Reconstruction of all-sky daily air temperature datasets with high accuracy in China from 2003 to 2022
文献类型：期刊论文
| 作者 | Wang, Min4,5; Wei, Jing3; Wang, Xiaodong2; Luan, Qingzu1; Xu, Xinliang4,5 |
| 刊名 | SCIENTIFIC DATA
 |
| 出版日期 | 2024-10-15 |
| 卷号 | 11期号:1页码:1133 |
| DOI | 10.1038/s41597-024-03980-z |
| 产权排序 | 1 |
| 英文摘要 | A high-accuracy, continuous air temperature (Ta) dataset with high spatiotemporal resolution is essential for human health, disease prediction, and energy management. Existing datasets consider factors such as elevation, latitude, and surface temperature but insufficiently address meteorological and spatiotemporal factors, affecting accuracy. Additionally, no high-resolution dataset currently includes daily maximum (Tmax), minimum (Tmin), and mean (Tmean) temperatures generated using a unified methodology. Here, we introduce the four-dimensional spatiotemporal deep forest (4D-STDF) model, integrating 12 multisource factors, encompassing static and dynamic parameters, and six refined spatiotemporal factors to produce Ta datasets. This approach generates three high-accuracy Ta datasets at 1 km spatial resolution covering mainland China from 2003 to 2022. These datasets, in GeoTIFF format with WGS84 projection, comprise daily Tmax, Tmin, and Tmean. The overall RMSE are 1.49 degrees C, 1.53 degrees C, and 1.18 degrees C for the estimates. The 4D-STDF model can also be applied to other regions with sparse meteorological stations. |
| WOS关键词 | 1 KM RESOLUTION ; SURFACE-TEMPERATURE ; DAILY MAXIMUM ; MORTALITY ; MODIS ; PRODUCT ; AREAS ; URBAN |
| WOS研究方向 | Science & Technology - Other Topics |
| WOS记录号 | WOS:001335843400004 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/208206]  |
| 专题 | 资源与环境信息系统国家重点实验室_外文论文 |
| 通讯作者 | Luan, Qingzu |
| 作者单位 | 1.Beijing Municipal Climate Ctr, Beijing Meteorol Bur, Beijing 100089, Peoples R China 2.Beijing Visiorld Technol Co Ltd, Beijing 100029, Peoples R China 3.Univ Maryland, Earth Syst Sci Interdisciplinary Ctr, Dept Atmospher & Ocean Sci, College Pk, MD 20742 USA 4.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 5.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 | Wang, Min,Wei, Jing,Wang, Xiaodong,et al. Reconstruction of all-sky daily air temperature datasets with high accuracy in China from 2003 to 2022[J]. SCIENTIFIC DATA,2024,11(1):1133. |
| APA | Wang, Min,Wei, Jing,Wang, Xiaodong,Luan, Qingzu,&Xu, Xinliang.(2024).Reconstruction of all-sky daily air temperature datasets with high accuracy in China from 2003 to 2022.SCIENTIFIC DATA,11(1),1133. |
| MLA | Wang, Min,et al."Reconstruction of all-sky daily air temperature datasets with high accuracy in China from 2003 to 2022".SCIENTIFIC DATA 11.1(2024):1133. |
入库方式： OAI收割
来源：地理科学与资源研究所
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