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346 results for “Ship”
PolarFront cruise 2023-08 ship logs from Helmer Hanssen
<p><strong>PolarFront 2023-08 ship logs</strong> </p><p>Original (ISO 8859-1 encoded) text files from the ship logger on Helmer Hanssen.</p>
Raw stable water isotope measurements in water vapour at 8 m a.s.l. on the port side of the ship, made in the austral summer of 2016/2017 during the Antarctic Circumnavigation Expedition (ACE).
<p><strong>Dataset abstract</strong></p> <p>This dataset includes the raw data of stable water vapour isotope (δ18O, δ2H, deuterium excess) and water vapour mixing ratio measurements at a height of approximately 8 meters above sea level taken in the Southern Ocean during the Antarctic Circumnavigation Expedition (ACE) from November 2016 to April 2017 using a Picarro laser spectrometer L2120 mounted on the port side of the ship. The spectrometer was operated throughout the whole expedition. This data has to be calibrated using the calibration runs and applying an appropriate calibration procedure following the IAEA guide lines.</p> <p>Two similar datasets also measuring stable water isotopes (SWIs) in water vapour were collected during the same expedition and can be distinguished from this dataset due to the height of the measurement collection (at 8 m a.s.l and 13.5 m a.s.l). The three ACE datasets of SWIs in water vapour are described and compared in Thurnherr et al. (2020).</p> <p><strong>Dataset contents</strong></p> <ul> <li>leg*/HBDS2190-yyyymmdd-hhmmssZ-DataLog_User.dat, data file, comma-separated values</li> <li>data_file_header.txt, metadata, text format</li> <li>README.txt, metadata, text format</li> </ul> <p><strong>Dataset license</strong></p> <p>This raw stable water isotope measurements dataset is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full description can be found at https://creativecommons.org/licenses/by/4.0/</p> <p><strong>Dataset citation</strong></p> <p>Please cite this dataset as:<br> Kozachek, A. (2020). Raw stable water isotope measurements in water vapour at 8 m a.s.l. on the port side of the ship, made in the austral summer of 2016/2017 during the Antarctic Circumnavigation Expedition (ACE). (Version 1.0) [Data set]. Zenodo.</p>
Calibrated data of stable water isotope measurements in water vapour at 8 m a.s.l. on the starboard side of the ship, made in the austral summer of 2016/2017 around the Southern Ocean during the Antarctic Circumnavigation Expedition.
<p><strong>Dataset abstract</strong></p> <p>This data set includes the calibrated data of stable water vapour isotope (δ18O, δ2H, deuterium excess) and water vapour mixing ratio measurements at approximately 8 m a.s.l. on the starboard of the ship, taken around the Southern Ocean during the Antarctic Circumnavigation Expedition (ACE) from February to March 2017 using a Picarro laser spectrometers L2130-i. The data provide continuous timelines of atmospheric water vapour properties in the marine boundary layer for studies of the atmospheric water cycle.</p> <p>The raw data from which this calibrated dataset originates has been published separately (Kozachek, 2020; DOI 10.5281/zenodo.3667535).</p> <p>Two other calibrated stable water isotope measurement datasets were also collected during ACE. They differ by the location of measurement on the ship: 8 m a.s.l on the port side (DOI: 10.5281/zenodo.3739354) and 13.5 m a.s.l (DOI 10.5281/zenodo.3250790).</p> <p><strong>Dataset contents</strong></p> <ul> <li>ACE_watervapour_isotopes_SWI8-sb_1h.csv, data file, comma-separated values</li> <li>ACE_watervapour_isotopes_SWI8-sb_5min.csv, data file, comma-separated values</li> <li>cal_runs_SWI8-sb.csv, metadata, comma-separated values</li> <li>cal_flag_times_SWI8-sb.csv, metadata, comma-separated values</li> <li>data_file_header.txt, metadata, text format</li> <li>README.txt, metadata, text format</li> </ul> <p>NaN values denote missing values which occur because of e.g., maintenance, instrument calibration, large cavity variations.</p> <p><strong>Dataset license</strong></p> <p>This calibrated stable water isotope measurements in water vapour is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p>
EPITOME ship emissions: Projections of shipping emissions towards 2050.
