Contributions of convective and orographic gravity waves to the Brewer–Dobson circulation estimated from NCEP CFSR

Min Jee Kang, Hye Yeong Chun, Byeong Gwon Song

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Abstract

Contributions of convective gravity waves (CGWs) and orographic gravity waves (OGWs) to the Brewer–Dobson circulation (BDC) are examined and compared to those from resolved waves. OGW drag (OGWD) is provided by NCEP Climate Forecast System Reanalysis (CFSR), while CGW drag (CGWD) is obtained from an offline calculation of a physically based CGW parameterization with convective heating and background data provided by CFSR. CGWD contributes to the shallow branch of the BDC regardless of the season, while OGWD contributes to both the shallow and deep branches except for the summertime, when OGWs hardly propagate into the stratosphere. At 70 hPa, the annual-mean tropical upward mass fluxes from Eliassen–Palm flux divergence (EPD), OGWD, and CGWD are 68%, 7%, and 4% of the total mass flux, respectively. The tropical upward mass flux at 70 hPa shows an increasing trend during the time period from 1979 to 1998, with 28%, 18%, and 6% of the trend driven by EPD, OGWD, and CGWD, respectively. The width of the turnaround latitudes tends to narrow for the streamfunctions induced by OGWD and CGWD but tends to widen for that induced by EPD. The contributions of GWD from MERRA (MERRA-2) to the climatology and long-term trend of the BDC are 7% (7%) and 13% (4%), respectively, somewhat smaller than the contributions of CGWD plus OGWD, which are estimated from CFSR to be 12% and 20%, respectively.

Original languageEnglish
Pages (from-to)981-1000
Number of pages20
JournalJournal of the Atmospheric Sciences
Volume77
Issue number3
DOIs
Publication statusPublished - 2020 Mar 1

Bibliographical note

Funding Information:
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the South Korea government (MSIT) (2017R1A2B2008025). The NCEP CFSR data were downloaded from the Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory, Boulder, Colorado (http://dx.doi.org/10.5065/D69K487J), and from the National Ocean and Atmospheric Administration (NOAA) National Operational Model Archive and Distribution System, National Climatic Data Center, Asheville, North Carolina (http://nomads.ncdc.noaa.gov/modeldata/cmd_pgbh/). The MERRA and MERRA-2 data were provided by the Global Modeling and Assimilation Office at NASA Goddard Space Flight Center through the NASA GES DISC online archive (https://gmao.gsfc.nasa.gov/reanalysis/). The ERA-I data were obtained from the ECMWF data server (http://apps.ecmwf.int/datasets/).

Funding Information:
Acknowledgments. This work was supported by the National Research Foundation of Korea (NRF) grant funded by the South Korea government (MSIT) (2017R1A2B2008025). The NCEP CFSR data were downloaded from the Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory, Boulder, Colorado (http://dx.doi.org/10.5065/D69K487J), and from the National Ocean and Atmospheric Administration (NOAA) National Operational Model Archive and Distribution System, National Climatic Data Center, Asheville, North Carolina (http://nomads. ncdc.noaa.gov/modeldata/cmd_pgbh/). The MERRA and MERRA-2 data were provided by the Global Modeling and Assimilation Office at NASA Goddard Space Flight Center through the NASA GES DISC online archive (https://gmao.gsfc.nasa.gov/reanalysis/). The ERA-I data were obtained from the ECMWF data server (http://apps.ecmwf.int/datasets/).

Publisher Copyright:
© 2020 American Meteorological Society.

All Science Journal Classification (ASJC) codes

  • Atmospheric Science

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