K?ppen versus the computer: comparing K?ppen-Geiger and multivariate regression tree climate classifications in terms of climate homogeneity

摘要

A global climate classification is defined using a multivariate regression tree (MRT). The MRT algorithm is automated, hierarchical, and rule-based, thus allowing a system of climate classes to be quickly defined and easily interpreted. Climate variables used in the MRT are restricted to those from the K?ppen-Geiger classification system. The result is a set of classes that can be directly compared against those from the traditional system. The two climate classifications are compared at their 5, 13, and 30 class hierarchical levels in terms of climate homogeneity. Results indicate that both perform well in terms of identifying regions of homogeneous temperature variability, although the MRT still generally outperforms the K?ppen-Geiger system. In terms of precipitation discrimination, the K?ppen-Geiger classification performs poorly relative to the MRT. The data and algorithm implementation used in this study are freely available. Thus, the MRT climate classification offers instructors and students in the geosciences a simple instrument for exploring modern, computer-based climatological methods.