Physical statistical algorithm for precipitable water vapor inversion on land surface based on multi-source remotely sensed data

Author:

Wang YongQian,Shi JianCheng,Wang Hao,Feng WenLan,Wang YanJun

Publisher

Springer Science and Business Media LLC

Subject

General Earth and Planetary Sciences

Reference59 articles.

1. Aires F, Prigent C, Rossow W B. 2001. A new neural network approach including first guess for retrieval of atmospheric water vapor, cloud liquid water path, surface temperature, and emissivities over land from satellite microwave observations. J Geophys Res, 106: 14887–14907

2. Bennartz R, Fischer J. 2001. Retrieval of columnar water vapor over land from backscattered solar radiation using the medium resolution imaging spectrometer. Remote Sens Environ, 78: 274–283

3. Bennouna Y S, Torres B, Cachorro V E. 2013. The annual cycle of total precipitable water vapor derived from different remote sensing techniques: An application to several sites of the Iberian Peninsula. In: AIP Conference Proceedings. Berlin. 1531

4. Brodzik M J, Knowles K W. 2002. EASE-Grid: A versatile set of equal-area projections and grids. Discrete Global Grids, 5: 110–125

5. Chang L, Jin S G. 2013. MODIS infrared water vapor calibration model and assessment. In: 21st International Conference on Geoinformatics (Geoinformatics). Kaifeng. 1–5

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