Bibliografie tematiche / Wave forecasting

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Letteratura scientifica selezionata sul tema "Wave forecasting"

Autore: Grafiati
Pubblicato: 4 giugno 2021
Ultima modifica: 19 febbraio 2022

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Articoli di riviste sul tema "Wave forecasting"

1

Arthur, Robert S. "WAVE FORECASTING AND HINDCASTING." Coastal Engineering Proceedings 1, no. 1 (May 12, 2010): 8. http://dx.doi.org/10.9753/icce.v1.8.

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As a result of wartime research on ocean surface waves a method has been available since 1943 for the prediction of wave characteristics of interest to engineers (O'Brien and Johnson, 1947). The initial stimulus for the development came during the planning of the invasion of North Africa, and the methods subsequently devised were later used in a number of amphibious operations (Bates, 1949). The same techniques have found useful peacetime application in problems connected with coastal engineering. Much of the application to date has consisted in applying wave prediction techniques to historica
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Bretschneider, C. L. "REVISED WAVE FORECASTING RELATIONSHIPS." Coastal Engineering Proceedings 1, no. 2 (January 1, 2000): 1. http://dx.doi.org/10.9753/icce.v2.1.

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Data on the generation and decay of wind-generated gravity waves have been collected for several years by the University of California. These data together with the original data by Sverdrup and Munk have been analyzed, and the results were presented in dimensionless graphs suitable for use in wave forecasting (Bretschneider, 1951). No analysis was made of the effect of following or opposing winds.
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Bretschneider, C. L. "REVISIONS IN WAVE FORECASTING: DEEP AND SHALLOW WATER." Coastal Engineering Proceedings 1, no. 6 (January 29, 2011): 3. http://dx.doi.org/10.9753/icce.v6.3.

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During the past six years since the latest revisions in wave forecasting (Bretschneider 1951) were made, much information has become available such that another revision is in order. An abundance of published (and unpublished) accounts of wave generation and decay in both deep and shallow water from various sources, as well as new ideas in the art of wave forecasting, are used in this revision. Deep water wave forecasting relationships, relationships for the generation of wind waves in shallow water of constant depth, and techniques for forecasting wind waves over the Continental Shelf are inc
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Shutts, Glenn. "Operational lee wave forecasting." Meteorological Applications 4, no. 1 (March 1997): 23–35. http://dx.doi.org/10.1017/s1350482797000340.

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Chawla, Arun, Hendrik L. Tolman, Vera Gerald, Deanna Spindler, Todd Spindler, Jose-Henrique G. M. Alves, Degui Cao, Jeffrey L. Hanson, and Eve-Marie Devaliere. "A Multigrid Wave Forecasting Model: A New Paradigm in Operational Wave Forecasting." Weather and Forecasting 28, no. 4 (July 30, 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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Simpson, Alexandra, Merrick Haller, David Walker, Patrick Lynett, and David Honegger. "Wave-by-Wave Forecasting via Assimilation of Marine Radar Data." Journal of Atmospheric and Oceanic Technology 37, no. 7 (July 1, 2020): 1269–88. http://dx.doi.org/10.1175/jtech-d-19-0127.1.

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AbstractThis work describes a phase-resolving wave-forecasting algorithm that is based on the assimilation of marine radar image time series. The algorithm is tested against synthetic data and field observations. The algorithm couples X-band marine radar observations with a phase-resolving wave model that uses the linear mild slope equations for reconstruction of water surface elevations over a large domain of O(km) and a prescribed time window of O(min). The reconstruction also enables wave-by-wave forecasting through forward propagation in space and time. Marine radar image time series provi
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Chen, Shien-Tsung. "Probabilistic forecasting of coastal wave height during typhoon warning period using machine learning methods." Journal of Hydroinformatics 21, no. 2 (February 4, 2019): 343–58. http://dx.doi.org/10.2166/hydro.2019.115.

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Abstract This study applied machine learning methods to perform the probabilistic forecasting of coastal wave height during the typhoon warning period. The probabilistic forecasts comprise a deterministic forecast and the probability distribution of a forecast error. A support vector machine was used to develop a real-time forecasting model for generating deterministic wave height forecasts. The forecast errors of deterministic forecasting were then used as a database to generate probabilistic forecasts by using the modified fuzzy inference model. The innovation of the modified fuzzy inference
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Janssen, Peter A. E. M., and Jean-Raymond Bidlot. "Progress in Operational Wave Forecasting." Procedia IUTAM 26 (2018): 14–29. http://dx.doi.org/10.1016/j.piutam.2018.03.003.

