Author(s):
Allan Frei - Hunter College
Ross Brown - Meteorological Service of Canada
James A. Miller - Arizona State University
David A. Robinson - Rutgers University
Abstract:
18 Global Atmospheric General Circulation Models (AGCMs) participating in the second phase of the Atmospheric Model Intercomparison Project (AMIP-2) are evaluated for their ability to simulate the observed spatial and temporal variability in snow mass, or water equivalent (SWE), over North America during the AMIP-2 period (1979-1995). The evaluation is based on a new gridded SWE data set developed from objective analysis of daily snow depth observations from Canada and the U.S. with snow density estimated from a simple snowpack model. Most AMIP-2 models simulate the seasonal timing and the relative spatial patterns of continental scale SWE fairly well. However, significant between-model variability is found in every aspect of the simulations, and at every spatial scale analyzed. For example, on the continental scale, the peak monthly SWE integrated over the North American continent in AMIP-2 models varies between ± 50% of the observed value of ~1500 km3. It also appears that the median result from the suite of models tends to do a better job of estimating climatological mean features than any individual model. Year-to-year variations in large scale SWE are only weakly correlated to observed variations, indicating that sea surface temperatures (specified from observations as boundary conditions) do not drive interannual variations of SWE in these models. These results have implications for simulations of the large scale hydrologic cycle and for climate change impact assessments.
