A comparison between atmospheric water vapour content retrieval methods using MSG2-SEVIRI thermal-IR data

作者：Zhang Xiaoyu^*; Pang Jing

来源：International Journal of Remote Sensing, 2015, 36(19-20): 5075-5086.

DOI：10.1080/01431161.2015.1041180

Atmospheric water vapour content (WVC) is a vital parameter in the study of climate change. Various methods have been developed to derive atmospheric WVC from remotely sensed data. In this study, we compared three methods for retrieving atmospheric WVC from thermal infrared data in the Meteosat Second Generation-SEVIRI channels 9 (10.8m) and 10 (12.0?m). The three methods are (1) the split-window covariance-variance ratio method using a spatial moving window (method 1); (2) the split-window covariance-variance ratio method using a temporal moving window (method 2); and (3) the varying surface temperature method using split-window channel data (method 3). The derived WVC using these three methods was compared to two WVC data sets from European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis data and the MODIS WVC product. Compared with these two data sets, the derived WVC using method 1 performed proved optimal. The valid pixels using methods 1 and 2 are greater than those using method 3. Furthermore, method 2 can be used to retrieve WVC over pixels where method 1 is invalid.

• 出版日期2015-10
• 单位山西大学