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1,702 results for “shelf”
Zooplankton abundance from net tows on Northeast U.S. Shelf Long Term Ecological Research (NES-LTER) Transect cruises, ongoing since 2018
This data package provides abundance data for zooplankton collected during seasonal transect cruises conducted as part of the Northeast U.S. Shelf Long-Term Ecological Research (NES-LTER) program, ongoing since 2018. Zooplankton are collected at standard NES-LTER transect stations (L1–L11) and the Martha’s Vineyard Coastal Observatory (MVCO) via oblique tows, using a 61-cm Bongo net with two mesh sizes (335 µm and 150 µm). The transect extends southward from near Martha’s Vineyard, Massachusetts, reaching approximately 150 km offshore along longitude 70 deg 53 min W, covering the continental shelf from nearshore to the shelf break, with sampling depths between 20 and 200 meters. Only the 335-µm mesh data is included here, as samples from this net are preserved on board and shipped to Morski Instytut Rybacki in Szczecin, Poland, where they are counted and identified to the lowest possible taxonomic level. Counts of taxa identified are provided by the NOAA’s Northeast Fisheries Science Center. Samples from the 150 um are preserved for other purposes and will be published as a separate data package. This second version of the data package includes staged and unstaged abundance data in volumetric (100 m³) and aerial (10 m²) units from the 335-µm net. Supplemental tables provide metadata for the cruises and stations.
Annual Water Quality in Everglades National Park, Florida Bay, West Florida Shelf, and Florida Keys National Marine Sanctuary, Florida, USA: 1994-2019
Annual (water year basis) geometric mean concentrations of total phosphorus (TP), soluble-reactive phosphorus (SRP), total nitrogen (TN), dissolved inorganic nitrogen (DIN; calculated as nitrate + nitrite + ammonia), chlorophyll-a (Chl-a), and total organic carbon (TOC) concentrations across Everglades National Park (ENP), Florida Keys National Marine Sanctuary (FKNMS), West Florida Shelf and Florida Bay. This dataset is composed of data from multiple sources including Florida Coastal Everglades, Florida International University Southeast Research Center (FIU SERC), South Florida Water Management District (SFWMD), and National Oceanic and Atmospheric Administration Atlantic Oceanographic and Meteorological Laboratory (NOAA AOML). All values reported less than the laboratory minimum detection limit (MDL) were set to one-half the MDL. Annual geometric mean concentrations were computed for monitoring locations with greater than five years of data and four samples per year with a minimum of one sample in the wet and dry seasons. This dataset was created to evaluate long-term spatial and temporal trends in nutrients, chlorophyll-a, and total organic carbon at the landscape scale relative to freshwater and marine ecosystems.
Size-fractionated net primary productivity (NPP) estimates based on 13C uptake during cruises along the Northeast U.S. Shelf Long Term Ecological Research (NES-LTER) Transect, ongoing since 2019
This dataset consists of primary production measurements based on uptake of carbon-13 added as 13C-bicarbonate during 24-h deckboard incubations of seawater. Sampling occurred on cruises along the Northeast U.S. Shelf Long Term Ecological Research (NES-LTER) Transect during summer, fall, and winter, starting in summer 2019. Net primary production (NPP) was determined from particulate organic carbon (POC) content and associated stable isotope enrichment. Three data tables are included: 1. Depth-specific primary productivity based on fractional light levels of the surface irradiance with reference to the profile of photosynthetically active radiation (PAR). 2. Integrated primary productivity. 3. Natural abundance POC. The tables derive from the raw data included as other entities.
Diet composition for small pelagic fishes across the Northeast U.S. Continental Shelf for NES-LTER, ongoing since 2013
These data represent the diet composition of small pelagic fishes assessed by the Northeast U.S. Shelf Long-Term Ecological Research (NES-LTER) project. The six species of fish in this dataset represent a subset of the species collected in bottom trawls conducted by the NOAA Fisheries Northeast Ecosystems Surveys from Cape Hatteras to the Gulf of Maine. Sampling occurred in the Spring and Fall seasons. Fish were frozen and stomach content analyses were conducted by the Fisheries Oceanography and Larval Fish Ecology Lab at the Woods Hole Oceanographic Institution. Data are counts and length measurements for prey items examined under a dissecting microscope. Prey species were matched to the lowest taxonomic level in the Integrated Taxonomic Information System (ITIS) for scientific name and taxonomic serial number. The dataset was supplemented with geospatial and temporal information from NOAA Fisheries trawl databases.
