Projections of Extreme Ocean Waves in the Arctic and Potential Implications for Coastal Inundation and Erosion

Casas-Prat, Mercè

doi:10.1029/2019jc015745

Cited by 52 publications

(24 citation statements)

References 62 publications

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“…The increase in

{false{H_{s} false}}_{\max}^{AN}

is accompanied by a delay of the month in which

{false{H_{s} false}}_{\max}^{AN}

occurs (Figure S8), consistent with Casas‐Prat and Wang (2020). This is more accentuated in ArOE, ArOW, BafB, HudB, TheN, ChuS, BeaS, EasS, LapS, and KarS.…”

Section: Resultssupporting

confidence: 84%

“…This study analyzed the projected changes and trends of the annual/monthly regional maximum of H s ,

{false{H_{s} false}}_{\max}^{AN}

and

{false{H_{s} false}}_{\max}^{MON}

, in the Arctic region (including the Hudson Bay). These projections were derived from five sets of CMIP5‐derived wave climate simulations for the historical (1979–2005) and the future (2081–2100) period under the RCP8.5 emission scenario, which were presented in Casas‐Prat and Wang (2020).…”

Section: Discussionmentioning

confidence: 99%

“…The wave projections of Casas‐Prat and Wang (2020) span the periods 1979–2005 (historical period) and 2081–2100 (future period) and were obtained using the WAVEWATCH (WW3) wave model (The WAVEWATCH III Development Group (WW3DG), 2016) with a Spherical Multi‐Cell (SMC) computational grid (Li, 2012, 2016) of 25‐km resolution offshore. The conventional parametrizations of wave physics in WW3 (ST4, NL1 switches) were used (Ardhuin et al, 2010; Hasselmann & Hasselman, 1985), with the Naval Research Laboratory Digital Bathymetry 92 Data Base 2‐min resolution (NRL DBDB2).…”

Section: Methodsmentioning

confidence: 99%

“…N MON is calculated as the number of wave grid points accumulated over each month, which are weighted by the respective cell size relative to the reference surface (∼625 km 2 ). Note that the SMC grid cells slightly vary in size due to converge of meridians at high latitudes (even with the longitudinal merging of cells) and due to coastal refinement (at ∼12.5‐km resolution) (Casas‐Prat & Wang, 2020). We considered one possible realization per day (rather than the subdaily resolution of the wind speed) to minimize the effect of the dependency between consecutive time steps.…”

Section: Methodsmentioning

confidence: 99%

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Sea Ice Retreat Contributes to Projected Increases in Extreme Arctic Ocean Surface Waves

Casas-Prat

2020

Geophysical Research Letters

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The projected changes and trends in the regional annual and monthly maxima of the significant wave height (Hs) in the Arctic Ocean are studied using wave simulations derived from the CMIP5 (Coupled Model Intercomparison Project Phase 5) climate simulations for 1979–2005 and 2081–2100 periods. Under the RCP8.5 scenario, the regional annual maximal Hs increases on average up to ∼3 cm/year, or >0.5%/year, relative to the 1986–2005 climatological value, in many Arctic areas (and up to 0.8%/year in the east side of the Arctic Ocean). While strong winds need to occur for large waves to develop, the changes in wind speed alone cannot explain the increases in the regional maximal Hs. Sea ice retreat also plays an important role by increasing fetch to promote wave growth, thereby contributing notably to the projected increase in wave height. It also contributes to increasing the probability of strong winds over the widening ice‐free waters.

