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Abstract Cyclone Gabrielle passed along the northern coast of Aotearoa New Zealand in February 2023, producing historic rainfall accumulations and impacts. Gabrielle was an ex‐tropical cyclone that stalled and re‐energised off the north coast, resembling descriptions of worst case scenarios for the northeast of the country. Here we report on a comparison of the actual forecast of the storm against forecasts under conditions representative of a climate without anthropogenic interference and of a climate +2.0°C warmer than pre‐industrial (about 1.0°C cooler and warmer than present respectively). We find that regional total rainfall accumulations from a Gabrielle‐like storm are about 10% higher because of the historical anthropogenic warming, and will increase by a larger amount under similar future warming. These differences are driven by a 20% (relative to a non‐anthropogenic world) to 30% (relative to a +2.0°C world) rise in peak rainfall rates, which in turn is mainly driven by a more temporally concentrated column‐integrated moisture flux. The forecast model generates the larger increase for the +2.0°C world through greater precipitation efficiency, reflecting the importance of unresolved precipitation processes in the climate change response of rainfall extremes.

A largely automated extreme weather event (EWE) attribution system has been developed that uses the Weather Research and Forecast numerical weather prediction model to simulate EWEs under current and pre-industrial climate conditions. The system has been applied to two extreme precipitation events in Aotearoa New Zealand with the goal of quantifying the effect of anthropogenic climate change on the severity of these events. The forecast simulation of the target event under current climate conditions constitutes the first scenario (ALL). We then apply a climate change signal in the form of delta fields in sea-surface temperature, atmospheric temperature and specific humidity, creating a second ‘naturalised’ scenario (NAT) which is designed to represent the weather system in the absence of human interference with the climate system. A third scenario, designed to test for coherence, is generated by applying deltas of opposite sign compared to the naturalised scenario (ALL+). Each scenario comprises a 22-member ensemble which includes one simulation that was not subject to stochastic perturbation. Comparison of the three ensembles shows that: (1) the NAT ensemble develops an extreme event which resembles the observed event, (2) the severity, i.e. maximum intensity and/or the size of area affected by heavy precipitation, changes when naturalising the boundary conditions, (3) the change in severity is consistently represented within the three scenarios and the signal is robust across the different ensemble members, i.e. it is typically shown in most of the 22 ensemble members. Thus, the attribution system presented here can be used to provide information about the influence of anthropogenic climate change on the severity of specific extreme events.