Shiying Li, Xiaolong Huang, Bing Du, Wei Wu, Yuhe Jiang
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The threshold value, spatial consistency, and temporal consistency are verified using meteorological station precipitation data, and the relationship thresholds between satellite and radar products and hourly precipitation are summarized and verified for consistency. Subsequently, collaborative quality control results are derived using a comprehensive scoring method. Testing this quality control method suggests that the method will not classify too many correct data as mistakes and the detection rate of incorrect data can be more than 0.7. Following quality control, the hourly precipitation error for hydrological station data fell dramatically, the False Alarm Rate decreased by 19%, and the anomalous maxima were successfully eliminated. Therefore, this collaborative quality control method can compensate for the deficiencies of a single quality-control source, thus allowing precipitation data not from the meteorological industry to be screened effectively.</p>","PeriodicalId":51132,"journal":{"name":"Meteorology and Atmospheric Physics","volume":"93 1","pages":""},"PeriodicalIF":1.9000,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Application of gauge-radar-satellite data in surface precipitation quality control\",\"authors\":\"Shiying Li, Xiaolong Huang, Bing Du, Wei Wu, Yuhe Jiang\",\"doi\":\"10.1007/s00703-024-01028-w\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Precipitation observation data from different departments are highly complementary in the application, but there are some differences in observation equipment, data sampling methods, accuracy, and data transmission methods. To better apply the precipitation data of different departments in meteorological services, it is necessary to carry out a quality control method. In this study, rain gauge precipitation data, radar data, and satellite data from the China Meteorological Administration are used to perform collaborative quality control of precipitation data from the Ministry of Water Resources of the People’s Republic of China. The threshold value, spatial consistency, and temporal consistency are verified using meteorological station precipitation data, and the relationship thresholds between satellite and radar products and hourly precipitation are summarized and verified for consistency. Subsequently, collaborative quality control results are derived using a comprehensive scoring method. Testing this quality control method suggests that the method will not classify too many correct data as mistakes and the detection rate of incorrect data can be more than 0.7. Following quality control, the hourly precipitation error for hydrological station data fell dramatically, the False Alarm Rate decreased by 19%, and the anomalous maxima were successfully eliminated. Therefore, this collaborative quality control method can compensate for the deficiencies of a single quality-control source, thus allowing precipitation data not from the meteorological industry to be screened effectively.</p>\",\"PeriodicalId\":51132,\"journal\":{\"name\":\"Meteorology and Atmospheric Physics\",\"volume\":\"93 1\",\"pages\":\"\"},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2024-08-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Meteorology and Atmospheric Physics\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.1007/s00703-024-01028-w\",\"RegionNum\":4,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"METEOROLOGY & ATMOSPHERIC SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Meteorology and Atmospheric Physics","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1007/s00703-024-01028-w","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
Application of gauge-radar-satellite data in surface precipitation quality control
Precipitation observation data from different departments are highly complementary in the application, but there are some differences in observation equipment, data sampling methods, accuracy, and data transmission methods. To better apply the precipitation data of different departments in meteorological services, it is necessary to carry out a quality control method. In this study, rain gauge precipitation data, radar data, and satellite data from the China Meteorological Administration are used to perform collaborative quality control of precipitation data from the Ministry of Water Resources of the People’s Republic of China. The threshold value, spatial consistency, and temporal consistency are verified using meteorological station precipitation data, and the relationship thresholds between satellite and radar products and hourly precipitation are summarized and verified for consistency. Subsequently, collaborative quality control results are derived using a comprehensive scoring method. Testing this quality control method suggests that the method will not classify too many correct data as mistakes and the detection rate of incorrect data can be more than 0.7. Following quality control, the hourly precipitation error for hydrological station data fell dramatically, the False Alarm Rate decreased by 19%, and the anomalous maxima were successfully eliminated. Therefore, this collaborative quality control method can compensate for the deficiencies of a single quality-control source, thus allowing precipitation data not from the meteorological industry to be screened effectively.
期刊介绍:
Meteorology and Atmospheric Physics accepts original research papers for publication following the recommendations of a review panel. The emphasis lies with the following topic areas:
- atmospheric dynamics and general circulation;
- synoptic meteorology;
- weather systems in specific regions, such as the tropics, the polar caps, the oceans;
- atmospheric energetics;
- numerical modeling and forecasting;
- physical and chemical processes in the atmosphere, including radiation, optical effects, electricity, and atmospheric turbulence and transport processes;
- mathematical and statistical techniques applied to meteorological data sets
Meteorology and Atmospheric Physics discusses physical and chemical processes - in both clear and cloudy atmospheres - including radiation, optical and electrical effects, precipitation and cloud microphysics.