Find research datasets worth reusing

opencc-by-4.0Apr 2020View details →

Eddy Kinetic Energy in the Arctic Ocean from a High-resolution Global Simulation with 1-km Arctic (data).

Data for the "Eddy Kinetic Energy in the Arctic Ocean from a High-resolution Global Simulation with 1-km Arctic".

opencc-by-4.0Jan 2021View details →

Eddy Kinetic Energy and SST gradients global datasets and trends. Additionally, this dataset includes ocean basins and ocean processes masks.

This dataset includes the post-processed data used for the paper titled "Mesoscale kinetic energy response to changing oceans". The original data was obtained from AVISO+ SSH altimetry and NOAA optimal interpolated sea surface temperature (OISST): AVISO+ SSH: https://www.aviso.altimetry.fr/en/data/products/sea-surface-height-products/global/gridded-sea-level-heights-and-derived-variables.html NOAA-OISST: https://www.ncdc.noaa.gov/oisst From satellite observations of sea surface height (SSH) and sea surface temperature (SST) over the satellite record (1993 - 2019), EKE and SST gradients are derived.  Then the fields are then temporally smoothed using a running average of 12 months.  Trends and the significance of each field are finally computed with linear regression and a modified Mann–Kendall test (https://github.com/josuemtzmo/xarrayMannKendall). Geographical regions consist of the following ocean basins: the Southern Ocean, the Indian Ocean, the Pacific Ocean, and the Atlantic ocean. These ocean basins were expert-defined to capture ocean processes at all scales (ocean_basins_and_dynamical_masks.nc). Dynamical regions (Fig. 5d): the Antarctic Circumpolar Current (ACC), the boundary currents and their extensions, the tropics, the subtropical ocean gyres, and the remaining regions (ocean_basins_and_dynamical_masks.nc). Further information and scripts to reproduce the result of the manuscript can be found at: https://github.com/josuemtzmo/EKE_SST_trends

opencc-by-4.0Jan 2022View details →

Ensemble statistics for modelled Eddy Kinetic Energy in the Southern Ocean

This dataset contains surface eddy kinetic energy over the Southern Ocean region, sourced from a 50-member ensemble of 0.25° ocean model simulations. It is used in the paper "Circumpolar variations in the chaotic nature of Southern Ocean eddy dynamics" published in Journal of Geophysical Research - Oceans. This dataset has been computed from the OceaniC Chaos – ImPacts, strUcture, predicTability (OCCIPUT) global ocean/sea-ice ensemble simulation. It is composed of 50 members with a horizontal resolution of 1/4° and 75 geopotential levels (<a href="http://doi.org/10.5194/gmd-10-1091-2017">Bessières et al., 2017</a>, Penduff et al., 2014). The numerical configuration is based on the version 3.5 of the NEMO model (<a href="https://www.nemo-ocean.eu/doc">Madec, 2008</a>). The 50 members were started on January 1st 1960 from a common 21-year spinup. A small stochastic perturbation is applied to the equation of state of sea water (as in <a href="https://doi.org/10.1016/j.ocemod.2013.02.004">Brankart, 2013</a>) within each member during 1960, then switched off during the rest of the simulation. This 1-year perturbation generates an ensemble spread which grows and saturates after a few months up to a few years depending on the region. The 50 members are driven through bulk formulae during the whole 1960-2015 simulation by the same realistic 6-hourly atmospheric forcing (Drakkar Forcing Set DFS5.2, Dussin et al., 2016) derived from ERA interim atmospheric reanalysis. Data is for the period 1979-2015. The sea level anomaly is found according to <a href="http://doi.org/10.1016/j.pocean.2020.102314">Close et al (2020)</a> and converted into surface geostrophic velocity anomaly using the geostrophic relation. This velocity field is then used to calculate the eddy kinetic energy (EKE). Data is averaged over calendar month, and restricted to the latitude range 40°-60°S. A full description of this process is included in the companion paper. The dataset includes EKE files (eke_0??.nc), with monthy EKE saved for the period 1979-2015 for each ensemble member, and a single file (tau.nc) for the monthly-averaged wind stress over the same period.

opencc-by-4.0Jan 2022View details →

Dataset associated with paper "Topographic hotspots of Southern Ocean eddy upwelling"

