AgriClimate Insights

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.

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.

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.

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:

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:

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

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.