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An 18‐Year Climatology of Directional Stratospheric Gravity Wave Momentum Flux From 3‐D Satellite Observations
Author(s) -
Hindley N. P.,
Wright C. J.,
Hoffmann L.,
MoffatGriffin T.,
Mitchell N. J.
Publication year - 2020
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1029/2020gl089557
Subject(s) - quasi biennial oscillation , climatology , stratosphere , northern hemisphere , atmospheric circulation , atmospheric sciences , momentum (technical analysis) , flux (metallurgy) , southern hemisphere , environmental science , atmospheric wave , gravity wave , general circulation model , atmosphere (unit) , zonal flow (plasma) , satellite , geology , gravitational wave , physics , meteorology , climate change , plasma , oceanography , materials science , finance , quantum mechanics , astronomy , astrophysics , economics , tokamak , metallurgy
Abstract Atmospheric gravity waves (GWs) are key drivers of the atmospheric circulation, but their representation in general circulation models (GCMs) is challenging, leading to significant biases in middle atmospheric circulations. Unresolved GW momentum transport in GCMs must be parameterized, but global directional GW observations are needed to constrain this. Here we present an 18‐year climatology of directional stratospheric GW momentum flux (GWMF) from global AIRS/Aqua 3‐D satellite observations during 2002 to 2019. Striking hemispheric asymmetries are found at high latitudes, including dramatic reductions and reversals of GWMF during sudden stratospheric warmings. During Southern Hemisphere winter, a lateral convergence of GWMF toward 60°S is found that has no Northern Hemisphere counterpart. In the tropics, we find that zonal GWMF in AIRS measurements is strongly modulated by the semiannual oscillation (SAO) but not the quasi‐biennial oscillation (QBO). Our results provide guidance for future GW parameterizations needed to resolve long‐standing biases in GCMs.

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