Model assessment of regional surface temperature trends (1949-1997)

Analyses are conducted to assess whether simulated trends in SST and land surface air temperature from two versions of a coupled ocean-atmosphere model are consistent with the geographical distribution of observed trends over the period 1949-1997. The simulated trends are derived from model experiments with both constant and time-varying radiative forcing. The models analyzed are low-resolution (R15, similar to 4 degrees) and medium-resolution (R30, similar to 2 degrees) versions of the Geophysical Fluid Dynamics Laboratory (GFDL) coupled climate model. Internal climate variability is estimated from long control integrations of the models with no change of external forcing. The radiatively forced trends are based on ensembles of integrations using estimated past concentrations of greenhouse gases and direct effects of anthropogenic sulfate aerosols (G+S). For the regional assessment, the observed trends at each grid point with adequate temporal coverage during 1949-1997 are first compared with the R15 and R30 model unforced internal variability Nearly 50% of the analyzed areas have observed warming trends exceeding the 95th percentile of trends from the control simulations. These results suggest that regional warming trends over much of the globe during 1949-1997 are very unlikely to have occurred due to internal climate variability alone and suggest a role for a sustained positive thermal forcing such as increasing greenhouse gases. The observed trends are then compared with the trend distributions obtained by combining the ensemble mean G+S forced trends with the internal variability "trend" distributions from the control runs. Better agreement is found between the ensemble mean G+S trends and the observed trends than between the model internal variability alone and the observed trends. However, the G+S trends are still significantly different from the observed trends over about 30% of the areas analyzed. Reasons for these regional inconsistencies between the simulated and the observed trends include possible deficiencies in (1) specified radiative forcings, (2) simulated responses to specified radiative forcings, (3) simulation of internal climate variability, or (4) observed temperature records.