Some Better Climate Models
Climate models may be the part of the science that most people know the least about. Be very clear — scientists do not tell their computers to produce global warming, and then get excited when global warming comes out of the computer!
The simplest climate model we just discussed shows you a tiny bit of what goes into a real climate model. The starting point is physics. This includes the rules that mass and energy are not created or destroyed but just changed around. The physics also includes interactions between mass and energy — how much energy is needed to evaporate an inch of water per week, for example, or to warm the atmosphere by a degree. Interactions of radiation and greenhouse gases are specified from the fundamental physics worked out by the US Air Force after World War II, and other such studies.
The model also must “know” about the Earth-how much sunshine we get, how big the planet is and how fast it rotates, where the land and oceans are, how much air we have and what it is made of. (Climate models are applied to other planets, and very clearly give different answers because of the differences between the planets.)
All of this information is written down in equations, translated into computer language, and then the computer is turned on. What happens next is remarkable — the computer simulates a climate that looks like the real one. Air rises and rains in the tropics, then sinks and dries over the Sahara and Kalahari. Storms scream out of the west riding the jet stream, and snow grows and shrinks with the seasons across the high-latitude lands.
The model will not be perfect, of course. Suppose you are interested in wind speed. You know from personal experience that you can hide behind a windbreak for relief on a windy day. A forest can serve as a windbreak, giving weaker winds than on a prairie. So, the model must be “told” about the distribution of forests and grasslands (or else must calculate where they grow), and about the “roughness” of the forest and the grass. Scientists have conducted studies on the effects of forests and grasslands on winds, but all studies include some uncertainty. So, the modelers know that the surface roughness in this region must be about this much, but could be a little less or a little more within the range allowed by the data.
The modeler (or more typically, the modeling team) can now “tune” the model. If the winds in the model are a little stronger in some places than in the real world, the modeler may increase the roughness a little, although without going outside the uncertainties. To avoid any biases, different groups in different countries with different funding sources build different models, and tune them in different ways; when all of them agree closely, it is evident that the tuning hasn’t controlled the answer.
Some of the models are used for weather forecasting and for climate studies, and work fine for both. There are differences between weather and climate (see Weather Forecasts End, But Climate Forecasts Continue) - many climate models are simulating changes in vegetation, for example, but if you’re worried about the weather for next week, you don’t really care whether global warming endangers the Amazonian rainforest over the coming decades.
As a general rule, in talking to the public or policymakers, climate modelers rely especially on those results that:
- are exhibited by a range of models from simple to complex run by different scientific groups;
- are understood based on the physics;
- are observed in the history of climate; and
- are confirmed by recent instrumental observations.