Primary Convener:
Tiffany Shaw, The University of Chicago

Convener:
Isla Simpson, National Center for Atmospheric Research
Robert Wills, ETH Zurich
Stephen Po-Chedley, Lawrence Livermore National Laboratory

Chair:
Tiffany Shaw, The University of Chicago
Isla Simpson, National Center for Atmospheric Research
Robert Wills, ETH Zurich
Stephen Po-Chedley, Lawrence Livermore National Laboratory

Anthropogenically forced climate change signals are emerging from the noise of internal variability in observations, and the impacts on society are growing. For decades, Climate or Earth System Models have been predicting how these climate change signals will unfold. The climate science community is now in a position to confront the signals, as represented by historical trends, in models with observations. We welcome contributions that take stock of the ability of models to capture recent trends across all Earth system components. Contributions highlighting successes and discrepancies, robust procedures for confronting observed and modeled trends, moving beyond quantification into understanding the origins of historical trends in the observational record and/or models, and cutting-edge methods (e.g. Machine Learning, kilometer scale models, hindcasts) for identifying sources of discrepancies and separating forced signals from internal variability are all welcome.

Index Terms
3305 Climate change and variability
1616 Climate variability
1620 Climate dynamics
1626 Global climate models

Cross-Listed:
C - Cryosphere
A - Atmospheric Sciences
H - Hydrology
OS - Ocean Sciences

Co-Organized Sessions:
Atmospheric Sciences

Neighborhoods:
3. Earth Covering