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Deo, M. C., A. Jha, A. S. Chaphekar, and K. Ravikant. "Neural networks for wave forecasting." Ocean Engineering 28, no. 7 (July 2001): 889–98. http://dx.doi.org/10.1016/s0029-8018(00)00027-5.

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Monastersky, Richard. "Tsunami forecasting: The next wave." Nature 483, no. 7388 (March 2012): 144–46. http://dx.doi.org/10.1038/483144a.

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Tesi sul tema "Wave forecasting"

1

Cohen, Jennifer Esther. "Theory of turbulent wind over fast and slow waves." Thesis, University of Cambridge, 1997. https://www.repository.cam.ac.uk/handle/1810/283717.

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Coşkun, Mustafa. "Atmospheric short wave - long wave trough interaction with associated surface cyclone development /." free to MU campus, to others for purchase, 2003. http://wwwlib.umi.com/cr/mo/fullcit?p3115537.

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Monk, Kieran. "Forecasting for control and environmental impacts of wave energy converters." Thesis, University of Plymouth, 2016. http://hdl.handle.net/10026.1/5292.

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This work is divided in to two distinct parts. In the first part a model is developed to assess the redistribution of wave energy about an offshore array of overtopping type wave energy converters. The model is based on a classical analytical solution for diffraction about a breakwater which is modified to consider an array of dissipating, reflecting and transmitting breakwater segments, which are used to approximate an overtopping type WEC array. The model is computationally efficient and phase resolving which allows the effect of wave scattering to be investigated for large domains with high
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Coughlin, Joseph D. "Forecasting the onset and intensity of vertically propagating mountain waves over the Alps." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2005. http://library.nps.navy.mil/uhtbin/hyperion/05Mar%5FCoughlin.pdf.

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Pallarès, López Elena. "High-resolution wave forecasting : the Catalan coast case : modelling, coupling and validation." Doctoral thesis, Universitat Politècnica de Catalunya, 2016. http://hdl.handle.net/10803/397750.

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It is widely known that wind and wave predictions in the nearshore are less precise for semi enclosed domains than in the open ocean. The Catalan coast is a clear example of this situation, with a wave climate controlled by short fetches, complex bathymetry, high wind field variability in time and space, and sea and swell waves combined that generate bimodal spectra. These characteristics, typical for a semi-enclosed basin, limit the reliability of wave predictions in the area, with errors on the significant wave height around 10% and a clear under-prediction of the wave period with errors aro
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Alves, Jose Henrique Gomes de Mattos Mathematics UNSW. "A Saturation-Dependent Dissipation Source Function for Wind-Wave Modelling Applications." Awarded by:University of New South Wales. Mathematics, 2000. http://handle.unsw.edu.au/1959.4/17786.

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This study reports on a new formulation of the spectral dissipation source term Sds for wind-wave modelling applications. This new form of Sds features a nonlinear dependence on the local wave spectrum, expressed in terms of the azimuthally integrated saturation parameter B(k)=k^4 F(k). The basic form of this saturation-dependent Sds is based on a new framework for the onset of deep-water wave breaking due to the nonlinear modulation of wave groups. The new form of Sds is succesfully validated through numerical experiments that include exact nonlinear computations of fetch-limited wind-wave ev
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Alfredsson, Johan, and Lina Augustsson. "The Next Wave of the Suit-Era : A Forecasting Model of the Men’s Suit." Thesis, Högskolan i Borås, Akademin för textil, teknik och ekonomi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:hb:diva-12731.

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Background   By the beginning of the 20th century, the men’s suit entered the menswear market as one the most important fashion garments everdevised. At the same time, fashion became mainly a female engagement, resulting in an under representation of men’s fashion through out the past decade. Relating to the textile and apparel industry, fashion forecasting has become an increasingly important business activity. But the nature of fashion forecasting and the historical neglecting of the men’s suit has created complications when performing this activity. Purpose   The purpose of this thesis is t
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Liu, Jun. "Biomarker Detection at Risk Forecasting Level Using Metal-Enhanced Fluorescence Combined with Surface Acoustic Wave." Scholar Commons, 2016. http://scholarcommons.usf.edu/etd/6534.

