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Keywords:

  • Kalman filter;
  • TM3

Abstract

A data-assimilation scheme to assimilate the Global Ozone Monitoring Experiment (GOME) total-ozone data is described. The corresponding software (called TM3DAM) has been operational since early 2000 and is used to produce daily ozone analyses and five-day ozone forecasts. The model is a tracer-transport model with a parametrized description of stratospheric gas-phase and heterogeneous ozone chemistry. It is driven by operational meteorological fields from the ECMWF numerical weather-prediction model. TM3DAM analyses near-real-time level-2 ozone data from the GOME instrument on the ESA ERS-2 satellite. The focus of this paper is on the data-assimilation aspects and the analysis results. The assimilation approach is based on the Kalman-filter equations and provides detailed and realistic maps of the forecast error. The analysis scheme is nevertheless computationally efficient. The forecast-minus-observation statistics, accumulated over a two-year period, are described in detail. A comparison with TOMS and Brewer observations shows good agreement. Copyright © 2003 Royal Meteorological Society