Data repository for Yung, Morrison and Hogg (2022) Topographic hotspots of Southern Ocean eddy upwelling, submitted to Frontiers in Marine Science   This repository contains processed data, created using scripts available in the github repository <a href="https://github.com/claireyung/Topographic_Hotspots_Upwelling-Paper_Code">https://github.com/claireyung/Topographic_Hotspots_Upwelling-Paper_Code</a>.   The data comes from the repeat year atmospheric forcing version of the ACCESS-OM2 modelling suite 0.1 degree model (see Kiss et al. (2020), http://www.cosima.org.au, model available at <a href="https://github.com/COSIMA/access-om2">https://github.com/COSIMA/access-om2</a>). The model was spun up for 270 years, and the next 10 years of output were used.   Daily resolution data was used in the calculation of quantities, which results in a large amount of raw data (~4TB for Southern Ocean latitudes (35-70S), 10 years). Therefore, we only provide relevant processed data. Details of these calculations are available in the above github repository.   Any quantities calculated along sea surface height contours are labelled with a letter. These are referred to in the following table.   | Letter |  SSH  | | :---:  | :---: | |   A    | -0.1m | |   B    | -0.2m | |   C    | -0.3m | |   D    | -0.4m | |   E    | -0.5m | |   F    | -0.6m | |   G    | -0.7m | |   H    | -0.8m | |   I    | -0.9m | |   J    | -1.0m | |   K    | -1.1m | |   L    | -1.2m | |   M    | -1.3m | |   N    | -1.4m | |   O    | -1.5m | |   P    | -0.15m| |   Q    | -0.25m| |   R    | -0.35m| |   S    | -0.45m| |   T    | -0.55m| |   U    | -0.65m| |   V    | -0.75m| |   W    | -0.85m| |   X    | -0.95m| |   Y    | -1.05m| |   Z    | -1.15m| |   Z1   | -1.25m| |   Z2   | -1.35m| |   Z3   | -1.45m|   There are two versions of the along-contour coordinates for each contour. The latlon named files are more useful for analysis, the other is used while computing transport across contours. These are made using <a href="https://github.com/claireyung/Topographic_Hotspots_Upwelling-Paper_Code/blob/main/Analysis_Code/make_contour.ipynb">https://github.com/claireyung/Topographic_Hotspots_Upwelling-Paper_Code/blob/main/Analysis_Code/make_contour.ipynb</a>.   Distance along contour files contain the cumulative distance along the contour in 10^3 km from 80E (<a href="https://github.com/claireyung/Topographic_Hotspots_Upwelling-Paper_Code/blob/main/Figure_Code/Fig7-upwelling_characteristics.ipynb">https://github.com/claireyung/Topographic_Hotspots_Upwelling-Paper_Code/blob/main/Figure_Code/Fig7-upwelling_characteristics.ipynb</a>). Dimensions are contour index, counting from 80E. There are also segment length files of each part of the contour.   