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1

Putri, Annisa Agustina Kurnia, Gusti Diansyah, and Wike Ayu Eka Putri. "Analisis Tinggi Gelombang Signifikan Berdasarkan Model Wavewatch-III di Pantai Alau-Alau, Kalianda, Lampung Selatan." Buletin Oseanografi Marina 11, no. 2 (2022): 123–30. http://dx.doi.org/10.14710/buloma.v11i2.39567.

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Perairan Pantai Alau-Alau merupakan daerah pesisir yang dimanfaatkan sebagai kegiatan pariwisata dan juga kegiatan perikanan seperti bagan perahu. Peramalan tinggi gelombang sangat berguna untuk menghindari kejadian kecelakaan kapal ataupun hantaman ombak besar di sekitar kawasan pantai. Tujuan dari penelitian ini adalah untuk menganalisis tinggi gelombang signifikan di wilayah Pantai Alau-Alau, Kalianda, Lampung Selatan dan menganalisis tingkat akurasi model Wavewatch-III BMKG (Badan Meteorologi Klimatologi dan Geofisika) dengan data lapangan. Data dari Model Wavewatch-III divisualisasi mengg
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2

Swain, J., PA Umesh, and AN Balchand. "WAM and WAVEWATCH-III intercomparison studies in the North Indian Ocean using Oceansat-2 Scatterometer winds." Journal of Ocean and Climate: Science, Technology and Impacts 9 (January 2019): 251601921986656. http://dx.doi.org/10.1177/2516019219866569.

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This paper presents the intercomparison of wave hindcasts using the third-generation models WAM and WAVEWATCH-III for the North Indian Ocean over 1° × 1° (latitude × longitude) grid resolutions, which reveals the first assessment of their relative performance through intercomparison of the model results. Hindcast wave parameters such as significant wave height, mean wave period, and swell wave height obtained from the simulations using Oceansat-2 scatterometer winds are analyzed to understand the quality and variability associated with the individual model outputs in the Indian Ocean. WAM and
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3

Lucero, Felipe, Caio Eadi Stringari, and Jean-François Filipot. "Improving WAVEWATCH III hindcasts with machine learning." Coastal Engineering 185 (October 2023): 104381. http://dx.doi.org/10.1016/j.coastaleng.2023.104381.

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4

Smith, Jane McKee, Ali Abdolali, Aron Roland, Heloise Michaud, Tyler J. Hesser, and Mary Anderson Bryant. "UNSTRUCTURED WAVEWATCH III DEVELOPMENTS FOR MULTISCALE MODELING." Coastal Engineering Proceedings, no. 38 (May 29, 2025): 91. https://doi.org/10.9753/icce.v38.waves.91.

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The US Army Engineer Research and Development Center (ERDC) is working collaboratively with the National Oceanic and Atmospheric Administration (NOAA), BGS ITandE GmbH, and the French Naval Hydrographic and Oceanographic Service (Shom) to extend the spectral wave modeling with WAVEWATCH III (WW3) (WW3DG 2019) from global and basin scales (e.g., ERDC Wave Information Studies hindcasting and NOAA forecasting) to local, nearshore processes into the surf zone. WW3 is undergoing rapid community development (Alves, et al. 2023). The unstructured, implicit solution option in WW3 provide flexibility a
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5

Chu, Peter C., Yiquan Qi, Yuchun Chen, Ping Shi, and Qingwen Mao. "South China Sea Wind-Wave Characteristics. Part I: Validation of Wavewatch-III Using TOPEX/Poseidon Data." Journal of Atmospheric and Oceanic Technology 21, no. 11 (2004): 1718–33. http://dx.doi.org/10.1175/jtech1661.1.

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Abstract A full-spectral third-generation ocean wind-wave model, Wavewatch-III, has been implemented in the South China Sea (SCS) for investigating wind-wave characteristics. This model was developed at the Ocean Modeling Branch of the National Centers for Environmental Prediction (NCEP). The NASA QuickSCAT data (0.25° resolution) 2 times daily were used to simulate the wind waves for the entire year of 2000. The significant wave heights from Wavewatch-III are compared to the TOPEX/Poseidon (T/P) significant wave height data over the satellite crossover points in SCS. The model errors of signi
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6

SUZUKI, Yoshimitsu, Tomotsuka TAKAYAMA, Yasusuke YOSHINAGA, et al. "WAVE REPRODUCTION PROPERTIES OF WAM AND WAVEWATCH III." Journal of Japan Society of Civil Engineers, Ser. B3 (Ocean Engineering) 72, no. 2 (2016): I_265—I_270. http://dx.doi.org/10.2208/jscejoe.72.i_265.