<p>As part of the EPITOME project, we have setup global shipping emission scenarios. They are based on a combination of the global CO<sub>2</sub> ship emission inventory for 2015 produced with the Ship Traffic Emissions Assessment Model (STEAM) (Johansson et al., 2017) and Arctic fuel consumption and emission scenarios calculated with the DCE ship emission model (Winther et al., 2017).</p> <p>The scenarios include a Baseline scenario, a SO<sub>x</sub> Emission Control Area (SECA) and a heavy fuel oil (HFO) ban scenario. The Baseline scenario is calculated in two variants involving Business As Usual (BAU) and High Growth (HiG) traffic growths. The SECA and HFO ban scenarios are given with the BAU traffic development.</p> <p>Additionally a Polar route scenario is included, with new (diversion) ship traffic routes in the future Arctic with less sea ice. The applied traffic growths and the polar routes are Corbett et al. (2010).</p> <p>The emissions are monthly on a spatial resolution of 0.1º×0.1º. </p> <p>Base year is 2015 and the scenarios are for 2050.</p> <p>A scientific paper providing details on the methodology behind these data will be submitted to ACPD (Geels et al, submitted). In this paper we apply the data to assess the contribution from shipping emissions to air pollution in the Nordic and Arctic area and the potential benefits of the mitigation options included in the shipping emission scenarios. This paper should be referenced if the data is used. </p> <p>The data are given as netcdf files for a number of components. The emission related to the diversion routes is given as a separate field and can be added the other field. <br> </p>
Model simulation data used in "The global impact of the transport sectors on atmospheric aerosol in 2030 – Part 1: Land transport and shipping" (Righi et al., Atmos. Chem. Phys., 2015)
<p>This dataset contains the output of the EMAC global model simulations analysed and discussed in Righi et al. (<i>Atmos. Chem. Phys.</i>, 2015). For details see the README.md file.</p>
Outer Port of Punta Langosteira (Spain) ship movement dataset: 2021 - 2022
<p>This dataset contains the movements of 21 ships recorded in the Outer Port of Punta Langosteira (A Coruña, Spain) from 2021 until 2022.</p>
10-day backward trajectories from ECMWF analysis data along the ship track of the Antarctic Circumnavigation Expedition in austral summer 2016/2017.
<p><strong>Dataset abstract</strong></p> <p>This dataset contains 10-day backward trajectories along the ship track of the Antarctic Circumnavigation Expedition from Nov 2016 – April 2017 calculated with the Lagrangian analysis tool LAGRANTO using the 3D-wind fields from the European Centre for Medium Range Weather Forecasts (ECMWF) operational analysis data. The trajectories were started from up to 56 vertical levels between 0 and 500 hPa a.s.l. and various variables were interpolated along the trajectories.</p> <p><strong>Dataset contents</strong></p> <ul> <li>trajs_ACE.zip: lsl_${year}${month}${day}_${hour}, trajectory files (containing all trajectories starting at ${year}${month}${day} ${hour}UTC at the ACE track from different vertical levels), comma-separated values</li> <li>fig_map.zip: map_long10_${year}${month}${day}_${hour}.png, map plots of all trajectories starting at ${year}${month}${day} ${hour}UTC coloured by pressure, portable network graphics</li> <li>fig_cross.zip: cross10_q_${year}${month}${day}_${hour}.png, cross-section plots of all trajectories starting at ${year}${month}${day} ${hour}UTC coloured by specific humidity, portable network graphics</li> <li>data_file_header.txt, metadata for lsl-files, text</li> <li>README.txt, metadata, text</li> </ul> <p><strong>Dataset license</strong></p> <p>This 10-day backward trajectory dataset from ACE is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p>
Metabomatching: Using Genetic Association to Identify Metabolites in Proton NMR Spectroscopy. SHIP Pseudospectra.
