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Detection and Attribution of climate change over the Western US

PI: G. Bala
Institution: Lawrence Livermore National Laboratory
Additional Investigators: Art Mirin
Abstract:
Detection and attribution of climate change to human causes requires that we demonstrate that the observed changes cannot be accounted for by the natural variability of the climate system. Detection and attribution of climate change has primarily been based on the statistical analysis of global scale quantities such as near surface temperatures, satellite based temperature measurements, height of the tropopause, ocean heat content, sea ice extent, length of the growing season, sea level pressure etc. Recently, some studies have investigated the detection and attribution problem over continental scales. Karoly et al. (2003) made a comparison of index trends in observations and model simulations over North America, and they showed that the temperature changes from 1950 to 1999 were unlikely to be due to natural climate variation alone. No previous study has investigated this problem over sub-continental scales, and our work will fill that void and specifically focus on the western US.

Our project will use the data from the pre-industrial control and historical runs of NCAR CCSM3 and other climate models that are submitted to the IPCC data portal. The proposed detection variables are surface air temperature, precipitation, diurnal temperature range, mean magnitude of the annual cycle in surface air temperature, land sea temperature contrast, and snow depth. The pre-industrial control runs will be used to establish the "natural variability" of the climate system. We will compare the historical ensemble simulations with control simulations and observations of the climate detection variables. The goal is to determine if we can attribute the historical climate change over the western US to our "best estimate" of the historical forcing. It will also investigate if higher resolutions of the climate model, land use change and other local and regional scale forcings such as black carbon are important to detect regional climate change.
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