A Simple Method of Coupled Merging and Downscaling for Multi-Source Daily Precipitation Data
文献类型：期刊论文
| 作者 | Zhao, Na2,3,4; Chen, Kainan1,4 |
| 刊名 | REMOTE SENSING
 |
| 出版日期 | 2023-09-01 |
| 卷号 | 15期号:18页码:18 |
| 关键词 | precipitation downscaling and merging daily China |
| DOI | 10.3390/rs15184377 |
| 通讯作者 | Zhao, Na(zhaon@lreis.ac.cn) |
| 英文摘要 | High accuracy and a high spatiotemporal resolution of precipitation are essential for the hydrological, ecological, and environmental fields. However, the existing daily gridded precipitation datasets, such as remote sensing products, are limited both by the coarse resolution and the low accuracy. Despite considerable efforts having been invested in downscaling or merging, a method of coupled and simultaneously downscaling and merging multiple datasets is currently lacking, which limits the wide application of individual popular satellite precipitation products. For the first time, in this study, we propose a simple coupled merging and downscaling (CMD) method for simultaneously obtaining multiple high-resolution and high-accuracy daily precipitation datasets. A pixel-repeated decomposition method was first proposed, and the random forest (RF) method was then applied to merge multiple daily precipitation datasets. The individual downscaled dataset was obtained by multiplying the result of merging by an explanatory rate obtained by RF. The results showed that the CMD method exhibited significantly better performance compared with the original datasets, with the mean absolute error (MAE) improving by up to 50%, the majority of the values of bias ranging between -1 mm and 1 mm, and the majority of the Kling-Gupta efficiency (KGE) values being greater than 0.7. CMD was more accurate than the widely used dataset, Multi-Source Weighted-Ensemble Precipitation (MSWEP), with a 43% reduction in the MAE and a 245% improvement in the KGE. In addition, the long-term estimation suggested that the proposed method exhibits stable good performance over time. |
| WOS关键词 | SPATIAL INTERPOLATION ; COVER CHANGE ; SATELLITE ; SIMULATIONS ; GAUGE |
| 资助项目 | Major Program of the National Natural Science Foundation of China[42293270] ; National Program of National Natural Science Foundation of China[42071374] ; Key Project of Innovation LREIS[KPI001] |
| WOS研究方向 | Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:001075052600001 |
| 出版者 | MDPI |
| 资助机构 | Major Program of the National Natural Science Foundation of China ; National Program of National Natural Science Foundation of China ; Key Project of Innovation LREIS |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/198169]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Zhao, Na |
| 作者单位 | 1.Minist Nat Resources, Inst Oceanog 1, Qingdao 266061, Peoples R China 2.Jiangsu Ctr Collaborat Innovat Geog Informat Resou, Nanjing 210023, Peoples R China 3.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100101, Peoples R China 4.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhao, Na,Chen, Kainan. A Simple Method of Coupled Merging and Downscaling for Multi-Source Daily Precipitation Data[J]. REMOTE SENSING,2023,15(18):18. |
| APA | Zhao, Na,&Chen, Kainan.(2023).A Simple Method of Coupled Merging and Downscaling for Multi-Source Daily Precipitation Data.REMOTE SENSING,15(18),18. |
| MLA | Zhao, Na,et al."A Simple Method of Coupled Merging and Downscaling for Multi-Source Daily Precipitation Data".REMOTE SENSING 15.18(2023):18. |
入库方式： OAI收割
来源：地理科学与资源研究所
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