548 m, and the deviation azimuth is not regular. (2) The positioning deviation data of four reference points of high-rise buildings and the actual lightning stroke points of lightning disaster accidents corresponding to the lightning monitoring system show that the average positioning error of the system in plain area is 539 m, the average positioning error in mountainous area is 1384 m, and the positioning error in mountainous area is significantly greater than that in plain area. (3) The temporal and spatial distribution characteristics of the system’s monitoring data are in good agreement with the precipitation characteristics of Hubei and the monitoring data of similar monitoring systems in surrounding provinces and cities of Hubei. The fitting degree between the cumulative probability characteristics of lightning current and the distribution regulation recommended by IEEE is high, indicating that the main parameters monitored by the system have a certain accuracy.
4 Improving the FY-3D MWRI Sea Surface Temperature Based on Simulated 6.9 GHz Brightness Temperature
2022, 50(2):189-193.
DOI: 10.19517/j.1671-6345.20210337
Abstract:
SST (Sea Surface Temperature) is one of the most important parameters in the global ocean and climate research. Satellite passive microwave remote sensing is used more and more in SST research to realize all-weather observation. The Microwave Imager (MWRI) on the FY-3 satellite lacks the 7GHz vertical polarization channel, which is more sensitive to SST. In this study, FY-3 MWRI and AQUA AMSR-2 are spatiotemporally matched, and the neural network method is used to simulate the 6.9 GHz vertical polarization brightness temperature (6.9V) of AMSR-2 using the matched MWRI channel brightness temperature. The simulated 6.9V is introduced to the inversion of FY3 MWRI SST. The results show that: After introducing the simulated 6.9V, the inversion accuracy of SST is improved, and the improvement in 35°-90°S is more significant, mainly due to the higher sensitivity of 6.9V to low SST and the less influence of wind speed in the inversion of low SST. If the follow-up satellite of FY-3 can carry 6.9 GHz channel, the retrieval accuracy of the low SST particularly at the higher latitudes will be further improved.
SST (Sea Surface Temperature) is one of the most important parameters in the global ocean and climate research. Satellite passive microwave remote sensing is used more and more in SST research to realize all-weather observation. The Microwave Imager (MWRI) on the FY-3 satellite lacks the 7GHz vertical polarization channel, which is more sensitive to SST. In this study, FY-3 MWRI and AQUA AMSR-2 are spatiotemporally matched, and the neural network method is used to simulate the 6.9 GHz vertical polarization brightness temperature (6.9V) of AMSR-2 using the matched MWRI channel brightness temperature. The simulated 6.9V is introduced to the inversion of FY3 MWRI SST. The results show that: After introducing the simulated 6.9V, the inversion accuracy of SST is improved, and the improvement in 35°-90°S is more significant, mainly due to the higher sensitivity of 6.9V to low SST and the less influence of wind speed in the inversion of low SST. If the follow-up satellite of FY-3 can carry 6.9 GHz channel, the retrieval accuracy of the low SST particularly at the higher latitudes will be further improved.
2022, 50(2):194-201.
DOI: 10.19517/j.1671-6345.20210224
Abstract:
Meteorological data are essential for weather forecast and climate prediction with complex formats. In view of the lack of convenient and general format conversion processing tools in meteorological data application research, a general meteorological data format conversion tool is designed and developed with python, which implements the algorithm factory and calls the third-party meteorological data processing library to integrate the interpretation, analysis and format conversion of meteorological data. It provides the command-line and visual application tool for application scenarios. The tool has been published on the website of the Beijing high-performance computer application centre and deployed in the pilot support environment of the numerical prediction model.
Meteorological data are essential for weather forecast and climate prediction with complex formats. In view of the lack of convenient and general format conversion processing tools in meteorological data application research, a general meteorological data format conversion tool is designed and developed with python, which implements the algorithm factory and calls the third-party meteorological data processing library to integrate the interpretation, analysis and format conversion of meteorological data. It provides the command-line and visual application tool for application scenarios. The tool has been published on the website of the Beijing high-performance computer application centre and deployed in the pilot support environment of the numerical prediction model.
