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Relevant bibliographies by topics / Ocean winds

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Academic literature on the topic 'Ocean winds'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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Journal articles on the topic "Ocean winds"

1

Swain, J., P. A. Umesh, and A. S. N. Murty. "Demonstration of an efficient interpolation technique of inverse time and distance for Oceansat-2 wind measurements at 6-hourly intervals." International Journal of Ocean and Climate Systems 8, no. 3 (October 14, 2017): 101–12. http://dx.doi.org/10.1177/1759313117736596.

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Indian Space Research Organization had launched Oceansat-2 on 23 September 2009, and the scatterometer onboard was a space-borne sensor capable of providing ocean surface winds (both speed and direction) over the globe for a mission life of 5 years. The observations of ocean surface winds from such a space-borne sensor are the potential source of data covering the global oceans and useful for driving the state-of-the-art numerical models for simulating ocean state if assimilated/blended with weather prediction model products. In this study, an efficient interpolation technique of inverse distance and time is demonstrated using the Oceansat-2 wind measurements alone for a selected month of June 2010 to generate gridded outputs. As the data are available only along the satellite tracks and there are obvious data gaps due to various other reasons, Oceansat-2 winds were subjected to spatio-temporal interpolation, and 6-hour global wind fields for the global oceans were generated over 1 × 1 degree grid resolution. Such interpolated wind fields can be used to drive the state-of-the-art numerical models to predict/hindcast ocean-state so as to experiment and test the utility/performance of satellite measurements alone in the absence of blended fields. The technique can be tested for other satellites, which provide wind speed as well as direction data. However, the accuracy of input winds is obviously expected to have a perceptible influence on the predicted ocean-state parameters. Here, some attempts are also made to compare the interpolated Oceansat-2 winds with available buoy measurements and it was found that they are reasonably in good agreement with a correlation coefficient of R > 0.8 and mean deviation 1.04 m/s and 25° for wind speed and direction, respectively.

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Yonehara, Yoshinari, Yusuke Goto, Ken Yoda, Yutaka Watanuki, Lindsay C. Young, Henri Weimerskirch, Charles-André Bost, and Katsufumi Sato. "Flight paths of seabirds soaring over the ocean surface enable measurement of fine-scale wind speed and direction." Proceedings of the National Academy of Sciences 113, no. 32 (July 25, 2016): 9039–44. http://dx.doi.org/10.1073/pnas.1523853113.

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Ocean surface winds are an essential factor in understanding the physical interactions between the atmosphere and the ocean. Surface winds measured by satellite scatterometers and buoys cover most of the global ocean; however, there are still spatial and temporal gaps and finer-scale variations of wind that may be overlooked, particularly in coastal areas. Here, we show that flight paths of soaring seabirds can be used to estimate fine-scale (every 5 min, ∼5 km) ocean surface winds. Fine-scale global positioning system (GPS) positional data revealed that soaring seabirds flew tortuously and ground speed fluctuated presumably due to tail winds and head winds. Taking advantage of the ground speed difference in relation to flight direction, we reliably estimated wind speed and direction experienced by the birds. These bird-based wind velocities were significantly correlated with wind velocities estimated by satellite-borne scatterometers. Furthermore, extensive travel distances and flight duration of the seabirds enabled a wide range of high-resolution wind observations, especially in coastal areas. Our study suggests that seabirds provide a platform from which to measure ocean surface winds, potentially complementing conventional wind measurements by covering spatial and temporal measurement gaps.

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Portabella, M., and A. Stoffelen. "On Scatterometer Ocean Stress." Journal of Atmospheric and Oceanic Technology 26, no. 2 (February 1, 2009): 368–82. http://dx.doi.org/10.1175/2008jtecho578.1.

