Literatura académica sobre el tema "Wind Forecasts"
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Artículos de revistas sobre el tema "Wind Forecasts"
Sampson, Charles R., Paul A. Wittmann, Efren A. Serra, Hendrik L. Tolman, Jessica Schauer y Timothy Marchok. "Evaluation of Wave Forecasts Consistent with Tropical Cyclone Warning Center Wind Forecasts". Weather and Forecasting 28, n.º 1 (1 de febrero de 2013): 287–94. http://dx.doi.org/10.1175/waf-d-12-00060.1.
Texto completoRiordan, Allen J. "Forecasting for a Remote Island: A Class Exercise". Bulletin of the American Meteorological Society 84, n.º 6 (1 de junio de 2003): 777–84. http://dx.doi.org/10.1175/bams-84-6-777.
Texto completoTyner, Bryce, Anantha Aiyyer, Jonathan Blaes y Donald Reid Hawkins. "An Examination of Wind Decay, Sustained Wind Speed Forecasts, and Gust Factors for Recent Tropical Cyclones in the Mid-Atlantic Region of the United States". Weather and Forecasting 30, n.º 1 (1 de febrero de 2015): 153–76. http://dx.doi.org/10.1175/waf-d-13-00125.1.
Texto completoKnaff, John A. y Charles R. Sampson. "After a Decade Are Atlantic Tropical Cyclone Gale Force Wind Radii Forecasts Now Skillful?" Weather and Forecasting 30, n.º 3 (1 de junio de 2015): 702–9. http://dx.doi.org/10.1175/waf-d-14-00149.1.
Texto completoRoads, JO, K. Ueyoshi, SC Chen, J. Alpert y F. Fujioka. "Medium-range fire weather forecasts". International Journal of Wildland Fire 1, n.º 3 (1991): 159. http://dx.doi.org/10.1071/wf9910159.
Texto completoJacobs, A. J. M. y N. Maat. "Numerical Guidance Methods for Decision Support in Aviation Meteorological Forecasting". Weather and Forecasting 20, n.º 1 (1 de febrero de 2005): 82–100. http://dx.doi.org/10.1175/waf-827.1.
Texto completoKnaff, John A., Charles R. Sampson y Galina Chirokova. "A Global Statistical–Dynamical Tropical Cyclone Wind Radii Forecast Scheme". Weather and Forecasting 32, n.º 2 (20 de marzo de 2017): 629–44. http://dx.doi.org/10.1175/waf-d-16-0168.1.
Texto completoHallgren, Christoffer, Stefan Ivanell, Heiner Körnich, Ville Vakkari y Erik Sahlée. "The smoother the better? A comparison of six post-processing methods to improve short-term offshore wind power forecasts in the Baltic Sea". Wind Energy Science 6, n.º 5 (16 de septiembre de 2021): 1205–26. http://dx.doi.org/10.5194/wes-6-1205-2021.
Texto completoLehr, William J., Debra Simecek-Beatty y Marc Hodges. "Wind Uncertainty in Long Range Trajectory Forecasts". International Oil Spill Conference Proceedings 2003, n.º 1 (1 de abril de 2003): 435–39. http://dx.doi.org/10.7901/2169-3358-2003-1-435.
Texto completoTheuer, Frauke, Andreas Rott, Jörge Schneemann, Lueder von Bremen y Martin Kühn. "Observer-based power forecast of individual and aggregated offshore wind turbines". Wind Energy Science 7, n.º 5 (24 de octubre de 2022): 2099–116. http://dx.doi.org/10.5194/wes-7-2099-2022.
Texto completoTesis sobre el tema "Wind Forecasts"
Mason, Jesse Cheyenne. "On improving wind-turbine hub-height wind-speed forecasts". Thesis, University of British Columbia, 2014. http://hdl.handle.net/2429/46558.
Texto completoSiuta, David. "Improving hub-height wind forecasts in complex terrain". Thesis, University of British Columbia, 2017. http://hdl.handle.net/2429/61055.
