Mathematical Geophysics Meeting Report

Toward Improving Decadal Climate Predictions

Aspen Global Change Institute Workshop on Decadal Climate Predictions: Improving Our Understanding of Processes and Mechanisms to Make Better Predictions; Aspen, Colorado, 7–12 June 2015

By , Gerald A. Meehl, and Doug M. Smith

The new field of decadal climate prediction has the potential to provide time-evolving regional climate information on timescales of 1–10 years. To improve decadal climate predictions, the climate science community must learn more about the processes and mechanisms controlling decadal timescale variability. Scientists met in June in Aspen, Colo., to finalize a set of coordinated experiments designed to advance research in this emerging field.

Workshop participants considered two central questions:

  • What are the relative contributions of internally generated variability and of external forcing to the observed climate record?
  • How can researchers understand and model the climate processes and mechanisms that will increase the accuracy of near-term regional climate predictions using models initialized with observations?

The group also focused on several specific questions:

  • Can periods of accelerated and retarded global warming be attributed to basin-wide ocean variations? What are the respective roles of the eastern tropical Pacific and the North Atlantic?
  • To what extent do Atlantic Multidecadal Variability (AMV) and Interdecadal Pacific Variability (IPV) and the associated teleconnections determine decadal climate anomalies observed at regional scales?
  • Can the interplay on decadal timescales between the Pacific and Atlantic basins be assessed? Can AMV events be a precursor of IPV shifts and vice versa, and what are the mechanisms involved?
  • What role do volcanic eruptions play in decadal timescale climate variability?
The warm-phase spatial patterns of (top) Atlantic Multidecadal Variability (AMV) and (bottom) Interdecadal Pacific Variability (IPV). AMV results are the regression pattern of monthly sea temperatures on the AMV index, and IPV results are the regression pattern for the IPV index. The color scale units are degrees Celsius per standard deviation of the respective index. Credit: (top) Giorgiogp2; (bottom) Giorgiogp2, CC BY-SA 3.0
The warm-phase spatial patterns of (top) Atlantic Multidecadal Variability (AMV) and (bottom) Interdecadal Pacific Variability (IPV). AMV results are the regression pattern of monthly sea temperatures on the AMV index, and IPV results are the regression pattern for the IPV index. The color scale units are degrees Celsius per standard deviation of the respective index. Credit: (top) Giorgiogp2; (bottom) Giorgiogp2, CC BY-SA 3.0

The mechanisms involved in AMV and IPV decadal variability (also referred to as the Atlantic Multidecadal Oscillation and the Pacific Decadal Oscillation, respectively) are still not fully understood. Participants proposed a sequence of experiments in which observed sea surface temperature anomalies are introduced into coupled models in the tropical eastern Pacific to assess the response of the rest of the climate system to these changes. In a second experiment, observed sea surface temperature anomalies are specified in the North Atlantic in order to study the response of the climate system. Preliminary results indicate that it is particularly critical to treat the tropical Atlantic and tropical eastern Pacific accurately in climate models in order to improve decadal prediction skill.

A second set of experiments was proposed to address the role of volcanic eruptions. In these experiments models include observed aerosols from the three major volcanic eruptions since 1960 (Agung, 1963; El Chichón, 1982; and Pinatubo, 1991) in retrospective decadal predictions (called hindcasts) and then exclude the aerosols in sets of hindcasts and forecasts to assess the effects on decadal prediction skill.

The results of these coordinated experiments, performed by an international group of climate modeling centers, will provide a wealth of information that is expected to improve understanding of climate system variation on decadal timescales and to improve scientists’ ability to predict their evolution.

We acknowledge the contributions of the workshop’s 32 participants and sponsors: NASA, the National Oceanic and Atmospheric Administration, the National Science Foundation, and the World Climate Research Programme.

—George J. Boer, Canadian Centre for Climate Modelling and Analysis, Environment Canada, Victoria, B.C.; email: [email protected]; Gerald A. Meehl, Climate and Global Dynamics Division and Advanced Study Program, National Center for Atmospheric Research, Boulder, Colo.; and Doug M. Smith, Met Office, Hadley Centre for Climate Science and Services, Exeter, U.K.

Citation: Boer, G. J., G. A. Meehl, and D. M. Smith (2015), Toward improving decadal climate predictions, Eos, 96, doi:10.1029/2015EO041555. Published on 21 December 2015.

© 2015. The authors. CC BY 3.0