Pub Date : 2019-12-01DOI: 10.1109/ICMO49322.2019.9025816
Yan Jiaming, Tang Jie, Chen Haojun, Lin Li-min
This study investigates the feasibility of wind profiler in the typhoon observation. From six typhoon cases during 2014 to 2019, 34 groups datasets, the Airda3000 boundary layer wind profiler and GPS balloon sounding data are selected to be compared. Preliminary analysis shows that 30 out of 34 datasets satisfy the prerequisite condition of greater than 80% data completion. These 30 datasets have an average standard deviation of about 3.64m/s and average difference of 4.67m/s. Furthermore, 20 out of 34 datasets achieved good results (standard deviation < 4 and correlation >0.5) with much overlap of 2 lines above 250m altitude, and less overlap of 2 lines below that altitude, Moreover, the sounding wind speed is observed to be much smaller than the wind profiler data for altitudes below 250m, likely due to the fact that sounding accelerates from stationary to consistent with environmental winds at altitudes below 250m in typhoon environment. This may also be due to disturbance in lower atmosphere of wind profiler which earlier studies mentioned. Thus, while ignoring the lowest 250m region, the standard deviation of profiler and balloon sounding decreased remarkably. This may implied that wind profiler may have very high feasibility in the region of boundary layer from 250 m to the top of boundary layer under typhoon environment. In addition, data with lower validity are always located in the region which is about more than 200km away from typhoon center, while the distribution of high validity data observation does not showed an obvious pattern and located from typhoon center to the outer region. There are also no relationship found between data validity and precipitation intensity. These two founding may implied that wind profiler may have great utility and potential under the condition of heavy precipitation and severe wind. Despite very limited data we collected in study, wind profiler shows an very hopeful potential and higher validity in the observation and diagnosis of boundary layer even in severe convective weather environment such as typhoon inner core regions.
{"title":"Application Validity of Wind Profiler in Typhoon Environment","authors":"Yan Jiaming, Tang Jie, Chen Haojun, Lin Li-min","doi":"10.1109/ICMO49322.2019.9025816","DOIUrl":"https://doi.org/10.1109/ICMO49322.2019.9025816","url":null,"abstract":"This study investigates the feasibility of wind profiler in the typhoon observation. From six typhoon cases during 2014 to 2019, 34 groups datasets, the Airda3000 boundary layer wind profiler and GPS balloon sounding data are selected to be compared. Preliminary analysis shows that 30 out of 34 datasets satisfy the prerequisite condition of greater than 80% data completion. These 30 datasets have an average standard deviation of about 3.64m/s and average difference of 4.67m/s. Furthermore, 20 out of 34 datasets achieved good results (standard deviation < 4 and correlation >0.5) with much overlap of 2 lines above 250m altitude, and less overlap of 2 lines below that altitude, Moreover, the sounding wind speed is observed to be much smaller than the wind profiler data for altitudes below 250m, likely due to the fact that sounding accelerates from stationary to consistent with environmental winds at altitudes below 250m in typhoon environment. This may also be due to disturbance in lower atmosphere of wind profiler which earlier studies mentioned. Thus, while ignoring the lowest 250m region, the standard deviation of profiler and balloon sounding decreased remarkably. This may implied that wind profiler may have very high feasibility in the region of boundary layer from 250 m to the top of boundary layer under typhoon environment. In addition, data with lower validity are always located in the region which is about more than 200km away from typhoon center, while the distribution of high validity data observation does not showed an obvious pattern and located from typhoon center to the outer region. There are also no relationship found between data validity and precipitation intensity. These two founding may implied that wind profiler may have great utility and potential under the condition of heavy precipitation and severe wind. Despite very limited data we collected in study, wind profiler shows an very hopeful potential and higher validity in the observation and diagnosis of boundary layer even in severe convective weather environment such as typhoon inner core regions.","PeriodicalId":257532,"journal":{"name":"2019 International Conference on Meteorology Observations (ICMO)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114814590","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-12-01DOI: 10.1109/ICMO49322.2019.9026109
Zhi Li, Debin Su, Yang Cao, Xiaohong Fang, Yue Liu, Jingxin He
In order to understand of physics process in the hailstorm, a hail event on August 9, 2019 had been analyzed by using the data collected of two X-band dual polarization radars located in Wuyuan County Meteorological Bureau and Ulansuhai Meteorological Observation Station in Bayan Nur, Inner Mongolia Autonomous Region. Hailstorm information recorded by 58 hail pads which were deployed in the experiment region were also used for the validation of the radar observation. The volume scan data of the Wuyuan radar is meshed by three-dimensional coordinates of longitude, latitude and altitude by vertical interpolation. In the common observation area, through comparing and validating the values of the polarization parameters on the crossover line to analyze the vertical structure characteristics of hail cloud. The results showed that the characteristics of hail observation data of the two radars in the same observation area are similar, Combining with two radar data can more completely obtain the hail information. The paper can provide relevant basis for the X-band dual polarization radar to the artificial hail suppression work in the Bayan Nur area.
