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Representing Mesoscale Cloud Variability in Superparameterized Climate models
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  • Fredrik Jansson,
  • Gijs van den Oord,
  • Inti Pelupessy,
  • Maria Chertova,
  • Johanna H Grönqvist,
  • Pier Siebesma,
  • Daan Crommelin
Fredrik Jansson
TU Delft, TU Delft

Corresponding Author:[email protected]

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Gijs van den Oord
Netherlands eScience Center, Netherlands eScience Center
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Inti Pelupessy
Netherlands eScience Center, Netherlands eScience Center
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Maria Chertova
Netherlands eScience Center, Netherlands eScience Center
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Johanna H Grönqvist
Åbo Akademi University, Åbo Akademi University
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Pier Siebesma
TU Delft, TU Delft
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Daan Crommelin
Centrum voor Wiskunde en Informatica, Centrum voor Wiskunde en Informatica, the Netherlands
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Abstract

In atmospheric modeling, superparameterization has gained popularity as a technique to improve cloud and convection representations in large scale models by coupling them locally to cloud-resolving models. We show how the different representations of cloud water in the local and the global models in superparameterization lead to a suppression of cloud advection and ultimately to a systematic underrepresentation of the cloud amount in the large scale model. We demonstrate this phenomenon in a regional superparameterization experiment with the global model OpenIFS coupled to the local model DALES (the Dutch Atmospheric Large Eddy Simulation), as well as in an idealized setup, where the large-scale model is replaced by a simple advection scheme. To mitigate the problem of suppressed cloud advection, we propose a scheme where the spatial variability of the local model’s total water content is enhanced in order to achieve the correct cloud condensate amount.