ABSTRACT

Climate change detection and attribution refers to a set of statistical tools to relate observed changes to external forcings, specifically to anthropogenic influences. While this issue can be viewed in different ways, the most commonly applied framework is linear regression. The goal of climate-change detection and attribution methods is to differentiate if observed changes in variables quantifying weather are consistent with processes internal to the climate system or are evidence for a change in climate due to so-called external forcings. External forcings are often categorized into natural and anthropogenic forcings, where solar and volcanic activity are examples of natural forcings and increased greenhouse gas emissions and land use change are examples of anthropogenic forcings. Climate-change detection and attribution methods have been developed by a variety of groups in the climate science and, to a lesser degree, in the statistics community and notations have varied accordingly. This chapter applies the notation used in the corresponding original literature.