2017
DOI: 10.1175/jas-d-17-0053.1
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Momentum Flux of Convective Gravity Waves Derived from an Offline Gravity Wave Parameterization. Part I: Spatiotemporal Variations at Source Level

Abstract: Spatiotemporal variations in momentum flux spectra of convective gravity waves (CGWs) at the source level (cloud top), including nonlinear forcing effects, are examined based on calculations using an offline version of CGW parameterization and global reanalysis data for a period of 32 years (1979–2010). The cloud-top momentum flux (CTMF) is not solely proportional to the convective heating rate but is affected by the wave-filtering and resonance factor and background stability and temperature underlying the co… Show more

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Cited by 34 publications
(62 citation statements)
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“…There are two major factors that result in the seasonal variations in the occurrence frequency of GWs: (i) variations in the GW source itself and (ii) wave propagation conditions from the source to the observation altitude (i.e., impact of background wind and stability) (Kang et al, 2017). For a stationary mountain source, seasonal variation of orographic GWs is due mainly to (ii) depending on the transient background atmosphere around the mountain.…”
Section: Gws With Respect To the Potential Sourcesmentioning
confidence: 99%
“…There are two major factors that result in the seasonal variations in the occurrence frequency of GWs: (i) variations in the GW source itself and (ii) wave propagation conditions from the source to the observation altitude (i.e., impact of background wind and stability) (Kang et al, 2017). For a stationary mountain source, seasonal variation of orographic GWs is due mainly to (ii) depending on the transient background atmosphere around the mountain.…”
Section: Gws With Respect To the Potential Sourcesmentioning
confidence: 99%
“…The generation of GWs by convection is affected by many parameters, including lower-level wind shear, the width and depth of convective cells (Beres et al 2004(Beres et al , 2005, and resonance between wave modes and latent heating (Kang et al 2017). At the model resolutions considered here, parameterizations for deep convection are turned off (with the exception of IFS-9), but deep convection is still underresolved.…”
Section: ) Convective Sourcesmentioning
confidence: 99%
“…It is worth noting here that even large horizontal-scale phenomena may not be well represented at low latitudes in the reanalysis data because they are not balanced with well-observed quantities such as temperature due to small f . In fact, there is a large discrepancy in horizontal winds in the equatorial stratosphere among reanalysis datasets (Kawatani et al, 2016;Podglajen et al, 2014). It is also discussed by Kim and Chun (2015) that amplitudes of large horizontal-scale equatorial waves may be underestimated because the vertical grid spacing of the model is too coarse to resolve short vertical wavelengths that the equatorial waves may have in the strong vertical shear of the mean zonal wind of the QBO.…”
Section: Methods Of Analysismentioning
confidence: 99%