4.6 Article

Lessons learnt from the operational 1D+4D-Var assimilation of rain- and cloud-affected SSM/I observations at ECMWF

Journal

QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY
Volume 134, Issue 635, Pages 1513-1525

Publisher

WILEY
DOI: 10.1002/qj.304

Keywords

precipitation; numerical weather prediction; microwave radiance; satellite

Funding

  1. EUMETSAT
  2. Japan National Space Development Agency (NASDA)
  3. US National Aeronautics and Space Administration (NASA) Office of Earth Sciences

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Rain- and cloud-affected Special Sensor Microwave/Imager (SSM/I) observations are assimilated operationally at the European Centre for Medium-Range Weather Forecasts (ECMWF). The four-dimensional variational analysis (4D-Var) assimilates total column water vapour (TCWV) derived from one-dimensional variational retrievals (1D-Var). From the SSM/I radiances, 1D-Var retrieves surface wind and the vertical profiles of temperature, humidity, cloud and precipitation. The main shortcoming of the '1D+4D-Var' technique is that, of all this information, only TCWV gets into the 4D-Var analysis. More information could be used: the rainwater path agrees well, in an instantaneous comparison, with observations from the precipitation radar on the Tropical Rainfall Measuring Mission. There are other issues, however: the simplified moist physics operators used in 1D-Var produce roughly twice the observed amount of rain, but the problem is masked by a sampling bias, which comes from applying 1D+4D-Var when the observations are cloudy or rainy, but not when the first guess is rainy or cloudy and the observations are clear. The shortcomings of 1D+4D-Var will be addressed by moving to a direct 4D-Var assimilation which includes all SSM/I observations, whether clear, cloudy or rainy, in the same stream. Copyright (C) 2008 Royal Meteorological Society.

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