Single-Column Model Simulations of Subtropical Marine Boundary-Layer Cloud Transitions Under Weakening Inversions
Neggers, R. a. J. ; Ackerman, A. S. ; Angevine, W. M. ; Bazile, Eric ; Beau, Isabelle ; Blossey, P. N. ; Boutle, I. A. ; de Bruijn, C. ; Cheng, A. ; van der Dussen, J. ; Fletcher, J. ; Dal Gesso, S. ; Jam, A. ; Kawai, H. ; Cheedela, S. K. ; Larson, V. E. ; Lefebvre, Marie-Pierre ; Lock, A. P. ; Meyer, N. R. ; de Roode, S. R. ; de Rooy, W. ; Sandu, I. ; Xiao, H. ; Xu, K.-M.
Results are presented of the GASS/EUCLIPSE single-column model intercomparison study on the subtropical marine low-level cloud transition. A central goal is to establish the performance of state-of-the-art boundary-layer schemes for weather and climate models for this cloud regime, using large-eddy simulations of the same scenes as a reference. A novelty is that the comparison covers four different cases instead of one, in order to broaden the covered parameter space. Three cases are situated in the North-Eastern Pacific, while one reflects conditions in the North-Eastern Atlantic. A set of variables is considered that reflects key aspects of the transition process, making use of simple metrics to establish the model performance. Using this method, some longstanding problems in low-level cloud representation are identified. Considerable spread exists among models concerning the cloud amount, its vertical structure, and the associated impact on radiative transfer. The sign and amplitude of these biases differ somewhat per case, depending on how far the transition has progressed. After cloud breakup the ensemble median exhibits the well-known 'too few too bright' problem. The boundary-layer deepening rate and its state of decoupling are both underestimated, while the representation of the thin capping cloud layer appears complicated by a lack of vertical resolution. Encouragingly, some models are successful in representing the full set of variables, in particular, the vertical structure and diurnal cycle of the cloud layer in transition. An intriguing result is that the median of the model ensemble performs best, inspiring a new approach in subgrid parameterization.
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