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57 results for “Drifters”
CARTHE drifter trajectories acquired at Fruholmen domain in October 2017 to January 2018
<p>The dataset contains trajectories from 21 CARTHE drifters which were released in October 2017 near the Fruholmen island (northern Norway). Geographical coordinates for each drifter were acquired approximately every 5 minutes via GPS. The project was funded by Research Council of Norway grants 237906 (CIRFA) and 244262 (Retrospect).</p>
MetOcean drifters for NORSE2019 experiment
<p>Trajectories for two triplets of MetOcean drifters (2 iSphere, 2 CODE, 2 SVP) deployed during the oil-on-water experiment conducted in the North Sea June 2019. The data and experiment is described in Brekke et al., Integration of multi-sensor datasets and oil drift simulations - a free floating oil experiment in open ocean, to be submitted to JGR Oceans June 2020.</p>
Light and water quality observations from neutrally buoyant drifters in rivers
<p><span>Vertical motion is an important driver of sunlight exposure in aquatic environments, shaping the growth and fate of materials and organisms. We derive a simple model accounting for turbulent depth fluctuations of particles to predict the depth that contributes the most sunlight exposure (effective depth) as well as the single depth that, if measured at one place over time, produces the same total sunlight exposure as a moving particle (functional depth). Field measurements of light and depth in rivers using neutrally buoyant drifters and buoys validate our model. Effective depth varied from 0.1-1.5 m below the water surface and was ~30% of the overall water depth on average. Functional depth varied from 0.67-2.3 m and was ~50% of the overall water depth on average. Functional and effective depth are physically based concepts incorporating turbulent motion, spatial variability, and water clarity offering new approaches to characterize light exposure in aquatic environments.</span></p> <p class="MsoNormal"><span> </span></p>
Sample Drifter Dataset for example in JuliaConProceedings2023
<p>Summary : </p> <ul> <li>jld2 file that contains inputs to the particle tracking example</li> <li>region : Gulf of Mexico</li> <li>source : OceanRobots.jl (incl. data references)</li> </ul> <p>File content :</p> <p> ├─🔢 drifters_real<br> ├─🔢 u<br> ├─🔢 v<br> ├─🔢 x<br> ├─🔢 y<br> ├─🔢 x0<br> ├─🔢 y0<br> ├─🔢 polygons<br> ├─🔢 res</p> <p> └─ ⋯ (3 more entries)</p>
North Atlantic Ocean Drifter Dataset for Multivariate Probabilistic Regression with Natural Gradient Boosting
<p>Dataset created for Multivariate Probabilistic Regression with Natural Gradient Boosting application section. Supplied for replication. Variables in the dataset:</p> <ul> <li>Tx, Ty, Wx, Wy: Wind Stress (Pa) (T), Wind Speed (m/s) (W) in the longitudinal (x) and latitudinal (y) directions.</li> <li>u_av, v_av: surface geostrophic sea water velocity (m/s) longitudinal and latitudinal respectively.</li> <li>lon,lat: The longitude (-180,180) and latitude (-90,90) of the drifters.</li> <li>t: day of year (0,366).</li> <li>u, v: The velocities of the drifters (m/s).</li> </ul> <p>Note u, v, Tx, Ty, Wx, Wy are all filtered as described in the papers supplemental information.</p> <p>If used the following must be acknowledged or cited appropriately. You must follows the terms of the use of the following sources:</p> <p>The Global Drifter Program</p> <p>https://www.aoml.noaa.gov/phod/gdp/interpolated/data/all.php</p> <p>(lon, lat, u, v)</p> <p>CMEMS datasets which are interpolated to the drifter locations:</p> <p>1. GLOBAL OCEAN GRIDDED L4 SEA SURFACE HEIGHTS AND DERIVED VARIABLES REPROCESSED (COPERNICUS CLIMATE SERVICE) https://resources.marine.copernicus.eu/product-detail/SEALEVEL_GLO_PHY_CLIMATE_L4_REP_OBSERVATIONS_008_057/INFORMATION<br> (u_av, v_av)</p> <p>2. Global Ocean Wind L4 Reprocessed 6 hourly Observations https://resources.marine.copernicus.eu/product-detail/WIND_GLO_WIND_L4_REP_OBSERVATIONS_012_006/INFORMATION (Wx, Wy, Tx, Ty)<br> <br> <br> <strong>Note</strong> this dataset will not be regularly updated. Any changes in the source products will not be brought into this dataset.</p>
Garden Island Drifter Study
<p>This data set contains data related to the manuscript "Flow re-entrainment in coastal reef systems".</p> <p>The file "Modelled_exitrates.mat" contains the drifter exit rates <em>E<sub>1</sub></em> and <em>E<sub>2</sub></em> for the parameter space wave height <em>H<sub>m0</sub></em>, alongshore current <em>v<sub>along</sub></em>, channel spacing and bed friction <em>c<sub>f</sub></em> and time series of relative exit rate <em>E<sub><span> </span>2</sub></em> (max. 1)<em>. </em>For more details, please see related manuscript.</p>
Light and water quality observations from neutrally buoyant drifters in rivers
Open the record for dataset details and reuse information.
