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772 results for “fronts”
Raw Experimental Data for work presented in 'Precise Localization of Multiple Noncooperative Objects in a Disordered Cavity by Wave Front Shaping'
<p>This is the raw experimental data for the work presented in 'Precise Localization of Multiple Noncooperative Objects in a Disordered Cavity by Wave Front Shaping', to be published in Physical Review Letters.</p> <p> </p> <p>https://journals.aps.org/prl/accepted/b307fY31A5a13c5579fc4252303f8b2e5e024fc00</p> <p> </p> <p>See the README file for an explanation of the data.</p> <p> </p> <p> </p>
Mapping of the calving front of Eqip Sermia Glacier, West Greenland, by UAV photogrammetry
<p>These data contain photogrammetrical data collected by unmanned aerial vehicle (UAV) in July 2018 at Eqip Sermia Glacier. The data include processed data (orthoimage and digital elevation models) with the Structure-fom-Motion photogrammetrical software Agisoft Photoscan.</p> <p>For each, processed and raw, data are organized by glacier surveys with the following convention GLACIER_YYYYMMDD_HHMM or GLACIER_YYYYMMDD_HHMM_N.</p> <p>For instance : eqip_20180708_1225 contains the Data of the LARGE-SCALE survey of Eqip glacier that started on July 8, 2018 at 12:25 UTC time. eqip_20180707_1245_1 contains the Data of the FIRST repeat survey of the calving front of Eqip glacier that started on July 7, 2018 at 12:45 UTC time, eqip_20180707_1245_2 is the second repeat survey, eqip_20180707_1245_3 is the third and eqip_20180707_1245_4 is the last.</p> <p>Coordinate system used is UTM Zone 22W based on WGS84</p> <p>Take-off and landing site latitude and longitude was ( 69.757767 , - 50.228172 )</p> <p>This dataset is related to the article "High-endurance UAV for monitoring calving glaciers: Application to the Inglefield Bredning and Eqip Sermia, Greenland", G. Jouvet, Y. Weidmann, E. van Dongen, M. Lüthi, A. Vieli, J. V. Ryan, Frontiers in Earth Sciences.</p> <p> </p> <p> </p>
Mapping of the calving front of Hart, Sharp, Melville and Farquhar glaciers, Northwest Greenland, by UAV photogrammetry
<p>These data contain photogrammetrical data collected by unmanned aerial vehicle (UAV) in July 2017 in the Inglefield Bredning. The data include processed data (orthoimage and digital elevation models) with the Structure-fom-Motion photogrammetrical software Agisoft Photoscan.</p> <p>Data are organized by glacier surveys with the following convention GLACIER_YYYYMMDD_HHMM. For instance : farquhar_20170705_1914 contains the Data of the survey of Farquhar glacier that started on July 5, 2017 at 19:14 UTC time.</p> <p>Coordinate system used is UTM Zone 19N based on WGS84</p> <p>Take-off and landing site lattitude and longitude was ( 77.497424 , -66.678433 )</p> <p>This paper is related to the article "High-endurance UAV for monitoring calving glaciers: Application to the Inglefield Bredning and Eqip Sermia, Greenland", G. Jouvet, Y. Weidmann, E. van Dongen, M. Lüthi, A. Vieli, J. V. Ryan, Frontiers in Earth Sciences</p> <p> </p>
Mapping of the calving front of Heilprin Glacier, North West Greenland, by UAV photogrammetry
<p>These data contain photogrammetrical data collected by unmanned aerial vehicle (UAV) in July 2017 in the Inglefield Bredning. The data include processed data (orthoimage and digital elevation models) with the Structure-fom-Motion photogrammetrical software Agisoft Photoscan.</p> <p>Data are organized by glacier surveys with the following convention GLACIER_YYYYMMDD_HHMM. For instance : heilprin_20170705_1914 contains the Data of the survey of Heilprin glacier that started on July 5, 2017 at 19:14 UTC time.</p> <p>Coordinate system used is UTM Zone 19N based on WGS84</p> <p>Take-off and landing site lattitude and longitude was ( 77.497424 , -66.678433 )</p> <p>The data are related to the article "High-endurance UAV for monitoring calving glaciers: Application to the Inglefield Bredning and Eqip Sermia, Greenland", G. Jouvet, Y. Weidmann, E. van Dongen, M. Lüthi, A. Vieli, J. Ryan, Frontiers in Earth Sciences</p>
Mapping of the calving front of Tracy Glacier, North West Greenland, by UAV photogrammetry
