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118 results for “Ocean observations”
Sparse observations induce large biases in estimates of the global ocean CO2 sink: an ocean model subsampling experiment
<p>Dataset underlying the analysis in Hauck et al., 2023: Sparse observations induce large biases in estimates of the global ocean CO<sub>2</sub> sink - an ocean model subsampling experiment, Philosophical Transactions A</p> <p>Surface ocean partial pressure of CO<sub>2 </sub>(pCO<sub>2</sub>) and air-sea CO<sub>2</sub> flux reconstructions, using two mapping methods (MPI-SOM-FFN, CarboScope) three different sampling masks: SOCAT, SOCAT+SOCCOM, IDEAL (based on bgcArgo, Roemmich et al., 2019).</p> <p>Also, all FESOM-REcoM output fields that were used in the reconstructions are provided.</p> <p>We further provide the three masks that were used for subsampling: SOCAT, SOCAT+SOCCOM, IDEAL (bgcArgo).</p> <p> </p>
Journey North - Gray Whale observations by volunteer community scientists across the Eastern Pacific Ocean (1997-2020)
This data package contains Gray Whale migration data consisting of 1,546 total observational reports from 1997 - 2020 across the Eastern Pacific Ocean. These data were collected by 163 community scientists for Journey North, a crowdsourced participatory science program of the University of Wisconsin-Madison Arboretum. The Journey North Gray Whale Project is a study of Gray Whale phenology conducted at broad spatial and temporal scales. Since 1997, community scientists have tracked the migration of Gray Whales (Eschrichtius robustus) through the Eastern Pacific Ocean. Observers also provide estimates of the number of whales sighted. However, observers do not follow standardized methods for counting species observed. Observers do not observe at set times of the day, do not repeat observations regularly, and are not required to provide the length of time during which a specified number of species observed were counted. Therefore, it is recommended that this dataset be analyzed to indicate presence not abundance. Researchers are encouraged to read the rich information provided by volunteers in their comments. These comments provide qualitative information about observational reports. Researchers are also encouraged to refer to submitted photographs that also provide context for observational reports. The Journey North Gray Whale Project dataset is hosted by the University of Wisconsin-Madison Shared Web Hosting Service.
Seasonal to decadal western boundary current variability from sustained ocean observations
<p> </p> <p>Cross-transect velocity time series for HR-XBT transects IX21, PX30, and PX40 in support of: <a href="http://doi.org/10.1029/2022GL097834">Chandler et al. (2022). Seasonal to decadal western boundary current variability from sustained ocean observations.</a> </p> <p> </p> <p>Each netcdf file includes the following variables:</p> <ul> <li>time</li> <li>longitude</li> <li>latitude</li> <li>depth</li> <li>vel</li> <li>gvel_LNM</li> <li>long_for_vel_err</li> <li>lat_for_vel_err</li> <li>vel_err</li> <li>wbc_transport</li> </ul> <p> </p> <p>See also <a href="https://github.com/mlchandler/wbc_sustained_obs">https://github.com/mlchandler/wbc_sustained_obs</a></p>
SO-WISE South Atlantic Ocean and Indian Ocean Observational Constraints
<p>This dataset contains an initial set of curated and processed oceanographic observations collected as part of a joint effort between the EU SO-CHIC project and a UKRI Future Leaders Fellowship. It is partly intended to be used as a set of observational constraints for a Weddell Gyre region state estimate, although it can be used for more general analysis purposes as well. It has been used as part of an unsupervised clustering analysis [see Jones (2022) for software and Jones and Zhou (2022) for labelled dataset, see references]. </p> <p><strong>Overall spatial and temporal coverage</strong></p> <ul> <li>Latitude: 85°S-30°S</li> <li>Longitude: 65°W-80°E</li> <li>Time: 1974-2020</li> </ul> <p><strong>Contents</strong></p> <ul> <li>CPOM_SSH: sea-ice corrected sea surface height </li> <li>CTD: temperature and salinity profiles from ship-based CTD casts </li> <li>FLOATS: temperature and salinity profiles from Argo floats </li> <li>SEALS: temperature and salinity profiles from seal-mounted profilers</li> <li>Stress_and_EKE: sea-ice corrected surface stress and EKE </li> <li>XBT: temperature and salinity profiles from expendable bathythermographs (XBTs)</li> </ul> <p><strong>Profile quality control</strong></p> <p>We only consider