Dataset to accompany the manuscript "Drifter observations reveal intense vertical velocity in a surface ocean front"
<p>This dataset has been used in the publication "Drifter observations reveal intense vertical velocity in a surface ocean front"</p> <p>The dataset contains data from the following platforms<br> · Drifters<br> · Underway-CTD</p>
SPURS-2 Drifter data for the E. Tropical Pacific field campaign
The SPURS (Salinity Processes in the Upper Ocean Regional Study) project is a NASA-funded oceanographic process study and associated field program that aim to elucidate key mechanisms responsible for near-surface salinity variations in the oceans. The project is comprised of two field campaigns and a series of cruises in regions of the Atlantic and Pacific Oceans exhibiting salinity extremes. SPURS employs a suite of state-of-the-art in-situ sampling technologies that, combined with remotely sensed salinity fields from the Aquarius/SAC-D, SMAP and SMOS satellites, provide a detailed characterization of salinity structure over a continuum of spatio-temporal scales. The SPURS-2 campaign involved two month-long cruises by the R/V Revelle in August 2016 and October 2017 combined with complementary sampling on a more continuous basis over this period by the schooner Lady Amber. Focused around a central mooring located near 10N,125W, the objective of SPURS-2 was to study the dynamics of the rainfall-dominated surface ocean at the western edge of the eastern Pacific fresh pool subject to high seasonal variability and strong zonal flows associated with the North Equatorial Current and Countercurrent. A drifter is a passive Lagrangian sensor platform consisting of a surface buoy and tethered subsurface drogue. Drifter buoys contain GPS/ARGOS and satellite data transmitters, with sensors measuring temperature and other properties. For SPURS-2, a range of drifters were deployed during both Revelle SPURS-2 cruises. These included: standard Surface Velocity Program (SVP) drifters with salinity sensors added (SVP/S), Surface Contact Salinity drifters, CODE, SADOS, AOML and CARTHE-SUPRACT drifters. For each series, drifter data have been aggregrated within single netCDF data files with their corresponding drifter-IDs and associated near-surface salinity, temperature georeferenced (GPS and ARGOS) trajectory series data.
