Three-Dimensional Variational Assimilation of InSAR PWV Using the WRFDA Model

This paper studies the problem of the assimilation of precipitable water vapor (PWV), estimated by synthetic aperture radar interferometry, using the Weather Research and Forecast Data Assimilation model 3-D variational data assimilation system. The experiment is designed to assess the impact of the PWV assimilation on the hydrometers and the rainfall predictions during 12 h after the assimilation time. A methodology to obtain calibrated maps of PWV and estimated their precision is also presented. The forecasts are compared with GPS estimates of PWV and with rainfall observations from a meteorological radar. Results show that after data assimilation, there is a correction of the bias in the PWV prediction and an improvement in the prediction of the weak to moderate rainfall up to 9 h after the assimilation time.

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