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7

Lee, Beng-Chun, Yang-Ming Fan, Laurence Zsu-Hsin Chuang, and Chia Chuen Kao. "Parametric Sensitivity Analysis of the WAVEWATCH III Model." Terrestrial, Atmospheric and Oceanic Sciences 20, no. 2 (2009): 425. http://dx.doi.org/10.3319/tao.2008.04.25.01(oc).

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8

Smith, Jane McKee, Tyler Hesser, Aron Roland, and Mary Bryant. "VALIDATION OF UNSTRUCTURED WAVEWATCH III FOR NEARSHORE WAVES." Coastal Engineering Proceedings, no. 36 (December 30, 2018): 55. http://dx.doi.org/10.9753/icce.v36.waves.55.

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Unstructured wave model grids in the nearshore coastal region provide flexibility and efficiency to resolve complex shorelines and high-gradient wave zones to drive nearshore circulation, wave setup and wave-driven sediment transport. Recent improvements to the unstructured version of WAVEWATCH III (WW3) (WW3DG 2016) to support nearshore application include an implicit solution scheme and domain decomposition for multi-scale spatial coverage over approximately three orders of magnitude. The hybrid approach to parallelization involves spectral partitioning for advection in geographical space an
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9

Kuznetsova, Alexandra, Georgy Baydakov, Vladislav Papko, et al. "Adjusting of Wind Input Source Term in WAVEWATCH III Model for the Middle-Sized Water Body on the Basis of the Field Experiment." Advances in Meteorology 2016 (2016): 1–13. http://dx.doi.org/10.1155/2016/8539127.

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Adjusting of wind input source term in numerical model WAVEWATCH III for the middle-sized water body is reported. For this purpose, the field experiment on Gorky Reservoir is carried out. Surface waves are measured along with the parameters of the airflow. The measurement of wind speed in close proximity to the water surface is performed. On the basis of the experimental results, the parameterization of the drag coefficient depending on the 10 m wind speed is proposed. This parameterization is used in WAVEWATCH III for the adjusting of the wind input source term within WAM 3 and Tolman and Cha
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10

Janjić, Jelena, Sarah Gallagher, and Frédéric Dias. "Case study of the winter 2013/2014 extreme wave events off the west coast of Ireland." Advances in Science and Research 15 (July 26, 2018): 145–57. http://dx.doi.org/10.5194/asr-15-145-2018.

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Abstract. Using the third generation WAVEWATCH III wave model in an unstructured formulation, and driven by HARMONIE-AROME mesoscale model hourly winds with a 2.5 km horizontal resolution, we reproduce the winter storms of 2013/2014 and analyse their effect on the western coastline of Ireland. WAVEWATCH III was forced at its ocean boundaries by directional wave spectra obtained from the ECMWF ERA-Interim re-analysis dataset. The wave model has a high resolution grid (up to 225 m resolution in the nearshore) with around 20 000 nodes, producing an abundance of important wave parameters outputted
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11

Sangalugeme, Chuki, Philbert Luhunga, Agness Kijazi, and Hamza Kabelwa. "Validation of Operational WAVEWATCH III Wave Model Against Satellite Altimetry Data Over South West Indian Ocean Off-Coast of Tanzania." Applied Physics Research 10, no. 4 (2018): 55. http://dx.doi.org/10.5539/apr.v10n4p55.

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The WAVEWATCH III model is a third generation wave model and is commonly used for wave forecasting over different oceans. In this study, the performance of WAVEWATCH III to simulate Ocean wave characteristics (wavelengths, and wave heights (amplitudes)) over the western Indian Ocean in the Coast of East African countries was validated against satellite observation data. Simulated significant wave heights (SWH) and wavelengths over the South West Indian Ocean domain during the month of June 2014 was compared with satellite observation. Statistical measures of model performance that includes bia
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12

Chen, Wei, Jian Shi, Jie Chen, Wenjing Zhang, and Shaoze Zhang. "Optimizing wave simulation to improve the ocean circulation model in the North Pacific Ocean." Journal of Physics: Conference Series 2718, no. 1 (2024): 012032. http://dx.doi.org/10.1088/1742-6596/2718/1/012032.