Drifter data for the SPURS-1 N. Atlantic field campaign
The SPURS (Salinity Processes in the Upper Ocean Regional Study) project is an oceanographic process study and associated field program that aim to elucidate key mechanisms responsible for near-surface salinity variations in the oceans. The project involves two field campaigns and a series of cruises in regions of the Atlantic and Pacific Oceans exhibiting salinity extremes. SPURS employs a suite of state-of-the-art in-situ sampling technologies that, combined with remotely sensed salinity fields from the Aquarius/SAC-D and SMOS satellites, provide a detailed characterization of salinity structure over a continuum of spatio-temporal scales. The SPURS-1 campaign involved a series of 5 cruises during 2012 - 2013 seeking to characterize the salinity structure and balance in a high salinity, high evaporation, and low rainfall region of the subtropical North Atlantic. It aims to resolve processes responsible for maintaining the subtropical surface salinity maximum in this region and within a 900 x 800-mile square study area centered at 25N, 38W. Approximately 83 drifters were deployed during the SPURS-1 campaign. A drifter is a passive Lagrangian sensor platform consisting of a surface buoy and tethered subsurface drogue. Drifter buoys contain GPS/ARGOS and satellite data transmitters, with sensors measuring temperature and other properties. For SPURS-1, these were standard Surface Velocity Program (SVP) drifters with salinity sensors added (SVP/S). Data for both US and European drifter deployments during SPURS-1 are available here. For each series, drifter data have been aggregrated within single netCDF data filea with their corresponding drifter-IDs and associaciated near-surface salinity, temperaure georeferenced (GPS and ARGOS) trajectory series data.
subset of the ocean drifter data set from the CloudDrift project
<p>For more information see :</p> <ul> <li>https://www.ncei.noaa.gov/access/metadata/landing-page/bin/iso?id=gov.noaa.nodc:AOML-GDP-1hr</li> <li>https://www.aoml.noaa.gov/phod/gdp/hourly_data.php</li> <li>https://clouddrift.org/index.html</li> </ul>
S-MODE L2 Position Data from Surface Drifters Version 1
This dataset contains in-situ position data from surface drifters from the Sub-Mesoscale Ocean Dynamics Experiment (S-MODE) conducted approximately 300 km offshore of San Francisco during a pilot campaign over two weeks in October 2021, and two intensive operating periods (IOPs) in Fall 2022 and Spring 2023. S-MODE aims to understand how ocean dynamics acting on short spatial scales influence the vertical exchange of physical and biological variables in the ocean. Drifting buoys were deployed from the research vessels and configured to nominally report positions every five minutes. Drifters deployed were a mixture of CARTHE and Microstar types. CARTHE drifters are drogued at 40 cm depth and measure the average horizontal velocity of currents in the upper 60 cm of the ocean (Novelli et al., 2017). Microstar drifters are drogued at 1 m depth and measure the average horizontal velocity of ocean currents between 0.4 m and 1.6 m depth (Ohlmann et al., 2005). See the S-MODE Data Submission Report sections 2.3.2.2, 2.4.2.2 and 2.5.2.3 for more information. Tracking and telemetry of the drifters is done by Pacific Gyre, Inc. The data are available in netCDF format with a dimension of time. <br><br> Novelli, G., C. M. Guigand, C. Cousin, E. H. Ryan, N. J. M. Laxague, H. Dai, B. K. Haus, and T. M. Özgökmen, 2017: A Biodegradable Surface Drifter for Ocean Sampling on a Massive Scale. J. Atmos. Oceanic Technol., 34, 2509–2532, https://doi.org/10.1175/JTECH-D-17-0055.1.<br><br>Ohlmann, J. C., P. F. White, A. L. Sybrandy, and P. P. Niiler, 2005: GPS–Cellular Drifter Technology for Coastal Ocean Observing Systems. J. Atmos. Oceanic Technol., 22, 1381–1388, https://doi.org/10.1175/JTECH1786.1.<br><br>Westbrook, E., Bingham, F. M., Brodnitz, S., Farrar, J. T., Rodriguez, E., & Zappa, C., (2024). Submesoscale Ocean Dynamics Experiment (S-MODE) Data Submission Report. Technical Report. Woods Hole Oceanographic Institution, WHOI-2024-03, https://doi.org/10.1575/1912/69362
SASSIE Arctic Field Campaign Drifter Hydrography Data Fall 2022 Version 2p
The Salinity and Stratification at the Sea Ice Edge (SASSIE) project is a NASA experiment that aims to understand how salinity anomalies in the upper ocean generated by melting sea ice affect sea surface temperature (SST), stratification, and subsequent sea-ice growth. SASSIE involved a field campaign that sampled the transition from summer melt to autumn ice advance in the Beaufort Sea during August-October 2022, making intensive in situ and remote sensing observations within ~200 km of the sea ice edge. This dataset contains ocean temperature and salinity data collected by surface drifting buoys (called UpTempO or Hydrobuoys, interchangeably) deployed in the Beaufort Sea. Each buoy has a different configuration of sensors, and records to a maximum of 60 m depth. Drifters were left at sea after the completion of the field deployment and are recording data into March 2023. Version 2p data has major quality control performed. Data are available in netCDF format.
