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An empirical parameterization of the subgrid-scale distribution of water vapor in the UTLS for atmospheric general circulation models
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  • Audran Borella,
  • Étienne VIGNON,
  • Olivier Boucher,
  • Susanne Rohs
Audran Borella
Institut Pierre-Simon Laplace

Corresponding Author:[email protected]

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Étienne VIGNON
Laboratoire de Météorologie Dynamique
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Olivier Boucher
Institut Pierre-Simon Laplace
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Susanne Rohs
Forschungszentrum Juelich
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Temperature and water vapor are known to fluctuate on multiple scales. In this study 27 years of airborne measurements of temperature and relative humidity from IAGOS (In-service Aircraft for a Global Observing System) are used to parameterize the distribution of water vapor in the upper troposphere and lower stratosphere (UTLS). The parameterization is designed to simulate water vapor fluctuations within gridboxes of atmospheric general circulation models (AGCMs) with typical size of a few tens to a few hundreds kilometers. The distributions currently used in such models are often not supported by observations at high altitude. More sophisticated distributions are key to represent ice supersaturation, a physical phenomenon that plays a major role in the formation of natural cirrus and contrail cirrus. Here the observed distributions are fitted with a beta law whose parameters are adjusted from the gridbox mean variables. More specifically the standard deviation and skewness of the distributions are expressed as empirical functions of the average temperature and specific humidity, two typical prognostic variables of AGCMs. Thus, the distribution of water vapor is fully parameterized for a use in these models. The new parameterization simulates the observed distributions with a determination coefficient always greater than 0.917, with a mean value of 0.997. Moreover, the ice supersaturation fraction in a model gridbox is well simulated with a determination coefficient of 0.983. The parameterization is robust to a selection of various geographical subsets of data and to gridbox sizes varying between 25 to 300 km.
01 Mar 2024Submitted to ESS Open Archive
05 Mar 2024Published in ESS Open Archive