The University of Arizona

Modeling at the Global Scale

By Melanie Lenart | The University of Arizona | September 12, 2008

Advances in the past decade have given researchers more confidence in the coupled atmosphere-ocean Global Climate Models (coupled GCMs) used to make projections of future temperature and precipitation:

  • Coupled GCMs have improved with computers and increasing knowledge about climate patterns
  • Ensemble” runs averaging results from multiple models consistently yield better results than individual models
  • Other models are improving our understanding of processes beyond temperature and precipitation

On one hand, it’s good news that people can trust the newer models more than previous versions. On the other hand, it means there’s even more reason to believe projections that the Earth’s average temperature will rise by 4 to 8 degrees Fahrenheit if carbon dioxide levels double compared to preindustrial values.

Coupled GCMs have improved

Several factors have combined to enhance today’s models compared to those of previous decades.1

For one, an increase in computer capacity allows modern models to run at higher spatial resolutions (Figure 1). Many GCMs run at resolutions as fine as 1 degree latitude by 1 degree longitude. This means grid squares average roughly 4,000 square miles—about eight times the size of metropolitan Phoenix—at the equator, and increasingly smaller toward the poles. Some “spectral” models have similar resolutions, but with grids that minimize size discrepancies between the equator and the poles.

Many coupled GCMs also no longer rely on “flux corrections” to resolve problems. Earlier models required corrections of heat, momentum, and other fluxes to keep climate from drifting over virtual time to unrealistic states. Most of the current batch of models can run on their own without these artificial adjustments.

horizontal resolution illustration

Figure 1. The best geographic resolution of global climate models used in the IPCC's Assessment Reports have improved over time. The illustrations above are representative of the most detailed horizontal resolution used for short-term climate simulations. The century-long simulations cited in IPCC Assessment Reports were typically run with the previous generation’s resolution. Vertical resolution in both atmosphere and ocean models is not shown, but has increased comparably with the horizontal resolution. Models used in the 2007 report include approximately thirty vertical levels in representing the atmosphere and ocean.
| Enlarge This Figure |
Credit: Intergovernmental Panel on Climate Change, 2007

More computer power has led to improved understanding of climate processes by speeding up computations, thus allowing for more testing of how modeling equations relate to actual climate data.

The higher resolution and improved understanding, in turn, has allowed for a more sophisticated modeling of climate factors and related parameters. That was the conclusion of a pair of researchers who systematically compared 57 models developed over the decades based on their performance on up to 14 different factors, such as temperature, precipitation, sea surface temperature, winds, specific humidity, the fractions of snow and sea ice, and sea salinity.2

Based on comparisons to climate patterns of the 20th century, coupled GCMs have consistently improved in their ability to capture average seasonal conditions. While there’s no guarantee that future climate will feature the same patterns as those of the historical past, such comparisons remain the best means of assessing a model’s skill.

graph of model ensembles

Figure 2. Multi-model means of surface warming (compared to the 1980–1999 base period) for the SRES scenarios A2 (red), A1B (green) and B1 (blue), shown as continuations of the 20th-century simulation. The latter two scenarios are continued beyond the year 2100 with forcing kept constant. An additional experiment, in which the forcing is kept at the year 2000 level, is also shown (orange). Linear trends from the corresponding control runs have been removed from these time series. Lines show the multi-model means, shading denotes the ±1 standard deviation range. Discontinuities between different periods have no physical meaning and are caused by the fact that the number of models that have run a given scenario is different for each period and scenario (numbers indicated in figure). For the same reason, uncertainty across scenarios should not be interpreted from this figure.
Credit: Intergovernmental Panel on Climate Change, 2007

Ensembles: Better than the sum of its parts

Researchers have found that the average of all available models—sometimes called the ensemble mean—almost always weighs in with more accuracy than any one model (Figure 2). Although the reason for this remains somewhat unclear, the finding recurs consistently through different model generations.

These findings from two assessments of GCM skill, both published in 2008, have given climate scientists renewed confidence in the 2007 projections by the Intergovernmental Panel on Climate Change (IPCC).

The IPCC uses ensemble means when developing its projections of average annual temperature for the globe with doubled carbon dioxide concentrations compared to pre-industrial times, the period before people began burning fossil fuels such as gas, coal, and oil. Carbon dioxide is expected to reach double its pre-industrial value sometime between the middle and end of the century; exactly when this occurs depends on several factors—most notably, whether society takes action to reduce its greenhouse gas emissions.

Incidentally, the current projected 4- to 8-degree temperature range for doubled carbon dioxide has made little advance in precision over the years, despite increasing confidence among scientists in its accuracy. In large part, the wide range relates to uncertainties over the future of clouds and other factors that could dampen or exacerbate global warming.1

Other types of models

The confidence applied to the results of coupled GCMs comes from extensive comparisons with actual climate conditions captured in historic records. Many other kinds of models exist in addition to the coupled GCMs, but few of them have been tested rigorously against historic conditions. Scientists thus have less confidence in their projections than they do in projections from coupled GCMs.

Given their complexity, coupled GCMs are rarely linked directly to models assessing factors beyond the atmosphere’s interaction with oceans, sea ice, and land surfaces over time and space. Scientists employ less complex models when considering the potential impact of climate changes on vegetation dynamics, the carbon cycle, and ocean chemistry.

Earth System Models of Intermediate Complexity, known as EMICs, include many of the same processes simulated in GCMs, but they operate at a coarser resolution than the typical modern GCM.

EMICs also rely more heavily on specified equations—or parameterizations—than GCMs do. While GCMs must resort to parameterizations for some factors, such as thunderstorms and other processes occurring at scales smaller than a grid cell, they derive their results largely based on dynamic processes.

Because the resolution of EMICs falls well below that of modern coupled GCMs, results from the intermediate models apply only at the large scales of the globe or a continent.3To get results down to the scale of a region smaller than a continent, scientists often apply downscaling techniques to coupled GCMs.

References

  1. Bader, D.C., et al. 2008. Climate models: An assessment of strengths and limitations. A Report by the U.S. Climate Change Science Program and the Subcommittee on Global Change Research. Department of Energy, Office of Biological and Environmental Research, Washington, D.C.
  2. Reichler, T. and J. Kim. 2008. How well do coupled models simulate today’s climate? Bulletin for the American Meteorological Society, 89(3): 303-311.
  3. Meehl, G.A., et al. 2007. Global climate projections. In Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M. Tignor and H.L. Miller (eds.)] Cambridge University Press, Cambridge, United Kingdom, and New York, NY, USA.