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Rockhampton future climate (2050) 100 year Average Recurrence Interval bushfire hazard

Note: This metadata describes the dataset in accordance with the ANZLIC (Australia New Zealand Land Information Council) Core Metadata Guidelines Version 2.

Dataset citation

ANZLIC unique identifier: ANZCW0703017001

Title: Rockhampton future climate (2050) 100 year Average Recurrence Interval bushfire hazard


Custodian: Geoscience Australia

Jurisdiction: Australia



This use of this data should be carried out with the knowledge of the contained metadata and with reference to the associated report provided by Geoscience Australia with this data (Reforming Planning Processes Trial: Rockhampton 2050). A copy of this report is available from the the Geoscience Australia website ( or the Geoscience Australia sales office (, 1800 800 173). This raster file identifes the future climate bushfire hazard for the Rockhamtpon study region. The name of the file indicates the content; either 50 or 100 year Return Period (RP), 2 or 3 model (General Circulation Model) average and the time period: 2050 or 2090.

ANZLIC search words:

  • HAZARDS Fire Mapping

Spatial domain:

locality map

Geographic extent name: FITZROY (S) - QLD-FITZROY (S) - Local Government Areas (LGA) - Queensland

Geographic extent polygon: 150.0851 -22.9778, 150.9521 -22.9778, 150.9521 -23.6073, 150.0851 -23.6073, 150.0851 -22.9778,

Note: The format for each Geographic extent name is: Name - Identifier - Category - Jurisdiction (as appropriate) See GEN Register

Geographic bounding box:
North bounding latitude: -22.9778 °
South bounding latitude: -23.6073 °
East bounding longitude: 150.9521 °
West bounding longitude: 150.0851 °

Data currency

Beginning date: Not Known

Ending date: Not Known

Dataset status

Progress: Complete

Maintenance and update frequency: Not Known


Stored data format:
DIGITAL - tif Tagged Image File Format (TIFF) - including GeoTIFF
Available format type:
DIGITAL - tif Tagged Image File Format (TIFF) - including GeoTIFF

Access constraints:

? Commonwealth of Australia (Geoscience Australia) 2013

With the exception of the Commonwealth Coat of Arms and where otherwise noted, all material

in this publication is provided under a Creative Commons Attribution 3.0 Australia Licence (

Geoscience Australia has tried to make the information in this product as accurate as possible. However, it does not guarantee that the information is totally accurate or complete. Therefore, you should not solely rely on this information when making a commercial decision.

Free Data Download

Data quality


The extract below is summarised from the technical report. The metadata attached to the data is more extensive and can be viewed via ArcCatalog. See the technical report for tables, images and reference list referenced in the summary.

This study utilised data (climate simulations) from three Global Circulation Models (GCMs) being forced by the A2 SRES (A2; see Nakicenovic and Swart, 2000) Green House Gas (GHG) emissions scenario and then downscaled using a Regional Climate Model (RCM).

CSIRO Marine and Atmospheric Research produced high-resolution climate change projections for the eastern part of the Australian continent as part of the South East Queensland Climate Adaptation Research Initiative project (CSIRO 2012). We utilised the new high-resolution projections provided by CSIRO to obtain a 0.15? grid of meteorological parameters (approx 15 km horizontal resolution) across the eastern part of the continent (Latitude -10?S to -50?S; Longitude 135?E to 155?E) generated by downscaling the GCMs using the CSIRO RCM, the Conformal Cubic Atmospheric Model (CCAM - McGregor, 2005; McGregor and Dix 2008).

Three GCMs were dynamically downscaled using CCAM at the grid resolution of 0.15? for the period 1971-2100. The GCMs selected were ECHAM 5 (Max-Planck Institut (Germany)), GFDL_CM 2.1 (Princeton Univ./NOAA (USA)), and MIROC 3.2 medres (Interdisciplinary Research on Climate (Japan)). The model selection was based on an assessment by Smith and Chandler (2009) that examined the ability of selected models to reproduce the present-day climate of the Australian region.

Forest Fire Danger Index

For current climate, the FFDI was obtained utilising the observational record, which spanned four decades in the Central Queensland region. High-resolution spatial detail for the FFDI was obtained by using a modelling approach that considered a number of extreme events that were identified as ?typical? of the type of event that would be experienced for a 50 year ARI or 100 year ARI event.

For future climate, the GCMs were initially run in ?control? mode where the present-day (1990) atmospheric forcings were kept constant. From 1991 to 2100 the atmospheric forcing followed the A2 scenario (Nakicenovic and Swart, 2000) resulting in a change within each model from the ?control? climate. Three periods of the simulation within each of the three models were considered:

? (Dataset 1) 1971 ? 1990 (considered as the current climate [CC] simulation)

? (Dataset 2) 2041 ? 2060 (considered as the simulated climate of 2050)

? (Dataset 3) 2081 ? 2100 (considered as the simulated climate of 2090)

The maximum FFDI for the Rockhampton region was calculated for each day in these datasets (as with the observed current climate data) and extreme value statistics were employed to determine the magnitude of the 50 year ARI [50ARI] and 100 year ARI [100ARI] FFDI event. Finally, the FFDI for the observed current climate data was scaled by the simulated data (see equations below) to determine how the FFDI would be modified in a new climate.


50ARI (2050) = [50ARI (2041-2060) / 50ARI (1971-1990)] x 50ARI (observed current climate)

100ARI (2050) = [100ARI (2041-2060) / 100ARI (1971-1990)] x 100ARI (observed current climate)


50ARI (2090) = [50ARI (2081-2100) / 50ARI (1971-1990)] x 50ARI (observed current climate)

100ARI (2090) = [100ARI (2081-2100) / 100ARI (1971-1990)] x 100ARI (observed current climate)

NOTE: The ensemble average of the three downscaled GCMs was used to provide estimates for the 50 year ARI and the 100 year ARI FFDI predictors that inform the future climate FFDI. For the 100 year ARI estimate for 2090, the MIROC3.2 model was not used as it gave extremely high FFDI values compared with the other two models. The FFDI is an exponential index therefore care needs to be taken that any significant model bias has been removed before calculating the FFDI values.

Positional accuracy:

Consistent match between the input layers, (vegetation and elevation) as compared with other layers, e.g. aerial photography.

Attribute accuracy:

The western extent of the bushfire hazard data has been identified as an area of lesser confidence as the weather simulation model has been identified as propagating a gravity wave through the data that is not realistic.

Logical Consistency:

Not applicable.


The numerical weather model (WRF) was run on a smaller area than the Rockhampton study region to ascertain the appropriateness, accuracy and timeliness of the numerical weather prediction model. There was not time to expand the study region following the test of the smaller domain.

Contact information

Contact organisation: Commonwealth of Australia (Geoscience Australia) (GA)
Contact position: Manager Client Services
Mail address: Cnr Jerrabomberra Ave and Hindmarsh Dr
Mail address: GPO Box 378
Locality: Canberra
State: ACT
Country: Australia
Postcode: 2601
Telephone: 02 6249 9966
Facsimile: 02 6249 9960
Electronic mail address:

Metadata information

Metadata date: 2013-05-28

Additional metadata

Metadata reference XHTML:

Metadata reference XML:


Authors:Cechet, R.P. French, I. Sanabria, A. Moore, D.