Global Climate Models and Simulating the Arctic: How do They Perform in the Cold?
Svensson, G. and Karlsson, J. 2012. On the arctic wintertime climate in global climate models. Journal of Climate 24: 5757-5771.
Specifically, the authors used several General Circulation Models (GCMs) of various horizontal and vertical resolutions to examine the climate of the Arctic, defined as the region north of the Arctic Circle (66.6° N), in order to model the winter months during the period 1980-1999. This corresponded to limited observational data sets that were available during that time period. The observations used were the European Centre for Long Range Forecasting (ECMWF) ERA re-analyses. But, as the authors note, "one should be cautious to interpret the data as 'truth' in this remote region. However, the abundance of observations at lower latitudes [in the arctic] and sea ice extent should at least constrain the properties of the air masses that enter and exit the Arctic." Much of the observational data in this region is augmented with satellite observations.
Some of the more interesting results showed that the winter sea ice cover was similar among the models and observations across much of the Arctic Ocean. However, there were some differences at the margins and in the North Atlantic, and the result is that most of the models produce too much sea ice. In validating other quantities, it was found that the models tend to underestimate the long wave energy being radiated into space, some by as much as 10%. In terms of wintertime mean cloudiness, the models generate winter season values between 35 to 95%, whereas observations show there were values ranging from 68% to 82%, which is a smaller range. But, near the surface, the latent and sensible heat fluxes within the arctic were consistent with observations.
An examination of vertical profiles (Fig. 1) showed that the models were generally cooler in the lower troposphere and a little more humid. This led to wide differences between the characteristics of air masses in each of the models. Also all models showed stronger gradients in temperature and humidity than observed in the lower troposphere which results in lower clear-sky radiation than observations. One possible explanation was that many of the models were less "active" in terms of synoptic weather patterns in this region. From these findings, the authors inferred that the humidity was more important contributor in the arctic to the radiation budgets. This leads to the conclusion that it is important to know that the models are simulating temperature and moisture profiles correctly in this region of the world.
Figure 1. Adapted from Svensson and Karlsson (2012) their Fig. 8. The median vertical profiles for temperature (K), specific humidity (g kg-1), and relative humidity over (a)-(c) entire Arctic, (d)-(f) open ocean, and (g)-(i) sea ice from the GCMs and ERA-Interim over the southernmost latitude band 66.6°-70°N.
In conclusion, although models are generally improving in representing the Earth's climate, there are still areas of the planet where a lack of observations makes modeling the atmosphere a difficult task. However, as the authors of the present paper concede, the converse is also true. The lack of observations can also mean that model validation is difficult to determine in a given region as well. Thus, caution needs to be taken when examining future climate scenarios of the Artic, and how it might impact the mid-latitudes. As has been stated when critiquing other studies, we need to have confidence in a model's ability to capture the current climate before we can have confidence in using future climate scenarios to make decisions and/or policy.