Bias adjustment of satellite-based precipitation estimation using artificial neural networks-cloud classification system over Saudi Arabia-Reference-Cited by-同舟云学术

Bias adjustment of satellite-based precipitation estimation using artificial neural networks-cloud classification system over Saudi Arabia

Published:2018-09 Issue:17 Volume:11 Page:
ISSN:1866-7511
Container-title:Arabian Journal of Geosciences
language:en
Short-container-title:Arab J Geosci

Author:

Alharbi Raied,Hsu Kuolin,Sorooshian Soroosh

Funder

King Saud University

Saudi Arabia Cultural Mission

National Science Foundation Cyber-Enabled Sustainability Science and Engineering program

the NASA Minority University Research and Education Project

Publisher

Springer Science and Business Media LLC

Subject

General Earth and Planetary Sciences,General Environmental Science

Link

http://link.springer.com/article/10.1007/s12517-018-3860-4/fulltext.html

Reference57 articles.

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2. Ahmed BYM (1997) Climate classification of Saudi Arabia: an application of factor—cluster analysis. GeoJournal 41(1):69–84

3. Ahmed K, Shahid S, Harun S, Nawaz N (2015) Performance assessment of different bias correction methods in statistical downscaling of precipitation. Malays J Civil Eng 2:311–324

4. Ajaaj AA, Mishra AK, Khan AA (2016) Comparison of BIAS correction techniques for GPCC precipitation data in semi-arid climate. Stoch Env Res Risk A 30(6):1659–1675

5. Al JET, Joyce RJ, Janowiak JE et al (2004) CMORPH: a method that produces global precipitation estimates from passive microwave and infrared data at high spatial and temporal resolution. J Hydrometeorol 5:487–503. https://doi.org/10.1175/1525-7541(2004)005<0487:CAMTPG>2.0.CO;2

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