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Abstract In this paper, the simulation performance of two source terms, ST4 and ST6, of the wave model WAVEWATCH III on significant wave heights is investigated in the North Pacific Ocean, and the root mean square error (RMSE), correlation coefficient (R) and mean absolute error (E MAE) were compared between them, and all indices showed that the waves was better modelled by using ST4 in the North Pacific region. Based on the ST4 source term scheme, the Stokes drift is calculated from the wave elements simulated by WAVEWATCH III, and is added to the momentum equation of the SBPOM circulation mo
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13

Tolman, Hendrik L. "Distributed-memory concepts in the wave model WAVEWATCH III." Parallel Computing 28, no. 1 (2002): 35–52. http://dx.doi.org/10.1016/s0167-8191(01)00130-2.

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14

Mentaschi, Lorenzo, Giovanni Besio, Federico Cassola, and Andrea Mazzino. "Performance evaluation of Wavewatch III in the Mediterranean Sea." Ocean Modelling 90 (June 2015): 82–94. http://dx.doi.org/10.1016/j.ocemod.2015.04.003.

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15

Umesh, P. A., and Manasa R. Behera. "Performance evaluation of input-dissipation parameterizations in WAVEWATCH III and comparison of wave hindcast with nested WAVEWATCH III-SWAN in the Indian Seas." Ocean Engineering 202 (April 2020): 106959. http://dx.doi.org/10.1016/j.oceaneng.2020.106959.

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16

Kuznetsova, Alexandra, Georgy Baydakov, Alexander Dosaev, and Yuliya Troitskaya. "Drag Coefficient Parameterization under Hurricane Wind Conditions." Water 15, no. 10 (2023): 1830. http://dx.doi.org/10.3390/w15101830.

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The influence of small-scale processes at the ocean–atmosphere boundary layer such as spray and foam on the surface waves prediction is studied. Estimates of the effect of including the exact number of specific fragmentation “parachute” type in the spray on the resulting drag coefficient is shown. For the estimates, the numerical simulations within WAVEWATCH III wave model are performed. The parameterizations of wind input are tested within WAVEWATCH III wave model: default ST4 and ST6 parameterizations and the ST1 and ST6 parameterizations used together with the implemented drag coefficient p
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17

Borges, Dayanis Montero, Humberto Varona, and Marcelo Alonso. "Database of extreme waves generated during the passage of a cold front in Rio Grande do Sul coast, southern Brazil." Latin American Data in Science 1, no. 3 (2021): 87–94. http://dx.doi.org/10.53805/lads.v1i3.34.

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This datapaper supports the use of a database generated from wavefield simulations with the WAVEWATCH III model in waters off the coast of Rio Grande do Sul in the South Atlantic Ocean. In the WAVEWATCH III simulations, three domains are generated as a part of a numerical experiment to set up the best configuration. This database includes all input and output files for the two best-fit simulations. Bathymetry and wind files at 10 m above the surface are available as input files. The period of simulation and non-stationary wind data input corresponds to March 22-28, 2016. The date was chosen be
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18

Li, Qing, Adrean Webb, Baylor Fox-Kemper, et al. "Langmuir mixing effects on global climate: WAVEWATCH III in CESM." Ocean Modelling 103 (July 2016): 145–60. http://dx.doi.org/10.1016/j.ocemod.2015.07.020.

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19

Pramita, Ayu W., Denny N. Sugianto, Indra B. Prasetyawan, Roni Kurniawan, and Alfan S. Praja. "POLA TINGGI GELOMBANG DI LAUT JAWA MENGGUNAKAN MODEL WAVEWATCH-III." Jurnal Meteorologi dan Geofisika 21, no. 1 (2020): 21. http://dx.doi.org/10.31172/jmg.v21i1.609.

