2研ロゴ

Multi-Model Ensemble Dynamical Down-Scaling of precipitation over Japan for Seasonal Climate Predictions

Japanese
left parenthis Introduction right parenthis

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 (June-July-Augst) and winter (December-January-February). 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.

left parenthis Interannual variability right parenthis

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. These improvement in simulations of climatological mean precipitation in southwestern Japan in summer and on the Japan Sea side in winter is attributed to improved simulation of orographic precipitation as a result of their more realistic representation of topography.

The three RCMs simulated interannual variations, particularly summer precipitation, better than JRA-25 (Fig. 1). 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.

Figure 1

Fig. 1: Temporal correlation coefficients of interannual variability in summer precipitation versus observations in the 60 regions. The correlation coefficients are statistically significant at the a = 0.05 level when the absolute value of the correlation coefficient is greater 0.46.

Figure 2 shows the temporal correlation coefficients for the 60 regions of the AEM and the ensemble mean weighted according to the reliability. These results show that the skills of the AEM and the ensemble mean weighted according to the reliability are better than those of JRA-25 and each of the RCMs, although the improvements are not so large in winter than in summer.

Figure 2

Fig. 2: Same as in Fig. 1 but for winter.

References

Y. Ishizaki, T. Nakaegawa, and I. Takayabu, 2012: Validation of the precipitation simulated by three regional climate models and two multi-model ensemble means over Japan for the period 1985-2RCM Downscaling of Precipitation. Climate Dynamics. DOI: 10.1007/s00382-012-1304-5. Click here for Full Paper



前画面に戻る