Assimilation of Satellite Precipitable Water in a Meteorological Forecast Model

Abstract

The lack of local humidity observations over a large portion of the globe hinders any improvement of humidity forecasting in meteorological models. However, satellite microwave radiometers routinely provide fields of precipitable water content over the means, with a horizontal resolution of a few tens of kilometers. The aim of this paper is therefore to establish the feasibility of the assimilation of microwave radiometer precipitable water content in a forecast model. This preliminary study presents the assimilation method, which is based on optimal interpolation, and results of analysis and forecast runs over 12 h for one case. The Special Sensor Microwave/Imager (SSM/I) radiometer (the scanning microwave radiometer aboard the U.S. Navy Defense Meteorological Satellite Program satellite) and the Prévision à Echéance Rapprochée, Intégrant des Données Observées et Télédetéctées (PERIDOT) model (operational limited-area model of the French Meteorological Office) were used to perform this test. We show that assimilation of SSM/I data has a significant impact on the forecast, since the resulting fields, especially the humidity field, are more coherent with the next SSM/I data and radiosonde observations. The SSM/I assimilation is performed first once only, then throughout a 24-h assimilation cycle. Also, the model sensitivity is established to the vertical error in humidity in the optimal interpolation.