<p>Summary statistics between urine NMR metabolome features and genotypes in the SHIP cohort. Used as test pseudospectra for metabomatching, a method for metabolite identification using genetic spiking.</p>
Interagency Ecological Program: Discrete dissolved oxygen monitoring in the Stockton Deep Water Ship Channel, collected by the Environmental Monitoring Program, 1997-2018
Dissolved oxygen levels in the Stockton Deep Water Ship Chanel (SDWSC) have been monitored since 1968 by the Interagency Ecological Program's (IEP) Environmental Monitoring Program (EMP). The SDWSC is located on the San Joaquin River near Stockton, California. Beginning in 1997, 14 stations were routinely monitored typically in summer and fall. Dissolved oxygen impairment can occur in the SDWSC; therefore, two water quality objectives were established. The objectives of the dissolved oxygen monitoring study in the SDWSC are to: (1) determine if dissolved oxygen levels comply with the water quality objectives, (2) monitor long term trends, and (3) detect and document changes along the SDWSC. The EMP collects discrete dissolved oxygen readings near the surface and bottom of the water column during ebb slack tide. The 14 stations are located between Prisoner's Point on the San Joaquin River and ends at the terminus of the channel called Turning Basin. The site locations were selected at the channel markers on the San Joaquin River; therefore, may be referred as station number or channel marker they are located at. Dissolved oxygen and water temperature were recorded 1-meter below surface and 1-meter above the bottom of the channel. Over the period of record the following water quality parameters have been added: water temperature, specific conductance, pH, fluorescence, turbidity, secchi disk and a rating score for the blue-green algae, Microcystis aeruginosa.
CCE LTER process cruise, in the California Current region, event log records including date, time, position and activity for use in post-cruise data integration based on co-sampling indexes. From 2006 to 2019 CCE LTER used a locally developed event logging system. During P2107, CCE LTER started to utilize the R2R Event Logger on UNOL ships, 2006 - 2024 (ongoing).
The event logger program developed and maintained by the California Cooperative Oceanic Fisheries Investigations, SIO, program is used aboard CCE LTER process cruises to create indexes with temporal, spatial and activity information for post-cruise data integration. The event log is configured aboard the ship for the recording of sampling events by both ship crew personnel on the bridge, and research personnel in the lab. The event log is processed post-cruise to correct for various errors.
Impact of urban and shipping emissions on NASA-Unified Weather Research and Forecasting model results
<p>This dataset supports Huang et al. (2019, JGR-Atmospheres): "Impact of aerosols from urban and shipping emission sources on terrestrial carbon uptake and evapotranspiration: a case study in East Asia". The file named "NUWRFout.tar.gz" contains NUWRF base and sensitivity simulation results on 31 May 2016. The file named "LIS_soil_LAI.zip" contains model grid information, soil conditions and leaf area index (LAI) at NUWRF initialization times in late May 2016.</p>
Five-minute average cruise track and ship velocity of the Antarctic Circumnavigation Expedition (ACE) undertaken during the austral summer of 2016/2017.