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20

Qi, Peng, and Lei Cao. "Establishment and tests of EnOI assimilation module for WAVEWATCH III." Chinese Journal of Oceanology and Limnology 33, no. 5 (2015): 1295–308. http://dx.doi.org/10.1007/s00343-015-4282-8.

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21

Barbariol, Francesco, Jose-Henrique G. M. Alves, Alvise Benetazzo, et al. "Numerical modeling of space-time wave extremes using WAVEWATCH III." Ocean Dynamics 67, no. 3-4 (2017): 535–49. http://dx.doi.org/10.1007/s10236-016-1025-0.

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22

Smith, Jane McKee, Tyler J. Hesser, Ali Abdolali, Mary Anderson Bryant, and Aron Roland. "ADVANCES IN UNSTRUCTURED WAVEWATCH III AND APPLICATIONS TO NEARSHORE WAVES." Coastal Engineering Proceedings, no. 37 (September 1, 2023): 40. http://dx.doi.org/10.9753/icce.v37.waves.40.

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The spectral wave generation and propagation model WAVEWATCH III (WW3) (WW3DG 2019) is undergoing rapid community development to extend capability and nearshore modeling applicability. An option for unstructured grids and implicit solution provides WW3 with the flexibility and efficiency to resolve complex shorelines and high-gradient wave zones to drive nearshore circulation, wave setup, and wave-driven sediment transport with multi-scale spatial coverage over approximately three orders of magnitude. A hybrid approach to parallelization uses spectral partitioning for advection in geographical
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23

Chawla, Arun, Hendrik L. Tolman, Vera Gerald, et al. "A Multigrid Wave Forecasting Model: A New Paradigm in Operational Wave Forecasting." Weather and Forecasting 28, no. 4 (2013): 1057–78. http://dx.doi.org/10.1175/waf-d-12-00007.1.

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Abstract A new operational wave forecasting system has been implemented at the National Centers for Environmental Prediction (NCEP) using the third public release of WAVEWATCH III. The new system uses a mosaic of grids with two-way nesting in a single model. This global system replaces a previous operational wave modeling suite (based on the second release of WAVEWATCH III). The new forecast system consists of nine grids at different resolutions to provide the National Weather Service (NWS) and NCEP centers with model guidance of suitable resolution for all areas where they have the responsibi
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24

Liu, Jin, Ian Young, and Alberto Meucci. "THE WAVE CLIMATE OF SOUTH-EAST AUSTRALIA AND FUTURE WAVE PROJECTION BY THE END OF 21ST CENTURY." Coastal Engineering Proceedings, no. 37 (September 1, 2023): 1. http://dx.doi.org/10.9753/icce.v37.waves.1.

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In this study, high-resolution unstructured ocean wave datasets based on a third-generation wave model (WAVEWATCH III, WW3) were developed for south-east Australia. Through this study, we aim to understand the wave climate based on hindcast model datasets and develop future wave projections by the end of the 21st century.
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25

Protsenko, S. V. "Forecasting the development dynamics of coastal systems utilizing remote sensing data." E3S Web of Conferences 549 (2024): 07006. http://dx.doi.org/10.1051/e3sconf/202454907006.

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The article addresses the task of adapting the third-generation mathematical wind-wave model, WAVEWATCH III, for constructing predictive scenarios of the Azov Sea development based on satellite imagery data. In addition to the effective utilization of remote sensing data, WAVEWATCH III enables modeling using multicellular grids, thereby reducing the temporal constraints required for forecasting hydrophysical phenomena, including hazardous and catastrophic events. Within the article, modeling of the dynamics of the coastal system of the Sea of Azov is conducted based on remote sensing data. The
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Aror, Ricky Daniel, Wilhelmina Patty, and Andri Ramdhani. "Utilization of Wavewatch III Model Output Data for High Wave Analysis." ILMU KELAUTAN: Indonesian Journal of Marine Sciences 24, no. 3 (2019): 132. http://dx.doi.org/10.14710/ik.ijms.24.3.132-138.

