A kriging approach to the analysis of climate model experiments

A climate model is a computer implementation of a mathematical model for the physical, chemical and biological processes underlying the climate. An immediate use of a climate model is in performing climate model experiments, where uncertain input quantities, such as greenhouse gas and aerosol concentrations, are systematically varied to gain insight into their effects on the climate system. Climate models are computationally intensive, allowing only small experiments. We present a multidimensional kriging method to predict climate model variables at new inputs, based on the experimental data available. The method is particularly suitable for situations in which the climate model data sets share a common pattern across the input space, such as surface temperatures that are lower at the Poles, higher at the Equator, and increasing over time. The results demonstrate the potential of our kriging method as an exploratory tool in climate science.

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