Event logs from Northeast U.S. Shelf Long Term Ecological Research (NES-LTER) Transect cruises, ongoing since 2017
This package provides a concatenated table of events recorded on seasonal Transect cruises for Northeast U.S. Shelf Long-Term Ecological Research (NES-LTER) and other opportunistic cruises within the transect region. Events were recorded onboard with Rolling Deck to Repository (R2R) event logger (elog) software. Event listings include date, time, ship's position, instrument, and action for over the side operations, underway data collection, and other miscellaneous events during the cruise. The event log is used post-cruise in physical sample cataloging and data integration. Cruises are seasonal and include NES-LTER dedicated voyages, spring and fall cruises in collaboration with the Ocean Observatories Initiative (OOI), and additional opportunistic cruises.
Event logs from Northeast U.S. Shelf Long Term Ecological Research (NES-LTER) cruises to the Martha's Vineyard Coastal Observatory (MVCO) ongoing since 2017
This package provides a table of cruises to the Martha's Vineyard Coastal Observatory for Northeast U.S. Shelf Long-Term Ecological Research (NES-LTER). The majority of events are single day cruises, however, samples missing an MVCO Event Number were collected on multi-day NES-LTER transect cruises aboard larger research vessels. The same sampling protocols for CTD and bongo collection are used on both cruise types. Sampling frequency is approximately monthly, with NES-LTER sampling ongoing since 2017. Cruises involve collection of water column bottle samples, surface bucket samples, and zooplankton net tow samples, as well as ship-provided data. NES-LTER transect cruises will have more extensive underway and acoustic data which can be found by searching by cruise at https://www.rvdata.us/data. The event number for each cruise is provided, along with date, vessel name, cruise identifier where applicable, link to data location (for CTD, ADCP, and other underway data), and checklist of six data types.
Dissolved Organic Carbon (DOC) and Dissolved Total Nitrogen (DTN) from Northeast U.S. Shelf Long Term Ecological Research (NES-LTER) Transect cruises, ongoing since 2022
Dissolved organic carbon and dissolved total nitrogen are measured from discrete bottle samples collected during CTD rosette casts on Northeast U.S. Shelf Long-Term Ecological Research (NES-LTER) transect cruises (ongoing since 2022). Sampling frequency is approximately seasonal. Sample collection is paired with particulate organic carbon at surface, subsurface chlorophyll max, and sometimes a third depth. Samples are filtered directly from the CTD rosette and acidified in the field, then analyzed using a Shimadzu TOC-LCPH total organic carbon analyzer coupled to a TNM-L analyzer for total nitrogen. Values are reported in micromoles per liter.
Zooplankton sample inventory for Northeast U.S. Shelf Long Term Ecological Research (NES-LTER) Transect cruises, ongoing since 2018
This dataset provides an inventory of physical samples collected from zooplankton bongo and/or ring net tows conducted during the Northeast U.S. Shelf Long-Term Ecological Research (NES-LTER) Transect cruises, ongoing since 2018. The NES-LTER transect, located south of Martha’s Vineyard, Massachusetts, comprises standard stations L1-L11 and extends 150 km offshore. Dedicated NES-LTER cruises target all four seasons: winter, spring, summer, and fall. Samples are collected via oblique tows with a 61-cm bongo net fitted with 150- and 335-micron mesh nets, as well as a ring net with a 20-micron mesh net. During earlier spring and fall cruises along the NES-LTER Transect, in collaboration with the Ocean Observatories Initiative, samples were collected through vertical tows using a ring net with a 150-micron mesh. Samples collected are distributed among various laboratories for DNA metabarcoding, stable isotopes analysis, and morphological identification.
Particulate organic carbon (POC) and nitrogen (PON) from Northeast U.S. Shelf Long Term Ecological Research (NES-LTER) Transect cruises, ongoing since 2017
Particulate organic carbon and nitrogen are measured from discrete bottle samples collected during CTD-rosette casts on Northeast U.S. Shelf Long-Term Ecological Research (NES-LTER) Transect cruises (ongoing since 2017). Sampling frequency is approximately seasonal. Samples were filtered and collected on combusted glass fiber filters, pelletized using ultra clean tin disks, and combusted using a Flash EA1112 CHN analyzer to calculate concentrations of particulate organic carbon and particulate organic nitrogen in micromoles per liter. Values are also reported as concentrations in micrograms per liter and carbon to nitrogen molar ratio.