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This study discusses the occurrence of extreme waves in North Sulawesi waters from 17 to 24 June 2016 using Wavewatch III (WW3) model output data with resolution 0.125o x 0.125o extracted from MIDAS-BMKG. The extracted WW3 data is mapped using ArcMap and presented in graphical form. Based on the results of the study, the significant wave height is in the range of 0.0 to 1.0 m and the average wind speed ranges from 0 to 15 knots in the early phase of 17-19 June 2016. Significant wave increases in the peak phase of 20-22 June 2016 that reaches 1.5 - 2.0 m and average wind speeds reach 25 knots.
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Waters, Jennifer, Lucy R. Wyatt, Judith Wolf, and Adrian Hines. "Data assimilation of partitioned HF radar wave data into Wavewatch III." Ocean Modelling 72 (December 2013): 17–31. http://dx.doi.org/10.1016/j.ocemod.2013.07.003.

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28

Smith, Jane McKee, Tyler Hesser, Mary Anderson Bryant, Aron Roland, and Andrew Cox. "ADVANCES IN THE UNSTRUCTURED WAVEWATCH III AND APPLICATION TO HURRICANE DORIAN." Coastal Engineering Proceedings, no. 36v (December 28, 2020): 42. http://dx.doi.org/10.9753/icce.v36v.waves.42.

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The spectral wave generation and propagation model WAVEWATCH III (WW3) is undergoing rapid development to extend capability and applicability. An option for unstructured grids and implicit solution provides WW3 with the flexibility and efficiency to resolve complex shorelines and high-gradient wave zones to drive nearshore circulation, wave setup, and wave-driven sediment transport with multi-scale spatial coverage over approximately three orders of magnitude. The model is compatible with community-based coupling infrastructure to facilitate two-way coupling with circulation models for simulat
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29

Ikuyajolu, Olawale James, Luke Van Roekel, Steven R. Brus, Erin E. Thomas, Yi Deng, and Sarat Sreepathi. "Porting the WAVEWATCH III (v6.07) wave action source terms to GPU." Geoscientific Model Development 16, no. 4 (2023): 1445–58. http://dx.doi.org/10.5194/gmd-16-1445-2023.

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Abstract. Surface gravity waves play a critical role in several processes, including mixing, coastal inundation, and surface fluxes. Despite the growing literature on the importance of ocean surface waves, wind–wave processes have traditionally been excluded from Earth system models (ESMs) due to the high computational costs of running spectral wave models. The development of the Next Generation Ocean Model for the DOE’s (Department of Energy) E3SM (Energy Exascale Earth System Model) Project partly focuses on the inclusion of a wave model, WAVEWATCH III (WW3), into E3SM. WW3, which was origin
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30

Ostritz, Frederico Francisco, Nelson Violante de Carvalho, and Leonardo Maturo Marques da Cruz. "Estimativas de um modelo de geração e propagação de ondas empregando campos de vento com diferentes resoluções espaciais e temporais." Revista Brasileira de Meteorologia 27, no. 3 (2012): 315–28. http://dx.doi.org/10.1590/s0102-77862012000300006.

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O presente trabalho apresenta uma comparação entre algumas rodadas do modelo numérico de geração e propagação de ondas Wavewatch III empregando campos de vento com diferentes resoluções espaciais e temporais em uma região tropical do oceano Atlântico Sul. Os campos de vento utilizados de entrada são os da Reanálise do NCEP (com resolução espacial de cerca de 2º e resolução temporal de 6 horas), do Global Forecast System (resolução espacial de 1º e resolução temporal de 6 horas), bem como os campos de maior resolução espacial e temporal de um modelo de mesoescala (Mesoscale Modeling System), co
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31

Myslenkov, Stanislav, Alexander Zelenko, Yuriy Resnyanskii, Victor Arkhipkin, and Ksenia Silvestrova. "Quality of the Wind Wave Forecast in the Black Sea Including Storm Wave Analysis." Sustainability 13, no. 23 (2021): 13099. http://dx.doi.org/10.3390/su132313099.

