Merging Satellites, Models and Gauges to Obtain New Precipitation Estimates

The most frequently used merged satellite/gauge global analyses of precipitation are the Global Precipitation Climatology Project (GPCP) analysis and the CPC Merged Analysis of Precipitation (CMAP). The multi-source nature of these datasets allows them to use the best data available to produce the most accurate estimate of precipitation for any given place and time. However, the quality of these datasets is reduced over mid- and high-latitude oceans where satellite estimates are of lower quality. Additionally, discontinuities, artifacts and inhomogeneities can be introduced by the use of time-varying inputs, which can impact the suitability of these datasets for investigation of long-term changes in global precipitation. The Multi-Source Analysis of Precipitation (MSAP) is a new global analysis of precipitation using Optimum Interpolation (OI) which naturally yields errors associated with the analysis that are needed for many applications. The initial version of the dataset uses the relatively long, consistent precipitation record (~20 years) from the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I) and forecast precipitation from the ERA-40 reanalysis. This version has been updated to include the ERA-Interim data which extends the record to 22 years, as well as several other modifications and corrections. We will also show results form recent experiments to construct an even longer version of MSAP which uses satellite estimate based on the OLR record which extends to 30 years.