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14 December 1998 Using IR satellite data to improve the initialization of a mesoscale model
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An empirical technique to blend satellite imagery into a conventional meteorological analysis has been developed in order to enhance the 3D humidity field in a numerical weather prediction model. Temperatures retrieved from IR Meteosat images are used to locate and grossly characterize clouds, and this information further employed to dry and moisten individual atmospheric cells from a previous conventional analysis. To verify the improvements attained with this technique, we have compared a set of 260 forecasts obtained with a conventional initialization of the mesoscale model MASS, and those from the enhanced initialized. Standard indexes, such as mean error, k root mean squared error and S1, have been used to objectively evaluate the quality of the forecasts over the Southwestern European region. It turns out that the inclusion of satellite imagery in the initial analysis leads to improvements up to 30 percent in more than 200 out of the 260 days considered over the typical meteorological fields. Although for several reasons no attempt has been made to compare complex fields such as precipitations, it is obvious that an improved depiction of the driving fields might result in better weather forecasts.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
B. Codina, A. Sairouni, Josep Vidal, and Angel Redano "Using IR satellite data to improve the initialization of a mesoscale model", Proc. SPIE 3495, Satellite Remote Sensing of Clouds and the Atmosphere III, (14 December 1998);

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