{"title":"Analysis and Cross Validation of a Hail Process Based on Two X-Band Dual Polarization Radar Observations","authors":"Zhi Li, Debin Su, Yang Cao, Xiaohong Fang, Yue Liu, Jingxin He","doi":"10.1109/ICMO49322.2019.9026109","DOIUrl":"https://doi.org/10.1109/ICMO49322.2019.9026109","url":null,"abstract":"In order to understand of physics process in the hailstorm, a hail event on August 9, 2019 had been analyzed by using the data collected of two X-band dual polarization radars located in Wuyuan County Meteorological Bureau and Ulansuhai Meteorological Observation Station in Bayan Nur, Inner Mongolia Autonomous Region. Hailstorm information recorded by 58 hail pads which were deployed in the experiment region were also used for the validation of the radar observation. The volume scan data of the Wuyuan radar is meshed by three-dimensional coordinates of longitude, latitude and altitude by vertical interpolation. In the common observation area, through comparing and validating the values of the polarization parameters on the crossover line to analyze the vertical structure characteristics of hail cloud. The results showed that the characteristics of hail observation data of the two radars in the same observation area are similar, Combining with two radar data can more completely obtain the hail information. The paper can provide relevant basis for the X-band dual polarization radar to the artificial hail suppression work in the Bayan Nur area.","PeriodicalId":257532,"journal":{"name":"2019 International Conference on Meteorology Observations (ICMO)","volume":"105 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134409473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-12-01DOI: 10.1109/ICMO49322.2019.9026076
Houyu Wu, Debin Su, Xingang Fan
In this study, the Weather Research and Forecasting (WRF) model is used to simulate a severe convective process in Hainan, China on September 16, 2019. For the purpose of improving precipitation simulation and forecast, the WRF model’s three-dimensional Variational (3DVAR) assimilation system is used to assimilate CINRAD/SA Weather radar data. The assimilation results and precipitation forecast are compared and analyzed in order to study the influence of weather radar data assimilation on precipitation prediction. Four experiments of assimilation are carried out: 1) Control experiment: no assimilation of any data; 2) Only radar reflectivity data is assimilated; 3) Assimilating the radar radial velocity data; 4) Simultaneously assimilating the radar reflectivity and radial velocity data. The results show that the assimilation of the reflectivity data from the weather radar can effectively adjust the spatial distribution and magnitude of water vapor and temperature field in the background field. Assimilating the radar radial velocity data mainly improves the wind field of initial field. The assimilation of reflectivity can better adjust the precipitation forecast compared with the assimilation of radial velocity. Assimilating both reflectivity and radial velocity at the same time shows the best positive effect on precipitation forecast.
