From CSIRO Marlin

GEOMACS (Geological and Oceanographic Model of Australias Continental Shelf) Trimmed mean

ARCHIVED

Created 13/01/2025

Updated 13/01/2025

Geoscience Australias GEOMACS model was utilised to produce hindcast hourly time series of continental shelf (~20 to 300 m depth) bed shear stress (unit of measure: Pascal, Pa) on a 0.1 degree grid covering the period March 1997 to February 2008 (inclusive). The hindcast data represents the combined contribution to the bed shear stress by waves, tides, wind and density-driven circulation. The trimmed mean is simply the arithmetic mean calculated excluding a percentage of the highest and lowest values in the distribution. On this occasion the highest and lowest 25% of model observations were excluded for the calculation. The geometric mean was used alongside the trimmed mean to provide a more robust representation of the bulk of the values than the arithmetic mean would have provided (Hughes and Harris 2008). This dataset is a contribution to the CERF Marine Biodiversity Hub and is hosted temporarily by CMAR on behalf of Geoscience Australia.

Files and APIs

Tags

Additional Info

Field Value
Title GEOMACS (Geological and Oceanographic Model of Australias Continental Shelf) Trimmed mean
Language eng
Licence notspecified
Landing Page https://devweb.dga.links.com.au/data/dataset/1373e9e8-f019-4b9a-b359-86b0d01f506b
Contact Point
Atlantic Oceanographic and Meteorological Laboratory (AOML)
marine@ga.gov.au
Reference Period 24/07/2008
Geospatial Coverage {"type": "Polygon", "coordinates": [[[110.0, -44.0], [156.0, -44.0], [156.0, -7.0], [110.0, -7.0], [110.0, -44.0]]]}
Data Portal data.gov.au

Data Source

This dataset was originally found on data.gov.au "GEOMACS (Geological and Oceanographic Model of Australias Continental Shelf) Trimmed mean". Please visit the source to access the original metadata of the dataset:
https://devweb.dga.links.com.au/data/dataset/geomacs-geological-and-oceanographic-model-of-australias-continental-shelf-trimmed-mean2

No duplicate datasets found.