profiles with good position and time flags, as well as good temperature, salinity, and pressure measurements with good flags. Duplicated profiles are identified when multiple profiles are found within 24 hours over the same 2 km x 2 km grid cell, and only one profile within the spatio-temporal window is used. We then used the MITprof toolbox (Forget, G., 2017) to pre-process the selected profiles, re-gridding them onto 72 standard pressure levels; the vertical interval varies from 20 dbar at the surface to 100 dbar in the deep ocean. </p> <p><strong>SSH processing</strong></p> <p>SSH data is sea-ice corrected version provided by the Centre for Polar Observation and Modelling (CPOM) in the UK. It is composed by two satellite missions, Envisat (2004/05-2012/03) and Cryosat-2 (2010/07-2020/04). The data is available in montly along-track format. A gaussian 300km filter, ±3 std outliner removal and 0.5x0.25 deg interpolation is applied to grid the data. Intersatellite offset is removed using the overlapped period between two missions using the mean difference map. SSH is referenced to EIGEN6C4 geoid to obtain the dynamic ocean topography feild for the computation of geostrophic velocity. See the README in the Stress_and_EKE directory for more information. </p> <p><strong>Sources</strong></p> <ul> <li>Argo floats: <a href="http://argo.ucsd.edu">http://argo.ucsd.edu</a></li> <li>World Ocean Database: <a href="https://www.ncei.noaa.gov/products/world-ocean-database">https://www.ncei.noaa.gov/products/world-ocean-database</a></li> <li>MEOP-CTD Database (seal profilers): <a href="https://www.meop.net/">https://www.meop.net/</a></li> <li>CDRv4 available via NSIDC: <a href="https://nsidc.org/data/G02202">https://nsidc.org/data/G02202</a></li> <li>Polar Pathfinder sea ice drift data via NSIDC: <a href="https://nsidc.org/data/nsidc-0116">https://nsidc.org/data/nsidc-0116</a></li> </ul> <p><strong>Version</strong></p> <p>This is a pre-production version, in that it has not yet been used with a state estimate. </p>
Dataset for manuscript "Thermal infrared dust optical depth and coarse-mode effective diameter over oceans retrieved from collocated MODIS and CALIOP observations"
<p>This is the long-term satellite retrieval dataset of dust aerosol optical depth at 10 μm (DAOD<sub>10μm</sub>) and dust coarse mode effective diameter (D<sub>eff</sub>) based on collocated MODIS and CALIOP observations from July 2006 to August 2018. The full description is in the manuscript "<strong>Thermal infrared dust optical depth and coarse-mode effective diameter over oceans retrieved from collocated MODIS and CALIOP observations" </strong>by Zheng, Jianyu, et al. The readme file for the data is in "readme_dust_aod_size_product.txt". The variable list of Level-2 data is in "variable_list_L2.txt". The variable list of Level-3 data is in "variable_list_L3.txt".</p>
Air-Sea Ammonia Fluxes Calculated from High-Resolution Summertime Observations Across the Atlantic Southern Ocean
<p>This data set includes ocean ammonium concentrations, atmospheric ammonia gas concentrations, and calculated air-sea ammonia fluxes from the Atlantic sector of the Southern Ocean during summer. Associated with the folloiwng paper: </p> <p> https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2020GL091963</p>
Still images from the KuramBio expedition 2012 (Stations 3-6, 8-11) obtained with the Ocean Floor Observation System
<p>Repository with still images obtained from the videos of the KuramBio 2012 expedition in 5 second intervals. Still images belong to deep-sea stations where the Ocean Floor Observation System (OFOS) was deployed and enough video survey was obtained (i.e., Stations 3-6, 8-11). The Station 7 survey length was enough but has no HD video. Thus, images were not retrieved since the quality does not allow accurate lebensspuren or benthic fauna identification. </p><p>The OFOS was lowered into the water at the CTD position. The first 300 meters lowering was conducted with 0.5 m/sec, and then the speed was increased to 0.8 m/sec while the ship was kept in position. At 500 meters above ground the speed was reduced to 0.5 m/sec, and further reduced to 0.3 m/sec at 200 meters above ground. As soon as visual contact with the bottom was established, the winch was stopped. The ship started moving with 0.5 knots in the appropriate direction, which was chosen depending on current and wind situation at the according station. The OFOS was kept in an appropriate distance to the seafloor, enabling the scientists to watch the macrofaunal organisms. The approximate size of the observed animals could be calculated with the help of two laser pointers having a distance of 10 cm between each other (see Fig. 1-3). Generally, the survey lasted slightly over one hour, then the ship was stopped and heaving of the OFOS started. This was first conducted at 0.5 m/sec and accelerated to 1.0 m/sec. For more information see the cruise report (RV Sonne cruise SO223; doi:10.1016/j.dsr2.2014.11.001).</p>
