气候变化领域集成服务门户(CCPortal): Estimating daily air temperatures over the Tibetan Plateau by dynamically integrating MODIS LST data

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DOI	10.1002/2016JD025154
	Estimating daily air temperatures over the Tibetan Plateau by dynamically integrating MODIS LST data
	Zhang, Hongbo; Zhang, Fan; Ye, Ming; Che, Tao; Zhang, Guoqing
通讯作者	Zhang, F (通讯作者)
发表日期	2016
ISSN	2169-897X
EISSN	2169-8996
起始页码	11425
结束页码	11441
卷号	121 期号:19
英文摘要	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.
关键词	ESTIMATING DAILY MAXIMUM SURFACE TEMPERATURE NEURAL-NETWORK SPATIAL INTERPOLATION BOOTSTRAP METHODS CLIMATE REGRESSION MINIMUM MASS
英文关键词	daily average air temperature; MODIS LST; support vector regression; random forests; cubist regression; Tibetan Plateau
语种	英语
WOS研究方向	Meteorology & Atmospheric Sciences
WOS类目	Meteorology & Atmospheric Sciences
WOS记录号	WOS:000386976100033
来源期刊	JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
来源机构	中国科学院青藏高原研究所
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/258757
推荐引用方式 GB/T 7714	Zhang, Hongbo,Zhang, Fan,Ye, Ming,et al. Estimating daily air temperatures over the Tibetan Plateau by dynamically integrating MODIS LST data[J]. 中国科学院青藏高原研究所,2016,121(19).
APA	Zhang, Hongbo,Zhang, Fan,Ye, Ming,Che, Tao,&Zhang, Guoqing.(2016).Estimating daily air temperatures over the Tibetan Plateau by dynamically integrating MODIS LST data.JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,121(19).
MLA	Zhang, Hongbo,et al."Estimating daily air temperatures over the Tibetan Plateau by dynamically integrating MODIS LST data".JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES 121.19(2016).