scholarly journals Future Changes in Precipitation Extremes in East Asia and Their Uncertainty Based on Large Ensemble Simulations with a High-Resolution AGCM

SOLA ◽  
2017 ◽  
Vol 13 (0) ◽  
pp. 7-12 ◽  
Author(s):  
Hirokazu Endo ◽  
Akio Kitoh ◽  
Ryo Mizuta ◽  
Masayoshi Ishii
Keyword(s):  
High Resolution ◽  
East Asia ◽  
Precipitation Extremes ◽  
Large Ensemble ◽  
Ensemble Simulations

scholarly journals Future Changes in Tropical Cyclone Activity in High‐Resolution Large‐Ensemble Simulations

2017 ◽  
Vol 44 (19) ◽  
pp. 9910-9917 ◽  
Author(s):  
Kohei Yoshida ◽  
Masato Sugi ◽  
Ryo Mizuta ◽  
Hiroyuki Murakami ◽  
Masayoshi Ishii
Keyword(s):  
High Resolution ◽  
Tropical Cyclone ◽  
Tropical Cyclone Activity ◽  
Cyclone Activity ◽  
Large Ensemble ◽  
Ensemble Simulations

scholarly journals Evaluation and Future Projection of Chinese Precipitation Extremes Using Large Ensemble High-Resolution Climate Simulations

2019 ◽  
Vol 32 (8) ◽  
pp. 2169-2183 ◽  
Author(s):  
Weili Duan ◽  
Naota Hanasaki ◽  
Hideo Shiogama ◽  
Yaning Chen ◽  
Shan Zou ◽  
...  
Keyword(s):  
High Resolution ◽  
General Circulation ◽  
Southern China ◽  
Coupled Model ◽  
Circulation Model ◽  
Internal Variability ◽  
Precipitation Extremes ◽  
Large Ensemble ◽  
Extreme Precipitation Events ◽  
The Difference

AbstractEvaluation of Chinese precipitation extremes is conducted based on large ensemble projections of the present climate and 4-K-warmer climates derived from a high-resolution atmospheric general circulation model. The model reproduced the overall trend and magnitude of total precipitation and extreme precipitation events for China reasonably well, revealing that this dataset can represent localized precipitation extremes. Precipitation extremes are more frequent and more severe in future projections under 4-K-warmer climates than in the representative concentration pathway 8.5 (RCP8.5) scenario of phase 5 of the Coupled Model Intercomparison Project (CMIP5). Our results show that using a large-ensemble simulation can improve the ability to estimate with high precision both the precipitation mean and the precipitation extremes compared with small numbers of simulations, and the averaged maximum yearly precipitation will be likely to increase by approximately 18% under a +4-K future in southern China compared with the past. Finally, uncertainty evaluation in future precipitation projections indicates that the component caused by the difference in six ΔSST patterns is more important in southern China compared with the component due to the atmospheric internal variability. All these results could provide valuable insights in simulating and predicting precipitation extremes in China.

scholarly journals CAS FGOALS-f3-L Large-ensemble Simulations for the CMIP6 Polar Amplification Model Intercomparison Project

2021 ◽  
Author(s):  
Bian He ◽  
Xiaoqi Zhang ◽  
Anmin Duan ◽  
Qing Bao ◽  
Yimin Liu ◽  
...  
Keyword(s):  
Time Lag ◽  
The Arctic ◽  
Global Ocean ◽  
Arctic Amplification ◽  
Model Intercomparison ◽  
Large Ensemble ◽  
Sea Ice Concentration ◽  
Ensemble Simulations ◽  
Polar Amplification ◽  
Intercomparison Project