<p><strong>Dataset abstract</strong></p> <p>The ship's cruise track, velocity, course over ground and heading at one-minute resolution for all five legs of the Antarctic Circumnavigation Expedition (ACE) are derived from a combination of:<br> - the latitude/longitude record of the Quality-checked, one-second cruise track for 21.12.2016 to 11.04.2017.<br> - the latitude/longitude record of the Uncorrected inertial navigation dataset (one-second resolution) for 27.11.2016 to 21.12.2016<br> - the latitude/longitude record of the raw meteorological data (30-second resolution) from 17.11.2016 to 27.11.2016<br> - where no latitude/longitude record at one-second resolution is available and the ship's velocity was above 2 meters per second, the three-second resolution record of the true and relative wind speed and direction, as well as the heading are used to re-calculate the ship's velocity under the assumption that the course of the ship equalled the heading.</p> <p>Basic filtering are applied to remove erroneous observations before the data are averaged to a one-minute resolution (DOI: 10.5281/zenodo.3752667).<br> The one-minute time series are averaged to five-minute resolution, whereby the vector averaging is used for the platform velocity and orientation.<br> For the latitude and longitude coordinates a simple average is calcualted, i.e., ignoring the curvature of the Earth.<br> Short stretches of missing coordinates are filled with linear interpolation between neighbouring observations.</p> <p><strong>Dataset contents</strong></p> <ul> <li>cruise-track-5min-legs0-4.csv, data file, comma-separated values</li> <li>data_file_header, metadata, text format</li> <li>README.txt, metadata, text format</li> <li>ace-cruise-track-5min-legs0-4-change-log.txt, metadata, text format</li> </ul> <p><strong>Change log</strong></p> <p><strong>v1.1</strong> - Added additional data coverage from 2016-11-17 - 2016-11-22 inclusive. Updated README.txt with information about data coverage. Added this change_log file.</p> <p><strong>v1.0</strong> - Initial release of averaged cruise track data set.</p> <p><strong>Dataset license</strong></p> <p>This five-minute averaged cruise track and velocity dataset is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p>
GO-SHIP Easy Ocean: Formatted and gridded ship-based hydrographic section data
<p><a href="https://www.go-ship.org">GO-SHIP</a> (The Global Ocean Ship-based Hydrographic Investigations Program) has developed the protocols and methods to generate a data product that concatenates all occupations of individual sections into a time-series; the GO-SHIP Easy Ocean. Here we provide access to the analysis-ready gridded GO-SHIP Easy Ocean product that enhances the accessibility of this unique data set that spans four decades, comprised of more than 40 cross-ocean transects, many with multiple repeats.</p> <p>This product, of uniformly calibrated CTD (temperature, salinity and oxygen) data, provides easy access to and use of the high-quality hydrographic temperature and salinity data that span more than 40 years. The GO-SHIP Easy Ocean product will underpin the quality control of autonomous platforms, provide a ready assessment of ocean-only and coupled climate model simulations, and be used in specific research projects. The GO-SHIP Easy Oceanis a companion to the GLODAP inorganic and carbon product. The section data are available from Zenodo in two standard arrangements: Uninterpolated (reported) and interpolated (gridded). For both arrangements, five quantities are recorded; in situ temperature in ITS-90 scale, in situ salinity in PSS-78 scale, the dissolved oxygen concentration in μmol/kg, Conservative Temperature in °C, and Absolute Salinity in g/kg. The data are available in various formats.</p> <p>Cite <a href="https://doi.org/10.1038/s41597-022-01212-w">Katsumata et al (2022)</a> when using this product and include the following acknowledgment statement in any publication or derived product:</p> <p><em>Data were collected and made publicly available by the International Global Ship-based Hydrographic Investigations Program GO-SHIP (https://www.go-ship.org/) and the national programs that contribute to it.</em></p>
Properties of identified ship tracks
