This study presents a method for estimating daily rainfall on a 0.05°latitude/longitude grid covering all of New Zealand for the period 1960-2004 using a second order derivative trivariate thin plate smoothing spline spatial interpolation model. Use of a hand-drawn (and subsequently digitised) mean annual rainfall surface as an independent variable in the interpolation is shown to reduce the interpolation error compared with using an elevation surface. This result is confirmed when long-term average annual rainfall data, derived from the daily interpolations, are validated using long-term river flow data.

Rain gauge, radar, and atmospheric observations during a prolonged northwesterly storm in November 1994 have been used to study factors influencing the distribution of precipitation across the Southern Alps. Despite the persistent northwesterly flow, the location and intensity of precipitation varied markedly during this storm, providing an excellent dataset for these investigations. Data from 36 recording gauges in the northern half of the Alps were supplemented by data from 57 daily gauges, which were partitioned into 6-h values. These data were grouped according to distance from the alpine divide, and best-fit transect curves, normalized for rainfall intensity, were established every 6 h. The fraction of the total transect precipitation falling in leeside catchments varied between 0.11 and 0.70, while a ''spillover distance'' index varied between 6 and 29 km. Comparison with atmospheric profiles of temperature and wind from Hokitika on the west coast of New Zealand and with European Centre for Medium-Range Weather Forecasts analyses revealed that precipitation was confined upwind of the divide during a period of blocked flow near the start of the storm, and only extended into leeside catchments with the onset of stronger flow and reduced static stability. Regression equations involving these factors explained up to 93% of the spillover variations. It is suggested that ascent and precipitation maxima are shifted upstream during blocked flow, while spillover is enhanced during stronger and/or unstable flow as the upstream influence lessens and snow and ice particles drift farther downwind before falling below the freezing level. Further case and modeling studies are needed to demonstrate the wider applicability of these findings.

This paper introduces a generic framework for multi-risk modelling developed in the project 'Regional RiskScape' by the Research Organizations GNS Science and the National Institute of Water and Atmospheric Research Ltd. (NIWA) in New Zealand. Our goal was to develop a generic technology for modelling risks from different natural hazards and for various elements at risk. The technical framework is not dependent on the specific nature of the individual hazard nor the vulnerability and the type of the individual assets. Based on this generic framework, a software prototype has been developed, which is capable of 'plugging in' various natural hazards and assets without reconfiguring or adapting the generic software framework. To achieve that, we developed a set of standards for treating the fundamental components of a risk model: hazards, assets (elements at risk) and vulnerability models (or fragility functions). Thus, the developed prototype system is able to accommodate any hazard, asset or fragility model, which is provided to the system according to that standard. The software prototype was tested by modelling earthquake, volcanic ashfall, flood, wind, and tsunami risks for several urban centres and small communities in New Zealand.

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