AbstractLarge-ensemble simulations of the atmosphere-only time-slice experiments for the Polar Amplification Model Intercomparison Project (PAMIP) were carried out by the model group of the Chinese Academy of Sciences (CAS) Flexible Global Ocean-Atmosphere-Land System (FGOALS-f3-L). Eight groups of experiments forced by different combinations of the sea surface temperature (SST) and sea ice concentration (SIC) for pre-industrial, present-day, and future conditions were performed and published. The time-lag method was used to generate the 100 ensemble members, with each member integrating from 1 April 2000 to 30 June 2001 and the first two months as the spin-up period. The basic model responses of the surface air temperature (SAT) and precipitation were documented. The results indicate that Arctic amplification is mainly caused by Arctic SIC forcing changes. The SAT responses to the Arctic SIC decrease alone show an obvious increase over high latitudes, which is similar to the results from the combined forcing of SST and SIC. However, the change in global precipitation is dominated by the changes in the global SST rather than SIC, partly because tropical precipitation is mainly driven by local SST changes. The uncertainty of the model responses was also investigated through the analysis of the large-ensemble members. The relative roles of SST and SIC, together with their combined influence on Arctic amplification, are also discussed. All of these model datasets will contribute to PAMIP multi-model analysis and improve the understanding of polar amplification.

scholarly journals d4PDF: large-ensemble and high-resolution climate simulations for global warming risk assessment

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Masayoshi Ishii ◽  
Nobuhito Mori
Keyword(s):  
Risk Assessment ◽  
Global Warming ◽  
High Resolution ◽  
Climate Changes ◽  
Future Climate ◽  
Atmospheric Models ◽  
Large Ensemble ◽  
Past Climate ◽  
The Past ◽  
Climate Simulations

Abstract A large-ensemble climate simulation database, which is known as the database for policy decision-making for future climate changes (d4PDF), was designed for climate change risk assessments. Since the completion of the first set of climate simulations in 2015, the database has been growing continuously. It contains the results of ensemble simulations conducted over a total of thousands years respectively for past and future climates using high-resolution global (60 km horizontal mesh) and regional (20 km mesh) atmospheric models. Several sets of future climate simulations are available, in which global mean surface air temperatures are forced to be higher by 4 K, 2 K, and 1.5 K relative to preindustrial levels. Nonwarming past climate simulations are incorporated in d4PDF along with the past climate simulations. The total data volume is approximately 2 petabytes. The atmospheric models satisfactorily simulate the past climate in terms of climatology, natural variations, and extreme events such as heavy precipitation and tropical cyclones. In addition, data users can obtain statistically significant changes in mean states or weather and climate extremes of interest between the past and future climates via a simple arithmetic computation without any statistical assumptions. The database is helpful in understanding future changes in climate states and in attributing past climate events to global warming. Impact assessment studies for climate changes have concurrently been performed in various research areas such as natural hazard, hydrology, civil engineering, agriculture, health, and insurance. The database has now become essential for promoting climate and risk assessment studies and for devising climate adaptation policies. Moreover, it has helped in establishing an interdisciplinary research community on global warming across Japan.

scholarly journals Surface and top-of-atmosphere radiative feedback kernels for CESM-CAM5

2018 ◽  
Vol 10 (1) ◽  
pp. 317-324 ◽  
Author(s):  
Angeline G. Pendergrass ◽  
Andrew Conley ◽  
Francis M. Vitt
Keyword(s):  
Water Vapor ◽  
Greenhouse Gases ◽  
Surface Temperature ◽  
Radiative Forcing ◽  
Surface Albedo ◽  
Large Ensemble ◽  
Radiative Fluxes ◽  
Radiative Feedback ◽  
Ensemble Simulations ◽  
Temperature Water

Abstract. Radiative kernels at the top of the atmosphere are useful for decomposing changes in atmospheric radiative fluxes due to feedbacks from atmosphere and surface temperature, water vapor, and surface albedo. Here we describe and validate radiative kernels calculated with the large-ensemble version of CAM5, CESM1.1.2, at the top of the atmosphere and the surface. Estimates of the radiative forcing from greenhouse gases and aerosols in RCP8.5 in the CESM large-ensemble simulations are also diagnosed. As an application, feedbacks are calculated for the CESM large ensemble. The kernels are freely available at https://doi.org/10.5065/D6F47MT6, and accompanying software can be downloaded from https://github.com/apendergrass/cam5-kernels.

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