Time-averaged borehole temperatures at AM01–AM06 on the Amery Ice Shelf
<p>These are supplementary materials for the paper:</p> <p>Wang, Y., Zhao, C., Gladstone, R., Galton-Fenzi, B., and Warner, R.: Thermal structure of the Amery Ice Shelf from borehole observations and simulations, The Cryosphere Discuss. [preprint], https://doi.org/10.5194/tc-2021-248, in review, 2021.</p> <p>Full description is given in the paper.</p>
Ensemble of NEMO present-day (1989-2009) and future (2080-2100 under RCP8.5) ocean properties and ice shelf melt rates in the Amundsen Sea
<p>Model outputs used in <a href="https://www.essoar.org/doi/10.1002/essoar.10511482.3">Jourdain et al. (GRL, 2022)</a></p> <p>The output files consist of monthly climatologies over either 1989-2009 or 2080-2100. The file names have the form:</p> <p><strong>climato_monthly_AMUXL12-GNJ002_<simu>_<group>_1989_2009.nc</strong>, where :</p> <ul> <li><simu> is either : <ul> <li>"BM02MAR" (ensemble member A, present-day),</li> <li>"BM03MAR" (ensemble member B, present-day),</li> <li>"BM04MAR" (ensemble member C, present-day),</li> <li>"BM02MARrcp85" (ensemble member A, future for both surface and lateral boundaries),</li> <li>"BM03MARrcp85" (ensemble member B, future for surface BUT NOT for lateral boundaries),</li> <li>"BM03MARrcBDY" (ensemble member B, future for both surface and lateral boundaries),</li> <li>"BM04MARrcp85" (ensemble member C, future for both surface and lateral boundaries),</li> </ul> </li> <li><group> is either : <ul> <li>"SBC" (surface boundary conditions),</li> <li>"icemod" (sea ice variables),</li> <li>"gridT" (temperature, salinity),</li> <li>"gridU" (zonal velocities),</li> <li>"gridV" (meridional velocities).</li> </ul> </li> </ul> <p>Grid information in:</p> <ul> <li>mesh_mask_AMUXL12_BedMachineAntarctica-2019-05-24.nc (ensemble member A),</li> <li>mesh_mask_AMUXL12_BedMachineAntarctica-2020-07-15_v02_ICB380.nc (ensemble members B & C).</li> </ul> <p>where:</p> <ul> <li>glamt : longitude</li> <li>gphit: latitude</li> <li>e1t, e2t, e3t_0 : mesh size (in meters) along x, y, z</li> <li>tmask = 1 for ocean mesh, = 0 otherwise (land, continental ice).</li> </ul> <p> </p> <p><strong>Acknowledgments:</strong> This work was granted access to the HPC resources of CINES (occigen) under the allocation A0100106035 attributed by GENCI.</p>
Drainage basins and shelf sea areas in the Arctic
<p>Arctic shelf seas within the Arctic Ocean and surrounding the Arctic Ocean were combined from Jakobsson (2002) and IHO (1953) to account for the whole marine area of the Arctic Ocean according to the IHO definition that receives terrestrial riverine drainage. The seaward border of the shelf is defined as the break in topograhy (bathymetry) of the seafloor according to Jakobsson (2002).</p> <p>Terrestrial drainage basins from the pan-Arctic catchment database (ARCADE; Speetjens et al., 2023) were matched with the Arctic shelf seas, where both datasets meet at the coast. Terrestrial drainage basins were aligned with the boundaries of the Arctic shelf seas to define broader regions, always with a pair of shelf sea and terrestrial catchment.</p> <p> </p> <p>References:</p> <p>International Hydrographic Organization (IHO)(1953). Limits of oceans and seas. 3rd edition. IHO Special Publication 23, Monaco, 38 pp. https://www.marineregions.org/gazetteer.php?p=details&id=1904.</p> <p>Jakobsson, M. (2002). Hypsometry and volume of the Arctic Ocean and its constituent seas. Geochemistry, Geophysics, Geosystems 3, 1-18, doi:https://doi.org/10.1029/2001GC000302.</p> <p>Speetjens, N. J., Hugelius, G., Gumbricht, T., Lantuit, H., Berghuijs, W. R., Pika, P. A., Poste, A., and Vonk, J. E. (2023). The pan-Arctic catchment database (ARCADE), Earth Syst. Sci. Data 15, 541–554, https://doi.org/10.5194/essd-15-541-2023.</p>
Shelf–to–basin shuttle of highly fractionated chromium isotopes in the Arctic Ocean
