9.1
One-dimensional variational assimilation of SSM/I observations in rainy atmospheres at the Meteorological Service of Canada

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Thursday, 2 February 2006: 11:00 AM
One-dimensional variational assimilation of SSM/I observations in rainy atmospheres at the Meteorological Service of Canada
A305 (Georgia World Congress Center)
Godelieve Deblonde, AES, Dorval, PQ, Canada; and J. F. Mahfouf, B. Bilodeau, and D. Anselmo

Currently, satellite radiances in the Canadian Meteorological Centre operational data assimilation system are only assimilated in clear skies. A two-step method, developed at the European Centre for Medium Range Weather Forecasts, is considered to assimilate Special Sensor Microwave/Imager (SSM/I) observations in rainy atmospheres. The first step consists of a one-dimensional variational (1D-Var) assimilation method. Model temperature and humidity profiles are adjusted by assimilating either SSM/I brightness temperatures (Tb) or retrieved surface rain rates (derived from SSM/I Tb). In the second step, 1D-Var column integrated water vapor analyses are assimilated in 4D-Var. At the Meteorological Service of Canada, such a 1D-Var assimilation system has been developed. Model profiles are obtained from a research version of the Global Environmental Multi-Scale model. Several issues raised while developing the 1D-Var system are addressed. The impact of the size of the observation error is studied when Tb is assimilated. For a given case study, analyses are derived when either surface rain rate or Tb is assimilated. Differences in the analyzed fields between these configurations are discussed and shortcomings of each approach are identified. Results of sensitivity studies are also provided. First the impact of observation error correlation between channels is investigated. Second, the size of the background temperature error is varied to assess its impact on the analyzed column integrated water vapor. Thirdly, the importance of each moist physical scheme is investigated. Finally, the portability of moist physical schemes specifically developed for data assimilation is discussed.