2001
DOI: 10.5194/hess-5-259-2001
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Statistical atmospheric downscaling for rainfall estimation in Kyushu Island, Japan

Abstract: Abstract. The present paper develops linear regression models based on singular value decomposition (SVD) with the aim of downscaling atmospheric variables statistically to estimate average rainfall in the Chikugo River Basin, Kyushu Island, southern Japan, on a 12-hour basis. Models were designed to take only significantly correlated areas into account in the downscaling procedure. By using particularly precipitable water in combination with wind speeds at 850 hPa, correlation coefficients between observed an… Show more

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Cited by 36 publications
(20 citation statements)
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References 30 publications
(32 reference statements)
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“…However, the outputs from the FGOALS model (see section S1.3 in supplementary information for more details) have a coarser spatial resolution of 2.8°longitude by 2.8°latitude. The projections for the A1B and B1 scenarios (IPCC, 2000) of the FGOALS were therefore statistically downscaled (Bertacchi et al, 2001;Lanza et al, 2001) to a resolution of 10 km 9 10 km.…”
Section: Methodsmentioning
confidence: 99%
“…However, the outputs from the FGOALS model (see section S1.3 in supplementary information for more details) have a coarser spatial resolution of 2.8°longitude by 2.8°latitude. The projections for the A1B and B1 scenarios (IPCC, 2000) of the FGOALS were therefore statistically downscaled (Bertacchi et al, 2001;Lanza et al, 2001) to a resolution of 10 km 9 10 km.…”
Section: Methodsmentioning
confidence: 99%
“…MCA identifies pairs of SLP and precipitation fields, characterized by high covariance, and the time evolution of their expression in the source data [principal components (PCs)]. Several studies applied MCA to a combination of meteorological and hydrological fields to link large-scale circulation patterns to local rainfall/temperature variability (Bertacchi Uvo et al 2001;Castaings et al 2009;Martín et al 2011). Extended descriptions on MCA analysis can be found in Bretherton et al (1992), Von Storch and Navara (1995), and Von Storch and Zwiers (1999).…”
Section: Maximum Covariance Analysis and Principal Componentsmentioning
confidence: 99%
“…Seasonal variability is a well-known characteristic of Japanese climate, ingrained in Japanese culture with innumerable mentions of the 'four seasons' (shiki) in Japanese literature and arts (Ackermann, 1997). This seasonality stems from the combination of several stationary weather systems and fronts (Uvo et al, 2001). In the south of Japan, during the winter season (December, January, February, or DJF in figures) air flow towards Japan is mainly controlled by the stationary Siberian High and Aleutian Low systems leading to low amounts of precipitation (Kazaoka and Kida, 2006).…”
Section: Introductionmentioning
confidence: 99%