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10,391 results for “oceans”
Hydrolysable carbohydrate data collected from the trace metal rosette in the Southern Ocean during the austral summer of 2016/2017, on board the Antarctic Circumnavigation Expedition.
<p><strong>Dataset abstract</strong></p> <p>Hydrolysable carbohydrate (referred to as TPZT from the analytical methodology used) is part of the labile pool of dissolved organic carbon that is excreted by most (micro)organisms or released by continental margins/sediments. It is a carbon source for heterotrophic bacteria. These carbohydrates could also potentially bind iron and act as an iron binding ligand.</p> <p>This data is used to explore the nature of iron ligands and relate to biological and chemical oceanography.</p> <p><strong>Dataset contents</strong></p> <ul> <li>ace_hydrolysable_carbohydrates_tpzt_data.csv, data file, comma-separated values</li> <li>ace_hydrolysable_carbohydrates_tpzt_data_visual_summary.png, metadata, portable network graphics</li> <li>README.txt, metadata, text format</li> <li>data_file_header.txt, metadata, text format</li> <li>change_log.txt</li> </ul> <p><strong>Dataset license</strong></p> <p>This hydrolysable carbohydrate 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> <p><strong>Change log</strong></p> <p>v1.1 - permissions changed to open access (CC BY 4.0 license) and small changes</p> <ul> <li>add license to README.txt</li> <li>format of data_file_header.txt</li> <li>add Frictionless Data schema files</li> </ul> <p>v1.0 - initial release of dataset</p>
Northwest Europe NEMO-ERSEM ocean model hindcast and climate projection under RCP8.5
<p>Dataset of model hindcast and climate projection data from a NEMO-ERSEM simulation of the 7km-resolution Atlantic Margin Model (AMM7). Model description and data are presented in </p> <p>Wakelin, S. L., Y. Artioli, J. T. Holt, M. Butenschön, and J. Blackford (2020), Controls on near-bed oxygen concentration on the Northwest European Continental Shelf under a potential future climate scenario, Progress in Oceanography, 102400. doi: https://doi.org/10.1016/j.pocean.2020.102400.</p> <p>Coupled NEMO-ERSEM model simulations are used to study temperature, salinity and near-bed oxygen concentrations on the northwest European Continental Shelf (NWES). Data are from a hindcast (1980 to 2007) and a climate projection (1980 to 2099) under the RCP8.5 climate emissions scenario.</p> <p>The climate projection (1980 to 2099) under the RCP8.5 climate emissions scenario is described as experiment E1 in</p> <p>Holt, J., J. Polton, J. Huthnance, S. Wakelin, E. O'Dea, J. Harle, A. Yool, Y. Artioli, J. Blackford, J. Siddorn, and M. Inall (2018), Climate-Driven Change in the North Atlantic and Arctic Oceans Can Greatly Reduce the Circulation of the North Sea, Geophysical Research Letters, 45(21), 11,827-811,836. doi: 10.1029/2018gl078878.</p> <p>The dataset consists of </p> <ul> <li>Hindcast simulation data</li> </ul> <ol> <li>AMM7_hindcast_3D_S_1980_2007.nc - monthly mean salinity fields.</li> <li>AMM7_hindcast_3D_T_1980_2007.nc - monthly mean temperature fields.</li> <li>AMM7_hindcast_near_bed_O2o_1980_2007.nc - near-bed oxygen concentrations on the NWES.</li> </ol> <ul> <li>Climate projection data</li> </ul> <ol> <li>AMM7_RCP8_5_3D_S_1980_2099.nc - monthly mean salinity fields.</li> <li>AMM7_RCP8_5_3D_T_1980_2099.nc - monthly mean temperature fields.</li> <li>AMM7_RCP8_5_3D_U_1980_2099.nc - monthly mean eastwards currents.</li> <li>AMM7_RCP8_5_3D_V_1980_2099.nc - monthly mean northwards currents.</li> <li>AMM7_RCP8_5_near_bed_1980_2099.nc - monthly mean near-bed oxygen concentrations and near-bed bacterial respiration on the NWES.</li> <li>AMM7_RCP8_5_netPP_1980_2099.nc - monthly mean depth integrated net primary production.</li> </ol>
Atmospheric profiling data collected from radiosondes in the Southern Ocean in the austral summer of 2016/2017 during the Antarctic Circumnavigation Expedition.