The Gulf of Mexico Eddy Dataset (GOMED), a census of statistically significant eddy-like events from all available surface drifter data
<p>This dataset uses trajectory data from a large set of drifters to extract and analyze displacement signals associated with coherent eddies in the Gulf of Mexico, using a multivariate wavelet ridge analysis as presented in Lilly and Pérez-Brunius (2021). The data includes eddy displacement signals for all ridges, as well as the time-varying ellipse parameters and estimated ellipse center location. The instantaneous frequency is also included, as is the instantaneous bias estimate derived by Lilly and Olhede (2012). The data are organized as appended trajectory data that can be readily separated through the use of the "ids" field. The ridge length (<span class="math-tex">\(L\)</span>),and ridge-averaged circularity (<span class="math-tex">\(\overline{\xi}\)</span>) are also included, as is measure of statistical significance denoted by (<span class="math-tex">\(\rho\)</span>). The dataset is available for download as a NetCDF file.</p> <p>Lilly, J. M. and P. Pérez-Brunius (2021). Extracting statistically significant eddy signals from large Lagrangian datasets using wavelet ridge analysis, with application to the Gulf of Mexico. <em>Nonlinear Processes in Geophysics</em>, 28: 181–212. <a href="https://doi.org/10.5194/npg-28-181-2021">https://doi.org/10.5194/npg-28-181-2021</a>. </p> <p>Lilly, J. M. and Olhede, S. C.: Analysis of modulated multivariate oscillations, IEEE T. Signal Proces., 60, 600–612, 2012. <a href="https://doi.org/10.1109/TSP.2011.2173681">10.1109/TSP.2011.2173681</a></p>
DWDE drifters: Trajectories of surface drifters in the western Gulf of Mexico from the Deep-Water Dispersion Experiment
<p>This dataset is comprised of the final processed data collected by 207 surface drifters deployed in the western Gulf of Mexico during the Deep Water Dispersion Experiment (DWDE), as part of the project “Implementación de redes de observación oceanográficas (físicas geoquímicas, ecológicas) para la generación de escenarios ante posibles contingencias relacionadas a la exploración y producción de hidrocarburos en aguas profundas del Golfo de México” of the Gulf de Mexico Research Consortium (CIGoM), funded by CONACYT‐SENER‐Hydrocarbon Fund, Mexico”. </p> <p>The DWDE drifter data is also made available with the GulfDriftersWithDWDE dataset (<a href="http://doi.org/10.5281/zenodo.3985917">http://doi.org/10.5281/zenodo.398591</a><a href="http://doi.org/10.5281/zenodo.3985916">6</a>), which is a merged and uniformly processed surface drifter dataset which includes publicly available data from several different drifter experiments. These latter database is the basis for the gridded product GulfFlow (<a href="http://doi.org/10.5281/zenodo.3978793">http://doi.org/10.5281/zenodo.3978793</a>). See Lilly and Pérez-Brunius (2021) <a href="https://essd.copernicus.org/articles/13/645/2021/">"A gridded surface current product for the Gulf of Mexico from consolidated drifter measurements"</a> for details.</p> <p>García Carrillo, P., Ronquillo Méndez, A., Rodríguez Outerelo, J., Pérez Brunius, P. 2018. <a href="https://cicese.repositorioinstitucional.mx/jspui/bitstream/1007/3262/1/Reporte_DatosDrifters_DWDE.pdf">Experimento de Dispersión en Aguas Profundas ( DWDE ).</a> Centro de Investigación Científica y de Educación Superior de Ensenada, Baja California. 253 pp.</p> <p>Pérez-Brunius P., P. García Carrillo, A. Ronquillo Méndez, J. Rodríguez Outerelo, A. Sandoval Rangel, C. Liera Grijalva, X. Flores Vidal (2019). Trayectorias de Derivadores Superficiales en el Oeste del Golfo de México del Experimento de Dispersión en Aguas Profundas. Reg. INDAUTOR, México (03-2019- 120510255600-01, 13 December 2019).</p>
Southern Pacific Ocean drifter measurements in 1996
Measurements taken by a drifter in the Southern Pacific Ocean in 1996.
