Based on stakeholder consultation, the key climate variables for the electricity sector are temperature (maximum and minimum), rainfall, wind and Forest Fire Danger Index (FFDI), although other variables are also available. Selecting one of these variables will activate or deactivate relevant options in the menu for Intensity/Frequency.

Note that some datasets contain data for multiple variables in each file.

Extreme event intensities have been calculated for average return intervals (ARI) of 2, 5 and 10 years for temperature. Extreme event frequencies will be calculated for maximum temperature thresholds of 35, 40 and 45 °C and daily Forest Fire Danger Index (FFDI) thresholds of 25 (very high) and 50 (severe).

Regional climate changes are simulated by climate models in response to increases in greenhouse gases. Dozens of climate models are available, each with strengths and weaknesses. There isn't a single 'best' model, but the ESCI project has identified a subset of models that perform well over Australia and represent most of the range of projected changes in key climate variables such as temperature and rainfall.

The ESCI project recommends using three climate models as a starting point to represent the range of possible temperature changes.  Data for other climate models are also provided for those who want to explore additional climate change scenarios. For more information, see the Key Concepts —ESCI Recommended Data Sets – Testing and Validation.

You can filter the list for the 1986-2005 baseline (IPCC/ESCI standard) as well as projections for four future periods.

You can filter the list for selected seasons (e.g. Mar-May) or the whole year (Jan-Dec).

These periods represent the time-period over which the data have been averaged or summed (depending on the variable/dataset).

The following codes are used:

1. Annual (annual)
2. DJF (December to February, southern hemisphere summer)
3. MAM (March to May; southern hemisphere autumn)
4. JJA (June to August; southern hemisphere winter)
5. SON (September to November; southern hemisphere spring)

The rate of future climate change will be partly determined by future concentrations of greenhouse gases. A number of representative concentration pathways (RCPs) have been developed internationally, based on different assumptions about socio-economic change, technological change, energy transitions, land-use change, and emissions of greenhouse gases.

Choice of RCP may be guided by the context of the climate risk assessment, for example:

1. If the  risk assessment is required for financial reporting then the Taskforce on Climate-related Financial Disclosure (TCFD) recommends using scenarios that give a global warming of 2 °C and 4 °C by the year 2100.
2. The Climate Measurement Standards Initiative (CMSI) recommends using RCP2.6 for a 2 °C warming scenario and RCP8.5 for a 4 °C warming scenario.
3. AEMO ISP scenarios are each associated with specific RCPs.

The ESCI project recommends RCP4.5 (a medium concentration pathway giving a global warming of 0.9-2.4 °C by the year 2090) and  RCP8.5 (a high concentration pathway giving a warming of 3.2-5.4 °C by 2090).

For more details, see the Key Concepts —Choosing Representative Emissions Pathways (RCPs).

The data are available as a map image (.png file) or as a NetCDF file, on a 5 km grid.

NetCDF files can be imported to a GIS program (e.g. ESRI ArcView, QGIS) or viewed and analysed using programs such as Panoply (available free from NASA ).

The NetCDF format is widely used by climate scientists and sophisticated analyses and manipulation can be done using a range of scientific computer languages such as Python, R and Fortran.

Based on stakeholder consultation, the key climate variables for the electricity sector are temperature (maximum and minimum), rainfall, wind and Forest Fire Danger Index (FFDI), although other variables are also available. Selecting one of these variables will activate or deactivate relevant options in the menu for Intensity/Frequency.

Note that some datasets contain data for multiple variables in each file.

The rate of future climate change will be partly determined by future concentrations of greenhouse gases. A number of representative concentration pathways (RCPs) have been developed internationally, based on different assumptions about socio-economic change, technological change, energy transitions, land-use change, and emissions of greenhouse gases.

Choice of RCP may be guided by the context of the climate risk assessment, for example:

1. If the  risk assessment is required for financial reporting then the Taskforce on Climate-related Financial Disclosure (TCFD) recommends using scenarios that give a global warming of 2 °C and 4 °C by the year 2100.
2. The Climate Measurement Standards Initiative (CMSI) recommends using RCP2.6 for a 2 °C warming scenario and RCP8.5 for a 4 °C warming scenario.
3. AEMO ISP scenarios are each associated with specific RCPs.

The ESCI project recommends RCP4.5 (a medium concentration pathway giving a global warming of 0.9-2.4 °C by the year 2090) and  RCP8.5 (a high concentration pathway giving a warming of 3.2-5.4 °C by 2090).

For more details, see the Key Concepts —Choosing Representative Emissions Pathways (RCPs).

Use the check-boxes to filter the list of datasets by temporal resolution (time-step).

The data are available at daily and 30-minute time steps.  Note that 30-minute resolution data have not been biased-corrected (this bias must be allowed for when using the data). These are very large datasets which are intended for expert users.

Filter the list of datasets by location (multiple can be selected).

Start typing the name of the location of interest into the "Filter location results by keyword" box to show only matching locations (the list responds as you type).

The 168 locations can be view along with the transmission network by clicking Select on Map.

Regional climate changes are simulated by climate models in response to increases in greenhouse gases. Dozens of climate models are available, each with strengths and weaknesses. There isn't a single 'best' model, but the ESCI project has identified a subset of models that perform well over Australia and represent most of the range of projected changes in key climate variables such as temperature and rainfall.

The ESCI project recommends using three climate models as a starting point to represent the range of possible temperature changes.  Data for other climate models are also provided for those who want to explore additional climate change scenarios. For more information, see the Key Concepts —ESCI Recommended Data Sets – Testing and Validation.

The data are available as a text (.csv) file or as a NetCDF file.

The text files will open directly in Microsoft Excel, Libre Office or a text editor.

NetCDF files can be imported to a GIS program (e.g. ESRI ArcView, QGIS) or viewed and analysed using programs such as Panoply (available free from NASA ).

The NetCDF format is widely used by climate scientists and sophisticated analyses and manipulation can be done using a range of scientific computer languages such as Python, R and Fortran."