Explore Ocean Data
- Ocean State Estimates (➭ code link) : explore ocean transports, climate indices, subsurface temperature, and many more variables from full ocean state estimates (ECCO, OCCA).
- Sea Surface Temperature (➭ code link) : plot global mean and regional sea surface temperature (NOAA's OISST).
- Air Sea Fluxes (➭ code link) : estimate surface heat flux balance from Atmospheric and Oceanic state.
- Sea Level Anomalies (➭ code link) : gridded satellite altimetry data
- Plankton, Chemistry, and Light (➭ code link) : visualize ocean colour and biomass climatologies estimated using the Darwin3 model.
Detail
sst_anomaly_notebook.jl plots a map of SST anomaly, as well as time series (SST and anomalies). Source : NOAA/OISST.
SatelliteAltimetry.jl plots a map a sea level anomaly maps derived from altimetry. Sources : NASA/PODAAC, CMEMS.
ECCO_standard_plots.jl lets you explore a wide range of variables derived from gridded time-variable ocean climatologies (ECCO4, OCCA2). The data is retrieved from dataverse.org, and intermediate results from zenodo.org. Source: MIT, NASA/ECCO. Source code: here, here.
The CBIOMES1 climatology (alpha version) is a global ocean state estimate that covers the period from 1992 to 2011 (ECCO). It is based on Forget et al 2015 for ocean physics MIT general circulation model and on Dutkiewicz et al 2015 for marine biogeochemistry and ecosystems Darwin Project model.
CBIOMES_climatology_create (➭ code link) : recreate the CBIOMES-global climatology files
OptimalTransport_demo.jl : using optimal transport for model-data comparison (CBIOMES1 vs satellite data).
References
- OCCA2 : Forget 2026
- ECCO4 : Forget et al 2015
- CBIOMES1: Forget 2018
- OCCA1 : Forget 2010
More Notebooks
- HadIOD_viz.jl : download, read, and plot a subset of the HadIOD T/S database
- Sea Level Time Series (➭ code link) : plot global mean and regional sea level data from NASA (NASA's NSLCT and ECCO). (broken data source)
- NSLCT_notebook.jl lets you access sea level data from NASA and Dataverse portals (
HTTP.jl,Dataverse.jl), organize it into tables (DataFrames.jl), and plot it (Makie.jl). (broken data source) - examples in OceanRobots.jl for observations collected at sea (in situ data).
Notes
For more on these estimates, and how to use them in Julia, please refer to the following documentation and links therein.
- OceanRobots.jl : access, analyze, process, and simulate data generated by ocean robots. These ocean observing platforms collect observations in the field, and allow us to monitor climate.
- MITgcm.jl : framework to interact with MITgcm (setup, run, output, plot, etc), CBIOMES, and ECCO output.
- MeshArrays.jl : gridded Earth variables, domain decomposition, C-grid support; Ocean Circulation, Geography tutorials.
- IndividualDisplacements.jl : simulation and analysis of materials moving through oceanic and atmospheric flows.
For more notebooks involving CBIOMES and related efforts, take a look at the following pages.
- Marine Ecosystem Notebooks : Darwin3 model, ocean color data, gradients field program, and more.
- JuliaCon2021 workshop : Modeling Marine Ecosystems At Multiple Scales Using Julia.
- PlanktonIndividuals.jl : simulate the life cycle of ocean phytoplankton cells and their environment.
To run the notebook on a local computer or in the cloud, please refer to the Pluto docs. Directions are also provided in the following pages.