Advances in the Stochastic Modeling of Satellite-Derived Rainfall Estimates Using a Sparse Calibration Dataset

As satellite technology develops, satellite rainfall estimates are likely to become ever more important in the world of food security. It is therefore vital to be able to identify the uncertainty of such estimates and for end users to be able to use this information in a meaningful way. This paper presents new developments in the methodology of simulating satellite rainfall ensembles from thermal infrared satellite data. Although the basic sequential simulation methodology has been developed in previous studies, it was not suitable for use in regions with more complex terrain and limited calibration data. Developments in this work include the creation of a multithreshold, multizone calibration procedure, plus investigations into the causes of an overestimation of low rainfall amounts and the best way to take into account clustered calibration data. A case study of the Ethiopian highlands has been used as an illustration.

© American Meteorological Society 2014.

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Work Title Advances in the Stochastic Modeling of Satellite-Derived Rainfall Estimates Using a Sparse Calibration Dataset
Access
Open Access
Creators
  1. Helen Greatrex
  2. David Grimes
  3. Tim Wheeler
Keyword
  1. Africa
  2. Complex terrain
  3. Rainfall
  4. Satellite observations
  5. Error analysis
  6. Ensembles
License In Copyright (Rights Reserved)
Work Type Article
Publisher
  1. Journal of Hydrometeorology
Publication Date October 1, 2014
Publisher Identifier (DOI)
  1. https://doi.org/10.1175/JHM-D-13-0145.1
Deposited February 19, 2024

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Version 1
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  • Added Creator David Grimes
  • Added Creator Tim Wheeler
  • Added hydr-jhm-d-13-0145_1.pdf
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    License
    • https://rightsstatements.org/page/InC/1.0/
  • Published
  • Updated Keyword, Publisher Show Changes
    Keyword
    • Africa, Complex terrain, Rainfall, Satellite observations, Error analysis, Ensembles
    Publisher
    • Journal of Hydrometeorology
  • Updated