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In this paper, metal-enhanced fluorescence (MEF) technique is used to lower the detection limit of carcinoembryonic antigen (CEA) which is able to be utilized in forecasting the risk of having certain kinds of cancers, especially colon and rectal cancer. By incubating silver nanocubes (Ag NCs) on the surface of the chips, the detection limit goes down to below 1ng/mL of CEA. Also, when combining MEF with surface acoustic wave (SAW) devices, the incubation time between antigen and antibody will decrease significantly with the fluorescence signal keeping similar or higher level.
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Tshisaphungo, Mpho. "Validation of high frequency propagation prediction models over Africa." Thesis, Rhodes University, 2010. http://hdl.handle.net/10962/d1015239.

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The ionosphere is an important factor in high frequency (HF) radio propagation providing an opportunity to study ionospheric variability as well as the space weather conditions under which HF communication can take place. This thesis presents the validation of HF propagation conditions for the Ionospheric Communication Enhanced Profile Analysis and Circuit (ICEPAC) and Advanced Stand Alone Prediction System (ASAPS) models over Africa by comparing predictions with the measured data obtained from the International Beacon Project (IBP). Since these models were not developed using information on t
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Alomar, Domínguez Marta. "Improving wave forecasting in variable wind conditions : the effect of resolution and growth rate for the catalan coast." Doctoral thesis, Universitat Politècnica de Catalunya, 2012. http://hdl.handle.net/10803/111230.

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The main objective of this study is to improve wind wave forecasting in the NW Mediterranean Sea while focusing on the characteristic sharp gradients of the wind and wave conditions. This work was motivated by the limited accuracy of wave models in semi-enclosed-basins and orography-controlled wind conditions, especially during fetch-limited storm events. First, to reduce the commonly observed under-estimation of wave parameters, the mesoscale variability of wind and wave fields was characterized in time (1 h to 1 day) and in space (10 km to 100 km). Second, to better capture the typical s
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Libri sul tema "Wave forecasting"

1

Ride the wave. London: Financial Times/Prentice Hall, 2001.

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Organization, World Meteorological. Guide to wave analysis and forecasting. 2nd ed. Geneva: Secretariat of the World Meteorological Organization, 1988.

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Organization, World Meteorological. Guide to wave analysis and forecasting. Geneva, Switzerland: Secretariat of the World Meteorological Organization, 1988.

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Wave 4: Network marketing in the 21st century. Rocklin, CA: Prima, 1999.

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Lowe, Theresa J. A third population wave to affect the K through 12 system. [Olympia, Wash.]: Washington State Office of Financial Management, 2005.

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Abrahamse, Allan F. The coming wave of violence in California. Santa Monica, CA: RAND, 1997.

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Copsey, Ian. Harmonic Elliott Wave: The case for modification of R. N. Elliott's impulsive wave structure. Singapore: John Wiley & Sons (Asia) Pte. Ltd., 2011.

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Maynard, Herman Bryant. The fourth wave: Business in the 21st century. San Francisco: Berrett-Koehler, 1993.

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Trading with the Elliott Wave principle: A practical guide. Memphis, Tenn: Tape Readers Press, 1988.

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Canada Oil and Gas Lands Administration. Evaluation of wave forecasting models and forecast wind fields in the Canadian context. [Ottawa: Energy Mines and Resources], 1988.

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Capitoli di libri sul tema "Wave forecasting"

1

Matthews, Ann. "Forecasting the Residential Data-Wave." In Forecasting the Internet, 59–79. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-0861-8_6.

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Gang, Wang, MA Xiao-wei, Jiang Tao, Gong Hong-ming, KONG Rong-zong, and YANG Yan-guang. "Forecasting Method of Shock-Standoff Distance for Forward-Facing Cavity." In Shock Wave Interactions, 95–106. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-73180-3_7.

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Wan, Qin, Yong Wei, and Xiongqiong Yang. "Research on Grey Wave Forecasting Model." In Understanding Complex Systems, 349–59. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13938-3_30.

