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Boreal Winter MJO Teleconnection in the Community Atmosphere Model Version 5 with the Unified Convection Parameterization

Cited 21 time in Web of Science Cited 22 time in Scopus
Authors

Yoo, Changhyun; Park, Sungsu; Kim, Daehyun; Yoon, Jin-Ho; Kim, Hye-Mi

Issue Date
2015-10
Publisher
American Meteorological Society
Citation
Journal of Climate, Vol.28 No.20, pp.8135-8150
Abstract
The Madden-Julian oscillation (MJO), the dominant mode of tropical intraseasonal variability, influences weather and climate in the extratropics through atmospheric teleconnection. In this study, two simulations using the Community Atmosphere Model version 5 (CAM5)one with the default shallow and deep convection schemes and the other with the unified convection scheme (UNICON)are employed to examine the impacts of cumulus parameterizations on the simulation of the boreal wintertime MJO teleconnection in the Northern Hemisphere. It is demonstrated that the UNICON substantially improves the MJO teleconnection. When the UNICON is employed, the simulated circulation anomalies associated with the MJO better resemble the observed counterpart, compared to the simulation with the default convection schemes. Quantitatively, the pattern correlation for the 300-hPa geopotential height anomalies between the simulations and observation increases from 0.07 for the default schemes to 0.54 for the UNICON. These circulation anomalies associated with the MJO further help to enhance the surface air temperature and precipitation anomalies over North America, although room for improvement is still evident. Initial value calculations suggest that the realistic MJO teleconnection with the UNICON is not due to the changes in the background wind, but rather primarily to the improved tropical convective heating associated with the MJO.
ISSN
0894-8755
URI
https://hdl.handle.net/10371/200991
DOI
https://doi.org/10.1175/JCLI-D-15-0022.1
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  • College of Natural Sciences
  • Department of Earth and Environmental Sciences
Research Area Climate Change, Earth & Environmental Data, Severe Weather, 기후과학, 위험기상, 지구환경 데이터과학

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