Novel implementations of observational constraints for understanding past and future climate change in Canada and the world

Observational constraints are widely used to reduce uncertainty in multi-model climate projections and have been proven to be effective in reducing the uncertainty of projected future change and in estimates of some key climate system parameters. In this talk, we will describe an approach that uses available observations to constrain both past changes and future projections. We investigate the use of observations to constrain future global warming and both past and future temperatures in Canada.

The global mean surface temperature (GMST) datasets that are widely used to estimate global warming are generally available from 1850 to the present. We found that using annual GMST data that incorporates the full transition from a quasi-equilibrium pre-industrial state to the recent strong transient response results in a better constraint on future global warming than other approaches that use more limited parts of this record. In particular, using a simple linear warming trend from recent decades, as in many studies, improves upon unconstrained projections but to a lesser extent than using the full GMST time series. By varying the observational endpoints, we found an effective constraint only becomes possible when data from the recent period of rapid transient climate change are included in the analysis.

In contrast to GMST, reliable gridded surface air temperature data with national coverage for Canada is only available from 1948 onwards. Thus, to estimate historical and projected future warming in Canada relative to the 1850-1900 preindustrial period requires constrained estimates of both past and future temperatures. We develop an approach that uses annual mean temperatures in six regions covering Canada to provide constrained estimates of the historical warming in Canada induced by external forcings since the preindustrial period and the additional future warming that we are apt to experience in the rest of this century under different emission scenarios.

Bio
Dr. Tong Li is a Post-doctoral Scientist in the Pacific Climate Impacts Consortium (PCIC) at the University of Victoria. Before coming to Canada, she earned her Ph.D. from the Nanjing University of Information Science and Technology, which is an internationally recognized meteorological research and training institute. Her research focuses on global and regional climate change, detection and attribution, and future projections. Currently, she is working on exploring the implementation of observational constraint techniques to improve estimation accuracy, as well as integrating historical climate change with future projections within a unified statistical framework to better understand the onging changes in our climate — the focus of today’s talk.

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