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Sipos, Béla. "Empirical Research and Forecasting Based on Hungarian and World Economic Data Series." In The Long-Wave Debate, 119–26. Berlin, Heidelberg: Springer Berlin Heidelberg, 1987. http://dx.doi.org/10.1007/978-3-662-10351-7_10.

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Crampin, Stuart. "Shear-Wave Splitting: New Geophysics and Earthquake Stress-Forecasting." In Encyclopedia of Solid Earth Geophysics, 1355–65. Dordrecht: Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-90-481-8702-7_19.

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Crampin, Stuart. "Shear-Wave Splitting: New Geophysics and Earthquake Stress-Forecasting." In Encyclopedia of Solid Earth Geophysics, 1–11. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-10475-7_19-1.

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Crampin, Stuart. "Shear-Wave Splitting: New Geophysics and Earthquake Stress-Forecasting." In Encyclopedia of Solid Earth Geophysics, 1687–97. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-58631-7_19.

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Loktev, Fedor, Alexandra Kuznetsova, Georgy Baydakov, and Yulia Troitskaya. "Development of Methods for Wind Speed and Wave Parameters Forecasting in Inland Waters." In Processes in GeoMedia - Volume II, 15–20. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-53521-6_4.

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Li, Xingyuan, Qifeng Tang, and Shaojun Ning. "Index Frequency-Based Contour Selection of Gray Wave Forecasting Model and Its Application in Shanghai Stock Market." In Smart Service Systems, Operations Management, and Analytics, 283–91. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30967-1_26.

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Komen, Gerbrand J. "Forecasting Wind-driven Ocean Waves." In Ocean Forecasting, 267–79. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-662-22648-3_14.

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Atti di convegni sul tema "Wave forecasting"

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Tuomi, L., and J. V. Bjorkqvist. "Wave forecasting in coastal archipelagos." In 2014 IEEE/OES Baltic International Symposium (BALTIC). IEEE, 2014. http://dx.doi.org/10.1109/baltic.2014.6887855.

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Yang-Ming Fan, Shunqi Pan, Jia-Ming Chen, and Chia Chuen Kao. "Ensemble wave forecasting over typhoon period." In 2013 MTS/IEEE OCEANS. IEEE, 2013. http://dx.doi.org/10.1109/oceans-bergen.2013.6608029.

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Qin, Wan, Wei Yong, and Yang Xiongqiong. "Research on grey wave forecasting model." In 2009 IEEE International Conference on Grey Systems and Intelligent Services (GSIS 2009). IEEE, 2009. http://dx.doi.org/10.1109/gsis.2009.5408288.

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Cavaleri, Luigi, and Luciana Bertotti. "The Mediterranean Sea Wave Forecasting System." In 23rd International Conference on Coastal Engineering. New York, NY: American Society of Civil Engineers, 1993. http://dx.doi.org/10.1061/9780872629332.009.

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Levy, M. F. "Hybrid models for operational EM forecasting with EEMS." In IEE Colloquium on Common Modelling Techniques for Electromagnetic Wave and Acoustic Wave Propagation. IEE, 1996. http://dx.doi.org/10.1049/ic:19960352.

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Naaijen, Peter, and Rene´ Huijsmans. "Real Time Wave Forecasting for Real Time Ship Motion Predictions." In ASME 2008 27th International Conference on Offshore Mechanics and Arctic Engineering. ASMEDC, 2008. http://dx.doi.org/10.1115/omae2008-57804.

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This paper presents results of a validation study into a linear short term wave and ship motion prediction model for long crested waves. Model experiments have been carried out during which wave elevations were measured at various distances down stream of the wave maker simultaneously. Comparison between predicted and measured wave elevation are presented for 6 different wave conditions. The theoretical relation between spectral content of an irregular long crested wave system and optimal prediction distance for a desired prediction time is explained and validated. It appears that predictions
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Stefanakos, Christos N., Orestis Schinas, and Grim Eidnes. "Application of Fuzzy Time Series Techniques in Wind and Wave Data Forecasting." In ASME 2014 33rd International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/omae2014-24612.

