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Keywords:

  • model evaluation;
  • radar forward operator;
  • CloudSat

Abstract

This article explores the uncertainties associated with evaluating a global atmospheric model with radar reflectivity observations. A forward operator for radar reflectivity (ZmVar) is described and used for the comparison of the ECMWF global numerical weather prediction model short-range forecasts with radar data from CloudSat. A sensitivity study is performed to determine which differences can be attributed to either specific radar forward operator assumptions or to deficiencies in the global model. The results show that model-derived reflectivities are particularly sensitive to the definition of subgrid precipitation fraction, as precipitation dominates the radar reflectivity signal, but also to the choice of particle size distribution and scattering properties of the different hydrometeor categories. However, there are a number of consistent differences in the reflectivity comparison that are significantly larger than can be explained by the sensitivity tests. This suggests that these discrepancies are due to deficiencies in the model cloud and precipitation frequency of occurrence and hydrometeor water contents. These include too frequent occurrence at high altitudes, too low occurrence in the Southern Hemisphere storm track and an overestimate of rain in warm-phase low cloud. The study shows the value of CloudSat for evaluating the model in terms of radar reflectivity and highlights the importance of taking into account forward operator uncertainties for both model evaluation and data assimilation applications. Copyright © 2012 Royal Meteorological Society