{"title":"Impacts of Doppler Radar Data Assimilation on Precipitation Forecast of a Severe Convective Process in Hainan, China","authors":"Houyu Wu, Debin Su, Xingang Fan","doi":"10.1109/ICMO49322.2019.9026076","DOIUrl":"https://doi.org/10.1109/ICMO49322.2019.9026076","url":null,"abstract":"In this study, the Weather Research and Forecasting (WRF) model is used to simulate a severe convective process in Hainan, China on September 16, 2019. For the purpose of improving precipitation simulation and forecast, the WRF model’s three-dimensional Variational (3DVAR) assimilation system is used to assimilate CINRAD/SA Weather radar data. The assimilation results and precipitation forecast are compared and analyzed in order to study the influence of weather radar data assimilation on precipitation prediction. Four experiments of assimilation are carried out: 1) Control experiment: no assimilation of any data; 2) Only radar reflectivity data is assimilated; 3) Assimilating the radar radial velocity data; 4) Simultaneously assimilating the radar reflectivity and radial velocity data. The results show that the assimilation of the reflectivity data from the weather radar can effectively adjust the spatial distribution and magnitude of water vapor and temperature field in the background field. Assimilating the radar radial velocity data mainly improves the wind field of initial field. The assimilation of reflectivity can better adjust the precipitation forecast compared with the assimilation of radial velocity. Assimilating both reflectivity and radial velocity at the same time shows the best positive effect on precipitation forecast.","PeriodicalId":257532,"journal":{"name":"2019 International Conference on Meteorology Observations (ICMO)","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116581684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-12-01DOI: 10.1109/ICMO49322.2019.9026015
Kai Ye, Ling Yang, Shuqing Ma, Xiaoqiong Zhen
Array Weather Radar (AWR) is a new type weather radar. A distributed phased array technology is utilized to the AWR. With offering very high spatiotemporal resolution, the AWR can obtain the small-scale weather systems with high changing speed. The AWR system provides networked and coordinated observations of the same target from at least three radar front ends. This paper introduces a fast and high-resolution intensity field fusion algorithm for the AWR based on Graphics Processing Unit (GPU). By utilizing the feature of asynchronous execution between CPU and GPU, the fusion algorithm is parallelized and optimized on Compute Unified Device Architecture (CUDA). First, based on the intensity data from the AWR front end volume scans, resolution expansion coefficients in azimuths and elevations are calculated in each GPU thread. Then, the vertical and horizontal filling is completed simultaneously. Finally, the fusion of three front end intensity data is achieved in a common coordinate system. The entire process has been implemented on NVIDIA GPU architecture. The result shows that the GPU-based method for the AWR greatly improves the speed of calculation compared with the conventional CPUbased implementation, which can satisfy the requirements of meteorological applications in real-time.
{"title":"High-Resolution Intensity Field Fusion of Array Weather Radar on GPU","authors":"Kai Ye, Ling Yang, Shuqing Ma, Xiaoqiong Zhen","doi":"10.1109/ICMO49322.2019.9026015","DOIUrl":"https://doi.org/10.1109/ICMO49322.2019.9026015","url":null,"abstract":"Array Weather Radar (AWR) is a new type weather radar. A distributed phased array technology is utilized to the AWR. With offering very high spatiotemporal resolution, the AWR can obtain the small-scale weather systems with high changing speed. The AWR system provides networked and coordinated observations of the same target from at least three radar front ends. This paper introduces a fast and high-resolution intensity field fusion algorithm for the AWR based on Graphics Processing Unit (GPU). By utilizing the feature of asynchronous execution between CPU and GPU, the fusion algorithm is parallelized and optimized on Compute Unified Device Architecture (CUDA). First, based on the intensity data from the AWR front end volume scans, resolution expansion coefficients in azimuths and elevations are calculated in each GPU thread. Then, the vertical and horizontal filling is completed simultaneously. Finally, the fusion of three front end intensity data is achieved in a common coordinate system. The entire process has been implemented on NVIDIA GPU architecture. The result shows that the GPU-based method for the AWR greatly improves the speed of calculation compared with the conventional CPUbased implementation, which can satisfy the requirements of meteorological applications in real-time.","PeriodicalId":257532,"journal":{"name":"2019 International Conference on Meteorology Observations (ICMO)","volume":"697 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121991483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-12-01DOI: 10.1109/ICMO49322.2019.9026062
Jing Wang, Guangqiang Liu
Combining with the Dalian radiosonde station on August 12, 2019, the detection of the sudden failure of the Lband radar signal during the launch process is analyzed, and the cause, the location and the solution of the sudden loss of the l-band radar signal are analyzed. It is the radiosonde station of the country Maintenance L-band radar provides technical reference and reference to ensure the successful completion of meteorological detection.