<p><strong>Dataset abstract</strong></p> <p>The data set consists of the vertical profiles of the atmospheric variables measured using radiosondes (i-Met) during the Antarctic Circumnavigation Expedition from November 2016 to April 2017. The data include the raw variables measured directly by the radiosondes and derived parameters: altitude (km), air pressure (mb), air temperature (ºC), relative humidity (%), frostpoint (ºC), potential temperature (ºK), water vapour mixing ratio (ppmv), total column water (mm w.e.), wind speed (m/s) and wind direction (deg).</p> <p><strong>Dataset contents</strong></p> <ul> <li>aceNNN_yyyymmdd, directory <ul> <li>aceNNN_yyyymmdd.csv, data file, comma-separated values</li> <li>aceNNN_yyyymmdd.kml, metadata, XML</li> <li>aceNNN_yyyymmdd.raw, data file, raw, ASCII DOS</li> <li>aceNNN_yyyymmdd.raw_config, metadata, XML</li> <li>aceNNN.de1, metadata, ASCII text format</li> <li>aceNNNflt.dat, data file, ASCII text format</li> <li>aceNNNpre.dat, data file, ASCII text format</li> </ul> </li> <li>plots, directory <ul> <li>Sounding_ACENNN.png, metadata, portable network graphics</li> </ul> </li> <li>data_file_header_csv.txt, metadata, text format</li> <li>data_file_header_dat.txt, metadata, text format</li> <li>data_file_header_launches.txt, metadata, text format</li> <li>README.txt, metadata, text format</li> <li>overview_radiosonde_launches.csv, metadata, comma-separated value</li> </ul> <p>where NNN is the launch number yyyy is the year, mm is the month and dd is the day. Dates are in UTC.</p> <p>json files make up a Frictionless Data package.</p> <p><strong>Dataset citation</strong></p> <p>Please cite this dataset as:</p> <p>Gorodetskaya, I.V., Thurnherr, I., Tsukernik, M., Graf, P., Aemisegger, F., Wernli, H. and Ralph, F.M. (2021). Atmospheric profiling data collected from radiosondes in the Southern Ocean in the austral summer of 2016/2017 during the Antarctic Circumnavigation Expedition. (Version 1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.4382460</p>
Accessible Oceans: Auditory Display. Ocean Response to Extratropical Storm Hermine
<p>The twenty-one tracks make up an auditory display of the ocean response to extratropical storm Hermine in 2016. The tracks in the auditory display are comprised of data sonifications and contextual audio supports (dialogue, auditory icons, and music). You may <a href="https://samply.app/p/VGWHypmrFPZ1NqzeqZuM">listen online here</a>.</p> <p>The ocean data comes from the National Science Foundation (NSF) Ocean Observatories Initiative (OOI) and the display is based on the <a href="https://datalab.marine.rutgers.edu/ooi-nuggets/extratropical-storm-hermine/">OOI Nugget</a> developed by Dr. Leslie Smith. Please note that the Ocean Labs data nugget does not include sea wave height as part of its graph that we sonified. Storms also impact sea wave height, and Dr. Leslie Smith acquired this data from the OOI so that we could include it in the sonification and auditory display.</p> <p>The “Accessible Oceans” AISL Pilots and Feasibility study aims to inclusively design auditory displays that support the perception and understanding of ocean data in informal learning environments (ILEs). More can be found on the project website: <a href="https://accessibleoceans.whoi.edu/">https://accessibleoceans.whoi.edu/</a></p>
JasonAlongTrack: A reformatted version of the Integrated Multi-Mission Ocean Altimeter Data for Climate Research Version 5.1
<p>JasonAlongTrack contains geo-registered along-track sea surface height anomalies with respect to the DTU15 mean sea surface at 1-second intervals from Jason-class altimeters, reformatted for convenience into a 3D array with dimensions of along-track direction by geographically sorted track number by cycle.</p><p>This is a reformatted version of Beckley et al.'s <i>Integrated Multi-Mission Ocean Altimeter Data for Climate Research complete time series Version 5.1</i> dataset, available from <a href="https://podaac.jpl.nasa.gov/dataset/MERGED_TP_J1_OSTM_OST_ALL_V51">https://podaac.jpl.nasa.gov/dataset/MERGED_TP_J1_OSTM_OST_ALL_V51</a>. </p><p>The changes are as follows. Altimeter passes are sorted according to their initial longitude, then split into descending and ascending potions with all descending tracks preceding all ascending tracks. Descending tracks are then flipped so that latitude increases in the alongtrack direction for all tracks. This leads to a 3373 x 254 matrix of observational locations, with the first dimension being the along-track location and the second dimension being the track index. Sea surface height