Details

In 2026 Bodeker Scientific produced a synthesis of climate projections for the Horizons Region as part of a contract with the Horizons Regional Council. The projections were generated using the Conformal Cubic Atmospheric Model (CCAM) by Earth Sciences New Zealand (ESNZ) and made publicly available by the New Zealand Ministry for Cities, Environment, Regions and Transport (MCERT). We acknowledge ESNZ and thank them for making these simulations freely and easily available. 

CCAM is a regional climate model that dynamically downscales outputs from global climate models to produce higher‐resolution climate projections over New Zealand. Papers describing the generation of these climate projections for New Zealand are available here and here. Regional climate modelling is necessary because global climate models typically operate at spatial resolutions that are too coarse to adequately represent New Zealand’s complex topography. Mountains, coastlines, and local climatic gradients strongly influence regional climate and require higher spatial resolution to be represented realistically.

Analyses were conducted for 25 different climate variables (see below). Four Shared Socioeconomic Pathway (SSP) emissions scenarios were considered:

1. SSP1‐2.6: A low‐emissions pathway consistent with strong global mitigation efforts and relatively limited future warming.

2. SSP2‐4.5: An intermediate pathway representing moderate emissions reductions and moderate warming.

3. SSP3‐7.0: A medium‐to‐high emissions pathway associated with substantial future warming.

4. SSP5‐8.5: A high‐emissions pathway characterised by continued growth in GHG emissions and large increases in global temperature.

The likelihood of these four scenarios occurring is not equal. Given the current trajectory of international actions on greenhouse gas  emissions mitigation, it is highly unlikely the global future climate will follow the SSP1‐2.6 scenario. In contrast, the GHG emissions reduction actions that have been achieved to date increasingly rule out the SSP5‐8.5 scenario. This is not to say that these two scenarios do not have their uses: SSP1‐2.6 shows us what could have been achieved had earlier climate projection pledges been realised, while the SSP5‐8.5 scenario shows the world that has been avoided by actions to date. For planning purposes, however, more weight should be assigned to the SSP2‐4.5 and SSP3‐7.0 scenarios.

Three future periods were examined:

1. 2021–2040 (near future)

2. 2041–2060 (mid‐century)

3. 2080–2099 (late century)

All projections were evaluated relative to a baseline period of 1986–2005. Although the radiative forcing (the rate at which energy is being added to the climate system compared to the pre‐industrial baseline) increases to 2.6 W m⁻² under SSP1 by 2100, to 4.5 W m⁻² under SSP2 by 2100, to 7.0 W m⁻² under SSP3 by 2100, and to 8.5 W m⁻² under SSP5 by 2100, one should not expect that there will always be a consistent (monotonic) increase or decrease for some climate variable from SSP1‐2.6 to SSP2‐4.5 to SSP3‐7.0 to SSP5‐8.5 since the pathways to that 2100 end point can be very different, and over the near‐term to mid‐century, natural variability can dominate the climate signal; often the climate signal only emerges later in the century. This is demonstrated in the figure below which shows annual mean surface temperature time series extracted from the six different model simulations, for the Horizons Region, for the historical baseline (black traces) and for the four different SSP scenarios (SSP1‐2.6 in red; SSP2‐4.5 in green, SSP3‐7.0 in blue and SSP5‐8.5 in cyan. Also shown are the three different analysis periods considered in this report. It is clear that both over the near‐future and mid‐century, the year‐to‐year variability (unforced climate variability), and inter‐model spread, obscures any statistically significant separation of the projections under the four different SSPs.