Verification of TMI-Adjusted Rainfall Analyses of Tropical Cyclones at ECMWF Using TRMM Precipitation Radar

Author:

Benedetti A.1,Lopez P.1,Moreau E.1,Bauer P.1,Venugopal V.2

Affiliation:

1. European Centre for Medium-Range Weather Forecasts, Reading, United Kingdom

2. Saint Anthony Falls Laboratory, University of Minnesota, Minneapolis, Minnesota

Abstract

Abstract A validation of passive microwave–adjusted rainfall analyses of tropical cyclones using spaceborne radar data is presented. This effort is part of the one-dimensional plus four-dimensional variational (1D+4D-Var) rain assimilation project that is being carried out at the European Centre for Medium-Range Weather Forecasts (ECMWF). Brightness temperatures or surface rain rates from the Tropical Rainfall Measuring Mission (TRMM) satellite are processed through a 1D-Var retrieval to derive values of total column water vapor that can be ingested into the operational ECMWF 4D-Var. As an indirect validation, the precipitation fields produced at the end of the 1D-Var minimization process are converted into equivalent radar reflectivity at the frequency of the TRMM precipitation radar (13.8 GHz) and are compared with the observations averaged at model resolution. The averaging process is validated using a sophisticated downscaling/upscaling approach that is based on wavelet decomposition. The precipitation radar measurements are ideal for this validation exercise, being approximately collocated with but completely independent of the TRMM Microwave Imager (TMI) radiometer measurements. Qualitative and statistical comparisons between radar observations and retrievals from the TMI-derived surface rain rates and from TMI radiances are made using 17 well-documented tropical cyclone occurrences between January and April of 2003. Several statistical measures, such as bias, root-mean-square error, and Heidke skill score, are introduced to assess the 1D-Var skill as well as the model background skill in producing a realistic rain distribution. Results show a good degree of skill in the retrievals, especially near the surface and for medium–heavy rain. The model background produces precipitation in the domain that is sometimes in excess with respect to the observations, and it often shows an error in the location of precipitation maxima. Differences between the two 1D-Var approaches are not large enough to make final conclusions regarding the advantages of one method over the other. Both methods are capable of redistributing the rain patterns according to the observations. It appears, however, that the brightness temperature approach is in general more effective in increasing precipitation amounts at moderate-to-high rainfall rates.

Publisher

American Meteorological Society

Subject

Atmospheric Science

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