Assessment of a Gauge-Radar-Satellite Merged Hourly Precipitation Product for Accurately Monitoring the Characteristics of the Super-Strong Meiyu Precipitation over the Yangtze River Basin in 2020
The recently developed gauge-radar-satellite merged hourly precipitation dataset (CMPAS-NRT) offers broad applications in scientific research and operations, such as intelligent grid forecasting, meteorological disaster monitoring and warning, and numerical model testing and evaluation. In this pape...
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| Format: | Article |
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MDPI AG
2021-09-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/13/19/3850 |
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| author | Zihao Pang Chunxiang Shi Junxia Gu Yang Pan Bin Xu |
| author_facet | Zihao Pang Chunxiang Shi Junxia Gu Yang Pan Bin Xu |
| author_sort | Zihao Pang |
| collection | DOAJ |
| description | The recently developed gauge-radar-satellite merged hourly precipitation dataset (CMPAS-NRT) offers broad applications in scientific research and operations, such as intelligent grid forecasting, meteorological disaster monitoring and warning, and numerical model testing and evaluation. In this paper, we take a super-long Meiyu precipitation process experienced in the Yangtze River basin in the summer of 2020 as the research object, and evaluate the monitoring capability of the CMPAS-NRT for the process from multiple perspectives, such as error indicators, precipitation characteristics, and daily variability in different rainfall areas, using dense surface rain-gauge observation data as a reference. The results show that the error indicators for CMPAS-NRT are in good agreement with the gauge observations. The CMPAS-NRT can accurately reflect the evolution of precipitation during the whole rainy season, and can accurately capture the spatial distribution of rainbands, but there is an underestimation of extreme precipitation. At the same time, the CMPAS-NRT product features the phenomenon of overestimation of precipitation at the level of light rain. In terms of daily variation of precipitation, the precipitation amount, frequency, and intensity are basically consistent with the observations, except that there is a lag in the peak frequency of precipitation, and the frequency of precipitation at night is less than observed, and the intensity of precipitation is higher than observed. Overall, the CMPAS-NRT product can successfully reflect the precipitation characteristics of this super-heavy Meiyu precipitation event, and has a high potential hydrological utilization value. However, further improvement of the precipitation algorithm is needed to solve the problems of overestimation of light rainfall and underestimation of extreme precipitation in order to provide more accurate hourly precipitation monitoring dataset. |
| first_indexed | 2024-03-10T06:53:31Z |
| format | Article |
| id | doaj.art-e04dddc385954439b51a0832208e0987 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T06:53:31Z |
| publishDate | 2021-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-e04dddc385954439b51a0832208e09872023-11-22T16:41:46ZengMDPI AGRemote Sensing2072-42922021-09-011319385010.3390/rs13193850Assessment of a Gauge-Radar-Satellite Merged Hourly Precipitation Product for Accurately Monitoring the Characteristics of the Super-Strong Meiyu Precipitation over the Yangtze River Basin in 2020Zihao Pang0Chunxiang Shi1Junxia Gu2Yang Pan3Bin Xu4National Meteorological Information Center, Beijing 100081, ChinaNational Meteorological Information Center, Beijing 100081, ChinaNational Meteorological Information Center, Beijing 100081, ChinaNational Meteorological Information Center, Beijing 100081, ChinaNational Meteorological Information Center, Beijing 100081, ChinaThe recently developed gauge-radar-satellite merged hourly precipitation dataset (CMPAS-NRT) offers broad applications in scientific research and operations, such as intelligent grid forecasting, meteorological disaster monitoring and warning, and numerical model testing and evaluation. In this paper, we take a super-long Meiyu precipitation process experienced in the Yangtze River basin in the summer of 2020 as the research object, and evaluate the monitoring capability of the CMPAS-NRT for the process from multiple perspectives, such as error indicators, precipitation characteristics, and daily variability in different rainfall areas, using dense surface rain-gauge observation data as a reference. The results show that the error indicators for CMPAS-NRT are in good agreement with the gauge observations. The CMPAS-NRT can accurately reflect the evolution of precipitation during the whole rainy season, and can accurately capture the spatial distribution of rainbands, but there is an underestimation of extreme precipitation. At the same time, the CMPAS-NRT product features the phenomenon of overestimation of precipitation at the level of light rain. In terms of daily variation of precipitation, the precipitation amount, frequency, and intensity are basically consistent with the observations, except that there is a lag in the peak frequency of precipitation, and the frequency of precipitation at night is less than observed, and the intensity of precipitation is higher than observed. Overall, the CMPAS-NRT product can successfully reflect the precipitation characteristics of this super-heavy Meiyu precipitation event, and has a high potential hydrological utilization value. However, further improvement of the precipitation algorithm is needed to solve the problems of overestimation of light rainfall and underestimation of extreme precipitation in order to provide more accurate hourly precipitation monitoring dataset.https://www.mdpi.com/2072-4292/13/19/3850evaluationhourly precipitationradarsatellitemulti-source data mergeMeiyu |
| spellingShingle | Zihao Pang Chunxiang Shi Junxia Gu Yang Pan Bin Xu Assessment of a Gauge-Radar-Satellite Merged Hourly Precipitation Product for Accurately Monitoring the Characteristics of the Super-Strong Meiyu Precipitation over the Yangtze River Basin in 2020 Remote Sensing evaluation hourly precipitation radar satellite multi-source data merge Meiyu |
| title | Assessment of a Gauge-Radar-Satellite Merged Hourly Precipitation Product for Accurately Monitoring the Characteristics of the Super-Strong Meiyu Precipitation over the Yangtze River Basin in 2020 |
| title_full | Assessment of a Gauge-Radar-Satellite Merged Hourly Precipitation Product for Accurately Monitoring the Characteristics of the Super-Strong Meiyu Precipitation over the Yangtze River Basin in 2020 |
| title_fullStr | Assessment of a Gauge-Radar-Satellite Merged Hourly Precipitation Product for Accurately Monitoring the Characteristics of the Super-Strong Meiyu Precipitation over the Yangtze River Basin in 2020 |
| title_full_unstemmed | Assessment of a Gauge-Radar-Satellite Merged Hourly Precipitation Product for Accurately Monitoring the Characteristics of the Super-Strong Meiyu Precipitation over the Yangtze River Basin in 2020 |
| title_short | Assessment of a Gauge-Radar-Satellite Merged Hourly Precipitation Product for Accurately Monitoring the Characteristics of the Super-Strong Meiyu Precipitation over the Yangtze River Basin in 2020 |
| title_sort | assessment of a gauge radar satellite merged hourly precipitation product for accurately monitoring the characteristics of the super strong meiyu precipitation over the yangtze river basin in 2020 |
| topic | evaluation hourly precipitation radar satellite multi-source data merge Meiyu |
| url | https://www.mdpi.com/2072-4292/13/19/3850 |
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