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447 results for “plume”
Plumes and Blooms: phytoplankton pigment concentration
The data set provided here is a curated collection of phytoplankton pigment observations collected from the discrete seawater bottle samples by the Plumes and Blooms program (PnB). The curated data set was used to determine the dominant seasonal to multi-decadal patterns and forcings of phytoplankton groups in the Santa Barbara Channel, CA. The data included here encompass the PnB cruises since Nov 2005.
The Plunging of Hyperpycnal Plumes on Tilted Bed by Three-Dimensional Large-Eddy Simulations
<p><strong>Abstract:</strong> Theoretical and experimental interest in the transport and deposition of sediments from rivers to oceans has increased rapidly over the last two decades. The marine ecosystem is strongly affected by mixing at river mouths, with for instance anthropogenic actions like pollutant spreading. Particle-laden flows entering a lighter ambient fluid (hyperpycnal flows) can plunge at a sufficient depth, and their deposits might preserve a remarkable record across a variety of climatic and tectonic settings. Numerical simulations play an essential role in this context since they provide information on all flow variables for any point of time and space. This work offers valuable Spatio-temporal information generated by turbulence-resolving 3D simulations of poly-disperse hyperpycnal plumes over a tilted bed. The simulations are performed with the high-order flow solver Xcompact3d, which solves the incompressible Navier-Stokes equations on a Cartesian mesh using high-order finite-difference schemes. Five cases are presented, with different values for flow discharge and sediment concentration at the inlet. A detailed comparison with experimental data and analytical models is already available in the literature. The main objective of this work is to present a new data-set that shows the entire three-dimensional Spatio-temporal evolution of the plunge phenomenon and all the relevant quantities of interest.</p> <p><strong>Description:</strong> Data from the five simulations are included (cases 2, 4, 5, 6, and 7). The output files from Xcompact3d were converted to NetCDF, including coordinates and metadata, aiming to be more friendly than raw binaries.</p> <p>More details, including examples about how to read and plot the dataset using Python and xarray, are available at <a href="https://github.com/fschuch/the-plunging-flow-by-3D-LES">GitHub</a>.</p>
Passive gas plume database for metrics comparison
<p>Plume database used for the evaluation of different metrics that are presented in the submitted paper "New plume comparison metrics for the inversion of passive gases emissions". The synthetical CO2 plumes presented in the NetCDF file entitled "Synthetical_CO2_plume_database.nc" are the results of chemical transport model simulations described in the preprint available here <a href="https://amt.copernicus.org/preprints/amt-2022-48/">https://amt.copernicus.org/preprints/amt-2022-48/</a>.</p>
East African topography and volcanism explained by a single, migrating plume: supplementary data
<p>These data accompany the following paper:</p> <p>Hassan, R., Williams, S.E., Gurnis, M. and Müller, D., 2020. East African topography and volcanism explained by a single, migrating plume. <em>Geoscience Frontiers</em>, <em>11</em>(5), pp.1669-1680.</p> <p>The data (in simple text form) correspond to the dynamic topography and change in dynamic topography shown in Figure 7.</p>
Plumes and Blooms: Curated oceanographic and phytoplankton pigment observations
These data come from the Plumes and Blooms project (PnB), which has conducted approximately monthly 1-day oceanographic cruises since August 1996. The data included here encompass all PnB cruises from August 1996 through December 2018. Data are two data tables: one table includes conductivity-temperature-depth profiles (CTD) and derived physical parameters, the other table includes discrete seawater samples for various biological and biogeochemical parameters. Details are available in Catlett et al., in prep. References: Catlett, D., D. A. Siegel, R. D. Simons, N. Guillocheau, F. Henderikx-Freitas, C. S. Thomas.2021. Diagnosing seasonal to multi-decadal phytoplankton group dynamics in a highly productive coastal ecosystem, Progress in Oceanography. 197. https://doi.org/10.1016/j.pocean.2021.102637.
