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Downscaled Projections of Bioclimatic Indices for Species Distribution Modelling in Australia (1975 - 2099) 

Ver: 1.0
Status of Data: completed
Update Frequency: asNeeded
Security Classification: unclassified
Record Last Modified: 2026-05-21
Viewed 4 times
Accessed 3 times
Dataset Created: 2025-12-31
Dataset Published: 2026-03-31
HTTPPoint-of-truth metadata URL
HTTPro-crate-metadata.json
Data can be accessed from the following links:
OPeNDAPNetCDF files
How to cite this collection:
Toombs, N., Ma, S., Chapman, S. & Trancoso, R. (2026). Downscaled Projections of Bioclimatic Indices for Species Distribution Modelling in Australia (1975 - 2099). Version 1.0. Terrestrial Ecosystem Research Network. Dataset. https://dx.doi.org/10.25901/am36-t566 Toombs, N., Ma, S., Chapman, S., Trancoso, R., 2025. Downscaled projections of bioclimatic indices for species distribution modelling in Australia (1975 - 2099). 
Climate change is a major factor contributing to biodiversity loss globally and in Australia. Addressing this conservation challenge requires information about present and future species distributions. To improve assessment of future species distributions, we have calculated 19 bioclimatic indices using dynamically and statistically downscaled Coupled Model Intercomparison Project 6 (CMIP6) Global Climate Models (GCMs) over Australia at a 5 km resolution through 1975 – 2099 for three emissions scenarios (SSP1-2.6, SSP2-4.5 and SSP3-7.0). We used the Conformal Cubic Atmospheric Model (CCAM) for dynamical downscaling to 10km, and the Quantile Matching for Extremes (QME) method for statistical downscaling the CCAM output to 5km. This dataset will be useful for the study of climate change impacts on species distributions in Australia. 
Credit
We at TERN acknowledge the Traditional Owners and Custodians throughout Australia, New Zealand and all nations. We honour their profound connections to land, water, biodiversity and culture and pay our respects to their Elders past, present and emerging. The Queensland Future Climate Projections 2 dataset (QldFCP-2) was produced by the Queensland Future Climate Science Program, which aims to support climate adaptation and natural disasters preparedness and was funded by the Queensland Government, Australia (dataset DOI: https://doi.org/10.25914/8fve-1910). Citation: Chapman, S., Syktus, J., Trancoso, R., Thatcher, M., Toombs, N., Wong, K. K-H., Takbash, A., 2023. Earths Future. Evaluation of dynamically downscaled CMIP6-CCAM models over Australia. 
Purpose
To provide high-resolution climate data that can be used for species distribution modelling over Australia. 
Lineage
Data not provided. 
Method DocumentationData not provided.
Procedure Steps

1. 

Bioclimatic indices were calculated from dynamically and statistically downscaled CMIP6-CCAM data for minimum and maximum temperature and precipitation. Bias correction was applied to the downscaled CMIP6-CCAM dataset in two steps. 1) The downscaled CMIP6 outputs were regridded to the SILO 5-km grid using conservative remapping in Climate Data Operators (CDO). 2) SILO was used as the reference dataset to train the Quantile Mapping for Extremes (QME) model over 1975-2014. QME is a tailored univariate quantile-mapping approach designed to better correct biases in extremes while preserving the statistical characteristics of extreme events (Dowdy, A., 2023. A bias correction method designed for weather and climate extremes (No. 87), Bureau Research Report 087, Australian Bureau of Meteorology). The trained QME model was applied to bias-correct future projections for 2015-2100. Bioclimatic indices were derived using the R package dismo, Version 1.3-15. 

Spatial Description
The entire Australian continent. 
Temporal Coverage
From 1975-01-01 to 2099-12-31 
Spatial Resolution

Distance of 5000 Metres

Vertical Extent

Data not provided.

ANZSRC - FOR
Ecology
Global change biology
datastream
Model-Derived Gridded data
GCMD Sciences
ATMOSPHERE - AIR TEMPERATURE
ATMOSPHERE - RAIN
Horizontal Resolution
1 km - < 10 km or approximately .01 degree - < .09 degree
Parameters
annual mean temperature
annual total precipitation
isothemality
max temperature of warmest month
mean diurnal range
mean temperature of coldest quarter
mean temperature of driest quarter
mean temperature of warmest quarter
mean temperature of wettest quarter
min temperature of coldest month
precipitation of coldest quarter
precipitation of driest month
precipitation of driest quarter
precipitation of warmest quarter
precipitation of wettest month
precipitation of wettest quarter
precipitation seasonality
temperature annual range
temperature seasonality
Temporal Resolution
Climate Normal (30-year climatology)
Topic
biota
climatologyMeteorologyAtmosphere
environment
User Defined
Bioclimatic Indices
Climate Change
Species Distribution Modelling
Author
Toombs, Nathan
Ma, Shaoxiu
Co-Author
Chapman, Sarah
Trancoso, Ralph
Contact Point
Toombs, Nathan
Publisher
Terrestrial Ecosystem Research Network
Downscaled projections of bioclimatic indices for species distribution modelling in Australia - a case study for the greater glider
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The Creative Commons Attribution 4.0 International (CC BY 4.0) license allows others to copy, distribute, display, and create derivative works provided that they credit the original source and any other nominated parties. Details are provided at https://creativecommons.org/licenses/by/4.0/ 
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