Global Climate Model Performance over Alaska and Greenland

Abstract

The performance of a set of 15 global climate models used in the Coupled Model Intercomparison Project is evaluated for Alaska and Greenland, and compared with the performance over broader pan-Arctic and Northern Hemisphere extratropical domains. Root-mean-square errors relative to the 1958–2000 climatology of the 40-yr ECMWF Re-Analysis (ERA-40) are summed over the seasonal cycles of three variables: surface air temperature, precipitation, and sea level pressure. The specific models that perform best over the larger domains tend to be the ones that perform best over Alaska and Greenland. The rankings of the models are largely unchanged when the bias of each model’s climatological annual mean is removed prior to the error calculation for the individual models. The annual mean biases typically account for about half of the models’ root-mean-square errors. However, the root-mean-square errors of the models are generally much larger than the biases of the composite output, indicating that the systematic errors differ considerably among the models. There is a tendency for the models with smaller errors to simulate a larger greenhouse warming over the Arctic, as well as larger increases of Arctic precipitation and decreases of Arctic sea level pressure, when greenhouse gas concentrations are increased. Because several models have substantially smaller systematic errors than the other models, the differences in greenhouse projections imply that the choice of a subset of models may offer a viable approach to narrowing the uncertainty and obtaining more robust estimates of future climate change in regions such as Alaska, Greenland, and the broader Arctic.

Inter-Model Differences of Future Precipitation Changes in CMIP3 and MIROC5 Climate Models

“…As in previous studies (Walsh et al 2008;Smith and Chandler 2010), our results show that models with better reproducibility in the present-day precipitation predict a more consistent change over the tropics (30 S-30 N). As argued by Knutti (2010), this is helpful information for decreasing the spread of future changes.…”

“…Evaluating the credibility of future projections is becoming an increasingly important issue. Some studies constrain projections using observations, suggesting that the models performing well in a present-day climate predict more converged future changes (Walsh et al 2008;Smith and Chandler 2010;Shiogama et al 2011). Abe et al (2009) show that the similarities observed in the precipitation distribution among the models in the present-day climate is significantly correlated with the similarities observed in the projected precipitation change over the tropics (15 S-15 N).…”

Thresholds for boreal biome transitions

“…Change will also differ depending on the local trends in climate. Although trees in continental parts of the southern border of boreal forest may experience increased drought stress, precipitation will likely increase in more maritime southern boreal zones (e.g., in Scandinavia or Labrador) (37), perhaps leading to an expansion of forest (38,39). The scenarios of change are perhaps most difficult to infer at the northern end of the boreal range.…”

Exploration of parametric uncertainty in a surface mass balance model applied to the Greenland ice sheet

“…The CMIP3 ensemble is often used to quantify climate uncertainty, and based on the assumption that this ensemble would be used for future sensitivity analysis, it is reasonable to use a model that represents the ensemble mean. HadCM3 has also been shown to be one of the best performers when compared against absolute and bias corrected observations of surface parameters [Franco et al, 2011;Walsh et al, 2008].…”