Task 243

Development of a holistic statistical framework for precipitation estimation

Principal Investigator(s):

C. Kidd

Sponsor(s):

A. Hou

Last Updated:

October 26, 2012 15:26:09

Description of Problem

The objective is to develop and test techniques for the amalgamation of multi-sensor (satellite and surface) observations to improve global precipitation estimates.

Scientific Objectives and Approach

The project will exploit the wealth of satellite and surface data sets to provide a holistic statistical framework of precipitation estimation. Surface data sets will be sourced from gauge and radar products, and combined with satellite estimates sourced from multi-platforms observations. Results will be inter-compared with current state-of-the-art techniques to assess improvements and application potential. The project involves collaboration with colleagues at ESSIC, at Goddard Space Flight Center and major international partners.

Accomplishments

To date the primary goal has been the sourcing of both surface and satellite data sets. Surface data sets that have been procured so far include hourly and daily gauge data for the United Kingdom (1820-present), 1 km / 5 minute radar data for the UK (2002-present) and 5 km /15 minute radar data for Europe (2002-present). Satellite data sets, which would be used for intercomparison of the results have also be acquired, and include: PERSIANN (2000-present); CMORPH (2002-present); 3B42RT (2004-present); HYDRO-Estimator (2006-present); CPC merged microwave (2002-present); NRL-blended product (2003-present). In addition, the acquisition of model data sets has been initiated through cooperation with WGNE.

The project is also investigating optimal remapping strategies for the representation of global precipitation products, both from the developer’s point-of-view and from that of the user community.