Wave observations from an array of directional buoys over the southern Brazilian coast

Pereira, Henrique P. P.; Violante-Carvalho, Nelson; Nogueira, Izabel Christina Martins; Babanin, Alexander V.; Liu, Qingxiang; Pinho, Uggo; Nascimento, Fabio; Ribeiro, Carlos Eduardo Parente

doi:10.1007/s10236-017-1113-9

Cited by 24 publications

(14 citation statements)

References 29 publications

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“…BETAMAX was set on 1.55 because a better fit on high quantiles in the Atlantic were observed. Result consistent with Pereira et al (2017). After that, Γ was continue tuned reaching the best results for Γ=-0.012m 2 s -3 .…”

Section: Wave Model Calibrationsupporting

confidence: 77%

New Wave Hindcast for the Rio De La Plata Estuary

Alonso¹,

Santoro²,

Solari³

2018

Int. Conf. Coastal. Eng.

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This paper present a wave hindcast for the RÃo de la Plata Estuary. It was based on the version 5.16 of the numerical wave model WAVEWATCH III Â®, forcing with CFSR winds and considering non-stationary water levels and currents obtained from the hydrodynamic model TELEMAC 2D. A multi-mission altimetry database processed by IFREMER was considered as the ground truth. It was taken as reference to calibrate and validate the wave model, and also to do a local validation of CFSR winds. Tuning the Î“ coefficient of the JONSWAP parametrization of dissipation by bottom friction (Sbot) and the BETAMAX coefficient of the energy input by wind (Sin), it was possible to correct the large negative BIAS in significant wave height (Hs) obtained with the default configuration. The hindcast cover the period 1985â€“2016 providing wave parameters with a spatial resolution of 1 km and a time step of 1 hour and full spectra at a 10 km offshore distance along the coast.

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Section: Wave Model Calibrationsupporting

confidence: 77%

New Wave Hindcast for the Rio De La Plata Estuary

Alonso¹,

Santoro²,

Solari³

2018

Int. Conf. Coastal. Eng.

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“…An extensive data set of in‐situ wind and wave observations was collected as well for validating reanalysis winds and our wave hindcasts. For simplicity, hereafter we will refer to both buoys and operating platforms as “buoys.” The data set consists of buoy data archived by multiple agencies, including the U.S. National Data Buoy Center (NDBC; Meindl & Hamilton, 1992), Coastal Data Information Program (CDIP; Seymour et al., 1985), Canadian Marine Environmental Data Section (MEDS), ECMWF (Bidlot, 2017; Appendix ), Chinese Ocean Monitoring Network (Wang et al., 2019), Korea Meteorological Agency (KMA), Korea Hydrographic and Oceanographic Agency (KHOA; Ha et al., 2019), Australian Ocean Data Network (AODN) and Brazilian Navy PNBOIA (Pereira et al., 2017). A few buoys located in the Southern Ocean were sourced from Ocean Observatories Initiative (Trowbridge et al., 2019) and MetOcean Solutions (see also Young et al., 2020).…”

Section: Satellite and In‐situ Observationsmentioning

confidence: 99%

Global Wave Hindcasts Using the Observation‐Based Source Terms: Description and Validation

