Chapter 17 - GEM-SA: The Gaussian Emulation Machine for Sensitivity Analysis

Abstract

Computer simulation models are widely used in the study of real-world processes, and those that are associated with Earth observation (EO) are increasingly complex. To correctly integrate these models with observation data, it is important to understand the relative importance of individual parameters. For example, identifying the key driving parameters could dramatically reduce the costs and efforts in terms of data acquisition. The freely available software tool Gaussian Emulation for Sensitivity Analysis (GEM-SA) is designed to handle complex models and efficiently explore large parameter spaces, without requiring many thousands of simulation runs. This chapter provides an overview of GEM-SA functionalities for employing sensitivity analysis, and the practical use of the tool is illustrated using the SimSphere land biosphere model, which is a model that is used synergistically with EO data for deriving spatiotemporal estimates of key parameters characterizing Earth's water cycle. In this example, it is shown how using only 400 model simulation runs, the most important model inputs can be robustly identified and how each of the main effect relationships can be mapped. Such information can be of key importance to the SimSphere user's community where this model is used either as a stand-Ealone tool or synergistically with EO data.