Simulation of snow mass and extent in general circulation models

✍ Scribed by Zong-Liang Yang; Robert E. Dickinson; Andrea N. Hahmann; Guo-Yue Niu; M. Shaikh; Xiaogang Gao; Roger C. Bales; Soroosh Sorooshian; Jiming Jin

• Publisher: John Wiley and Sons
• Year: 1999
• Tongue: English
• Weight: 837 KB
• Volume: 13
• Category: Article
• ISSN: 0885-6087
• DOI: 10.1002/(sici)1099-1085(199909)13:12/13<2097::aid-hyp895>3.0.co;2-w

✦ Synopsis

An evaluation of the Biosphere±Atmosphere Transfer Scheme (BATS) snow submodel was conducted, both in a stand-alone mode and within the National Center for Atmospheric Research (NCAR) Community Climate Model version 3 (CCM3). We evaluated, in the stand-alone mode, the performance of BATS parameterizations at local scales using ground-based observations from the former Soviet Union and from Mammoth Mountain, California. The BATS snow scheme reproduces well the seasonal evolution of snow water equivalent in both sites, and the results for the Mammoth Mountain site compare well with those from a more complex, physically based model (SNTHERM). In the coupled mode, we evaluated the modelled snow cover extent, snow mass, precipitation and temperature from BATS as linked to the NCAR CCM3 using available observations. The coupled models capture the broad pattern of seasonal and geographical distribution of snow cover, with better overall performance than the passive microwave snow data derived from the Nimbus-7 Scanning Multi-channel Microwave Radiometer (SMMR) which generally underestimates snow depth. In terms of continents, the snow mass is better simulated during the accumulation period than during the melt period, which is the case for both North America and Eurasia. The simulation of snow mass, precipitation and air temperature for North America is slightly better than that for Eurasia. A rigorous evaluation of snow simulations in coupled land±atmosphere models requires high quality global datasets of snow cover extent, snow depth and snow water equivalent. The available datasets and model outputs are not yet ready to ful®l this objective.