Liu

Babanin

Rogers

et al. 2021

J Adv Model Earth Syst

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Global wave hindcasts are developed using the third generation spectral wave model WAVEWATCH III with the observation-based source terms (ST6) and a hybrid rectilinear-curvilinear, irregular-regular-irregular grid system (approximately at 0.25 0.25   ). Three distinct global hindcasts are produced: (a) a long-term hindcast forced by the ERA5 conventional winds 10 U and (b) two short-term hindcasts (2011)(2012)(2013)(2014)(2015)(2016)(2017)(2018)(2019) driven by the NCEP climate forecast system (CFS)v2 10 U and the ERA5 neutral winds 10,neu U, respectively. The input field for ice is sourced from the Ocean and Sea Ice Satellite Application Facility (OSI SAF) sea-ice concentration climate data records. These wave simulations, together with the driving wind forcing, are validated against extensive in-situ observations and satellite altimeter records. The performance of the ST6 wave hindcasts shows promising results across multiple wave parameters, including the conventional wave characteristics (e.g., wave height s H and wave period) and high-order spectral moments (e.g., the surface Stokes drift and mean square slope). The ERA5-based simulations generally present lower random errors, but the CFS-based run represents extreme sea states (e.g., 10 s H  m) considerably better. Novel wave parameters available in our hindcasts, namely the dominant wave breaking probability, wave-induced mixed layer depth, freak wave indexes and wavespreading factor, are further described and briefly discussed. Inter-comparisons of s H from the long-term (41 years) wave hindcast, buoy measurements and two different calibrated altimeter data sets highlight the inconsistency in these altimeter records arising from different calibration methodology. Significant errors in the low-frequency bins (period T  s) for both wave energy and directionality call for further model development.Plain Language Summary Ocean surface waves are fundamentally important for ocean engineering design, ship navigation, air-sea exchange of gas, heat, momentum and energy, upper ocean dynamics, and remote sensing of the ocean. Spectral wave modeling is an indispensable tool to estimate sea state information. In this study, we present new global wave hindcasts developed using the stateof-the-art model physics and numerics and the modern reanalysis winds and satellite sea ice records. It is demonstrated through validation against in-situ observations and altimeter records that the global wave hindcasts perform well across multiple parameters. Meanwhile, intercomparisons of wave height from the long-term hindcast, buoys, and altimeters reveal inconsistency and potential inhomogeneity in these different data sets. The wave hindcasts we developed, in combination with global wave databases published previously, will form a large ensemble of realizations of historical evolution of sea states simulated with distinct wave physics and wind forcing, which will help quantify sea states in real oceans more accurately. LIU ET AL.

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“…Because of that, an evaluation of the ERA5 wave parameters was performed using buoy data. For that, we used an array of moored buoys, which are part of the Global Ocean Observing System and Brazil's national buoy program (PNBOIA; see Pereira et al, 2017, for more details) and have measured meteo-oceanographic parameters since 2011. Among the entire data collection, three sites have better temporal availability: São Paulo, Santa Catarina and Rio Grande buoys.…”

Section: Datasetsmentioning

confidence: 99%

Intraseasonal variability of ocean surface wind waves in the western South Atlantic: the role of cyclones and the Pacific South American pattern

Sasaki

Gramcianinov²,

Castro³

et al. 2021

Weather Clim. Dynam.

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Abstract. Extratropical cyclones are known to generate extreme significant wave height (swh) values at the ocean surface in the western South Atlantic (wSA), which are highly influenced by intraseasonal scales. This work aims to investigate the importance of intraseasonal timescales (30–180 d) in the regional climatology of waves and its atmospheric forcing. The variability is explained by analyzing the storm track modulation due to westerly winds. These winds present timescales and spatial patterns compatible with the intraseasonal component of the Pacific South American (PSA) patterns. The analyses are made using ECMWF’s ERA5 from 1979 to 2019 and a database of extratropical cyclones based on the same reanalysis. Empirical orthogonal function (EOF) analyses of the 10 m zonal wind and swh are used to assess the regime of westerlies and waves in the wSA. The EOF1 of the 10 m zonal wind (u10) presented a core centered at 45∘ W and 40∘ S, while the EOF2 is represented by two cores organized into a seesaw pattern with a center between 30–40∘ S and another to the south of 40∘ S. Composites of cyclone genesis and track densities as well as swh fields were calculated based on the phases of both EOFs. In short, EOF phases presenting cores with a positive (negative) u10 anomaly provide a favorable (unfavorable) environment for cyclone genesis and track densities and, therefore, positive (negative) swh anomalies. The modulation of the cyclone tracks is significant for extreme values of the swh. The spatial patterns of the EOFs of u10 are physically and statistically consistent with 200 and 850 hPa geopotential height signals from the Pacific, indicating the importance of the remote influence of the PSA patterns over the wSA.

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Wave observations from an array of directional buoys over the southern Brazilian coast

Cited by 24 publications

References 29 publications

New Wave Hindcast for the Rio De La Plata Estuary

New Wave Hindcast for the Rio De La Plata Estuary

Global Wave Hindcasts Using the Observation‐Based Source Terms: Description and Validation

Intraseasonal variability of ocean surface wind waves in the western South Atlantic: the role of cyclones and the Pacific South American pattern

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