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Satellite Rainfall Applications for Surface Hydrology pp 49–67Cite as

Extreme Precipitation Estimation Using Satellite-Based PERSIANN-CCS Algorithm

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Abstract

The need for frequent observations of precipitation is critical to many hydrological applications. The recently developed high resolution satellite-based precipitation algorithms that generate precipitation estimates at sub-daily scale provide a great potential for such purpose. This chapter describes the concept of developing high resolution Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS). Evaluation of PERSIANN-CCS precipitation is demonstrated through the extreme precipitation events from two hurricanes: Ernesto in 2006 and Katrina in 2005. Finally, the global near real-time precipitation data service through the UNESCO G-WADI data server is introduced. The query functions for viewing and accessing the data are included in the chapter.

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Acknowledgement

Partial support for this research is from NASA-EOS (Grant NA56GPO185), NASA-PMM (Grant NNG04GC74G), NASA NEWS (Grant NNX06AF93G) and NSF STC for “Sustainability of Semi-Arid Hydrology and Riparian Areas” (SAHRA) (Grant EAR-9876800). Authors appreciate the satellite data processing from Dan Braithwaite and manuscript editing from Diane Hohnbaum.

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Authors and Affiliations

  1. Civil and Environmental Engineering, The Henry Samueli School of Engineering, Center for Hydrometeorology and Remote Sensing, UC Irvine, 92697-2175, Irvine, CA, USA

    Kuo-Lin Hsu

  2. The Henry Samueli School of Engineering, Center for Hydrometeorology and Remote Sensing, UC Irvine, Irvine, CA, USA

    Ali Behrangi, Bisher Imam & Soroosh Sorooshian

Authors
  1. Kuo-Lin Hsu
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  2. Ali Behrangi
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  3. Bisher Imam
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  4. Soroosh Sorooshian
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Corresponding author

Correspondence to Kuo-Lin Hsu .

Editor information

Editors and Affiliations

  1. Dept. Civil & Environmental Engineering, University of Connecticut, Glenbrook Road 261, Storrs, 06269-2037, U.S.A.

    Mekonnen Gebremichael

  2. Dept. Civil & Environmental Engineering, Tennessee Technological University, Cookeville, 38505-0001, U.S.A.

    Faisal Hossain

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Hsu, KL., Behrangi, A., Imam, B., Sorooshian, S. (2010). Extreme Precipitation Estimation Using Satellite-Based PERSIANN-CCS Algorithm. In: Gebremichael, M., Hossain, F. (eds) Satellite Rainfall Applications for Surface Hydrology. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-2915-7_4

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