AgriClimate Insights

An Interactive Climate Analysis for Australian Grain Growers and Researchers

This web application provides an easy-to-use platform for analysing climate data tailored for growers and researchers in Australia. It simplifies decision-making around sowing by making complex data accessible without the need for advanced computing skills.

Getting Started

What interests you?

  • Current (1950s-Now) or Future (Now-2100s)
    • Want an overall understanding? Check out the Summary
    • Explore a detailed understanding of your local Sowing Opportunity
    • Understand the changes surrounding Extremes

Please ensure to;

  • Register with a valid email for full data access as per SILO's policy.
  • Submit your data and click ‘Submit’ to view or update results.
  • Download reports or data directly from each page.

Need help? Visit our FAQ section or contact us via email.


Understanding a Sowing Opportunity

A 'Sowing Opportunity' arises when certain environmental conditions are met within a given time frame, which make it an ideal time to sow your seeds. Here are the factors that define a sowing opportunity: Sowing Window: This is the specific range of dates within a year when you are considering sowing. The choice of this window is often dependent on the crop type and the local climate conditions. Rain requirement: This refers to the total amount of rainfall that must be accumulated over a certain number of consecutive days within your sowing window to create suitable conditions for sowing. For instance, a standard definition for a sowing opportunity in our application could be: 'Between March 1st and April 30th, if there is an accumulated rainfall of 5mm over three consecutive days, then a Sowing Opportunity has arisen.' Please note that our application can also consider different levels of rain requirement, such as 15mm and 20mm, and calculate the sowing opportunities accordingly.

Exploring Multiple Sowing Opportunities

A unique feature of our application is the ability to explore multiple sowing opportunities. There may be times when you decide not to seize the first sowing opportunity due to various reasons. Hence, it’s beneficial to understand when the subsequent opportunities might arise. Our application calculates these sequential opportunities, helping you understand the frequency and potential advantages of waiting for the second or even third opportunity. Currently, the calculation for the next opportunity begins four days after the last day of the consecutive rainfall that defined the previous opportunity. This allows for a comprehensive exploration of sowing strategy within the context of fluctuating environmental conditions.

Where is the historic climate data coming from?

Our historic climate analysis relies on data procured through the weatherOz R package, specifically drawing from the SILO weather dataset. SILO is an extensive database of Australian climate data, encompassing records from 1889 to the present day . It offers daily meteorological datasets for a variety of climate variables, provided in formats that are readily usable for biophysical modelling, research, and climate applications. As an enabling technology, SILO allows researchers to concentrate on their work, liberating them from the intricacies of data preparation. Key features of SILO include: Nationwide coverage, with infilled values for missing data, and Ready-to-use datasets, available in various formats. Hosted by the Queensland Department of Environment and Science (DES), SILO originated in 1996 as a joint project between the Queensland Government and the Australian Bureau of Meteorology (BoM), under the sponsorship of the Land and Water Resources Research and Development Corporation. The datasets are compiled from observational data acquired from BoM and other providers.

Emission Projection Scheme Choices

Our platform provides you with the autonomy to select the emission projection scheme that aligns with your analysis. We currently offer two options: RCP4.5 and RCP8.5. Let’s delve into what these entail: RCP4.5: This represents a medium emissions scenario, where greenhouse gas emissions peak around the year 2040, and subsequently decline to levels below the present-day emissions by the end of this century. RCP8.5: On the other hand, RCP8.5 is considered a high emissions scenario, envisioning a future where emissions continue to ascend until 2100. These emissions scenarios illustrate potential trajectories of how changes in various socioeconomic factors could impact global concentrations of greenhouse gases. Such factors may encompass population and economic growth, technological evolutions, along with political and societal transitions. The climate modelling community developed these Representative Concentration Pathways (RCPs) to aid in the exploration of future emissions scenarios. For more comprehensive understanding of these emission scenarios, we recommend visiting this informative page:

Greenhouse Gas Scenarios
Understanding Climate Models

In our pursuit of depicting the future climate, it’s important to understand that no single model can be deemed absolutely correct or perfect. Each model provides a different representation of the future, thereby giving us an array of plausible modelled future climates. It is this variety that helps us form a more comprehensive picture of potential future scenarios. Below is a quick rundown of the models currently incorporated into our framework:

Selected Models Climate Futures Other
ACCESS1.0 Maximum consensus for many regions. This model exhibited a high skill score with regard to historical climate.
CESM1-CAM5 Hotter and wetter, or hotter and least drying This model was representative of a low change in an index of the Southern Annular Mode (per degree global warming). It also has results representing all RCPs.
CNRM-CM5 Hot/wet end of range in Southern Australia This model was representative of low warming/dry SST modes. It has a good representation of extreme El Niño in CMIP5 evaluations.
GFDL-ESM2M Hotter and drier model for many clusters This model was representative of the hot/dry SST mode. It also has a good representation of extreme El Niño in CMIP5 evaluations and has results representing all RCPs.
HadGEM2-CC Maximum consensus for many regions. This model has good representation of extreme El Niño in CMIP5 evaluations.
CanESM2 Hotter and wetter, or hotter and least drying This model was representative of the hot/wet SST mode. It has a high skill score with regard to historical climate and good representation of extreme El Niño in CMIP5 evaluations.
MIROC5 Low warming wetter model This model was representative of a higher change in an index of the Southern Annular mode (per degree global warming). It also has good representation of extreme El Niño in CMIP5 evaluations and has results representing all RCPs.
NorESM1-M Low warming wettest representative model This model was representative of the low warming/wet SST mode. The model also has results representing all RCPs.

To add further context, here’s some information about each model’s institute and resolution:

Model Institute
ACCESS1.0 CSIRO-BOM, Australia
CanESM2 CCCMA, Canada
NorESM1-M NCC, Norway
Where can I read more about future climate outlook?

Visit the CSA for anyone to use.

When complete, CSA will contain millions of data points for one location, providing a range of insights for farmers.

It’s currently being trialed across eight pilot regions to gather critical user feedback and input to ensure the platform is relevant to farmers and the wider agriculture sector.

In future, the underlying INDRA technology platform could be applied to other industry sectors impacted by climate change.


We value your feedback to enhance the application's functionality. Share your thoughts and suggestions via email at [email protected] .


The information provided by this application is for general informational purposes only. All information on the site is provided in good faith. However, we make no representation or warranty of any kind, express or implied, regarding the accuracy, adequacy, validity, reliability, availability, or completeness of any information on the site. Your use of the site and reliance on any information is solely at your own risk.


The weather data obtained from the SILO database hosted by the Queensland Department of Environment and Science, as well the future data from CSA Climate Services for Agriculture, under the Creative Commons Attribution 4.0 International (CC BY 4.0) licence.