An Integrated Framework for Mapping Nationwide Daily Temperature in China
文献类型：期刊论文
| 作者 | Zhong, Shaobo1; Ye, Xinlan3; Wang, Mingxing3; Mei, Xin3; Song, Dunjiang2; Wang, Wenhui3 |
| 刊名 | ADVANCES IN METEOROLOGY
 |
| 出版日期 | 2022 |
| 卷号 | 2022 |
| ISSN号 | 1687-9309 |
| DOI | 10.1155/2022/9895576 |
| 文献子类 | Article |
| 英文摘要 | Air temperature (T-a) is an essential parameter for science research and engineering practice. While the traditional site-based approach is only able to obtain observations in limited and discrete locations, satellite remote sensing is promising to retrieve some environmental variables with spatially continuous coverage. Nowadays, land surface temperature (T-s) measurements can be obtained from some satellite sensors (e.g., MODIS), further enabling us to estimate T-a in view of the relationship between T-a and T-s. In this article, we proposed a two-phase integrated framework to estimate daily mean T-a nationwide. In the first phase, multivariate linear regression models were fitted between site-based observations of daily mean air temperature (Ta-mean) and MODIS land surface temperature products (including Terra day: TMOD-day, Terra night: TMOD-night, Aqua day: TMYD-day, and Aqua night: TMYD-night) conditional on some covariates of environmental factors. The fitted models were then used to predict Ta-mean from those covariates at unobserved locations. The predicted Ta-mean were looked on as stochastic variables, and their distributions were also obtained. In the second phase, Bayesian maximum entropy (BME) methods were used to produce spatially continuous maps of Ta-mean taking the meteorological station observations as hard data and the predicted Ta-mean in the first phase as soft data. It is shown that the proposed approach is promising to improve the interpolation accuracy significantly, comprehensively considering the prior knowledge and the context of space variability and correlation, which will enable it to compile spatially continuous air temperature products with higher accuracy. |
| WOS关键词 | YUN-GUI-GUANG ; AIR-TEMPERATURE ; DAILY MAXIMUM ; PRECIPITATION ; PRODUCTS ; DROUGHT |
| WOS研究方向 | Meteorology & Atmospheric Sciences |
| 语种 | 英语 |
| WOS记录号 | WOS:000800285700002 |
| 源URL | [http://ir.casisd.cn/handle/190111/12055]  |
| 专题 | 可持续发展政策研究所 |
| 作者单位 | 1.Beijing City Univ, Urban Construct Sch, Beijing, Peoples R China 2.Hubei Univ, Fac Resources & Environm Sci, Wuhan, Peoples R China 3.Beijing Acad Sci & Technol, Inst Urban Syst Engn, Beijing 100035, Peoples R China 4.Chinese Acad Sci, Inst Sci & Dev, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhong, Shaobo,Ye, Xinlan,Wang, Mingxing,et al. An Integrated Framework for Mapping Nationwide Daily Temperature in China[J]. ADVANCES IN METEOROLOGY,2022,2022. |
| APA | Zhong, Shaobo,Ye, Xinlan,Wang, Mingxing,Mei, Xin,Song, Dunjiang,&Wang, Wenhui.(2022).An Integrated Framework for Mapping Nationwide Daily Temperature in China.ADVANCES IN METEOROLOGY,2022. |
| MLA | Zhong, Shaobo,et al."An Integrated Framework for Mapping Nationwide Daily Temperature in China".ADVANCES IN METEOROLOGY 2022(2022). |
入库方式： OAI收割
来源：科技战略咨询研究院
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