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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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https://doi.org/10.5194/gmd-2019-193
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-2019-193
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: model evaluation paper 26 Aug 2019

Submitted as: model evaluation paper | 26 Aug 2019

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This preprint is currently under review for the journal GMD.

Effects of model configuration for superparametrised long-term simulations – Implementation of a cloud resolving model in EMAC (v2.50)

Harald Rybka1,2 and Holger Tost1 Harald Rybka and Holger Tost
  • 1Institute for Atmospheric Physics, Johannes Gutenberg-University, Mainz, Germany
  • 2German Weather Service, Offenbach am Main, Germany

Abstract. A new module has been implemented in the ECHAM5/MESSy Atmospheric Chemistry (EMAC) Model that simulates cloud related processes on a much smaller grid. This so called superparametrisation acts as a replacement for the convection parametrisation and large-scale cloud scheme. The concept of embedding an ensemble of cloud resolving models (CRMs) inside of each grid box of a general circulation model leads to an explicit representation of cloud dynamics.

The new model component is evaluated against observations and the conventional usage of EMAC using a convection parametrisation. In particular, effects of applying different configurations of the superparametrisation are analyzed in a systematical way. Consequences of changing the CRMs orientation, cell size and number of cells range from regional differences in cloud amount up to global impacts on precipitation distribution and its variability. For some edge case setups the analysed climate state of superparametrised simulations even deteriorates from the mean observed energy budget.

In the current model configuration different climate regimes can be formed that are mainly driven by some of the parameters of the CRM. Presently, the simulated cloud cover is at the lower edge of the CMIP5 model ensemble indicating that the hydrological overturning is too efficient. However, certain "tuning" of the current model configuration could improve the currently underestimated cloud cover, which will result in a shift of the climate.

The simulation results show that especially tropical precipitation is better represented with the superparamerisation in the EMAC model configuration. Furthermore, the diurnal cycle of precipitation is heavily affected by the choice of the CRM parameters. However, despite an improvement of the representation of the continental diurnal cycle in some configurations, other parameter choices result in a deterioration compared to the reference simulation using a conventional convection parameterisation.

The ability of the superparametrisation to represent latent and sensible heat flux climatology is dependent on the chosen CRM setup. Further interactions of the planetary boundary layer and the free troposphere can significantly influence cloud development on the large-scale. Therefore a careful selection of the CRM setup is recommended to compensate for computational expenses.

Harald Rybka and Holger Tost

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Harald Rybka and Holger Tost

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Latest update: 28 Feb 2020
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Short summary
Simulating cloud processes and their interactions with their environment is still one of the biggest challenge in atmospheric science. This study couples a cloud resolving model with a global climate model to improve the representation of small-scale processes for climate simulations. Unlike conventional approaches tropical precipitation is better simulated with the new model setup. However, interactions between the land surface and atmosphere is highly dependent on the chosen small-scale setup.
Simulating cloud processes and their interactions with their environment is still one of the...
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