<p>The ship track database of is used, which used "day microphysics" images comprised of a composite of visible, near and thermal infrared channels were used to manually locate likely positions of ship tracks. Identification was assisted by examining the CDNC, calculated from the MYD06 level 2 cloud retrieval products from Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua satellite. The CDNC is calculated based on the adiabatic assumption, using the cloud optical depth and cloud effective radius from the MODIS MYD06 level 2 product.</p><p>Ship locations were sourced from their automatic identification system (AIS) data, allowing an observed ship track to be linked to the generating ship. Local meteorology was gathered from the European Centre for Medium-Range Weather Forecasts ERA5 reanalysis data, and ships mass emission rates were calculated using their specific fuel consumption and estimated drag. </p><p>Data labels:</p><ul><li>trackno: Ship track identifier (-)</li><li>sox: SO emission rate (kg s^-1)</li><li>cbh: Cloud base height (m)</li><li>blh: Boundary layer height (m)</li><li>cth: Cloud top height (m)</li><li>spd_res: Relative velocity between ship velocity and wind velocity (m s^-1)</li><li>nd_cln: Background cloud droplet number concentration (cm^-3)</li><li>nd_pol: Ship track cloud droplet number concentration (cm^-3)</li><li>cf_liq: Liquid cloud fraction (-)</li><li>lwp: Liquid water path (g m^-2)</li><li>t1000: Temperature at 1000 hPa (K)</li><li>LTS: Low tropospheric stability (K)</li><li>ctt: Cloud top temperature (K)</li><li>ctrc: Cloud top radiative cooling (W m^-2)</li><li>is_coupled: Flag for cloud coupling according to cloud base height indicator (cbh<1000 m)</li></ul>
Ship logs from ARCTOS Barents Sea Polar Front 2021-05 cruise
<p>PolarFront 2021-05 ship logs. Original (ISO 8859-1 encoded) text files from the ship logger on Helmer Hanssen.</p>
Underwater noise from ships during 2014-2020
<p>These data accompany the manuscript "Underwater noise emissions from ships during 2014-2020" submitted for publication in Environmental Pollution. These data consist of daily emissions of underwater noise emissions from global shipping, reported as noise energy in Joules, in three frequencies (63, 125 and 2000 Hz). The data is provided in zip compressed gridded binary netcdf3 data format using Climate & Forecast conventions. </p>
Underwater noise from ships during 2014-2020
<p>These data accompany the manuscript "Underwater noise emissions from ships during 2014-2020" submitted for publication in Environmental Pollution. These data consist of daily emissions of underwater noise emissions from global shipping, reported as noise energy in Joules, in three frequencies (63, 125 and 2000 Hz). The data is provided in zip compressed gridded binary netcdf3 data format using Climate & Forecast conventions. <br> </p>
High temporal and spatial resolution emission inventory for maritime shipping emissions on the North Sea and Baltic Sea (2015)
<p>A temporally and spatially highly resolved emission inventory for the North Sea and Baltic Sea for the year 2015, created with current emission factors and ship activity data. The emissions inventory is available as 396 csv files, one for each day in 2015 and December 2014, grouped as monthly archives. </p> <p><strong>Note that due to the underlying ship activity data and the geographic boundaries, the time index in the <em>Datetime </em>column in the <em>ship_emissions_YYYYMMDD.csv</em> files is not equidistant.</strong> For example, since vessels leave the geographic area and reenter later, no data is available for the time the vessel is not within the area.</p> <p>The underlying model source code is available on Github, with a release of the associated version on Zenodo: [](https://doi.org/10.5281/zenodo.6951672)</p> <p> </p>
Dataset related to the Journal Article 'A deep learning method for the prediction of ship fuel consumption in real operational conditions'
<p>This dataset contains the data used to plot the graphs and create tables corresponding to the figure/table number in the published version of the paper.<br>Paper DOI:https://doi.org/10.1016/j.engappai.2023.107425</p> <p> </p>
MSSWD - Multi-Spectral Ship Wake Dataset
<p>The <strong>Multi-Spectral Ship Wake Dataset (MSSWD)</strong> is a dataset designed for ship wake detection in multi-spectral satellite imagery. It is structured as follows:</p> <p>- <strong>Source</strong>: 661 image chips derived from 50 Sentinel-2 images, captured by the Multi-Spectral Instrument (MSI) at 10-meter resolution across the visible, near-infrared (VNIR), and short-wave infrared (SWIR) spectral bands. The chips come already pre-processed to highlight sea surface features by using a Contrast Limited Adaptive Histogram Equalization (CLAHE) technique. <br> <br>- <strong>Content</strong>: The dataset includes 1059 ship wakes, with various configurations such as:<br> - Single ship wakes<br> - Multiple ship wakes<br> - False wakes (e.g., airplane wakes, sea crests)<br> - Sea clutter with no visible wakes</p> <p>- <strong>Wake Characteristics</strong>: Diverse patterns of ship wakes are captured, including:<br> - Vertical, horizontal, and tilted wakes<br> - Cluttered sea scenes<br> - Partial occlusions due to cloud cover</p> <p>- <strong>Data Quality</strong>: Focused on <em>quality over quantity</em>, MSSWD reflects real-world complexity by collecting data in congested, crowded maritime environments.</p> <p>- <strong>Data Labelling</strong>: Manually annotated using polygonal annotations to delineate wake contours, which allows:<br> - Instance segmentation<br> - Enhanced refinement during data augmentation</p>
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