artificial neural-network technique for precipitation nowcasting from satellite imagery

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ID: 248646
2006
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Abstract
The term nowcasting reflects the need of timely and accurate predictions of risky situations related to the development of severe meteorological events. In this work the objective is the very short term prediction of the rainfall field from geostationary satellite imagery entirely based on neural network approach. The very short-time prediction (or nowcasting) process consists of two steps: first, the infrared radiance field measured from geostationary satellite (Meteosat 7) is projected ahead in time (30 min or 1 h); secondly, the projected radiances are used to estimate the rainfall field by means of a calibrated microwave-based combined algorithm. The methodology is discussed and its accuracy is quantified by means of error indicators. An application to a satellite observation of a rainfall event over Central Italy is finally shown and evaluated.
Reference Key
rivolta2006advancesartificial Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;G. Rivolta;F. S. Marzano;F. S. Marzano;E. Coppola;M. Verdecchia
Journal journal of the medical library association
Year 2006
DOI
DOI not found
URL
http://www.adv-geosci.net/7/97/2006/adgeo-7-97-2006.pdf
Keywords
sciencegeologydynamic and structural geology

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