{"title":"Analysis and Processing of L-band Radar Signal Sudden Failure","authors":"Jing Wang, Guangqiang Liu","doi":"10.1109/ICMO49322.2019.9026062","DOIUrl":"https://doi.org/10.1109/ICMO49322.2019.9026062","url":null,"abstract":"Combining with the Dalian radiosonde station on August 12, 2019, the detection of the sudden failure of the Lband radar signal during the launch process is analyzed, and the cause, the location and the solution of the sudden loss of the l-band radar signal are analyzed. It is the radiosonde station of the country Maintenance L-band radar provides technical reference and reference to ensure the successful completion of meteorological detection.","PeriodicalId":257532,"journal":{"name":"2019 International Conference on Meteorology Observations (ICMO)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124811255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-12-01DOI: 10.1109/ICMO49322.2019.9026051
J. Jin, Yong Zhang, Yang Wang, Qing Zhou, Shanshan Lv, Jianzhong Ma
Multi-Axis Differential Optical Absorption Spectroscopy, MAX-DOAS for short, is a thriving ground-based passive remote sensing technique, which retrieves the vertical characteristics of aerosol and trace gases in the lower atmosphere using scattered sunlight measured from different axis angles. Clouds have obvious influence on atmospheric radiative transfer process and thus affect the inversion of vertical distribution, making it essential to study and classify the cloud properties. In this study, a cloud identification and classification algorithm script was developed based on several key quantities derived from MAX-DOAS observations, like radiance, color index and the absorption of oxygen dimer $text{O}_{mathbf {4}}$ et al. The algorithm was applied to two-month’s MAX-DOAS observations in southern urban Beijing $( 39.81 ^{circ}mathrm {N}, 116.47 ^{circ}mathrm {E})$, the megacity in North China, in summer 2017. A cloud classification dataset was created with relatively high time resolution. Aerosol profiles, near surface aerosol extinction and AOD (aerosol optical density) were derived as well by applying PriAM methods of MPIC. The results were compared systematically to several remote sensing techniques, like MODIS, sun photometer and Millimeter wave cloud radar, which have rarely been done before. General consistency and good agreement were achieved under respective aerosol and cloud scenarios, assuring the reliability of the cloud identification and classification algorithm script and the dependable capability of MAX-DOAS to provide aerosol and cloud information. This further indicates that more thorough studies should be carried out to diminish the influence of aerosol and cloud and improve the retrieval accuracy of vertical column densities and profiles from MAX-DOAS in the future.