2022, 50(2):202-213.
DOI: 10.19517/j.1671-6345.20210111
Abstract:
On November 25th 2015, the cold air broke out over the Yellow Sea, causing snow storms in the northern China. Cloud streets with NW-SE orientation were densely distributed over the Yellow Sea. In order to study whether the grid size dependence of vertical heat transport will affect the numerical simulation of convective cloud streets over the Yellow Sea, this paper uses the Weather Research and Forecasting (WRF) model with the Planetary Boundary Layer (PBL) parameterization scheme considering grid size dependence and non-local K-type Yonsei University (YSU) PBL scheme to simulate this case, respectively. The results show that both schemes can reproduce the occurrence area and prevailing wind direction of cloud streets. However, due to the stronger robustness in simulating horizontal roll convection and secondary circulation using the PBL scheme considering grid size dependence, the simulated horizontal and vertical velocity intensity is greater, and the cloud water mixing ratio is higher, which enables more clouds to develop. At the same time, its stability parameter ζ is smaller and the simulated horizontal roll convection intensity is greater.
On November 25th 2015, the cold air broke out over the Yellow Sea, causing snow storms in the northern China. Cloud streets with NW-SE orientation were densely distributed over the Yellow Sea. In order to study whether the grid size dependence of vertical heat transport will affect the numerical simulation of convective cloud streets over the Yellow Sea, this paper uses the Weather Research and Forecasting (WRF) model with the Planetary Boundary Layer (PBL) parameterization scheme considering grid size dependence and non-local K-type Yonsei University (YSU) PBL scheme to simulate this case, respectively. The results show that both schemes can reproduce the occurrence area and prevailing wind direction of cloud streets. However, due to the stronger robustness in simulating horizontal roll convection and secondary circulation using the PBL scheme considering grid size dependence, the simulated horizontal and vertical velocity intensity is greater, and the cloud water mixing ratio is higher, which enables more clouds to develop. At the same time, its stability parameter ζ is smaller and the simulated horizontal roll convection intensity is greater.
2022, 50(2):214-223.
DOI: 10.19517/j.1671-6345.20210197
Abstract:
FY-4 satellite cloud images, the hourly surface AWS data, NCEP-FNL reanalysis data and ERA-Interim SST data are used for analyzing intensity characteristics of Typhoon Yagi (1814) and typhoon Lekima (1909) above the Bohai Sea. The results show that Yagi’s intensification was accompanied by the invasion of cold air in the middle and upper layers. When the cold air invaded the centre of the typhoon cloud, the intensity of typhoon Yagi weakened. Before the typhoon Lekima entered the sea, the cold air had intruded into the typhoon’s centre; the typhoon weakened and died after entering the ocean. The warm-core structure of the northward typhoon was destroyed, and the symmetrical structure became asymmetrical. The lower level of the typhoon showed baroclinic characteristics. Typhoon Yagi entered a strong divergence zone through the Bohai Sea. However, the Lekima entered a weak convergence field through the Bohai Sea. The high-altitude divergence in the northward direction was conducive to the strengthening of the typhoon before the typhoon lands. The vertical wind shear and the typhoon intensity were distributed opposite, but the position conversed when the typhoons land. After Yagi entered the sea, the water vapour channel was broken, and its strength above the sea was more dependent on thermal and dynamic conditions. The water vapour flux and water vapour flux divergence of Typhoon Lekima originated from its circulation. After Yagi entered the sea, the latent heat heating rate increased sharply. The lower layer of the Lekima maintained a weak latent heating centre until the typhoon disappears.