GulfFlow: A gridded surface current product for the Gulf of Mexico from consolidated drifter measurements
<p>This dataset is comprised of mean and variance of the surface velocity field of the Gulf of Mexico, obtained from a large set of historical surface drifter data from the Gulf of Mexico—3770 trajectories spanning 28 years and more than a dozen data sources— which were uniformly processed and quality controlled, and assimilated into a spatially and temporally gridded dataset. A gridded product, called GulfFlow, is created by averaging all available data from the GulfDrifters dataset within quarter-degree spatial bins, and within overlapping monthlong temporal bins having a semimonthly spacing. The dataset spans monthly time bins centered on July 16, 1992 through July 1, 2020, for a total of 672 overlapping time slices. Odd- numbered slices correspond to calendar months, while even-numbered slices run from halfway through one month to halfway through the following month. A higher spatial resolution version, GulfFlow-1/12 degree is created in the identical way but using 1/12 degree bins instead of quarter-degree bins. In addition to the average velocities within each 3D bin, the count of sources contributing to each bin is also distributed, as is the subgridscale velocity variance. The count variable is a four-dimensional array of integers, the fourth dimension of which has length 45. This variable gives the number of hourly observations from each source dataset contributing to each three-dimensional bin. Values 1–15 are the count of velocity observations from drifters from each of the 15 experiments that are flagged as having retained their drogues, values 16–30 are for observation from drifters that are flagged as having lost their drogues, and values 31–45 are for observations from drifters of an unknown drogue status. In defining averaged quantities, we represent the velocity as a vector, <strong>u</strong> = [u v]<sup>T</sup> , where the superscript “T” denotes the transpose. Let an overbar, <strong><span class="math-tex">\(\overline {\bf u}\)</span></strong> , denote an average over a spatial bin and over all times, while angled brackets, <<strong>u</strong>>, denote an average over a spatial bin and a particular temporal bin. Thus, <<strong>u</strong>>, is a function of time while <span class="math-tex">\(\overline {\bf u}\)</span> is not. We refer to <<strong>u</strong>>, as the local average, <span class="math-tex">\(\overline {\bf u}\)</span> as the global average, and <span class="math-tex">\(\overline {<\bf u>}\)</span> as the double average. Given the inhomogeneity of the drifter data, turns out the global average is biased towards intensive but short duration programs, hence the double average results in a much better representation of the true mean velocity field. The dataset includes the global average <span class="math-tex">\(\overline {<\bf u>}\)</span>, the local covariance defined as</p> <p><span class="math-tex">\(\bf{ε}=<(u − <u>)(𝐮−< 𝐮 >)^T>\)</span></p> <p>and <span class="math-tex">\(\epsilon^2\)</span>which is the trace of <span class="math-tex">\(\overline{\bf ε}\)</span></p> <p><span class="math-tex">\(\epsilon^2\)</span>=<span class="math-tex">\(tr\{\overline{\bf ε}\}\)</span></p> <p>The data is distributed in two separate netcdCDF files, one for each grid resolution. </p> <p>Here the article describing this dataset.</p> <p>Lilly, J. M. and P. Pérez-Brunius (2021). A gridded surface current product for the Gulf of Mexico from consolidated drifter measurements. <em>Earth System Science Data</em>, 13: 645–669. <a href="https://doi.org/10.5194/essd-13-645-2021">https://doi.org/10.5194/essd-13-645-2021</a>.</p>
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