{"title":"Aerosol and Cloud Classifications Derived from MAX-DOAS Measurements in Urban North China and their Comparisons to Multiple Remote Sensing Datasets","authors":"J. Jin, Yong Zhang, Yang Wang, Qing Zhou, Shanshan Lv, Jianzhong Ma","doi":"10.1109/ICMO49322.2019.9026051","DOIUrl":"https://doi.org/10.1109/ICMO49322.2019.9026051","url":null,"abstract":"Multi-Axis Differential Optical Absorption Spectroscopy, MAX-DOAS for short, is a thriving ground-based passive remote sensing technique, which retrieves the vertical characteristics of aerosol and trace gases in the lower atmosphere using scattered sunlight measured from different axis angles. Clouds have obvious influence on atmospheric radiative transfer process and thus affect the inversion of vertical distribution, making it essential to study and classify the cloud properties. In this study, a cloud identification and classification algorithm script was developed based on several key quantities derived from MAX-DOAS observations, like radiance, color index and the absorption of oxygen dimer $text{O}_{mathbf {4}}$ et al. The algorithm was applied to two-month’s MAX-DOAS observations in southern urban Beijing $( 39.81 ^{circ}mathrm {N}, 116.47 ^{circ}mathrm {E})$, the megacity in North China, in summer 2017. A cloud classification dataset was created with relatively high time resolution. Aerosol profiles, near surface aerosol extinction and AOD (aerosol optical density) were derived as well by applying PriAM methods of MPIC. The results were compared systematically to several remote sensing techniques, like MODIS, sun photometer and Millimeter wave cloud radar, which have rarely been done before. General consistency and good agreement were achieved under respective aerosol and cloud scenarios, assuring the reliability of the cloud identification and classification algorithm script and the dependable capability of MAX-DOAS to provide aerosol and cloud information. This further indicates that more thorough studies should be carried out to diminish the influence of aerosol and cloud and improve the retrieval accuracy of vertical column densities and profiles from MAX-DOAS in the future.","PeriodicalId":257532,"journal":{"name":"2019 International Conference on Meteorology Observations (ICMO)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125470284","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-12-01DOI: 10.1109/ICMO49322.2019.9025874
Wang Mian, Tang Jie, Wu Yunfei, Xia Yunjie, Zhang Ren-jian, An Tao
Black carbon (BC) aerosol has an important contribution to the local and global climate effects. For a long time, the research on the quality control, regional atmospheric baseline extraction and change trend of BC concentration is not enough. In this paper, two methods of filter-loading compensation and many of baseline data filtering methods are introduced. Based on the data of BC concentration of Lin'an station in Zhejiang Province, which is the regional atmospheric baseline observatory in China, the change of BC aerosol concentration and the observation results of seasonal characteristics in East China are analyzed. The results show that the accuracy of BC mass concentration obtained by dual-point correction combined with lanczos filter is 10% $sim 20$% higher than that of direct measurement.
{"title":"Method study on Filter-loading Compensation and Digital Filtering for Black Carbon Measurement in Regional Atmospheric Baseline","authors":"Wang Mian, Tang Jie, Wu Yunfei, Xia Yunjie, Zhang Ren-jian, An Tao","doi":"10.1109/ICMO49322.2019.9025874","DOIUrl":"https://doi.org/10.1109/ICMO49322.2019.9025874","url":null,"abstract":"Black carbon (BC) aerosol has an important contribution to the local and global climate effects. For a long time, the research on the quality control, regional atmospheric baseline extraction and change trend of BC concentration is not enough. In this paper, two methods of filter-loading compensation and many of baseline data filtering methods are introduced. Based on the data of BC concentration of Lin'an station in Zhejiang Province, which is the regional atmospheric baseline observatory in China, the change of BC aerosol concentration and the observation results of seasonal characteristics in East China are analyzed. The results show that the accuracy of BC mass concentration obtained by dual-point correction combined with lanczos filter is 10% $sim 20$% higher than that of direct measurement.","PeriodicalId":257532,"journal":{"name":"2019 International Conference on Meteorology Observations (ICMO)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125665708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-12-01DOI: 10.1109/ICMO49322.2019.9026042
L. Cuina, Liu Tianqi, Wu Dongli
Soil moisture plays a crucial role in the study of agricultural drought monitoring, yield prediction, soil erosion, and so on, which is of great significance for agriculture, drought, and climate. With the advantages of high precision, high spatial and temporal resolution, and non-destructive, the automatic soil moisture observing instrument has become an important component of automatic soil moisture observation station for the meteorological department in china. In the process of observing soil moisture, the accuracy of data is seriously affected by the calibration methods, equipment stability, soil texture, etc. Therefore, it is especially important to establish a quality control method for the automatic soil moisture observation data from the origin of affecting the observation quality. To solve the outstanding quality problems in the automatic soil moisture observation data, firstly, based on the historical data, the inherent variation characteristics of soil moisture were studied. Secondly, combined with the instrument observation principle, data characteristics and error sources of abnormal data, classified and statistical analyzed the form of abnormal data caused by various reasons and given the threshold, this paper preliminarily puts forward a practical set of quality control methods for the hourly soil moisture observation data. Finally, the application effect of the quality control method was verified by using the data in china in 2019. The result shows that: (1) Four mainly categories of abnormal data are gross errors, mutation, abnormal high values, and stiffness, which are mostly caused by instrument failure, abnormal soil hydrological constant, and unreasonable calibration of sensors. (2) The method of frequency characteristic detection can identify the error caused by instrument fault. (3) This quality control method can effectively detect abnormal data in china. At present, the method has been applied to the Integrated Meteorology Observation Data Quality Control System.
