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Gravity wave momentum fluxes estimated from Project Loon balloon data
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  • Brian Green,
  • Aditi Sheshadri,
  • M. Joan Alexander,
  • Martina Bramberger,
  • François Lott
Brian Green
Stanford University

Corresponding Author:[email protected]

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Aditi Sheshadri
Stanford University
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M. Joan Alexander
NorthWest Research Associates, CoRA Office
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Martina Bramberger
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François Lott
Laboratoire de Météorologie Dynamique (LMD)/IPSL
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We present estimates of gravity wave momentum fluxes calculated from Project Loon superpressure balloon data collected between 2013 and 2021. In total, we analyzed more than 5000 days of data from balloon flights in the lower stratosphere, flights often over regions or during times of the year without any previous in-situ observations of gravity waves. Maps of mean momentum fluxes show significant regional variability; we analyze that variability using the statistics of the momentum flux probability distributions for six regions: the Southern Ocean, the Indian Ocean, and the tropical and extratropical Pacific and Atlantic Oceans. The probability distributions are all approximately log-normal, and using only their geometric means and geometric standard deviations we explain the sign and magnitude of regional mean and 99th percentile zonal momentum fluxes, and regional momentum flux intermittencies. We study the dependence of the zonal momentum flux on the background zonal wind and argue that the increase of the momentum flux with the wind speed over the Southern Ocean is likely due to a varying combination of both wave sources and filtering. Finally, we show that as the magnitude of the momentum flux increases, the fractional contributions by high-frequency waves increases, waves which need to be parameterized in large-scale models of the atmosphere. In particular, the near-universality of the log-normal momentum flux probability distribution, and the relation of its statistical moments to the mean momentum flux and intermittency, offer useful checks when evaluating parameterized or resolved gravity waves in models.
11 Sep 2023Submitted to ESS Open Archive
11 Sep 2023Published in ESS Open Archive