GC44A-08
Trend of climate extremes in North America: A comparison between dynamically downscaled CMIP3 and CMIP5 simulations

Thursday, 17 December 2015: 17:45
3012 (Moscone West)
Hsin-I Chang1, Christopher L Castro1, Linda O Mearns2 and Melissa S Bukovsky2, (1)University of Arizona, Tucson, AZ, United States, (2)National Center for Atmospheric Research, Boulder, CO, United States
Abstract:
Ascertaining the impact of anthropogenically-influenced climate change on climate extremes is of high priority for civil infrastructure and water resource planning. The current future projections based on IPCC models, for example as documented in the recent Climate Change Assessment for the Southwest, indicate a declining trend in precipitation with a warming climate, with associated dramatic reductions in streamflow in the Colorado River basin. However, inconsistent precipitation trends are projected by individual IPCC global climate models (i.e. Sheffield et al. 2013, Bukovsky et al., 2013). The North American Monsoon interannual variability is partly controlled by warm season atmospheric teleconnections emanating from the western tropical Pacific, related to the El Niño Southern Oscillation (ENSO) and Pacific Decadal Variability (PDV). Departure from the ensemble mean approach for long-term climate projection analysis, a physics-based methodology is designed to analyze the relationship between climate extremes and the large scale forcing (Chang et al. 2015). Analysis from the observational record and downscaled CMIP3 regional climate runs has shown intensifying warm season precipitation and temperature extremes following the natural variability of large scale forcing.

We will utilize the ongoing community effort in dynamically downscaling the CMIP5 climate projection datasets, part of the North American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX), and compare with the previous generation of CMIP3 downscaled products for future climate assessment. We aim to examine the difference in large scale forcing from different generations of the CMIP models, and the related impact on regional scale climate extreme characteristics.