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An Evaluation of WRF Simulations of Clouds over the Southern Ocean with A-Train Observations

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  • 1 Monash Weather and Climate, Monash University, Melbourne, Australia
  • 2 National Center for Atmospheric Research, Boulder, Colorado
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Abstract

The representation of the marine boundary layer (BL) clouds remains a formidable challenge for state-of-the-art simulations. A recent study by Bodas-Salcedo et al. using the Met Office Unified Model highlights that the underprediction of the low/midlevel postfrontal clouds contributes to the largest bias of the surface downwelling shortwave radiation over the Southern Ocean (SO). A-Train observations and limited in situ measurements have been used to evaluate the Weather Research and Forecasting Model, version 3.3.1 (WRFV3.3.1), in simulating the postfrontal clouds over Tasmania and the SO. The simulated cloud macro/microphysical properties are compared against the observations. Experiments are also undertaken to test the sensitivity of model resolution, microphysical (MP) schemes, planetary boundary layer (PBL) schemes, and cloud condensation nuclei (CCN) concentration. The simulations demonstrate a considerable level of skill in representing the clouds during the frontal passages and, to a lesser extent, in the postfrontal environment. The simulations, however, have great difficulties in portraying the widespread marine BL clouds that are not immediately associated with fronts. This shortcoming is persistent to the changes of model configuration and physical parameterization. The representation of large-scale conditions and their connections with the BL clouds are discussed. A lack of BL moisture is the most obvious explanation for the shortcoming, which may be a consequence of either strong entrainment or weak surface fluxes. It is speculated that the BL wind shear/turbulence may be an issue over the SO. More comprehensive observations are necessary to fully investigate the deficiency of the simulations.

Corresponding author address: Yi Huang, Monash School of Mathematical Sciences, Monash University, Clayton Campus,Wellington Rd., Clayton, VIC 3800, Australia. E-mail: vivian.huang@monash.edu

Abstract

The representation of the marine boundary layer (BL) clouds remains a formidable challenge for state-of-the-art simulations. A recent study by Bodas-Salcedo et al. using the Met Office Unified Model highlights that the underprediction of the low/midlevel postfrontal clouds contributes to the largest bias of the surface downwelling shortwave radiation over the Southern Ocean (SO). A-Train observations and limited in situ measurements have been used to evaluate the Weather Research and Forecasting Model, version 3.3.1 (WRFV3.3.1), in simulating the postfrontal clouds over Tasmania and the SO. The simulated cloud macro/microphysical properties are compared against the observations. Experiments are also undertaken to test the sensitivity of model resolution, microphysical (MP) schemes, planetary boundary layer (PBL) schemes, and cloud condensation nuclei (CCN) concentration. The simulations demonstrate a considerable level of skill in representing the clouds during the frontal passages and, to a lesser extent, in the postfrontal environment. The simulations, however, have great difficulties in portraying the widespread marine BL clouds that are not immediately associated with fronts. This shortcoming is persistent to the changes of model configuration and physical parameterization. The representation of large-scale conditions and their connections with the BL clouds are discussed. A lack of BL moisture is the most obvious explanation for the shortcoming, which may be a consequence of either strong entrainment or weak surface fluxes. It is speculated that the BL wind shear/turbulence may be an issue over the SO. More comprehensive observations are necessary to fully investigate the deficiency of the simulations.

Corresponding author address: Yi Huang, Monash School of Mathematical Sciences, Monash University, Clayton Campus,Wellington Rd., Clayton, VIC 3800, Australia. E-mail: vivian.huang@monash.edu
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