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Abstract Scatterometers estimate the relative atmosphere–ocean motion at spatially high resolution and provide accurate inertial-scale ocean wind forcing information, which is crucial for many ocean, atmosphere, and climate applications. An empirical scatterometer ocean stress (SOS) product is estimated and validated using available statistical information. A triple collocation dataset of scatterometer, and moored buoy and numerical weather prediction (NWP) observations together with two commonly used surface layer (SL) models are used to characterize the SOS. First, a comparison between the two SL models is performed. Although their roughness length and the stability parameterizations differ somewhat, the two models show little differences in terms of stress estimation. Second, a triple collocation exercise is conducted to assess the true and error variances explained by the observations and the SL models. The results show that the uncertainty in the NWP dataset is generally larger than in the buoy and scatterometer wind/stress datasets, but it depends on the spatial scales of interest. The triple collocation analysis also shows that scatterometer winds are as close to real winds as to equivalent neutral winds, provided that the appropriate scaling is used. An explanation for this duality is that the small stability effects found in the analysis are masked by the uncertainty in SL models and their inputs. The triple collocation analysis shows that scatterometer winds can be straightforwardly and reliably transformed to wind stress. This opens the door for the development of wind stress swath (level 2) and gridded (level 3) products for the Advanced Scatterometer (ASCAT) on board Meterological Operation (MetOp) and for further geophysical development.

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Von Ahn, Joan M., Joseph M. Sienkiewicz, and Paul S. Chang. "Operational Impact of QuikSCAT Winds at the NOAA Ocean Prediction Center." Weather and Forecasting 21, no. 4 (August 1, 2006): 523–39. http://dx.doi.org/10.1175/waf934.1.

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Abstract The NASA Quick Scatterometer (QuikSCAT) has revolutionized the analysis and short-term forecasting of winds over the oceans at the NOAA Ocean Prediction Center (OPC). The success of QuikSCAT in OPC operations is due to the wide 1800-km swath width, large retrievable wind speed range (0 to in excess of 30 m s−1), ability to view QuikSCAT winds in a comprehensive form in operational workstations, and reliable near-real-time delivery of data. Prior to QuikSCAT, marine forecasters at the OPC made warning and forecast decisions over vast ocean areas based on a limited number of conventional observations or on the satellite presentation of a storm system. Today, QuikSCAT winds are a heavily used tool by OPC forecasters. Approximately 10% of all short-term wind warning decisions by the OPC are based on QuikSCAT winds. When QuikSCAT is available, 50%–68% of all weather features on OPC surface analyses are placed using QuikSCAT. QuikSCAT is the first remote sensing instrument that can consistently distinguish extreme hurricane force conditions from less dangerous storm force conditions in extratropical cyclones. During each winter season (October–April) from 2001 to 2004, 15–23 extratropical cyclones reached hurricane force intensity over both the North Atlantic and North Pacific Oceans. Due to QuikSCAT, OPC forecasters are now more likely to anticipate the onset of hurricane force conditions. QuikSCAT has also revealed significant wind speed gradients in the vicinity of strong sea surface temperature (SST) differences near the Gulf Stream and shelfbreak front of the western North Atlantic. These wind speed gradients are most likely due to changes in low-level stability of the boundary layer across the SST gradients. OPC forecasters now use a variety of numerical guidance based tools to help predict boundary layer stability and the resultant near-surface winds.

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Smith, H. Jesse. "Ocean winds blowing harder." Science 364, no. 6440 (May 9, 2019): 542.1–542. http://dx.doi.org/10.1126/science.364.6440.542-a.

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Ricciardulli, Lucrezia, and Frank J. Wentz. "A Scatterometer Geophysical Model Function for Climate-Quality Winds: QuikSCAT Ku-2011." Journal of Atmospheric and Oceanic Technology 32, no. 10 (October 2015): 1829–46. http://dx.doi.org/10.1175/jtech-d-15-0008.1.

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AbstractSpace-based observations of ocean surface winds have been available for more than 25 years. To combine the observations from multiple sensors into one record with the accuracy required for climate studies requires a consistent methodology and calibration standard for the various instruments. This study describes a new geophysical model function (GMF) specifically developed for preparing the QuikSCAT winds to serve as a backbone of an ocean vector wind climate data record. This paper describes the methodology used and presents the quality of the reprocessed winds. The new Ku-2011 model function was developed using WindSat winds as a calibration truth. An extensive validation of the Ku-2011 winds was performed that focused on 1) proving the consistency of satellite winds from different sensors at all wind speed regimes; 2) exploring and understanding possible sources of bias in the QuikSCAT retrievals; 3) validating QuikSCAT wind speeds versus in situ observations, and comparing observed wind directions versus those from numerical models; 4) comparing satellite observations of high wind speeds with measurements obtained from aircraft flying into storms; 5) analyzing case studies of satellite-based observations of winds in tropical storms; and 6) illustrating how rain impacts QuikSCAT wind speed retrievals. The results show that the reprocessed QuikSCAT data are greatly improved in both speed and direction at high winds. Finally, there is a discussion on how these QuikSCAT results fit into a long-term effort toward creating a climate data record of ocean vector winds.

