Wave hindcast in the North Pacific area considering the propagation of surface disturbances

Hisaki, Yukiharu

doi:10.1016/j.pocean.2018.06.003

Cited by 6 publications

(4 citation statements)

References 29 publications

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“…The resamples and computations of the skill metrics were conducted 1000 times, and the probabilities of C rmsd (H g , H e , U) < C rmsd (H g , H e , F), and |S sdn (H g , H e , U) − 1| > |S sdn (H g , H e , F) − 1| were evaluated from 1000 resamples. This method is almost the same as those in [34,36]. The probabilities of C rmsd (H g , H e , U) < C rmsd (H g , H e , F) were greater than 95% in nine buoys out of 10 buoys.…”

Section: Comparison Under Various Conditionsmentioning

confidence: 83%

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Intercomparison of Assimilated Coastal Wave Data in the Northwestern Pacific Area

Hisaki

2020

JMSE

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The assimilated coastal wave data are useful for wave climate study, coastal engineering, and design for marine disaster protection. However, the assimilated coastal wave data are few. Here, wave analysis data produced by the JMA (Japan Meteorological Agency) and ERA5 wave data were compared with GPS (Global Positioning System) buoy-measured wave data. In addition, the accuracy of ERA5 wave data for various conditions was investigated. The accuracy of JMA analysis wave height was better than that of ERA5 wave height. The ERA5 wave height was underestimated as the wave height increased. The accuracy of the ERA5 wave height was significantly different in fetch-unlimited and fetch-limited conditions. The difference of the skill metrics between fetch-unlimited and fetch-limited conditions was due to the overestimation of the fetch in the ERA5 grid. This result also applied to the wave period.

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Section: Comparison Under Various Conditionsmentioning

confidence: 83%

“…, F) − 1|, which can be compared across different data groups, is explored. The bootstrap method [33,34] is used for the validation. The effective sample size N e is evaluated by the method in [33,35], which is smaller than the number of comparisons N c (1 ≤ N e ≤ N c ) from the serial data of (H g , H e ).…”

Section: Comparison Under Various Conditionsmentioning

confidence: 99%

Intercomparison of Assimilated Coastal Wave Data in the Northwestern Pacific Area

Hisaki

2020

JMSE

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“…The locations of drifting buoys change because of currents; therefore, compared to moored buoys, the drifting buoys are unsuitable for investigating the accuracy of regionality, seasonality, or long-term trends in predicted data. Consequently, validation studies of wave prediction using data from drifting buoys are rare, e.g., References [1][2][3][4]. Nevertheless, using drifting buoys has advantages (aside from operational costs) because their positions are unrestricted compared with those of moored buoys.…”

Section: Introductionmentioning

confidence: 99%

Validation of Drifting Buoy Data for Ocean Wave Observation

Hisaki

2021

JMSE

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Drifting buoys collect wave data in the open ocean far from land and in areas with strong currents. However, the validation of the drifting buoy wave data is limited. Here, we compared the drifting buoy wave data, ERA5 wave data, and moored GPS buoy wave data. Data from 2009 to 2018 near the coast of Japan were used. The agreement of the drifting buoy-observed wave parameters with the moored GPS buoy-observed wave parameters is better than that of ERA5 wave parameters, which is statistically significant. In particular, the accuracy of the ERA5 wave heights tends to be lower where the ocean currents are fast. On the other hand, the agreement between the drifting buoy-observed wave heights and the moored GPS buoy-observed wave heights was good even in the areas with strong currents. It is confirmed that the drifting buoy wave data can be used as reference data for wave modeling study.

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“…Knowing the wave climate is crucial for a variety of applications, such as ocean wave research, coastal morphodynamics, navigation, and the planning of marine operations and offshore and coastal structures (Hisaki, ). Available evidence, for example in situ measurements and remotely sensed recordings, has increased to the extent that we can characterize the variability in surface ocean wave characteristics like wave heights, periods, and directions in addition to their means.…”

Section: Introductionmentioning

confidence: 99%

Wave climate projections along the Indian coast

Chowdhury

Behera

Reeve

2019

Intl Journal of Climatology

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Future changes in wave climate will influence the marine ecosystem, coastal erosion, design of coastal defences, operation of near-and off-shore structures, and coastal zone management policies and may further add to the potential vulnerabilities of coastal regions to projected sea level rise. Many studies have reported changes in the global wave characteristics under climate change scenarios, but it is important to project future changes in local/regional wave climate for smooth implementation of policies and preventing severe coastal erosion and flooding. In this study the regional wave climate along the Indian coast for two time slices, 2011-2040 and 2041-2070, is reported using an ensemble of near-surface winds generated by four different CMIP5 general circulation models (GCMs), under RCP4.5 scenario. Comparison of the wave climate for the two time slices shows an increase in wave heights and periods along much of the Indian coast, with the maximum wave heights increasing by more than 30% in some locations. An important finding is that at most locations along the east coast, wave periods are expected to increase by almost 20%, whereas along the west coast an increase of around 10% is expected. This will alter the distribution of wave energy at the shoreline through changes in wave refraction and diffraction, with potential implications for the performance and design of coastal structures and swash-aligned beaches. Furthermore, the computations show material changes in the directional distribution of waves. This is particularly important in determining the longshore transport of sediments and can lead to realignment of drift-aligned beaches, manifesting itself as erosion and/or siltation problems. This study is a preliminary contribution towards regional climate projections for the Indian Ocean region which are needed to plan and mitigate the impacts of future climate change. K E Y W O R D S climate change, coastal vulnerability, dynamical projections, Indian coast, surface ocean waves, wave climate variability

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Wave hindcast in the North Pacific area considering the propagation of surface disturbances

Cited by 6 publications

References 29 publications

Intercomparison of Assimilated Coastal Wave Data in the Northwestern Pacific Area

Intercomparison of Assimilated Coastal Wave Data in the Northwestern Pacific Area

Validation of Drifting Buoy Data for Ocean Wave Observation

Wave climate projections along the Indian coast

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