An unprecedentedly large ensemble of climate simulations with a 60-km atmospheric general circulation model and dynamical downscaling with a 20-km regional climate model has been performed to obtain probabilistic future projections of low-frequency local-scale events. The climate of the latter half of the twentieth century, the climate 4 K warmer than the preindustrial climate, and the climate of the latter half of the twentieth century without historical trends associated with the anthropogenic effect are each simulated for more than 5,000 years. From large ensemble simulations, probabilistic future changes in extreme events are available directly without using any statistical models. The atmospheric models are highly skillful in representing localized extreme events, such as heavy precipitation and tropical cyclones. Moreover, mean climate changes in the models are consistent with those in phase 5 of the Coupled Model Intercomparison Project (CMIP5) ensembles. Therefore, the results enable the assessment of probabilistic change in localized severe events that have large uncertainty from internal variability. The simulation outputs are open to the public as a database called “Database for Policy Decision Making for Future Climate Change” (d4PDF), which is intended to be utilized for impact assessment studies and adaptation planning for global warming.

Using an international, multi-model suite of historical forecasts from the World Climate Research Programme (WCRP) Climate-system Historical Forecast Project (CHFP), we compare the seasonal prediction skill in boreal wintertime between models that resolve the stratosphere and its dynamics ("high-top") and models that do not ("low-top"). We evaluate hindcasts that are initialized in November, and examine the model biases in the stratosphere and how they relate to boreal wintertime (Dec-Mar) seasonal forecast skill.We are unable to detect more skill in the high-top ensemble-mean than the low-top ensemble-mean in forecasting the wintertime North Atlantic Oscillation, but model performance varies widely. Increasing the ensemble size clearly increases the skill for a given model. We then examine two major processes involving stratosphere-troposphere interactions (the El Niño-Southern Oscillation/ENSO and the Quasi-biennial Oscillation/QBO) and how they relate to predictive skill on intra-seasonal to seasonal timescales, particularly over the North Atlantic and Eurasia regions. High-top models tend to have a more realistic stratospheric response to El Niño and the QBO compared to low-top models. Enhanced conditional wintertime skill over high-latitudes and the North Atlantic region during winters with El Niño conditions suggests a possible role for a stratospheric pathway.

A new high-resolution atmosphere-ocean coupled general circulation model named MIROC4h has been developed, and its performance in a 120-year control experiment (including a 50-year spin-up) Compared with MIROC3h and MIROC3m, many improvements have been achieved; for example, errors in the surface air temperature and sea surface temperature are smaller, there is less drift of the ocean water temperature in the subsurface-deep ocean, and the frequency of heavy rain is comparable to observations. The fine horizontal resolution in the atmosphere makes orographic wind and its effects on the ocean more realistic than those of the former models, and the treatment of coastal upwelling motion in the ocean has been improved. Phenomena in the atmosphere and ocean related to the El Niño and southern oscillation are now closer to observations than was obtained by MIROC3h and MIROC3m. The effective climate sensitivity for CO 2 doubling is calculated to be about 5.7 K, which is much larger than the value obtained using the IPCC AR4 models, and is mainly due to a decrease in the low-level clouds at low latitudes.

The high sensitivity of the El Niñ o-Southern Oscillation (ENSO) to cumulus convection is examined by means of a series of climate simulations using an updated version of the Model for Interdisciplinary Research on Climate (MIROC), called MIROC5. Given that the preindustrial control run using MIROC5 shows a realistic ENSO, the integration is repeated with four different values of the parameter, l, which affects the efficiency of the entrainment rate in cumuli. The ENSO amplitude is found to be proportional to l 21 and to vary from 0.6 to 1.6 K.A comparison of four experiments reveals the mechanisms for which the cumulus convections control behavior of ENSO in MIROC as follows. Efficient entrainment due to a large l increases congestus clouds over the intertropical convergence zone (ITCZ) and reduces the vertical temperature gradient over the eastern Pacific, resulting in a wetter ITCZ and drier cold tongue via accelerated meridional circulation. The dry cold tongue then shifts the atmospheric responses to El Niñ o/La Niñ a westward, thereby reducing the effective Bjerknes feedback. The first half of these processes is identifiable in a companion set of atmosphere model experiments, but the difference in mean precipitation contrast is quite small. On one hand, the mean meridional precipitation contrast over the eastern Pacific is a relevant indicator of the ENSO amplitude in MIROC. On the other hand, the nonlinear feedback from ENSO affects the mean state, the latter therefore not regarded as a fundamental cause for different ENSO amplitudes.

The high temperature event in July 2018 caused record-breaking human damage throughout Japan. Large-ensemble historical simulations with a high-resolution atmospheric general circulation model showed that the occurrence rate of this event under the condition of external forcings in July 2018 was approximately 20%. This high probability was a result of the high-pressure systems both in the upper and lower troposphere in July 2018. The event attribution approach based on the large-ensemble simulations with and without human-induced climate change indicated the following: (1) The event would never have happened without anthropogenic global warming. (2) The strength of the two-tiered high-pressure systems was also at an extreme level and at least doubled the level of event probability, which was independent of global warming. Moreover, a set of the large-ensemble dynamically downscaled outputs revealed that the mean annual occurrence of extremely hot days in Japan will be expected to increase by 1.8 times under a global warming level of 2°C above pre-industrial levels.