- 著者
-
Chihiro Kodama
Akira Kuwano-Yoshida
Shingo Watanabe
Takeshi Doi
Hiroki Kashimura
Tomoe Nasuno
- 出版者
- Japan Agency for Marine-Earth Science and Technology
- 雑誌
- JAMSTEC Report of Research and Development (ISSN:18801153)
- 巻号頁・発行日
- vol.28, pp.5-34, 2019-04-01 (Released:2019-04-03)
- 参考文献数
- 133
The JAMSTEC Model Intercomparison Project (JMIP) provides a first opportunity to systematically compare multiple global models developed and/or used in JAMSTEC with the aim of moving toward better weather and climate predictions. Here, we evaluate climate simulations obtained from atmospheric models (AFES and MIROC5), atmospheric model with slab ocean (NICAM.12), and fully coupled model (SINTEX-F1 and SINTEX-F2). In these simulations, the sea surface temperature is fixed (for AFES and MIROC5) or nudged (NICAM.12, SINTEX-F1, and SINTEX-F2) to the observed historical one. We focus on the climatology and variability of precipitation and its associated phenomena, including the basic state, the energy budget of the atmosphere, extratropical cyclones, teleconnection, and the Asian monsoon. We further discuss the possible causes of similarities and differences among the five JMIP models. Though some or most of the dynamical and physical packages in the JMIP models have been developed independently, common model biases are found among them. The AFES and MIROC5, and the SINTEX-F1 and SINTEX-F2, show strong similarities. In many respects, NICAM.12 shows unique characteristics, such as the distributions of precipitation, shortwave radiation, and explosive extratropical cyclones and the onset of the Asian summer monsoon. To some extent, the similarities and differences among the JMIP models overlap with those among the Coupled Model Intercomparison Project Phase-5 (CMIP5) models, suggesting that JMIP can be used as a simple and in-depth version of CMIP to investigate the mechanisms of model bias. We suggest that this JMIP framework could be expanded to an intercomparison of weekly-to-seasonal scale weather forecasting; here, more fruitful discussion is expected through intensive collaboration among modeling and observation groups.