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Zhai, Xiaoming, Helen L. Johnson, David P. Marshall, and Carl Wunsch. "On the Wind Power Input to the Ocean General Circulation." Journal of Physical Oceanography 42, no. 8 (August 1, 2012): 1357–65. http://dx.doi.org/10.1175/jpo-d-12-09.1.

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Abstract The wind power input to the ocean general circulation is usually calculated from the time-averaged wind products. Here, this wind power input is reexamined using available observations, focusing on the role of the synoptically varying wind. Power input to the ocean general circulation is found to increase by over 70% when 6-hourly winds are used instead of monthly winds. Much of the increase occurs in the storm-track regions of the Southern Ocean, Gulf Stream, and Kuroshio Extension. This result holds irrespective of whether the ocean surface velocity is accounted for in the wind stress calculation. Depending on the fate of the high-frequency wind power input, the power input to the ocean general circulation relevant to deep-ocean mixing may be less than previously thought. This study emphasizes the difficulty of choosing appropriate forcing for ocean-only models.

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Gille, Sarah T. "Statistical Characterization of Zonal and Meridional Ocean Wind Stress." Journal of Atmospheric and Oceanic Technology 22, no. 9 (September 1, 2005): 1353–72. http://dx.doi.org/10.1175/jtech1789.1.

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Abstract Four years of ocean vector wind data are used to evaluate statistics of wind stress over the ocean. Raw swath wind stresses derived from the Quick Scatterometer (QuikSCAT) are compared with five different global gridded wind products, including products based on scatterometer observations, meteorological analysis winds from the European Centre for Medium-Range Weather Forecasts, and reanalysis winds from the National Centers for Environmental Prediction. Buoy winds from a limited number of sites in the Pacific Ocean are also considered. Probability density functions (PDFs) computed for latitudinal bands show that mean wind stresses for the six global products are largely in agreement, while variances differ substantially, by a factor of 2 or more, with swath wind stresses indicating highest variances for meridional winds and for zonal winds outside the Tropics. Higher moments of the PDFs also differ. Kurtoses are large for all wind products, implying that PDFs are not Gaussian. None of the available gridded products fully captures the range of extreme wind events seen in the raw swath data. Frequency spectra for the five gridded products agree with frequency spectra from swath data at low frequencies, but spectral slopes differ at higher frequencies, particularly for frequencies greater than 100 cycles per year (cpy), which are poorly resolved by a single scatterometer. In the frequency range between 10 and 90 cpy that is resolved by the scatterometer, spectra derived from swath data are flatter than spectra from gridded products and are judged to be flatter than ω−2/3 at all latitudes.

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Khandekar, M. L., and B. M. Eid. "WIND SPECIFICATION FOR SPECTRAL OCEAN-WAVE MODELS." Coastal Engineering Proceedings 1, no. 20 (January 29, 1986): 28. http://dx.doi.org/10.9753/icce.v20.28.

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This paper investigates the utility of winds obtainable from a numerical weather prediction model for driving a spectral ocean-wave model in an operational mode. Wind inputs for two operational spectral wave models were analyzed with respect to observed winds at three locations in the Canadian east coast offshore. Also, significant wave heights obtainable from the two spectral models were evaluated against measured wave data at these locations. Based on this analysis, the importance of appropriate wind specification for operational wave analysis and forecasting is demonstrated.

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Businger, Steven, Selen Yildiz, and Thomas E. Robinson. "The Impact of Hurricane Force Wind Fields on the North Pacific Ocean Environment." Weather and Forecasting 30, no. 3 (June 1, 2015): 742–53. http://dx.doi.org/10.1175/waf-d-14-00107.1.

