Download 'NRM' Datasets

• Future Climatological Averages (stations)
• Fire Danger Index Summaries (stations)
• Future Gridded Change Data (native grid)
• Application-Ready Gridded (5 km) Datasets
• Thresholds Datasets (5 km Gridded)
• Application-ready Station Datasets
• Historical Datasets

This page provides download links for a range of data produced for the 'NRM' Projections that were released in 2015. For a summary of all available datasets, please download the CCiA NRM Data Delivery brochure (6.1 MB PDF).

For assistance understanding the NetCDF file names, check the CCiA file naming convention .

Future Climatological Averages (stations)

Application-ready climatological averages (annual, seasonal and monthly) are provided for all stations as downloadable spreadsheet files. Each file contains all data for all locations for a single variable.

Mean temperature (2.1 MB)

Maximum temperature (2.0 MB)

Minimum temperature (1.9 MB)

Relative humidity 9am (752.6 KB)

Relative humidity 3pm (752.6 KB)

pan evaporation (1.1 MB)

Fire Danger Index Summaries (stations)

This Excel spreadsheet contains summary and threshold FFDI data for all 39 stations for which data are available.  Future data are provided from three models for each of two emissions scenarios and four time periods. Historic data are also included.  Data provided are:

1. Average annual cumulative FFDI
2. Average days/year of High, Very High, Extreme and Catastrophic fire danger

Fire summary data (72.8 KB)

Future Gridded Change Data (native grid)

Projected change (compared with 1986-2005) data are available on the native model grid (see here for more information) for each of the 40+ available CMIP5 global climate models (GCMs) used for the 'NRM' projections (see the Technical Report for detail). These data provide the 20-year averaged monthly, seasonal and annual changes for four time periods centred on 2030, 2050, 2070 & 2090 using a time-slice method (see figure, below) for four greenhouse gas emissions pathways (RCP2.6, RCP4.5, RCP6.0 & RCP8.5).

Stylised depiction of the time-slice method for computing future change values. By computing the difference between the model's future and past values, any inherent model bias is removed.

The data are provided in NetCDF format (a multi-dimensional, self-describing file format commonly used in the climate science field) and are stored on a THREDDS server in a CMIP DRS compliant directory structure.

Horizontal datum: All gridded data are on the WGS84 geographic datum.

The free software, Panoply developed by NASA, is useful for viewing NetCDF data and can also export data to text and csv formats.

Instructions for importing NetCDF format into ArcGIS are provided here .

The links below provide shortcuts directly to the relevant data. If you have problems with downloads consistently failing, please check the CCiA News & Updates page for advice on any relevant outages or bugs. If there are no relevant outages or bugs listed, please contact us.

For many purposes (such as a quick first look at likely areas of greatest vulnerability), projected change relative to 1986-2005 is sufficient.

For detailed impact assessments though, you're likely to need to have data showing likely future temperatures, rainfall amounts etc., perhaps as time-series. If this is the case you can:

1. Use the "application-ready" datasets described below.
2. Apply the projected change values to observed data yourself. A range of observed data are available from the Bureau of Meteorology (see below) or you may have collected your own data using data loggers or similar. Note that the observed data should be aligned with the relevant baseline period of the projected change data – 1986–2005 (20 years) or 1981–2010 (30 years).

How To Access These Data:

Click the "Gridded change datasets" button below, then:

1. Click on the variable of interest
2. Click on the time-period of interest
3. You will then see a list of files
4. Click on the file you wish to download
5. The catalogue entry for the file will now appear. This includes multiple options for accessing the data.
6. To download a copy of the file, click the "HTTPServer" link (This will trigger the usual browser download process)
7. If you need to convert the file format, click on the "OPENDAP" link. On the next page, click the "Get ASCII" button in the top left. The file metadata and data will then be displayed in ASCII format and can be saved or copied.
8. If offered a choice, it is best to Save the file (opening the file from here is generally not a good idea)

Application-Ready Gridded (5 km) Datasets

These application-ready datasets combine gridded observed data with gridded climate projections to produce plausible future climate data at daily, monthly, seasonal and annual time steps on the high-resolution 5 km grid. These data are appropriate to use as inputs to quantitative impact assessment processes, such as crop growth modelling and species distribution modelling.

The datasets have been developed using a scaling approach. In this technique, high-quality observational 5 x 5 km gridded data (1981-2010 from the BoM AGCD ) have been modified by the projected monthly mean or decile/percentile changes from the global climate models. This produces internally consistent datasets that preserve the spatial and temporal relationships in the observations while also capturing some of the projected changes in climate variability from the climate model.

