A169-01
Emergent Constraints on the Large Scale Atmospheric Circulation and Regional Hydroclimate: Do They Still Work in CMIP6 and How Much Can They Actually Constrain the Future?

Monday, 14 December 2020: 19:00
Virtual
Isla Simpson, National Center for Atmospheric Research, Climate and Global Dynamics Laboratory, Boulder, CO, United States, Karen A McKinnon, University of California Los Angeles, Departments of Statistics, Institute of the Environment and Sustainability, Los Angeles, CA, United States, Flavio Lehner, National Center for Atmospheric Research, Boulder, CO, United States; ETH Swiss Federal Institute of Technology Zurich, Zurich, Switzerland, Frances V Davenport, Stanford University, Stanford, CA, United States, Abdullah al Fahad, George Mason University Fairfax, Department of Atmospheric, Oceanic & Earth Sciences, Fairfax, VA, United States, Di Chen, UCLA, Department of Atmospheric and Oceanic Sciences, Los Angeles, United States and Martin Tingley, Los Gatos, California, CA, United States
Recorded Presentation
Abstract:
Accurate future projections of the climate system are hindered by a number of sources of uncertainty: forcing uncertainty, internal variability, and model structural uncertainty. An emergent constraint (EC) is a statistical relationship, across a model ensemble, between an aspect of the present day climate (the predictor) and an aspect of future projected climate change (the predictand). If such a relationship is robust and understood, it may provide constrained projections for the real world.

Here, the Coupled Model Intercomparison Project 6 (CMIP6) will be used to revisit several previously proposed ECs with two aims: (1) to assess whether these ECs survive the partial out-of-sample test of CMIP6 and (2) to more rigorously quantify the constrained projected change than previous studies. To achieve the latter, a method is proposed whereby uncertainties can be appropriately accounted for, including the influence of internal variability, uncertainty on the linear relationship, and the uncertainty associated with model structural differences, aside from those described by the EC. In addition, a Bayesian hierarchical model and least squares regression approaches will be compared.

Three ECs will be assessed: (a) the relationship between Southern Hemisphere jet latitude and projected jet shift; (b) the relationship between stationary wave amplitude in the Pacific-North American sector and meridional wind changes over North America (with extensions to hydroclimate); and (c) the relationship between ENSO teleconnections to California and California precipitation change. Constraint (a) is robust and provides a quantitatively useful constraint on future projections. Constraint (b) is also found to be robust, but there is enough improvement in the predictor in CMIP6 that it no longer substantially constrains projected change in either the circulation or hydroclimate. Constraint (c) does not appear to be robust when using historical ENSO teleconnections as the predictor.

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