What do climate models tell us – and how?

Julie J. Rehmeyer provides an overview to answer the question Can We Trust Climate Models?
(Stats April 24, 2008).

The short answer is that the models are very reliable about some things and not very reliable about others.

How do we know what things are reliable and what aren’t? How do we measure that reliability? How confident can we be about things the models tell us?

Climate scientists have a problem: They can’t do experiments. To perform the experiments they’d like, scientists would need a few million Earths, billions of years, and omnipotence. Then they could pump extra greenhouse gases into the atmosphere of one Earth, prod volcanoes into mad eruptions on another, summon up sunspots to stream extra radiation to the third. They could stop the oceans from circulating, cover the sky with clouds, melt the polar ice. Then they’d sit back and watch what happened, deducing from the consequences how climate works.

What can be done is to play with simulations. These take a set of conditions, squash and manipulate them in ways that reflect the operation of the laws of thermal dynamics, fluid mechanics, and other fields, and then see what happens.

The original goal wasn’t to predict climate change … The goal instead was to understand how the different aspects of climate interrelate. How does temperature affect precipitation? How do changes in ocean currents impact storms? Modelers hoped that understanding these dynamics would also help them predict large-scale climate events like El Niños, which occur every few years and affect weather around the world.

Over the last several decades, the models have grown into fantastically complex creations, built by hundreds of scientists working in parallel. By the mid-1990s, scientists were able to produce climate simulations that looked similar to the climate we actually experience, and they’ve continued to improve rapidly since then.

The complexity is due to increased understanding of mechanisms that influence weather and climate and to a more realistic picture of the starting conditions. What if ‘games’ are played to experiment with the model. See what happens when the number for atmospheric carbon dioxide is moved up and down and how the model says the climate will respond. Compare that to what can be observed. Look at a lot of things and figure out which starting conditions cause the most difference at the other end of the model.

A key part of all of this is to gain some information about much slop there is in the system. What can cause errors and how big might these errors be?

The models aren’t capable of serving as crystal balls, telling us our climate future; nevertheless, scientists are able to use the models as a tool to help them get a reasonable sense of how climate is likely to change, and how big a difference action now may make in the future.

A “reasonable sense” is the tough part.

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