Widespread inundation of Pacific islands triggered by distant-source wind-waves

Hoeke, Ron; McInnes, Kathleen L.; Krüger, Jens C.; McNaught, Rebecca; Hunter, John; Smithers, Scott G.

doi:10.1016/j.gloplacha.2013.06.006

Cited by 227 publications

(188 citation statements)

References 37 publications

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“…Crucially, both wave and wind setup effects are minimal at some locations, such as near the Apia tide gauge. This is an illustration of how poorly the likelihood of coastal inundation predicated on tide gauge data may represent the coastal areas in the immediate vicinity, particularly in areas that lack continental shelves (e.g., oceanic islands such as those of Samoa), something noted by a number of previous studies [6,7,9].…”

Section: Resultsmentioning

confidence: 84%

“…Several researchers have attempted to ameliorate such issues by blending reanalysis winds with vortex winds (e.g., [40]); this is of course not an option for the synthetic cyclones used in this study, however. Sensitivity of extreme wave prediction to different input wind fields remains poorly understood; something exacerbated by an almost total lack of in situ TC wind and wave records in the insular Pacific [2,7]. Further consideration of this is beyond the scope of this study, however, and remains an area of future research.…”

Section: Archipelago Wave Model Resultsmentioning

confidence: 94%

“…These contributions have a morphological dependence: storm surge tends to be the dominant contributing factor on wide-shelved continental coastlines, and wave setup is often assumed to contribute less than 10% to the total water level (e.g., [5,6]). Wave setup and run-up, on the other hand, have been shown to be an important contributor to extreme sea levels, particularly along steep-shelved coastlines and narrow fringing reefs that characterize many small islands and atolls, e.g., [6][7][8][9]. In addition, whereas the cyclone-induced storm surge tends to be concentrated in the region of maximum onshore winds close to the cyclone center, wind-waves propagate with little loss of energy over the deep ocean, and so can increase the scale and duration over which damaging coastal impacts occur during a TC event [10].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Wind and Wave Setup Contributions to Extreme Sea Levels at a Tropical High Island: A Stochastic Cyclone Simulation Study for Apia, Samoa

Hoeke

McInnes

O’Grady

2015

JMSE

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Wind-wave contributions to tropical cyclone (TC)-induced extreme sea levels are known to be significant in areas with narrow littoral zones, particularly at oceanic islands. Despite this, little information exists in many of these locations to assess the likelihood of inundation, the relative contribution of wind and wave setup to this inundation, and how it may change with sea level rise (SLR), particularly at scales relevant to coastal infrastructure. In this study, we explore TC-induced extreme sea levels at spatial scales on the order of tens of meters at Apia, the capitol of Samoa, a nation in the tropical South Pacific with typical high-island fringing reef morphology. Ensembles of stochastically generated TCs (based on historical information) are combined with numerical simulations of wind waves, storm-surge, and wave setup to develop high-resolution statistical information on extreme sea levels and local contributions of wind setup and wave setup. The results indicate that storm track and local morphological details lead to local differences in extreme sea levels on the order of 1 m at spatial scales of less than 1 km. Wave setup is the overall largest contributor at most locations; however, wind setup may exceed wave setup in some sheltered bays. When an arbitrary SLR scenario (+1 m) is introduced, overall extreme sea levels are found to modestly decrease relative to SLR, but wave energy near the shoreline greatly increases, consistent with a number of other recent studies. These differences have implications for coastal adaptation strategies.

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Section: Resultsmentioning

confidence: 84%

Section: Archipelago Wave Model Resultsmentioning

confidence: 94%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Wind and Wave Setup Contributions to Extreme Sea Levels at a Tropical High Island: A Stochastic Cyclone Simulation Study for Apia, Samoa

Hoeke

McInnes

O’Grady

2015

JMSE

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“…A combination of spring tides (highest astronomical tide), ENSO and distant storms induce large waves that affect Takú Atoll about every 30 years [54]. The latest so-called king tide happened in December 2008 and Smithers and Hoeke [21] showed that such events are capable of producing thick sand depositions on Nukutoa, building up the island.…”

