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Fig. 1 in Molecular identification and epidemiological data of Anisakis spp. (Nematoda: Anisakidae) larvae from Southeastern Pacific Ocean off Peru

Fig. 1. Scanning electron micrographs of Anisakis type I and II.1a and 2a. Cephalic end. Detail of the structures: oral cavity (oc), tooth (t), excretory pore (ep), subventral lip bulge (s). 1b. caudal end of Anisakis pegreffii. 2b. caudal end of Anisakis physeteris. Detail of the structures: anal pore (ap), mucron (m).

opencc-by-4.0Dec 2021View details →

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Fig. 2 in Molecular identification and epidemiological data of Anisakis spp. (Nematoda: Anisakidae) larvae from Southeastern Pacific Ocean off Peru

Fig. 2. Phylogenetic tree based on mtDNA cox2 gene sequences exploring the relationships among Anisakis species. The relationship was drawn using Bayesian inference (BI) and maximum likelihood (ML) methods. Posterior probability value (first) and nodal support is shown as bootstrap value (second) on the basis of 10 million generations for BI and 1000 replicates (only bootstrap values greater than 80% are shown) for ML, respectively. Scale bar indicate nucleotide substitutions per site. GenBank accession numbers are shown in parentheses. Hysterothylacium deardorffoverstreetorum was used as an outgroup.

opencc-by-4.0Dec 2021View details →

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SDUST2024MSS_AO: a mean sea surface model of the Arctic Ocean based on CryoSat-2 SAR altimeter data

This model is a mean sea surface model for ice-covered regions, using CryoSat-2 satellite SAR mode altimeter data from July 2010 to December 2023. The heights are referenced to the WGS-84 ellipsoid, and the grid size is 5 km × 5 km.

opencc-by-4.0Aug 2024View details →

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Early pyroxene crystallisation deep below mid-ocean ridges: Supplementary data of gabbro phase mapping

The data repository contains part of the original microscopy imagery datasets from optical microscopy, electron microscopy backscattered electron (SEM-BSE), and Synchrotron X-ray fluorescence microscopy (XFM) experiments presented in <a href="https://doi.org/10.1016/j.epsl.2025.119423">Ubide et al. (2025)</a> 'Early pyroxene crystallisation deep below mid-ocean ridges' by Teresa Ubide*, David T Murphy, Robert B Emo, Michael Jones, Marco Acevedo Zamora, and Balz S Kamber Specifically, it includes the QuPath software (<a href="https://www.nature.com/articles/s41598-017-17204-5">Bankhead et al., 2017</a>) project including rock (mid-ocean ridge olivine gabbro) thin sections 81-R5w and 80-R6w. The project contains the semantic image segmentation outputs generated with the <a href="https://qupath.readthedocs.io/en/stable/docs/tutorials/pixel_classification.html">Pixel Classifier</a> and MatLab script described in <a href="https://www.mdpi.com/2075-163X/13/2/156">Acevedo Zamora et al. 2023</a> (see <a href="https://github.com/marcoaaz/Acevedo-Kamber/tree/main/QuPath_generatingMaps">code repository</a>). Sample 80-R6w was segmented using image annotations in QuPath and an input comprising a false-colour Cr-Ti-Ca XFM image, cross-polarised light maximum intensity (XPL-max), and plane-polarised light (PPL-0 degrees) photomicrographs. Similarly, Sample 81-R5w used a false-colour Cr-Ti-Ca XFM image, <a href="https://github.com/marcoaaz/AcevedoEtAl._2024b_autoencoder">deep sparse autoencoder</a> image representation of XFM (after <a href="https://www.sciencedirect.com/science/article/pii/S0009254124000779?dgcid=rss_sd_all">Acevedo Zamora et al., 2024</a>), cross-polarised light (XPL-0 degrees), plane-polarised light (PPL-0 degrees) photomicrographs, and recoloured SEM-BSE (after <a href="https://www.mdpi.com/2075-163X/13/2/156">Acevedo Zamora et al. 2023</a>).  The segmentation of both samples provided a conservative estimate of the locations of relict clinopyroxene cores (~4% volume of cpx mask), mantles, and rims in a similar phase map colour scheme for better comparison. If there are questions regarding the utilisation of the data, contact Marco Acevedo (marco.acevedozamora@qut.edu.au ; maaz.geologia@gmail.com).

