Status of High latitude precipitation estimates from observations and reanalyses

J Geophys Res Atmos. 2016 May 16;121(9):4468-4486. doi: 10.1002/2015JD024546. Epub 2016 Apr 5.

Abstract

An intercomparison of high-latitude precipitation characteristics from observation-based and reanalysis products is performed. In particular the precipitation products from CloudSat provide an independent assessment to other widely used products, these being the observationally-based GPCP, GPCC and CMAP products and the ERA-Interim, MERRA and NCEP-DOE R2 reanalyses. Seasonal and annual total precipitation in both hemispheres poleward of 55° latitude is considered in all products, and CloudSat is used to assess intensity and frequency of precipitation occurrence by phase, defined as rain, snow or mixed phase. Furthermore, an independent estimate of snow accumulation during the cold season was calculated from the Gravity Recovery and Climate Experiment (GRACE). The intercomparison is performed for the 2007-2010 period when CloudSat was fully operational. It is found that ERA- Interim and MERRA are broadly similar, agreeing more closely with CloudSat over oceans. ERA-Interim also agrees well with CloudSat estimates of snowfall over Antarctica where total snowfall from GPCP and CloudSat is almost identical. A number of disagreements on regional or seasonal scales are identified: CMAP reports much lower ocean precipitation relative to other products, NCEP-DOE R2 reports much higher summer precipitation over northern hemisphere land, GPCP reports much higher snowfall over Eurasia, and CloudSat overestimates precipitation over Greenland, likely due to mischaracterization of rain and mixed-phase precipitation. These outliers are likely unrealistic for these specific regions and time periods. These estimates from observations and reanalyses provide useful insights for diagnostic assessment of precipitation products in high latitudes, quantifying the current uncertainties, improving the products, and establishing a benchmark for assessment of climate models.