vh_eddy files contain the eddy transport across the contours, averaged over 10 years. These are calculated by taking the time mean of the residual transport ($\overline{vh}$), e.g. SO_L_vol_trans_across_contour_binned.nc, and subtracting the mean transport $\overline{v}\overline{h}$, calculated from the time mean isopycnal thicknesses along contours (e.g. SO_L_dzu_across_contour_binned) and the time mean velocity, $v = vh/h$ (calculated in <a href="https://github.com/claireyung/Topographic_Hotspots_Upwelling-Paper_Code/blob/main/Analysis_Code/Save_and_bin_along_contours.ipynb">https://github.com/claireyung/Topographic_Hotspots_Upwelling-Paper_Code/blob/main/Analysis_Code/Save_and_bin_along_contours.ipynb</a>). The full files are provided for the contour L (SSH=-1.2 m) as is provided in the paper manuscript Fig. 6. These eddy transports have dimensions of sigma1 and contour index (the two extra SO_L files have time too).   vh_eddy_interp files contain the interpolated eddy transports at hotspots, for the density range 1032.2kg/m^3 <= sigma_1 <= 1032.5kg/m^3. Calculation method provided at <a href="https://github.com/claireyung/Topographic_Hotspots_Upwelling-Paper_Code/blob/main/Analysis_Code/Interpolation_between_contours.ipynb">https://github.com/claireyung/Topographic_Hotspots_Upwelling-Paper_Code/blob/main/Analysis_Code/Interpolation_between_contours.ipynb</a>.   We also provide files that summarise the transport in density and SSH space for hotspots and the circumpolar total. See <a href="https://github.com/claireyung/Topographic_Hotspots_Upwelling-Paper_Code/blob/main/Analysis_Code/UpwellingArmDefn.ipynb">https://github.com/claireyung/Topographic_Hotspots_Upwelling-Paper_Code/blob/main/Analysis_Code/UpwellingArmDefn.ipynb</a> for calculation details. The exact names and specifications are provided in the README.   We provide 10 year mean files of the energy conversion and energy terms over the Southern Ocean latitude range. These are made by binning daily transports and layer thicknesses into sigma 1 bins over the Southern Ocean (<a href="https://github.com/claireyung/Topographic_Hotspots_Upwelling-Paper_Code/blob/main/Analysis_Code/Binning_SouthernOcean_code.ipynb">https://github.com/claireyung/Topographic_Hotspots_Upwelling-Paper_Code/blob/main/Analysis_Code/Binning_SouthernOcean_code.ipynb</a>) and then calculating energy terms (<a href="https://github.com/claireyung/Topographic_Hotspots_Upwelling-Paper_Code/blob/main/Analysis_Code/Save_MKE_EKE.ipynb">https://github.com/claireyung/Topographic_Hotspots_Upwelling-Paper_Code/blob/main/Analysis_Code/Save_MKE_EKE.ipynb</a>, <a href="https://github.com/claireyung/Topographic_Hotspots_Upwelling-Paper_Code/blob/main/Analysis_Code/Save_Energy_Conversion_Terms.ipynb">https://github.com/claireyung/Topographic_Hotspots_Upwelling-Paper_Code/blob/main/Analysis_Code/Save_Energy_Conversion_Terms.ipynb</a>)     The files named with contour_energies contain the EKE, Form stress and Reynolds stress averaged over 10 years but extracted along the same contours as eddy transport. <a href="https://github.com/claireyung/Topographic_Hotspots_Upwelling-Paper_Code/blob/main/Analysis_Code/save_energy_terms_along_contours.ipynb">https://github.com/claireyung/Topographic_Hotspots_Upwelling-Paper_Code/blob/main/Analysis_Code/save_energy_terms_along_contours.ipynb</a>   We also provide 10 year averaged density binned transport, layer thickness and densities.   Please refer to the README file for additional details.