opencc-by-4.0Sep 2024View details →

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Table 1. Summary data for the 36 in New observations of Papulifères, putative ciliate cysts, from the plankton of the Chukchi Sea (Western Arctic Ocean) in August of 2023

Table 1. Summary data for the 36 stations sampled in 2023. Depth given is the vertical extent of the plankton net tow from the depth indicated to the surface. Chlorophyll a concentration (Chl a) is average integrated concentration (µg L-1) throughout the water column from the surface to approximately the depth of the plankton net tow. Cyst types found refer to the new forms shown in here in Figure 2 (2A-2H), and in the Figures 6 (6A, 6E, 6D) and 7 (7A, 7G, 7H, 7I, 7J, 7K, 7N) in Dolan et al. (2023). For convenience, the supplementary file contains images of all now known Chukchi Sea Papulifère forms in two plates, one showing the 16 spindle-shaped Fusopsis forms, another showing the 18 the spherical and oblong Sphaeropsi s forms.<table><thead><tr><th>St #</th><th>Date Aug 2023</th><th>lat (N°)</th><th>long (W°)</th><th>Tow Depth (m)</th><th>Station Depth</th><th>Chl a</th><th>SST (C°)</th><th>cyst types found</th></tr></thead><tbody><tr><th>1</th><td>3</td><td>65,17</td><td>–168,69</td><td>45</td><td>55</td><td>1,45</td><td>9,9</td><td>Ø</td></tr><tr><th>2</th><td>3</td><td>66,63</td><td>–168,69</td><td>35</td><td>45</td><td>7,47</td><td>7,8</td><td>Ø</td></tr><tr><th>3</th><td>3</td><td>67,67</td><td>–168,96</td><td>45</td><td>55</td><td>9,92</td><td>6</td><td>Ø</td></tr><tr><th>8</th><td>4</td><td>68,24</td><td>–167,12</td><td>38</td><td>48</td><td>0,74</td><td>12,6</td><td>Ø</td></tr><tr><th>9</th><td>4</td><td>69,17</td><td>–168,67</td><td>43</td><td>53</td><td>0,58</td><td>9,9</td><td>Ø</td></tr><tr><th>10</th><td>5</td><td>70,50</td><td>–168,67</td><td>35</td><td>45</td><td>6,48</td><td>6</td><td>2E, 2F</td></tr><tr><th>11</th><td>5</td><td>71,43</td><td>–168,67</td><td>40</td><td>50</td><td>0,75</td><td>7,9</td><td>Ø</td></tr><tr><th>13</th><td>5</td><td>72,36</td><td>–168,66</td><td>50</td><td>60</td><td>6,16</td><td>1</td><td>6A</td></tr><tr><th>16</th><td>6</td><td>73,89</td><td>–168,19</td><td>100</td><td>183</td><td>1,5</td><td>1</td><td>Ø</td></tr><tr><th>18</th><td>6</td><td>74,80</td><td>–167,90</td><td>100</td><td>195</td><td>0,413</td><td>1</td><td>Ø</td></tr><tr><th>21</th><td>7</td><td>76,00</td><td>–170,49</td><td>100</td><td>1315</td><td>1,22</td><td>–0,5</td><td>6A, 7H, 7K, 