The validation service of the hydrological SAF geostationary and polar satellite precipitation products

Abstract

The development phase (DP) of the EUMETSAT Satellite Application Facility for Support to Operational Hydrology and Water Management (H-SAF) led to the design and implementation of several precipitation products, after 5 yr (2005-2010) of activity. Presently, five precipitation estimation algorithms based on data from passive microwave and infrared sensors, on board geostationary and sun-synchronous platforms, function in operational mode at the H-SAF hosting institute to provide near real-time precipitation products at different spatial and temporal resolutions.

In order to evaluate the precipitation product accuracy, a validation activity has been established since the beginning of the project. A Precipitation Product Validation Group (PPVG) works in parallel with the development of the estimation algorithms with two aims: to provide the algorithm developers with indications to refine algorithms and products, and to evaluate the error structure to be associated with the operational products.

In this paper, the framework of the PPVG is presented: (a) the characteristics of the ground reference data available to H-SAF (i.e. radar and rain gauge networks), (b) the agreed upon validation strategy settled among the eight European countries participating in the PPVG, and (c) the steps of the validation procedures. The quality of the reference data is discussed, and the efforts for its improvement are outlined, with special emphasis on the definition of a ground radar quality map and on the implementation of a suitable rain gauge interpolation algorithm. The work done during the H-SAF development phase has led the PPVG to converge into a common validation procedure among the members, taking advantage of the experience acquired by each one of them in the validation of H-SAF products. The methodology is presented here, indicating the main steps of the validation procedure (ground data quality control, spatial interpolation, up-scaling of radar data vs. satellite grid, statistical score evaluation, case study analysis).

Finally, an overview of the results is presented, focusing on the monthly statistical indicators, referred to the satellite product performances over different seasons and areas.

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