A suite of numerical simulations with the Center for Ocean Land Atmosphere (COLA) Studies' atmospheric general circulation model (AGCM) has been performed in conjunction with the Dynamical Seasonal Prediction (DSP) Project. These simulations aim to quantify the impact of realistic land conditions on predictability and skill in the COLA AGCM. The numerical experiments cover three seasonal simulation periods: Northern Hemisphere winter (December-March), spring (March-June), and summer (June-September), and span the years 1982-1999. Within each seasonal simulation, a set of complementary runs are performed in which realistic precipitation, downward radiation at the surface, and land conditions (that includes soil moisture and snow depth) are prescribed in combination. Only the land model (that is coupled to the AGCM) responds to these improved atmospheric forcings and initialized (or assimilated) land states. The suite of analyses that is presented quantifies the impact of the land-model's response on the skill and predictability of simulated atmospheric quantities.

Results from the winter and spring runs indicate that improved snow conditions play a significant role toward skillfully capturing the interannual variations of near-surface air temperature, but primarily during the widespread ablation of the ephemeral snow cover, which typically occurs during April. Snow initialization tests indicate that the impact of the realistic initialization is short-lived, but can be strongly affected by model systematic error. Biases in near-surface air temperature at high-latitudes can be considerably reduced through the land model's response to realistic downward radiative fluxes. During the warm season, the land-model's response to realistic precipitation has a significant and beneficial feedback to simulated precipitation in the AGCM, and is most notable in mid-latitude summer. In addition, the response of the land model to prescribed (and more realistic) radiative forcing has a beneficial feedback on simulated warm-season precipitation. A diagnostic summary of these and other key findings will be presented.