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13 results for “Wind forcing”
Regional HYCOM output: absolute and relative wind forcing experiments
<p>Hybrid Coordinate Ocean Model (HYCOM) output from 2 forced regional simulations of the Agulhas Current. The first experiment is forced by absolute winds, the second experiment is forced by relative winds (the wind speed relative to the current speed). Data uploaded here are the sea surface height and surface u and v velocities, for both experiments. This is weekly output from January 1993- December 2013 at 1/10°. Also uploaded is a vertical section of the HYCOM output along the ACT transect in the Agulhas Current (~33.4°S at the coast and extending 300km offshore) for both experiments from 2010- 2013.</p> <p>For more information on the data please refer to "L. Braby, Backeberg, B., Krug M. and Reason C. (in prep), Quantifying the impact of wind-current feedback on mesoscale variability in forced simulation experiments of the Agulhas Current using an eddy tracking algorithm."</p>
CESM2 data for "Internal Wind Driven Ocean Circulation Variability Delays the Time of Emergence of Externally Forced Sea Surface Temperature Trends" - submitted to GRL
<p>CESM2 Experiment names:</p> <ul> <li>MDM = mechanically decoupled model (referred to as MDM in paper)</li> <li>FCM = fully coupled model (referred to as FCM in paper)</li> </ul> <p>Details for files cesm2.[experiment name].SST.noise.nc</p> <ul> <li>These files include the unfiltered time-varying SST noise </li> <li>"noise" refers to ensemble standard deviation (no 10-yr running mean has been applied) </li> <li>"SST" is the annual mean SST</li> <li>Time period is 1900-2014</li> </ul> <p>For the ensemble mean SST, see previously created Zenodo repository by Fu et al: https://zenodo.org/records/10484207</p> <p>For other ensemble mean variables, see previously created Zenodo repository by McMonigal et al: https://zenodo.org/records/7154374</p>
Diurnal waves forced by horizontal convergence of near-surface winds on Mars
<p>This site provides public access to data used in the following journal article: </p> <p>D. Hinson and J. Wilson (2023). Diurnal waves forced by horizontal convergence of near-surface winds on Mars, Icarus 394, 115420, doi: 10.1016/j.icarus.2022.115420 </p> <p><a href="https://ntrs.nasa.gov/api/citations/20230001896/downloads/20230001896-Hinson_2022_Diurnal_waves%5B1%5D.pdf">https://ntrs.nasa.gov/api/citations/20230001896/downloads/20230001896-Hinson_2022_Diurnal_waves%5B1%5D.pdf</a></p> <p> </p>
Data from wind-forced simulation of a salinity front
<p>This upload has data from a representative snapshot of a wind-forced simulation of a shallow salinity front, representative of conditions in the Bay of Bengal.</p> <p>1. You will need to use 'gunzip' followed by 'tar -xvf' to extract the zipped and tarred archive.</p> <p>2. The uncompressed archive has three files, one containing the basic flow variables (three components of velocity, temperature, salinity, etc.), and one containing the vertical coordinates of the cell faces/centers.</p>
GAIA model simulate data of doubled CO2 (Forces, advections, and winds)
<p>This dataset contains forces, advections, and winds output from the GAIA model, that are related to the Figures in the paper. The forces and advections are divided by the Coriolis parameter or a zonal mean absolute vorticity. </p>
supplementary to "SnowPappus v1.0, a blowing-snow model for large-scale applications of Crocus snow scheme" , 2D wind forcing
<p>This is a supplementary material to article "SnowPappus v1.0, a blowing-snow model for large-scale applications of Crocus snow scheme" ( unpublished at the publication date of this dataset)</p> <p>It contains the 2D wind forcing for Crocus-SnowPappus simulations on the Grandes Rousses test zone. It was generated using DEVINE wind downscaling method ( Le Toumelin et al., 2022 )</p>
Linking Seasonal-to-Interannual Variability of Intermediate Currents in the Southwest Tropical Pacific to Wind Forcing and ENSO
<p>This dataset contains zonal velocity data observed by the mooring at 142E/0,142E,1S,141.4E/1.7S. It is supplementary of the paper "<strong>Linking Seasonal-to-Interannual Variability of Intermediate Currents in the Southwest Tropical Pacific to Wind Forcing and ENSO</strong>" published by the Geophysical Research Letters (https://doi.org/10.1029/2021GL092440). Please let me know if you need any more information.</p>
Data from: Covariation in abscission force and terminal velocity of wind-borne sibling seeds alters long distance dispersal projections
