Projected 21st century climate change on snow conditions over Shasta Dam watershed by means of dynamical downscaling. Issue 16 (28th June 2017)

• Record Type: Journal Article
• Authors: Trinh, Toan; Kavvas, M. Levent; Ishida, Kei; Carr, Kara; Ohara, Noriaki
• Is Part Of: Hydrological processes. Volume 31:Issue 16(2017)
• Page Start: 2887
• Page End: 2901
• Publication Date: 2017-06-28
• Subjects: dynamical downscaling (DD) -- emission scenarios -- global climate models (GCMs) -- regional climate model (RCM) -- Shasta Dam watershed (SDW) -- snow water equivalent (SWE); Hydrology -- Periodicals; Hydrology -- Research -- Periodicals; Hydrologic models -- Periodicals; Hydrological forecasting -- Periodicals; 631.432
• DOI: 10.1002/hyp.11231
• Languages: English
• ISSNs: 0885-6087

Abstract

Abstract: Snow is an important component of the Earth's climate system and is particularly vulnerable to global warming. It has been suggested that warmer temperatures may cause significant declines in snow water content and snow cover duration. In this study, snowfall and snowmelt were projected by means of a regional climate model that was coupled to a physically based snow model over Shasta Dam watershed to assess changes in snow water content and snow cover duration during the 21st century. This physically based snow model requires both physical data and future climate projections. These physical data include topography, soils, vegetation, and land use/land cover, which were collected from associated organizations. The future climate projections were dynamically downscaled by means of the regional climate model under 4 emission scenarios simulated by 2 general circulation models (fifth‐generation of the ECHAM general circulation model and the third‐generation atmospheric general circulation model). The downscaled future projections were bias corrected before projecting snowfall and snowmelt processes over Shasta Dam watershed during 2010–2099. This study's results agree with those of previous studies that projected snow water equivalent is decreasing by 50–80% whereas the fraction of precipitation falling as snowfall is decreasing by 15% to 20%. The obtained projection results show that future snow water content will change in both time and space. Furthermore, the results confirm that physical data such as topography, land cover, and atmospheric–hydrologic data are instrumental in the studies on the impact of climate change on the water resources of a region.