Articles | Volume 25, issue 12
Research article
06 Dec 2021
Research article |  | 06 Dec 2021

Coherence of global hydroclimate classification systems

Kathryn L. McCurley Pisarello and James W. Jawitz

Data sets

CRU TS4.04: Climatic Research Unit (CRU) Time-Series (TS) version 4.04 of high-resolution gridded data of month-by-month variation in climate (Jan. 1901–Dec. 2019) University of East Anglia Climatic Research Unit, I. C. Harris, P. D. Jones, and T. Osborn

GLEAM v3: satellite-based land evaporation and root-zone soil moisture ( B. Martens, D. G. Miralles, H. Lievens, R. van der Schalie, R. A. M. de Jeu, D. Fernández-Prieto, H. E. Beck, W. A. Dorigo, and N. E. C. Verhoest

Global land-surface evaporation estimated from satellite-based observations ( D. G. Miralles, T. R. H. Holmes, R. A. M. De Jeu, J. H. Gash, A. G. C. A. Meesters, and A. J. Dolman

G-RUN : Global Runoff Reconstruction G. Ghiggi, L. Gudmundsson, and V. Humphrey

Model code and software

ktpisa/Coherence-of-global-hydroclimate-classification-systems (v1.1.0c) K. Pisarello and J. Jawitz

Short summary
Climate classification systems divide the Earth into zones of similar climates. We compared the within-zone hydroclimate similarity and zone shape complexity of a suite of climate classification systems, including new ones formed in this study. The most frequently used system had high similarity but high complexity. We propose the Water-Energy Clustering framework, which also had high similarity but lower complexity. This new system is therefore proposed for future hydroclimate assessments.