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Thomas Nehrkorn, Ross N. Hoffman, Jean-François Louis, Ronald G. Isaacs, and Jean-Luc Moncet

Abstract

The potential improvements of analyses and forecasts from the use of satellite-observed rainfall and water vapor measurements from the Defense Meteorological Satellite Program Special Sensor Microwave (SSM) T-1 and T-2 instruments are investigated in a series of observing system simulation experiments using the Air Force Phillips Laboratory (formerly Air Force Geophysics Laboratory) data assimilation system. Simulated SSM radiances are used directly in a radiance retrieval step following the conventional optimum interpolation analysis. Simulated rainfall rates in the tropics are used in a moist initialization procedure to improve the initial specification of divergence, moisture, and temperature.

Results show improved analyses and forecasts of relative humidity and winds compared to the control experiment in the tropics and the Southern Hemisphere. Forecast improvements are generally restricted to the first 1–3 days of the forecast.

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Ross N. Hoffman, Christopher Grassotti, Ronald G. Isaacs, Jean-Francois Louis, Thomas Nehrkorn, and Donald C. Norquist

Abstract

A series of observing system simulation experiments (0SSEs) was conducted to assess the impacts on the Air Force Geophysics Laboratory (GL) global data assimilation system (GDAS) of a satellite Doppler wind lidar sounding system (WINDSAT) and of the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave (SSM) T-1 and T-2 temperature and moisture retrievals. (The SSM/T-2 is expected to be launched in the early 1990s.) In simulating the SSM data, some horizontal correlations were induced because the simulated errors had different biases in different geophysical regimes. As an interpretative aid we calibrated our results to a series of real data experiments.

In an experiment in which the WINDSAT data is added to the observational database, the analyses and forecasts are improved relative to the control experiment. These improvements are large in the Southern Hemisphere extratropics. The addition of the SSM data improves the analysis of moisture particularly in the tropics and Southern Hemisphere extratropics.

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