Coaura

15 MAY 2002

GIORGI AND MEARNS

1141

Calculation of Average, Uncertainty Range, and Reliability of Regional Climate Changes from AOGCM Simulations via the ‘‘Reliability Ensemble Averaging’’ (REA) Method
FILIPPO GIORGI
Abdus Salam International Centre for Theoretical Physics, Trieste, Italy

LINDA O. MEARNS
NCAR, Boulder, Colorado (Manuscript received 21 May 2001, in final form 6November 2001) ABSTRACT The ‘‘reliability ensemble averaging’’ (REA) method for calculating average, uncertainty range, and a measure of reliability of simulated climate changes at the subcontinental scale from ensembles of different atmosphere– ocean general circulation model (AOGCM) simulations is introduced. The method takes into account two ‘‘reliability criteria’’: the performance of the model inreproducing present-day climate (‘‘model performance’’ criterion) and the convergence of the simulated changes across models (‘‘model convergence’’ criterion). The REA method is applied to mean seasonal temperature and precipitation changes for the late decades of the twenty-first century, over 22 land regions of the world, as simulated by a recent set of nine AOGCM experiments for two anthropogenicemission scenarios (the A2 and B2 scenarios of the Intergovernmental Panel for Climate Change). In the A2 scenario the REA average regional temperature changes vary between about 2 and 7 K across regions and they are all outside the estimated natural variability. The uncertainty range around the REA average change as measured by the REA root-mean-square difference (rmsd) varies between 1 and 4 Kacross regions and the reliability is mostly between 0.2 and 0.8 (on a scale from 0 to 1). For precipitation, about half of the regional REA average changes, both positive and negative, are outside the estimated natural variability and they vary between about 25% and 30% (in units of percent of present-day precipitation). The uncertainty range around these changes ( rmsd) varies mostly betweenabout 10% and 30% and the corresponding reliability varies widely across regions. The simulated changes for the B2 scenario show a high level of coherency with those for the A2 scenario. Compared to simpler approaches, the REA method allows a reduction of the uncertainty range in the simulated changes by minimizing the influence of ‘‘outlier’’ or poorly performing models. The method also produces aquantitative measure of reliability that shows that both criteria need to be met by the simulations in order to increase the overall reliability of the simulated changes.

1. Introduction Projections of climatic changes for the twenty-first century at the broad regional, or subcontinental, spatial scale (10 6–10 7 km 2 ) are based on transient simulations with coupled atmosphere–ocean generalcirculation models (AOGCMs) including relevant anthropogenic forcings, for example, due to greenhouse gases (GHG) and atmospheric aerosols (e.g., Kattenberg et al. 1996). To date, such projections have been characterized by a low level of confidence and a high level of uncertainty deriving from different sources (Visser et al. 2000; Giorgi and Francisco 2000b): estimates of future anthropogenicforcings, the response of a climate model to a
Corresponding author address: Dr. Filippo Giorgi, Abdus Salam International Centre for Theoretical Physics, P.O. Box 586, Trieste 34100, Italy. E-mail: giorgi@ictp.trieste.it

given forcing, the natural variability of the climate system. Quantifying uncertainties in the projection of future climate scenarios used for impact assessments has been identifiedas a critical research need both in the climate and impacts research communities (e.g., Carter et al. 1999; Mearns et al. 2001), and has inspired a recent flurry of research (e.g., Jones 2000a,b; New and Hulme 2000; Katz 2001). One of the primary factors of uncertainty is that different AOGCMs can simulate quite different regional changes even under the same anthropogenic forcing scenario (e.g.,...