FY-4 satellite cloud images, the hourly surface AWS data, NCEP-FNL reanalysis data and ERA-Interim SST data are used for analyzing intensity characteristics of Typhoon Yagi (1814) and typhoon Lekima (1909) above the Bohai Sea. The results show that Yagi’s intensification was accompanied by the invasion of cold air in the middle and upper layers. When the cold air invaded the centre of the typhoon cloud, the intensity of typhoon Yagi weakened. Before the typhoon Lekima entered the sea, the cold air had intruded into the typhoon’s centre; the typhoon weakened and died after entering the ocean. The warm-core structure of the northward typhoon was destroyed, and the symmetrical structure became asymmetrical. The lower level of the typhoon showed baroclinic characteristics. Typhoon Yagi entered a strong divergence zone through the Bohai Sea. However, the Lekima entered a weak convergence field through the Bohai Sea. The high-altitude divergence in the northward direction was conducive to the strengthening of the typhoon before the typhoon lands. The vertical wind shear and the typhoon intensity were distributed opposite, but the position conversed when the typhoons land. After Yagi entered the sea, the water vapour channel was broken, and its strength above the sea was more dependent on thermal and dynamic conditions. The water vapour flux and water vapour flux divergence of Typhoon Lekima originated from its circulation. After Yagi entered the sea, the latent heat heating rate increased sharply. The lower layer of the Lekima maintained a weak latent heating centre until the typhoon disappears.
2022, 50(2):224-233.
DOI: 10.19517/j.1671-6345.20210290
Abstract:
Based on the rainfall disaster data of Sichuan Province from 2002 to 2020, the daily and hourly rainfall data from 156 national meteorological stations and 5727 regional meteorological stations, the spatial and temporal distribution of rainfall disasters and its relationship with rainfall characteristics in Sichuan Province are analyzed. The results show that the number of rainfall disasters in Sichuan Province has increased obviously in recent years. The number and density of rainfall disasters are the largest in the west and south of the Basin, and the number of deaths is the largest in Liangshan Prefecture and the northeast of the Basin. The disasters mainly occur from June to September and develop from the northeast, south to the west, and finally to the northeast of the Basin. The Basin has the highest possibility of a disaster occurring with torrential rains. The frequency of disaster occurrence is more than 50%, the frequency of disaster caused by heavy rain is 20%-40%, caused by heavy rain is 20%-30% in Panxi Region, caused by heavy rain is less in the western Sichuan Plateau, and caused by heavy rain is the highest, which is 10%-30%. The disasters with maximum hourly rainfall less than 10 mm in the basin area mainly occur in the south and northeast of the Basin. The disasters in the west of the Basin account for a larger proportion in each rainfall grade range. The disasters in the Panxi Region are mainly concentrated in 10-40 mm, and those in the western Sichuan Plateau are less than 20 mm. Disasters with maximum daily rainfall of less than 50 mm are mainly distributed in the south of the Basin, and those with maximum daily rainfall of more than 300 mm are mainly in the northwest of the Basin. Those with maximum daily rainfall of 50-100 mm are mainly in the south and southwest of the Basin. The proportion of 50-100 mm in the Panxi Region is the largest, and that in the western Sichuan Plateau is 25-50 mm.
Based on the rainfall disaster data of Sichuan Province from 2002 to 2020, the daily and hourly rainfall data from 156 national meteorological stations and 5727 regional meteorological stations, the spatial and temporal distribution of rainfall disasters and its relationship with rainfall characteristics in Sichuan Province are analyzed. The results show that the number of rainfall disasters in Sichuan Province has increased obviously in recent years. The number and density of rainfall disasters are the largest in the west and south of the Basin, and the number of deaths is the largest in Liangshan Prefecture and the northeast of the Basin. The disasters mainly occur from June to September and develop from the northeast, south to the west, and finally to the northeast of the Basin. The Basin has the highest possibility of a disaster occurring with torrential rains. The frequency of disaster occurrence is more than 50%, the frequency of disaster caused by heavy rain is 20%-40%, caused by heavy rain is 20%-30% in Panxi Region, caused by heavy rain is less in the western Sichuan Plateau, and caused by heavy rain is the highest, which is 10%-30%. The disasters with maximum hourly rainfall less than 10 mm in the basin area mainly occur in the south and northeast of the Basin. The disasters in the west of the Basin account for a larger proportion in each rainfall grade range. The disasters in the Panxi Region are mainly concentrated in 10-40 mm, and those in the western Sichuan Plateau are less than 20 mm. Disasters with maximum daily rainfall of less than 50 mm are mainly distributed in the south of the Basin, and those with maximum daily rainfall of more than 300 mm are mainly in the northwest of the Basin. Those with maximum daily rainfall of 50-100 mm are mainly in the south and southwest of the Basin. The proportion of 50-100 mm in the Panxi Region is the largest, and that in the western Sichuan Plateau is 25-50 mm.