anomaly, time, and flag values are then placed into their correct locations within this matrix, such that these three variables are all of size 3373 x 254 x K where K is the number of cycles, currently 1087. A very good approximation to the time at each of the 3373 x 254 x K observation points is constructed with a length K array of cycles times together with a 3373 x 254 array of time offsets. A median-based editing criterion in introduced to identify a small number of suspect data points. These are set to a value of NaN in sla, but their positions and values are recorded in rejected_index and rejected_values, respectively. The DTU15 mean dynamic topography (mdt) is included, in addition to the mean sea surface field already provided, interpolated onto the track locations using bicubic interpolation. Finally, an estimate of the small-scale noise level, sigma, is produced using a wavelet transform filter.</p>
The Southern Ocean carbon cycle 1985-2018: Mean, seasonal cycle, trends and storage - Data
<p>Postprocessed data set used for RECCAP2 Southern Ocean chapter:</p><p>Hauck, Gregor, et al.: The Southern Ocean carbon cycle 1985-2018: Mean, seasonal cycle, trends and storage</p><p>The raw data is available at: Müller, Jens Daniel. (2023). RECCAP2-ocean data collection [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7990823</p><p>Scripts for plotting are available at https://github.com/RECCAP2-ocean/Southern-Ocean and a frozen version of the scripts is deposited at:</p><p>Judith Hauck, Luke Gregor, Cara Nissen, Lavinia Patara, Mark Hague, & Precious Mongwe. (2023). The Southern Ocean carbon cycle 1985-2018: Mean, seasonal cycle, trends and storage - Scripts. Zenodo. https://doi.org/10.5281/zenodo.10076121</p><p> </p>
Database of local seismicity registered on ocean bottom seismometers (OBS). Database related to Bornstein et al. (accepted in Earth and Space Science), PICKBLUE
<p>We assembled a database of Ocean Bottom Seismometer (OBS) waveforms and manual P and S picks from local seismicity, on which we trained PickBlue, a deep-learning picker, using the seismometer data and the hydrophone channel. The dataset belongs to Bornstein et al. (accepted 2023 in Earth and Space Science). The picker and database are available in the SeisBench platform, allowing easy and direct application to OBS traces and hydrophone records.</p><p>The complete database is also accessible with SEISBENCH: <br><a href="https://seisbench.readthedocs.io">https://seisbench.readthedocs.io</a><br>SEISBENCH on github:<br><a href="https://github.com/seisbench">https://github.com/seisbench</a></p><p>Related paper:</p><p>Bornstein, T., Lange, D., Münchmeyer, J., Woollam, J., Rietbrock., A., Barcheck, G., Grevemeyer, I., Tilmann, F. (accepted 2023 in Earth and Space Science). PickBlue: Seismic phase picking for ocean bottom seismometers with deep learning, Earth and Space Science. </p>
Transparent exopolymer particle (TEP) and Coomassie stainable particle (CSP) data collected from the Southern Ocean in the austral summer of 2016/2017, during the Antarctic Circumnavigation Expedition.
<p><strong>Dataset abstract</strong></p> <p>TEP are operationally defined as gel particles that are retained on 0.4 µm polycarbonate filters and stained with the cationic copper phthalocyanine dye Alcian Blue 8GX at pH 2.5. CSP are gel particles retained on 0.4 µm polycarbonate filters that are stained with a solution of Coomassie Brilliant Blue G (CCB) at pH 7.4. Seawater surface samples (5 m) were collected every 6 hours from the ship’s underway pump. In addition, vertical profiles (6 depths, generally from 5 to 100-150 m) were sampled from 19 CTD casts using a SBE 911 Plus attached to a rosette of 24 12-L PVC Niskin bottles. This dataset presents TEP and CSP from seawater samples collected from the ship’s underway pump and CTDs. Samples were collected around the Southern Ocean on the R/V Akademik Tryoshnikov in the austral summer of 2016/2017, as part of the Antarctic Circumnavigation Expedition (ACE).</p> <p><strong>Dataset contents</strong></p> <ul> <li>ace_seawater_csp.csv, data file, comma-separated values</li> <li>ace_seawater_tep.csv, data file, comma-separated values</li> <li>data_file_header_csp.txt, metadata, text</li> <li>data_file_header_tep.txt, metadata, text</li> <li>README.txt, metadata, text</li> </ul> <p><strong>Dataset license</strong></p> <p>This TEP and CSP 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>
Concentration of gaseous sulfuric acid measured over the Southern Ocean in the austral summer of 2016/2017, during the Antarctic Circumnavigation Expedition (ACE).