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This paper presents the results of wind wave forecasts for the Black Sea. Three different versions utilized were utilized: the WAVEWATCH III model with GFS 0.25 forcing on a regular grid, the WAVEWATCH III model with COSMO-RU07 forcing on a regular grid, and the SWAN model with COSMO-RU07 forcing on an unstructured grid. AltiKa satellite altimeter data were used to assess the quality of wind and wave forecasts for the period from 1 April to 31 December 2017. Wave height and wind speed forecast data were obtained with a lead time of up to 72 h. The presented models provide an adequate forecast
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Pham Tien, Dat, Huan Nguyen Minh, and Anh Nguyen Phuong. "Numerical modeling and validating waves generated by typhoons in the East Vietnam Sea using satellite data." Tạp chí Khoa học và Công nghệ Biển 21, no. 2 (2021): 107–20. http://dx.doi.org/10.15625/1859-3097/16408.

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Calculating waves generated by typhoons is one of the most important tasks for wave forecasting at a stormy region like the East Vietnam Sea. It is, however, difficult to access the accuracy of calculated wave heights due to the lack of observed data. An approach of combining numerical models and satellite data has been widely used. In this study, we used the WAVEWATCH III model to stimulate wave fields caused by three strong typhoons: Damrey (2005), Ketsana (2009) and Haiyan (2013), then compared significant wave heights with the merged satellite observations. The results show that the BIAS v
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33

Sampson, Charles R., Paul A. Wittmann, Efren A. Serra, Hendrik L. Tolman, Jessica Schauer, and Timothy Marchok. "Evaluation of Wave Forecasts Consistent with Tropical Cyclone Warning Center Wind Forecasts." Weather and Forecasting 28, no. 1 (2013): 287–94. http://dx.doi.org/10.1175/waf-d-12-00060.1.

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Abstract An algorithm to generate wave fields consistent with forecasts from the official U.S. tropical cyclone forecast centers has been made available in near–real time to forecasters since summer 2007. The algorithm removes the tropical cyclone from numerical weather prediction model surface wind field forecasts, replaces the removed winds with interpolated values from surrounding grid points, and then adds a surface wind field generated from the official forecast into the background. The modified wind fields are then used as input into the WAVEWATCH III model to provide seas consistent wit
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34

Григорьева, В. Г., С. К. Гулев та В. Д. Шармар. "Верификация глобальной спектральной волновой модели WAVEWATCH III по данным попутных судовых наблюдений". Океанология 60, № 1 (2020): 14–26. http://dx.doi.org/10.31857/s003015742001013x.

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Zheng, Zhenjun, Xiaozhou Ma, Xuezhi Huang, Yuxiang Ma, and Guohai Dong. "Wave forecasting within a port using WAVEWATCH III and artificial neural networks." Ocean Engineering 255 (July 2022): 111475. http://dx.doi.org/10.1016/j.oceaneng.2022.111475.

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36

Lim, Hye Min, Kyeong Ok Kim, Hanna Kim, Sang Myeong Oh, and Young Ho Kim. "Sensitivity of Data Assimilation Configuration in WAVEWATCH III applying Ensemble Optimal Interpolation." Journal of the Korean earth science society 45, no. 4 (2024): 349–62. http://dx.doi.org/10.5467/jkess.2024.45.4.349.

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37

Mora-Escalante, Rodney E., and Juan Pablo Ureña-Mora. "Simulación de oleaje en los alrededores de la Isla del Coco, Costa Rica." Revista de Biología Tropical 68, S1 (2020): S198—S212. http://dx.doi.org/10.15517/rbt.v68is1.41181.

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Introducción: La Isla del Coco por su ubicación en el océano Pacífico y en aguas profundas, periódicamente arriban olas energéticas que se originan en el Océano del Sur. La isla actúa como un abrigo disipando parte de la energía de las olas que llegan a la costa pacífica de Costa Rica. Objetivo: El objetivo del trabajo es caracterizar las condiciones generales del oleaje a través de la simulación numérica del oleaje en el Pacífico Tropical del Este (PTE), con especial interés en la Isla del Coco. Métodos: Las olas se propagan con el modelo espectral de oleaje WAVEWATCH III. Se usa en el modelo
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Kuznetsova, A. M., G. A. Baydakov, and Yu I. Troitskaya. "Study of wind and wave parameters at the Gorky reservoir: field measurements and numerical simulation." Izvestiâ Akademii nauk SSSR. Fizika atmosfery i okeana 60, no. 3 (2024): 357–72. https://doi.org/10.31857/s0002351524030081.