{"title":"Study on Anomaly Data Detection Method for Automatic Soil Moisture Observation","authors":"L. Cuina, Liu Tianqi, Wu Dongli","doi":"10.1109/ICMO49322.2019.9026042","DOIUrl":"https://doi.org/10.1109/ICMO49322.2019.9026042","url":null,"abstract":"Soil moisture plays a crucial role in the study of agricultural drought monitoring, yield prediction, soil erosion, and so on, which is of great significance for agriculture, drought, and climate. With the advantages of high precision, high spatial and temporal resolution, and non-destructive, the automatic soil moisture observing instrument has become an important component of automatic soil moisture observation station for the meteorological department in china. In the process of observing soil moisture, the accuracy of data is seriously affected by the calibration methods, equipment stability, soil texture, etc. Therefore, it is especially important to establish a quality control method for the automatic soil moisture observation data from the origin of affecting the observation quality. To solve the outstanding quality problems in the automatic soil moisture observation data, firstly, based on the historical data, the inherent variation characteristics of soil moisture were studied. Secondly, combined with the instrument observation principle, data characteristics and error sources of abnormal data, classified and statistical analyzed the form of abnormal data caused by various reasons and given the threshold, this paper preliminarily puts forward a practical set of quality control methods for the hourly soil moisture observation data. Finally, the application effect of the quality control method was verified by using the data in china in 2019. The result shows that: (1) Four mainly categories of abnormal data are gross errors, mutation, abnormal high values, and stiffness, which are mostly caused by instrument failure, abnormal soil hydrological constant, and unreasonable calibration of sensors. (2) The method of frequency characteristic detection can identify the error caused by instrument fault. (3) This quality control method can effectively detect abnormal data in china. At present, the method has been applied to the Integrated Meteorology Observation Data Quality Control System.","PeriodicalId":257532,"journal":{"name":"2019 International Conference on Meteorology Observations (ICMO)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121170802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-12-01DOI: 10.1109/ICMO49322.2019.9026019
Liang Li, Wenjing Pang, Lei Yong, Liang Cun
The national Lightning Detection Network of the China Meteorological Administration (CMA LDN) has been under construction since 2008. It works in the VLF/LF frequency band to detect Cloud-to-Ground (CG) flashes. It uses the time of arrival and direction finding integrated method to locate, and its operations are stable. The evaluation of the detection efficiency within the network using historical data is close to 70%, while the location accuracy using four stations and above is less than 200 meters. The peak current error is less than 30%. Through the analysis of the lightning monitoring data for 5 years from 2013 to 2017, it is found that the lightning activity as a whole has a downward trend in recent years. There is a large difference in lightning activity in different regions. Generally, the south is the most active, and the flash density is the highest in southern China. The most, especially the average proportion in August is more than 30%.
