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1,337 results for “antarctica”
FIGURES – 8. LM images of Craspedostauros laevissimus and C. confusus sp. nov. 2–8. Craspedostauros laevissimus (sample 11). 9–18. Craspedostauros laevissimus (sample 13). 19–26. Craspedostauros confusus sp. nov. (type population, sample 14). 27. Craspedostauros laevissimus (enlarged view of Fig. 4, sample 11). 28. Craspedostauros confusus sp. nov. (enlarged view of Fig. 22, type specimen). Scale bars = 10 µm. in The genus Craspedostauros E.J.Cox (Bacillariophyta) on the coasts of Livingston Island, Maritime Antarctica
FIGURES – 8. LM images of Craspedostauros laevissimus and C. confusus sp. nov. 2–8. Craspedostauros laevissimus (sample 11). 9–18. Craspedostauros laevissimus (sample 13). 19–26. Craspedostauros confusus sp. nov. (type population, sample 14). 27. Craspedostauros laevissimus (enlarged view of Fig. 4, sample 11). 28. Craspedostauros confusus sp. nov. (enlarged view of Fig. 22, type specimen). Scale bars = 10 µm.
FIGURE. Map of the region and sampling area showing the relative position of Livingston Island to Antarctic Peninsula (A), and the main sampling locations (B): 1—Hannah Point, 2—Mongolian (Reserve) Port, 3—Caleta Argentina. Map outlines are based on OpenStreetMap© contributors (www.openstreetmap.org), edited and arranged using Adobe Illustrator© and Adobe Photoshop®. Scale bars = 35 km (A); 2 km (B). in The genus Craspedostauros E.J.Cox (Bacillariophyta) on the coasts of Livingston Island, Maritime Antarctica
FIGURE. Map of the region and sampling area showing the relative position of Livingston Island to Antarctic Peninsula (A), and the main sampling locations (B): 1—Hannah Point, 2—Mongolian (Reserve) Port, 3—Caleta Argentina. Map outlines are based on OpenStreetMap© contributors (www.openstreetmap.org), edited and arranged using Adobe Illustrator© and Adobe Photoshop®. Scale bars = 35 km (A); 2 km (B).
SNOWPACK simulations for Thwaites Cavity and Channel AMIGOS sites in West Antarctica
<p>Compressed zip file, containing the SNOWPACK model simulations used in the manuscript: Maclennan, M. L., Lenaerts, J. T. M., Shields, C. A., Hoffman, A. O., Wever, N., Thompson-Munson, M., Winters, A. C., Pettit, E. C., Scambos, T. A., and Wille, J. D.: <em>Climatology and Surface Impacts of Atmospheric Rivers on West Antarctica</em>, The Cryosphere Discuss. [preprint], https://doi.org/10.5194/tc-2022-101, in review, 2022.</p> <p>MeteoIO and SNOWPACK are software published under the GNU LGPLv3 license by the WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland at <a href="https://gitlabext.wsl.ch/snow-models">https://gitlabext.wsl.ch/snow-models</a>. The repository used to develop the versions of MeteoIO and SNOWPACK used in this study can be accessed at <a href="https://github.com/snowpack-model/snowpack">https://github.com/snowpack-model/snowpack</a> (<a href="https://doi.org/10.5281/zenodo.3891845">doi: 10.5281/zenodo.3891845</a>) with the exact version corresponding to commit 149c586 (doi: <a href="https://doi.org/10.5281/zenodo.7331794">10.5281/zenodo.7331794</a>).</p> <p>The workflow consists of two phases. First, using MERRA-2 reanalysis as forcing, a spinup is performed for the MERRA-2 grid point closest to the AMIGOS weather stations Channel (CHA) and Cavity (CAV).