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Validation of precipitation over Japan during 1985–2004 simulated by three regional climate models and two multi-model ensemble means

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Abstract

We dynamically downscaled Japanese reanalysis data (JRA-25) for 60 regions of Japan using three regional climate models (RCMs): the Non-Hydrostatic Regional Climate Model (NHRCM), modified RAMS version 4.3 (NRAMS), and modified Weather Research and Forecasting model (TWRF). We validated their simulations of the precipitation climatology and interannual variations of summer and winter precipitation. We also validated precipitation for two multi-model ensemble means: the arithmetic ensemble mean (AEM) and an ensemble mean weighted according to model reliability. In the 60 regions NRAMS simulated both the winter and summer climatological precipitation better than JRA-25, and NHRCM simulated the wintertime precipitation better than JRA-25. TWRF, however, overestimated precipitation in the 60 regions in both the winter and summer, and NHRCM overestimated precipitation in the summer. The three RCMs simulated interannual variations, particularly summer precipitation, better than JRA-25. AEM simulated both climatological precipitation and interannual variations during the two seasons more realistically than JRA-25 and the three RCMs overall, but the best RCM was often superior to the AEM result. In contrast, the weighted ensemble mean skills were usually superior to those of the best RCM. Thus, both RCMs and multi-model ensemble means, especially multi-model ensemble means weighted according to model reliability, are powerful tools for simulating seasonal and interannual variability of precipitation in Japan under the current climate.

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Acknowledgments

This work was supported by the Global Environment Research Fund (S-5-3) of the Ministry of the Environment, Japan. Comments by two anonymous reviewers, and editor are highly appreciated.

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Correspondence to Yasuhiro Ishizaki.

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Ishizaki, Y., Nakaegawa, T. & Takayabu, I. Validation of precipitation over Japan during 1985–2004 simulated by three regional climate models and two multi-model ensemble means. Clim Dyn 39, 185–206 (2012). https://doi.org/10.1007/s00382-012-1304-5

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