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The paper provides an overview of a series of articles aimed at creating a regional model based on the WAVEWATCH III spectral wave model adapted to the conditions of an inland water body using the WRF atmospheric model. Adaptation and verification of the models was carried out on the basis of the results of a series of field experiments to study the wind-wave regime of the Gorky reservoir performed in 2012–2019 using an autonomous buoy station based on the Froude oceanographic buoy. Within the framework of the WAVEWATCH III model, an analysis was made of the influence on the simulation result
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39

Myslenkov ., S. A. "Modeling of the wind waves in the Laptev, East Siberian and Chukchi seas." Hydrometeorological research and forecasting 1 (March 30, 2023): 87–101. http://dx.doi.org/10.37162/2618-9631-2023-1-87-101.

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The paper presents an analysis of wind wave parameters in the Laptev, East Siberian and Chukchi seas based on the results of numerical experiments with the WAVEWATCH III wave model for a period from 1979 to 2021. Wave modeling was carried out using an unstructured computational grid with a high resolution (up to 800 m) in the coastal zone. The NCEP/CFSR/CFSv2 reanalysis was used as wind forcing. The maps of the long-term mean values of the wave height, wave length and period were obtained. For the several points in the central part of each sea, the mean annual values of wave heights are calcul
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40

Zheng, Kaiwen, Jian Sun, Changlong Guan, and Weizeng Shao. "Analysis of the Global Swell and Wind Sea Energy Distribution Using WAVEWATCH III." Advances in Meteorology 2016 (2016): 1–9. http://dx.doi.org/10.1155/2016/8419580.

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Over the past several decades, an increasing number of studies have focused on the global view of swell and wind sea climate. However, our understanding of wind sea and swell is still incomplete as is the lack of an integrated description for all the wave components. In this paper, the European Centre for Medium-Range Weather Forecasts (ECMWF) Era-medium wind data is used to run the WAVEWATCH III model and the global wave fields in 2010 are reproduced. Using the spectra energy partition (SEP) method, two-dimensional wave spectra were separated and detailed information for the components of win
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Kuznetsova, A., G. Baydakov, D. Sergeev, and Yu Troitskaya. "High Resolution Waves and Weather Forecasts Using Adapted Wavewatch III and WRF Models." Journal of Physics: Conference Series 1163 (February 2019): 012031. http://dx.doi.org/10.1088/1742-6596/1163/1/012031.

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Zhou, Liangming, Zhanbin Li, Lin Mou, and Aifang Wang. "Numerical simulation of wave field in the South China Sea using WAVEWATCH III." Chinese Journal of Oceanology and Limnology 32, no. 3 (2014): 656–64. http://dx.doi.org/10.1007/s00343-014-3155-x.

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Zou, Tao, and Miroslaw Lech Kaminski. "Applicability of WaveWatch-III wave model to fatigue assessment of offshore floating structures." Ocean Dynamics 66, no. 9 (2016): 1099–108. http://dx.doi.org/10.1007/s10236-016-0977-4.

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Hanson, Jeffrey L., Barbara A. Tracy, Hendrik L. Tolman, and R. Douglas Scott. "Pacific Hindcast Performance of Three Numerical Wave Models." Journal of Atmospheric and Oceanic Technology 26, no. 8 (2009): 1614–33. http://dx.doi.org/10.1175/2009jtecho650.1.

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Abstract Although mean or integral properties of wave spectra are typically used to evaluate numerical wave model performance, one must look into the spectral details to identify sources of model deficiencies. This creates a significant problem, as basin-scale wave models can generate millions of independent spectral values. To facilitate selection of a wave modeling technology for producing a multidecade Pacific hindcast, a new approach was developed to reduce the spectral content contained in detailed wave hindcasts to a convenient set of performance indicators. The method employs efficient
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Xu, Yue, and Xiping Yu. "Enhanced ocean wave modeling by including effect of breaking under both deep- and shallow-water conditions." Geoscientific Model Development 16, no. 10 (2023): 2811–31. http://dx.doi.org/10.5194/gmd-16-2811-2023.