{"title":"The National Light Detection Network of the China Meteorological Administration","authors":"Liang Li, Wenjing Pang, Lei Yong, Liang Cun","doi":"10.1109/ICMO49322.2019.9026019","DOIUrl":"https://doi.org/10.1109/ICMO49322.2019.9026019","url":null,"abstract":"The national Lightning Detection Network of the China Meteorological Administration (CMA LDN) has been under construction since 2008. It works in the VLF/LF frequency band to detect Cloud-to-Ground (CG) flashes. It uses the time of arrival and direction finding integrated method to locate, and its operations are stable. The evaluation of the detection efficiency within the network using historical data is close to 70%, while the location accuracy using four stations and above is less than 200 meters. The peak current error is less than 30%. Through the analysis of the lightning monitoring data for 5 years from 2013 to 2017, it is found that the lightning activity as a whole has a downward trend in recent years. There is a large difference in lightning activity in different regions. Generally, the south is the most active, and the flash density is the highest in southern China. The most, especially the average proportion in August is more than 30%.","PeriodicalId":257532,"journal":{"name":"2019 International Conference on Meteorology Observations (ICMO)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115496657","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-12-01DOI: 10.1109/ICMO49322.2019.9026126
Wang Liang, Su Debin, Liu Yan
Observations in September 2018 from 2-D video disdrometer (2DVD) and 1-D disdrometer (Parsivel2) are used to study the performance difference of the two instruments at the same location in the campus of CUIT (Chengdu University of Information Technology). The characteristics of rainfall intensity, raindrop size distribution (DSD) and particle number density from the two instruments respectively are analyzed and compared according to rainfall intensity classification. The results show that 1) In the process of light rain, moderate rain, heavy rain and rainstorm, the DSD of the two instruments shows a single peak characteristic, and the peak value appears at the raindrop diameter of about 0.6mm. 2) For the number of raindrops with diameter less than 2mm, 2DVD detection value is greater than Parsivel2 detection value, and the D-value increases with the increase of rainfall intensity. 3) With the increase of rainfall intensity, the proportion of raindrops with diameter less than 2mm to the total raindrops decreases. 4) Parsivel2 can hardly detect raindrops with a diameter less than 0.3mm, while 2DVD has a better detection effect on raindrops with a diameter of about 0.19mm, and the detection ability for raindrops with a diameter less than 1mm is far lower than 2DVD. 5) The rainfall in Chengdu is mainly composed of small raindrops with a diameter of about 1mm. 6) The peak value of rainfall intensity of 2DVD is prior to that of Parsivel2, and the two peaks are basically the same in light rain, but with the increase of rainfall, the peak value of 2DVD will be greater than that of Parsivel2.
{"title":"Data Comparative Analysis of 2DVD and Parsivel2 Raindrop Spectrometer","authors":"Wang Liang, Su Debin, Liu Yan","doi":"10.1109/ICMO49322.2019.9026126","DOIUrl":"https://doi.org/10.1109/ICMO49322.2019.9026126","url":null,"abstract":"Observations in September 2018 from 2-D video disdrometer (2DVD) and 1-D disdrometer (Parsivel2) are used to study the performance difference of the two instruments at the same location in the campus of CUIT (Chengdu University of Information Technology). The characteristics of rainfall intensity, raindrop size distribution (DSD) and particle number density from the two instruments respectively are analyzed and compared according to rainfall intensity classification. The results show that 1) In the process of light rain, moderate rain, heavy rain and rainstorm, the DSD of the two instruments shows a single peak characteristic, and the peak value appears at the raindrop diameter of about 0.6mm. 2) For the number of raindrops with diameter less than 2mm, 2DVD detection value is greater than Parsivel2 detection value, and the D-value increases with the increase of rainfall intensity. 3) With the increase of rainfall intensity, the proportion of raindrops with diameter less than 2mm to the total raindrops decreases. 4) Parsivel2 can hardly detect raindrops with a diameter less than 0.3mm, while 2DVD has a better detection effect on raindrops with a diameter of about 0.19mm, and the detection ability for raindrops with a diameter less than 1mm is far lower than 2DVD. 5) The rainfall in Chengdu is mainly composed of small raindrops with a diameter of about 1mm. 6) The peak value of rainfall intensity of 2DVD is prior to that of Parsivel2, and the two peaks are basically the same in light rain, but with the increase of rainfall, the peak value of 2DVD will be greater than that of Parsivel2.","PeriodicalId":257532,"journal":{"name":"2019 International Conference on Meteorology Observations (ICMO)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115453126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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