Hack, J. J. and J. Kiehl, 1995: Reduction of systematic errors in the NCAR CCM2. Abstracts of the First International AMIP Scientific Conference, Monterey, California, 96.

The NCAR Community Climate Model was extensively redesigned with the introduction of the CCM2 in order to produce a state-of-the-art atmospheric general circulation model which was easy to use and to modify. Excessively simplified physical parameterizations, particularly for the determination of surface temperature, surface energy exchanges, boundary layer transfers, moist convection, and the diagnosis of cloud amount and its interaction with the radiation field, were all improved. Consequently, the overall CCM2 climate was substantially better than climates produced by previous versions of the CCM, which suffered from a variety of large systematic biases in the mean climate state.

Although many of the aspects of the CCM2 simulation represent improvements, a number of important systematic deficiencies remain, particularly in the context of coupling the CCM2 to land and ocean component models. These include a large warm bias in simulated July surface temperature over the Northern Hemisphere, a systematic overprediction of precipitation maxima, primarily over warm land areas, excessive ridging over the North Pacific and an anomalous reduction in the height field over Western North America in January, and cold polar tropopause temperatures. Our current understanding of the sources of these simulation deficiencies are in various stages of development, as are the associated solution strategies. We will report on the reduction of many of these systematic errors in the latest version of the NCAR CCM which has been developed as the atmospheric component for the NCAR Climate Systems Modelling initiative. We will illustrate the improvements in the simulation, both regionally and globally, and discuss the physical reasons for the response. We will also describe ongoing activities aimed at further improving the suitability of the CCM as an atmospheric component in future community coupled modeling initiatives.