<p><strong>Dataset abstract</strong></p> <p>The authors would highly appreciate being contacted if the data is used for any purpose.</p> <p>We measured sulfuric acid concentration in the gas phase with a nitrate chemical ionization mass spectrometer (we used an APi-HTOF mass spectrometer produced by Tofwerk AG coupled with a Chemical ionization inlet A70 produced by Airmodus). Sulfuric acid is detected in the mass spectrometer either as a deprotonated ion or as a cluster with the reagent ion (NO3-). The concentration is calculated as the area of these two peaks normalized to the concentration of the reagent ions (monomer, dimer and trimer) and multiplied by a calibration factor that was experimentally derived at Paul Scherrer Institute in the summer 2017, after the campaign. In the atmosphere, sulfuric acid is produced by the oxidation of sulfur dioxide that could have both a natural or anthropogenic origin (e.g. phytoplankton emission or fossil fuel combustion). Sulfuric acid in the atmosphere is responsible for a very large fraction of the newly formed particles, therefore it is important to have accurate measurements of this vapour in remote places like the Southern Ocean to better understand secondary aerosol sources and processes.</p> <p>The data have been cleaned from the influence of the exhaust of the research vessel. Temporal coverage is from January 22, 2017 to March 19, 2017. There are no data for the first leg of the expedition because the instrument was not on the ship. The instrument was operated during leg 4 but data has not been processed yet as they require additional work due to some instrumental issues that affects their quality. Data were collected with one-second time resolution but integrated to five minutes to increase the signal to noise ratio.</p> <p>Concentrations are reported as molecules per cubic centimeter. The lower limit of detection is in the ppq (part per quadrillion) range but was not determined exactly as it varies with the integration time and background noise.</p> <p><strong>Dataset contents</strong></p> <ul> <li>gas_sulfuric_acid_concentration_data.csv, data file, comma-separated values</li> <li>data_file_header.txt, metadata, text format</li> <li>README.txt, metadata, text format</li> <li>change_log.txt, metadata, text format</li> </ul> <p>Data that were missing or bad because of instrumental problems were simply removed from the file (no entry).</p> <p><strong>Change log</strong></p> <p>v1.1 - data files updated</p> <ul> <li>re-analysis of the raw data with an improved mass spectra peak fitting routine, a different calibration factor was also applied to the data following a more detailed analysis of the calibration experiment</li> <li>use updated, corrected GPS data</li> </ul> <p>v1.0 - initial release of dataset</p>
Concentration of gaseous methanesulfonic acid measured over the Southern Ocean in the austral summer of 2016/2017, during the Antarctic Circumnavigation Expedition (ACE).
<p><strong>Dataset abstract</strong></p> <p>The authors would highly appreciate being contacted if the data is used for any purpose.</p> <p>We measured methanesulfonic acid concentration in the gas phase with a nitrate chemical ionization mass spectrometer (we used an APi-HTOF mass spectrometer produced by Tofwerk AG coupled with a Chemical ionization inlet A70 produced by Airmodus). Methanesulfonic acid is detected in the mass spectrometer either as a deprotonated ion or as a cluster with the reagent ion (NO3-). The concentration is calculated as the area of these two peaks normalized to the concentration of the reagent ions (monomer, dimer and trimer) and multiplied by a calibration factor that was experimentally derived at Paul Scherrer Institute in the summer 2017, after the campaign.</p> <p>In the atmosphere, methanesulfonic acid is produced by the oxidation of dimethyl sulfide that is mostly emitted in the atmosphere by phytoplankton. Methanesulfonic acid can contribute to the growth of aerosol particles by condensation or aqueous phase processing in clouds. The data have been cleaned from the influence of the exhaust of the research vessel. Temporal coverage is from 22 January 2017 to 19 March 2017. There are no data for the first leg of the expedition because the instrument was not on the ship. The instrument was operated during leg 4 but data has not been processed yet as they require additional work due to some instrumental issues that affects their quality. Data were collected with one-second time resolution but integrated to five minutes to increase the signal-to-noise ratio.</p> <p>Concentrations are reported as molecules per cubic centimeter. The lower limit of detection is in the ppq (part per quadrillion) range but was not determined exactly as it varies with the integration time and background noise.</p> <p><strong>Dataset contents</strong></p> <ul> <li>gas_methanesulfonic_acid_concentration_data.csv, data file, comma-separated values</li> <li>data_file_header.txt, metadata, text format</li> <li>README.txt, metadata, text format</li> <li>change_log.txt, metadata, text format</li> </ul> <p>There are no null values in the file. Data that were missing or bad because of instrumental problems were simply removed from the file (no entry).</p> <p><strong>Change log</strong></p> <p>v1.1 - data files updated</p> <ul> <li>re-analysis of the raw data with an improved mass spectra peak fitting routine, a different calibration factor was also applied to the data following a more detailed analysis of the calibration experiment</li> <li>use updated, corrected GPS data</li> </ul> <p>v1.0 - initial release of dataset</p>
Quality-checked horizontal particle flux data collected using a snow particle counter on board the R/V Akademik Tryoshnikov in the Southern Ocean during the austral summer of 2016/17 as part of the Antarctic Circumnavigation Expedition (ACE).