<p>This dataset contains total dissolved chromium concentration and isotopic ratios in seawater associated with our paper "Shelf–to–basin shuttle of highly fractionated chromium isotopes in the Arctic Ocean" (submitted and accepted in Geochimica Cosmochimica Acta).</p> <p>The seawater samples were collected during the 2015 ArcticNet/Geotraces cruise aboard the CCGS Amundsen along the sections GN02 and GN03. </p> <p>All processing and measurements were done at the Saskatchewan Isotope Laboratory at the University of Saskatchewan (Canada).</p> <p>This data will also be available in the next GEOTRACES Intermediate Data Product (November 2025).</p> <p><span><strong>></strong> Cr_53_52_D_DELTA_BOTTLE_METADATA-2015CanadianArcticGEOTRACEScruise_OVERVIEW.csv : details the context of the expedition and the sampling/processing methods;</span></p> <p><span><strong>></strong> Cr_53_52_D_DELTA_BOTTLE_METADATA-2015CanadianArcticGEOTRACEScruise_DATA.csv : gives details on the data (<em>e.g.</em> units), as well as technical information associated with the measurements;</span></p> <p><span><strong>></strong> Cr_53_52_D_DELTA_BOTTLE_DATA-2015CanadianArcticGEOTRACEScruise.csv : chromium data associated with the paper.</span></p>
Ensemble of ice shelf basal melt rates and ocean properties for tipped-over continental shelves
<p><strong>Summary</strong><strong>:</strong></p> <p>This dataset contains the reference and tipped states from several model configurations developed at the <a href="https://www.awi.de/en/">Alfred Wegener Institute (AWI)</a> and the <a href="https://www.ige-grenoble.fr/?lang=en">Institut des Géosciences de l’Environnement (IGE)</a>. They were gathered here in the context of the <a href="https://www.tipaccs.eu">TiPACCs European project</a> and constitute a useful ensemble of reference and tipped ocean–ice-shelf simulations that <strong>can be used to feed ice-sheet simulations or to train melt parameterizations</strong>.</p> <p>The simulations produced by AWI are based on the <a href="https://fesom.de">FESOM</a> global ocean–sea-ice model using either Z- or Sigma- coordinates and all show a cold-to-warm tipping point for Filchner-Ronne Ice Shelf. The two sets of simulations produced by IGE are based on the <a href="https://www.nemo-ocean.eu">NEMO</a> ocean–sea-ice model. They include a global configuration showing a cold-to-warm tipping point for Ross Ice Shelf, and regional Amundsen Sea configuration showing a warm-to-warmer transition (likely not a proper tipping point). </p> <p>The files include 3-dimensional and sea-floor ocean temperatures and salinities, ice-shelf melt rates, as well as topographic and grid data. All variables are interpolated onto the common 8km stereographic grid that was used to provide ocean forcing in ISMIP6 (<a href="https://doi.org/10.5194/tc-14-2331-2020">Nowicki et al. 2020</a>).</p> <p>We provide the reference state and the anomaly, so that the tipped state is:</p> <ul> <li><em>Tipped = Reference + Anomaly</em></li> </ul> <p>To have an overview of the reference and tipped states, have a look at these figures:</p> <ul> <li><em>figure_ref_and_anomalies_1.pdf</em></li> <li> <p><em>figure_ref_and_anomalies_2.pdf</em></p> </li> <li> <p><em>figure_seafloor_temp_zooms.pdf</em></p> </li> </ul> <p> </p> <p>_______________________________________________</p> <p><strong>Detailed Data Description</strong><strong>:</strong></p> <p> </p> <ul> <li><strong>reference_high_FESOM_sigma_AWI_TiPACCs.nc</strong> <ul> <li>contact: Ralph Timmermann <a href="mailto:ralph.timmermann@awi.de">ralph.timmermann@awi.de</a>, Verena Haid <a href="mailto:verena.haid@awi.de">verena.haid@awi.de</a></li> <li>model: FESOM1.4, sigma-coordinates (global with refined grid around Antarctica)</li> <li>atmospheric forcing: HadCM3 20C</li> <li>provided average: 1990-1999 (10-year mean)</li> <li>more: <a