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“…The increase in

{false{H_{s} false}}_{\max}^{AN}

is accompanied by a delay of the month in which

{false{H_{s} false}}_{\max}^{AN}

occurs (Figure S8), consistent with Casas‐Prat and Wang (2020). This is more accentuated in ArOE, ArOW, BafB, HudB, TheN, ChuS, BeaS, EasS, LapS, and KarS.…”

Section: Resultssupporting

confidence: 84%

“…This study analyzed the projected changes and trends of the annual/monthly regional maximum of H s ,

{false{H_{s} false}}_{\max}^{AN}

and

{false{H_{s} false}}_{\max}^{MON}

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Sea Ice Retreat Contributes to Projected Increases in Extreme Arctic Ocean Surface Waves

Casas-Prat

2020

Geophysical Research Letters

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“…Several studies have projected a decrease in SLP over the western Arctic (Labe et al., 2018) and an associated weakening of the Beaufort High through the 21st century (Casas‐Prat & Wang, 2020), making the Beaufort High more prone to collapse as it did during winter 2017. In particular, the collapse of the Beaufort High during winter 2017 was the result of cyclonic intrusions from the north Atlantic that occurred due to an anomalously thin ice cover in the Barents Sea during Fall 2016 (Moore et al., 2018).…”

Section: Discussionmentioning

confidence: 99%

The 2017 Reversal of the Beaufort Gyre: Can Dynamic Thickening of a Seasonal Ice Cover During a Reversal Limit Summer Ice Melt in the Beaufort Sea?

et al. 2020

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The anticyclonic Beaufort Gyre is one of the defining characteristics of the Arctic Ocean. The Gyre is driven by the semipermanent Beaufort High (Serreze & Barrett, 2011), which circulates sea ice anticyclonically (Rigor & Wallace, 2002) and has been accumulating a large volume of freshwater in the western Arctic (Giles et al., 2012; Proshutinsky et al., 2009). Historically, the gyre has occasionally reversed for short periods of time as cyclones passed through the region, causing cyclonic ice drift (Mclaren et al., 1987; Serreze et al., 1989) and allowing freshwater to be released from the gyre (Manucharyan & Spall, 2016; Meneghello et al., 2018). Generally, these reversals have only occurred during summer, when the mechanically weak and therefore more mobile ice cover was more responsive to cyclones (LeDrew et al., 1991; Lukovich &

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Local environmental conditions structured discrete fish assemblages in Arctic lagoons

Laske,

von Biela,

Stanek

et al. 2024

Polar Biol

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Rapid changes in sea ice extent and changes in freshwater inputs from land are rapidly changing the nature of Arctic estuarine ecosystems. In the Beaufort Sea, these nearshore habitats are known for their high productivity and mix of marine resident and diadromous fishes that have great subsistence value for Indigenous communities. There is, however, a lack of information on the spatial variation among Arctic nearshore fish communities as related to environmental drivers. In summers of 2017–2019, we sampled fishes in four estuarine ecosystems to assess community composition and relate fish abundance to temperature, salinity, and wind conditions. We found fish communities were heterogeneous over larger spatial extents with rivers forming fresh estuarine plumes that supported diadromous species (e.g., broad whitefish Coregonus nasus), while lagoons with reduced freshwater input and higher salinities were associated with marine species (e.g., saffron cod Eleginus gracilis). West–East directional winds accounted for up to 66% of the community variation, indicating importance of the wind-driven balance between fresh and marine water masses. Salinity and temperature accounted for up to 54% and 37% of the variation among lagoon communities, respectively. Recent sea ice declines provide more opportunity for wind to influence oceanographic conditions and biological communities. Current subsistence practices, future commercial fishing opportunities, and on-going oil and gas activities benefit from a better understanding of current fish community distributions. This work provides important data on fish spatial distributions and community composition, providing a basis for fish community response to changing climatic conditions and anthropogenic use.

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Projections of Extreme Ocean Waves in the Arctic and Potential Implications for Coastal Inundation and Erosion

Cited by 52 publications

References 62 publications

Sea Ice Retreat Contributes to Projected Increases in Extreme Arctic Ocean Surface Waves

Sea Ice Retreat Contributes to Projected Increases in Extreme Arctic Ocean Surface Waves

The 2017 Reversal of the Beaufort Gyre: Can Dynamic Thickening of a Seasonal Ice Cover During a Reversal Limit Summer Ice Melt in the Beaufort Sea?

Local environmental conditions structured discrete fish assemblages in Arctic lagoons

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