2022, 50(2):234-242.
DOI: 10.19517/j.1671-6345.20210345
Abstract:
The evolution characteristics of “16.7” extremely torrential rain in Shijiazhuang is analyzed using multi-source observation data such as wind profile radar, ground GPS water vapour, microwave radiometer, weather radar, satellite cloud, lightning location and ground intensive automatic weather stations. The results show that: (1) High-value stage of total water vapour by ground-based GPS and microwave radiometer was parallel with the heavy precipitation stage. The entire water vapour was positively related to the precipitation intensity. The total water vapour content increased significantly before the beginning of precipitation, and the sudden increase of total water vapour had a hint effect on the beginning time of precipitation. The high-value time was 5 hours ahead of the starting time of precipitation. (2) The thickness and intensity of east wind in the low layer positively correlated with heavy precipitation. The wind direction of the lower layer turned to the northwest wind, indicating the end of the heavy rainfall. The emergence time of low-level jet was 5 hours earlier than the beginning time of precipitation, and the dissipation time of low-level jet was 3 hours earlier than the end time of precipitation. When its wind speed was more than 20 m·s-1, the east wind jet had a certain indication effect on the heavy precipitation. The strong rainfall corresponded to the decrease of the minimum height of low-level jet and the increase of the maximum wind speed at the lower level, which was the peak area of the low-level jet index and vertical wind shear of 0-3 km. (3) The process was more stable, and the weak lightning and thunderstorm only occurred on the 19th. Radar echo and satellite cloud showed this precipitation of mixed clouds, including large-scale stratiform cloud and cumulus cloud. The centroid of echo was low, and the training effect was obvious. It belongs to the type of tropical precipitation. The minimum of TBB was -55 ℃. The maximum reflectivity factor, vertical cumulative liquid water content, and echo top were 55 dBz, 15 kg·m-2, and 11 km, respectively, obviously related to precipitation. The large value area or velocity ambiguity appeared in the radial velocity fields.
The evolution characteristics of “16.7” extremely torrential rain in Shijiazhuang is analyzed using multi-source observation data such as wind profile radar, ground GPS water vapour, microwave radiometer, weather radar, satellite cloud, lightning location and ground intensive automatic weather stations. The results show that: (1) High-value stage of total water vapour by ground-based GPS and microwave radiometer was parallel with the heavy precipitation stage. The entire water vapour was positively related to the precipitation intensity. The total water vapour content increased significantly before the beginning of precipitation, and the sudden increase of total water vapour had a hint effect on the beginning time of precipitation. The high-value time was 5 hours ahead of the starting time of precipitation. (2) The thickness and intensity of east wind in the low layer positively correlated with heavy precipitation. The wind direction of the lower layer turned to the northwest wind, indicating the end of the heavy rainfall. The emergence time of low-level jet was 5 hours earlier than the beginning time of precipitation, and the dissipation time of low-level jet was 3 hours earlier than the end time of precipitation. When its wind speed was more than 20 m·s-1, the east wind jet had a certain indication effect on the heavy precipitation. The strong rainfall corresponded to the decrease of the minimum height of low-level jet and the increase of the maximum wind speed at the lower level, which was the peak area of the low-level jet index and vertical wind shear of 0-3 km. (3) The process was more stable, and the weak lightning and thunderstorm only occurred on the 19th. Radar echo and satellite cloud showed this precipitation of mixed clouds, including large-scale stratiform cloud and cumulus cloud. The centroid of echo was low, and the training effect was obvious. It belongs to the type of tropical precipitation. The minimum of TBB was -55 ℃. The maximum reflectivity factor, vertical cumulative liquid water content, and echo top were 55 dBz, 15 kg·m-2, and 11 km, respectively, obviously related to precipitation. The large value area or velocity ambiguity appeared in the radial velocity fields.
