This service provides generated summaries (daily, monthly, annual) of the eReefs CSIRO hydrodynamic model v2.0 (https://research.csiro.au/ereefs) outputs at both 1km and 4km resolution, generated by the AIMS eReefs Platform (https://ereefs.aims.gov.au/ereefs-aims). This provides the data as an OPeNDAP service and as NetCDF files (https://thredds.ereefs.aims.gov.au/thredds/). These summaries are derived from the original hourly model outputs available via the National Computing Infrastructure (NCI) (https://dapds00.nci.org.au/thredds/catalogs/fx3/catalog.html), and have been re-gridded from the original curvilinear grid used by the eReefs model into a regular grid so that the data files can be easily loaded into standard GIS software.
These datasets were updated in near-real time up until Jan 2024 when the near-real time Hydrodynamic model was stopped.
Notice: In the second half of 2025 these products will be replaced with a new version of the hydrodynamic model (v4.0) that is based on a hindcast rather than near real time model forcing. This dataset and Thredds service will be updated when the raw model data becomes available on NCI available. The v2.0 data will then be deprecated and may become unavailable as it is too expensive to maintain both datasets
Method:
A description of the processing, especially aggregation and regridding, is available in the "Technical Guide to Derived Products from CSIRO eReefs Models" document (https://nextcloud.eatlas.org.au/apps/sharealias/a/aims-ereefs-platform-technical-guide-to-derived-products-from-csiro-ereefs-models-pdf ). For the GBR 4 model the outputs were re-gridded to 0.03 degrees (~3 km) and the GBR 1 model is regridded to 0.005 degrees (~500 m). The regular grids were chosen to be finer than the original grids to minimise defects introduced by the regridding process.
Data Dictionary:
The following variables are available:
- eta: Surface elevation (sea surface height above sea level) (metres) - This can be used to estimate tides.
- salt: Salinity (PSU)
- temp: Temperature (degrees C)
- wspeed_u: Eastward wind (ms-1) - Average over time
- wspeed_v: Northward wind (ms-1) - Average over time
- u: Eastward sea water velocity (component of the ocean current vector in the eastward direction) (ms-1)
- v: Northward sea water velocity (component of the ocean current vector in the northern direction) (ms-1)
- mean_wspeed: Mean Wind speed magnitude - Average of the hourly wspeed magnitude over time (ms-1)
- mean_cur: Mean sea water velocity (current) magnitude - Average of the hourly current magnitude over time (ms-1)
FAQ:
With the aggregate results why is the mean_cur not equal to the sqrt(u^2+v^2)?
The mean_cur is not equal to the sqrt(u^2 + v^2) in the aggregate results, because the u and v represent the net current flow, with most of the tidal signal averaged out, while the mean_cur represents the mean of the current magnitude which includes tidal flows.
With the instantaneous (raw hourly) model data current_magitude=sqrt(u^2 + v^2). After temporal aggregation (this dataset) u and v are an average over time of the vector components. The positive and negative oscillations in the original hourly values, typically due to the tides, tend to be average to zero over time. As a result the temporal aggregate u and v components represent the vector of the net current flow. In high tidal areas the net flow can be quite low, with water sloshing back and forth to the same location, even though the average of the magnitude of the current is high (mean_cur).
The mean_cur is therefore useful for understanding bottom steer stress and mixing due to currents, while the temporal aggregate u and v components are useful for understanding large ocean currents.
How does the regridding work? What algorithm is used?
The raw eReefs model (available via NCI) use a curvilinear grid to minimise the number of simulation cells. This grid format is incompatible with many GIS applications. The products associated with this dataset, available from the AIMS eReefs THREDDS server, are regridded on to a regular rectangular grid. This regridding is performed using an Inverse Distance Weight from the nearest 4 grid cells. A consequence of this approach is that there are an additional set of interpolated pixels along the coastline. Additional detail on the regridding is available in the "Technical Guide to Derived Products from CSIRO eReefs Models".
Depths:
This data set contains a subset of the depths available in the source data sets, which differ slightly between the 1km and 4km models.
Depths at 1km resolution: -0.5, -2.35, -5.35, -9.0, -13.0, -18.0, -24.0, -31.0, -39.5, -49.0, -60.0, -73.0, -88.0, -103.0, -120.0, -140.0,
Depths are 4km resolution:-0.5, -1.5, -3.0, -5.55, -8.8, -12.75, -17.75, -23.75, -31.0, -39.5, -49.0, -60.0, -73.0, -88.0, -103.0, -120.0, -145.0.
Limitations:
The wind data is originally from the BOM Access-R weather models. These models capture synoptic winds and some of the features of cyclones, however they do not represent the high speed winds near the eye of cyclones well. For this reason the maximum wind speed aggregations do not capture the peak winds of cyclones.
The GBR1 yearly summaries of salinity and temperature have a known problem where the data is WRONG with a sharp boundary appearing at edge of the GBR. Do not use this data. We will investigate and resolve the issue with this data.
This dataset is based on a spatial and temporal model and as such is an estimate of the environmental conditions. It is not based on in-water measurements, and thus will have a spatially varying level of error in the modelled values. It is important to consider if the model results are fit for the intended purpose.
Change Log:
2020-08-18 (Version 1): Initial version of the system and dataset. Dataset and service covers GBR4 BGC v3.1 from 2010 - 2019.
2025-05-16 (Version 1): Improved the metadata title and abstract to better represent the dataset. Also minted a DOI and added how the dataset should be cited.
