Seasonal characteristics of future climate change over Japan and the associated atmospheric circulation anomalies in global model experiments

Ito, Rui; Ose, Tomoaki; Endo, Hirokazu; Mizuta, Ryo; Yoshida, Kohei; Nakaegawa, Tosiyuki

doi:10.3178/hrl.14.130

Cited by 12 publications

(2 citation statements)

References 19 publications

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“…These results suggest that we can evaluate the effect of the moisture flux variability mainly with its northward component. Note that a somewhat similar result was obtained by Ito et al (2020), who investigated inter-model correlations in future centennial changes in seasonal mean climatology by using CMIP5 models and showed that the mean precipitation changes in the June-July-August period over Japan and surrounding ocean is positively correlated with the southwesterly wind changes over the same region.…”

Section: Relationship With Moisture Flux and Low-level Flowsupporting

confidence: 78%

Inter-model variability of the CMIP5 future projection of Baiu, Meiyu, and Changma precipitation

2022

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Many studies have suggested that mean precipitation associated with the East Asian Summer Monsoon (EASM) will be increased by the ongoing global warming, but its quantitative projection by climate models has large variability, with some models suggesting even decreases. We investigate the inter-model variability of projected centennial changes of the EASM separately for Baiu over Japan, Meiyu over eastern China, and Changma over Korea by using monthly-mean model outputs provided by the Coupled Model Intercomparison Project Phase 5 (CMIP5) project. Results with the Representative Concentration Pathway 4.5 and 8.5 scenarios (RCP4.5 and RCP8.5) are consolidated by normalizing with the global-mean near-surface air temperature changes. For all the three EASM land regions, inter-model differences in the mean precipitation changes are positively correlated with the southerly moisture flux changes to the south of the regions. The correlation is highest in June among the June-to-August months, whose reason may be because precipitation in early summer relies on large-scale southerly moisture transport. These changes are localized and nearly independent among the three regions where Baiu, Meiyu and Changma occur. The low-level southerly change to the south of Japan, which affects the Baiu precipitation change, is positively correlated with upper-tropospheric meridional wind to its north; it further exhibits a stationary Rossby-wave feature associated with the Silk-Road teleconnection. This study suggests that future changes in the EASM mean precipitation depend on circulation changes and more-or-less localized.

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Section: Relationship With Moisture Flux and Low-level Flowsupporting

confidence: 78%

Inter-model variability of the CMIP5 future projection of Baiu, Meiyu, and Changma precipitation

2022

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“…Note that the difference in the simulations between various model resolutions derives from not only the represented topography but also the precipitation systems themselves that the model is able to resolve. According to Ito et al (2020b), focusing on the areas around Japan that are included in EAS (22), the projection of the regional precipitation changes when considering the effect of typhoons that low-resolution models cannot represent.…”

Section: Enhanced Model Resolutionmentioning

confidence: 99%

Comparison of regional characteristics of land precipitation climatology projected by an MRI-AGCM multi-cumulus scheme and multi-SST ensemble with CMIP5 multi-model ensemble projections

Ito

Nakaegawa

Takayabu

2020

Prog Earth Planet Sci

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Ensembles of climate change projections created by general circulation models (GCMs) with high resolution are increasingly needed to develop adaptation strategies for regional climate change. The Meteorological Research Institute atmospheric GCM version 3.2 (MRI-AGCM3.2), which is listed in the Coupled Model Intercomparison Project phase 5 (CMIP5), has been typically run with resolutions of 60 km and 20 km. Ensembles of MRI-AGCM3.2 consist of members with multiple cumulus convection schemes and different patterns of future sea surface temperature, and are utilized together with their downscaled data; however, the limited size of the high-resolution ensemble may lead to undesirable biases and uncertainty in future climate projections that will limit its appropriateness and effectiveness for studies on climate change and impact assessments. In this study, to develop a comprehensive understanding of the regional precipitation simulated with MRI-AGCM3.2, we investigate how well MRI-AGCM3.2 simulates the present-day regional precipitation around the globe and compare the uncertainty in future precipitation changes and the change projection itself between MRI-AGCM3.2 and the CMIP5 multiple atmosphere–ocean coupled GCM (AOGCM) ensemble. MRI-AGCM3.2 reduces the bias of the regional mean precipitation obtained with the high-performing CMIP5 models, with a reduction of approximately 20% in the bias over the Tibetan Plateau through East Asia and Australia. When 26 global land regions are considered, MRI-AGCM3.2 simulates the spatial pattern and the regional mean realistically in more regions than the individual CMIP5 models. As for the future projections, in 20 of the 26 regions, the sign of annual precipitation change is identical between the 50th percentiles of the MRI-AGCM3.2 ensemble and the CMIP5 multi-model ensemble. In the other six regions around the tropical South Pacific, the differences in modeling with and without atmosphere–ocean coupling may affect the projections. The uncertainty in future changes in annual precipitation from MRI-AGCM3.2 partially overlaps the maximum–minimum uncertainty range from the full ensemble of the CMIP5 models in all regions. Moreover, on average over individual regions, the projections from MRI-AGCM3.2 spread over roughly 0.8 of the uncertainty range from the high-performing CMIP5 models compared to 0.4 of the range of the full ensemble.

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Projection of future heat-related morbidity in three metropolitan prefectures of Japan based on large ensemble simulations of climate change under 2 °C global warming scenarios

Ueta,

Kodera,

Sugimoto

et al. 2024

Environmental Research

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Seasonal characteristics of future climate change over Japan and the associated atmospheric circulation anomalies in global model experiments

Cited by 12 publications

References 19 publications

Inter-model variability of the CMIP5 future projection of Baiu, Meiyu, and Changma precipitation

Inter-model variability of the CMIP5 future projection of Baiu, Meiyu, and Changma precipitation

Comparison of regional characteristics of land precipitation climatology projected by an MRI-AGCM multi-cumulus scheme and multi-SST ensemble with CMIP5 multi-model ensemble projections

Projection of future heat-related morbidity in three metropolitan prefectures of Japan based on large ensemble simulations of climate change under 2 °C global warming scenarios

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