<p><strong>Dataset abstract</strong></p> <p>Flux of particles (snow, rain and other particles including sea spray) were recorded passing through a photo-electric snow particle counter installed on board the R/V Akademik Tryoshnikov as part of the Antarctic Circumnavigation Expedition (ACE). Data were recorded from January to March 2017 in the Southern Ocean. Here we present the finalised, quality-checked, horizontal particle flux data where counts have been averaged over a one-minute period.</p> <p><strong>Dataset contents</strong></p> <ul> <li>SPC_HPF_windtrue_1min.csv, data file, comma-separated values</li> <li>SPC_HPF_windtrue_1min.png, metadata, portable network graphics</li> <li>SPC_HPF_windtrue_saveplot.py, script, Python code</li> <li>data_file_header.txt, metadata, text</li> <li>README.txt, metadata, text</li> </ul> <p><strong>Dataset license</strong></p> <p>This quality-checked horizontal particle flux 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>
Intermediate processing stage of horizontal particle flux data collected using a snow particle counter on board the R/V Akademik Tryoshnikov in the Southern Ocean during the austral summer of 2016/17 as part of the Antarctic Circumnavigation Expedition (ACE).
<p><strong>Dataset abstract</strong></p> <p>Flux of particles (snow, rain and other particles including sea spray) were recorded passing through a photo-electric snow particle counter installed on board the R/V Akademik Tryoshnikov as part of the Antarctic Circumnavigation Expedition (ACE). Data were recorded from January to March 2017 in the Southern Ocean. Here we present an intermediate step in data processing, with relative horizontal particle flux of particles with a size between 36 – 2000 μm averaged over one-minute periods. Data are presented in daily files.</p> <p><strong>Dataset contents</strong></p> <ul> <li>SPC_HPF_1min_YYYY_MM_DD.csv, data files, comma-separated values</li> <li>data_file_header.txt, metadata, text</li> <li>README.txt, metadata, text</li> </ul> <p><strong>Dataset license</strong></p> <p>This one-minute averaged horizontal particle flux 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>
Antarctic Circumnavigation Expedition event log: recording data and sample collection in the Southern Ocean during the austral summer of 2016/17.
<p><strong>Dataset abstract</strong></p> <p>The Antarctic Circumnavigation Expedition (ACE) spent 90 days circumnavigating Antarctica on the R/V Akademik Tryoshnikov during the austral summer of 2016/17. This dataset provides a record of the instrument deployments as well as dataset and sample collection events that took place during the expedition.</p> <p><strong>Dataset contents</strong></p> <ul> <li>ace_events.csv, data file, comma-separated values</li> <li>sampling_method_descriptions.csv, metadata, comma-separated values</li> <li>README.txt, metadata, text</li> <li>data_file_header.txt, metadata, text</li> </ul> <p><strong>Dataset license</strong></p> <p>This event log is made available under a 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> <p> </p>
Data from: Basin-scale biogeochemical and ecological impacts of islands in the tropical Pacific Ocean
<p><strong>Abstract</strong></p> <p>In the relatively unproductive waters of the tropical ocean, islands can enhance phytoplankton biomass and create hotspots of productivity and biodiversity that sustain upper trophic levels, including fish that are crucial to the survival of islands’ inhabit- ants. This phenomenon, termed the island mass effect 65 years ago, has been widely described. However, most studies focused on individual islands, and very few documented phytoplankton community composition. Consequently, basin-scale impacts on phytoplankton biomass, primary production and biodiversity remain largely unknown. Here we systematically identify enriched waters near islands from satellite chlorophyll concentrations (a proxy for phytoplankton biomass) to analyse the island mass effect for all tropical Pacific islands on a climatological basis. We find enrichments near 99% of islands, impacting 3% of the tropical Pacific Ocean. We quantify local and basin-scale increases in chlorophyll and primary production by contrasting island-enriched waters with nearby waters. We also reveal a significant impact on phytoplankton community structure and biodiversity that is identifiable in anomalies in the ocean colour signal. Our results suggest that, in addition to strong local bio- geochemical impacts, islands may have even stronger and farther-reaching ecological impacts.</p> <p> </p> <p><strong>Data set and method</strong></p> <p>For each island, an algorithm detected the Island Mass Effect (IME) from climatological satellite chlorophyll maps as a contour enclosing the island and surrounding high-chlorophyll waters, termed IME region. A reference (REF) region of the same size was detected alongside each IME region, enclosing nearby non-IME waters. The IME and REF regions were used to build the IME database described in Messié et al. (2022), that includes variables related to satellite chlorophyll, primary production, and PHYSAT phenoclass diversity metrics in IME and REF regions on a climatological basis.</p> <p>This data set includes 4 files:</p> <ul> <li>island_database.csv: information regarding the 664 islands and shallow reefs where the IME detection was applied</li> <li>IME_masks.nc: monthly climatological masks for the IME and REF regions for all islands,</li> <li>IME_database.nc: IME database as a function of island and climatological month (chlorophyll, primary production, and phenoclass-derived variables calculated within the IME and REF masks).</li> <li>PHYSAT_climatology.nc: climatological maps for each PHYSAT phenoclass, used to calculate phenoclass-derived variables in the IME database.</li> </ul> <p>See details regarding data sources and calculations in <a href="https://rdcu.be/cO4qr">Messié et al. (2022)</a>.</p>
AMOC reconstruction between 1981 and 2016 from hydrographic data using an empirical linear regression model from Worthington, E. L., Moat, B. I., Smeed, D. A., Mecking, J. V., Marsh, R., and McCarthy, G. D.: A 30-year reconstruction of the Atlantic meridional overturning circulation shows no decline, Ocean Sci., 17, 285–299, https://doi.org/10.5194/os-17-285-2021, 2021.
