In:
Journal of Climate, American Meteorological Society, Vol. 27, No. 17 ( 2014-09-01), p. 6526-6550
Abstract:
Statistically downscaled climate projections from nine global climate models (GCMs) are used to force a snow accumulation and ablation model (SNOW-17) across the central-eastern North American Landscape Conservation Cooperatives (LCCs) to develop high-resolution projections of snowfall, snow depth, and winter severity index (WSI) by the middle and late twenty-first century. Here, projections of a cumulative WSI (CWSI) known to influence autumn–winter waterfowl migration are used to demonstrate the utility of SNOW-17 results. The application of statistically downscaled climate data and a snow model leads to a better representation of lake processes in the Great Lakes basin, topographic effects in the Appalachian Mountains, and spatial patterns of climatological snowfall, compared to the original GCMs. Annual mean snowfall is simulated to decline across the region, particularly in early winter (December–January), leading to a delay in the mean onset of the snow season. Because of a warming-induced acceleration of snowmelt, the percentage loss in snow depth exceeds that of snowfall. Across the Plains and Prairie Potholes LCC and the Upper Midwest and Great Lakes LCC, daily snowfall events are projected to become less common but more intense. The greatest reductions in the number of days per year with a present snowpack are expected close to the historical position of the −5°C isotherm in December–March, around 44°N. The CWSI is projected to decline substantially during December–January, leading to increased likelihood of delays in timing and intensity of autumn–winter waterfowl migrations.
Type of Medium:
Online Resource
ISSN:
0894-8755
,
1520-0442
DOI:
10.1175/JCLI-D-13-00520.1
DOI:
10.1175/JCLI-D-13-00520.s1
Language:
English
Publisher:
American Meteorological Society
Publication Date:
2014
detail.hit.zdb_id:
246750-1
detail.hit.zdb_id:
2021723-7
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