Reconnection rates of the paper "Simulation of plasmaspheric plume impact on dayside magnetic reconnection"
<p>This repository contains the dataset needed for the paper "Simulation of plasmaspheric plume impact on dayside magnetic reconnection", i.e. the magnetic reconnection rates at each time and the quantities needed to normalize them. All the data are stored in the file "rates_norm.h5". The file "si_content.pdf" explain how the data are stored and how you can extract them.</p>
Data from: Electron Populations and Neutralization Process in the Plume of a Gridded Ion Thruster
<h2>Data from: Electron Populations and Neutralization Process in the Plume of a Gridded Ion Thruster</h2> <ul> <li>Authors: Matteo Guaita, Alberto Marín-Cebrián, Eduardo Ahedo, Mario Merino, Fabrice Cipriani, Käthe Dannenmayer</li> <li>Contact email: mguaita@pa.uc3m.es</li> <li>Date: 15/11/2024</li> <li>Keywords: Plasma Physics, Plasma Plumes, Gridded Ion Thruster, Cathode, Facility Effects, Particel in Cell</li> <li>Version: 1.0.0</li> <li>Digital Object Identifier (DOI): 10.5281/zenodo.14165272</li> <li>License: This dataset is made available under the <a href="http://opendatacommons.org/licenses/by/1.0/" target="_blank" rel="noopener">Open Data Commons Attribution License</a></li> </ul> <h2>Abstract</h2> <p>This dataset contains the data from the simulations presented in the article submitted for pubblicaiton in the Journal: Plasma Sources Science and Technology (PSST):</p> <p>"Electron Populations and Neutralization Process in the Plume of a Gridded Ion Thruster"</p> <p>The data in this repository is the result of several hybrid PIC simulations as described in the reference. For further information on the setup, numerical parameters and physical meaning of the simulations please refer to the article</p> <h2>Dataset description</h2> <p>The simulations that produced the datasets in this repository were run with the full PIC code Picaso. The majority of the data is at steady-state, and has been averaged over the last 7000 simulation time-steps to reduce numerical noise. This averaging has been performed as a first step directly by the code through time-step accumulation techniques, and at a later stage in post-processing by averaging over the last 20 print-outs of the code. The data inside the "time_dependent" folder is instead time-varying.</p> <h2>Data files</h2> <p>Each HDF5 data-group contains the mesh and time coordinates and plasma properties of a specific simulation. In particular, the naming convention is the following:</p> <ul> <li><strong>Ref_planar.hdf5: </strong>Contains the results of the "reference planar simulation" presented in Sections III and IV of the article.</li> <li><strong>2Te_planar.hdf5: </strong>Contains the results of the simulation with a doubled electron temperature at the cathode presented in Section V of the article.</li> <li><strong>2Ie_planar.hdf5: </strong>Contains the results of the simulation with a doubled electron current at the cathode presented in Section V of the article.</li> <li><strong>No_coll_planar.hdf5: </strong>Contains the results of the simulation without inelastic electron collisions presented in Section V of the article.</li> <li><strong>Ref_axisym.hdf5: </strong>Contains the results of the non-accelerated axis-symmetric simulation presented in Section VI of the article</li> <li><strong>fcol_2.5_axisym.hdf5: </strong>Contains the results of the axis-symmetric simulation,accelerated by a factor 2.5, presented in Section VI of the article</li> <li><strong>fcol_5_axisym.hdf5: </strong>Contains the results of the axis-symmetric simulation,accelerated by a factor 5, presented in Section VI of the article</li> <li><strong>fcol_7.5_axisym.hdf5: </strong>Contains the results of the axis-symmetric simulation,accelerated by a factor 7.5, presented in Section VI of the article</li> <li><strong>fcol_10_axisym.hdf5: </strong>Contains the results of the axis-symmetric simulation,accelerated by a factor 10, presented in Section VI of the article</li> </ul> <p>In each of these files the data is organized in a series of subfolders:</p> <ul> <li><strong>Electrons_prim: </strong>Contains the steady-state properties of primary electrons</li> <li><strong>Electrons_trap: </strong>Contains the steady-state properties of trapped electrons</li> <li><strong>Ions_fast: </strong>Contains the steady-state properties of fast ions (ions injected through the thruster grids)</li> <li><strong>Ions_slow: </strong>Contains the steady-state properties of slow ions (ions produced by collisions in the plume)</li> <li><strong>Time_dependent: </strong>Contains the vector of time-stamps and spatially global data saved at the corresponding time</li> </ul> <p>The data files found in the outer simulation folder are:</p> <ul> <li><strong>xs:</strong> Physical x coordinates [cm]</li> <li><strong>zs:</strong> Physical z coordinates [cm]</li> <li><strong>phi: </strong>electric potential [V]</li> <li><strong>rho_el: </strong>space charge density [C/m³]</li> <li><strong>nn: </strong>Total neutral density [1/m³]</li> </ul> <p>The data files for each particle population are:</p> <ul> <li><strong>n: </strong>Plasma (ion) density [1/m³]</li> <li><strong>f_x: </strong>Particle flux along x [1/(m² s)]</li> <li><strong>f_y: </strong>Particle flux along y [1/(m² s)]</li> <li><strong>f_z: </strong>Particle flux along z [1/(m² s)]</li> <li><strong>p_xx: </strong>xx component of the pressure tensor [J/m³]</li> <li><strong>p_yy: </strong>yy component of the pressure tensor [J/m³]</li> <li><strong>p_zz: </strong>zz component of the pressure tensor [J/m³]</li> </ul> <p>The data files in the time dependent folder are:</p> <ul> <li><strong>t: </strong>Time coordinates [s]</li> <li><strong>phi_W: </strong>Potential of the vacuum chamber walls [V]</li> <li><strong>phi_max:</strong> Maximum value of the potential in the plume [V]</li> <li><strong>nte_frac: </strong>Fraction between the number of trapped electrons and ions in the plume bulk [%]</li> <li><strong>nu_te_ela: </strong>globally averaged trapped electron-neutral elastic collision frequency [Hz]</li> <li><strong>nu_te_ion: </strong>globally averaged trapped electron-neutral ionization collision frequency [Hz]</li> <li><strong>nu_te_exc: </strong>globally averaged trapped electron-neutral excitation collision frequency [Hz]</li> <li><strong>nu_te_cou: </strong>globally averaged trapped electron-neutral Coulomb collision frequency [Hz]</li> <li><strong>nu_pe_ela: </strong>globally averaged primary electron-neutral elastic collision frequency [Hz]</li> <li><strong>nu_pe_ion: </strong>globally averaged primary electron-neutral ionization collision frequency [Hz]</li> <li><strong>nu_pe_exc: </strong>globally averaged primary electron-neutral excitation collision frequency [Hz]</li> <li><strong>nu_pe_cou: </strong>globally averaged primary electron-neutral Coulomb collision frequency [Hz]</li> </ul> <p> </p> <p>Note that all the other quantities shown in the article may be obtained from the ones saved here. We remind here that the gas employed is Xenon and that all ions are considered to be singly charged.</p> <h2>Citation</h2> <p>Any works using this dataset or any part of it in any form shall cite it as follows. The BibTeX entry s provided for convenience:</p> <p>@dataset{sim_data_guai25b,<br> author = {Matteo Guaita and Alberto Marín-Cebrián and Mario Merino and Eduardo Ahedo and Fabrice Cipriani and Käthe Dannenmayer},<br> title = {Data from: Electron populations and neutralization process in the plume of a gridded ion thruster},<br> month = November,<br> year = 2024,<br> publisher = {Zenodo},<br> version = {1.0.1},<br> doi = {10.5281/zenodo.14165272},<br> url = {https://doi.org/10.5281/zenodo.12751281}<br>}</p> <p>The journal article associated with this data-set shall also be cited as follows:</p> <p>@article{guai25b,<br> doi = {10.1088/1361-6595/adc482},<br> year = {2025},<br> month = {mar},<br> publisher = {IOP Publishing},<br> author = {Matteo Guaita and Alberto Marín-Cebrián and Mario Merino and Eduardo Ahedo and Fabrice Cipriani and Käthe Dannenmayer},<br> title = {Electron populations and neutralization process in the plume of a gridded ion thruster},<br> journal = {Plasma Sources Science and Technology },<br>}</p> <p> </p> <p><br><br></p> <h2>Acknowledgments</h2> <p>This work, and the corresponding dataset, has been supported by the ECOMODIS project, funded by the European Space Agency, under contract 4000137869/22/NL/RA</p>
Supporting Data for Figures in "Evolving Interior Mixing Regimes in a Tidal River Plume"
<p>Supporting data for figures in "Evolving Interior Mixing Regimes in a Tidal River Plume" by Preston S. Spicer, Kimberly D. Huguenard, Kelly L. Cole, Daniel G. MacDonald, and Michael M. Whitney. The scientific journal article is published in Geophysical Research Letters (2022). The article elucidates the evolution of stratified shear mixing in a tidal river plume using observational data taken over an ebb pulse throughout the interior of the Merrimack River plume. The file GRL_figs.m is a MATLAB file which produces Figures 1 thru 4 in the article taking the accompanying .mat and .txt files as input. Variables names and units correspond to graphed data of each figure in the journal article.</p>
IMS sulphate aerosol in the stratospheric plume of the January 2022 Tong aeruption
<p>This animation is made using the IMS sulphate aerosol optical depth product (see https://www?doi.org/10.5281/zenodo.7102472) for all day and night orbits of each day between 13 January and 30 April 2022. The indicated times are those of the intersection of the orbits with the equator. The upper chart of each view is a daily composite of the day orbits and the lower chart is a daily composite of the night orbits. When two orbit swaths overlap, the crossing time of the overlapped orbit is indicated in red. Missing orbits are blanked out. Several days are entirely missing between 8 and 14 March.</p>