A detailed description of the method is available here

Limitations

1. As these datasets use the gridded observed datasets as a key input, the limitations of these gridded datasets flow through to the final dataset. The gridded observed data are produced using sophisticated techniques to 'infill' the data between BoM observing stations. The implications of this include:
   1. Comparison of the gridded data with a corresponding station will usually reveal differences. The size of these differences varies with location, and is largely dependent on the distance between observing stations and proximity to the coastline.
   2. The methods used for infilling space between stations results in the smoothing of the most extreme values. For this reason, the 'NRM' application-ready datasets underestimate daily extremes.
   3. As the method applies projected changes to a fixed set of historic observations, the resultant data do not completely represent changes to climate variability.
   4. As the 30-year observed time-series is modified by time-slice averaged changes, the resultant data represent a plausible future realisation of daily weather typical of the future mean climate state. Consequently, the time-series data for each future time period cannot be combined to form a continuous time-series spanning the whole of the 21^st Century.

The data are best regarded as plausible realisation of daily 'weather like' data that are consistent with the future mean state of the climate. The data are most useful for deriving daily statistics that describe the future climate. For example:

1. The daily maximum temperature data can be used 'as is' to analyse the number of days per year with maximum temperature greater than 35°C.
2. The daily data could be used as inputs to a crop growth model to derive statistics such as annual yield.

How To Access These Data:

The datasets are divided into two sets: Daily time-series files and Aggregated files containing Monthly, seasonal and annual data as time-series (Coming Soon!).

To access them, click the appropriate 'time-series' button, below, then:

1. Click on the variable of interest
2. Click on the time-period of interest
3. You will then see a list of files. See below for the explanation of the file naming convention.
4. Click on the file you wish to download
5. The catalogue entry for the file will now appear. This includes multiple options for accessing the data.
6. To download a copy of the entire file (approx. 1.2 GB), click the "HTTPServer" link. (This will trigger the usual browser download process.)
7. To download a subset of the file, click the "NetcdfSubset" link. This opens another window:
   1. You can adjust the 'bounding box' and 'time range' of the data to download.
   2. There is an option to add latitude and longitude fields to the data, which can be useful for some applications.
   3. Tick the checkbox next to the variable name on the left of the screen
   4. Choose the download format: NetCDF or NetCDF4 (stronger compression)
   5. Click the 'Submit' button (which will trigger your browser's usual download process).
8. If offered a choice, it is best to Save the file (opening the file from here is generally not a good idea)

For assistance understanding the file names, see the CCiA File Naming Convention .

Thresholds Datasets (5 km Gridded)

These datasets are derived from the gridded application-ready daily time-series described above. The data have been analysed to find the number of days (on average) when:

1. Maximum daily temperature exceeds: 30, 31, 32 ... 44, 45°C
2. Minimum daily temperature exceeds: 20, 21, 22 ... 29, 30°C
3. Minimum daily temperature is less than: 0, 2, 4, ... 20, 22°C

Results for annual, seasonal and monthly totals are provided.

Limitations

As these datasets are derived from the application-ready daily time-series described above, the same limitations apply to the thresholds datasets.

How To Access These Data:

Click the "Thresholds datasets (5 km gridded)" button below, then:

1. Click on the variable of interest
2. Click on the time-period of interest
3. You will then see a list of files. See below for the explanation of the file naming convention.
4. Click on the file you wish to download
5. The catalogue entry for the file will now appear. This includes multiple options for accessing the data.
6. To download a copy of the entire file (approx. 1.2 GB), click the "HTTPServer" link. (This will trigger the usual browser download process.)
7. To download a subset of the file, click the "NetcdfSubset" link. This opens another window:
   1. You can adjust the 'bounding box' and 'time range' of the data to download.
   2. There is an option to add latitude and longitude fields to the data, which can be useful for some applications.
   3. Tick the checkbox next to the variable name on the left of the screen
   4. Choose the download format: NetCDF or NetCDF4 (stronger compression)
   5. Click the 'Submit' button (which will trigger your browser's usual download process).
8. If offered a choice, it is best to Save the file (opening the file from here is generally not a good idea)

Application-ready station datasets (coming soon!)

These application-ready data are available for a selection of towns across Australia. Download individual model data in NetCDF format (from the full set of models) for high quality BoM stations.

Note that due to limitations in observed data availability, not all climate variables are available for every location.

How To Access These Data:

Click the "Application-ready town/location datasets" button below, then:

1. Click on the variable of interest
2. Click on the time-period of interest
3. You will then see a list of files. See below for the explanation of the file naming convention.
4. Click on the file you wish to download
5. The catalogue entry for the file will now appear. This includes multiple options for accessing the data.
6. To download a copy of the file, click the "HTTPServer" link. (This will trigger the usual browser download process.)
7. If offered a choice, it is best to Save the file (opening the file from here is generally not a good idea)

Historical Datasets

Gridded observed datasets (on request)

The gridded observed datasets that were used to produce the application-ready gridded datasets are available by contacting us . These datasets are available as daily and monthly time-series, spanning the 30-year period 1981-2010.

Please note that the licensing and/or terms of use varies from dataset to dataset. By using these data, you accept responsibility to check and comply with the associated license conditions and/or terms of use.

Bureau of Meteorology observations and trends

A wide range of observed data are available from the Bureau of Meteorology's Climate Data Online portal.

Clicking the button below will take you out of Climate Change in Australia, to the Bureau of Meteorology's website.

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