Over 5,000 Years of Ensemble Future Climate Simulations by 60-km Global and 20-km Regional Atmospheric Models

Abstract

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.

Future Changes in Global Precipitation Projected by the Atmospheric Model MRI-AGCM3.2H with a 60-km Size

“…Studies by [3][4][5] (Table S1) have revealed that the realistic reproduction of summertime precipitation over East Asia requires an atmospheric model with higher horizontal resolution. Therefore, we have been conducting a series of global warming projection experiments using the Meteorological Research Institute-Atmospheric General Circulation Model Version 3 (MRI-AGCM3) with 20-km and 60-km grid sizes [3,4,[6][7][8][9][10][11][12][13][14] (Table S1). These models have relatively higher horizontal resolution compared with global atmospheric models generally used in climate variability studies.…”

“…They found that the uncertainty of precipitation over the southern part of Asia originates in the difference among cumulus convection schemes, while that over the Maritime Continent (MC) is caused by the difference among SSTs. The dependence of precipitation change on SST was further investigated using future SSTs obtained from the fifth phase of the Coupled Model Intercomparison Project (CMIP5) AOGCMs [11][12][13][14] (Table S1). However, the dependence of precipitation change on the cumulus convection scheme has not yet been fully examined using future SSTs of CMIP5 AOGCMs.…”

Attributing Historical Changes in Probabilities of Record-Breaking Daily Temperature and Precipitation Extreme Events

“…We described the experimental setup of the historical and the non-warming experiments of d4PDF, which is briefly explained in Mizuta et al (2016) and Kamae et al (2016). This is also the first study that has compared large-size longterm attribution experiments using two AGCMs, specifically MRI-AGCM3.2 and CAM5.1, to investigate the impacts of anthropogenic factors on historical changes in the frequencies of recordbreaking daily temperature and precipitation extreme indices.…”

“…The NW ensemble included SST data, excluding the first principal component mode of the historical SST change, which is similar to the linear trend pattern (i.e., we approximately removed the linear trends in SST). The SIC in the NW runs were estimated using an empirical quadratic relationship between SST-SIC (Hirahara et al 2014;Mizuta et al 2016). We used GHG concentrations, anthropogenic aerosol and volcanic sulfate aerosol values of 1850, and 1961 ozone concentrations.…”

Statistical Downscaling of AGCM60km Precipitation based on Spatial Correlation of AGCM20km Output

“…If the number of the AGCM20km ensemble outputs is as many as the number of the AGCM60km outputs, such as more than 100 ensemble outputs from the database for Policy Decision making for Future climate change (d4PDF) experiments (Mizuta et al, 2016), the applicability of the model outputs in variant impact assessment research will be drastically increased.…”