Global Teleconnection Operators

Wednesday 24 May, 2017
Climate Change Research Centre Seminar Room, Level 4 Mathews Building, Kensington Campus, Sydney

Uncertainty in regional climate predictions is a critical component of understanding risks of future climate impacts. Unfortunately,  state of the science Earth System Models fail to show significant skill reproducing climate change at sub-continental and smaller scales (i.e., regional scales) despite their ability detect and attribute climate change at global to continental scales.  Large internal climate variability is one reason for this lack of skill although when forced by historical tropical sea surface temperature (SST) patterns,  atmospheric general circulation models (AGCMs) show reasonable skill at reproducing regional climate change over continents. In this talk, we investigate how multiple AGCMs respond over continents to idealized SST anomaly patterns and define a global teleconnection operator (GTO) as a tool for investigating regional climate sensitivities of individual models. This GTO permits identifying a component of internal climate variability that is forced by SST variablity and also evaluating how AGCMs differ in their idealized regional responses.




Chris E. Forest is Associate Professor of Climate Dynamics in the Department of Meteorology and Atmospheric Science at The Pennsylvania State University.  He is also affiliated wth the Department of Geosciences, an associate in the Earth and Environmental Systems Institute, and associate director for the Network for Sustainable Climate Risk Management. He served as a lead author on the report of the Intergovernmental Panel on Climate Change for the chapter on the evaluation of climate models and on a report for the U.S. Climate Change Science Program examining the estimates of temperature trends in the atmospheric and surface climate data. He was elected to serve on the Electorate Nominating Committee for the Atmospheric and Hydrospheric Sciences Section of the American Association for the Advancement of Science. His research focuses on quantifying uncertainty in climate predictions and their implications for assessing climate risks. He has a B.S. in applied mathematics, engineering, and physics from the University of Wisconsin-Madison and a Ph.D. in meteorology from the Massachusetts Institute of Technology.