plume-rise-paper-dataset
<p>the dataset includes:</p> <p>1, 1D_mode_95_data.zip</p> <p>2, cam5_onlineplume_code, for CESM version 1.2.2</p> <p>3, MISR_list_good_all.txt,</p>
CoCO2 WP4.1 Library of Plumes
<p>This data collects synthetic CO2M images (the 'Library of Plumes' for CoCO2 WP4.1) in the form of NetCDF files, for 5 modelling systems applied to 7 case studies. The files contain 'raw' results (e.g., "CO2_PP_M") in units of mol/m2, total column results (e.g., "XCO2_PP_M") in units of ppm, and additionally the column mass ("dry_mol_mass" and surface pressure ("surface pressure").</p> <p>This work was carried out in the context of the EU project CoCO2, by the following institutes: Empa (Switzerland), Deutsche Wetterdienst (Germany), Le Laboratoire des Sciences du Climat et de l'Environnement (France), TNO (The Netherlands), Wageningen University & Research (the Netherlands). More details about the model runs, their input data, possible issues, expected data quality, etc., can be found in the accompanying report CoCO2 D4.2, <a href="https://www.coco2-project.eu/node/357">https://www.coco2-project.eu/node/357</a>.</p>
Dataset: all TROPOMI detected plumes for 2021. [Schuit et al. 2023: Automated detection and monitoring of methane super-emitters using satellite data]
<p>Dataset of all TROPOMI detected methane plumes in 2021, including estimates for the source location, emission quantification and source type. Corresponds to Figure 6 of Schuit et al. 2023 [Automated detection and monitoring of methane super-emitters using satellite data, https://doi.org/10.5194/acp-23-9071-2023]. Additional details and context are provided in Section 3 of the paper.</p> <p> </p> <p><em>Contents and data formats</em></p> <p><strong>date</strong>, date of the TROPOMI observation. format: YYYYMMDD</p> <p><strong>time_UTC</strong>, time of the TROPOMI observation in UTC. format: HH:MM:SS</p> <p><strong>lat</strong>, latitude of the center of the TROPOMI pixel at the estimated source location. format: float</p> <p><strong>lon</strong>, longitude of the center of the TROPOMI pixel at the estimated source location. format: float</p> <p><strong>source_rate_t/h</strong>, estimated emission source rate in tonnes per hour, the methodology is described in Section 2.5.1 of the paper. format: int</p> <p><strong>uncertainty_t/h</strong>, the uncertainty of the emission source rate in tonnes per hour, the methodology is described in Section 2.5.1 of the paper. format: int</p> <p><strong>estimated_source_type</strong>, the locally dominant anthropogenic source sector based on bottom-up inventories, the methodology is described in Section 2.5.3 of the paper. format: str</p> <p> </p> <p>Full citation of the paper:</p> <p>Schuit, B. J., Maasakkers, J. D., Bijl, P., Mahapatra, G., van den Berg, A.-W., Pandey, S., Lorente, A., Borsdorff, T., Houweling, S., Varon, D. J., McKeever, J., Jervis, D., Girard, M., Irakulis-Loitxate, I., Gorroño, J., Guanter, L., Cusworth, D. H., and Aben, I.: Automated detection and monitoring of methane super-emitters using satellite data, Atmos. Chem. Phys., 23, 9071–9098, https://doi.org/10.5194/acp-23-9071-2023, 2023.</p>
Plumes and Blooms: Microbial eukaryote diversity and composition
These are amplicon sequencing data collected during Plumes and Blooms (PnB) cruises conducted from March, 2011, through September, 2014. The V9 hypervariable region of the 18S rRNA gene derived from microbial eukaryotic communities was amplified and sequenced from 345 discrete seawater samples. Sample collection and laboratory methods are described in Catlett et al. 2020 and Catlett et al. in review. Bioinformatic and data manipulation methods follow those employed in Catlett et al. in review. The data are provided in two tables: one includes amplicon sequence variant (ASV) sequences and relative sequence abundances for each sampling event, and the other includes ASV taxonomy predictions for each ASV sequence. References: Catlett, D., P. G. Matson, C. A. Carlson, E. G. Wilbanks, D. A. Siegel, and M. D. Iglesias‐Rodriguez. 2020. Evaluation of accuracy and precision in an amplicon sequencing workflow for marine protist communities. Limnol. Oceanogr.: Methods. 18(1): 20-40. https://doi.org/10.1002/lom3.10343. Catlett, D., D. A. Siegel, P. G. Matson, E. K. Wear, C. A. Carlson, T. S. Lankiewicz, and M. D. Iglesias‐Rodriguez. In review. Integrating phytoplankton pigment and DNA meta-barcoding observations to determine phytoplankton community composition in the coastal ocean. Limnol. Oceanogr.
