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Dataset results
8 results for “Wind-waves”
Laboratory measurements of wind, waves, and turbulence in hurricane conditions in the ASIST wind-wave facility
<p>Laboratory measurements of wind, waves, and turbulence in hurricane conditions, collected in September and October of 2018 and January of 2019 in the ASIST wind-wave facility, in the SUSTAIN laboratory at the University of Miami.</p> <p>This dataset includes two experiments, one with fresh water ("fresh") and another with seawater ("salt"), each in 10-m winds from 0 to approximately 42 m/s. Data include:</p> <ul> <li>3-dimensional wind velocity at 20 Hz sampling frequency from Campbell Scientific IRGASON sonic anemometer (collected in 2018)</li> <li>2-dimensional (along-tank and vertical) wind velocity at 1000 Hz sampling frequency from TSI IFA-300 hot film anemometer (collected in 2018)</li> <li>1-dimensional (along-tank) wind velocity at 10 Hz sampling frequency from a pitot anemometer (collected in 2018 and 2019)</li> <li>3-dimensional water velocity in the bottom 5 cm of the tank at 100 Hz sampling velocity from Nortek Vectrino velocimeter. (collected in 2018)</li> <li>Water elevation at 20 Hz sampling frequency at 6 locations in the tank from Senix Toughsonic 30 ultrasonic distance meters (collected in 2019)</li> <li>Along-tank static air pressure difference at 10 Hz sampling frequency from Baratron MKS 226 differential pressure transducer (collected in 2019)</li> </ul> <p>All data is in NetCDF4 format.</p> <p>Experiment set up and positions of instruments are documented in more detail in Curcic and Haus (2020), Revised estimates of ocean surface drag in strong winds, <em>Geophysical Research Letters</em>, <a href="https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2020GL087647">https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2020GL087647</a>.</p> <p>Produced as part of the National Science Foundation Award #1745384, titled "Air-Sea Momentum Transfer in Extreme Wind Conditions"<strong>.</strong></p> <p>Contact: Milan Curcic <mcurcic@miami.edu></p>
Adriatic Sea wind-wave climate years 1981-2010 and 2021-2050 (RCP4.5 and RCP8.5)
<p>Adriatic Sea mean annual 50th, 90th, 95th and 99th percentiles of the significant wave height (Hs) from WAVEWATCH III v6.07 (2 km) forced with 1-hour ERA5 wind fields statistically scaled to QQ-match COSMO-CLM fields (available at https://doi.org/10.5281/zenodo.6021380).</p> <p>Reference periods:</p> <p>1) Historical climate: years 1981-2010</p> <p>2) Future climate: years 2021-2050 (IPCC scenario RCP4.5 and RCP8.5)</p>
Data/ codes used in the the Natural Hazards and Earth System Sciences (NHESS) publication titled "Wind-Wave Characteristics and extremes along the Emilia-Romagna coast" by Pranavam Ayyappan Pillai et al. (2022)
<p>The archive contains datasets and codes used in the manuscript titled "Wind-Wave Characteristics and extremes along the Emilia-Romagna coast", and published in the journal <em>Natural Hazards and Earth System Sciences</em> (<em>NHESS</em>) by Pranavam Ayyappan Pillai et al., 2022.</p> <p>Pranavam Ayyappan Pillai, U., Pinardi, N., Federico, I., Causio, S., Trotta, F., Unguendoli, S., and Valentini, A.: Wind-Wave Characteristics and extremes along the Emilia-Romagna coast, Nat. Hazards Earth Syst. Sci. Discuss. https://doi.org/10.5194/nhess-2022-103, 2022.</p>
Data for: Ocean surface wave slopes and wind-wave alignment observed in Hurricane Idalia
Open the record for dataset details and reuse information.
SWAN simulations: Local wind-waves in partial sea ice cover
<p>This repository contains data and scripts associated with the study: <em>Scaling simulations of local wind-waves amid sea ice floes </em>by S. Brenner & C. Horvat.</p>
Datatset from "Coastal flooding in the Maldives induced by mean sea-level rise and wind-waves: from global to local coastal modelling"
<p>Resulting downscaled wave fields from the WaveWatch III simulations for the four main wave directions identified and six return periods (10, 20, 50, 100, 500, and 1000 years).</p>
Dataset for the paper "Parameter study and optimization of floating wind-wave co-generation system based on the Taguchi method"
<p>The Dataset is the result files for the paper "Parameter study and optimization of floating wind-wave co-generation system based on the Taguchi method"</p>
Data for Paper: Wind-wave momentum flux in steep, strongly forced, surface gravity wave conditions
<p>Laboratory measurements of wind, waves, and airside static pressure under low to moderate wind forcing (U10 ~ 6 -16 m/s) collected in Oct 2022 in the SUSTAIN wind-wave facility at the University of Miami.</p> <p>This dataset includes 11 runs, all of which contain monochromatic waves generated by the wave paddles with various wind forcing exerted above. All data is in ".mat" formate readable via MATLAB.</p> <p>Experiment set up and positions of instruments are documented in more details in the manuscript Tan et al (2024): Wind-wave momentum flux in steep, strongly forced, surface gravity wave conditions.</p> <p> Fig_3: time series static pressure p sampled at 100 Hz and horizontal/vertical wind speed (u/w) sampled at 1000 Hz</p> <p>Fig_4: Frictional velocity u_star_Rn* obtained at differenet heights (h) using frictional velocity</p> <p>Fig_5: a folder that containes the phase-averaged, spline-interpolated static pressure (p2_total), X-coordinate (long-wave phase), Y coordinate (heights above the stationary water) and the u/w at respective heights to generate airflow streamlines</p> <p>Fig_6 and 7: NSS-based phase-averaged, spline-interpolated pressure (delta_P_new).</p> <p>Fig_8: phase-averaged form stress based on measurements and NSS for all 11 runs</p> <p>Fig_9: NSS-based form stress deviation from measured form stress (NSS miscal) against wind-steepness and wave age;</p> <p>Fig_10 and 11: wave growth rate (gamma) against wave age (Cp/ustar) and two other parameterization from Fig.10</p> <p>(The revised version contains the projection of Donelan (1999) and Yang et al. (2013)'s data to the U10/Cp parameterization in panel (b) per reviewer's suggestion);</p> <p>Fig_12: form stress values (tau_form) and form stress to total stress (tau_tot) ratio.</p> <p>(The revised version contains U10 per reviewer's suggesion).</p> <p>This project was Funded in part by Office of Naval Research/Naval Research Laboratory base program unit 73-1Y91.</p> <p>Please cite our JGR: Oceans paper "Wind-wave momentum flux in steep, strongly forced,1 surface gravity wave conditions" if you were to use our dataset.</p> <p>Contact: Peisen Tan <pxt254@miami.edu> for different levels of raw data collected in this experiment.</p> <p>We kindly ask the readers who use our dataset to cite our paper:</p> <p><span>Tan, P.</span><span>, </span><span>Savelyev, I.</span><span>, </span><span>Laxague, N. J. M.</span><span>, </span><span>Haus, B. K.</span><span>, </span><span>Curcic, M.</span><span>, </span><span>Matt, S.</span><span>, et al. (</span><span>2025</span><span>). </span><span>Wind-wave momentum flux in steep, strongly forced, surface gravity wave conditions</span><span>. </span><em>Journal of Geophysical Research: Oceans</em><span>, </span><span>130</span><span>, e2024JC021616. </span><a href="https://doi.org/10.1029/2024JC021616">https://doi.org/10.1029/2024JC021616</a></p> <p>We would also appreciate if you can send us a copy of your manuscript if you have used our data. Thank you!</p>
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