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Shiling Peng, L. A. Mysak, J. Derome, H. Ritchie, and B. Dugas


Using an atmospheric global spectral model, it is shown that the winter atmosphere in the midlatitudes is capable of reacting to prescribed sea surface temperature (SST) anomalies in the northwest Atlantic with two very different responses. The nature of the response is determined by the climatological conditions of the winter regime. Experiments are performed using either the perpetual November or January conditions with or without the prescribed SST anomalies.

Warm SST anomalies in November result in a highly significant anomalous ridge downstream over the Atlantic with a nearly equivalent barotropic structure; in January, the response is a statistically less significant trough. The presence of the SST anomalies also causes a northward (southward) shift of the Atlantic storm track in the November (January) cases. A diagnostic analysis of the anomalous heat advection in the simulations reveals that in the January cases, the surface heating is offset primarily by the strong horizontal cold advection in the lower troposphere. In the November cases, there is a vitally important vertical heat advection through which a potential positive ocean-atmosphere feedback was found. The positive air temperature anomalies exhibit a deep vertical penetration in the November cases but not in the January cases.

The simulated atmospheric responses to the warm SST anomalies in the November and January cases are found to be in qualitative agreement with the observational results using 50-yr ( 1930-1979) records. The atmospheric responses to the cold SST anomalies in the simulations are found to be insignificant.

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J. F. Scinocca, V. V. Kharin, Y. Jiao, M. W. Qian, M. Lazare, L. Solheim, G. M. Flato, S. Biner, M. Desgagne, and B. Dugas


A new approach of coordinated global and regional climate modeling is presented. It is applied to the Canadian Centre for Climate Modelling and Analysis Regional Climate Model (CanRCM4) and its parent global climate model CanESM2. CanRCM4 was developed specifically to downscale climate predictions and climate projections made by its parent global model. The close association of a regional climate model (RCM) with a parent global climate model (GCM) offers novel avenues of model development and application that are not typically available to independent regional climate modeling centers. For example, when CanRCM4 is driven by its parent model, driving information for all of its prognostic variables is available (including aerosols and chemical species), significantly improving the quality of their simulation. Additionally, CanRCM4 can be driven by its parent model for all downscaling applications by employing a spectral nudging procedure in CanESM2 designed to constrain its evolution to follow any large-scale driving data. Coordination offers benefit to the development of physical parameterizations and provides an objective means to evaluate the scalability of such parameterizations across a range of spatial resolutions. Finally, coordinating regional and global modeling efforts helps to highlight the importance of assessing RCMs’ value added relative to their driving global models. As a first step in this direction, a framework for identifying appreciable differences in RCM versus GCM climate change results is proposed and applied to CanRCM4 and CanESM2.

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