href="https://doi.org/10.1007/s10236-013-0642-0">Timmermann and Hellmer (2013)</a></li> </ul> </li> </ul> <p> </p> <ul> <li><strong>reference_low_FESOM_sigma_AWI_TiPACCs.nc</strong> <ul> <li>contact: Ralph Timmermann <a href="mailto:ralph.timmermann@awi.de">ralph.timmermann@awi.de</a>, Verena Haid <a href="mailto:verena.haid@awi.de">verena.haid@awi.de</a></li> <li>model: FESOM1.4, sigma-coordinates (global with refined grid around Antarctica)</li> <li>atmospheric forcing: HadCM3 20C</li> <li>provided average: 1990-1999 (10-year mean)</li> <li>more: <a href="https://doi.org/10.5194/os-13-765-2017">Timmermann and Goeller (2017)</a></li> </ul> </li> </ul> <p> </p> <ul> <li><strong>reference_FESOM_z_AWI_TiPACCs.nc</strong> <ul> <li>contact: Verena Haid <a href="mailto:verena.haid@awi.de">verena.haid@awi.de</a></li> <li>model: FESOM1.4, Z-coordinates (global with refined grid around Antarctica)</li> <li>atmospheric forcing: ERA Interim</li> <li>provided average: 2008-2017 (10-year mean), i.e. model year 30-39</li> <li>more: same mesh as <a href="https://doi.org/10.5194/tc-13-2317-2019">Gürses et al. (2019)</a></li> </ul> </li> </ul> <p> </p> <ul> <li><strong>reference_NEMO4_eORCA025.L121_IGE_TiPACCs.nc</strong> <ul> <li>contact: Pierre Mathiot <a href="mailto:pierre.mathiot@univ-grenoble-alpes.fr">pierre.mathiot@univ-grenoble-alpes.fr</a></li> <li>model: NEMO-4.0, eORCA025.L121 (Global, 1/4°, 121 vertical levels)</li> <li>atmospheric forcing: JRA55do</li> <li>provided average: 2<sup>nd</sup> cycle of 1989-1998 (10-year mean); we first run 1979-2018, and we redo 1979-1998 starting from the 2018 state.</li> <li>more: <a href="https://pmathiot.github.io/NEMOCFG/docs/build/html/simu_eORCA025_OPM021.html">https://pmathiot.github.io/NEMOCFG/docs/build/html/simu_eORCA025_OPM021.html</a></li> </ul> </li> </ul> <p> </p> <ul> <li><strong>reference_NEMO3_AMUXL12.L75_IGE_TiPACCs.nc</strong> <ul> <li>contact: Nicolas Jourdain <a href="mailto:nicolas.jourdain@univ-grenoble-alpes.fr">nicolas.jourdain@univ-grenoble-alpes.fr</a></li> <li>model: NEMO-3.6, AMUXL12.L75 (Amundsen, 1/12°, 75 vertical levels)</li> <li>atmospheric forcing: MAR (<a href="https://doi.org/10.5194/tc-14-229-2020">Donat-Magnin et al. 2020</a>)</li> <li>provided average: 1989-2009 (21-year mean)</li> <li>more: similar model set-up as <a href="https://doi.org/10.1016/j.ocemod.2018.11.001">Jourdain et al. (2019)</a>.</li> </ul> </li> </ul> <p> </p> <ul> <li><strong>anomaly_high_FESOM_sigma_AWI_TiPACCs.nc</strong> <ul> <li>continuation of reference_high_FESOM_sigma_AWI_TiPACCs.nc</li> <li>forced with HadCM3 A1B</li> <li>provided average: 2190-2199 (10-year mean)</li> </ul> </li> </ul> <p> </p> <ul> <li><strong>anomaly_low_FESOM_sigma_AWI_TiPACCs.nc</strong> <ul> <li>continuation of reference_low_FESOM_sigma_AWI_TiPACCs.nc</li> <li>forced with HadCM3 A1B</li> <li>provided average: 2190-2199 (10-year mean)</li> </ul> </li> </ul> <p> </p> <ul> <li><strong>anomaly_high_FESOM_z_AWI_TiPACCs.nc</strong> <ul> <li>same model set-up as reference_FESOM_z_AWI_TiPACCs.nc</li> <li>atmospheric forcing south of 60°S HadCM3 A1B starting 2050, otherwise ERA Interim starting 1979</li> <li>provided average: model year 69-78 (10-year mean), i.e. 2008-2017 of 2<sup>nd</sup> 39yr-cycle</li> </ul> </li> </ul> <p> </p> <ul> <li><strong>anomaly_medium_FESOM_z_AWI_TiPACCs.nc</strong> <ul> <li>same model set-up as reference_FESOM_z_AWI_TiPACCs.nc</li> <li>atmospheric forcing: ERA Interim modified with a strong imprint of the seasonal cycle of HadCM3 A1B 2070-2089</li> <li>provided average: model year 69-78 (10-year mean), i.e. 2008-2017 of 2<sup>nd</sup> 39yr-cycle</li> </ul> </li> </ul> <p> </p> <ul> <li><strong>anomaly_low_FESOM_z_AWI_TiPACCs.nc</strong> <ul> <li>same model set-up as reference_FESOM_z_AWI_TiPACCs.nc</li> <li>atmospheric forcing: manipulated ERA Interim with prolongued summer and shorter, milder winter south of 50°S, additional modification of winds in Weddell Sea region</li> <li>provided average: model year 108-117 (10-year mean), i.e. 2008-2017 of 3<sup>rd</sup> 39yr-cycle</li> </ul> </li> </ul> <p> </p> <ul> <li><strong>anomaly_NEMO4_eORCA025.L121_IGE_TiPACCs.nc</strong> <ul> <li>similar to reference_NEMO4_eORCA025.L121_IGE_TiPACCs.nc</li> <li>perturbation of the model parameters: Different iceberg distribution and different sea-ice–ocean drag and snow conductivity on sea-ice, leading to less sea-ice production in the eastern Ross Sea.