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Welcome to the publications directory for the Climate Impacts Group and the Climate Dynamics Group. Please contact the web administrator for assistance with any of these publications.

View: Abstract

A high-resolution climate model for the U.S. Pacific Northwest: Mesoscale feedbacks and local responses to climate change

Salathé, E.P., R. Steed, C.F. Mass, and P. Zahn. 2008. A high-resolution climate model for the U.S. Pacific Northwest: Mesoscale feedbacks and local responses to climate change. Journal of Climate 21(21): 5708-5726, doi:10.1175/2008JCLI2090.1.


Simulations of future climate scenarios produced with a high-resolution climate model show markedly different trends in temperature and precipitation over the Pacific Northwest than in the global model in which it is nested, apparently due to mesoscale processes not resolved at coarse resolution. Present-day (1990-1999) and future (2020-2029, 2045-2054, and 2090-2099) conditions are simulated at high resolution (15-km grid spacing) using the MM5 model system and forced by ECHAM5 global simulations. Simulations use the IPCC Special Report on Emissions Scenarios (SRES) A2 emissions scenario, which assumes a rapid increase in greenhouse gas concentrations. The mesoscale simulations produce regional alterations in snow cover, cloudiness, and circulation patterns associated with interactions between the large-scale climate change and the regional topography and land-water contrasts. These changes substantially alter the temperature and precipitation trends over the region relative to the global model result or statistical downscaling. Warming is significantly amplified, through snow-albedo feedback, in regions where snow cover is lost. Increased onshore flow in the spring reduces the daytime warming along the coast. Precipitation increases in autumn are amplified over topography due to changes in the large-scale circulation and its interaction with the terrain. The robustness of the modeling results is established through comparisons with the observed and simulated seasonal variability and with statistical downscaling results.