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Abstract
As part of an international intercomparison project, the weak temperature gradient (WTG) and damped gravity wave (DGW) methods are used to parameterize large-scale dynamics in a set of cloud-resolving models (CRMs) and single column models (SCMs). The WTG or DGW method is implemented using a configuration that couples a model to a reference state defined with profiles obtained from the same model in radiative-convective equilibrium. We investigated the sensitivity of each model to changes in SST, given a fixed reference state. We performed a systematic comparison of the WTG and DGW methods in different models, and a systematic comparison of the behavior of those models using the WTG method and the DGW method. The sensitivity to the SST depends on both the large-scale parameterization method and the choice of the cloud model. In general, SCMs display a wider range of behaviors than CRMs. All CRMs using either the WTG or DGW method show an increase of precipitation with SST, while SCMs show sensitivities which are not always monotonic. CRMs using either the WTG or DGW method show a similar relationship between mean precipitation rate and column-relative humidity, while SCMs exhibit a much wider range of behaviors. DGW simulations produce large-scale velocity profiles which are smoother and less top-heavy compared to those produced by the WTG simulations. These large-scale parameterization methods provide a useful tool to identify the impact of parameterization differences on model behavior in the presence of two-way feedback between convection and the large-scale circulation.
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Details
1 Department of Meteorology, University of Reading, Reading, UK
2 National Centre for Atmospheric Science, Department of Meteorology, University of Reading, Reading, UK
3 Department of Physics, New Mexico Tech, Socorro, New Mexico, USA
4 Department of Environmental Sciences, Columbia University, New York, New York, USA
5 Department of Applied Physics and Applied Mathematics, Columbia University, New York, New York, USA
6 Department of Atmospheric Sciences, University of Washington, Seattle, Washington, USA
7 Climate Science Branch, NASA Langley Research Centre, Hampton, Virginia, USA
8 The Department of Physics, University of Auckland, Auckland, New Zealand
9 Meteo France, Toulouse, France
10 Royal Netherlands Meteorological Institute, De Bilt, Netherlands; Delft University of Technology, Delft, Netherlands
11 Royal Netherlands Meteorological Institute, De Bilt, Netherlands