Historically, wave data coverage of New Zealand's coast has been poor, particularly for directional records. With very few data sets available of more than 1 year's duration, it has been difficult to establish accurate wave climatologies. To help fill in the gaps in our wave records, the wave generation model WAM (WAve Model) has been implemented over a domain covering the south-west Pacific and Southern Oceans. The model has been used to hindcast the generation and propagation of deep-water waves incident on the New Zealand coast over a 20-year period (1979-98), using winds from the European Centre for Medium-Range Weather Forecasts (ECMWF). The resulting synthetic climatology is expected to provide a valuable tool for researchers and coastal planners. The hindcasts were compared with data from wave buoy deployments at eight representative sites around the New Zealand coast. With appropriate interpolation and correction for the effects of limited fetch and sheltering by land, the hindcast was found to provide a satisfactory simulation of wave conditions at sites on exposed coasts. Regression between measured and hindcast significant heights at the four deep-water sites (100-120 m) achieved scatter indices (ratio of root mean square error to mean) averaging 0.28. At the four shallower sites (30-45 m), the corresponding scatter index averaged 0.49, indicating that for regions of complex coastal topography, deep-water spectra do not represent inshore conditions well. Wave spectra can be considerably modified by the processes of refraction and shoaling. To address these effects, nearshore wave transformations in the outer Hauraki Gulf were investigated using the shallow water model SWAN (Simulating WAves Nearshore), which was used to derive wave statistics at nearshore locations from deep-water wave spectra obtained from the hindcast. The simulations were validated using data from an inshore site in 30 m water depth at Mangawhai on the north-east coast of the North Island. Use of the nested model improved the agreement between model and measured significant wave height, decreasing the scatter index from 0.50 to 0.26. The suite of tools provided by the hindcast and localised, shallow water models can provide accurate new wave information for most of New Zealand's coastline.

The wave evolution model WAM (WAve Model) has been implemented for the New Zealand region and used to simulate the generation and propagation of deep-water waves over a 20-year period . The model extends to include the relevant generation areas of the south-west Pacific and Southern Oceans. Input winds for the model were derived from the European Centre for MediumRange Weather Forecasts (ECMWF). The resulting synthetic wave climatology will provide a valuable tool for researchers and coastal planners, as it will help fill gaps in the available wave information for New Zealand waters. In this paper the hindcasts are described, and comparisons are made with wave height data from the altimeters flown on the TOPEX/ Poseidon and ERS1 and ERS2 satellite missions. Long-term mean significant wave heights from the hindcast were generally 0.3-0.5 m lower than values from "buoy-equivalent" altimeter data throughout the comparison region (150°E-170°W, 60°S-20°S). Hindcast distributions of significant wave height occurrence matched satellite data at the lowest wave heights and above the peaks of the distributions, but tended to overestimate occurrence below the peak and underestimate the occurrence of the largest wave events. The hindcast was then used to characterise the wave climate of the New Zealand region. Some prominent features noted were the large mean heights (3.6 m) in the high latitudes of the Southern Ocean, associated with strong prevailing westerlies. North of this band, waves largely propagate towards the north-east, with diminishing mean heights, further attenuated by the blocking effect of the New Zealand landmasses. This results in mean wave heights of c. 2 m in offshore waters north-east of New Zealand. Annual cycles of mean wave height with a range of c. 1 m were identified throughout the region. These were found to have minima in summer (December/January), and either unimodal maxima in winter (June/July) for tropical and temperate latitudes, or bimodal maxima (May and August) in southern waters. Longer-term variations were also noted in the form of correlations with the El Niño/Southern Oscillation. Positive correlations (R +0.2) were found off the north-east coast of the North Island, indicating a moderate tendency for increased wave heights there during La Niña conditions, whereas negative correlations were found south and south-west of New Zealand (R -0.2), and in the Fiji/Vanuatu region (R +0.4), reflecting wave height enhancements in the El Niño phase.

SUMMARYSmoothed particle hydrodynamics (SPH) is becoming increasingly common in the numerical simulation of complex fluid flows and an understanding of the errors is necessary. Recent advances have established techniques for ensuring completeness conditions (low-order polynomials are interpolated exactly) are enforced when estimating property gradients, but the consequences on errors have not been investigated. Here, we present an expression for the error in an SPH estimate, accounting for completeness, an expression that applies to SPH generally. We revisit the derivation of the SPH equations for fluids, paying particular attention to the conservation principles. We find that a common method for enforcing completeness violates a property required of the kernel gradients, namely that gradients with respect the two position variables be equal and opposite. In such models this means conservation principles are not enforced and we present results that show this. As an aside we show the summation interpolant for density is a solution of, and may be used in the place of, the discretized, symmetrized continuity equation. Finally, we examine two examples of discretization errors, namely numerical boundary layers and the existence of crystallized states.

We describe here the development of an ecosystem classification designed to underpin the conservation management of marine environments in the New Zealand region. The classification was defined using multivariate classification using explicit environmental layers chosen for their role in driving spatial variation in biologic patterns: depth, mean annual solar radiation, winter sea surface temperature, annual amplitude of sea surface temperature, spatial gradient of sea surface temperature, summer sea surface temperature anomaly, mean wave-induced orbital velocity at the seabed, tidal current velocity, and seabed slope. All variables were derived as gridded data layers at a resolution of 1 km. Variables were selected by assessing their degree of correlation with biologic distributions using separate data sets for demersal fish, benthic invertebrates, and chlorophyll-a. We developed a tuning procedure based on the Mantel test to refine the classification's discrimination of variation in biologic character. This was achieved by increasing the weighting of variables that play a dominant role and/or by transforming variables where this increased their correlation with biologic differences. We assessed the classification's ability to discriminate biologic variation using analysis of similarity. This indicated that the discrimination of biologic differences generally increased with increasing classification detail and varied for different taxonomic groups. Advantages of using a numeric approach compared with geographic-based (regionalisation) approaches include better representation of spatial patterns of variation and the ability to apply the classification at widely varying levels of detail. We expect this classification to provide a useful framework for a range of management applications, including providing frameworks for environmental monitoring and reporting and identifying representative areas for conservation.

[1] The increased use of ambient seismic noise for seismic imaging requires better understanding of the ambient seismic noise wavefield and its source locations and mechanisms. Although the source regions and mechanisms of Rayleigh waves have been studied extensively, characterization of Love wave source processes are sparse or absent. We present here the first systematic comparison of ambient seismic noise source directions within the primary (~10-20 s period) and secondary (~5-10 s period) microseism bands for both Rayleigh and Love waves in the Southern Hemisphere using vertical-and horizontalcomponent ambient seismic noise recordings from a dense temporary network of 68 broadband seismometers in New Zealand. Our analysis indicates that Rayleigh and Love waves within the primary microseism band appear to be mostly generated in different areas, whereas in the secondary microseism band they arrive from similar backazimuths. Furthermore, the source areas of surface waves within the secondary microseism band correlate well with modeled deep-water and near-coastal source regions.Citation: Behr Y., J. Townend, M. Bowen, L. Carter, R. Gorman, L. Brooks, and S. Bannister (2013), Source directionality of ambient seismic noise inferred from three-component beamforming,