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29 results for “Lagrangian data”
Data for "Investigating temporary capture in the Sun-Jupiter three-body system via Lagrangian coherent structures"
<p>The supplementary online materials for the paper "Investigating temporary capture in the Sun-Jupiter three-body system via Lagrangian coherent structures" consist of two parts.</p> <h3>Part 1: Coordinates of the LCS Surfaces in Figure 8</h3> <p>This part contains the coordinates of the local maxima of FTLE (Finite-Time Lyapunov Exponent) values that compose the Lagrangian Coherent Structures (LCS) surface presented in Figure 8 of the paper. These coordinates are crucial for understanding the formation and characteristics of the LCS in the three-body system.</p> <h3>Part 2: Orbital States of Asteroid 2002 GV28 Based on the High-Fidelity Ephemeris Model from Section 2.2 of the Paper</h3> <p>This part includes the orbital states of asteroid 2002 GV28, propagated using a high-fidelity ephemeris model as described in Section 2.2 of the paper. The data provides information on the asteroid's state in two different coordinate systems:</p> <ol> <li> <p><strong>Heliocentric J2000.0 Ecliptic Coordinate System:</strong></p> <ul> <li>This dataset includes the position and velocity of the asteroid relative to the Sun at various time steps.</li> <li>The columns typically include: Time (Julian Date), X (km), Y (km), Z (km), Vx (km/s), Vy (km/s), Vz (km/s).</li> </ul> </li> <li> <p><strong>Sun-Jupiter Rotating Coordinate System:</strong></p> <ul> <li>This dataset provides the position and velocity of the asteroid relative to the Sun-Jupiter rotating frame.</li> <li>The columns typically include: Time (Julian Date), X (normlized), Y (normlized), Z (normlized), Vx (normlized), Vy (normlized), Vz (normlized).</li> </ul> </li> </ol> <p>Each entry in these datasets corresponds to specific time steps during the propagation, providing a comprehensive view of the asteroid's trajectory in both coordinate systems.</p>
Data - Evaluation performance 2 TCM Lagrangian
<p>The dataset contains the processed model output used to create the figure for the paper `Evaluation of the performance of two turbulence closure schemes in a Lagrangian frame of reference along a fluvial-to-marine transition zone'. </p>
Data accompanying the article "Arctic sea ice data assimilation combining an ensemble Kalman filter with a novel Lagrangian sea ice model for the winter 2019–2020"
<p>The .zip file contains temporal-spatial averaged metrics for evaluating simulations against observed ice thickness, concentration, volume, and drift. These quantities are presented in the manuscript "Arctic sea ice data assimilation combining an ensemble Kalman filter with a novel Lagrangian sea ice model for the winter 2019–2020"</p> <p>Subfolders are named by the experiment IDs, including metrics obtained from the relevant experimental results and observations.</p> <p>In case information is missing, do not hesitate to contact chengsukun@hotmail.com</p> <p>We thank Pavel Sakov for helpful discussions and improvement regarding the EnKF-C code and Jiping Xie for contributing the TOPAZ interface to sea ice observations. We are grateful for the support from Timothy Williams and Anton Korosov regarding the environments of neXtSIM and its analysis tools. The work is funded by the DASIM-II grant from ONR (grant nos. N00014-18-1-2493 and N00014-18-1-2204). Alberto Carrassi, Christopher K. R. T. Jones, Ali Aydo ̆gdu, and Pierre Rampal acknowledge the support of the project SASIP funded by Schmidt Futures – a philanthropic initiative that seeks to improve societal outcomes through the development of emerging science and technologies. Sukun Cheng and Laurent Bertino were co-funded by the FOCUS project from the Research Council of Norway (grant no. 301450), and Alberto Carrassi and Yumeng Chen are also supported by the UK National Centre for Earth Observation (grant no. NCEO02004). Computations were carried out on the Norwegian Supercomputing InfrastructureSigma2 (grants nn2993k for computing and NS2993K for data storage)</p>
Data from: Population genomics meet Lagrangian simulations: oceanographic patterns and long larval duration ensure connectivity among Paracentrotus lividus populations in the Adriatic and Ionian seas
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Data presented in the paper "Impact of Giant Sea Salt Aerosol Particles on Precipitation in Marine Cumuli and Stratocumuli: Lagrangian Cloud Model Simulations"
<p>View Readme.</p>
Data for publication "Chasing ice crystals: interlinking cloud microphysics and dynamics in cloud seeding plumes with Lagrangian trajectories"
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Data from: Does perspective matter? A case study comparing Eulerian and Lagrangian estimates of common murre (Uria aalge) distributions
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Supporting data to "Sediment source and pathway identification using Sentinel-2 imagery and (kayak-based) lagrangian river profiles on the Vjosa river"
<p>This release contains the supporting data files that are part of the manuscript "Sediment source and pathway identification using Sentinel-2 imagery and (kayak-based) lagrangian river profiles on the Vjosa river."</p>
Data and scripts for "Unraveling the discrepancies between Eulerian and Lagrangian moisture tracking models in monsoon- and westerly-dominated basins of the Tibetan Plateau", to appear in Atmos. Chem. Phys.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
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.