<p>These data contain photogrammetrical data collected by unmanned aerial vehicle (UAV) in July 2017 in the Inglefield Bredning. The data include processed data (orthoimage and digital elevation models) with the Structure-fom-Motion photogrammetrical software Agisoft Photoscan.</p> <p>Data are organized by glacier surveys with the following convention GLACIER_YYYYMMDD_HHMM. For instance : tracy_20170705_1914 contains the Data of the survey of Tracy glacier that started on July 5, 2017 at 19:14 UTC time.</p> <p>Coordinate system used is UTM Zone 19N based on WGS84</p> <p>Take-off and landing site lattitude and longitude was ( 77.497424 , -66.678433 )</p> <p>The data are related to the article "High-endurance UAV for monitoring calving glaciers: Application to the Inglefield Bredning and Eqip Sermia, Greenland", G. Jouvet, Y. Weidmann, E. van Dongen, M. Lüthi, A. Vieli, J. Ryan, Frontiers in Earth Sciences</p>
Ice front blocking in a laboratory model of the Antarctic ice shelf
<p>Mass loss from the Antarctic Ice Sheet to the ocean has increased in recent decades, largely because the thinning of its floating ice shelves has allowed the outflow of grounded ice to accelerate. Enhanced basal melting of the ice shelves is thought to be the ultimate driver of change, motivating a recent focus on the processes that control ocean heat transport onto and across the seabed of the Antarctic continental shelf towards the ice. However, the shoreward heat flux typically far exceeds that required to match observed melt rates, suggesting other critical controls. By laboratory experiments on the Coriolis rotating platform, we show that the depth-independent component of the flow towards an ice shelf is blocked by the dramatic step shape of the ice front, and that only the depth-varying component, typically much smaller, can enter the sub-ice cavity. These results are consistent with direct observations of the Getz Ice Shelf system, as shown by Wahlin et al. (Nature 2019, in press).</p> <p>The selected data are velocity fields from a selection of 6 experiments, described in Wahlin et al. (2019), supplementary material, fig 4 and 9.</p> <ul> <li> EXP26,30,34 correspond to Fig. 4 a,b,c respectively (barotropic case)</li> <li> EXP44,50,51 correspond to Fig. 9 a,b,c respectively (baroclinic case)</li> </ul> <p>The velocity fields are measured by PIV from short image series (bursts) obtained by laser sheet illumination in several quasi-horizontal planes (for Fig 4, N=12 planes vertically separated by 6.2 cm, with 25 images per level, for Fig 9, N=7 planes vertically separated by 5.8 cm, with 19 images per level). The quasi-horizontal planes are parallel to the channel, slanted downward toward the iceshelf with an angle of 1.15 degree.</p> <p>For each experiment, the whole series of velocity fields is provided in /PCO1.png.sback.civ-PCO2.png.sback.civ.mproj (those are obtained by merging velocity fields from the images of two cameras denoted PCO1 and PCO2) velocity fields averaged inside each burst are provided in PCO1.png.sback.civ-PCO2.png.sback.civ.mproj.stat. Each velocity field is in a single netcdf file labeled by two indices denoting respectively the time and the index in the burst. Planes are scanned in a cyclic way, so that the same position is reached again after each increment of N in the first index.</p> <p>The average of these averaged velocity fields over 4 volumes when the current is fully established are provided in PCO1.png.sback.civ-PCO2.png.sback.civ.mproj.stat.stat. Details of the set-up and experimental conditions are provided in <a href="http://servforge.legi.grenoble-inp.fr/projects/pj-coriolis-17iceshelf">http://servforge.legi.grenoble-inp.fr/projects/pj-coriolis-17iceshelf</a></p> <p> </p> <div> </div>
Figure 4. Sphaerassiminea brevicula. A. front view B in Brackish water snails from Qi'ao-Dan'gan Island in the Pearl River estuary, China
Figure 4. Sphaerassiminea brevicula. A. front view B. back view. Scale bar = 1 mm.
Figure 2. Assiminea estuarina. A. front view B in Brackish water snails from Qi'ao-Dan'gan Island in the Pearl River estuary, China
Figure 2. Assiminea estuarina. A. front view B. back view. Scale bar = 1 mm.
