The eReefs research project is a collaboration between the Great Barrier Reef Foundation, CSIRO, the Australian Institute of Marine Science, Bureau of Meteorology, and Queensland Government. It aims to develop a platform that will provide a picture of what is currently happening on the reef.

The system spans the catchments, estuaries, reef lagoon and the open ocean. It provides information on physical processes, sediment transport, biogeochemistry and ocean colour. The project addresses enhanced monitoring, data standards, data architecture, operational modelling, reporting and data visualisation.

For more information, see eReefs research website

Derived data

The original eReefs models produced by CSIRO use a curvilinear grid as it is better suited to the modelling and execution requirements than a rectilinear grid. However, curvilinear grids are incompatible with many off-the-shelf GIS software packages and can be cumbersome to process with typical data science tools. Therefore, all eReefs-derived datasets generated by the AIMS eReefs Platform (available through this THREDDS data service) have been regridded to a rectilinear grid.

To limit the storage requirements for this service we only provide temporal aggregations for the hydrodynamic models. This service regrids and aggregates to daily data (using an average of the hourly samples). This is then used to produce further temporal aggregations (monthly, annual). If you need hourly hydrodynamic data, then you will need to use the original eReefs model data from CSIRO available through the eReefs THREDDS catalogue on NCI.

For the BioGeoChemical models the original eReefs model data from CSIRO has a daily temporal resolution. We provide a regridded version of this data (with a subset of the depths and variables), along with temporal aggregations (monthly and annual).

This repository only serves the regridded derived data. For the original data, see eReefs THREDDS catalogue on NCI

Regridding algorithm

The regridding algorithm calculates the value of each cell of the linear grid by calculating the sum of the 4 closest neighbour cells from the curvilinear grid, weighted by the inverse distance of each neighbour cell.

For more information about the regridding algorithm and the aggregation applied to the original data files, see Technical Guide to Derived Products from CSIRO eReefs Models.pdf

Virtual datasets vs File download

eReefs model data is stored in NetCDF data files. Each NetCDF file can contain one or more time steps. To limit the size of the NetCDF files and to allow easy addition of new data, the files are organised into limited time periods. For example, data labelled as ‘daily-monthly’ means daily timesteps, organised into monthly files. In this example to analyse one year of data you would need to download 12 data files. To connect via OpenDAP you would need to connect to the end point for each month. The individual NetCDF files are available from the ‘File download’ folders.

The same data is also available as ‘virutal datasets’. These combine all the NetCDF files for a given product, into a single timeseries. This means the entire time series appears as a single data service. This allows OpenDAP connections to access the data from any time slice without needed to know which NetCDF file the data exists in.

If you need to download the data use the ‘File download’ option using the ‘HTTPServer’ option. If you want to use OpenDAP use the ‘Virtual datasets’ options.

Resources

For more information about the eReefs model in general, see Models - eReefs Research

For data visualisation, see eReefs AIMS Visualisation Portal

To extract data from the model output, see eReefs Data Extraction Tool

For information about how to use these files, see eReefs AIMS - Help pages

AIMS eReefs THREDDS versus CSIRO eReefs available on NCI

Feature	CSIRO Hydro	CSIRO BGC	AIMS Hydro (derived from CSIRO Hydro)	AIMS BGC (derived from CSIRO BGC)
Key variables	Current, Temperature, Salinity, Wind	Nutrients, Carbon chemistry, Sediment, Light, Water clarity	Current, Temperature, Salinity, Wind	Nutrients, Carbon chemistry, Sediment, Light, Water clarity
Number of variables	14	321	13	112
Hourly timestep	X
Daily timestep (noon)		X		X
Daily timestep (average of hourly data)			X
Monthly (average of daily data)			X	X
Annual (average of daily data)			X	X
Curvilinear grid	X	X
Regular grid			X	X
Depth range	1.5m to -3890m (44 layers)	1.5m to -3890m (44 layers)	-0.5m to -140m (16 layers)	-0.5m to -145m (17 layers)
Use case	Finest timescale, deep water	Understand how the model works (rare model variables), deep water	Shallow water analysis where daily data is fine enough	Shallow water analysis
Programmatic Libraries	eReefs (R library), emsarray (Python). These help with curvilinear grids.	eReefs (R library), emsarray (Python). These help with curvilinear grids.	RNetCDF (R library), netCDF4 (Python), eReefs tutorials	RNetCDF (R library), netCDF4 (Python), eReefs tutorials
Data source	NCI THREDDS	NCI THREDDS	AIMS eReefs THREDDS	AIMS eReefs THREDDS

