Japan Geoscience Union Meeting 2016

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International Session (Poster)

Symbol A (Atmospheric and Hydrospheric Sciences) » A-AS Atmospheric Sciences, Meteorology & Atmospheric Environment

[A-AS02] High performance computing of next generation weather, climate, and environmental sciences using K

Sun. May 22, 2016 5:15 PM - 6:30 PM Poster Hall (International Exhibition Hall HALL6)

Convener:*Masaki Satoh(Atmosphere and Ocean Research Institute, The University of Tokyo), Masahide Kimoto(Atmosphere and Ocean Research Institute, The University of Tokyo), Kazuo Saito(Forecast Research Department, Meteorological Research Institute), Hiromu Seko(Meteorological Research Institute), Takemasa Miyoshi(RIKEN Advanced Institute for Computational Science), Tetsuro Tamura(Tokyo Institute of Technology), Hiroshi Niino(Dynamic Marine Meteorology Group, Department of Physical Oceanography, Atmosphere and Ocean Research Institute,The University of Tokyo), Masayuki Takigawa(Japan Agency for Marine-Earth Science and Technology), Hirofumi Tomita(AICS, RIKEN), Chihiro Kodama(Japan Agency for Marine-Earth Science and Technology)

5:15 PM - 6:30 PM

[AAS02-P06] High cloud size dependency in the applicability of the fixed anvil temperature hypothesis using global non-hydrostatic simulations

★Invited papers

*Akira Noda1, Tatsuya Seiki1, Masaki Satoh1, Yohei Yamada1 (1.Japan Agency for Marine-Earth Science and Technology)

Keywords:climate change, global nonhydrostatic cloud-resolving simulation, High cloud

The applicability of the fixed anvil temperature (FAT) hypothesis is examined using data of a global non-hydrostatic model, focusing particularly on high cloud size dependency. Decomposition of outgoing-longwave radiation (OLR) into three components, including cloud-top temperature (TCT), upward cloud emissivity (ε), and clear-sky OLR (FCLR), reveals that the relative contributions of these three components to changes of OLR are highly dependent on cloud size. That is, the FAT hypothesis is applicable only to smaller clouds, because the contribution of TCT by those clouds is small, and ε is more important. In contrast, for larger clouds, the contribution of ε is comparable to that of TCT, and thus, both components are equally important. FCLR slightly reduces OLR, but shows dependence on cloud size.