1. Despite the fact that seeds are unlikely to be identical—even among siblings within a maternal individual—dispersal models typically use one mean trait value to represent the ability of an entire species to disperse. Previous work has shown that the environmental conditions under which individuals leave the maternal site strongly affect how far seeds will travel. However, less is known about how trait variation within individuals contributes to dispersal or how such variation might interact with abiotic factors. 2. Here, we develop the use of an ergometer in a novel application to investigate variation in seed traits, specifically the force required for seed abscission and seed terminal velocity, exhibited by seeds from different locations within maternal capitula of the invasive species Carduus nutans (Asteraceae). 3. We find that seeds from the center of capitula are significantly easier to liberate and have slower falling velocities than siblings found near the edge of capitula. When abscission force is positively correlated with terminal velocity, slowly falling, easily abscised seeds are projected to travel much further than the average seed on slow winds. 4. Our experimental and theoretical results, which together show that within-individual variation can strongly affect model projections of species dispersal, have important implications for our broader understanding of population spread rates, the spatial structure of populations, metapopulation connectivity, and gene flow in the landscape.
Upstream and downstream wind-stress forcing of seasonal variability of Luzon Strait Deep Overflow transport
<p>This is the dataset used for figures in paper "Upst<span>ream and downstream wind-stress forcing of seasonal variability of Luzon Strait Deep Overflow transport".</span></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>
Blowing in the wind: Experimental assessment of clinging performance and behavior in Anolis lizards during hurricane-force winds
<p>1. Extreme weather events, such as hurricanes, can be ecologically devastating and cause widespread mortality. Recent studies in <em>Anolis</em> lizards report hurricane-induced phenotypic shifts and selection favoring morphological variation related to clinging performance. Although it is difficult to observe organismal responses during extreme events in nature, we can experimentally simulate the high-speed winds associated with hurricanes to evaluate the putative mechanism underlying observed patterns of natural selection.</p> <p>2. In this study, we used two laboratory experiments to better understand the clinging performance and behavior of <em>Anolis</em> lizards when experiencing hurricane-force winds. We assessed the physical ability of lizards when using the combined function of their claws, limbs, toepads, and other traits to resist forces pulling them off a perch. We also evaluated the combination of this physical clinging ability of lizards and their behavioral responses to avoid being blown off a perch during high winds. We assessed behavior that could decrease exposure of lizards to wind and increase their clinging ability.</p> <p>3. Clinging force measurements revealed variation in performance among species and substrates not reflected in clinging times for lizards experiencing hurricane-force winds, revealing the importance of behavior when experiencing high winds. The most arboreal species (<em>A</em>. <em>carolinensis</em>) had substantially longer clinging times on rough substrates compared to the other species, presumably due to its larger toepads for increased clinging as well as its shorter limbs that reduced drag.</p> <p>4. Under high-speed winds, lizards commonly shifted to the more protected leeward side of dowels, especially on broad and rough substrates, presumably to reduce exposure. This reveals how behavior can mediate factors influencing clinging ability during hurricanes and, in conjunction with ecologically relevant variation in morphology and substrate properties, contribute to clinging performance.</p> <p>5. Our experiments reveal that behavior strongly influences clinging performance during high winds beyond that predicted by physical traits alone. Thus, microhabitat selection of perches and the position of a lizard on its perch during a hurricane will likely have important consequences for clinging performance. This may alter how selection acts on morphological traits and influence the susceptibility of different species to these extreme weather events.</p>
Blowing in the wind: Experimental assessment of clinging performance and behavior in Anolis lizards during hurricane-force winds
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Data from: Covariation in abscission force and terminal velocity of wind-borne sibling seeds alters long distance dispersal projections
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