7N</td></tr><tr><th>23</th><td>8</td><td>77,00</td><td>–170,00</td><td>100</td><td>2214</td><td>0,53</td><td>–1,1</td><td>6A</td></tr><tr><th>24</th><td>8</td><td>77,00</td><td>–174,99</td><td>100</td><td>2012</td><td>0,34</td><td>–1,3</td><td>Ø</td></tr><tr><th>25</th><td>9</td><td>77,00</td><td>179,95</td><td>100</td><td>1081</td><td>0,09</td><td>–1,2</td><td>OE</td></tr><tr><th>27</th><td>12</td><td>78,54</td><td>–177,58</td><td>100</td><td>1009</td><td>0,07</td><td>–1,2</td><td>7K</td></tr><tr><th>28</th><td>13</td><td>80,00</td><td>172,40</td><td>100</td><td>2702</td><td>0,14</td><td>–1</td><td>6A</td></tr><tr><th>29</th><td>14</td><td>79,00</td><td>172,80</td><td>100</td><td>2561</td><td>0,15</td><td>–0,9</td><td>Ø</td></tr><tr><th>30</th><td>14</td><td>78,00</td><td>173,20</td><td>100</td><td>1133</td><td>0,14</td><td>0,3</td><td>Ø</td></tr><tr><th>31</th><td>15</td><td>77,00</td><td>173,60</td><td>100</td><td>740</td><td>0,4</td><td>0,2</td><td>Ø</td></tr><tr><th>32</th><td>15</td><td>76,00</td><td>173,61</td><td>100</td><td>265</td><td>0,2</td><td>–1,1</td><td>7H</td></tr><tr><th>33</th><td>16</td><td>75,00</td><td>173,60</td><td>100</td><td>147</td><td>0,07</td><td>–0,06</td><td>6E</td></tr><tr><th>36</th><td>16</td><td>74,00</td><td>170,16</td><td>40</td><td>52</td><td>0,1</td><td>–0,8</td><td>Ø</td></tr><tr><th>37</th><td>17</td><td>74,69</td><td>174,62</td><td>60</td><td>72</td><td>0,2</td><td>–1</td><td>2A</td></tr><tr><th>39</th><td>18</td><td>75,73</td><td>177,18</td><td>100</td><td>499</td><td>0,15</td><td>–1,3</td><td>2G</td></tr><tr><th>40</th><td>20</td><td>75,07</td><td>176,80</td><td>100</td><td>196</td><td>0,31</td><td>–1,2</td><td>2B, 2H, 7I, 7N</td></tr><tr><th>43</th><td>21</td><td>75,16</td><td>–179,97</td><td>100</td><td>539</td><td>0,35</td><td>–1,4</td><td>6D, 6E, 7J</td></tr><tr><th>45</th><td>21</td><td>75,15</td><td>–176,00</td><td>100</td><td>327</td><td>1,36</td><td>–1</td><td>Ø</td></tr><tr><th>47</th><td>22</td><td>75,24</td><td>–171,97</td><td>100</td><td>505</td><td>2,73</td><td>–0,7</td><td>6A, 7J</td></tr><tr><th>50</th><td>23</td><td>75,69</td><td>–166,64</td><td>100</td><td>392</td><td>3,1</td><td>–0,9</td><td>6A, 7H, 7N</td></tr><tr><th>52</th><td>23</td><td>76,57</td><td>–164,36</td><td>100</td><td>550</td><td>0,019</td><td>–1,1</td><td>7G</td></tr><tr><th>54</th><td>24</td><td>77,47</td><td>–164,10</td><td>100</td><td>280</td><td>0,32</td><td>–1,3</td><td>2C, 7J</td></tr><tr><th>56</th><td>25</td><td>77,49</td><td>–158,73</td><td>100</td><td>1323</td><td>0,02</td><td>–1,3</td><td>7H, 7J</td></tr><tr><th>57</th><td>26</td><td>76,30</td><td>–156,22</td><td>100</td><td>725</td><td>0,23</td><td>–0,1</td><td>Ø</td></tr><tr><th>58</th><td>26</td><td>76,52</td><td>–159,78</td><td>100</td><td>2113</td><td>0,21</td><td>–1</td><td>Ø</td></tr><tr><th>59</th><td>27</td><td>75,50</td><td>–161,15</td><td>100</td><td>2098</td><td>0,2</td><td>–0,5</td><td>2D, 7A</td></tr><tr><th>60</th><td>27</td><td>74,52</td><td>–162,15</td><td>100</td><td>1596</td><td>0,27</td><td>1,8</td><td>2G, 6A, 7A, 7H</td></tr></tbody></table>

