A Novel Merging Method for Generating High-Quality Spatial Precipitation Information over Mainland China
文献类型：期刊论文
| 作者 | Zhao, Na2,3 |
| 刊名 | WATER
 |
| 出版日期 | 2023-02-01 |
| 卷号 | 15期号:3 |
| ISSN号 | 2073-4441 |
| 关键词 | precipitation data fusion accuracy China |
| DOI | 10.3390/w15030575 |
| 文献子类 | Article |
| 英文摘要 | Accurate estimation of precipitation is critically important for a variety of fields, such as climatology, meteorology, and water resources. However, the availability of precipitation measurements has proved to be spatially inadequate for many applications. In this study, to acquire high-quality precipitation fields with enhanced accuracy and a fine-scale spatial resolution of 1 km x 1 km, we developed a new data fusion method by establishing an energy function model using the downscaled Global Precipitation Measurement (GPM) Integrated Multi-satellite Retrievals (IMERG) precipitation product and high-density station observation in mainland China. Our merging approach was inspired by the interdisciplinary research framework integrating the methods in the fields of image processing, earth science, and machine learning. Cross-validation analyses were performed for the monthly precipitation over the period 2009-2018. It was found that the results of the newly developed method were more accurate than the original IMERG products in terms of root mean squared error (RMSE), mean absolute error (MAE), correlation coefficient (CC), and Kling-Gupta efficiency (KGE). The merging precipitation results exhibit consistent spatial patterns with the original IMERG products, yet have good agreement with station observations. The gauge observations were the major source of the prediction skill of precipitation for the proposed method, and the downscaled-IMERG precipitation products added additional spatial details in the final merging results. Results indicate that the proposed merging method can reproduce the spatial details of the precipitation fields as well as enhance their accuracy. In addition, the time evolution of the error index indicates that the improvement in the merged result was stable over time, with KGE improving by 14% on average. The developed approach provides a promising way of estimating precipitation with high spatial resolution and high accuracy, which will benefit hydrological and climatological studies. |
| WOS关键词 | MULTISATELLITE ; PERFORMANCE ; MODEL ; PRODUCTS ; REGRESSION ; ALGORITHM ; SCHEME |
| WOS研究方向 | Environmental Sciences & Ecology ; Water Resources |
| 出版者 | MDPI |
| WOS记录号 | WOS:000935704000001 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/190341]  |
| 专题 | 资源与环境信息系统国家重点实验室_外文论文 |
| 作者单位 | 1.Jiangsu Ctr Collaborat Innovat Geog Informat Resou, Nanjing 210023, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100101, Peoples R China 3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhao, Na. A Novel Merging Method for Generating High-Quality Spatial Precipitation Information over Mainland China[J]. WATER,2023,15(3). |
| APA | Zhao, Na.(2023).A Novel Merging Method for Generating High-Quality Spatial Precipitation Information over Mainland China.WATER,15(3). |
| MLA | Zhao, Na."A Novel Merging Method for Generating High-Quality Spatial Precipitation Information over Mainland China".WATER 15.3(2023). |
入库方式： OAI收割
来源：地理科学与资源研究所
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