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43 results for “Surface currents”
Leeuwin Current Dynamics in the SE Indian Ocean and Implications for Regional Surface Hydrography since the Latest Miocene: Results from ODP Hole 763A
<p>The main findings of this research are based on comprehensive analyses, including planktic foraminiferal census counts and their stable isotope ratios, as well as XRF analysis of bulk sediments from Ocean Drilling Program Hole 763A in the southeastern Indian Ocean. We have documented valuable insights into the dynamics of the Leeuwin Current and West Australian Current, as well as changes in the surface hydrography and their implications for regional climate. The study established a teleconnection between the shallowing of the mixed layer in the southeast Indian Ocean and the aridity over Northwest Australia.</p>
Nicosia, Bedestan. Plan of the complex prepared in 1980-81 combined with resistivity tomography at a depth of 1.25m below the current surface.
<p>Nicosia, Bedestan. Plan of the complex prepared in 1980-81 combined with resistivity tomography at a depth of 1.25m below the current surface.</p>
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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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.