eReefs AIMS-CSIRO Aggregations of hydrodynamic model outputs

This generated data set contains 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). 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 summaries are updated in near-real time (daily) and are made available via a THREDDS server (http://thredds.ereefs.aims.gov.au/thredds/catalog.html) in NetCDF format. For more information about the eReefs hydrodynamic modelling see https://research.csiro.au/ereefs/models/models-about/models-hydrodynamics/.

# 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://eatlas.org.au/pydio/public/aims-ereefs-platform-technical-guide-...).

# Data Dictionary:

The following variables are available:
- eta: Surface elevation (sea surface height above sea level) (metres)
- salt: Salinity (PSU)
- temp: Temperature (degrees C)
- wspeed_u: Eastward wind (ms-1)
- wspeed_v: Northward wind (ms-1)
- u: Eastward sea water velocity (second half of the current vector) (ms-1)
- v: Northward sea water velocity (half of the current vector) (ms-1)
- mean_wspeed: Mean Wind speed magnitude (ms-1)
- mean_cur: Mean sea water velocity (current) magnitude (ms-1)

# FAQ:

## 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) due to the aggregation process. The instantaneous (raw hourly) u and v values take both positive and negative values as the current changes direction. When these values are averaged over a day or a month, the positive and negative swings tend to cancel out, removing most of the tidal signal. As a result, the aggregate u and v values only show the net current flow. The mean current is different because the current value corresponds to the magnitude of the current, calculated on the hourly data with sqrt(u^2 + v^2). This is then averaged over time. Since the current magnitude is always a positive number there is no ‘averaging out’ of the tidal currents and thus the average is much higher. The daily u and v values show the net current flow (cancelling out any back and forth movement), the mean_cur shows the average current magnitude, i.e. average strength of the net flows and the tidal flows over the period.

# How does the regridding work? What algorithm is used?

The raw eReefs model (available via NCI) uses a curvilinear grid to minimise the number of simulation cells. This grid format is incompatible with many GIS applications. The products 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.