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AbstractThis study analyzes QuikSCAT surface wind data over the North Pacific Ocean to document the distribution of captured fetches in extratropical cyclones that produced hurricane force (HF) wind fields from January 2003 through May 2008. A case study is presented to introduce the datasets, which include surface wind analyses from the Global Forecast System (GFS) Global Data Assimilation System (GDAS), and wave hindcasts from the third-generation wave model (WAVEWATCH III; hereafter, WW3), in addition to the QuikSCAT surface wind data. The analysis shows significant interannual variability in the location of the captured fetches as documented by QuikSCAT, including a shift in the distribution of captured fetches associated with ENSO. GDAS surface winds over the ocean are consistently underanalyzed when compared to QuikSCAT surface winds, despite the fact that satellite observations of ocean surface winds are assimilated. When the WW3 hindcasts associated with HF cyclones are compared with buoy observations over the eastern and central North Pacific Ocean, the wave model significantly underestimates the large-swell events.

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Dissertations / Theses on the topic "Ocean winds"

1

Patoux, Jérôme. "Frontal wave development over the Southern Ocean /." Thesis, Connect to this title online; UW restricted, 2003. http://hdl.handle.net/1773/10067.

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Konstantinou, Nikolaos. "Ocean mixed layer response to gap wind scenarios." Thesis, Monterey, Calif. : Naval Postgraduate School, 2006. http://bosun.nps.edu/uhtbin/hyperion.exe/06Dec%5FKonstantinou.pdf.

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Thesis (M.S. in Meteorology)--Naval Postgraduate School, December 2006.
Thesis Advisor(s): Qing Wang, Roland W. Garwood. "December 2006." Includes bibliographical references (p. 61-62). Also available in print.

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Zeng, Lixin. "The verification and application of satellite scatterometer winds /." Thesis, Connect to this title online; UW restricted, 1996. http://hdl.handle.net/1773/10077.

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Fei, Chen-Yang. "Vortex-induced vibrations of structural members in natural winds." Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/36006.

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Kennedy, Richard A. "A numerical study of the forcing mechanisms of the Leeuwin current system /." Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2002. http://library.nps.navy.mil/uhtbin/hyperion-image/02sep%5FKennedy.pdf.

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Thesis (M.S. in Meteorology and Physical Oceanography)--Naval Postgraduate School, September 2002.
Thesis advisor(s): Mary L. Batteen, Curtis A. Collins. Includes bibliographical references (p. 93-96). Also available online.

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Byars, Beverly J. "Variation of the drag coefficient with wind and wave state." Thesis, Monterey, Calif. : Naval Postgraduate School, 1985. http://catalog.hathitrust.org/api/volumes/oclc/52763691.html.

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Duhaut, Thomas H. A. "Wind-driven circulation : impact of a surface velocity dependent wind stress." Thesis, McGill University, 2006. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=101117.

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The use of an ocean surface velocity dependent wind stress is examined in the context of a 3-layer double-gyre quasigeostrophic wind-driven ocean circulation model. The new wind stress formulation results in a large reduction of the power input by the wind into the oceanic circulation. This wind stress is proportional to a quadratic function of Ua--u o, where Ua is the wind at 10m above the ocean surface and uo is the ocean surface current. Because the winds are typically faster than the ocean currents, the impact of the ocean surface velocity on the wind stress itself is relatively small. However, the power input is found to be greatly reduced with the new formulation. This is shown by simple scaling argument and numerical simulations in a square basin. Our results suggest that the wind power input may be as much as 35% smaller than is typically assumed.
The ocean current signature is clearly visible in the scatterometer-derived wind stress fields. We argue that because the actual ocean velocity differs from the modeled ocean velocities, care must be taken in directly applying scatterometer-derived wind stress products to the ocean circulation models. This is not to say that the scatterometer-derived wind stress is not useful. Clearly the great spatial and temporal coverage make these data sets invaluable. Our point is that it is better to separate the atmospheric and oceanic contribution to the stresses.
Finally, the new wind stress decreases the sensitivity of the solution to the (poorly known) bottom friction coefficient. The dependence of the circulation strength on different values of bottom friction is examined under the standard and the new wind stress forcing for two topographic configurations. A flat bottom and a meridional ridge case are studied. In the flat bottom case, the new wind stress leads to a significant reduction of the sensitivity to the bottom friction parameter, implying that inertial runaway occurs for smaller values of bottom friction coefficient. The ridge case also gives similar results. In the case of the ridge and the new wind stress formulation, no real inertial runaway regime has been found over the range of parameters explored.

