Natural hazards in Australia: sea level and coastal extremes

McInnes, Kathleen L.; White, Christopher J.; Haigh, Ivan D.; Hemer, Mark; Hoeke, Ron; Holbrook, Neil J.; Kiem, Anthony S.; Oliver, Eric C. J.; Ranasinghe, Roshanka; Walsh, Kevin; Westra, Seth; Cox, Ron

doi:10.1007/s10584-016-1647-8

Cited by 80 publications

(59 citation statements)

References 57 publications

(32 reference statements)

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“…Figure shows the maps of the SWL, shoreline wave setup and the MTWL for a 1‐year and 100‐year event. The 1‐year SWL (Figure a) is largest in northwest of Western Australia (NWWA) and can be principally attributed to the magnitude of the highest astronomical tide (McInnes et al, ). For the 100‐year SWL levels (Figure b), the influence of storm surge is increased for the southern margin in the South Australian Bight and Bass Strait, notionally driven by eastward traveling extratropical cyclones and fronts most frequent in winter months (McInnes et al, ).…”

Section: Resultsmentioning

confidence: 99%

Extreme Water Levels for Australian Beaches Using Empirical Equations for Shoreline Wave Setup

et al. 2019

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Empirical equations for wave breaking and wave setup are compared with archived shoreline wave setup measurements to investigate the contribution of wind waves to extreme Mean Total Water Levels (MTWL, the mean height of the shoreline), for natural beaches exposed to open ocean wind waves. A broad range of formulations is compared through linear regression and quantile regression analysis of the highest measured values. Shoreline wave setup equations are selected based on the availability of local beach slope data and the ability of the quantile regression to show a good representation of the highest measured levels. Wave parameters from an existing spectral wave hindcast are used as input to the selected equations and are combined with a storm tide time series to quantify the relative contribution of shoreline wave setup to the extreme MTWL climate along Australian beaches. A multipass analysis is provided to understand the ability to capture the shoreline wave setup estimates with and without considering beach slope. The national scale analysis which does not include beach slope indicates there are multiple contributing factors to MTWL. Examples are provided at two locations of differing local beach slope to show the importance of including local beach slope in determining the contribution of waves to MTWL. A tool is in development for further investigation of wave setup for Australian beaches.

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Section: Resultsmentioning

confidence: 99%

Extreme Water Levels for Australian Beaches Using Empirical Equations for Shoreline Wave Setup

et al. 2019

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“…Australia extends from the tropics to the mid-latitudes with a variety of meteorological systems responsible for extreme sea levels along its coastline [McInnes et al, 2016]. The range of weather systems, and more particularly their associated spatial scales means that it is challenging to obtain meteorological forcing that consistently represents all weather 5 systems responsible for sea level extremes.…”

Section: Pagementioning

confidence: 99%

Atmospheric Circulation Changes and their Impact on Extreme Sea Levels around Australia

Colberg¹,

McInnes²,

O’Grady³

et al. 2018

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Abstract.Projections of sea level rise (SLR) will lead to increasing coastal impacts during extreme sea level events globally, however, there is significant uncertainty around short-term coastal sea level variability and the attendant frequency and severity of extreme sea level events. In this study, we investigate drivers of coastal sea level variability For the southern mainland coast the simulated scenarios suggest that a southward movement of the subtropical ridge leads to a small reduction in sea level extremes.

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“…For each of the twelve random epochs, the OTPS model was used to populate the raster grid with the tidal height relative to mean sea level (MSL) at the selected date and time, so that each raster layer provided a snapshot of the spatial variability of the OTPS model at a different point in time. By modelling dates and times across a full year, we aimed to capture potential seasonal and temporal variability in different tidal regimes across the continent [21].…”

Section: Developing the Multi-resolution Frameworkmentioning

confidence: 99%

“…Complicating this requirement is the sun-synchronous nature of Landsat data acquisition, which means that all observations are made at approximately the same time of day (mid-morning in Australia) at any given location. Practically, this means that we are likely to only observe a limited subset of the full tidal range (Figure 2), and the size and nature of the subset in any location will vary along with the different tidal regimes and ranges of the continent [21]. Hence, we adopt the terminology used in [16] using the observed tidal range (OTR), highest observed tide (HOT), and lowest observed tide (LOT) as distinct from common datums, such as lowest astronomical tide (LAT).…”

Section: Composite Domain Determinationmentioning

confidence: 99%

Generating Continental Scale Pixel-Based Surface Reflectance Composites in Coastal Regions with the Use of a Multi-Resolution Tidal Model

et al. 2018

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Generating continental-scale pixel composites in dynamic coastal and estuarine environments presents a unique challenge, as the application of a temporal or seasonal approach to composite generation is confounded by tidal influences. We demonstrate how this can be resolved using an approach to compositing that provides robust composites of multi-type environments. In addition to the visual aesthetics of the images created, we demonstrate the utility of these composites for further interpretation and analysis. This is enabled by the manner in which our approach captures the spatial variation in tidal dynamics through the use of a Voronoi mesh, and preserves the band relationships within the modelled spectra at each pixel. Case studies are presented which include continental-scale mosaics of the Australian coastline at high and low tide, and tailored examples demonstrating the potential of the tidally constrained composites to address a range of coastal change detection and monitoring applications. We conclude with a discussion on the potential applications of the composite products and method in the coastal and marine environment, as well as further development directions for our tidal modelling framework.

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Natural hazards in Australia: sea level and coastal extremes

Cited by 80 publications

References 57 publications

Extreme Water Levels for Australian Beaches Using Empirical Equations for Shoreline Wave Setup

Extreme Water Levels for Australian Beaches Using Empirical Equations for Shoreline Wave Setup

Atmospheric Circulation Changes and their Impact on Extreme Sea Levels around Australia

Generating Continental Scale Pixel-Based Surface Reflectance Composites in Coastal Regions with the Use of a Multi-Resolution Tidal Model

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