Climate FAQs: Climate Model Shortcomings

What are the shortcomings of climate models?

The best climate models encapsulate the current understanding of the physical processes involved in the climate system, the interactions, and the performance of the system as a whole. They have been extensively tested and evaluated using observations. They are exceedingly useful tools for carrying out numerical climate experiments, but they are not perfect, and some models are better than others. Uncertainties arise from shortcomings in our understanding of climate processes operating in the atmosphere, ocean, land and cryosphere, and how to best represent those processes in models. Yet, in spite of these uncertainties, today's best climate models are now able to reproduce the climate of the past century, and simulations of the evolution of global surface temperature over the past millennium are consistent with paleoclimate reconstructions. This gives increased confidence in future projections. The shortcomings in our understanding of the processes involved in climate and how they are depicted in models arise from inadequate observations and theoretical underpinnings associated with the incredible complexity of dealing with scales from molecules and cloud droplets to the planetary-scale atmospheric circulation. These issues are addressed in several steps:

  • Individual climate processes are dealt with as best as is possible given the understanding and computational limitations.
  • The processes are assembled in models and then the model components are tested with strong constraints. The components include modules of the atmosphere, the oceans, the land and sea ice, and the land surface. These modules are coupled together to mimic the real world.
  • The climate system model as a whole is then integrated in an unconstrained mode and thoroughly tested against observations.

One strong test is to simulate the annual cycle of seasonal variations (the changes in climate from winter to summer). Another is to simulate observed variability from one year to the next. Yet another is to simulate past climate, even going back in time thousands or millions of years tested against records from ice cores, tree rings, and other "proxy" data.

As our knowledge of the different components of the climate system and their interactions increases, so does the complexity of today's climate models. Also, many of the most pressing scientific questions regarding the climate system and its response to natural and anthropogenic forcings cannot be readily addressed with traditional models of the physical climate. One of the open issues for near-term climate change, for example, is the response of terrestrial ecosystems to increased concentrations of carbon dioxide. Will plants begin releasing carbon dioxide to the atmosphere in a warmer climate, thereby acting as a positive feedback, or will vegetation absorb more carbon dioxide and hence decelerate global warming? Related issues include the interactions among land use change, deforestation by biomass burning, emission of greenhouse gases and aerosols, weathering of rocks, carbon in soils, and marine biogeochemistry.

Exploration of these questions requires a comprehensive treatment of the integrative Earth system. In order to address these emerging issues, physical models are being extended to include the interactions of climate with biogeochemistry, atmospheric chemistry, ecosystems, glaciers and ice sheets, and anthropogenic environmental change. These new "Earth System Models", however, will require large investments in computing infrastructure before they can be fully utilized.