</li> <li>More: <a href="https://pmathiot.github.io/NEMOCFG/docs/build/html/simu_eORCA025_OPM020.html">https://pmathiot.github.io/NEMOCFG/docs/build/html/simu_eORCA025_OPM020.html</a></li> </ul> </li> </ul> <p> </p> <ul> <li><strong>anomaly_NEMO3_AMUXL12.L75_IGE_TiPACCs.nc</strong> <ul> <li>similar to reference_NEMO3_AMUXL12.L75_IGE_TiPACCs.nc</li> <li>perturbation of atmospheric forcing: MAR forced by the CMIP5 multi-model anomaly under the RCP8.5 scenario (<a href="https://doi.org/10.5194/tc-15-571-2021">Donat-Magnin et al. 2021</a>).</li> <li>provided average: 2080-2100 (21-year average)</li> </ul> </li> </ul> <p> </p>
Bathymetry beneath the Amery ice shelf, East Antarctica, revealed by airborne gravity
<p>We estimated the seafloor topography beneath the Amery Ice Shelf, East Antarctica, from airborne gravity anomaly through a nonlinear inversion method called simulated annealing. The estimation results provide a view of the seafloor beneath the Amery Ice Shelf, where direct bathymetric observations are rare. The model, 'gravity_estimated_seafloor_topography_beneath_the_Amery_Ice_Shelf.nc', is in NetCDF format which can be read through MATLAB commands "ncdisp" and "ncread". Contents of the model can be found in "contents.txt". The MATLAB program "nc2mat.m" reads the NetCDF ".nc" format model and saves the variables in the model to a MATLAB ".mat" format file.</p>
Simulations of Miocene Antarctic ice-sheet variability under increased precipitation and sub-shelf melt, using the ice-sheet model IMAU-ICE
<p>To demonstrate the viability of a precipitation regime change leading to a fundamentally different volume-to-area ratio of the Antarctic ice sheet, we deploy the 3D thermodynamical ice sheet/shelf model IMAU-ICE v1.1.1. In the standard set-up (<a href="https://doi.org/10.5194/cp-2023-12">Stap et al., 2021a</a>, <a href="https://doi.pangaea.de/10.1594/PANGAEA.939114">2021b</a>), climate forcing follows from pre-run warm and cold snapshot climate simulations. The applied climate forcing is transiently calculated based on the prescribed CO<sub>2</sub> concentration and the modelled ice sheet size, through a matrix interpolation method. Equilibrium experiments are performed at various CO<sub>2</sub> levels between preindustrial and 3x preindustrial CO<sub>2</sub> values, with insolation at present-day levels and initiated from an ice-free Miocene Antarctic topography (dataset <a href="https://doi.pangaea.de/10.1594/PANGAEA.923109">Hochmuth et al., 2020</a>). Here, we perform additional sensitivity experiments, in which we apply a fixed precipitation increase and extreme sub-shelf melt rates. The precipitation anomaly is calculated as 25% of the warm snapshot precipitation fields, sub-shelf melt rates are set to 400 m/yr.</p> <p> </p>
Atlantic sea scallop energy budget data on the Northeast U.S. Shelf, monthly in 2010 and 2012
This dataset includes monthly Atlantic sea scallop energy budget data from Georges Bank to the Mid-Atlantic Bight based on Scope For Growth (SFG) model results in 2010 and 2012. Results were supported in part by Northeast U.S. Shelf Long-Term Ecological Research (NES-LTER). For more details please see: Zang, Z., et al. (2022) Modeling Atlantic sea scallop (Placopecten magellanicus) scope for growth on the Northeast U.S. Shelf. Fisheries Oceanography, https://doi.org/10.1111/fog.12577.