Adjusted ERA5, COREv2 and JRA-55 products constrained by ocean observations
<p>This dataset contains ERA5, JRA-55 and COREv2 air-sea flux fields that have been adjusted to match ocean heat and salt content change in EN4 and IAP ocean observations. It also contains estimes of meridional heat and freshwater transports, globally and in the Atlantic and Indo-Pacific, based on these adjusted air-sea surface flux fields. Please consult the README for more information on the dataset. <br><br>The net heat flux and net freshwater flux into the ocean have been adjusted using the "Optimal Transformation Method" (OTM), a watermass-based inverse method that uses physics-based constraints to close the observed ocean heat and salt budgets. The formulation of OTM and a model validation is provided at Zika & Sohail (2024). The process of producing these adjusted air-sea fluxes is described in Sohail & Zika (2025).</p>
Model results and observation data in Zhang et al. modeling of wave interference at Ocean Beach, CA
<p>The dataset contains modeling results and observation data supporting the manuscript of Phase-resolved modeling of wave interference and its effects on nearshore circulation in a large ebb shoal-beach system by Yu Zhang, Fengyan Shi, Jim Kirby, Xi Feng.</p>
Archived Model Output for "Simulating Observations of Southern Ocean Clouds and Implications for Climate"
<p>This is an archive of CAM6 simulation output used in the paper Southern Ocean Aerosol and Ice Nucleating Particles in the Community Earth System Model Version 2, submitted to the Journal of Geophysical Research Atmospheres. </p>
Variability in the global ocean carbon sink from 1959-2020 by correcting models with observations (LDEO-HPD)
<p><strong>* The latest versions of this dataset are maintained and available here: <a href="https://zenodo.org/record/7901433">https://zenodo.org/record/7901433</a> *</strong></p> <p>The ocean reduces human impact on the climate by absorbing and sequestering CO2. From 1950s to the 1980s, observations of pCO2 and related ocean carbon variables were sparse and uncertain. Thus, global ocean biogeochemical models (GOBMs) have been the basis for quantifying the ocean carbon sink. The LDEO-Hybrid Physics Data product (LDEO-HPD) interpolates sparse surface ocean pCO2 data to global coverage by using GOBMs as priors, applying machine learning to estimate full-coverage corrections. The largest component of the GOBM corrections are climatological. This is consistent with recent findings of large seasonal discrepancies in GOBMs, but contrasts the long-held view that interannual variability is a major source of GOBM error. This supports extension of the LDEO-HPD pCO2 product back to 1959, using a climatology of model-observation misfits prior to 1982. Consistent with previous studies for 1980 onward, air-sea CO2 fluxes for 1959-2020 demonstrate response to atmospheric pCO2 growth and volcanic eruptions.</p> <p>This data is the final reconstruction of air-sea CO2 fluxes for 1959-2020 using the mean pCO2 from the corrected models. Both annual flux time series and spatially explicit fluxes are included. RIVERINE CARBON EFFLUX ADJUSTMENTS ARE NOT INCLUDED WITHIN THESE FILES. File metadata provides units.</p>
Supporting Movies from: Seismo-acoustic observations of crashing ocean waves: Investigating surf monitoring at Coal Oil Point Reserve, Santa Barbara, California
<div> <div> <div> <p>This repository includes supplementary movies from the manuscript titled, "Seismo-acoustic observations of crashing ocean waves: Investigating surf monitoring at Coal Oil Point Reserve, Santa Barbara, California," submitted to the Journal of Geophysical Research: Solid Earth.</p> <p> </p> <p>Movies S1 and S2. These two movies taken during array deployment 4 on October 20, 2023 show the NW tip of Coal Oil Point at the left of the field of view and Sands Beach northwest of that toward the right. Frames have the same figure layout as Figure 4 of the main text.</p> <p>Movie S3. Same as Movies S1 and S2 but with the NW tip of Coal Oil Point at the right of the field of view and Devereux Beach southeast of that toward the left.</p> </div> </div> </div>
