Statistical Downscaling of AGCM60km Precipitation based on Spatial Correlation of AGCM20km Output
Author:
Affiliation:
1. Graduate School of Engineering, Kyoto University
2. Disaster Prevention Research Institute, Kyoto University
Publisher
Japan Society of Hydrology and Water Resources
Subject
Earth and Planetary Sciences (miscellaneous),Water Science and Technology
Link
https://www.jstage.jst.go.jp/article/hrl/11/1/11_58/_pdf
Reference12 articles.
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2. Fowler H, Blenkinsop S, Tebaldi C. 2007. Linking climate change modelling to impacts studies: recent advances in downscaling techniques for hydrological modelling. International Journal of Climatology 27: 1547–1578. DOI: 10.1002/joc.1556.
3. Kim S, Nakakita E, Tachikawa Y, Shiiba M, Inoue M. 2014. Statistical downscaling of precipitation with a formatted regression frame. Journal of Japan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering) 70: I_901–I_906. DOI: 10.2208/jscejhe.70.I_901.
4. Kitoh A, Ose T, Kurihara K, Kusunoki S, Sugi M, KAKUSHIN Team-3 Modeling Group. 2009. Projection of changes in future weather extremes using super-high-resolution global and regional atmospheric models in the KAKUSHIN Program: Results of preliminary experiments. Hydrological Research Letter 3: 49–53. DOI: 10.3178/hrl.3.49.
5. Kitoh A, Kusunoki S, Nakaegawa T. 2011. Climate change projections over South America in the late 21st century with the 20 and 60 km mesh Meteorological Research Institute atmospheric general circulation model (MRI-AGCM). Journal of Geophysical Research 116: D06105. DOI: 10.1029/2010JD014920.
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