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David Randall
,
Marat Khairoutdinov
,
Akio Arakawa
, and
Wojciech Grabowski

A key factor limiting the reliability of simulations of anthropogenic climate change is the inability to accurately represent the various effects of clouds on climate. Despite the best efforts of the community, the problem has resisted solution for several decades. The reasons for this are briefly reviewed and it is argued that it will be many more decades before the problem can be solved through the approaches to cloud parameterization that have been used up to now. An alternative approach, called superparameterization, is then outlined, in which high-resolution cloud system-resolving models (CSRMs) are used in place of the conventional cloud parameterizations. Tests performed with the Community Atmosphere Model show that superparameterizations can give more realistic simulations of the current climate, including greatly improved simulations of the Madden–Julian oscillation and other tropical wave disturbances. Superparameterizations increase the cost of climate simulation by a factor of several hundred dollars, but can make efficient use of massively parallel computers. In addition, superparameterizations make it possible for a climate model to converge to a global CSRM as the horizontal grid spacing of the climate model decreases to a few kilometers. No existing global atmospheric model has this convergence property. Superparameterizations have the potential to greatly increase the reliability of climate change simulations.

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Akiyo Yatagai
,
Kenji Kamiguchi
,
Osamu Arakawa
,
Atsushi Hamada
,
Natsuko Yasutomi
, and
Akio Kitoh

A daily gridded precipitation dataset covering a period of more than 57 yr was created by collecting and analyzing rain gauge observation data across Asia through the activities of the Asian Precipitation—Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE) project. APHRODITE's daily gridded precipitation is presently the only long-term, continental-scale, high-resolution daily product. The product is based on data collected at 5,000–12,000 stations, which represent 2.3–4.5 times the data made available through the Global Telecommunication System network and is used for most daily gridded precipitation products. Hence, the APHRODITE project has substantially improved the depiction of the areal distribution and variability of precipitation around the Himalayas, Southeast Asia, and mountainous regions of the Middle East. The APHRODITE project now contributes to studies such as the determination of Asian monsoon precipitation change, evaluation of water resources, verification of high-resolution model simulations and satellite precipitation estimates, and improvement of precipitation forecasts. The APHRODITE project carries out outreach activities with Asian countries, and communicates with national institutions and world data centers. We have released open-access APHRO_V1101 datasets for monsoon Asia, the Middle East, and northern Eurasia (at 0.5° × 0.5° and 0.25° × 0.25° resolution) and the APHRO_JP_V1005 dataset for Japan (at 0.05° × 0.05° resolution; see www.chikyu.ac.jp/precip/ and http://aphrodite.suiri.tsukuba.ac.jp/). We welcome cooperation and feedback from users.

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Ryo Mizuta
,
Akihiko Murata
,
Masayoshi Ishii
,
Hideo Shiogama
,
Kenshi Hibino
,
Nobuhito Mori
,
Osamu Arakawa
,
Yukiko Imada
,
Kohei Yoshida
,
Toshinori Aoyagi
,
Hiroaki Kawase
,
Masato Mori
,
Yasuko Okada
,
Tomoya Shimura
,
Toshiharu Nagatomo
,
Mikiko Ikeda
,
Hirokazu Endo
,
Masaya Nosaka
,
Miki Arai
,
Chiharu Takahashi
,
Kenji Tanaka
,
Tetsuya Takemi
,
Yasuto Tachikawa
,
Khujanazarov Temur
,
Youichi Kamae
,
Masahiro Watanabe
,
Hidetaka Sasaki
,
Akio Kitoh
,
Izuru Takayabu
,
Eiichi Nakakita
, and
Masahide Kimoto

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.

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