2022, 50(2):243-253.
DOI: 10.19517/j.1671-6345.20210103
Abstract:
To provide a basis for local fog and haze forecast in Taizhou, a heavy fog-haze episode which occurred from January 12th to 15th in 2020 is analysed based on conventional meteorological observation data, NCEP reanalysis data (1°×1°) and air quality data of environmental monitoring station from the aspects of evolution features, mechanism and backward trajectory. The results show that: Both the fog and had have diurnal variation. The PM2.5 and PM10 concentrations AQI were slightly higher than those of the fog during the process, related to the wet settlement caused during the fog. The cold air from the east road negatively impacted Taizhou, making air pollutants gather locally. More than 90% relative humidity, within 1 m·s-1 near-ground wind speed, and weak vertical exchange were significant conditions for fog formation, from night to early morning. During the day, with the relative humidity weakened to 80%, the near-ground airfield increased to 2 m·s-1, and higher air pollutants concentrate, the fog developed to haze. On the 13th, the warm advection increased above 900 hPa, causing a temperature inversion in the boundary layer. At the same time, relative humidity was over 90%, which strengthened the fog and haze. Finally, by analysing the backward trajectory, it was found that the air mass below 500 m caused the hazing process to be stable. On the 14th, the clean air mass above 500 m was supplied to lower levels, conducive to the diffusion of haze. On the evening of the 15th, the high wind and precipitationed ended the fog-haze process.
To provide a basis for local fog and haze forecast in Taizhou, a heavy fog-haze episode which occurred from January 12th to 15th in 2020 is analysed based on conventional meteorological observation data, NCEP reanalysis data (1°×1°) and air quality data of environmental monitoring station from the aspects of evolution features, mechanism and backward trajectory. The results show that: Both the fog and had have diurnal variation. The PM2.5 and PM10 concentrations AQI were slightly higher than those of the fog during the process, related to the wet settlement caused during the fog. The cold air from the east road negatively impacted Taizhou, making air pollutants gather locally. More than 90% relative humidity, within 1 m·s-1 near-ground wind speed, and weak vertical exchange were significant conditions for fog formation, from night to early morning. During the day, with the relative humidity weakened to 80%, the near-ground airfield increased to 2 m·s-1, and higher air pollutants concentrate, the fog developed to haze. On the 13th, the warm advection increased above 900 hPa, causing a temperature inversion in the boundary layer. At the same time, relative humidity was over 90%, which strengthened the fog and haze. Finally, by analysing the backward trajectory, it was found that the air mass below 500 m caused the hazing process to be stable. On the 14th, the clean air mass above 500 m was supplied to lower levels, conducive to the diffusion of haze. On the evening of the 15th, the high wind and precipitationed ended the fog-haze process.
2022, 50(2):254-266.
DOI: 10.19517/j.1671-6345.20210248
Abstract:
The natural icing flight test is a highly difficult and high-risk subject that must be implemented for transportation aircraft certification. It needs to meet the conditions of ambient temperature, cloud Liquid Water Content (LWC) and cloud drop Median Volume Diameter (MVD) and complete the required flight manoeuvres in an environment containing a lot of supercooled liquid water. This paper uses the ground, high-altitude, satellite, radar and airborne detection data from the natural icing test flight of a domestic large transport aircraft at Yanliang Airport on 16th, 26th and 27th March 2020. The meteorological conditions of the three natural icing test flights are compared and analyzed. And the effectiveness of Li Baiping’s improved natural icing potential algorithm is verified. The results show that Li Baiping’s improved natural icing potential algorithm is more accurate for predicting icing location, but it needs further optimization in the prediction of icing intensity. Due to insufficient water vapour conditions in the west wind system, the natural icing weather conditions are worse than those in the southern branch system. Before the high-altitude cold air reaches the test flight area, the ambient temperature in the cloud is relatively high, and the icing intensity is low. The cold and warm air meets a higher LWC, a more suitable MVD, and strong icing. The research results are of reference significance for determining the window and airspace for the natural icing flight test of transportation aircraft at Yanliang Airport and the coordinated command guarantee in the future.