opencc-by-4.0Feb 2024View details →

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Processed data used for JGR publication "Role of Midwater Mixed Waves in the Loop Current Separation Events from A Coupled Ocean-Atmosphere Regional Model and In-Situ Observations"

This is the processed dataset used in the JGR publication "Role of Midwater Mixed Waves in the Loop Current Separation Events from A Coupled Ocean-Atmosphere Regional Model and In-Situ Observations" by Xiao Ge. Please contact the author (gexiao@tamu.edu) for all the original/processed outputs of R-CESM, and use the following original papers as citations. The dataset used in this research includes: 1. Loop Current Dynamics 2009-2011: LC_*.nc is the processed (reorganized) data for each in-situ station, * represents their station ID <ul> <li>https://digital.library.unt.edu/ark:/67531/metadc955416/</li> <li>https://www.sciencedirect.com/science/article/pii/S0377026516301348?via%3Dihub</li> <li>https://search.dataone.org/view/%7BBD2513E6-3B34-4B7C-BCB9-3C4ED5E8D0FB%7D</li> </ul> 2. Regional Community Earth System Model, R-CESM: <a href="https://zenodo.org/api/records/13932074/draft/files/h.nc/content" target="_blank" rel="noopener noreferrer">h.nc</a> is the bathymetry data of R-CESM; cmpr_*.nc files are provided as examples of the original R-CESM outputs; pvsf_prho_*.nc are the processed (subsampled at the target region and interpolated on potential density layers, derived stream function, potential vorticity, and relative vorticity) R-CESM outputs used in this research; and <a href="https://zenodo.org/uploads/13932074" target="_blank" rel="noopener noreferrer">LC_pv_40hlp_2013.nc</a> is the example of organized processed R-CESM (pvsf_prho_*.nc files) containing potential vorticity and relative vorticity for figures plotting <ul> <li>https://journals.ametsoc.org/view/journals/bams/102/9/BAMS-D-20-0024.1.xml?tab_body=fulltext-display</li> </ul>

opencc-by-4.0Oct 2024View details →

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Linked collectors and determiners for: Amphi-Indian Ocean Disjunction in the Trans-Pacific Genus Archaeoglenes Brown (Coleoptera: Tenebrionidae: Phrenapatinae): New Taxonomic and Distributional Data.

Natural history specimen data linked to collectors and determiners held within, "Amphi-Indian Ocean Disjunction in the Trans-Pacific Genus Archaeoglenes Brown (Coleoptera: Tenebrionidae: Phrenapatinae): New Taxonomic and Distributional Data". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/3574f6e2-f633-43f4-8079-53cc3eee22eb">https://bionomia.net/dataset/3574f6e2-f633-43f4-8079-53cc3eee22eb</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/3574f6e2-f633-43f4-8079-53cc3eee22eb">https://gbif.org/dataset/3574f6e2-f633-43f4-8079-53cc3eee22eb</a>. Formatted as a Frictionless Data package.

opencc-zeroJan 2024View details →

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Data and Analyses supporting "Human-caused ocean warming has intensified recent hurricanes"

Notebooks and data from "Human-caused ocean warming has intensified recent hurricanes", in press at Environmetal Research: Climate. A pre-print of the paper can be found at <a href="https://essopenarchive.org/users/667788/articles/1232538-human-caused-ocean-warming-has-intensified-recent-hurricanes">https://essopenarchive.org/users/667788/articles/1232538-human-caused-ocean-warming-has-intensified-recent-hurricanes</a> Included are study analysis notebooks, figure plotting notebooks supportiung the paper publication, and data file outputs forming the computation foundation of paper results. Please email <a href="mailto:dgilford@climatecentral.org" target="_blank" rel="noopener">dgilford@climatecentral.org</a> with any questions or feedback.   Funding for this work was provided by the Bezos Earth Fund, The Schmidt Family Foundation, and the CO2 Foundation.

opengpl-3.0-or-laterJul 2024View details →

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Data for: A further source of Tokyo earthquakes and Pacific Ocean tsunamis

This data repository contains the location of cores collected as part of this study, the microfossil and radiocarbon results from those cores, and fault parameters used in eleven historical and hypothetical tsunami simulations for Kujukuri, Japan (Boso Peninsula). The work is supported by the Geological Survey of Japan, National Institute of Advanced Industrial Science and Technology (AIST) and in part by grants awarded to J.E.P. [National Science Foundation (EAR-1303881 and 1624612), Natural Sciences and Engineering Council of Canada (NSERC), Canada Research Chair (CRC) program, and  Japan Society for the Promotion of Science (JSPS) International Research Fellow program at the Geological Survey of Japan (PE14038)]; A.C.P. [Science Foundation Ireland Career Development Award (17/CDA/4695),  Investigator Award (16/IA/4520), Marine Research Programme funded by the Irish Government, co-financed by the European Regional Development Fund (Grant-Aid Agreement No. PBA/CC/18/01), European Union’s Horizon 2020 research and innovation programme under grant agreement No 818144, and SFI Research Centre (16/RC/3872 and 12/RC/2289_P2); and B.P.H. [Singapore Ministry of Education Academic Research Fund (MOE2019-T3-1-004), National Research Foundation Singapore, and Singapore Ministry of Education, under the Reseach Centers of Excellence initiative].

