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overestimate. 2. Dynamical core As in CM2.1 ( Delworth et al. 2006 ), the dynamical core used in AM3/CM3 follows the finite-volume algorithms described in Lin and Rood (1996 , 1997) and Lin (1997 , 2004) , with the following major modifications. In an effort to enhance the model’s parallel computing efficiency and to improve simulation quality in polar regions, the dynamical core formulated on, and optimized specifically for, the latitude–longitude grid has been significantly modified to use a general
overestimate. 2. Dynamical core As in CM2.1 ( Delworth et al. 2006 ), the dynamical core used in AM3/CM3 follows the finite-volume algorithms described in Lin and Rood (1996 , 1997) and Lin (1997 , 2004) , with the following major modifications. In an effort to enhance the model’s parallel computing efficiency and to improve simulation quality in polar regions, the dynamical core formulated on, and optimized specifically for, the latitude–longitude grid has been significantly modified to use a general
surface to fluctuate to values as large as the local ocean depth, | η | < H , whereas the geopotential model is subject to the more stringent constraint | η | < Δ z 1 , with Δ z 1 the thickness of the top grid cell with a resting ocean. The ocean models in CM2.1 and CM3 set a minimum depth to H ≥ 40 m, whereas Δ z 1 = 10 m (note that there is no wetting and drying algorithm in MOM4p1). This flexibility with z * is further exploited if considering even finer vertical grid resolution. The second
surface to fluctuate to values as large as the local ocean depth, | η | < H , whereas the geopotential model is subject to the more stringent constraint | η | < Δ z 1 , with Δ z 1 the thickness of the top grid cell with a resting ocean. The ocean models in CM2.1 and CM3 set a minimum depth to H ≥ 40 m, whereas Δ z 1 = 10 m (note that there is no wetting and drying algorithm in MOM4p1). This flexibility with z * is further exploited if considering even finer vertical grid resolution. The second
