Global monthly CMIP6-downscaled high-resolution (1 km) near-surface air temperature dataset (1950-2100)
文献类型：期刊论文
| 作者 | Lei, Xuewen7,8; Meng, Qingyan6,7,8; Luo, Ming1; Zhang, Linlin6,7,8; Yin, Mijia5,7; Liu, Longfei2; Zhao, Qikang3,4,8 |
| 刊名 | SCIENTIFIC DATA
 |
| 出版日期 | 2025-10-28 |
| 卷号 | 12期号:1页码:1704 |
| DOI | 10.1038/s41597-025-05987-6 |
| 产权排序 | 5 |
| 文献子类 | Article |
| 英文摘要 | Temperature projections from general circulation models (GCMs), serving as an important approach of understanding future global warming, are essential for developing adaptation and mitigation strategies of climate change. However, the coarse spatial resolutions (similar to 1-3 degrees) limit their effectiveness at fine-scale (e.g., intra-urban) research. Here, we produced MoCHAT, a global monthly CMIP6-downscaled high-resolution (1 km) near-surface air temperature dataset. We utilized delta downscaling method to generate MoCHAT based on NEX-GDDP-CMIP6 and WorldClim. MoCHAT encompasses mean, maximum, and minimum air temperature of 16 GCMs. It covers both the historical period (1950-2014) and future scenarios (2015-2100) under three Shared Socioeconomic Pathways (SSPs) scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5). Validation with meteorological station observations and existing high-resolution climatic datasets showed that the mean absolute errors for these variables range from 1.60 to 2.38 K and overall biases below 2.0 K. With sufficiently long span and fine resolution, MoCHAT breaks through data resolution limitations and provides solid support for global fine-scale heat risk research. |
| URL标识 | 查看原文 |
| WOS关键词 | URBAN HEAT-ISLAND ; CLIMATE-CHANGE ; REGIONAL CLIMATE ; PROJECTIONS ; PRECIPITATION ; SIMULATIONS ; CHINA |
| WOS研究方向 | Science & Technology - Other Topics |
| 语种 | 英语 |
| WOS记录号 | WOS:001604750700005 |
| 出版者 | NATURE PORTFOLIO |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/217686]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Meng, Qingyan; Zhang, Linlin; Zhao, Qikang |
| 作者单位 | 1.Sun Yat Sen Univ, Sch Geog & Planning, Guangzhou 510006, Peoples R China; 2.Natl Disaster Reduct Ctr China, Beijing 100124, Peoples R China; 3.Univ Macau, State Key Lab Internet Things Smart City, Macau 999078, Peoples R China; 4.Univ Macau, Dept Ocean Sci & Technol, Macau 999078, Peoples R China 5.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China; 6.Hainan Aerosp Informat Res Inst, Key Lab Earth Observat Hainan Prov, Sanya 572029, Peoples R China; 7.Univ Chinese Acad Sci, Beijing 100049, Peoples R China; 8.Chinese Acad Sci, Aerosp Informat Res Inst, Beijing 100094, Peoples R China; |
| 推荐引用方式 GB/T 7714 | Lei, Xuewen,Meng, Qingyan,Luo, Ming,et al. Global monthly CMIP6-downscaled high-resolution (1 km) near-surface air temperature dataset (1950-2100)[J]. SCIENTIFIC DATA,2025,12(1):1704. |
| APA | Lei, Xuewen.,Meng, Qingyan.,Luo, Ming.,Zhang, Linlin.,Yin, Mijia.,...&Zhao, Qikang.(2025).Global monthly CMIP6-downscaled high-resolution (1 km) near-surface air temperature dataset (1950-2100).SCIENTIFIC DATA,12(1),1704. |
| MLA | Lei, Xuewen,et al."Global monthly CMIP6-downscaled high-resolution (1 km) near-surface air temperature dataset (1950-2100)".SCIENTIFIC DATA 12.1(2025):1704. |
入库方式： OAI收割
来源：地理科学与资源研究所
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