World Ocean Database XBT observations snapshot
<p>The <a href="https://www.ncei.noaa.gov/products/world-ocean-database">World Ocean Database (WOD)</a> is world's largest collection of uniformly formatted, quality controlled, publicly available ocean profile data. This dataset is a snapshot of the XBT observations which have been preprocessed for use in a machine learning pipeline.</p> <p>The data is organised by year in CSV files, covering 1966-2015. This dataset does not include the actual temperature and depth profiles, as this dataset was focused on a project to improve the metadata.</p> <p> </p>
Aerosol particles observed onboard the research vessel Mirai over the Southern Ocean in the austral summer of 2017
<p>We have compiled a dataset of field observations to measure aerosol particle size distributions and to collect the aerosols for the following laboratory analyses to quantify the chemical composition and ice nucleating properties of aerosols over the Southern Ocean in the austral summer of 2017 as a part of the research cruise of Japanese research vessel (R/V) Mirai (Cruise number of MR16-09 leg3). The particle size distributions (PSDs) of the submicron aerosols (14–737 nm in the electrical mobility diameter) were measured using a scanning mobility particle sizer, SMPS, which is composed of a differential mobility analyzer, DMA (model 3081, TSI Inc., Minnesota, USA) and a condensation particle counter, CPC (model 3010, TSI Inc.). Since a custom-made inlet system was installed in front of the SMPS, the PSDs of total and non-volatile aerosols upon heating at the 300°C were alternatively measured every 5 min. The PSDs of the coarse fluorescent and non-fluorescent particles (700–3000 nm in the optical diameter) were measured using a waveband integrated bioaerosol sensor, WIBS (type 4A, Droplet Measurement Technologies Ltd., Colorado, USA). Hourly averaged PSDs for the diameter range of 14–3000 nm were analyzed in the associated paper in order to relate the wave breaking state derived from the hourly observations of significant wave height on the R/V. Chemical compositions were derived from the collected samples with the following techniques at the laboratory, ion chromatography for water soluble ions (chloride, nitrate, sulfate, ammonium, sodium, potassium, magnesium, calcium ions), thermal optical transmittance technique for carbonaceous aerosols (organic and elemental carbons), and inductively coupled plasma mass spectrometry for aluminum (Al). Ice nucleating properties of the aerosol particles were analyzed using a droplet freezing method (Cryogenic Refrigerator Applied to Freezing Test, CRAFT) at National Institute of Polar Research (Tobo, 2016 <a href="https://doi.org/10.1038/srep32930">https://doi.org/10.1038/srep32930</a>). All the data indicating the concentrations were reported at standard temperature and pressure (0°C and 1 atm).</p> <p>We prepared five files (comma-separated values) in total, which are hourly aerosol concentrations measured using the SMPS and WIBS, Particle size distributions measured using the SMPS, Particle size distributions measured using the WIBS, Aerosol chemical compositions, and Ice nucleating particle concentrations during the research cruise of MR16-09 leg3. Each file includes the header part to describe the aerosol data including the date and time in UTC, and the positions of the R/V.</p> <p>The associated paper discusses some aspects of data treatment and questions regarding to the methods employed in this study.</p>
Estimating three-dimensional structures of eddy in the South Indian Ocean from the satellite observations based on the isQG method
<p>Supporting data for Estimating three-dimensional structures of eddy in the South Indian Ocean from the satellite observations based on the isQG method</p> <p>Matlab Codes to reconstruct the subsurface structures (Codes without Figure_*.m) and plot the figures (Figure_*.m) in the manuscript. The file in Netcdf format is our reconstructed 3D density and currents.</p> <p> </p>
Figure 3 in Observations on age and reproduction of the oceanic squid Ancistrocheirus lesueurii (d'Orbigny, 1842) (Cephalopoda: Ancistrocheiridae)
Figure 3. Ancistrocheirus lesueurii. (A) Statolith section of a mature intersexual male (ML 275 mm) in which 761 increments could be counted. The areas in boxes are enlarged in B, C and D, where B is the nucleus, C shows regular increments past the mid part of the rostrum and D shows the increments in the periphery of the rostrum.