The natural icing flight test is a highly difficult and high-risk subject that must be implemented for transportation aircraft certification. It needs to meet the conditions of ambient temperature, cloud Liquid Water Content (LWC) and cloud drop Median Volume Diameter (MVD) and complete the required flight manoeuvres in an environment containing a lot of supercooled liquid water. This paper uses the ground, high-altitude, satellite, radar and airborne detection data from the natural icing test flight of a domestic large transport aircraft at Yanliang Airport on 16th, 26th and 27th March 2020. The meteorological conditions of the three natural icing test flights are compared and analyzed. And the effectiveness of Li Baiping’s improved natural icing potential algorithm is verified. The results show that Li Baiping’s improved natural icing potential algorithm is more accurate for predicting icing location, but it needs further optimization in the prediction of icing intensity. Due to insufficient water vapour conditions in the west wind system, the natural icing weather conditions are worse than those in the southern branch system. Before the high-altitude cold air reaches the test flight area, the ambient temperature in the cloud is relatively high, and the icing intensity is low. The cold and warm air meets a higher LWC, a more suitable MVD, and strong icing. The research results are of reference significance for determining the window and airspace for the natural icing flight test of transportation aircraft at Yanliang Airport and the coordinated command guarantee in the future.
2022, 50(2):267-272.
DOI: 10.19517/j.1671-6345.20210317
Abstract:
Using the maximum wind speed data of 142 national meteorological stations in Hebei Province from 2001 to 2020, this paper analyzes the background of wind speed change in Hebei Province in recent 20 years. We select 30 representative days from February to May in 2021 with a daily extreme wind speed over 13.9 m/s and the daily 10min average maximum wind speed over 8 m/s. Using the wind observation data of the meteorological stations in Chongli, Nanwopu, Changdi, Gaojiaying and Xiwanzi, the ground 10 m wind forecast data in the corresponding period of time output by ECMWF model, and the SRTM3 terrain data with 3″ resolution, the wind forecast results along the Zhangcheng Expressway in two regions of Chongli mountain area are simulated and verified by using the WT model. It is found that the correlation coefficient of wind speed of the WT model with actual observation reaches 0.6225 and passes the significance test. The error of more than 80% of the samples between simulation results and the actual situation is controlled within ±2 m/s. The error of the open terrain is obviously small. The wind direction also shows high consistency. It is proved that using the WT model to revise the wind numerical forecast along the mountain expressway is feasible. The local terrain data and the relatively stable and reliable wind numerical forecast products can be used to drive the WT model to carry out the revision application of winds along the highway in mountainous areas.
Using the maximum wind speed data of 142 national meteorological stations in Hebei Province from 2001 to 2020, this paper analyzes the background of wind speed change in Hebei Province in recent 20 years. We select 30 representative days from February to May in 2021 with a daily extreme wind speed over 13.9 m/s and the daily 10min average maximum wind speed over 8 m/s. Using the wind observation data of the meteorological stations in Chongli, Nanwopu, Changdi, Gaojiaying and Xiwanzi, the ground 10 m wind forecast data in the corresponding period of time output by ECMWF model, and the SRTM3 terrain data with 3″ resolution, the wind forecast results along the Zhangcheng Expressway in two regions of Chongli mountain area are simulated and verified by using the WT model. It is found that the correlation coefficient of wind speed of the WT model with actual observation reaches 0.6225 and passes the significance test. The error of more than 80% of the samples between simulation results and the actual situation is controlled within ±2 m/s. The error of the open terrain is obviously small. The wind direction also shows high consistency. It is proved that using the WT model to revise the wind numerical forecast along the mountain expressway is feasible. The local terrain data and the relatively stable and reliable wind numerical forecast products can be used to drive the WT model to carry out the revision application of winds along the highway in mountainous areas.