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Abstract. Accurate description of the wind energy input into ocean waves is crucial to ocean wave modeling and a physics-based consideration on the effect of wave breaking is absolutely necessary to obtain such an accurate description. This study evaluates the performance of an improved formula recently proposed by Xu and Yu (2020), who took into account not only the effect of breaking but also the effect of airflow separation on the leeside of steep wave crests in a reasonably consistent way. Numerical results are obtained through coupling an enhanced atmospheric wave boundary layer model wit
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Sun, Rui, Alison Cobb, Ana B. Villas Bôas, et al. "Waves in SKRIPS: WAVEWATCH III coupling implementation and a case study of Tropical Cyclone Mekunu." Geoscientific Model Development 16, no. 12 (2023): 3435–58. http://dx.doi.org/10.5194/gmd-16-3435-2023.

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Abstract. In this work, we integrated the WAVEWATCH III model into the regional coupled model SKRIPS (Scripps–KAUST Regional Integrated Prediction System). The WAVEWATCH III model is implemented with flexibility, meaning the coupled system can run with or without the wave component. In our implementations, we considered the effect of Stokes drift, Langmuir turbulence, sea surface roughness, and wave-induced momentum fluxes. To demonstrate the impact of coupling we performed a case study using a series of coupled and uncoupled simulations of Tropical Cyclone Mekunu, which occurred in the Arabia
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Tindaon, Godwin Parulian, Rignolda Djamaluddin, Hermanto W. K. Manengkey, and Edwin L. A. Ngangi. "KARAKTERISTIK ARAH DAN TINGGI GELOMBANG SIGNIFIKAN DI LAUT SULAWESI." JURNAL PESISIR DAN LAUT TROPIS 10, no. 3 (2022): 356–67. http://dx.doi.org/10.35800/jplt.10.3.2022.55020.

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The Celebes Sea is an important area in terms of utilization of coastal and sea space. This study aims to describe the direction characteristics and significant wave heights in several areas of the Celebes Sea in various seasons and to analyze the characteristics of daily and monthly waves. The wave data used in this study is the result of Wavewatch-III wave predictions with a wave data duration of 2 years, January 2020 - December 2021. The areas that are the observation area are Station 1 (3°N 121°E), Station 2 (3° N 123° E), and Station 3 (3° N 125° E). Through the spatial-temporal analysis
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Panfilova, M. A., A. M. Kuznetsova, G. A. Baydakov, Yu I. Troitskaya, and V. Yu Karaev. "The method of comparison of WAVEWATCH III model calculation results with the data of Ka-band radar." Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa 17, no. 7 (2020): 9–18. http://dx.doi.org/10.21046/2070-7401-2020-17-7-9-18.

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Grossmann-Matheson, Guisela, Ian Young, Jose-Henrique Alves, and Alberto Meucci. "COMPUTATIONALLY EFFICIENT TROPICAL CYCLONE PARAMETRIC WIND-WAVE MODEL." Coastal Engineering Proceedings, no. 37 (September 1, 2023): 5. http://dx.doi.org/10.9753/icce.v37.waves.5.

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Waves generated by tropical cyclones (TCs) can cause damage to offshore structures and coastal settlements and play an important role in the design criteria for engineering projects, risk assessments and insurance purposes. Developing a rapid and simple way to estimate the wave heights associated with TCs has both a social and an economical advantage. The present study aims to develop a parametric TC wave prediction model, based on data generated by numerous simulations with a validated version of the WAVEWATCH III (WW3) spectral wave model (WW3DG, 2019).
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Alves, Jose-Henrique G. M., Arun Chawla, Hendrik L. Tolman, David Schwab, Gregory Lang, and Greg Mann. "The Operational Implementation of a Great Lakes Wave Forecasting System at NOAA/NCEP*." Weather and Forecasting 29, no. 6 (2014): 1473–97. http://dx.doi.org/10.1175/waf-d-12-00049.1.

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Abstract The development of a Great Lakes wave forecasting system at NOAA’s National Centers for Environmental Prediction (NCEP) is described. The system is an implementation of the WAVEWATCH III model, forced with atmospheric data from NCEP’s regional Weather Research and Forecasting (WRF) Model [the North American Mesoscale Model (NAM)] and the National Digital Forecast Database (NDFD). Reviews are made of previous Great Lakes wave modeling efforts. The development history of NCEP’s Great Lakes wave forecasting system is presented. A performance assessment is made of model wind speeds, as we
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