Hydrodynamic model

The hydrodynamic model SHOC (Sparse Hydrodynamic Ocean Code; Herzfeld et al., 2006, https://research.csiro.au/cem/software/ems/hydro/) is employed for this study for both the regional and shelf model applications. SHOC is a general purpose model (Herzfeld, 2006) based on the manuscript of Blumberg and Herring (1987), applicable on spatial scales ranging from estuaries to regional ocean domains. It is a three-dimensional finite-difference hydrodynamic model, based on the primitive equations. Outputs from the model include three-dimensional distributions of velocity, temperature, salinity, density, passive tracers, mixing coefficients and sea-level.

Hydrodynamic models

ID	Model name	Description
gbr4_v2	Hydrodynamic model - 4km grid	Hydrodynamic model of the Great Barrier Reef (GBR) at 4km resolution. For more information, visit the GBR 4km documentation page.
gbr1_2.0	Hydrodynamic model - 1km grid	Hydrodynamic model of the Great Barrier Reef (GBR) at 1km resolution. This model use the 4km hydrodynamic model as input. For more information, visit the GBR 1km documentation page.

Major variables found in hydrodynamic models

Variable	Description
temp	Temperature
salt	Salinity
u/v	Sea water velocity (current)
wspeed_u/wspeed_v	Wind

See introduction to eReefs for more information about the model's variables.

See eReefs models - Hydrodynamics for more information about the Hydrodynamic model.

BioGeoChemical model

The GBR4 BioGeoChemical (BGC) model builds on the GBR4 hydrodynamic model by modelling the water quality (nutrients and suspended sediment) and key ecological processes (coral, seagrass, plankton) that drive the water chemistry. This model allows us to better understand how water quality is affected by land runoff.

BioGeoChemical models

ID	Model name	Description
GBR4_H2p0_B3p1_Cq3b_Dhnd	BioGeoChemical model - Baseline scenario	Paddock to Reef SOURCE Catchments with 2019 catchment condition from Dec 1, 2010 - Jun 30, 2018 (used for GBR Report Card 8 published in 2019), Empirical SOURCE with 2019 catchment condition, Jul 1, 2018 - April 30, 2019. This scenario most closely corresponds to historic BioGeoChemical conditions of the reef (see limitation). For more information, visit the BGC Baseline scenario documentation page.
GBR4_H2p0_B3p1_Cq3R_Dhnd	BioGeoChemical model - Reduced scenario	SOURCE Catchments with 2019 catchment condition (q3b) with anthropogenic loads (q3b - q3p) reduced according to the percentage reductions of DIN, PN, PP and TSS specified in the Reef 2050 Water Quality Improvement Plan (WQIP) 2017-2022 as calculated in Brodie et al., (2017). Further, the reductions are adjusted to account for the cumulative reductions already achieved between 2014 and 2019 that will be reflected in the 2019 catchment condition used in the Baseline scenario (q3b). For more information, visit the BGC Reduced scenario documentation page.
GBR4_H2p0_B3p1_Cq3P_Dhnd	BioGeoChemical model - Pre-industrial scenario	Paddock to Reef SOURCE Catchments with Pre-Industrial catchment condition from Dec 1, 2010 - Jun 30, 2018 (used for GBR Report Card 8 published in 2019), Empirical SOURCE with Pre-Industrial catchment, Jul 1, 2018 - April 30, 2019. For more information, visit the BGC Pre-Industrial scenario documentation page.

Example of variables found in BioGeoChemical models

Variable	Description
EFI	Suspended solids
Chl_a_sum	Total chlorophyll
Oxygen	Dissolved oxygen
alk	Total alkalinity

See introduction to eReefs for more information about the model's variables.

You can explore eReefs data using Python code in a Jupyter Notebook.

Each dataset in AIMS eReefs THREDDS contains a Jupyter Notebook viewer link. The link can be used to download a JSON file representation of the Notebook. You can load that file in your JupyterLab and explore the data found in the chosen dataset.

See Jupyter Notebook guide for more information.