Rainfall is perhaps the most widely used of all meteorological observations. While forecasting rainfall is particularly important in many domains, so is the ability to look back and find out how much rain and over what time frame it fell at a particular location or area. We have a range of products and services that can help you better understand rainfall events from last week, last month, last year, or even last decade.


Historical rainfall can be used in a range of industries for different purposes. Here are some examples of where our rainfall tools have been used :

  • Insurance - Evaluation of a specific event for household and motor vehicle insurance claims. This can be helpful to support a claim and also evaluate any possible fraudulent activity.
  • Construction - Understanding event severity to better evaluate response. If it was a particularly severe and uncommon event then damaged infrastructure might be replaced as is, whereas if damage was caused by a more common event it can indicate some redesign of the infrastructure may be required.
  • Civil Infrastructure - Understanding rainfall over a catchment and over a longer period of time, can be used to better model stream flow and prepare flood defences.
  • Agriculture - Get a better picture of rainfall distribution over a property.
  • Emergency Management - Model how rainfall affected the progression of bushfires and flood events.
  • Water management - Evaluate the volume of water flowing into, and through a property versus that which was collected directly on it.

Primary Observational Data

Sample AWS Data Graph

The main observational data that directly records, or indicates rainfall, that we can provide are :

Rain Gauge Network

Screenshot from our observations map showing the spread of rain gauges

Australia is a large, sparsely populated country. While we have a large network of AWS run by the Australian Bureau of Meteorology along with even more rain gauges run by the Bureau, local councils, governmental organisations and landholders, it by no means provides a detailed picture for a particular location or area of interest. You can access observations from all of these from our main observations map.

Observations from AWS and rain gauges provide accurate data but with relatively sparse spatial information, even in the areas with the highest concentration of gauges. Conversely weather radar can provide high spatial resolution (up to 250m), high precision (up to 160 levels), but with lower accuracy.

Radar Network

Sample radar image showing coverage from the Ceduna radar in South Australia

Australia has an extensive network of weather radars that cover a significant portion of the country, and often with duplicate coverage over some of the more widely populated areas. The high definition radar imagery seen to the right shows the strength of the reflection from rain droplets in the atmosphere at around 1.5km above the ground. The strength of this reflection in turn, generally correlates with the amount of rain at that location.

Estimating Rainfall

Screenshot from a sample output of rainfall estimation

It is possible to combine these two very different forms of rainfall observations to obtain very close to the best of both worlds. Rainfall estimation is possible for a very large part of the country (anywhere there is radar coverage) over a large period of time (over a decade), and with accuracy that is much better than just using one of the two data sources.

By also applying interpolation to the source radar data, we are able to help ensure that gaps that might appear in rainfall estimations due to fast moving storms is mitigated.

There are two main outputs from this process :

  • A downloadable timeseries of estimated rainfall for a particular location. For instance where there may have been storm damage, or an accident. This data can be immediately viewed as a graph, and also exported for using in your spreadsheet software (eg Excel) or other tools.
  • A NetCDF file that contains rainfall estimation over a broad area, with all available spatial data for every timestep. This could be the extent of the radar, or a subset covering a particular property, or catchment area. This can in turn be imported into GIS and flood software for further processing.

Typically these outputs are generated at 30 minute intervals as we can incorporate an integer number of 5, 6, 10 or 15 minute source data into 30 minutes. This can in turn readily be accumulated at longer intervals of an hour or a day. If you have a particular need for estimations at shorter intervals, as low as 1 minute for instance for an extremely high intensity storm then that is also possible.

Also provided is the ability do download raw timeseries rainfall data from the closest AWS and rain gauges to the point of interest.

You can find a sample of one such process here to get a better idea of what is possible.

If you’d like to find out more, pleae get in touch with details of your time period and location/s of interest.

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  • Last 8 hours of data on the live weather map (satellite and radar)
  • Last 8 hours of SD and HD radar imagery
  • Last 3 days of AWS, rain gauge and river height observations
  • Automatic update of live radar and observation data
  • Save your options between use
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