Testing Climate Models: An Approach

The scientific merit of decadal climate projections can only be established by means of comparisons with observations. Testing of models that are used to predict climate change is of such importance that no single approach will provide the necessary basis to analyze systematic errors and to withstand critical analysis. Appropriate observing systems must be relevant, global, precise, and calibratable against absolute standards. This paper describes two systems that satisfy these criteria: spectrometers that can measure thermal brightness temperatures with an absolute accuracy of 0.1 K and a spectral resolution of 1 cm−1 , and radio occultation measurements of refractivity using satellites of the GPS positioning system, which give data of similar accuracy. Comparison between observations and model predictions requires an array of carefully posed tests. There are at least two ways in which either of these data systems can be used to provide strict, objective tests of climate models. The first looks for the emergence from the natural variability of a predicted climate “fingerprint” in data taken on different occasions. The second involves the use of high-order statistics to test those interactions that drive the climate system toward a steady state. A correct representation of these interactions is essential for a credible climate model. A set of climate model tests is presented based upon these observational and theoretical ideas. It is an approach that emphasizes accuracy, exposes systematic errors, and is focused and of low cost. It offers a realistic hope for resolving some of the contentious arguments about global change.