Figs 11-13. Aulacus fascius. 11Xead, front. 12Xead, dorsal. 13 in Aulacidae of the southwestern United States, Mexico, and Central America (Hymenoptera)
Figs 11-13. Aulacus fascius. 11Xead, front. 12Xead, dorsal. 13 Mesosoma, dorsal.
Code to find the cost-effective treatments to stop a propagating front
<p>Invasive species propagation is a common phenomenon, and a major question is how humans would stop its propagation in the most cost-effective manner. This package includes software and simulation results to find the optimal shape of the suppression function under certain conditions.</p> <p>This package accompanies the paper "Optimizing the use of suppression zones for containment of invasive species" by Adam Lampert and Andrew Liebhold. In particular, it includes the complete code for generating Figs. 2-4 in the paper. The file front_complete_code.zip includes the entire code. The file simulation_results.zip includes the results.</p>
Resonance at the front of lightning impulse voltage waveforms caused by the load capacitor
<p>Numerical simulations with NI-Multisim had been done to verify the hypothesis. Fig. 5 illustrated the simulated waveform , when was set to 150‍ W and was set to 350‍ W. Fig.‍ 5(a) shows the simulated result when no inductance was considered. But for actual circuit, inductance is not negligible. When inductances were added to the circuit in series with the capacitance and resistance, the voltage step would be less steep, and oscillation would appear at the front period. Fig.‍ 5(b) shows the simulated waveform when 0.5‍ mH, 1‍ mH and 2‍ mH inductances are in series with sphere gap (FS), and respectively. These values were estimated according to the LI waveform generation circuit used in my test, and with an approximation that the lead inductance is around 1‍ mH/m.</p>
NOAA Unified Surface Analysis Fronts
<p>Unified Surface Analyses for all fronts drawn from the NWS Weather Prediction Center (WPC), Ocean Prediction Center (OPC), Tropical Analysis & Forecast Branch (TAFB), and Honolulu Forecast Office (HFO) from Dec 2006 through Dec 2022. Fronts are provided for full domain at the synoptic hours (0000 UTC, 0600 UTC, 1200 UTC, 1800 UTC) and for CONUS at the synoptic hours and at 0003 UTC, 0900 UTC, 1500 UTC and 2100 UTC. The full unified surface analysis domain is ranges from the equator to 80N and from 130E eastward to 10E.</p> <p>Code to read in this data can be found at <a href="https://github.com/ai2es/fronts">https://github.com/ai2es/fronts</a>.</p> <p>This data was used in the paper: Justin, A., Willingham, C., McGovern, A., Allen, J.T. (accepted with major revisions) Toward Operational Real-time Identification of Frontal Boundaries Using Machine Learning. To appear in Artificial Intelligence for the Earth Systems. Please cite this paper if you use our code and data. This citation will be updated when the paper is published.</p>
Dataset for: Efficacy of prescribed fire as a fuel reduction treatment in the Colorado Front Range
<p>Prescribed fires are an important management tool for reducing fuels and returning fire to the landscape. However, rarely are changes in fuels fully quantified using pre- to post-prescribed fire measurements, and those studies that do exist show variable results. In the southern Rockies, little literature exists on the impacts of prescribed fires, thus we examined multiple prescribed fires in northern Colorado to understand fire effects and changes in fuel complexes. Most prominently, prescribed fires influenced litter, duff, and rotten coarse woody debris but did not influence other surface fuels. Crown base height increased and tree density decreased, while basal area was relatively unimpacted. Season of burning impacted fire effects as substrate burn severity, bole char, and crown volume scorched were highest in summer and fall. Continued monitoring of prescribed fires is critical to understand the influence of prescribed fire on wildfires and ultimately improving prescribed fire outcomes.</p>
Data for the manuscript titled "Solute front shear and coalescence control concentration gradient dynamics in porous micromodel"
