Articles | Volume 369
Proc. IAHS, 369, 7–11, 2015
https://doi.org/10.5194/piahs-369-7-2015
Proc. IAHS, 369, 7–11, 2015
https://doi.org/10.5194/piahs-369-7-2015

  11 Jun 2015

11 Jun 2015

Downscaling medium-range ensemble forecasts using a neural network approach

M. Ohba et al.

Cited articles

Gutiérrez, J. M., Cofiño, A. S., Cano, R., and Sordo, C.: Analysis and downscaling multi-model seasonal forecasts in Perú using self-organizing maps, Tellus A, 57, 435–447, 2005.
Hewitson, B. C. and Crane, R. G.: Self-organizing maps: applications to synoptic climatology, Clim. Res., 22, 13–26, 2002.
Kamiguchi, K., Arakawa, O., Kitoh, A., Yatagai, A., Hamada, A., and Yasutomi, N.: Development of APHRO_JP, the first Japanese high-resolution daily precipitation product for more than 100 years, Hydrolog. Res. Lett., 4, 60–64, 2010.
Kohonen, T.: Self-organized formation of topologically correct feature maps, Biol. Cybernet., 43, 59–69, 1982.
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Short summary
We present an application of self-organizing maps (SOMs) to downscaling weekly ensemble forecasts for probabilistic prediction of local precipitation. Downscaling weekly ensemble forecasts to local precipitation are conducted by using the obtained SOM lattice based on the WPs of the global model ensemble forecast. A probabilistic local precipitation is easily and quickly obtained from the ensemble forecast.