final_program_abstracts[1]

11 IMSC Session Program
Probabilistic surface air temperature predictions: comparing
global climate models with nonlinear time series models
Thursday - Parallel Session 6
Siddharth Arora 1,3 , Max A. Little 2 and Patrick E. McSharry 1,3
1 Department of Mathematics, University of Oxford, Oxford, UK
2 Department of Physics, University of Oxford, Oxford, UK
3 Smith School of Enterprise and the Environment, Oxford, UK
Climate variability can be attributed to either internal dynamics or external forcing.
Internal dynamics are the unforced natural changes in our environment, such as the El
Nino cycles or anomalies of ocean heat content, which usually account for short-term
regional changes in the climate [1]. External forcing caused by human activity, such
as increasing CO2 emissions, account for recent global climatic changes [2]. Long
term projections for global climatic change are undertaken using Global Climate
Models (GCMs). Government policy and decision-making in the private sector over
the coming decades relies heavily on accurate long term projections of surface air
temperatures. As these policies will in turn have a large effect on global climate
change, the need for rigorous evaluation of projections from GCMs is of utmost
importance. The focus of our study is to assess surface air temperature predictions
obtained from the Decadal Climate Prediction System (DePreSys), a dynamical GCM
based on the Hadley Center Coupled Model. We investigate the potential of
parsimonious nonlinear time series models, with only a few parameters, to compete
with the GCM both in terms of point and density forecasts over varying horizons.
Comparisons between GCM projections, appropriate benchmarks, and proposed
nonlinear models is undertaken using different performance scores, including root
mean square error (RMSE), mean absolute error (MAE), and the continuous ranked
probability score (CRPS).
[1] P. A. Stott, S. F. B. Tett, G. S. Jones, M. R. Allen, J. F. B. Mitchell, G. J. Jenkins,
“External Control of 20 th Century Temperature by Natural and Anthropogenic
Forcings”, Science, 2000, 290, 2133 – 2137.
[2] D. M. Smith, S. Cusack, A. W. Colman, C. K. Folland, G. R. Harris and J. M.
Murphy, “Improved Surface Temperature Prediction for the Coming Decade from a
Global Climate Model”, Science, 2007, 317, 796-799.
Abstracts 263