opencc-by-4.0Jun 2021View details →

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Ocean and ice with waves data for role of surface gravity waves in aquaplanet ocean climates

This data corresponds to the runs analysed in the manscript: Role of Surface Gravity Waves in Aquaplanet Ocean Climates (JAMES, 2021). In this work, we present a set of idealised numerical experiments that demonstrate the thermodynamic and dynamic implications of surface gravity waves for the oceanic climate of an aquaplanet. We study the impact of accounting for modulations by such waves upon air-sea momentum fluxes, Langmuir circulation and the Stokes-Coriolis force. This dataset is made up of atmospheric, oceanic and surface gravity wave simulations. When uncompressed the total dataset is 1.6 TB, the ocean and ice with waves component is 564 GB. See below for further details. See the related works section for the corresponding datasets.

opencc-zeroMay 2021View details →

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Ocean and ice without waves data for role of surface gravity waves in aquaplanet ocean climates

This data corresponds to the runs analysed in the manscript: Role of Surface Gravity Waves in Aquaplanet Ocean Climates (JAMES, 2021). In this work, we present a set of idealised numerical experiments that demonstrate the thermodynamic and dynamic implications of surface gravity waves for the oceanic climate of an aquaplanet. We study the impact of accounting for modulations by such waves upon air-sea momentum fluxes, Langmuir circulation and the Stokes-Coriolis force. This dataset is made up of atmospheric, oceanic and surface gravity wave simulations. When uncompressed the total dataset is 1.6 TB, the ocean and ice without waves component is 484 GB. See below for further details. See the related works section for the corresponding datasets.

opencc-zeroMay 2021View details →

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A Metamorphic Origin for Europa's Ocean - Supplementary Data Files

A Metamorphic Origin for Europa's Ocean - Supplementary Data Files M. Melwani Daswani, S. D. Vance, M. J. Mayne, and C. R. Glein Jet Propulsion Laboratory, California Institute of Technology daswani@jpl.nasa.gov 2021-08-18 This folder contains the Supplementary Data files consisting of input data and output data products. The paper is accepted in Geophysical Research Letters. A preprint may be found here: <a href="https://doi.org/10.1002/essoar.10507048.1">https://doi.org/10.1002/essoar.10507048.1</a>, but please see the article on Geophysical Research Letters for the properly formatted, peer-reviewed, revised version. Contents: AccretR Europa MC-Scale composition output.xlsx Contains the composition of Europa after accretion, obtained by running the AccretR program. AccretR can be found on Zenodo: https://doi.org/10.5281/zenodo.3827540 or GitHub (most up to date): https://github.com/mmelwani/AccretR Fe-S core composition models Contains the Perple_X input and output files for constraining the composition of the Fe+-S core. Thermodynamic data used was from Saxena and Eriksson (2015), also included as a Perple_X thermodynamic file. Rcrust prograde metamorphism models Contains the input and output files for the Rcrust models, which are the metamorphic prograde path thermodynamic. Rcrust is required to run these models (http://www.sun.ac.za/english/faculty/science/earthsciences/rcrust), as well as the "meemum" program from Perple_X (https://www.perplex.ethz.ch/). The Perple_X version used was "6.8.7", and was compiled from source to enable 12 thermodynamic components (i.e. major elements). CHIM-XPT ocean column composition models Contains the CHIM-XPT input and output files, which model the ocean composition from seafloor to surface, including precipitated minerals, aqueous solutes and saturated gases. Inputs for these models were the fluids extracted from the Rcrust prograde metamorphic models. Density and volume of clathrates.xlsx Shows the calculations carried out to find the temperature, density and volume of CO2 clathrates in Europa's ocean.

