| Estimating daily air temperatures over the Tibetan Plateau by dynamically integrating MODIS LST data | |
| Zhang, HB (Zhang, Hongbo)1,2; Zhang, F (Zhang, Fan)1,2; Ye, M (Ye, Ming)3; Che, T (Che, Tao)2,4; Zhang, GQ (Zhang, Guoqing)1,2; Zhang, F | |
| Source Publication | JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
 |
| 2016 | |
| Volume | 121Issue:19Pages:11425-11441 |
| DOI | 10.1002/2016JD025154 |
| Abstract | Recently, remotely sensed land surface temperature (LST) data have been used to estimate air temperatures because of the sparseness of station measurements in remote mountainous areas. Due to the availability and accuracy of Moderate Resolution Imaging Spectroradiometer (MODIS) LST data, the use of a single term or a fixed combination of terms (e.g., Terra/Aqua night and Terra/Aqua day), as used in previous estimation methods, provides only limited practical application. Furthermore, the estimation accuracy may be affected by different combinations and variable data quality among the MODIS LST terms and models. This study presents a method that dynamically integrates the available LST terms to estimate the daily mean air temperature and simultaneously considers model selection, data quality, and estimation accuracy. The results indicate that the differences in model performance are related to the combinations of LST terms and their data quality. The spatially averaged cloud cover of similar to 14% for the developed product between 2003 and 2010 is much lower than the 35-54% for single LST terms. The average cross-validation root-mean-square difference values are approximately 2 degrees C. This study identifies the best LST combinations and statistical models and provides an efficient method for daily air temperature estimation with low cloud blockage over the Tibetan Plateau (TP). The developed data set and the method proposed in this study can help alleviate the problem of sparse air temperature data over the TP. |
| Subject Area | 自然地理学 |
| WOS ID | WOS:000386976100033 |
| Language | 英语 |
| Indexed By | SCI |
| Keyword | Estimating Daily Maximum Support Vector Regression Land-surface Temperatures Neural-network Spatial Interpolation Bootstrap Methods Random Forests Avhrr Data Climate Resolution |
| Cooperation Status | 国际 |
| Department | 环境 |
| Subtype | Article |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.itpcas.ac.cn/handle/131C11/7537 |
| Collection | 图书馆 |
| Corresponding Author | Zhang, F |
| Affiliation | 1.Chinese Acad Sci, Inst Tibetan Plateau Res, Key Lab Tibetan Environm Changes & Land Surface P, Beijing, Peoples R China 2.CAS Ctr Excellence Tibetan Plateau Earth Sci, Beijing, Peoples R China 3.Florida State Univ, Dept Comp Sci, Tallahassee, FL 32306 USA 4.Chinese Acad Sci, Cold & Arid Reg Environm & Engn Res Inst, Beijing, Peoples R China |
| Recommended Citation GB/T 7714 | Zhang, HB ,Zhang, F ,Ye, M ,et al. Estimating daily air temperatures over the Tibetan Plateau by dynamically integrating MODIS LST data[J]. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,2016,121(19):11425-11441. |
| APA | Zhang, HB ,Zhang, F ,Ye, M ,Che, T ,Zhang, GQ ,&Zhang, F.(2016).Estimating daily air temperatures over the Tibetan Plateau by dynamically integrating MODIS LST data.JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,121(19),11425-11441. |
| MLA | Zhang, HB ,et al."Estimating daily air temperatures over the Tibetan Plateau by dynamically integrating MODIS LST data".JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES 121.19(2016):11425-11441. |
| Files in This Item: | ||||||
| File Name/Size | DocType | Version | Access | License | ||
| V.121(19) 11425-1144（3291KB） | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | View Application Full Text | |
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