<p>Dataset used to create Figure 8 in Worthington et al., 2021 (https://doi.org/10.5194/os-17-285-2021). Details of the data and methods can be found in the journal article.<br> <br> Worthington, E. L., Moat, B. I., Smeed, D. A., Mecking, J. V., Marsh, R., and McCarthy, G. D.: A 30-year reconstruction of the Atlantic meridional overturning circulation shows no decline, Ocean Sci., 17, 285–299, <a href="https://doi.org/10.5194/os-17-285-2021">https://doi.org/10.5194/os-17-285-2021</a>, 2021.</p>
Sub-micron aerosol particle size distribution collected in the Southern Ocean in the austral summer of 2016/2017, during the Antarctic Circumnavigation Expedition.
<p><strong>Dataset abstract</strong></p> <p>The authors would highly appreciate to be contacted if the data is used for any purpose.</p> <p>We measured sub-micrometer aerosol particles with two scanning mobility particle spectrometers (SMPSs) between 11 and 400 nm (file name ACESPACE_submicron_aerosol_particle_size_distribution.csv) in 100 bins, and 11 and 181 nm in 77 bins - so no data entry in the remaining 23 bins - (ACESPACE_submicron_aerosol_particle_size_distribution_nano.csv) at a time resolution of five minutes during the Antarctic Circumnavigation Expedition (ACE). Particles in this size range are important for cloud formation because a sub-set of them can act as cloud condensation nuclei (CCN).</p> <p>The time series of the size distribution shows that the particle population over the Southern Ocean can be quite variable featuring three dominant modes: a new particle formation mode (11 – 30 nm); an Aitken mode (20 – 70 nm); and an accumulation mode (> 70 nm). Often a concentration minimum between the Aitken and accumulation mode can be observed. It is known as Hoppel minimum (Hoppel and Frick, 1990; 10.1016/0960-1686(90)90020-N). Typically, particles larger than this minimum act as CCN. The variability of the particle size spectrum is a result of particle sources and atmospheric processes. Sea spray generation adds larger particles likely with a peak in the mode around 200 nm. Trace gas emissions from microbial communities in the ocean, such as dimethylsulfide (DMS) will be oxidized to either sulphuric acid or methanesulfonic acid in the atmosphere which condense onto pre-existing particles, hence growing those. Sulphuric acid can also form new particles (new particle formation mode). Rain and snow will remove particles larger than the Hoppel minimum.</p> <p>The data set can be used to explore the variability of the particle size distribution in three different oceans around Antarctica (Indian, Pacific, Atlantic Oceans) and from Cape Town to Europe in relation to weather patterns, air mass trajectories, microbial activity etc. It is best used in combination with CCN data to explore the importance of particles for cloud formation. This data set cannot be used to unambiguously determine sources of particles over the southern ocean or to trace anthropogenic impact in the region.</p> <p>The data have been cleaned from the influence of the exhaust of the research vessel.</p> <p>We give five-minute average data as dN/dlog(dp), where dN is the particle number concentration per measured size bin normalized over the logarithm of the bin width. The bin width is defined as the distance between two diameters. They are spaced equally in log-space with dlog(dp) = log(d_n+1/d_n) = 1/64. To derive the total particle number concentration between 11 and 400 nm one has to integrate over the diameter range taking into account the normalization by dlog(dp).</p> <p>Temporal coverage is from December 20, 2016 to April 10, 2017. The file “ACESPACE_submicron_aerosol_particle_size_distribution.csv” covers the entire time period except between 9 and 14 January 2017 due to instrument issues. The file “ACESPACE_submicron_aerosol_particle_size_distribution_nano.csv” contains data for the period between 9 and 14 January 2017 and can be used to fill the above gap. The second data file stems from another SMPS with a smaller differential mobility analyser, hence the smaller diameter coverage.</p> <p><strong>Dataset contents</strong></p> <p>The data set contains two files with the size distribution of sub-micrometer aerosol particles. The rows are indexed by the time stamp, which is the end of the 5-minutes averaging interval. The columns are the normalized concentrations of particles in the respective size bin. See the data abstract for details.</p> <ul> <li>ACESPACE_submicron_aerosol_particle_size_distribution.csv, data file, comma-separated values</li> <li>ACESPACE_submicron_aerosol_particle_size_distribution_nano.csv, data file, comma-separated values</li> <li>ACESPACE_particle_diameter_bins.csv, metadata, comma-separated values</li> <li>data_file_header.txt, metadata, text</li> <li>README.md, metadata, text</li> </ul> <p>NaN values in a complete row denote missing values because of e.g., calibration periods, ship exhaust contamination, instrument failure. NaN values which appear individually or only in small groups reflect that data were below detection limit. For latitude and longitude, NaN values are noted in cases where position data was not available for the given time period.</p> <p><strong>Dataset license</strong></p> <p>This sub-micron aerosol particle size distribution dataset collected during 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>