Final results from McCoy et al., 'Global Observations of Submesoscale Coherent Vortices in the Ocean', submitted to Progress in Oceanography.
<p>Submesoscale coherent vortices (SCVs) are small-scale, subsurface eddies that are ubiquitous in the ocean. Observations suggest that they efficiently trap and transport water, nutrients, and other properties thousands of kilometers away from their formation regions. However, the weak sea-surface signature restricts SCV observations to mostly chance encounters with shipboard subsurface instrumentation. Thus, the global occurrence, properties, and generation frequency of SCVs remain poorly constrained. Here we present results from a new algorithm used to identify SCVs from Argo float data, applied to roughly 2 million profiles conducted globally from August 1997 to January 2020.</p> <p>After application of the SCV detection algorithm to the global Argo array, we identify 2501 casts piercing spicy-core SCVs (those with anomalously hot and salty water mass characteristics), and 1583 casts piercing minty-core SCVs (anomalously cold and fresh cores) over more than 20 years of available data. The Matlab file 'final_individual_scvs.mat' contains various data for each SCV identified.</p> <p>By grouping detections from consecutive Argo casts, we are also able to record 383 spicy-core SCV time-series and 169 minty-core SCV time-series. The Matlab file 'final_timeseries_scvs.mat' contains the data for these time-series. </p> <p>For a more detailed description of each Matlab file, please see 'README.rtf'. </p> <p>Reach out to Daniel McCoy (dmccoy801@gmail.com) or Daniele Bianchi (dbianchi@atmos.ucla.edu) for inquiries. </p>
Evaluation of Upper Tropospheric Geopotential Height Anomalies over the Tropical and Subtropical Oceans in CMIP6 Models Using GNSS Radio Occultation Observations
<p>The set-up of CESM2-CAM6 sensitivity experiments for winter season (Dec-Jan-Feb: DJF), with prognostic falling ice radiative effects on (SON) and off (NOS), is an updated two-moment stratiform cloud scheme (MG2, Gettelman & Morrison, 2015) in the CESM2 atmospheric component of CAM6. CESM2-CAM6 participated in CMIP6. Both the NOS and SON simulations were configured following the same approach as the CMIP6 "historical" run spanning from 1980 to 2014.</p> <p> </p> <p>The data are:</p> <p> </p> <p>TS: skin temperature (K)</p> <p>TAUX: zonal surface wind stress</p> <p>TAUY: meridinal surface wind stress</p> <p>DTCOND: moist condensation heating rate</p> <p>QRL: long wave heating rate</p> <p>OMEGA: vertical motion</p> <p>Z3: geopotential height</p> <p> </p>
Extreme sea level rise along the Indian Ocean coastline: Observations and 21st century projections
<p>This file include all the data sets used to make the figures in the paper " <strong><em>Extreme sea level rise along the Indian Ocean coastline: Observations and 21<sup>st</sup> century projections</em></strong> "</p>
Observed Indian Ocean Warming Trend Applied to the IPSL-CM6A-LR model
<p>This experiment applies the observed warming trend of the tropical Indian Ocean (0.15 deg C per decade; Hu and Fedorov, 2019) to the tropical Indian Ocean region in the IPSL-CM6A-LR pre-industrial control run. The methods of nudging are defined in Ferster et al. (2021), where here we apply an observed warming rate rather than a constant (as in Ferster et al., 2021).</p> <p>This experiment relates to the submitted article entitled <em>Variations in tropical Indian Ocean SST drive multi-decadal AMOC variability in models and observations</em>.</p> <p>*The datasets are created from the IPSL-CM6A-LR output files</p> <p>**This version serves as a preliminary version of the dataset for publication purposes, additional output is available.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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DANDI Archive for NWB datasets
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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.