Thursday, 10 January 2013
Exhibit Hall 3 (Austin Convention Center)
Regionalizing global climate impacts to hydrologically relevant variables is critical to many impacts across the arid western U.S. In this work we use Bias Correction with Constructed Analogues (BCCA) statistical downscaling to examine the effect of human-induced climate change on snow resources. We find that there will be uneven effects on different snow-related variables such as the water content of the spring snowpack, total cold season snowfall, fraction of winter precipitation that falls as snow, length of the snow season, and fraction of cold season precipitation retained in the spring snowpack. Various stakeholders may be interested in different sets of these variables. For example, the winter recreation industry is affected by the snow season length and total snowfall; flooding is affected by the fraction of winter precipitation that falls as snow; water management is concerned with the amount of water stored in the spring snowpack; and the transportation industry is affected by the first and last days of the snow season. This work contrasts the effect of human-induced climate warming on different snow variables, comparing the relative time required for snow measures to achieve a statistically significant linear trend, using time series derived from global climate models regionally downscaled to the western U.S. It is found that temperature and the fraction of winter precipitation that falls as snow exhibit significant trends first, followed in 5-10 years by the fraction of cold season precipitation that is retained in the spring snowpack, and later still by the water content of the spring snowpack. Total cold-season snowfall is the measure least affected by anthropogenic climate change, since in snow-dominated regions it is strongly linked to precipitation, which has only a weak trend in the region. Averaging over increasingly wider areas monotonically increases the signal-to-noise ratio of the 1950-2025 linear trend by 0.15 to 0.37, depending on the snow measure.
- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner