eReefs Climatology GeoTiffs (AIMS, Source: CSIRO)

Full description

This dataset is a collection of spatial climatologies derived from the eReefs hydrodynamic and biogeochemical models for the Great Barrier Reef (GBR) region. It contains GeoTiff raster files representing long-term average conditions for numerous environmental variables across different depths (3m, 9m, 18m, and 39m below surface) and models (GBR4 BGC v3.1 2011 - 2018, GBR4 Hydro v2.0 2011 - 2023, and GBR1 Hydro v2.0 2015 - 2023).

Each GeoTiff represents the average conditions over the set of whole years in the model time series. Only whole years were used to ensure that the averages were not influenced by seasonal differences from partial years. Variables include temperature, salinity, nutrients, currents, chlorophyll, pH, and numerous other water quality parameters, all presented in their original units as continuous spatial fields. The outputs of this processing are saved as a series of GeoTiff images to make subsequent processing and use of the data easy.

Method:

The climatologies were generated by calculating the temporal mean of annual aggregates from the eReefs models available through the AIMS THREDDS server. Data was accessed via OPeNDAP, which allowed for efficient subsetting and processing of specific variables and depths. For each model (GBR4 BGC v3.1, GBR4 Hydro v2.0, and GBR1 Hydro v2.0), only complete years were included in the averaging process to ensure seasonal signals were not biased by partial years. The processing methodology carefully preserved the spatial structure and metadata from the original models.

For variables with a depth dimension, the nearest available model depth layer was selected for each target depth (3m, 9m, 18m, and 39m). For variables without a depth dimension (such as surface elevation), processing occurred once with results stored in a 'surface' directory. The temporal averaging was performed on a cell-by-cell basis, with proper handling of missing values to ensure unbiased results. The GeoTiff outputs maintain the original coordinate reference system (WGS84) and spatial resolution of the source models, with appropriate adjustments to ensure correct geographic registration for use in GIS applications.


Processing Code Availability:

The processing code used to generate this dataset is available in both R and Python, providing examples of how to work with eReefs data services. Both implementations perform identical processing steps and produce the same analysis products, offering users flexibility in their preferred programming language. The code demonstrates techniques for accessing data via OPeNDAP, processing NetCDF files, handling oceanographic data with proper depth selection, and exporting results to GeoTiff format with appropriate metadata. These scripts are available on GitHub as part of the GBR_AIMS_eReefs-climatology-geotiffs repository and can be adapted for other eReefs-related processing tasks. The dual-language implementation serves as a valuable resource for researchers seeking to understand and extend the processing methodology or apply similar techniques to other eReefs datasets.


Data Format:

The dataset is provided as a collection of GeoTiff (.tif) files, a widely supported raster format for geospatial data that can be used directly in GIS software, spatial analysis packages, and modeling frameworks. Each GeoTiff file:

- Contains a single variable at a specific depth from a specific model
- Uses the WGS84 (EPSG:4326) coordinate reference system
- Each GeoTiff uses the regridded version of the eReefs model model data (see technical report on regridding). The regridded grid is a slightly higher resolution than the original eReefs curvilinear grid, with inverse distance weighting interpolation. The higher resolution is to ensure that very little information is lost in the regridding process. This grid also includes approximately a one pixel extrapolation to help ensure that it doesn't have gaps near the coast or around islands.
- The files follow a consistent naming convention facilitating programmatic access and organisation.


Limitations:

This dataset has several important limitations that users should consider:

Temporal Coverage: The climatologies cover different time periods depending on the model: GBR4 BGC (2011-2018), GBR4 Hydro (2011-2023), and GBR1 Hydro (2015-2023). These periods may not capture longer-term climate variability or recent changes.

Model Versions: This dataset is based on eReefs BGC v3.1 and Hydro v2.0, which will be deprecated in July 2025 by the new model versions (v4.0). This dataset will be extended when the new version is available. Older version will be remain available.

Model Accuracy: The GBR4 Hydro v2.0 model is based on a near-real-time configuration rather than a hindcast, which may reduce its accuracy compared to the forthcoming v4.0 hindcast model that uses more consistent forcing data.

Spatial Biases: The eReefs models have known spatial biases, particularly in areas with complex bathymetry or near coastal boundaries. The GBR4 model (4km resolution) may not accurately represent fine-scale coastal processes, while the GBR1 model (1km resolution) provides improved coastal representation but with a shorter time series.

Averaging Limitations: The temporal averaging process smooths out extremes and temporal variability that may be ecologically significant. Species distributions and ecological processes are often influenced by extreme events or seasonal patterns that are obscured in these climatologies. Two locations with identical mean conditions may experience very different variability regimes.

Vector Averaging: For directional variables (u, v, wspeed_u, wspeed_v), the climatologies represent vector averages, which remove fluctuations from tides and capture only net movement. This means that areas with strong but reversing currents may show low average values despite experiencing significant water movement. Complementary variables 'mean_cur' and 'mean_wspeed' represent the average magnitude of currents and wind speed, indicating average strength regardless of direction.

Depth Approximation: The target depths (3m, 9m, 18m, 39m) are approximated to the nearest available depth in the model's vertical grid, which may vary slightly from the target values.

Ecological Interpretation: These climatologies do not capture the temporal dynamics, extremes, or variance that may be crucial for understanding species responses to their environment. They provide a simplified representation of average conditions that may not reflect the actual environmental drivers of ecological patterns.


Data Dictionary:
All variables are available at multiple depths, except for those indicated as surface variables.
GBR4 BGC v3.1 (2011-2018):
TN - Total Nitrogen (mg N m-3)
TP - Total Phosphorus (mg P m-3)
DIN - Dissolved Inorganic Nitrogen (mg N m-3)
DIP - Dissolved Inorganic Phosphorus (mg P m-3)
Chl_a_sum - Chlorophyll a concentration, sum across all phytoplankton groups (mg Chl m-3)
NO3 - Nitrate concentration (mg N m-3)
NH4 - Ammonium concentration (mg N m-3)
DOR_N - Dissolved Organic Nitrogen (mg N m-3)
DOR_P - Dissolved Organic Phosphorus (mg P m-3)
Secchi - Secchi depth (m) - surface variable
PH - pH (log(mM))
omega_ar - Aragonite saturation state (dimensionless)
EFI - Ecology Fine Inorganics (Total suspended solids) (kg m-3)
Oxy_sat = Oxygen saturation percent (%)
Oxygen = Dissolved oxygen (mg O m-3)

GBR4 Hydro v2.0 (2011-2023) and GBR1 Hydro v2.0 (2015-2023):
eta - Sea surface elevation (m) - surface variable
temp - Water temperature (°C)
salt - Salinity (PSU)
u - Eastward water current component (m/s)
v - Northward water current component (m/s)
wspeed_u - Eastward wind speed component (m/s) - surface variable
wspeed_v - Northward wind speed component (m/s) - surface variable
mean_cur - Mean current magnitude (m/s)
mean_wspeed - Mean wind speed magnitude (m/s) - surface variable

Available Depths:
Surface (for variables without depth dimension)
3m (closest available model depth)
9m (closest available model depth)
18m (closest available model depth)
39m (closest available model depth)
Each variable is provided as a separate GeoTiff file, organized by model and depth, in the format: geotiff_name = _avg--__m.tif.
- : 'GBR4_H2p0_B3p1_Cq3b_Dhnd', 'gbr4_v2_hydro', 'gbr1_2.0_hydro'
- : GBR4: 2011, GBR1: 2015
- : GBR4 BGC v3.1: 2018, GBR4 Hydro v2.0: 2023, GBR1 Hydro v2.0: 2023
- : Variable name, such as NH4.
- : For GBR4 v2.0 or v3.1 models depths are: '3.0', '8.8, '17.8', '39.5', 'surface'. For GBR1 v2.0: '2.4', '9.0', '18.0', '39.5', 'surface'. Note surface variables don't have the '_m' portion of their filename.


Direct data download:

The GeoTiff data files are available from a browsable service that allows one or more files to be downloaded as a zip file. These files are also available as direct downloads, which is useful for scripted processing.
This direct link has the following structure:
https://nextcloud.eatlas.org.au/s/imnBZiHwNKWLSf5/download?path=%2F%2Fm&files=
- : 'GBR4-BGC3p1-base', 'GBR4-H2p0', or 'GBR1-H2p0'.
For example:
https://nextcloud.eatlas.org.au/s/imnBZiHwNKWLSf5/download?path=%2FGBR4-BGC3p1-base%2F3.0m&files=GBR4_H2p0_B3p1_Cq3b_Dhnd_avg-2011-2018_Chl_a_sum_3.0m.tif

To download a whole directory as a zip file remove the 'files' parameter. So that: https://nextcloud.eatlas.org.au/s/imnBZiHwNKWLSf5/download?path=%2FGBR4-BGC3p1-base%2F3.0m will download all the BGC variables for a depth of 3.0 m.


Location of the data:

This dataset is filed in the eAtlas enduring data repository at: data\custodian\2025-2029-eReefs\GBR_AIMS_eReefs-climatology-geotiffs


Change Log:

2025-05-17 (Version 1): Initial release of the dataset based on averaging of GBR4 BGC3.1 base, GBR4 Hydro v2.0, GBR1 Hydro v2.0.

Lineage

Maintenance and Update Frequency: asNeeded

Statement: This data is derived from the AIMS regridded temporal aggregations of the eReefs model data.

Notes

Purpose
This dataset was created to address the need for accessible, ready-to-use spatial representations of typical environmental conditions across the GBR. It serves researchers who require environmental data for spatial modeling but may not have the technical capacity or time to process the raw eReefs model outputs. The dataset was specifically developed in response to requests from researchers requiring typical environmental conditions for species distribution modeling using MaxEnt and for studies examining the different environmental conditions experienced by fish at various life stages across reef and inshore habitats. By providing pre-processed climatologies in the widely supported GeoTiff format, this dataset enables immediate use in geographic information systems and spatial modeling frameworks without requiring specialized oceanographic data processing skills. The climatologies offer a simplified view of the complex oceanographic conditions in the GBR, making environmental data more accessible to ecologists, conservation scientists, and resource managers.