Characterization of the error distribution of satellite rainfall product has important benefits in practical applications such as rainfall-runoff modeling. Most operational satellite rainfall products are, however, still deterministic and lack any estimate of their uncertainty. Given a high resolution satellite rainfall estimate, it is of interest to know the distribution of the actual rainfall. We develop a new nonparametric model that generates the distribution of actual rainfall values for any given satellite rainfall estimate. The model handles the conditional distribution as the mixture of a positive continuous distribution and a point mass at zero. We fitted and validated the model using rain gauge-adjusted ground-based radar rainfall (representing actual rainfall) and CMORPH satellite rainfall estimates (representing high-resolution satellite rainfall), available at a resolution of 0.25° × 0.25° and 3-hourly, over a domain of 6.25° × 6.25° in the southern United States where the radar rainfall products are considered to be of high quality. The modeling approach can be replicated in other regions.
CITATION STYLE
Gebremichael, M., Liao, G. Y., & Yan, J. (2011). Nonparametric error model for a high resolution satellite rainfall product. Water Resources Research, 47(7). https://doi.org/10.1029/2010WR009667
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