The Use of High Horizontal Resolution Satellite Temperature and Moisture Profiles to Initialize a Mesoscale Numerical Weather Prediction Model—A Severe Weather Event Case Study
Graham Mills, Christopher M. Hayden
Abstract
Graham Mills, Christopher M. Hayden
Abstract
This note describes the assimilation of sub-synoptic resolution satellite-derived temperature and moisture profiles into a mesoscale numerical weather prediction model, intended for forecasting the environment of organized convective storm complexes in the midwest of the United States. It is demonstrated that the use of high resolution satellite data to initialize this system results in a good level of forecast accuracy for the case study chosen, with very encouraging accuracy in the forecast moisture and vertical motion fields. It is also demonstrated that it is not simply the satellite data, but also the high horizontal resolution of these data, which positively affect the accuracy of the satellite data forecast.
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This note describes the assimilation of sub-synoptic resolution satellite-derived temperature and moisture profiles into a mesoscale numerical weather prediction model, intended for forecasting the environment of organized convective storm complexes in the midwest of the United States. It is demonstrated that the use of high resolution satellite data to initialize this system results in a good level of forecast accuracy for the case study chosen, with very encouraging accuracy in the forecast moisture and vertical motion fields. It is also demonstrated that it is not simply the satellite data, but also the high horizontal resolution of these data, which positively affect the accuracy of the satellite data forecast.
Key concepts: Mesoscale meteorology, Satellite, Numerical weather prediction, Data assimilation, Meteorology, Environmental science, Storm, Global Forecast System