High Resolution Projections Data

High-resolution climate change projections for Queensland using dynamical downscaling of CMIP5 global climate models are available for download in gridded format with spatial resolution of 10 km at Terrestrial Ecosystem Research Network (TERN).

The eleven downscaled Global Climate Models are listed below:

 

CMIP5 model name:	Model name:	Institution name(s):	Country of origin:
ACCESS1-0	Australian Community Climate and Earth-System Simulator, version 1.0	CSIRO & BoM	Australia
ACCESS1-3	Australian Community Climate and Earth-System Simulator, version 1.3	CSIRO & BoM	Australia
CCSM4	Community Climate System Model	NCAR	USA
CNRM-CM5	Centre National de Recherches Météorologiques Coupled Global Climate Model, version 5	CNRM & CERFACS	France
CSIRO-Mk3.6	Commonwealth Scientific and Industrial Research Organisation Mark 3.6.0	CSIRO & Qld Govt	Australia
GFDL-CM3	Geophysical Fluid Dynamics Laboratory Climate Model, version 3	GFDL NOAA	USA
GFDL-ESM2M	Geophysical Fluid Dynamics Laboratory Earth System Model with Modular Ocean Model, version 4 component	GFDL NOAA	USA
HadGEM2	Hadley Centre Global Environment Model, version 2	Met Office Hadley Centre	UK
MIROC5	Model for Interdisciplinary Research on Climate, version 5	AORI Japan	Japan
MPI-ESM-LR	Max Planck Institute Earth System Model, low resolution	Max Planck Institute	Germany
NorESM1-M	Norwegian Earth System Model, version 1 (intermediate resolution)	Norwegian Climate Centre	Norway

 

Projections are available for both moderate- and high-emissions scenarios – that is Representative Concentration Pathways 4.5 and 8.5 (RCP4.5 and RCP8.5 respectively). Visit the Understanding the data to learn more about our modelling strategy. A subset of five variables is available at daily time-step to facilitate other modelling initiatives. Four of them have also been bias-corrected against observations. Eight mean climate variables are available at monthly time-step, while a comprehensive set of 32 metrics is available at seasonal scale. The seasonal dataset is the same featured in the Queensland Future Climate Dashboard.

The future climate projections in high temporal resolution (e.g., daily scale) were aggregated into 20-year averages with changes and percent changes in relation to reference period 1886-2005 (termed "absolute-change" and "percentage-change" respectively). The data are available for calendar seasons – i.e., summer (December, January and February), autumn (March, April and May), winter (June, July and August) and spring (September, October and November). In addition, we also provide aggregated information for wet (November to April) and dry (May to October) periods as well as at annual basis. Modelled climatologies for the reference period 1986-2005 are also available (termed "climatologies").

For additional information about our spatial data products, refer to Queensland Future Climate Datasets documentation.

A set of 32 climate variables is available at TERN as per table below. Click on “RCP4.5” or “RCP8.5” for direct access to the 11 downscaled CMIP5 models and the ensemble averages for the two emissions scenarios. Data format is Network Common Data Form (NetCDF). It can be easily converted to other grid formats using free software – check example in R on the bottom of this page.

 

Climate theme	Variables	Daily		Monthly		Seasonal (long-term averages)
Mean Climate	Mean Temperature	RCP4.5	RCP8.5	RCP4.5	RCP8.5	RCP4.5	RCP8.5
	Minimum Temperature	RCP4.5	RCP8.5	RCP4.5	RCP8.5	RCP4.5	RCP8.5
	Maximum Temperature	RCP4.5	RCP8.5	RCP4.5	RCP8.5	RCP4.5	RCP8.5
	Precipitation	RCP4.5	RCP8.5	RCP4.5	RCP8.5	RCP4.5	RCP8.5
	Pan-evaporation	RCP4.5	RCP8.5	RCP4.5	RCP8.5	RCP4.5	RCP8.5
	Relative Humidity			RCP4.5	RCP8.5	RCP4.5	RCP8.5
	Surface Wind			RCP4.5	RCP8.5	RCP4.5	RCP8.5
	Solar Radiation			RCP4.5	RCP8.5	RCP4.5	RCP8.5
Bias-corrected Mean Climate	Bias-corrected Mean Temperature	RCP4.5	RCP8.5
	Bias-corrected Minimum Temperature	RCP4.5	RCP8.5
	Bias-corrected Maximum Temperature	RCP4.5	RCP8.5
	Bias-corrected Precipitation	RCP4.5	RCP8.5
Heatwaves	Heatwave Peak Temperature					RCP4.5	RCP8.5
	Heatwave Frequency					RCP4.5	RCP8.5
	Heatwave Duration					RCP4.5	RCP8.5
	Maximum Heatwave Duration					RCP4.5	RCP8.5
Extreme Temperature	Hot Days					RCP4.5	RCP8.5
	Hot Nights					RCP4.5	RCP8.5
	Warm Spell Duration					RCP4.5	RCP8.5
	Cold Spell Duration					RCP4.5	RCP8.5
	Cool Nights					RCP4.5	RCP8.5
	Very Hot Days					RCP4.5	RCP8.5
Extreme Precipitation	Maximum 1-day Precipitation					RCP4.5	RCP8.5
	Maximum 5-day Precipitation					RCP4.5	RCP8.5
	Extreme Wet Day Precipitation					RCP4.5	RCP8.5
	Simple Daily Intensity					RCP4.5	RCP8.5
	Consecutive Dry Days					RCP4.5	RCP8.5
	Consecutive Wet Days					RCP4.5	RCP8.5
SPI-Droughts	Frequency of Moderate Drought					RCP4.5	RCP8.5
	Frequency of Severe Drought					RCP4.5	RCP8.5
	Frequency of Extreme Drought					RCP4.5	RCP8.5
	Duration of Droughts					RCP4.5	RCP8.5
SPI-Floods	Frequency of Moderate Floods					RCP4.5	RCP8.5
	Frequency of Severe Floods					RCP4.5	RCP8.5
	Frequency of Extreme Floods					RCP4.5	RCP8.5
	Duration of Floods					RCP4.5	RCP8.5

 

Converting NetCDF files to the GeoTIFF Format

All high resolution datasets are provided in the NetCDF format, which is the standard used for climate modelling and forecasting. For users who require the GeoTIFF format, these NetCDF files can be readily converted. An example on how this can be achieved in R is shown below. Note that the R packages raster and ncdf4 are required for the script below.

# Load required R packages
library(raster)
library(ncdf4)
# Define input and output file paths
input_file <- "rnd24_Asea_ACCESS1-0Q_rcp85_r1i1p1_2005-2024-abs-change-wrt-1986-2005-seasavg-clim_CCAM10km.nc"
output_file <- "sample.tif"
# Read one variable from a NetCDF file
nc <- raster(input_file, varname="rnd24_djf")
# Write variable to a GeoTIFF file
writeRaster(x=nc, filename=output_file, format="GTiff", overwrite=TRUE, options=c("ALPHA=YES"))

This creates an GeoTIFF dataset for the variable "rnd24_djf" within the specified NetCDF file. Note that this only achieves a basic conversion without a colour palette, and so the image cannot be viewed on common software such as Windows Photo Viewer. More sophisticated GeoTIFF creation can be achieved using GIS software such as GDAL.