Texto completoScience, Faculty of
Earth, Ocean and Atmospheric Sciences, Department of
Graduate
Welsh, David J. S. "The improvement of wind-wave forecasts in the Great Lakes /". The Ohio State University, 1997. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487948807587679.
Texto completoNchaba, Teboho. "Verification of gridded seasonal wind speed forecasts over South Africa". Master's thesis, University of Cape Town, 2013. http://hdl.handle.net/11427/4970.
Texto completoIncludes bibliographical references.
The Climate System Analysis Group (CSAG) at the University of Cape Town produces provisional global and Southern African seasonal wind forecasts generated using the United Kingdom Meteorological Office Atmospheric General Circulation Model (AGCM) HadAM3P (non-standard version of HadAM3). This study examines the quality of the seasonal wind speed forecasts through a forecast verification process for continuous variables using reanalysis products of the National Centers for Environmental Prediction and the Department of Energy (NCEP-DOE) as observations data. The verification analyses are performed using summary measures Mean Error (ME), Mean Absolute Error (MAE), Mean Squared Error (MSE), correlation coefficients, Linear Error in Probability Space (LEPS) and exploratory methods, scatter and conditional quantile plots. These methods are used to determine the aspects of forecast quality namely, bias, accuracy, reliability, resolution, and skill over a 20 year period (1991 to 2010). The results of the study have determined that the use of both accuracy and skill measures for the verification analyses provide more information about the quality of the forecasts, as opposed only one of these. In all provinces, the highest quality seasonal wind speed forecasts are made at 500 hPa and the lowest quality forecasts at 1000 hPa. Furthermore regions, pressure levels, and seasons with the highest forecast quality share the common characteristic that their wind speeds are relatively high. The forecasts add value to the climatology and thus are a useful tool for wind assessment at a seasonal scale. It is suggested that adding spatial resolution to the forecasts through downscaling may prepare them for use in applications such as wind power output forecasting.
Lau, Ada. "Probabilistic wind power forecasts : from aggregated approach to spatiotemporal models". Thesis, University of Oxford, 2011. http://ora.ox.ac.uk/objects/uuid:f5a66568-baac-4f11-ab1e-dc79061cfb0f.
Texto completode, Almeida Francisco M. S. C. "The influence of wind on HF radar surface current forecasts". Thesis, Monterey, Calif. : Naval Postgraduate School, 2008. http://edocs.nps.edu/npspubs/scholarly/theses/2008/Dec/08Dec%5Fde%5FAlmeida.pdf.
Texto completoThesis Advisor(s): Paduan, Jeffrey. "December 2008." Description based on title screen as viewed on January 29, 2009. Includes bibliographical references (p. 67-69). Also available in print.
Sjöberg, Ludvig. "Wind Forecasts Using Large Eddy Simulations for Stratospheric Balloon Applications". Thesis, Luleå tekniska universitet, Rymdteknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-74457.
Texto completoGallaher, Shawn G. "Performance of a high resolution diagnostic model for short range mesoscale wind forecasts in complex terrain". Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2002. http://library.nps.navy.mil/uhtbin/hyperion-image/02sep%5FGallaher.pdf.
Texto completoThesis advisor(s): Douglas K. Miller, Wendell A. Nuss. Includes bibliographical references (p. 125-128). Also available online.
Olaofe, Zaccheus Olaniyi. "Wind energy generation and forecasts: a case study of Darling and Vredenburg sites". Master's thesis, University of Cape Town, 2013. http://hdl.handle.net/11427/16831.
Texto completoIve, Federica. "Improving numerical simulation methods for the assessment of wind source availability and related power production for wind farms over complex terrain". Doctoral thesis, Università degli studi di Trento, 2022. http://hdl.handle.net/11572/350981.
Texto completoLibros sobre el tema "Wind Forecasts"
G, Benjamin Stanley y Forecast Systems Laboratory (U.S.), eds. A study of the accuracy of RUC-1 and RUC-2 wind and aircraft trajectory forecasts using ACARS observations. Boulder, Colo: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, Environmental Research Laboratories, Forecast Systems Laboratory, 1998.