opencc-by-4.0Jun 2023View details →

Processed data supporting figures in Yang et al. 2023: Oceanic eddies induce a rapid formation of an internal wave continuum

This data repository supports a manuscript by Luwei Yang, Roy Barkan, Kaushik Srinivasan, James C. McWilliams, Callum J. Shakespeare, and Angus H. Gibson, submitted to Communications Earth & Environment. This repository contains the processed data that support the figures in the manuscript.

opencc-by-4.0Jul 2023View details →

Estimating three-dimensional structures of eddy in the South Indian Ocean from the satellite observations based on the isQG method

Supporting data for Estimating three-dimensional structures of eddy in the South Indian Ocean from the satellite observations based on the isQG method 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.

opencc-by-4.0Mar 2023View details →

Evaluation of the CMCC global eddying ocean model for the Ocean Model Intercomparison Project (OMIP2)

Model output of the global eddy-rich configuration used in the Geoscientific Model Development publication: "Evaluation of the CMCC global eddying ocean model for the Ocean Model Intercomparison Project (OMIP2)"  Abstract: This paper describes the global eddying ocean-sea ice simulation produced at the Euro-Mediterranean Center on Climate Change (CMCC) obtained following the experimental design of the Ocean Model Intercomparison Project phase 2 (OMIP2). The eddy-rich model is based on the NEMOv3.6 framework, with a global horizontal resolution of 1/16° and 98 vertical levels, and was originally designed for an operational short-term ocean forecasting system. Here, it is driven by one multi-decadal cycle of the prescribed JRA55-do atmospheric reanalysis and runoff dataset in order to perform a long-term benchmarking experiment. To access the accuracy of simulated 3D ocean fields, and highlight the relative benefits of mesoscale activities, the GLOB16 performances are evaluated via a selection of key climate metrics against observational datasets and two other NEMO configurations at lower resolutions: an eddy-permitting resolution (ORCA025) and a non-eddying resolution (ORCA1) designed to form the ocean-sea ice component of the fully coupled CMCC climate model.  The well-known biases in the low-resolution simulations are significantly improved in the high-resolution model. The evolution and spatial pattern of large-scale features (such as sea surface temperature biases and winter mixed layer structure) in GLOB16 are generally better reproduced, and the large-scale circulation is remarkably improved compared to the low-resolution oceans. We find that eddying resolution is an advantage in resolving the structure of western boundary currents, the overturning cells, and flow through key passages. GLOB16 might be an appropriate tool for ocean climate modeling effort, even though the benefit of eddying resolution does not provide unambiguous advances for all ocean variables in all regions.

opencc-by-4.0Dec 2021View details →

Particle trajectories - Freilich et al. "Diversity of growth rates maximizes phytoplankton productivity in an eddying ocean"

The files provided here are the offline particle trajectories analyzed in Freilich, Flierl, and Mahadevan “Diversity of growth rates maximizes phytoplankton productivity in an eddying ocean” Both files are sqlite databases containing information about the same particle trajectories which are identified by the variable “iD”   ini_day135_z115_forward_biology.db contains nutrient concentration on particle trajectories. A different biological rate lambda is used for each variable denoted NX where X is 0-13. The rates are: 0.015,0.075,0.15,0.3,0.75,1.5,3,10,15,20,50,75,100,120 The variable DOY is the model day.    ini_day135_z115_physical_forward.db contains the physical variables on particle trajectories. The variables are: x - east-west position y - north-south position z - vertical position u - east-west velocity v - north-south velocity w - vertical velocity vorticity - vertical component of relative vorticity

opencc-by-4.0Feb 2022View details →

NetCDF data used in analysis presented in "Assessment of the z~ time-filtered Arbitrary Lagrangian-Eulerian coordinate in a global eddy-permitting ocean model"

NetCDF data used in analysis presented in "Assessment of the z~ time-filtered Arbitrary Lagrangian-Eulerian coordinate in a global eddy-permitting ocean model", submitted to Journal of Advances in Modelling the Earth System. The data are produced from an ensemble of six experiments based on the GO8p0 configuration of NEMO v4.0.1 on a global 1/4° grid, as described in the paper. The ensemble is intended to test the z~ vertical coordinate, and includes a control with the default "z-star" fixed coordinate, and five experiments with the z-tilde vertical coordinate, using a selection of values for the two z-tilde timescale parameters. The data includes time series of global mean ocean and ice fields; large-scale transports; and fields from diapycnal mixing analysis. The first part of each filename refers to the experiment from the ensemble ("zstar", "ztilde_5_30", "ztilde_10_30", "ztilde_20_30", ztilde_20_60" and "ztilde_40_60"); the following five-character string identifies the respective suite on the Met Office Rose system and the MASS archive system; and the rest of the name specifies the type of data contained in the file.

opencc-by-4.0Aug 2024View details →

Codes and source data for "Common occurrences of subsurface heatwaves and cold-spells in ocean eddies"

This repository contains the MATLAB (R2022b) codes (*.m files) and the figure source data (.mat files)  for the paper "Common occurrences of subsurface heatwaves and cold-spells in ocean eddies" (He et al., 2024).  For installation of MatLab, please refer to: https://au.mathworks.com/products/matlab.html For queries about this repository and its contents, please contact Dr. Qingyou He (qyhe@scsio.ac.cn). %% Fig1.m: For plotting main Fig.1. %% Fig2.m: For plotting main Fig.2. %% Fig3.m: For plotting main Fig.3. %% Fig4.m: For plotting main Fig.4. %% Fig5.m: For plotting main Fig.5. %% Fig6.m: For plotting main Fig.6. %% Data Fig1.mat: For main Fig.1. %% Data Fig2.mat: For main Fig.2. %% Data Fig3.mat: For main Fig.3. %% Data Fig4.mat: For main Fig.4. %% Data Fig5.mat: For main Fig.5. %% Data Fig6.mat: For main Fig.6. References: He, Q., W. Zhan, M. Feng, Y. Gong, S. Cai, and H. Zhan (2024), Common occurrences of subsurface heatwaves and cold spells in ocean eddies, Nature, 634, 1111–1117, doi:10.1038/s41586-024-08051-2.