</p> <p>To perform the spinup:</p> <ol> <li>navigate to the <code>./simulations_spinup/</code> directory</li> <li>edit the following line in the file <code>spinup.rc</code>, to modify the path where the time_shift_script can be found: <code>time_shift_script="/path/to/snowpack/Source/snowpack/tools/timeshift_sno_files.sh"</code> This script can be found in the SNOWPACK repository.</li> <li>Execute the two SNOWPACK spinup simulations specified below. Change the path to point to the SNOWPACK binary executable. The simulations are performed for the two sites, which use the same meteorological forcing, but have a different end date specified for the simulation (corresponding to the installation date of the AMIGOS weather station):</li> </ol> <pre><code class="language-bash">bash spinup.sh "/path/to/usr/bin/snowpack -c cfgfiles/THWAITES_CAV.ini -e 2020-01-10T01:00 > log/THWAITES_SPINUP.log 2>&1" startover=1 bash spinup.sh "/path/to/usr/bin/snowpack -c cfgfiles/THWAITES_CHA.ini -e 2020-01-16T01:00 > log/THWAITES_SPINUP.log 2>&1" startover=1</code></pre> <p>Brief overview of the files in the <code>simulations_spinup</code> directory:</p> <ul> <li><code>base.ini</code>: SNOWPACK settings shared by all simulations</li> <li><code>spinup.ini</code>: Specific settings used when the spinups are being performed</li> <li><code>final.ini</code>: Specific settings used when the final simulation is being performed, after the spinup has completed</li> <li><code>spinup.rc</code>: Specific spinup settings imported by the <code>spinup.sh</code> script</li> <li><code>spinup.sh</code>: bash script to perform spinups</li> <li><code>cfgfiles/THWAITES_CAV.ini</code>: Specific model settings for the Cavity site. This <code>*.ini</code> file is specified to SNOWPACK, and it directs to include other <code>*ini</code> files.</li> <li><code>cfgfiles/THWAITES_CHA.ini</code>: Specific model settings for the Channel site. This *.ini file is specified to SNOWPACK, and it directs to include other <code>*ini</code> files.</li> <li><code>current_snow/THWAITES.sno</code>: <code>*.sno</code> file used for the restarts within the spinup procedure</li> <li><code>log</code>: directory to store simulation logs. Note that in the commands above, we redirect <code>stdout</code> and <code>stderr</code> to files in this directory</li> <li><code>output</code>: directory to store model outputs. See SNOWPACK documentation for more details. <code>*.smet</code> and <code>*.pro</code> files can be visualized using <a href="https://niviz.org">NiViz</a></li> <li><code>smet</code>: directory to store the meteorological forcing data for the simulations</li> <li><code>snow_init/THWAITES.sno</code>: initial <code>*.sno</code> files used to start the spinup</li> </ul> <p><br> To perform the final simulations, covering the atmospheric river period:</p> <ol> <li>navigate to the <code>./simulations_final/</code> directory</li> <li>execute a snowpack simulation for each <code>*.ini</code> file in the <code>cfgfiles</code> directory:</li> </ol> <pre><code class="language-bash">for f in cfgfiles/*ini do /path/to/usr/bin/snowpack -c ${f} -e NOW done</code></pre> <p>The following simulations will be performed:</p> <table> <tbody> <tr> <td><strong>cfgfiles/*ini file:</strong></td> <td><strong>Label output files</strong></td> <td><strong>Mode</strong></td> <td><strong>AMIGOS AWS</strong></td> <td><strong>Parameters from AMIGOS AWS</strong></td> <td><strong>Reanalysis</strong></td> <td><strong>Parameters from reanalysis</strong></td> </tr> <tr> <td>THWAITES_CAV_ERA5.ini</td> <td>THWAITES_ERA5_HSDRIVEN_CAV_ERA5</td> <td>Snow height driven</td> <td>Cavity</td> <td>TA RH VW