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This work explores the applicability of widely known fuzzy time series forecasting techniques for the prediction of wind and wave data. These techniques have extensively been used with great success to the forecasting of stock prices. In the present work, long-term time series of wind speed, significant wave height, and peak period are examined and used for the verification of the forecasting performance of the fuzzy models. To examine the forecasting accuracy, the root mean squared error (RMSE) is used as an evaluation criterion to compare the forecasting performance of the listing models. As
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Singhal, Gaurav, and Vijay Panchang. "Wave forecasting in Prince William Sound (Alaska)." In OCEANS 2008. IEEE, 2008. http://dx.doi.org/10.1109/oceans.2008.5152004.

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De Masi, Giulia, Floriano Gianfelici, and Yo Poh Foo. "Optimization of operative wave forecasting by artificial intelligence." In 2013 MTS/IEEE OCEANS. IEEE, 2013. http://dx.doi.org/10.1109/oceans-bergen.2013.6608131.

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Pushpam P., Martina Maria, and Felix Enigo V.S. "Forecasting Significant Wave Height using RNN-LSTM Models." In 2020 4th International Conference on Intelligent Computing and Control Systems (ICICCS). IEEE, 2020. http://dx.doi.org/10.1109/iciccs48265.2020.9121040.

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Rapporti di organizzazioni sul tema "Wave forecasting"

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Simpson, Alexandra, Merrick Haller, David Walker, and Pat Lynett. Assimilation of Wave Imaging Radar Observations for Real-time Wave-by-Wave Forecasting. Office of Scientific and Technical Information (OSTI), August 2017. http://dx.doi.org/10.2172/1377063.

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Flatau, Piotr J. Experimental Validation of the Navy Air-Sea-Wave Coupled Forecasting Models. Fort Belvoir, VA: Defense Technical Information Center, September 2012. http://dx.doi.org/10.21236/ada574107.

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Mettlach, Theodore R., Eileen P. Kennelly, and Douglas A. May. Surf Forecasting Using Directional Wave Spectra with the Navy Standard Surf Model. Fort Belvoir, VA: Defense Technical Information Center, September 1996. http://dx.doi.org/10.21236/ada316031.

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Sheremet, Alexandru, Gregory W. Stone, and James M. Kaihatu. Wave Forecasting in Muddy Coastal Environments: Model Development Based on Real-Time Observations. Fort Belvoir, VA: Defense Technical Information Center, September 2003. http://dx.doi.org/10.21236/ada627316.

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Graber, Hans C., Mark A. Donelan, Michael G. Brown, Donald N. Slinn, Scott C. Hagen, Donald R. Thompson, Robert E. Jensen, et al. Real-Time Forecasting System of Winds, Waves and Surge in Tropical Cyclones. Fort Belvoir, VA: Defense Technical Information Center, January 2003. http://dx.doi.org/10.21236/ada491421.

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Graber, Hans C., Mark A. Donelan, Michael G. Brown, Donald N. Slinn, Scott C. Hagen, Donald R. Thompson, Robert E. Jensen, Peter G. Black, Mark D. Powell, and John L. Guiney. Real-Time Forecasting System of Winds, Waves and Surge in Tropical Cyclones. Fort Belvoir, VA: Defense Technical Information Center, January 2004. http://dx.doi.org/10.21236/ada483312.

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Graber, Hans C., Mark A. Donelan, Michael G. Brown, Donald N. Slinn, Scott C. Hagen, Donald R. Thompson, Robert E. Jensen, Peter G. Black, Mark D. Powell, and John L. Guiney. Real-Time Forecasting System of Winds, Waves and Surge in Tropical Cyclones. Fort Belvoir, VA: Defense Technical Information Center, September 2007. http://dx.doi.org/10.21236/ada573387.

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Graber, Hans C., Mark A. Donelan, Michael G. Brown, Donald N. Slinn, Scott C. Hagen, Donald R. Thompson, Robert E. Jensen, Peter G. Black, Mark D. Powell, and John L. Guiney. Real-Time Forecasting System of Winds, Waves and Surge in Tropical Cyclones. Fort Belvoir, VA: Defense Technical Information Center, September 2002. http://dx.doi.org/10.21236/ada627024.

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Graber, Hans C., Mark A. Donelan, Michael G. Brown, Donald N. Slinn, Scott C. Hagen, Donald R. Thompson, Robert E. Jensen, et al. Real-Time Forecasting System of Winds, Waves and Surge in Tropical Cyclones. Fort Belvoir, VA: Defense Technical Information Center, January 2006. http://dx.doi.org/10.21236/ada475368.

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