Section: Sea-level Extremes: Tsunamis Distant-source Wave Events Andmentioning

confidence: 99%

Assessing Long-Term Changes in the Beach Width of Reef Islands Based on Temporally Fragmented Remote Sensing Data

Mann

Westphal

2014

Remote Sensing

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Atoll islands are subject to a variety of processes that influence their geomorphological development. Analysis of historical shoreline changes using remotely sensed images has become an efficient approach to both quantify past changes and estimate future island response. However, the detection of long-term changes in beach width is challenging mainly for two reasons: first, data availability is limited for many remote Pacific islands. Second, beach environments are highly dynamic and strongly influenced by seasonal or episodic shoreline oscillations. Consequently, remote-sensing studies on beach morphodynamics of atoll islands deal with dynamic features covered by a low sampling frequency. Here we present a study of beach dynamics for nine islands on Takú Atoll, Papua New Guinea, over a seven-decade period. A considerable chronological gap between aerial photographs and satellite images was addressed by applying a new method that reweighted positions of the beach limit by identifying "outlier" shoreline positions. On top of natural beach variability observed along the reweighted beach sections, we found that one third of the analyzed islands show a statistically significant decrease in reweighted beach width since 1943. The total loss of beach area for all islands corresponds to 44% of the initial beach area. Variable shoreline trajectories suggest that changes in beach width on Takú Atoll are dependent on local control (that is, human activity and longshore sediment transport). Our results show that remote imagery with a low sampling frequency may be sufficient to characterize prominent morphological changes in planform beach configuration of reef islands.

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“…Wave-driven local water level set-up is one of the classic phenomena at open ocean coasts. It may often provide as much as 25 1/3 of the total water level rise during a storm (Dean and Bender, 2006) and significantly contribute to extreme sea level events (Hoeke et al, 2013;Melet et al, 2016). Even though the physics of wave-set up (Longuet-Higgins and Stewart, 1964) is known for half a century, adequate parameterizations have been introduced (Stockdon et al, 2006) and many models take into account wave set-up to a certain extent (SWAN, 2007;Roland et al, 2009;Alari and Kõuts, 2012;Moghimi et al, 2013), the contribution from this phenomenon apparently provides one of the largest uncertainties in modelling of storm 30 surges and flooding (Dukhovskoy and Morey, 2011;Melet et al, 2013).…”

mentioning

confidence: 99%

Inverse Gaussian distribution of wave set-up heights along a shoreline with complicated geometry

Soomere

Pindsoo

2017

Preprint

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Abstract. The phenomenon of wave set-up may substantially contribute to the formation of devastating coastal flooding in certain coastal sections. We study empirical probability distribution of the occurrence of different set-up heights in section of coastline near Tallinn in the Gulf of Finland, the eastern Baltic Sea. The shoreline in the study area is often attacked by high 10 waves from various directions and also has a complex geometry. Shown is that this distribution substantially deviates from the Rayleigh or the Weibull distribution that usually reflect the distribution of different wave heights. The distribution of wave set-up heights matches a Wald (inverse Gaussian) distribution along the entire study area. Even though different sections of the study area are open to different directions and host substantially different wave regimes, the leading term of the exponent in the associated inverse Gaussian distribution varies insignificantly along the study area and generally is close 15 to -1. This appearance signals that extreme set-up events are substantially more probable that it could be expected from the probability of occurrence of severe seas. This feature is invariant with respect to the orientation of the coastline and with respect to the properties of local wave climate.

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Widespread inundation of Pacific islands triggered by distant-source wind-waves

Cited by 227 publications

References 37 publications

Wind and Wave Setup Contributions to Extreme Sea Levels at a Tropical High Island: A Stochastic Cyclone Simulation Study for Apia, Samoa

Wind and Wave Setup Contributions to Extreme Sea Levels at a Tropical High Island: A Stochastic Cyclone Simulation Study for Apia, Samoa

Assessing Long-Term Changes in the Beach Width of Reef Islands Based on Temporally Fragmented Remote Sensing Data

Inverse Gaussian distribution of wave set-up heights along a shoreline with complicated geometry

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