Physics
Scientific paper
Oct 2002
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2002georl..29t..31g&link_type=abstract
Geophysical Research Letters, Volume 29, Issue 20, pp. 31-1, CiteID 1970, DOI 10.1029/2002GL015836
Physics
27
Global Change: Atmosphere (0315, 0325), Global Change: Instruments And Techniques, Meteorology And Atmospheric Dynamics: Numerical Modeling And Data Assimilation
Scientific paper
Averaging results from multiple models has previously been found to improve estimates of the climatology and seasonal predictions of atmospheric variables. Here we describe how a multi-model mean of the simulated response to greenhouse gas and sulphate aerosol changes may be used to detect anthropogenic influence on surface temperature. The scaling factor on a combined greenhouse gas and sulphate aerosol response pattern is estimated using a five model ensemble, and is found to be similar to that estimated using individual models, with similar uncertainties. When applied to the simultaneous detection of separate greenhouse gas and sulphate aerosol responses, the multi-model method indicates a closer consistency between the observations and simulated responses, with reduced uncertainties. This improvement is at least in part due to the larger ensemble sizes and increased length of control integration available when data from multiple models are combined.
Allen Meghan Rose
Gillett Nathan P.
Hegerl Gabriele C.
Stott Peter A.
Weaver Andrew J.
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