<p>Concentration images and data for plots for the manuscript "Solute front shear and coalescence control concentration gradient dynamics in porous micromodel" submitted for publication in Geophysical Research Letters.</p> <p>See the README file for explanations on the data file.</p> <p><strong>Movie captions:</strong></p> <p><strong>Movie S1:</strong> Concentration field for the Péclet Pe = 33 experiment. Solid pillars are represented by the gray discs, and the colormap corresponds to the rescaled concentration <span class="math-tex">\(c/c_\mathrm{max}\)</span>. The black line represents the solute front, which is the boundary of the continuous <span class="math-tex">\(c/c_\mathrm{max} < 0.5\)</span> region within the porous medium. The x- and y-coordinates of the porous medium length and width (respectively) are rescaled by the average pore diameter <span class="math-tex">\(\lambda\)</span>.</p> <p><strong>Movie S2:</strong> Concentration gradient field for the Pe = 33 experiment. Solid pillars are represented by the gray discs, and the colormap corresponds to the rescaled gradient <span class="math-tex">\( a \nabla c / c_\mathrm{max}\)</span>. The x- and y-coordinates of the porous medium length and width (respectively) are rescaled by the average pore diameter <span class="math-tex">\(\lambda\)</span>.</p> <p><strong>Movie S3:</strong> Concentration field for the Pe = 1104 experiment. Solid pillars are represented by the gray discs, and the colormap corresponds to the rescaled concentration <span class="math-tex">\(c/c_\mathrm{max}\)</span>. The black line represents the solute front, which is the boundary of the continuous <span class="math-tex">\(c/c_\mathrm{max} < 0.5\)</span> region within the porous medium. The x- and y-coordinates of the porous medium length and width (respectively) are rescaled by the average pore diameter <span class="math-tex">\(\lambda\)</span>.</p> <p><strong>Movie S4:</strong> Concentration gradients field for the Pe = 1104 experiment. Solid pillars are represented by the gray discs, and the colormap corresponds to the rescaled gradient <span class="math-tex">\( a \nabla c / c_\mathrm{max}\)</span>. The x- and y-coordinates of the porous medium length and width (respectively) are rescaled by the average pore diameter <span class="math-tex">\(\lambda\)</span>.</p>
Photogrammetric survey of the Fontebranda street front
<p>Photo set of the photogrammetric survey made by drone of the Fontebranda street front in Siena</p>
Photogrammetric Survey of via Pendola street front
<p>Photo set of the photogrammetric survey of via Pendola street front of the city centre of Siena</p>
Heat transport across the Antarctic Slope Front controlled by cross-slope salinity gradients
<p>Feb 2023 updates: </p> <ul> <li>Add code for EKE spectral analysis to MITgcm_ASF-heat-ver3/analysis/spectrum/</li> <li>Add products of 5km and 10km runs to products_new-ver3</li> <li>Add MITgcm source code, copied from <a href="http://mitgcm.org/">http://mitgcm.org</a></li> </ul> <p>This release contains updates on analysis code and products.</p> <ul> <li>MITgcm_ASF-heat-ver3/<strong>newexp</strong>/: the Matlab scripts used to generate and run the MITgcm simulations</li> <li>MITgcm_ASF-heat-ver3/<strong>analysis</strong>/<strong>cross_slope</strong>/ and MITgcm_ASF-heat-ver2/<strong>analysis</strong>/<strong>plots</strong>/: the Matlab scripts used to analyze model output and make plots.</li> <li>MITgcm_ASF-heat-ver3/analysis/<strong>spectrum</strong>/: the<strong> </strong>Matlab<strong> </strong>scripts to calculate EKE spectra<strong> </strong></li> <li>exps_configuration.zip: the configurations of the MITgcm simulations.</li> <li><strong>products_new-ver3.zip</strong>: the products calculated from MITgcm diagnostics, including 7-year means of all the model outputs, overturning streamfunctions, neutral density, shoreward heat transport, kinetic energy, temporal decomposition, isopycnal thickness fluxes of the 5km and 10km runs, etc. </li> <li>ThicknessFlux_FreshShelf.zip: products of isopycnal thickness flux, used to calculate the decomposition of eddy/tidal heat advection/diffusion, for the "fresh-shelf" simulation. </li> <li>ThicknessFlux_ref.zip: as above, but for the reference simulation.</li> <li>ThicknessFlux_DenseShelf.zip: as above, but for the "dense-shelf" simulation. </li> </ul> <p>The source code of the Massachusetts Institute of Technology General Circulation Model (MITgcm) is available at: <a href="http://mitgcm.org/">http://mitgcm.org</a>.</p> <p><strong>All the raw data of the model output are available at: <a href="https://doi.org/10.15144/S47P49">https://doi.org/10.15144/S47P49</a>.