Buscar texto completoGrasping for the wind: The search for meaning in the 20th century. Grand Rapids, Mich: Zondervan, 2001.
Buscar texto completoJohn F. Kennedy Space Center. y United States. National Aeronautics and Space Administration. Scientific and Technical Information Program., eds. Statistical short-range guidance for peak wind speed forecasts on Kennedy Space Center/Cape Canaveral Air Force Station: Phase 1 results. [Washington, D.C.]: National Aeronautics and Space Administration, Office of Management, Scientific and Technical Information Program, 2002.
Buscar texto completoJohn F. Kennedy Space Center. y United States. National Aeronautics and Space Administration. Scientific and Technical Information Program., eds. Statistical short-range guidance for peak wind speed forecasts on Kennedy Space Center/Cape Canaveral Air Force Station: Phase 1 results. [Washington, D.C.]: National Aeronautics and Space Administration, Office of Management, Scientific and Technical Information Program, 2002.
Buscar texto completoInc, Icon Group International, ed. The 2002 world market forecasts for imported wine. San Diego, Calif: Icon Group, 2002.
Buscar texto completoK, Sahai A. y Indian Institute of Tropical Meteorology., eds. Experimental seasonal forecast of Indian summer monsoon 2007: Statistical and dynamical models. Pune: Indian Institute of Tropical Meteorology, 2007.
Buscar texto completoMandke, S. K. Dynamical ensemble seasonal forecast experiments of recent Indian summer monsoons: An assessment using new approach. Pune: Indian Institute of Tropical Meteorology, 2005.
Buscar texto completoSpace Environment Center (U.S.), ed. Wang and Sheeley medium-range planetary A index forecast verification statistics. Boulder, Colo: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, Environmental Research Laboratories, Space Environment Center, 1996.
Buscar texto completoSpace Environment Center (U.S.), ed. Wang and Sheeley medium-range planetary A index forecast verification statistics. Boulder, Colo: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, Environmental Research Laboratories, Space Environment Center, 1996.
Buscar texto completoSpace Environment Center (U.S.), ed. Wang and Sheeley medium-range planetary A index forecast verification statistics. Boulder, Colo: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, Environmental Research Laboratories, Space Environment Center, 1996.
Buscar texto completoCapítulos de libros sobre el tema "Wind Forecasts"
Kay, Merlinde y Iain MacGill. "Improving NWP Forecasts for the Wind Energy Sector". En Weather Matters for Energy, 413–28. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4614-9221-4_20.
Texto completoKirthika, N., K. I. Ramachandran y Sasi K. Kottayil. "Deep Quantile Regression Based Wind Generation and Demand Forecasts". En Advances in Intelligent Systems and Computing, 112–22. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-49345-5_12.
Texto completoMoritz, Richard E. "Accuracy of Surface Geostrophic Wind Forecasts in the Central Arctic". En The Geophysics of Sea Ice, 1135–61. Boston, MA: Springer US, 1986. http://dx.doi.org/10.1007/978-1-4899-5352-0_19.
Texto completoGiannitrapani, Antonio, Simone Paoletti, Antonio Vicino y Donato Zarrilli. "Optimal Bidding Strategies for Wind Power Producers with Meteorological Forecasts". En 2013 Proceedings of the Conference on Control and its Applications, 13–20. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2013. http://dx.doi.org/10.1137/1.9781611973273.3.
Texto completoAbel, Rafael, Lutz Pegel y Andreas Waldmann. "On the Importance of Highly Resolved Wind Forecasts for Range Estimation". En Proceedings, 187–96. Wiesbaden: Springer Fachmedien Wiesbaden, 2022. http://dx.doi.org/10.1007/978-3-658-37011-4_16.