Figures 18–24. Bahamas Pterophoridae pinned adults. 18 in Additions to the plume moth fauna of The Bahamas (Lepidoptera: Pterophoridae) with description of four new species
Figures 18–24. Bahamas Pterophoridae pinned adults. 18) Hellinsia unicolor ♂, Abaco, 1.vi.2016. 19) Hellinsia bahamensis Matthews, new species, ♀, holotype, Grand Bahama Island, 27.x.2014. 20) Hellinsia lucayana Matthews, new species, ♂, holotype, Crooked Island, 8.vi.2015. 21) Adaina perplexus ♀, Long Island, 31.v–1. vi.2014. 22) Adaina thomae ♀, Crooked Island, 7.vi.2015. 23) Adaina simplicius ♂, Abaco, 30.x.2014. 24) Adaina ambrosiae ♀, Abaco, 3.vi.2016. Scale line below each name equals 1 mm.
Figures 25–28. Bahamas Pterophoridae male genitalia. 25a in Additions to the plume moth fauna of The Bahamas (Lepidoptera: Pterophoridae) with description of four new species
Figures 25–28. Bahamas Pterophoridae male genitalia. 25a) Lioptilodes albistriolatus, slide DM 2159. 25b) phallus, same individual. 26a) Lantanophaga pusillidactylus, slide DM 2161. 26b) phallus, same individual. 27a) Postplatyptilia flinti, slide DM 2099. 27b) phallus, same individual. 28a) Stenoptilodes brevipennis, slide DM 2101. 28b) phallus, same individual.
Figs 5-6 in New species of " giant " plume moths of the genus Platyptilia (Lepidoptera, Pterophoridae) from Uganda
Figs 5-6. Platyptilia stanleyi Ustjuzhanin & Kovtunovich sp. nov., holotype, ♂ (BMNH 21803). 5. Adult, habitus. 6. Male genitalia.
Processed ERA5, IMERG and TRMM PR/GPM DPR precipitation data for Nicolas & Boos - "Understanding the spatiotemporal variability of tropical orographic rainfall using convective plume buoyancy."
<p>The dataset contains processed data from large datasets that are freely available online. <br>All data cover the period 01/2001 - 12/2020. The file names describe the months & region that each file contains. Variable codes for ERA5 data (all files starting in e5.) are:</p><p> - 228_246_100u : 100m u-wind<br> - 228_247_100v : 100m v-wind<br> - qL : 900-600hPa averaged specific humidity<br> - thetaeb : surface - 900hPa averaged equivalent potential temperature<br> - thetaeL : 900-600hPa averaged equivalent potential temperature<br> - thetaeLstar : 900-600hPa averaged saturation equivalent potential temperature<br> - tL : 900-600hPa averaged temperature<br> - uBL : surface - 900hPa averaged u wind<br> - vBL : surface - 900hPa averaged v wind<br> - 128_034_sstk : sea surface temperature<br> - 162_071_viwve : eastward component of vertically integrated water vapor transport<br> - 162_072_viwvn : northward component of vertically integrated water vapor transport</p><p> </p>
Gaussian plume footprints
<p>Supplementary Gaussian plume footprints for the paper "Recovery of sparse urban greenhouse gas emissions". Code used with this dataset is found at <a href="https://doi.org/10.5281/zenodo.5900738">https://doi.org/10.5281/zenodo.5900738</a>.</p> <p>.</p>
Plume and wind data from ROMEO campaign on 17.10.2019.
<p>Measurements from the oil well 1474 in Darmanesti, Parhova County, Romania. Dataset contains plume transect measurements taken by the team from TNO during the ROMEO measurement campaign. Included in the dataset are the measurements from a tracer (N2O), emitted next to the oil well. The wind data measured on-site with a 3D sonic is also added as 1 min averages of 25 Hz measurements of the three wind components.</p>
Seasonal sediment plumes in the Krishna-Godavari basin using satellite observations - Dataset
<p>Seasonal plume patterns of diffuse attenuation coefficient at the wavelength of 490 nm, K<sub>d</sub>(490), in the coastal waters of Krishna-Godavari, southeast coast of India basin, are examined through remote sensing data collected from July 2002 to October 2021 by the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Aqua platform. This dataset provide point values extracted for K<sub>d</sub>(490) and SST at 16.32°N, 82.603°E in a 3x3 grid for turbidity region for the analysis of inter-annual variability in (a) spring, (b) summer, (c) autumn, and (d) winter during July 2002 to October 2021.</p>
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