</strong></p> <p>To reproduce MITgcm_ASF simulations: </p> <ol> <li>Start each simulation with a 20-year spin-up integration. Before running each simulation, you need to substitute <em>&OBCS_PARM04</em> with <em>&OBCS_PARM05 </em>in the file <em>input/<strong>d</strong>ata.obcs</em>, and substitute <em>&EXF_NML_05 </em>with <em>&EXF_NML_OBCS</em> <em> </em>in the file <em>input/data.exf</em>. For simulations with very fresh shelf waters (e.g., shelf salinity = 33 psu), you need to spin up the simulation with a very small time step (e.g., 60s) for ~ two months, and then use a larger time step. </li> <li> <p>Initialize the production run from the corresponding spin-up run, using the Matlab script <em>initialize.m</em> in the folder<em> MITgcm_ASF-heat-ver2/newexp/. </em>When using the LAYERS package, you need to substitute<em> numperlist = 1</em> with <em>numperlist = 2 </em>in the file<em> code/DIAGNOSTICS_SIZE.h</em> before running the simulations.</p> </li> </ol> <p> </p> <p>Notes on calculationg the overturning streamfunction and its mean/eddy/tidal decomposition using the MITgcm LAYERS package: </p> <ul> <li>avg_t: Calculate time averages. It has been modified since the vertical number of layers can be different from Nr. </li> <li>calc_Overturning_pt, usscar_plot_overturning_pt: calculate and plot eddy/mean/isopycnal overturning streamfunction using potential temperature layer fluxes.</li> </ul> <ul> <li>calc_Overturning_rho, usscar_plot_overturning_rho: calculate and plot eddy/mean/isopycnal overturning streamfunction using potential density layer fluxes.</li> </ul> <ul> <li>calc_Overturning_pt_Aocean, usscar_pt_overturning_rho_Aocean (<strong>recommended if your bathymetry is not flat</strong>): calculate and plot eddy/mean/isopycnal overturning streamfunction using <em>potential temperature</em> layer fluxes. For each latitude, use the total ocean area below a certain level to interpolate the streamfunction from pt space to z space. </li> </ul> <ul> <li>calc_Overturning_rho_Aocean, usscar_plot_overturning_rho_Aocean (<strong>recommended <strong>if your bathymetry is not flat</strong></strong>): calculate and plot eddy/mean/isopycnal overturning streamfunction using <em>potential density</em> layer fluxes. For each latitude, use the total ocean area below a certain level to interpolate the streamfunction from potential density space to z space.</li> </ul> <ul> <li>calc_decomposition_OT, plot_OT_rho_Aocean_TidalEddyMean: decompose the isopycnal overturning streamfunction into <strong>tidal</strong>/eddy/mean components, using potential density layer fluxes.</li> </ul> <p>Feel free to contact Yidongfang Si via <strong>ysi@g.ucla.edu</strong> if you have any questions.</p>
CCE fronts
<p>Code and data supporting the article "Sub-frontal niches of plankton communities driven by transport and trophic interactions at ocean fronts" (Inès Mangolte, Marina Lévy, Clément Haeck & Mark Ohman) submitted to Biogeosciences (EGUsphere) in march 2023.</p>
Identification of Sea Surface Temperature and Sea Surface Salinity Fronts along the California Coast: Application Using Saildrone and Satellite Derived Products
<p>Data and Method described in https://www.mdpi.com/2072-4292/15/2/484, "Identification of Sea Surface Temperature and Sea Surface Salinity Fronts along the California Coast: Application Using Saildrone and Satellite Derived Products"</p> <p> </p>
PDF of rescaled front fluctuations in Contact Process
<p>Data of the PDF of chi (rescaled front fluctuations), for 1, 2 and 3 dimensions. It has been measured for the interface representation of a contact process system at its critical point. See <a href="https://arxiv.org/abs/2304.10883">arXiv:2304.10883</a> for more details.</p> <p>Each file contain four headers starting with #. The columns show, in order, the chi, the probability and the error estimate by the jackknife procedure. All the columns are separated by space.</p> <p>Data for one-dimensional system in: chiPDF-1D-L8192-f2000.dat<br> Data for two-dimensional system in: chiPDF-2D-L512-f498.dat<br> Data for three-dimensional system in: chiPDF-3D-L128-f20.dat</p> <p>The datasets have been produced and employed in the context of a scientific work currently published in <a href="https://arxiv.org/abs/2304.10883">arXiv:2304.10883</a>. </p>
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