Texto completoDi Napoli, Claudia, Alessandro Messeri, Martin Novák, João Rio, Joanna Wieczorek, Marco Morabito, Pedro Silva, Alfonso Crisci y Florian Pappenberger. "The Universal Thermal Climate Index as an Operational Forecasting Tool of Human Biometeorological Conditions in Europe". En Applications of the Universal Thermal Climate Index UTCI in Biometeorology, 193–208. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-76716-7_10.
Texto completoAlonzo, Bastien, Riwal Plougonven, Mathilde Mougeot, Aurélie Fischer, Aurore Dupré y Philippe Drobinski. "From Numerical Weather Prediction Outputs to Accurate Local Surface Wind Speed: Statistical Modeling and Forecasts". En Springer Proceedings in Mathematics & Statistics, 23–44. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-99052-1_2.
Texto completoAlmeida, Vânia y João Gama. "Collaborative Wind Power Forecast". En Adaptive and Intelligent Systems, 162–71. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-11298-5_17.
Texto completoZjavka, Ladislav, Stanislav Mišák y Lukáš Prokop. "Post-processing of Wind-Speed Forecasts Using the Extended Perfect Prog Method with Polynomial Neural Networks to Elicit PDE Models". En Hybrid Intelligent Systems, 11–21. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-14347-3_2.
Texto completoNielsen, Henrik Aalborg. "Short Term Forecast of Wind Power". En Advances in Wind Energy Conversion Technology, 107–32. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-540-88258-9_4.
Texto completoActas de conferencias sobre el tema "Wind Forecasts"
Kemper, Jason J., Mark F. Bielecki y Thomas L. Acker. "Modeling of Wind Power Production Forecast Errors for Wind Integration Studies". En ASME 2010 4th International Conference on Energy Sustainability. ASMEDC, 2010. http://dx.doi.org/10.1115/es2010-90441.
Texto completoZhang, Jie, Anthony Florita, Bri-Mathias Hodge y Jeffrey Freedman. "Ramp Forecasting Performance From Improved Short-Term Wind Power Forecasting". En ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/detc2014-34775.
Texto completoHaupt, Sue Ellen, Gerry Wiener, Yubao Liu, Bill Myers, Juanzhen Sun, David Johnson y William Mahoney. "A Wind Power Forecasting System to Optimize Power Integration". En ASME 2011 5th International Conference on Energy Sustainability. ASMEDC, 2011. http://dx.doi.org/10.1115/es2011-54773.
Texto completoBai, Li, Emanuele Crisostomi, Marco Raugi y Mauro Tucci. "Wind Power Forecast Using Wind Forecasts at Different Altitudes in Convolutional Neural Networks". En 2019 IEEE Power & Energy Society General Meeting (PESGM). IEEE, 2019. http://dx.doi.org/10.1109/pesgm40551.2019.8973938.
Texto completoSroga, J., A. Rosenberg, L. O’Hara, P. Hays y B. Kennedy. "Ground Based 0.53 μm Wind Sensor". En Optical Remote Sensing. Washington, D.C.: Optica Publishing Group, 1985. http://dx.doi.org/10.1364/ors.1985.wc30.
Texto completoChagas, F. M., B. R. F. Rachid, B. G. Ambrosio, A. A. Luz, C. B. Gramcianinov, P. F. Serrao, R. Camargo y E. Siegle. "Assessment of Wind and Wave High-Resolution Forecasts During High-Energy Weather Events in the Brazilian Coast". En ASME 2021 40th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/omae2021-62030.
Texto completoWu, Yuan-Kang, Po-En Su y Jing-Shan Hong. "An overview of wind power probabilistic forecasts". En 2016 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC). IEEE, 2016. http://dx.doi.org/10.1109/appeec.2016.7779540.
Texto completoKaso, Mathias, Felix Musgens y Oliver Grothe. "Dynamic forecast combinations of improved individual forecasts for the prediction of wind energy". En 2016 13th International Conference on the European Energy Market (EEM). IEEE, 2016. http://dx.doi.org/10.1109/eem.2016.7521228.