HS</td> <td>ERA5</td> <td>ILWR ISWR</td> </tr> <tr> <td>THWAITES_CAVHS_ERA5.ini</td> <td>THWAITES_ERA5_HSDRIVEN_CAVHS_ERA5</td> <td>Snow height driven</td> <td>Cavity</td> <td>HS</td> <td>ERA5</td> <td>TA RH VW ILWR ISWR</td> </tr> <tr> <td>THWAITES_CHA_ERA5.ini</td> <td>THWAITES_ERA5_HSDRIVEN_CHA_ERA5</td> <td>Snow height driven</td> <td>Channel</td> <td>TA RH VW HS</td> <td>ERA5</td> <td>ILWR ISWR</td> </tr> <tr> <td>THWAITES_CHAHS_ERA5.ini</td> <td>THWAITES_ERA5_HSDRIVEN_CHAHS_ERA5</td> <td>Snow height driven</td> <td>Channel</td> <td>HS</td> <td>ERA5</td> <td>TA RH VW ILWR ISWR</td> </tr> <tr> <td>THWAITES_REFCAV_ERA5.ini</td> <td>THWAITES_ERA5_PSUM_CAV_ERA5</td> <td>Precipitation driven </td> <td>Cavity</td> <td> </td> <td>ERA5</td> <td>PSUM TA RH VW ILWR ISWR</td> </tr> <tr> <td>THWAITES_REFCHA_ERA5.ini</td> <td>THWAITES_ERA5_PSUM_CHA_ERA5</td> <td>Precipitation driven </td> <td>Channel</td> <td> </td> <td>ERA5</td> <td>PSUM TA RH VW ILWR ISWR</td> </tr> <tr> <td>THWAITES_CAV_MERRA2.ini</td> <td>THWAITES_MERRA2_HSDRIVEN_CAV_MERRA2</td> <td>Snow height driven</td> <td>Cavity</td> <td>TA RH VW HS</td> <td>MERRA-2</td> <td>ILWR ISWR</td> </tr> <tr> <td>THWAITES_CAVHS_MERRA2.ini</td> <td>THWAITES_MERRA2_HSDRIVEN_CAVHS_MERRA2</td> <td>Snow height driven</td> <td>Cavity</td> <td>HS</td> <td>MERRA-2</td> <td>TA RH VW ILWR ISWR</td> </tr> <tr> <td>THWAITES_CHA_MERRA2.ini</td> <td>THWAITES_MERRA2_HSDRIVEN_CHA_MERRA2</td> <td>Snow height driven</td> <td>Channel</td> <td>TA RH VW HS</td> <td>MERRA-2</td> <td>ILWR ISWR</td> </tr> <tr> <td>THWAITES_CHAHS_MERRA2.ini</td> <td>THWAITES_MERRA2_HSDRIVEN_CHAHS_MERRA2</td> <td>Snow height driven</td> <td>Channel</td> <td>HS</td> <td>MERRA-2</td> <td>TA RH VW ILWR ISWR</td> </tr> <tr> <td>THWAITES_REFCHA_MERRA2.ini</td> <td>THWAITES_MERRA2_PSUM_CAV_MERRA2</td> <td>Precipitation driven </td> <td>Cavity</td> <td> </td> <td>MERRA-2</td> <td>PSUM TA RH VW ILWR ISWR</td> </tr> <tr> <td>THWAITES_REFCAV_MERRA2.ini</td> <td>THWAITES_MERRA2_PSUM_CHA_MERRA2</td> <td>Precipitation driven </td> <td>Channel</td> <td> </td> <td>MERRA-2</td> <td>PSUM TA RH VW ILWR ISWR</td> </tr> </tbody> </table> <p> </p> <p>Brief overview of the files in the <code>simulations_final</code> directory:</p> <ul> <li><code>base.ini</code>: SNOWPACK settings shared by all simulations (identical to <code>base.ini</code> in simulations_spinup directory</li> <li><code>cfgfiles</code>: Specific model settings for each simulation as listed in the table above.</li> <li><code>current_snow</code>: The initial *.sno file containing the initial firn conditions</li> <li><code>final.ini</code>: Settings used by all simulations in this directory</li> <li><code>output</code>: directory to store model outputs. See SNOWPACK documentation for more details. <code>*.smet</code> and <code>*.pro</code> files can be visualized using <a href="https://niviz.org">NiViz</a></li> <li><code>prepare_snowpack.sh</code>: bash script setting up the final simulations after the simulations in simulations_spinup completed. Among others, the code to mark the installation reference layers for the snow depth measurements is included in this script.</li> <li><code>smet</code>: ERA5 and MERRA-2 forcing data, as well as snow height for Cavity and Channel (<code>cavity_hs.smet</code> and <code>channel_hs.smet</code>, respectively) as well as the other meteorological parameters (<code>cavity_meteo.smet</code> and <code>channel_meteo.smet</code>, respectively).</li> </ul> <p> </p> <p><br> Note:<br> Please refer to <a href="https://doi.org/10.15784/601552">doi: 10.15784/601552</a> and <a href="https://doi.org/10.15784/601549">doi: 10.15784/601549</a> for the AMIGOS weather station data</p>