opencc-by-4.0Aug 2021View details →

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Code and data archive to accompany "A derivative-free optimisation method for global ocean biogeochemical models", Oliver et. al. 2021

This archive is to accompany the article: A derivative-free optimisation method for global ocean biogeochemical models, Sophy Oliver, Coralia Cartis, Iris Kriest, Simon Tett, and Samar Khatiwala. The optimisation framework used in this study can be found here: https://doi.org/10.5281/zenodo.5517610 The original source code of MOPS were from the Supplement of Kriest et al. (2017). The most recent TMM source code is available at https://github.com/samarkhatiwala/tmm. In this archive: Supplement/Configurations/OxfordMOPS_Configs contains: - ReadOnlyFiles (Files and Code specifically used to run the global ocean biogeochemical model MOPS model with   the Transport Matrix Method, which have been edited to differ from the versions downloaded from the sources above.) - RunCode (runscripts to run the MOPS model with the TMM) - TWIN_Configs (JSON files required by each optimisation experiment carried out). Supplement/OxfordMOPS_EXP contains data for each iteration of all optimisation experiments carried out. Supplement/OPTCLIMSO_PlottingScripts contains MATLAB plotting scripts used to create results figures of these experiments.

opencc-by-4.0Sep 2021View details →

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Data for: Increasing hypoxia on global coral reefs under ocean warming

Ocean deoxygenation is predicted to threaten marine ecosystems globally. However, current and future oxygen concentrations and the occurrence of hypoxic events on coral reefs remain underexplored. Here, using autonomous sensor data to explore oxygen variability and hypoxia exposure at 32 representative reef sites, we reveal that hypoxia is already pervasive on many reefs. 84% of reefs experienced weak to moderate (≤153 to ≤92 μmol O2 kg-1) hypoxia and 13% experienced severe (≤61 μmol O2 kg-1) hypoxia. Under different climate change scenarios based on 4 Shared Socioeconomic Pathways (SSPs), we show that projected ocean warming and deoxygenation will increase the duration, intensity, and severity of hypoxia, with more than 94% and 31% of reefs experiencing weak to moderate and severe hypoxia, respectively, by 2100 under SSP5-8.5. This projected oxygen loss could have negative consequences for coral reef taxa due to the key role of oxygen in organism functioning and fitness.

opencc-zeroJan 2023View details →

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Supplementary material for "Including filter-feeding gelatinous macrozooplankton in a global marine biogeochemical model: model-data comparison and impact on the ocean carbon cycle"

Supplementary material for "Including filter-feeding gelatinous macrozooplankton in a global marine biogeochemical model: model-data comparison and impact on the ocean carbon cycle".   Clerc, C., Bopp, L., Benedetti, F., Vogt, M., and Aumont, O.: Including filter-feeding gelatinous macrozooplankton in a global marine biogeochemical model: model-data comparison and impact on the ocean carbon cycle, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2022-1282, 2022. Three directories can be downloaded: DataOBS :  AtlantECO [WP2] – Traditional microscopy dataset – Thaliacea (Salpida+Doliolida+Pyromosomatida) abundance and biomass concentration data, presented in Clerc et al. (2022).  FigPaper : Source code and .nc files for the figures presented in Clerc et al. (2022) (https://doi.org/10.5194/egusphere-2022-1282).  MY_SRC_PISCES_NEMO_3.6 : Additional fortran routines for the compilation of PISCES-FFGM, the model developed for Clerc et al. (2022), from NEMO-3.6 (https://www.nemo-ocean.eu)

opencc-by-4.0Jan 2023View details →

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GloRanV14 ocean reanalysis MOC data

MOC estimates from the 1/4 degree GloRanV14 global ocean reanalysis averaged over the time period 2000-2021. The MOC is integrated globally ("moc_glo"), and over the Atlantic ("moc_atl") and Indo-Pacific ("moc_indpac") basins. Further details on this reanalysis product are provided in Baker et al., 2023: South Atlantic overturning and heat transport variations in ocean reanalyses and observation-based estimates (https://sp.copernicus.org/articles/1-osr7/4/2023/). Production of GloRanV14 was funded by the E.U. Copernicus Marine Service.

