Abstract
A review of Variational Data Assimilation together with a brief historical review is presented. Furthermore, a few methods used for improving Initial and Boundary Conditions in Numerical Weather Prediction are presented. The application of simple techniques applied to a mesoscale model, to improve the local initial condition, is presented. Both model aided studies and numerical experiments performed using the MM5 show that the assimilation of conventional data at high resolution may improve the forecast of the precipitation and the understanding of the local circulation.
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Ferretti, R. (2002). Mesoscale Modeling and Methods Applications. In: Marzano, F.S., Visconti, G. (eds) Remote Sensing of Atmosphere and Ocean from Space: Models, Instruments and Techniques. Advances in Global Change Research, vol 13. Springer, Dordrecht. https://doi.org/10.1007/0-306-48150-2_14
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DOI: https://doi.org/10.1007/0-306-48150-2_14
Publisher Name: Springer, Dordrecht
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