Abstract: Flooding is the most frequent natural hazard in Aotearoa New Zealand and the second most costly after earthquakes. It will change in frequency and intensity, becoming more extreme as climate change impacts are realised. The main inundation driver is heavy rainfall. In this study, flood-inducing heavy rainfall is characterised locally by applying synoptic climatological techniques, using the study case of Aotearoa New Zealand. Extending on previous work in the field, a new set of 49 daily weather types (DWTs) is proposed for New Zealand, based on mean sea level pressure (MLSP) and 500hPa geopotential height (500GH) (predictor variables). The role of the DWTs, the large-scale climatic patterns (LSCPs) known to influence rainfall variability, and the wind conditions (as an additional explanatory variable since they play an essential role in the development of these events) as heavy rainfall and flooding (predictand variables) drivers is investigated using the Wairewa catchment (Little River, Canterbury) as the study site. Heavy rainfall is represented through its temporal and spatial features, based on two rainfall datasets (a rain gauge and a gridded product obtained by the Weather Research and Forecasting (WRF) numerical model). Useful relationships are found between the predictor and the predictand variables. Also, the predictor variables' temporal variability (interannual and intra-annual variability, seasonality) plays a key role, translating to the temporal variability of heavy rainfall and flooding. The proposed synoptic climatological approach provides qualitative and quantitative value, displaying the range of weather and climatic configurations leading to different types of storms and flooding and helping in their identification and understanding

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