Analysis and quantification of uncertainty in climate adaptation products for the southwestern US

Outputs from current generation General Circulation Models (GCMs) are being downscaled to produce primary adaptation products used to investigate the utility of such products for aiding end-user decisions on enduring public and private infrastructure, short and long-term policy alternatives, and evaluating risks from extreme events. Effective decision support products carry representations of both objective and subjective uncertainty through to the end-user, allowing them to appropriately weigh climate change factors in with myriad other relevant elements of their decisions. To that end, our methodology compares GCMs and their corresponding downscales with relevant objective historical measurements, systematically evaluates these products with respect to common baseline datasets, and then applies statistical bias correction and uncertainty analysis to establish objective confidence intervals. Our results show a four way comparison of point-records of conventional surface reports derived from Automated Surface Observing System (ASOS) stations in central Colorado and National Center for Environmental Prediction (NCEP) Reanalysis constrained reference downscales with European Center/Hamburg Model (ECHAM5) GCM constrained Weather Research and Forecasting (WRF) runs for a parallel current period of 1999-2009, and a future period for 2029-2039. Modest climate change in this relatively near-term future period is evident in derived end-user products such as Heating and Cooling Degree-Days (HDD and CDD) and associated confidence intervals distinguishing interannual within-model variability from statistically significant between-periods climate change signal.