Climate and weather forecasting
Most agricultural sectors are exposed to the vagaries of weather, which directly affects their productivity and economic return and indirectly affects them through global changes in prices. Next gen weather and climate forecasting capability and tools will help Australia’s agricultural and land management industries with enterprise planning, investment and profitable decision-making.
Digiscape’s climate projects
- Decadal climate forecasts project, led by Dr James Risbey
- Seamless provision of climate and weather data for agriculture, led by Dr Warren Jin
- Climate integration project, led by Dr Jaci Brown
What could the agricultural sector do if they had much longer term climate forecasts? We are harnessing our work developing a multi-year climate forecasting system to include key relevant Digiscape activities in beef, grains and carbon. We’re using our Climate Analysis Forecast Ensemble (CAFE) system to deploy advanced data assimilation and ensemble generation methods for high tech climate forecasting. We’re also generating a new set of forecasts every year for the World Meteorological Organisation’s World Climate Research Programme Decadal Climate Prediction Project.
A key challenge in advancing state-of-the-art climate forecast systems is to predict the onset of key climate modes of variability.
The primary aim of this project is to understand the basis of this climate variability and to forecast enough variability to be useful to sophisticated users of climate information such as land sector decision makers.
Paddock-scale and in-season forecasting
Each farming application responds to different features of the weather and climate as they unfold year by year. The success of a wheat crop, for example, is sensitive to the timing of rainfall through the year and whether it is accompanied by optimal temperatures and sunlight. On the other hand, the onset of the wet season is key to land managers in northern Australia. Having season-level forecasts could help farmers implement better management decisions for their particular enterprise.
Climate forecasts currently exist at ‘low res’ large scales (hundreds of kilometres) but we are turning them into paddock-scale, application-relevant information. A grain grower, for example, doesn’t just need to know that 70% above average rainfall is forecast for the year. But translating that into what variety of wheat to plant or how much nitrogen fertiliser to apply is where Digiscape is aiming to help.
We are integrating our expertise in weather and climate forecasting with individual Digiscape real-world use cases such as sugarcane, grains and aquaculture. We will explore what different weather and climate features each are sensitive to and quantify the confidence we can have in forecasts at the season-scale relevant to them.