Large-eddy simulation of subtropical cloud‐topped boundary layers: 1. A forcing framework with closed surface energy balance
Large‐eddy simulation (LES) of clouds has the potential to resolve a central question in climate dynamics, namely, how subtropical marine boundary layer (MBL) clouds respond to global warming. However, large‐scale processes need to be prescribed or represented parameterically in the limited‐area LES domains. It is important that the representation of large‐scale processes satisfies constraints such as a closed energy balance in a manner that is realizable under climate change. For example, LES with fixed sea surface temperatures usually do not close the surface energy balance, potentially leading to spurious surface fluxes and cloud responses to climate change. Here a framework of forcing LES of subtropical MBL clouds is presented that enforces a closed surface energy balance by coupling atmospheric LES to an ocean mixed layer with a sea surface temperature (SST) that depends on radiative fluxes and sensible and latent heat fluxes at the surface. A variety of subtropical MBL cloud regimes (stratocumulus, cumulus, and stratocumulus over cumulus) are simulated successfully within this framework. However, unlike in conventional frameworks with fixed SST, feedbacks between cloud cover and SST arise, which can lead to sudden transitions between cloud regimes (e.g., stratocumulus to cumulus) as forcing parameters are varied. The simulations validate this framework for studies of MBL clouds and establish its usefulness for studies of how the clouds respond to climate change.
© 2016. The Authors. This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial‐NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. Received 17 FEB 2016; Accepted 16 SEP 2016; Accepted article online 21 SEP 2016; Published online 8 OCT 2016. This work was supported by the U.S. National Science Foundation (grant CCF‐1048575), by Caltech's Terrestrial Hazard Observation and Reporting (THOR) Center, and by the Swiss National Science Foundation. The numerical simulations were performed on the Euler Cluster operated by the high performance computing (HPC) team at ETH Zürich. The PyCLES codes and the configurations for the new forcing framework are available online at climate-dynamics.org/software. We also thank Colleen Kaul for her contributions to the microphysics scheme in PyCLES.
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