2022, 50(2):273-281.
DOI: 10.19517/j.1671-6345.20210176
Abstract:
The wind disaster has caused great harm to agricultural and animal husbandry production in Xinjiang. In this study, the number of collapsed houses, collapsed sheds, death toll, damaged sheds, livestock deaths, and the affected areas of crops are taken as the six major disaster factors to construct a disaster index that can comprehensively express the wind disaster intensity using the ratio weight and dimensionless linear summation method. Based on the percentile method, the intensity of the wind disaster events is divided into four levels: general (level 1), heavy (level 2), severe (level 3), and extra heavy (level 4). The disaster damage index and disaster level are used to study the temporal and spatial variation characteristics of wind disasters in Xinjiang. The results show that the wind disasters in Xinjiang are concentrated from April to May, more in the southern Xinjiang than in the northern Xinjiang, and the Turpan Basin and the northern Tarim Basin are the frequent and serious wind disaster areas in Xinjiang. The annual occurrence times of wind disasters in the recent 30 years show a significant linear increasing trend. The annual disaster loss index does not show a linear increasing or decreasing trend, among which the interannual variation of level 1 to 4 wind disasters has apparent differences. The maximum wind speed thresholds causing level 1 to 4 wind disasters are 12.9, 13.7, 14.1 and 15.0 m·s-1, respectively. The number of days when the maximum wind speed exceeds 12.9 m·s-1 increases year by year, coupled with the rapid development of agriculture and animal husbandry production, resulting in the continuous increase of the number of wind disasters in the year.
The wind disaster has caused great harm to agricultural and animal husbandry production in Xinjiang. In this study, the number of collapsed houses, collapsed sheds, death toll, damaged sheds, livestock deaths, and the affected areas of crops are taken as the six major disaster factors to construct a disaster index that can comprehensively express the wind disaster intensity using the ratio weight and dimensionless linear summation method. Based on the percentile method, the intensity of the wind disaster events is divided into four levels: general (level 1), heavy (level 2), severe (level 3), and extra heavy (level 4). The disaster damage index and disaster level are used to study the temporal and spatial variation characteristics of wind disasters in Xinjiang. The results show that the wind disasters in Xinjiang are concentrated from April to May, more in the southern Xinjiang than in the northern Xinjiang, and the Turpan Basin and the northern Tarim Basin are the frequent and serious wind disaster areas in Xinjiang. The annual occurrence times of wind disasters in the recent 30 years show a significant linear increasing trend. The annual disaster loss index does not show a linear increasing or decreasing trend, among which the interannual variation of level 1 to 4 wind disasters has apparent differences. The maximum wind speed thresholds causing level 1 to 4 wind disasters are 12.9, 13.7, 14.1 and 15.0 m·s-1, respectively. The number of days when the maximum wind speed exceeds 12.9 m·s-1 increases year by year, coupled with the rapid development of agriculture and animal husbandry production, resulting in the continuous increase of the number of wind disasters in the year.
14 A Rapid Digitization Method of Meteorological Paper Forms Based on DBnet and Crowdfunding Strategies
2022, 50(2):282-289.
DOI: 10.19517/j.1671-6345.20210335
Abstract:
The historical data of meteorological paper forms have high scientific research value and important historical preservation significance. Digital archives are the collection, preservation and provision of various digital information resources of paper-based original materials through digital methods. This research proposes a rapid digitization method and system of “paper form scanning imaging”+“image fragmentation processing”+“crowdfunding recognition,” using meteorological big data resources, DBnet model, DSCC algorithm and other technologies to process the scanned images of paper weather forms for image fragmentation. “Crowdfunding Entry” is realized through user login behaviour, and the digital file work of weather paper table data is completed. It has been verified that the accuracy rate of one-recording of the fast digital system is about 99.7%, which is higher than the accuracy rate of one-recording of traditional digital manual input (95.6%); the input time efficiency is improved by 22.2% compared with traditional digitalization. The system ensures data accuracy, improves work efficiency, achieves the rapid formation of digital archives of meteorological paper forms and data, and provides new ideas for digital archives. The COVID19 epidemic has caused difficulties in traditional digital manual aggregation work models. Under the background of big risks, it has certain practical significance.