Concentration and spatial variation of atmospheric ice nucleating particles over East Antarctica retrieved from the surface snow
<p>This dataset is the INP concentration in water.</p>
The salinity budget of the Ross Sea continental shelf, Antarctica
<p>This dataset includes the model data used in our paper entitled 'The salinity budget of the Ross Sea continental shelf, Antarctica'.</p>
RACMO2.3p3 monthly SMB, SEB and t2m data for Antarctica (1979-2018)
<p>This data set includes RACMO2.3p3 (Rp3) data for Antarctica for various model settings at 27 km resolution. Netcdf files are available for the Greenland settings (GRL), fresh snow grain size settings (FSG), fresh dry snow metamorphism experiment (FSM), refreezing grain size experiment (RFG) and the control experiment (CON), including all changes, as is described in the manuscript 'Impact of radiation penetration on Antarctic surface melt and subsurface snow temperatures in RACMO2.3p3'.</p> <p>Monthly-accumulated (monthlyS) and monthly-averaged (monthlyA) data are available for the surface mass balance (SMB) and 2 m air temperature (t2m) for all experiments and surface energy balance (SEB) for GRL and CON. The data includes the following parameters: snow melt, refreezing, runoff, sublimation (subl), precipitation (precip), surface mass balance (smb), drifting snow erosion (sndiv), sensible heat flux (senf), latent heat flux (latf), shortwave downward radiation (swsd), shortwave upward radiation (swsu), longwave downward radiation (lwsd) and longwave upward radiation (lwsu) / net longwave radiation (lwsn). All output is available between 1979-2018 for GRL and CON; and between 1979-1990 for FSG, FSM and RFG.</p> <p>UPDATE: Added missing month for all monthlyS variables in the CON data set.</p>
The Success of the Montreal Protocol for Climate Mitigation: Antarctica Ozone hole Recovery Perspective
<p>The monitoring of the ozone in the Earth’s atmosphere began in the 1970s due to its absorbing nature of radiation from the Sun, which is harmful to humans and prevents it from reaching the surface of the Earth. However, considerable global attention has been drawn after the finding of the ozone hole, which is associated with a significant drop in total columnar ozone (TCO), specifically a fall in stratospheric ozone (SO) during the spring of 1984. Since then, numerous studies on the Antarctic ozone hole have been conducted following the Vienna Convention and its Montreal Protocol (the ozone treaties) to sustain the ozone layer. In response to this, the Montreal Protocol was developed under the umbrella of the United Nations Environment Programme (UNEP) to protect the thinning of the ozone layer. With 197 participating nations, it is a substantial step toward universal ratification. </p> <p>Towards this, the present study utilized TCO data from the National Aeronautics and Space Administration (NASA)'s Nimbus-7/Total Ozone Mapping Spectrometer (TOMS), TOMS-Earth Probe, and Aura/Ozone Monitoring Instrument (OMI) sensors at various time periods. Due to the varied spatial resolution of the missions, daily data were resampled to 1˚×1˚ (latitude × longitude) and generated daily unified spatial resolution matrixes.</p> <table> <tbody> <tr> <td> <p><strong>S.No.