Uncertainty Quantification of Regional Climate Change Based on Structural Uncertainty in Atmospheric GCMs
We examine the uncertainty in teleconnection response of multiple versions of the NCAR/DOE Community Atmospheric Model (CAM) and the GFDLAM2. We analyze the sensitivity of local changes in climate by estimating the linear operator that relates regional climate change to SST anomaly patterns in the tropics and extra-tropics. This linear method provides Global Teleconnection Operators (GTOs) for each model. When combined with historical SST anomaly patterns, we can test the method by estimating the impact of SST changes on the changes in regional climates compared to the response as simulated by the full non-linear model. (see Li, Forest, and Barsugli, 2012, JGR) The long-term goals of the project are twofold. First, we want to understand the impacts of structural differences in the climate models on the large-scale atmospheric dynamics contributing to the regional changes. Second, using the GTO, we want to understand the component of regional climate variability being driven by patterns of SST variability. Regarding structural uncertainty, these can relate to model physics parameterizations, to resolution, or to dynamical cores. In total, we have estimated the GTO for CAM3.1, CAM3.5, CAM4, CAM5, and GFDLAM2 for resolutions including T31, T42, T85, FV1.9x2.5, FV0.9x1.25, and HOMME_N96. Given the limits of internal variability for detecting changes, we are able to identify the model physics and resolution as the significant uncertainties. We have applied the GTO approach to understanding three specific regional prediction problems for seasonal climate. First, we have explored the sensitivity of dust emissions and deposition to SST anomaly patterns and identified the seasonal climate change influence on the dust cycle. Second, we have estimated the GTO for 12 major river basins to estimate the teleconnection response impacting regional water resources. Most of these rivers are in the tropical regions where teleconnections are strong. Third, we have applied the GTO method to understanding variability in the North Atlantic Oscillation and Pacific-North America patterns. The GTO approach can capture the decadal scale variability in each pattern and identify the relative importance of both the tropical Pacific and Indian Oceans. In future work, we will be examining the dependence of the GTO structure on equilibrium climate sensitivity (ECS) in versions of the CAM4 and CAM5 using the cloud feedback adjustment approach (Monier and Sokolov, 2012). We identify a strong dependence of the teleconnection response to SST anomalies in the NINO3.4 region for ECS values of 1K, 3K, and 5K.