Possible changes in the tropical cyclones in a future, greenhouse-warmed climate are investigated using a 20 km-mesh, high-resolution, global atmospheric model of MRI/JMA, with the analyses focused on the evaluation of the frequency and wind intensity. Two types of 10-year climate experiments are conducted. One is a present-day climate experiment, and the other is a greenhouse-warmed climate experiment, with a forcing of higher sea surface temperature and increased greenhouse-gas concentration. A comparison of the experiments suggests that the tropical cyclone frequency in the warm-climate experiment is globally reduced by about 30% (but increased in the North Atlantic) compared to the presentday-climate experiment. Furthermore, the number of intense tropical cyclones increases. The maximum surface wind speed for the most intense tropical cyclone generally increases under the greenhousewarmed condition (by 7.3 m s À1 in the Northern Hemisphere and by 3.3 m s À1 in the Southern Hemisphere). On average, these findings suggest the possibility of higher risks of more devastating tropical cyclones across the globe in a future greenhouse-warmed climate.

A Madden-Julian Oscillation (MJO) is a massive weather event consisting of deep convection coupled with atmospheric circulation, moving slowly eastward over the Indian and Pacific Oceans. Despite its enormous influence on many weather and climate systems worldwide, it has proven very difficult to simulate an MJO because of assumptions about cumulus clouds in global meteorological models. Using a model that allows direct coupling of the atmospheric circulation and clouds, we successfully simulated the slow eastward migration of an MJO event. Topography, the zonal sea surface temperature gradient, and interplay between eastward- and westward-propagating signals controlled the timing of the eastward transition of the convective center. Our results demonstrate the potential making of month-long MJO predictions when global cloud-resolving models with realistic initial conditions are used.

A global atmospheric general circulation model, with the horizontal grid size of about 20 km, has been developed, making use of the Earth Simulator, the fastest computer available at present for meteorological applications. We examine the model's performance of simulating the present-day climate from small scale through global scale by time integrations of over 10 years, using a climatological sea surface temperature.Global distributions of the seasonal mean precipitation, surface air temperature, geopotential height, zonal-mean wind and zonal-mean temperature agree well with the observations, except for an excessive amount of global precipitation, and warm bias in the tropical upper troposphere. This model improves the representation of regional-scale phenomena and local climate, by increasing horizontal resolution due to better representation of topographical effects and physical processes, with keeping the quality of representation of global climate. The model thus enables us to study global characteristics of small-scale phenomena and extreme events in unprecedented detail.

Although a theory of the climatology of tropical cyclone formation remains elusive, high-resolution climate models can now simulate many aspects of tropical cyclone climate. T he effect of climate change on tropical cyclones has been a controversial scientific issue for a number of years. Advances in our theoretical understanding of the relationship between climate and tropical cyclones have been made, enabling us to understand better the links between the mean climate and the potential intensity (PI; the theoretical maximum intensity of a tropical cyclone for a given climate condition) of tropical cyclones. Improvements in the capabilities of climate models, the main tool used to predict future climate, have enabled them to achieve a considerably improved and more credible simulation of the present-day climatology of tropical cyclones. Finally, the increasing ability of such models to predict the interannual variability of tropical cyclone formation in various regions of the globe indicates that they are capturing some of the essential physical relationships governing the links between climate and tropical cyclones. HURRICANES AND CLIMATEPrevious climate model simulations, however, have suggested some ambiguity in projections of future numbers of tropical cyclones in a warmer world. While many models have projected fewer tropical cyclones globally (Sugi et al. 2002;Bengtsson et al. 2007b; Gualdi et al. 2008; Knutson et al. 2010), other climate models and related downscaling methods have suggested some increase in future numbers (e.g., Broccoli and Manabe 1990;Haarsma et al. 1993; Emanuel 2013a). When future projections for individual basins are made, the issue becomes more serious: for example, for the Atlantic basin there appears to be little consensus on the future number of tropical cyclones or on the relative importance of forcing factors such as aerosols or increases in carbon dioxide (CO 2 ) concentration. One reason could be statistical: annual numbers of tropical cyclones in the Atlantic are relatively small, making the identification of such storms sensitive to the detection method used.Further, there is substantial spread in projected responses of regional tropical cyclone (TC) frequency and intensity over the twenty-first century from downscaling studies (Knutson et al. 2007; Emanuel 2013a). Interpreting the sources of those differences is complicated by different projections of large-scale climate and by differences in the present-day reference period and sea surface temperature (SST) datasets used. A natural question is whether the diversity in responses to projected twenty-firstcentury climate of each of the studies is primarily | a reflection of uncertainty arising from different large-scale forcing (as has been suggested by, e.g., Villarini et al. 2011;Villarini and Vecchi 2012;Knutson et al. 2013) or whether this spread reflects principally different inherent sensitivities across the various downscaling techniques, even including different sensitivity of responses within the same model due to...