</strong></p> </td> <td> <p><strong>Parameter</strong></p> </td> <td> <p><strong>Sensor</strong></p> </td> <td> <p><strong>Data Period</strong></p> </td> <td> <p><strong>Resolution in degrees</strong></p> <p><strong>(Latitude </strong><strong>× Longitude)</strong></p> </td> <td> <p><strong>Data Resource</strong></p> </td> </tr> <tr> <td> <p>1</p> </td> <td> <p>Total Columnar Ozone (TCO)</p> </td> <td> <p>NIMBUS-7/TOMS</p> </td> <td> <p>1979-1993</p> </td> <td> <p>1°×1.25°</p> </td> <td> <p> </p> <p>https://earthdata.nasa.gov/</p> </td> </tr> <tr> <td> <p>2</p> </td> <td> <p>TOMS-EP</p> </td> <td> <p>1996-2005</p> </td> <td> <p>1°×1.25°</p> </td> <td> <p> </p> <p>https://earthdata.nasa.gov/</p> </td> </tr> <tr> <td> <p>3</p> </td> <td> <p>AURA/OMI</p> </td> <td> <p>2004-2020</p> </td> <td> <p>0.25°×0.25°</p> </td> <td> <p> </p> <p>https://earthdata.nasa.gov/</p> </td> </tr> <tr> <td> <p>4</p> </td> <td> <p>Ozone Depleting Substances (ODS) emissions</p> </td> <td> <p> </p> <p>1985-2015</p> </td> <td> <p> </p> <p>Global data</p> </td> <td> <p>https://ourworldindata.org</p> </td> </tr> </tbody> </table>
Direct observation and measurements of subglacial deformation in a tunnel beneath Wright Lower Glacier, Antarctica
<p>Photographs and video of a tunnel excavated in the margin of Wright Lower Glacier, Antarctica</p>
Data used in the study: "The impact of landfast sea ice buttressing on ice dynamic speedup in the Larsen-B Embayment, Antarctica" by Surawy-Stepney et al, 2023.
<p>Calving front and sea ice front positions, mean speed and speed trend (pre and post sea ice evacuation) maps, timeseries of ice speed shown on Hektoria, Green, Evans, Crane Glaciers, freeboard and associated uncertainty point data over the Larsen-B Embayment, maps of thickness and bed topography used in the model simulations, basal melt rates over the Scar Inlet, and shapefiles used for the extraction of speed, modelled speed and sensitivity data.</p>
Fig. 5. A in Differential expression after UV-B radiation and characterization of chalcone synthase from the Patagonian hairgrass Deschampsia antarctica
Fig. 5. A) Structural alignment between DaCHS (red) and crystal 4YJY (cyan). The RMSD value was 0.25 Å. B) Molecular dynamics simulation analysis. The MDS was carried out using NAMD software and the trajectory analysis was carried out by using VMD software. C) Proteins' structural stability in the function of RMSD, during 2 ns of MDS. RMSF plots of DaCHS (red) and 4YJY chain A (blue) during MD simulation are compared. The greatest fluctuations are found in the loops region of proteins.
Fig. 1 in Differential expression after UV-B radiation and characterization of chalcone synthase from the Patagonian hairgrass Deschampsia antarctica
Fig. 1. Multiple alignment of amino acids for monocotyledons sequences: H. vulgare HvCHS1 (ID: P26018.1), H. vulgare HvCHS2 (ID: Q96562.1), O. sativa subsp. japonica OsjCHS1(ID: XP_015618054.1), O. sativa subsp. japonica OsjCHS2(ID: XP_015646206.1), O. sativa subsp. indica OsiCHS1 (ID: A2ZEX7.1), Sorghum bicolor SbCHS1(ID: XP_002450874.1), S. bicolor SbCHS2(ID: XP_002450871.1), S. bicolor SbCHS3 (ID: XP_002450875.1), S. bicolor SbCHS4(ID: XP_002450870.1), S. bicolor SbCHS5(ID: XP_002449616.1), S. bicolor SbCHS6 (ID: XP_002450877.1), S. bicolor SbCHS7(ID: XP_002450876.1), Z. mays ZmCHS1 (ID: P24824.1), Z. mays ZmCHS2 (ID: NP_001142246.1). Arrows show active site residues, described for chalcone synthase (Cys 167, Phe 218, His 306 and Asn 339). N-terminal domain and Cterminal domain are shown.