opencc-by-4.0Feb 2023View details →

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

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

dryad40/100

Eddy flux measurements and transfer velocities of momentum, water vapor, and sulfur dioxide over the coastal Atlantic ocean

Open the record for dataset details and reuse information.

publicAug 2019View details →

opencc-by-4.0Dec 2020View details →

Large Eddy Simulation of the Southern Ocean

The data set contains seven Large Eddy Simulations (LES) at the Southern Ocean Flux Site for studies of deep turbulent ocean boundary layers, with and without surface wave effects, and with both idealized and observed forcing by wind, surface buoyancy flux and Stokes drift profiles. There are 20 days of hourly statistics computed every half-hour of turbulence quantities; namely, the vertical fluxes of buoyancy (temperature) and momentum, buoyancy and velocity variances, and the turbulent kinetic energy, its production terms and its dissipation.

opencc-by-4.0Oct 2023View details →

Dataset for "Mesoscale Eddy-Induced Sharpening of Oceanic Tracer Front"

Data of the tracer experiments and the associated diagnostics in the shallow water model for the ocean front study.<ul><li>eforc.tar.gz: diagnosed eddy forcing fields for different tracers;</li><li>exps_trs.tar.gz: solutions in offline tracer experiments on the coarse grid;</li><li>forc_uvh.tar.gz: mass fluxes and layer thicknesses used to advect tracers;</li><li>params.tar.gz: parameters used for tracer experiments</li></ul>Please contact Yueyang Lu via yueyang.lu@miami.edu if there are any questions.

opencc-by-4.0Aug 2023View details →

The Heat and Carbon Characteristics of Modelled Mesoscale Eddies in the South Atlantic Ocean

Datasets in this repository are generated from BIOPERIANT12-CNCLNG01 model and are part of the manuscript entitled: "The Heat and Carbon Characteristics of Modelled Mesoscale Eddies in the South Atlantic Ocean".

opencc-by-4.0Nov 2023View details →

Stronger oceanic CO2 sink in eddy-resolving simulations of global warming: simulations outputs

This repository contains 1) the air-sea CO2 flux and the Dissolved Inorganic Carbon (DIC) distribution in idealized simulations run at different resolutions 2) the terms of the DIC budget for each simulation integrated temporally on the all simulation and integrated spatially on different boxes of the domain. These data are used in the article "Stronger oceanic CO$_2$ sink in eddy-resolving simulations of global warming" published in Geophysical Research Letters for producing Figs. 2, 3, 4. Refer to this paper for details about the data.

openJan 2022View details →

Dataset: Large-eddy simulation of the ice shelf-ocean boundary layer model output

This repository contains large-eddy simulation output from the CFD model Diablo. The simulations are of the boundary layer beneath a melting ice shelf. This model output underpins the submitted manuscript Regimes and transitions in the basal melting of Antarctic ice shelves submitted to the Journal of Physical Oceanography (December 2021).

opencc-by-4.0Apr 2022View details →

Supplementary material for paper "Contribution of the wind and Loop Current Eddies to the circulation in the southern Gulf of Mexico" submitted to journal of Ocean Dynamics

Movie including the time evolution of the daily SSH and surface velocity vector fields in the BoC, the meridional  velocity in the CG zonal section, meridional velocity in the 22°N zonal section, the vq sections at 22°N, the time series of PVF2 and CPFV2 and the time series of daily transport through the CG western arm.

opencc-by-4.0Jul 2022View details →

Data for "Properties of the lateral mesoscale eddy-induced transport in a high-resolution ocean model: Beyond the flux-gradient relation" (Lu et al. JPO)

Preprocessed data to reproduce results and figures in "Properties of the lateral mesoscale eddy-induced transport in a high-resolution ocean model: Beyond the flux-gradient relation" (Lu et al., In Review of Journal of Physical Oceanography).  Feel free to contact Yueyang Lu via yxl1496@miami.edu if you have any questions.