The historical data of meteorological paper forms have high scientific research value and important historical preservation significance. Digital archives are the collection, preservation and provision of various digital information resources of paper-based original materials through digital methods. This research proposes a rapid digitization method and system of “paper form scanning imaging”+“image fragmentation processing”+“crowdfunding recognition,” using meteorological big data resources, DBnet model, DSCC algorithm and other technologies to process the scanned images of paper weather forms for image fragmentation. “Crowdfunding Entry” is realized through user login behaviour, and the digital file work of weather paper table data is completed. It has been verified that the accuracy rate of one-recording of the fast digital system is about 99.7%, which is higher than the accuracy rate of one-recording of traditional digital manual input (95.6%); the input time efficiency is improved by 22.2% compared with traditional digitalization. The system ensures data accuracy, improves work efficiency, achieves the rapid formation of digital archives of meteorological paper forms and data, and provides new ideas for digital archives. The COVID19 epidemic has caused difficulties in traditional digital manual aggregation work models. Under the background of big risks, it has certain practical significance.
2022, 50(2):290-296.
DOI: 10.19517/j.1671-6345.20210195
Abstract:
In order to adapt to the requirements of computing power and storage resources for scientific research applications of meteorological operations, the cloud platform of meteorological infrastructure is built by using distributed computing, distributed storage and virtualization technology. And the cloud platform resource partition is designed according to different business categories, network partition, resource service objects, and each partition needs to have cloud resources. The designed cloud platform covers the functions of the IaaS layer and PaaS layer. The supporting hardware architecture is mainly distributed architecture, which provides physical computing power, virtual host and distributed storage to support meteorological big data business and much meteorological application deployment. The operation can meet the functional and performance requirements of meteorological applications for intensive infrastructure resources.
In order to adapt to the requirements of computing power and storage resources for scientific research applications of meteorological operations, the cloud platform of meteorological infrastructure is built by using distributed computing, distributed storage and virtualization technology. And the cloud platform resource partition is designed according to different business categories, network partition, resource service objects, and each partition needs to have cloud resources. The designed cloud platform covers the functions of the IaaS layer and PaaS layer. The supporting hardware architecture is mainly distributed architecture, which provides physical computing power, virtual host and distributed storage to support meteorological big data business and much meteorological application deployment. The operation can meet the functional and performance requirements of meteorological applications for intensive infrastructure resources.
2022, 50(2):297-302.
DOI: 10.19517/j.1671-6345.20210380
Abstract:
Combined with the experience of CMADaaS platform business trial operation and maintenance, this paper gives the application skills of service interface in client development and system integration from the technical perspective of meteorological forecast service personnel, including using functional programming to simplify the call and implementation of service interface, introducing a “retry” mechanism to ensure the success rate of interface call, using JSON return data to improve the efficiency of cloud platform meteorological element information extraction and processing, mastering the skills of avoiding system access restrictions to improve the application R&D experience. The results show that the open-source “Tianqing” cloud service algorithm and a series of software packages can deepen the application staff’s understanding of the system operation mechanism and service concept. They can promote the efficient and safe use of the meteorological big data cloud platform and the deep integration of the meteorological business system.
Combined with the experience of CMADaaS platform business trial operation and maintenance, this paper gives the application skills of service interface in client development and system integration from the technical perspective of meteorological forecast service personnel, including using functional programming to simplify the call and implementation of service interface, introducing a “retry” mechanism to ensure the success rate of interface call, using JSON return data to improve the efficiency of cloud platform meteorological element information extraction and processing, mastering the skills of avoiding system access restrictions to improve the application R&D experience. The results show that the open-source “Tianqing” cloud service algorithm and a series of software packages can deepen the application staff’s understanding of the system operation mechanism and service concept. They can promote the efficient and safe use of the meteorological big data cloud platform and the deep integration of the meteorological business system.
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.