Development and Assessment of the Monthly Grid Precipitation Datasets in China
Based on the high-quality homogenized precipitation data from all 2,419 national weather stations in China, the climatology and anomaly percentage fields are derived, and then the digital elevation model (DEM) is employed to reduce the influence of elevation on the spatial interpolation accuracy of...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2021-04-01
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| Series: | Frontiers in Environmental Science |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fenvs.2021.656794/full |
| _version_ | 1818661897118941184 |
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| author | Jiadong Peng Jiadong Peng Lijie Duan Wenhui Xu Qingxiang Li |
| author_facet | Jiadong Peng Jiadong Peng Lijie Duan Wenhui Xu Qingxiang Li |
| author_sort | Jiadong Peng |
| collection | DOAJ |
| description | Based on the high-quality homogenized precipitation data from all 2,419 national weather stations in China, the climatology and anomaly percentage fields are derived, and then the digital elevation model (DEM) is employed to reduce the influence of elevation on the spatial interpolation accuracy of precipitation due to the unique topography in China. Then, the gradient plus inverse distance squared (GIDS) method and the inverse distance squared (IDS) method are used to grid the climatology field and the anomaly percentage field, respectively, and the 0.5 × 0.5° gridded datasets during 1961–2018 in China are obtained by combining them together. The evaluation shows that the mean absolute error (MAE) between the analysis value and the observation is 15.8 mm/month. The MAE in South China is generally higher than that in North China, and the MAE is obviously larger in summer than in other seasons. Specifically, 94.6, 54.4, 4.6, and 53.8% of the MAE are below 10 mm/month in winter (DJF), spring (MAM), summer (JJA), and autumn (SON), respectively, and 99.5, 79.9, 22.8, and 82.1% of them are less than 20 mm/month. The MAE over China in four seasons is 3.8, 13.2, 33.5, and 12.7 mm/month, respectively. This dataset has the potential of broad application prospects in the evaluations of weather and climate models and satellite products. |
| first_indexed | 2024-12-17T04:52:21Z |
| format | Article |
| id | doaj.art-e15b4d3d76ae4994a880a6c468bba637 |
| institution | Directory Open Access Journal |
| issn | 2296-665X |
| language | English |
| last_indexed | 2024-12-17T04:52:21Z |
| publishDate | 2021-04-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Environmental Science |
| spelling | doaj.art-e15b4d3d76ae4994a880a6c468bba6372022-12-21T22:02:52ZengFrontiers Media S.A.Frontiers in Environmental Science2296-665X2021-04-01910.3389/fenvs.2021.656794656794Development and Assessment of the Monthly Grid Precipitation Datasets in ChinaJiadong Peng0Jiadong Peng1Lijie Duan2Wenhui Xu3Qingxiang Li4Climate Center of Hunan Province, Changsha, ChinaKey Laboratory of Hunan Province for Meteorological Disaster Prevention and Mitigation, Changsha, ChinaClimate Center of Hunan Province, Changsha, ChinaNational Meteorological Information Center, Beijing, ChinaSchool of Atmospheric Sciences, Sun Yat-sen University, and Key Laboratory of Tropical Atmosphere–Ocean System, Ministry of Education, Zhuhai, ChinaBased on the high-quality homogenized precipitation data from all 2,419 national weather stations in China, the climatology and anomaly percentage fields are derived, and then the digital elevation model (DEM) is employed to reduce the influence of elevation on the spatial interpolation accuracy of precipitation due to the unique topography in China. Then, the gradient plus inverse distance squared (GIDS) method and the inverse distance squared (IDS) method are used to grid the climatology field and the anomaly percentage field, respectively, and the 0.5 × 0.5° gridded datasets during 1961–2018 in China are obtained by combining them together. The evaluation shows that the mean absolute error (MAE) between the analysis value and the observation is 15.8 mm/month. The MAE in South China is generally higher than that in North China, and the MAE is obviously larger in summer than in other seasons. Specifically, 94.6, 54.4, 4.6, and 53.8% of the MAE are below 10 mm/month in winter (DJF), spring (MAM), summer (JJA), and autumn (SON), respectively, and 99.5, 79.9, 22.8, and 82.1% of them are less than 20 mm/month. The MAE over China in four seasons is 3.8, 13.2, 33.5, and 12.7 mm/month, respectively. This dataset has the potential of broad application prospects in the evaluations of weather and climate models and satellite products.https://www.frontiersin.org/articles/10.3389/fenvs.2021.656794/fullChinaprecipitationGIDSIDSgridded datasetaccuracy evaluation |
| spellingShingle | Jiadong Peng Jiadong Peng Lijie Duan Wenhui Xu Qingxiang Li Development and Assessment of the Monthly Grid Precipitation Datasets in China Frontiers in Environmental Science China precipitation GIDS IDS gridded dataset accuracy evaluation |
| title | Development and Assessment of the Monthly Grid Precipitation Datasets in China |
| title_full | Development and Assessment of the Monthly Grid Precipitation Datasets in China |
| title_fullStr | Development and Assessment of the Monthly Grid Precipitation Datasets in China |
| title_full_unstemmed | Development and Assessment of the Monthly Grid Precipitation Datasets in China |
| title_short | Development and Assessment of the Monthly Grid Precipitation Datasets in China |
| title_sort | development and assessment of the monthly grid precipitation datasets in china |
| topic | China precipitation GIDS IDS gridded dataset accuracy evaluation |
| url | https://www.frontiersin.org/articles/10.3389/fenvs.2021.656794/full |
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