Zooplankton and micronekton abundance using an Isaacs-Kidd Midwater trawl on Northeast U.S. Shelf Long Term Ecological Research (NES-LTER) Transect cruises, ongoing since 2023
During Northeast U.S. Shelf Long-Term Ecological Research (NES-LTER) Transect cruises, acoustic backscattering layers were identified using multifrequency echosounders and were targeted for collection of zooplankton and micronekton using an Isaacs-Kidd Midwater Trawl. On each cruise, trawling was conducted at at least three stations, including the one at the shelfbreak front, one inshore of the front, and one offshore of the front. The catches from the trawls were preserved on ship and later identified to the lowest possible taxonomic level using a dissecting microscope. Each identified taxon was counted to provide net total abundance by taxon. Trawling was initiated in spring 2023 and is ongoing.
SBC LTER: Cross-shelf Study 2008-2009: Profiles of CTD, biogeochemistry, primary production, abundance of phytoplankton groups, and abundance and production of bacteria
These data were used by the following papers: Goodman, J., M. A. Brzezinski, E. R. Halewood and C. A. Carlson. 2012. Sources of phytoplankton to the inner continental shelf in the Santa Barbara Channel inferred from cross-shelf gradients in biological, physical and chemical parameters. Continental Shelf Research, 48: 27-39. (DOI: 10.1016/j.csr.2012.08.011) Halewood, E. R., C. A. Carlson, M. A. Brzezinski, D. C. Reed and J. Goodman. 2012. Annual cycle of organic matter partitioning and its availability to bacteria across the Santa Barbara Channel continental shelf. Aquatic Microbial Ecology, 67:189-209. (DOI:10.3354/ame01586) These data were collected on monthly day cruises from January 2008 to April 2009 on the RV Kelp Fish at five stations across the shelf starting at Mohawk Reef in the nearshore area of the Santa Barbara Channel, California, USA. Data were collected with a SBE19-Plus and rosette sampler. Measurements include standard CTD parameters in 1 m bins (e.g. salinity, temperature, density). At selected depths (1, 5, 10, 20 m), rosette bottle samples were collected for nutrients, pigments, particulate and dissolved organic carbon and nitrogen, and bacterial abundance, community structure and productivity. Phytoplankton abundances (to genus) were obtained from the 5 m sample only.
ICESat-2 Water Depth Retrieval Comparisons for Four Supraglacial on Amery Ice Shelf, East Antarctica
<p>This archive contains the code used for analysis and producing figures for the following paper:</p> <p>Fricker, H.A., Arndt, P.S., Brunt, K.M., Datta, R.T., Fair, Z., Jasinski, M.F., Kingslake, J., Magruder, L.A., Moussavi, M., Pope, A. and Spergel, J.J., 2021. “ICESat-2 meltwater depth estimates: application to surface melt on Amery Ice Shelf, East Antarctica.” Geophysical Research Letters, 48(8), DOI: 10.1029/2020GL090550. URL: <a href="https://doi.org/10.1029/2020GL090550">https://doi.org/10.1029/2020GL090550</a><br><br>These materials are also on GitHub:<br><a href="github.com/fliphilipp/ameryMeltLakesICESat2">https://github.com/fliphilipp/ameryMeltLakesICESat2</a> </p> <p> </p> <p>The code for generating manually annotated baseline depth estimates from ICESat-2 ATL03 photon data is available here:<br><a href="https://github.com/fliphilipp/pondpicking">https://github.com/fliphilipp/pondpicking</a></p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.