opencc-by-4.0Feb 2023View details →

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The Mixed Layer Depth in the Ocean Model Intercomparison Project (OMIP): Impact of Resolving Mesoscale Eddies: supporting data

This file contains a jupyter notebook (python language) used to produce the figures of a manuscript submitted to the journal Geoscientific Model Development, and the data necessary to reproduce the figures. Abstract of the manuscript: The ocean mixed layer is the interface between the ocean interior and the atmosphere or sea ice, and plays a key role in climate variability. It is thus critical that numerical models used in climate studies are capable of a good representation of the mixed layer, especially its depth. Here we evaluate the mixed layer depth (MLD) in six pairs of non-eddying (1° resolution) and eddy-rich (up to 1/16°) models from the Ocean Model Intercomparison Project (OMIP), forced by a common atmospheric state. For model validation, we use an updated MLD dataset computed from observations using the OMIP protocol (a constant density threshold). In winter, low resolution models exhibit large biases in the deep water formation regions. These biases are reduced in eddy-rich models but not uniformly across models and regions. The improvement is most noticeable in the mode water formation regions of the northern hemisphere. Results in the Southern Ocean are more contrasted, with biases of either sign remaining at high resolution. In eddy-rich models, mesoscale eddies control the spatial variability of MLD in winter. Contrary to a hypothesis that the deepening of the mixed layer in anticyclones would make the MLD larger globally, eddy-rich models tend to have a shallower mixed layer at most latitudes than coarser models do. In addition, our study highlights the sensitivity of the MLD computation to the choice of a reference level and the spatio-temporal sampling, which motivates new recommendations for MLD computation in future model intercomparison projects.

opencc-by-4.0Feb 2023View details →

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LILBID spectra and geochemical data shown in article "Detection of Phosphates Originating from Enceladus' Ocean" by Frank Postberg et al. (2023)

Laser Induced Liquid Beam Ion Desorption (LILBID) mass spectra of phosphates and data of geochemical experiments, shown in article "Detection of Phosphates Originating from Enceladus’ Ocean" by Frank Postberg et al. (2023), published in Nature.

opencc-by-4.0Mar 2023View details →

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Ocean Data Hours - Ocean Race - Ocean Village - Genova Pavilllion - Cape Town 23.02.2023

The ocean plays a significant role in the Earth's system, and understanding its importance is crucial for ensuring sustainable management and exploitation.  Ocean observation should not be a task for experts and scientists alone. Citizen science is a form of scientific collaboration where members of the public participate in scientific research projects, providing data and observations that can be analyzed by researchers. This workshop presents a series of CS initiatives exploiting low cost technologies for ocean data collection by showing and discussing their maturity level and how scientists can already use these data. By supporting citizen science initiatives, policymakers can democratize marine observation science, creating a new type of self-driven, sustainable, and cost-efficient observatory concept, and at the same time, providing for the making of informed decisions based on the best available information. Ocean Data Hours is a series of workshops and talks organized in the Genova Pavillion at the Ocean Village - Ocean Race 2023.

opencc-by-4.0Feb 2023View details →

zenodo40/100

Data used in the definition of Harmful Algal Bloom hotspot for Northern Indian Ocean

The zipped rar file contain raw data used in the harmful algal bloom hotspot analysis for the Northern Indian Ocean. Annual_MK_full folder gives the data on the annual Mann kendal analysis of the chlorophyll data from satellite data. Boreal_season_full folder gives data on seasonally calculated chlorophyll concentration from the Northern Indian ocean. Monthly_MK folder gives the monthly averaged chlorophyll data. The chlorophyll data is further grouped into two; (1) Chlorophyll concentration greater than 4 mg/m^3 and (2) Chlorophyll concentration greater than 10 mg/m^3.

opencc-by-4.0May 2023View details →

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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

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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.

allen-brain-atlas

neuroscienceopenDocumentation, web resources, and API references are available online.

Last verified 2026-04-30Open record

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.

abode-home-cage

behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.

Last verified 2026-04-30Open record

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.

dandi-nwb

electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.

Last verified 2026-04-30Open record

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.

ibl

behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.

Last verified 2026-04-29Open record

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.

openneuro

neuroscienceopenPublished datasets are available on demand over the internet.

Last verified 2026-04-29Open record