Downscaled CMIP6 future climate projections for New Zealand: climatology and extremes

Gibson, P. B., Broadbent, A. M., Stuart, S. J., Lewis, H., Campbell, I., Rampal, N., Harrington, L. J. and Williams, J. ORCID: https://orcid.org/0000-0002-0680-0098 (2025) Downscaled CMIP6 future climate projections for New Zealand: climatology and extremes. Weather and Climate Extremes, 49. 100784. ISSN 2212-0947 doi: 10.1016/j.wace.2025.100784

Abstract/Summary

Downscaled climate projections provide regionally relevant information for climate adaptation and planning purposes. Updated climate projections (~12-km) are presented here for the New Zealand region, downscaling 6 global climate models (GCMs) from the Coupled Model Intercomparison Project (CMIP6) under a high emissions scenario (SSP3-7.0). Three regional climate models (RCMs) are used to explore differences when downscaling select GCMs. For end of century projections (relative to 1986–2005), the national multi-model annual mean warming is 3.1◦ C (model range 2.0–3.8◦C) across downscaled simulations. Downscaling generally enhances warming over New Zealand relative to the GCMs, with the largest increases across high-elevation regions. There can be important differences in the projections across RCMs, including at national scales for temperature and across local-to-regional scales for precipitation. Averaged across models, annual extreme heatwaves become 3–5◦C hotter for most regions. More frequent, intense, and longer duration meteorological drought is projected across northern and eastern regions of both islands. In terms of model uncertainty based on sign agreement, while summer mean precipitation projections carry the largest uncertainty, projections of summer meteoro-logical drought and precipitation extremes can be made with greater confidence. These results provide a foun-dation for further targeted regional climate change impact and adaptation studies.

Item Type	Article
URI	https://centaur.reading.ac.uk/id/eprint/125330
Identification Number/DOI	10.1016/j.wace.2025.100784
Refereed	Yes
Divisions	Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Publisher	Elsevier
Download/View statistics	View download statistics for this item