Equivalent black carbon aerosol measured over the Southern Ocean in the austral summer of 2016/2017, during the Antarctic Circumnavigation Expedition.
<p><strong>Dataset abstract</strong></p> <p>The authors would highly appreciate to be contacted if the data is used for any purpose.</p> <p>We measured equivalent black carbon (eBC) with an aethalometer (model AE33, Magee Scientific) at a time resolution of one second during the Antarctic Circumnavigation Expedition (ACE). We report five-minute averaged data, cleaned from exhaust gas influence. Temporal coverage is from December 20, 2016 to April 10, 2017.</p> <p>The mass concentration of eBC, reported in ng m<sup>-3</sup>, reflects how far fossil fuel combustion or biomass burning contribute to the aerosol population over the Southern Ocean and between South Africa and Europe. Over the Southern Ocean there are no sources of eBC, except for ship emissions and (sub-)Antarctic station emissions, and hence an enhancement of eBC points towards long-range influence from Africa, Australia, New Zealand and South America. When plotted against latitude, eBC concentrations drop south of 60°S, indicating a more pristine environment. Elevated concentration around the equator are likely influenced by biomass burning in tropical Africa.</p> <p><strong>Dataset contents</strong></p> <ul> <li>ACESPACE_equivalent_black_carbon_aerosol.csv, data file, comma-separated values</li> <li>data_file_header.txt, metadata, text</li> <li>README.md, metadata, text</li> </ul> <p>The data file listed above contains five-minute averaged values of equivalent black carbon (eBC) measured during the Antarctic Circumnavigation Expedition. Timestamps are the end of the five-minute period over which the eBC values were averaged. Latitude and longitude are average values of the position of the measurement during the five-minute interval.</p> <p>NaN values of eBC denote missing values because of e.g., ship exhaust contamination, maintenance, instrument failure or signal noise levels exceeding 200 ng/m<sup>3</sup>. For latitude and longitude, NaN values are noted in cases where position data was not available for the given time period.</p> <p><strong>Dataset license</strong></p> <p>This equivalent black carbon 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>
Coarse mode aerosol particle size distribution collected in the Southern Ocean in the austral summer of 2016/2017, during the Antarctic Circumnavigation Expedition.
<p><strong>Dataset abstract</strong></p> <p>The authors would highly appreciate to be contacted if the data is used for any purpose.</p> <p>We measured coarse mode aerosol particle size distributions with an aerodynamic particle sizer (APS, model TSI 3321) at a time resolution of five minutes during the Antarctic Circumnavigation Expedition (ACE). The diameter range is 0.7 to 19 µm. Particles in this size range are indicative of primary sea spray aerosol, biological particles and potentially long-range transported mineral dust. These particles are also important for cloud formation as they act as cloud condensation nuclei or ice nucleating particles, the latter especially in the case of biological particles and mineral dust.</p> <p>Typically the instrument reports data starting from particles with a diameter greater than 500 nm, however, particle number concentrations in the channels below 723 nm were overestimated, which is a common artefact with this instrument.</p> <p>The data have been cleaned from the influence of the exhaust of the research vessel. Temporal coverage is from December 20, 2016 to April 10, 2017. We give five-minute averaged data as dN/dlog(dp), where dN is the particle number concentration per measured size bin normalized over the logarithm of the bin width. The bin width is defined as the distance between two diameters. They are spaced equally in log-space with dlog(dp) = log(d_n+1/d_n) = 1/32. To derive the total particle number concentration one has to integrate over the diameter range taking into account the normalization by dlog(dp).</p> <p><strong>Dataset contents</strong></p> <ul> <li>ACESPACE_coarse_mode_aerosol_particle_size_distribution.csv, data file, comma-separated values</li> <li>data_file_header.txt, metadata, text</li> <li>README.md, metadata, text</li> </ul> <p>NaN values in a complete row denote missing values because of e.g., ship exhaust contamination, maintenance, instrument failure. NaN values which appear individually or only in small groups reflect that data were below detection limit. For latitude and longitude, NaN values are noted in cases where position data was not available for the given time period.</p> <p><strong>Dataset license</strong></p> <p>This coarse mode aerosol particle size distribution dataset collected during 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>
Aerosol particle number concentration measured over the Southern Ocean in the austral summer of 2016/2017, during the Antarctic Circumnavigation Expedition.
