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Earth Sciences & Geography - Atmospheric Sciences | Improving Infrared-Based Precipitation Retrieval Algorithms Using Multi-Spectral Satellite Imagery

Improving Infrared-Based Precipitation Retrieval Algorithms Using Multi-Spectral Satellite Imagery

Series: Springer Theses

Nasrollahi, Nasrin

2015, XXI, 68 p. 41 illus., 38 illus. in color.

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  • Nominated by the University of California, Irvine, USA, as an outstanding Ph.D. thesis
  • Presents data sets that reduce false rain signals in satellite precipitation measurements
  • Provides advances in the accuracy of satellite-based precipitation estimation

This thesis transforms satellite precipitation estimation through the integration of a multi-sensor, multi-channel approach to current precipitation estimation algorithms, and provides more accurate readings of precipitation data from space. 

Using satellite data to estimate precipitation from space overcomes the limitation of ground-based observations in terms of availability over remote areas and oceans as well as spatial coverage. However, the accuracy of satellite-based estimates still need to be improved. 

The approach introduced in this thesis takes advantage of the recent NASA satellites in observing clouds and precipitation. In addition, machine-learning techniques are also employed to make the best use of remotely-sensed "big data." The results provide a significant improvement in detecting non-precipitating areas and reducing false identification of precipitation.

Content Level » Research

Keywords » CloudSat precipitation data - CloudSat texts - MODIS satellite observations - award-winning thesis - current satellite precipitation products - false rain reduction - introduction to satellite precipitation - multi-spectral satellite imagery - precipitation retrival algorithms - satellite precipitation data - satellite precipitation measurements - satellite-based precipitation estimation

Related subjects » Atmospheric Sciences - Environmental Engineering and Physics - Geophysics & Environmental Physics - Meteorology

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