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Proceedings Paper

A local post-retrieval tool for satellite precipitation estimates
Author(s): Francesco Lo Conti; Antonia Incontrera; Leonardo V. Noto
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Paper Abstract

As illustrated by several literature case studies spread around different geographic locations, satellite precipitation estimates, obtained by means of consolidated algorithms, often result being considerably biased. Moreover observed bias is related to geographic location since particular features such as latitude, presence of coastal areas and climatological and weather regime, affect performances of satellite estimates. Bias adjusted products that make use of global ground-based precipitation estimates, are available as well but still these datasets may show a relevant bias level. In this study a procedure to bias-adjust satellite precipitation estimates has been developed for the local area of Sicily (Italy) based on rain-gauge network data. Considering that the latency time of satellite precipitation estimates is nowadays very short and close to that of satellite data availability, it has been investigated the possibility of designing a procedure that able to apply the bias reduction to satellite estimates without timely corresponding rain-gauge network data. Therefore, in order to obtain a tool that make available a first precipitation map estimate, the emphasis has been put on data readiness instead of achieving the best correction result. The developed procedure demonstrates to be able to improve the overall bias performances of examined satellite precipitation data. It is expected that such an approach increases its suitability as the developing of satellite estimates algorithms leads to better a description of rainfall dynamics.

Paper Details

Date Published: 19 October 2012
PDF: 12 pages
Proc. SPIE 8531, Remote Sensing for Agriculture, Ecosystems, and Hydrology XIV, 853119 (19 October 2012); doi: 10.1117/12.974675
Show Author Affiliations
Francesco Lo Conti, Univ. degli Studi di Palermo (Italy)
Antonia Incontrera, Univ. degli Studi di Palermo (Italy)
Leonardo V. Noto, Univ. degli Studi di Palermo (Italy)


Published in SPIE Proceedings Vol. 8531:
Remote Sensing for Agriculture, Ecosystems, and Hydrology XIV
Christopher M. U. Neale; Antonino Maltese, Editor(s)

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