<p><strong>Dataset abstract</strong></p> <p>The authors would highly appreciate to be contacted if the data is used for any purpose.</p> <p>We measured aerosol particle number concentration with a condensation particle counter CPC model TSI 3022 at a time resolution of 10 seconds during the Antarctic Circumnavigation Expedition (ACE). We report five-minute averaged data cleaned from exhaust gas influence. The lower cut-off of the CPC is 7 nm. Temporal coverage of the dataset is from December 20, 2016 to April 10, 2017.</p> <p>The total particle number concentration reflects aerosol particles from a variety of sources and processes. The concentrations include for example sea spray aerosol, long-range transported particles, newly formed particles and others. The variability in the concentration reflects processes such as wet removal through precipitation, new particle formation or sea spray formation.</p> <p><strong>Dataset contents</strong></p> <ul> <li>ACESPACE_aerosol_particle_concentration.csv, data file, comma-separated values</li> <li>data_file_header.txt, metadata, text</li> <li>README.md, metadata, text</li> </ul> <p>NaN values of aerosol particle number concentration denote missing values because of e.g., ship exhaust contamination, maintenance, instrument failure. For latitude and longitude, NaN values are noted in cases where position data was not available for the given time period.</p> <p><strong>Dataset license</strong></p> <p>This aerosol particle number concentration 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>
Non-refractory particulate sulfate and chloride data from a time of flight aerosol chemical speciation monitor around the Southern Ocean in the austral summer of 2016/17, during the Antarctic Circumnavigation Expedition (ACE).
<p><strong>Dataset abstract</strong></p> <p>The Antarctic Circumnavigation Expedition (ACE) campaign was conducted between 20th December 2016 and 19th March 2017. The time of flight aerosol chemical speciation monitor (ToF-ACSM, Aerodyne Research Inc.) was deployed. It is capable of providing 10-minute resolution chemical compositions of NR-PM1 (non-refractory particulate matter with aerodynamic diameter smaller than 1 µm), including sulphate, nitrate, ammonium and organics. Chloride is refractory and can only be measured qualitatively, that is relative changes in intensity are trustworthy while absolute concentrations are a clear underestimation, because most of the chloride is in refractory form as part of sea salt in the marine environment. Since this ACSM dataset was collected on the ship, the ship exhaust will occasionally interfere with the natural signal. Therefore data gaps exist. The overall concentrations of particulate organics, nitrate and ammonium remained low, mostly below detection limit, except during the polluted periods. Thus, we do not report these three components. Only sulphate can be retrieved as a quantitative variable from this dataset.</p> <p>This dataset provides limited information on the chemical composition of sub-micron non-refractory aerosol in the Southern Ocean and gives hints on potential sources. Chloride clearly reflects the contribution of sea salt to the aerosol population. This can be checked by relating the particulate chloride to wind speed (Landwehr et al., 2019; 10.5281/zenodo.3379590) and particles with large diameters (Schmale et al., 2019; 10.5281/zenodo.2636709). Particulate sulphate may originate from a variety of sources: sea salt (minor contribution), anthropogenic emissions and natural marine emissions of dimethylsulfide, which is converted to SO2 and sulphuric acid in the atmosphere and can subsequently partition into the particle phase via gas-phase or aqueous phase reactions (Schmale et al., 2019).</p> <p><strong>Dataset contents</strong></p> <ul> <li>raw_chl_SO4_mz_55_57_manual_with_flags.csv, data file, comma-separated values</li> <li>README.txt, metadata, text</li> <li>data_file_header.txt, metadata, text</li> <li>calibration_info.csv, metadata, comma-separated values</li> </ul>
ScienceDex guides
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Allen Brain Atlas
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International Brain Laboratory public data
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OpenNeuro
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