Texto completoCampos, Ricardo Martins, Andressa D’Agostini, Leandro Machado Cruz, Bruna Reis Leite França y C. Guedes Soares. "Extreme Wind and Wave Predictability From Operational Forecasts at the Drake Passage". En ASME 2019 38th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/omae2019-96626.
Texto completoFrate, Guido Francesco, Lorenzo Ferrari y Umberto Desideri. "Impact of Forecast Uncertainty on Wind Farm Profitability". En ASME Turbo Expo 2019: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/gt2019-91523.
Texto completoInformes sobre el tema "Wind Forecasts"
Pennock, K. Updated Eastern Interconnect Wind Power Output and Forecasts for ERGIS: July 2012. Office of Scientific and Technical Information (OSTI), octubre de 2012. http://dx.doi.org/10.2172/1056126.
Texto completoNorquist, Donald C. y Warner C. Meeks. A Comparative Verification of Forecasts from Two Operational Solar Wind Models (Postprint). Fort Belvoir, VA: Defense Technical Information Center, febrero de 2012. http://dx.doi.org/10.21236/ada558506.
Texto completoPiwko, Richard y Gary Jordan. Impacts of Improved Day-Ahead Wind Forecasts on Power Grid Operations: September 2011. Office of Scientific and Technical Information (OSTI), noviembre de 2011. http://dx.doi.org/10.2172/1031400.
Texto completoFinley, Cathy. The Wind Forecast Improvement Project (WFIP). A Public/Private Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations -- the Northern Study Area. Office of Scientific and Technical Information (OSTI), abril de 2014. http://dx.doi.org/10.2172/1129929.
Texto completoNachmani, Gil. Minimum-Energy Flight Paths for UAVs Using Mesoscale Wind Forecasts and Approximate Dynamic Programming. Fort Belvoir, VA: Defense Technical Information Center, diciembre de 2007. http://dx.doi.org/10.21236/ada475720.
Texto completoFreedman, Jeffrey M., John Manobianco, John Schroeder, Brian Ancell, Keith Brewster, Sukanta Basu, Venkat Banunarayanan, Bri-Mathias Hodge y Isabel Flores. The Wind Forecast Improvement Project (WFIP): A Public/Private Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations. The Southern Study Area, Final Report. Office of Scientific and Technical Information (OSTI), abril de 2014. http://dx.doi.org/10.2172/1129905.
Texto completoOptis, Michael, George N. Scott y Caroline Draxl. Evaluation of Wind Power Forecasts from the Vermont Weather Analytics Center and Identification of Improvements. Office of Scientific and Technical Information (OSTI), febrero de 2018. http://dx.doi.org/10.2172/1419925.
Texto completoDumais, Robert E., John W. Raby, Yansen Wang, Yasmina R. Raby y David Knapp. Performance Assessment of the Three-Dimensional Wind Field Weather Running Estimate - Nowcast and the Three-Dimensional Wind Field Air Force Weather Agency Weather Research and Forecasting Wind Forecasts. Fort Belvoir, VA: Defense Technical Information Center, diciembre de 2012. http://dx.doi.org/10.21236/ada573289.
Texto completoGallagher, Alex, Sandra LeGrand, Taylor Hodgdon y Theodore Letcher. Simulating environmental conditions for Southwest United States convective dust storms using the Weather Research and Forecasting Model v4.1. Engineer Research and Development Center (U.S.), agosto de 2022. http://dx.doi.org/10.21079/11681/44963.
Texto completoVenäläinen, Ari, Sanna Luhtala, Mikko Laapas, Otto Hyvärinen, Hilppa Gregow, Mikko Strahlendorff, Mikko Peltoniemi et al. Sää- ja ilmastotiedot sekä uudet palvelut auttavat metsäbiotaloutta sopeutumaan ilmastonmuutokseen. Finnish Meteorological Institute, enero de 2021. http://dx.doi.org/10.35614/isbn.9789523361317.
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