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Kunkee, David Bryan. "Polarimetric millimeter-wave thermal emission from anisotropic water surfaces : application to remote sensing of ocean surface wind direction." Diss., Georgia Institute of Technology, 1995. http://hdl.handle.net/1853/14689.

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Wu, Zhaohua. "Thermally driven surface winds in the tropics /." Thesis, Connect to this title online; UW restricted, 1998. http://hdl.handle.net/1773/10075.

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Cheon, Woo Geunn. "Impact of the Southern ocean winds on sea-ice - ocean interaction and its associated global ocean circulation in a warming world." [College Station, Tex. : Texas A&M University, 2008. http://hdl.handle.net/1969.1/ETD-TAMU-3029.

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Books on the topic "Ocean winds"

1

United, States Naval Oceanography Command Detachment Asheville N. C. U.S. Navy hindcast spectral ocean wave model climatic atlas: North Pacific Ocean. Asheville, N.C: The Detachment, 1985.

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United, States Naval Oceanography Command Detachment Asheville N. C. U.S. Navy hindcast spectral ocean wave model climatic atlas: North Pacific Ocean. Asheville, N.C: The Detachment, 1985.

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3

Halpert, Michael S. Atlas of tropical sea surface temperature and surface winds. Silver Spring, MD: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, National Weather Service, 1989.

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Gillham, Mary E. Islands of the trade winds: An Indian Ocean odyssey. London: Minerva, 2000.

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Andrew, Michael E. Extremal analysis of hindcast and measured wind and wave data at Kodiak, Alaska. Vicksburg, Miss: Dept. of the Army, Waterways Experiment Station, Corps of Engineers, 1985.

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Salo, S. A. Oceanographic conditions on the Northern Bering Sea shelf: 1984-1985. Seattle, Wash: National Oceanic and Atmospheric Administration, Environmental Research Laboratories, Pacific Marine Environmental Laboratory, 1988.

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Roach, A. T. Observations of currents, surface winds and bottom pressure in Shelikof Strait, autumn 1984. Seattle, Wash: National Oceanic and Atmospheric Administration, Environmental Research Laboratories, Pacific Marine Environmental Laboratory, 1987.

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Kumpel, Gail. Timmy Tumbleweed and the great ocean adventure. Rockwall, TX: Benton Woods Pub., 1999.

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9

Holderied, Kristine. Comparison study of SEASAT scatterometer and conventional wind fields. Woods Hole, Mass: Woods Hole Oceanographic Institution, 1988.

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United, States Naval Oceanography Command Detachment Asheville N. C. U.S. Navy hindcast spectral ocean wave model climatic atlas: North Pacific Ocean. Asheville, N.C: The Detachment, 1985.

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Book chapters on the topic "Ocean winds"

1

Klein, Patrice. "High-frequency winds and eddy-resolving models." In Ocean Modeling in an Eddying Regime, 83–100. Washington, D. C.: American Geophysical Union, 2008. http://dx.doi.org/10.1029/177gm07.

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Saenko, Oleg A. "Projected strengthening of the Southern Ocean winds: Some implications for the deep ocean circulation." In Ocean Circulation: Mechanisms and Impacts—Past and Future Changes of Meridional Overturning, 365–82. Washington, D. C.: American Geophysical Union, 2007. http://dx.doi.org/10.1029/173gm23.

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Mognard, Nelly M., William J. Campbell, Robert E. Cheney, James G. Marsh, and Duncan Ross. "Southern Ocean Waves and Winds Derived from SEASAT Altimeter Measurements." In Wave Dynamics and Radio Probing of the Ocean Surface, 479–89. Boston, MA: Springer US, 1986. http://dx.doi.org/10.1007/978-1-4684-8980-4_33.

