Articles | Volume 22, issue 2
Research article
26 Feb 2018
Research article |  | 26 Feb 2018

A nonparametric statistical technique for combining global precipitation datasets: development and hydrological evaluation over the Iberian Peninsula

Md Abul Ehsan Bhuiyan, Efthymios I. Nikolopoulos, Emmanouil N. Anagnostou, Pere Quintana-Seguí, and Anaïs Barella-Ortiz

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Cited articles

Adler, R. F., Kidd, C., Petty, G., Morissey, M., and Goodman, H. M.: Intercomparison of global precipitation products: the third precipitation intercomparison project (PIP–3), B. Am. Meteorol. Soc., 82, 1377–1396, 2001. 
AghaKouchak, A., Nasrollahi, N., and Habib, E.: Accounting for uncertainties of the TRMM Satellite Estimates, Remote Sens., 1, 606–619, 2009. 
Álvarez, J., Sánchez, A., and Quintas, L.: SIMPA, a GRASS based tool for hydrological studies, in: Proceedings of the FOSS/GRASS Users Conference, Bangkok, Thailand, 2004. 
Bhuiyan, M. A. E., Anagnostou, E. N, and Kirstetter, P. E.: A nonparametric statistical technique for modeling overland TMI (2A12) rainfall retrieval error, IEEE Geosci. Remote S., 14, 1898–1902, 2017. 
Bitew, M. M. and Gebremichael, M.: Evaluation of satellite rainfall products through hydrologic simulation in a fully distributed hydrologic model, Water Resour. Res., 47, W06526,, 2011. 
Short summary
This study investigates the use of a nonparametric model for combining multiple global precipitation datasets and characterizing estimation uncertainty. Inputs to the model included three satellite precipitation products, an atmospheric reanalysis precipitation dataset, satellite-derived near-surface daily soil moisture data, and terrain elevation. We evaluated the technique based on high-resolution reference precipitation data and further used generated ensembles to force a hydrological model.