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Clustering methods for statistical downscaling in short-range weather forecast
Title: | Clustering methods for statistical downscaling in short-range weather forecast |
Authors: | Gutiérrez Llorente, José Manuel; Cofiño González, Antonio Santiago; Cano Trueba, Rafael; Rodríguez, Miguel Ángel |
Keywords: | Clustering methods; Statistical downscaling; Short-range weather forecast |
Issue Date: | 2004 |
Publisher: | American Meteorological Society |
Citation: | Monthly Weather Review. 2004, 132(9), p. 2169-2183 |
Publisher version: | http://dx.doi.org/10.1175/1520-0493(2004)132<2169:CMFSDI>2.0.CO;2 |
Abstract: | In this paper we present an application of clustering algorithms for statistical downscaling in short-range weather forecast. The advantages of this technique compared with standard nearest neighbors analog methods are described both in terms of computational efficiency and forecast skill. We report some validation results of daily precipitation and maximum wind speed operative downscaling (lead time 1 to 5 days) on a network of 100 stations in the Iberian Peninsula the period 1998-1999. These results indicate that the weighting clustering method introduced in this paper clearly outperforms standard analog techniques for nfrequent, or extreme, events (precipitation > 20mm, wind > 80km/h). Outputs of an operative circulation model on different local-area or large-scale grids are considered to characterize the atmospheric circulation patterns, and the skill of both alternatives is compared. |
Sponsorship : | The authors are also grateful to the University of Cantabria, CSIC, and the Comisión Interministerial de Ciencia y Tecnología (CICYT; Grant REN2000-1572) for partial support of this work. |
URI: | http://hdl.handle.net/20.500.11765/1347 |
ISSN: | 0027-0644 1520-0493 |
Appears in Collections: | Artículos científicos 2000-2004 |
Files in This Item:
File | Description | Size | Format | ||
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![]() | 2004_Gutierrez_MWR.pdf | 2,68 MB | Adobe PDF | ![]() View/Open |
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