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Hardy, T. A., L. B. Mason, and J. D. McConochie. "Generating Synthetic Tropical Cyclone Databases for Input to Modeling of Extreme Winds, Waves, and Storm Surges." In Indian Ocean Tropical Cyclones and Climate Change, 57–64. Dordrecht: Springer Netherlands, 2009. http://dx.doi.org/10.1007/978-90-481-3109-9_9.

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Ross, Duncan, Linda M. Lawson, and William McLeish. "Comparisons of Hurricane Fico Winds and Waves from Numerical Models with Observations from SEASAT-A." In Wave Dynamics and Radio Probing of the Ocean Surface, 595–613. Boston, MA: Springer US, 1986. http://dx.doi.org/10.1007/978-1-4684-8980-4_41.

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Toggweiler, J. R., and B. Samuels. "Is the Magnitude of the Deep Outflow from the Atlantic Ocean Actually Governed by Southern Hemisphere Winds?" In The Global Carbon Cycle, 303–31. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-84608-3_13.

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Capotondi, Antonietta, and M. A. Alexander. "The Influence of Thermocline Topography on the Oceanic Response to Fluctuating Winds: A Case Study in the Tropical North Pacific." In IUTAM Symposium on Advances in Mathematical Modelling of Atmosphere and Ocean Dynamics, 119–24. Dordrecht: Springer Netherlands, 2001. http://dx.doi.org/10.1007/978-94-010-0792-4_12.

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Olbers, Dirk, Jürgen Willebrand, and Carsten Eden. "The Wind-Driven Circulation." In Ocean Dynamics, 445–86. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-23450-7_14.

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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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Mitsuyasu, H., and T. Kusaba. "Wind Waves and Wind-Generated Turbulence in the Water." In The Ocean Surface, 389–94. Dordrecht: Springer Netherlands, 1985. http://dx.doi.org/10.1007/978-94-015-7717-5_52.

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Conference papers on the topic "Ocean winds"

1

Zhang, X., M. X. He, Q. Yang, and K. Zeng. "Effects of Winds on Ocean Color." In 2006 IEEE International Symposium on Geoscience and Remote Sensing. IEEE, 2006. http://dx.doi.org/10.1109/igarss.2006.1040.

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Hasager, C. B., P. Astrup, and P. Nielsen. "QuikSCAT and SSM/I ocean surface winds for wind energy." In 2007 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2007. http://dx.doi.org/10.1109/igarss.2007.4423602.

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Nagai, T., K. Shimizu, J. H. Lee, M. Iwasaki, T. Fujita, and M. Kudaka. "Offshore Winds and Currents Observation by GPS Buoy with Numerical Filtering Analysis." In OCEANS 2008 - MTS/IEEE Kobe Techno-Ocean. IEEE, 2008. http://dx.doi.org/10.1109/oceanskobe.2008.4530902.

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Rodriguez, E., A. Wineteer, D. Perkovic-Martin, T. Gal, B. W. Stiles, N. Niamsuwan, and R. Rodriguez Monje. "Ocean Surface Currents and Winds Using Dopplerscatt." In IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2018. http://dx.doi.org/10.1109/igarss.2018.8517656.

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Chang, Paul S., Zorana Jelenak, Faozi Said, and Seubson Soisuvarn. "CYGNSS Observations of Ocean Winds and Waves." In IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2018. http://dx.doi.org/10.1109/igarss.2018.8517846.

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Fois, F., P. Hoogeboom, F. Le Chevalier, and A. Stoffelen. "Future ocean scatterometry at very strong winds." In IGARSS 2014 - 2014 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2014. http://dx.doi.org/10.1109/igarss.2014.6947333.

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Zhang, Han, James L. Garrison, Rozaine Wijekularatne, and James G. Warnecke. "S-band ocean reflectometry in high winds." In IGARSS 2016 - 2016 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2016. http://dx.doi.org/10.1109/igarss.2016.7729518.

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Yueh, S. "Polarimetric Microwave Remote Sensing of Hurricane Ocean Winds." In 2006 IEEE International Symposium on Geoscience and Remote Sensing. IEEE, 2006. http://dx.doi.org/10.1109/igarss.2006.913.