Fig. 4 in Differential expression after UV-B radiation and characterization of chalcone synthase from the Patagonian hairgrass Deschampsia antarctica
Fig. 4. Lineal alignment and secondary structure comparison between DaCHS and the template (code 4YJY). Sequences have a high homology index (92% of sequence identity).
Fig. 3 in Differential expression after UV-B radiation and characterization of chalcone synthase from the Patagonian hairgrass Deschampsia antarctica
Fig. 3. Model of DaCHS structure. The 3D model structure of DaCHS shows 13 β sheets (yellow), 12 α helices (purple) and 8 α helices 310 (blue) and 23 loops. The center core is shown where catalytic residues are positioned. Enlargement of the active site shows the three catalytic residues (Cys 167, His 306 and Asn 339) and the two structural Phe residues (Phe 218, Phe 268). (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Cold-Active Enzyme from Glaciozyma antarctica PI12: In Silico Approach
<p>The input files, structures and datasets utilized to generate the computational results featured in the manuscript titled "Low Temperature Adaptation of Cold-Active Lipase from <em>Glaciozyma antarctica</em> PI12: Insights from Alphafold2 Prediction and Molecular Dynamics Simulation". For further elaboration and specific information, kindly refer to the publication. This research was made possible with the generous support of the Universiti Putra Malaysia.</p>
U-Pb, Lu-Hf, and O in zircon from igneous and sedimentary rocks from the Ellsworth Mountains, West Antarctica
<p>This dataset includes U-Pb, Lu-Hf, and O analyses of zircons from two igneous rocks: sample EHD0701A (79°57'47.43"S, 82°56'58.32"W) and sample EHD0305A (80°03'00.87"S, 82°59'07.91"W). EHD0701A is a foliated porphyritic hornblende micro-diorite, while EHD0305A is a basaltic andesite. Additionally, it contains Lu-Hf and O analyses of detrital zircon grains from ten meta-sedimentary samples: 13EG-01, 13EG-02, EHD2302A, EHD0801A, 13EG-05, EHD1705A, EA6, EAM1001B, 13EG-15, and 13EG-10. The coordinates for these samples and U-Pb data are published in Castillo et al. (2017). Zircon separation and analysis were conducted at the Australian National University in Canberra, Australia.</p> <p>Castillo, P., Fanning, C.M., Fernandez, R., Poblete, F., Hervé, F. 2017. Provenance and age constraints of Paleozoic siliciclastic rocks from the Ellsworth Mountains in West Antarctica, as determined by detrital zircon geochronology. GSA Bulletin 129, 1568-1584.</p>
Data from: Mollusks from the upper Shackleton Limestone (Cambrian Series 2), Central Transantarctic Mountains, East Antarctica
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Data from: Cross-species screening of microsatellite markers for individual identification of snow petrel Pagodroma nivea and Wilson’s storm petrel Oceanites oceanicus in Antarctica
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Species distribution, hybridization and connectivity in the genus Chionodraco: unveiling unknown icefish diversity in Antarctica
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Data from: Hybridization of Southern Hemisphere blue whale subspecies and a sympatric area off Antarctica: impacts of whaling or climate change?
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Data from: Extinction and recolonization of maritime Antarctica in the limpet Nacella concinna (Strebel, 1908) during the last glacial cycle: toward a model of Quaternary biogeography in shallow Antarctic invertebrates
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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.