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Yin, Pengfei, Qiu Yin, Ziwei Li, Yiqiang Zhang, Hua Xu, Xingfeng Chen, and Shangguo Ning. "Ocean surface winds measurement using reflected GNSS signals." In IGARSS 2010 - 2010 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2010. http://dx.doi.org/10.1109/igarss.2010.5653993.

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Babanin, Alexander V., and Haoyu Jiang. "Ocean Swell: How Much Do We Know." In ASME 2017 36th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/omae2017-61692.

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Swell waves are present in more than 80% of ocean seas, and provide significant adverse impact on maritime operations. Their prediction by wave-forecast models, however, is poor, both in terms of wave amplitude and, particularly, arrival time. The very definition of ocean swell is ambiguous: while it is usually perceived as former wind-generated waves, in fact it may reconnect with the local wind through nonlinear interactions. The paper will bring together an overview of the complex swell problem. The visible swell attenuation is driven by a number of dissipative and non-dissipative processes. The dissipative phenomena include interaction with turbulence on the water and air sides, with adverse winds or currents. Non-dissipative contributions to the gradual decline of wave amplitude come from frequency dispersion, directional spreading, refraction by currents, and lateral diffraction of wave energy. The interactions with local winds/waves can, on the contrary, cause swell growth. Swell arrival time is the least understood and the most uncertain problem. Joint analysis of buoy observations and model reanalysis shows that swell can be tens of hours early or late by comparison with model predictions. Linear and nonlinear effects which can contribute to such biases are discussed.

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Reports on the topic "Ocean winds"

1

Weller, Robert A. Upper Ocean Dynamics and Horizontal Variability in Low Winds. Fort Belvoir, VA: Defense Technical Information Center, September 2007. http://dx.doi.org/10.21236/ada541377.

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Weller, Robert A. Upper Ocean Dynamics and Horizontal Variability in Low Winds. Fort Belvoir, VA: Defense Technical Information Center, July 2010. http://dx.doi.org/10.21236/ada524314.

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Weller, Robert A. Upper Ocean Dynamics and Horizontal Variability in Low Winds. Fort Belvoir, VA: Defense Technical Information Center, September 2006. http://dx.doi.org/10.21236/ada629982.

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Weller, Robert A. Upper Ocean Dynamics and Horizontal Variability in Low Winds. Fort Belvoir, VA: Defense Technical Information Center, August 2002. http://dx.doi.org/10.21236/ada627329.

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5

Banner, Michael L., Russel P. Morison, William L. Peirson, and Peter P. Sullivan. Turbulence Simulation of Laboratory Wind-Wave Interaction in High Winds and Upscaling to Ocean Conditions. Fort Belvoir, VA: Defense Technical Information Center, September 2012. http://dx.doi.org/10.21236/ada574611.

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6

Plant, William J. Microwave Measurements of Winds, Waves, and Currents in the Global and Coastal Ocean. Fort Belvoir, VA: Defense Technical Information Center, September 1997. http://dx.doi.org/10.21236/ada635378.

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7

Rennick, Mary A., and Robert L. Haney. Solutions to the Shallow Water Equations in an Ocean Basin Forced by Unsteady Winds. Fort Belvoir, VA: Defense Technical Information Center, October 1988. http://dx.doi.org/10.21236/ada201682.

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8

Harcourt, Ramsey R. Impact of Typhoons on the Western Pacific Ocean DRI: Numerical Modeling of Ocean Mixed Layer Turbulence and Entrainment at High Winds. Fort Belvoir, VA: Defense Technical Information Center, September 2010. http://dx.doi.org/10.21236/ada542500.

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Harcourt, Ramsey R. Impact of Typhoons on the Western Pacific Ocean DRI: Numerical Modeling of Ocean Mixed Layer Turbulence and Entrainment at High Winds. Fort Belvoir, VA: Defense Technical Information Center, September 2012. http://dx.doi.org/10.21236/ada590609.

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Harcourt, Ramsey R. Impact of Typhoons on the Western Pacific Ocean (ITOP) DRI:Numerical Modeling of Ocean Mixed Layer Turbulence and Entrainment at High Winds. Fort Belvoir, VA: Defense Technical Information Center, September 2013. http://dx.doi.org/10.21236/ada591722.

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