Ground Cover Supplement : GC Supplement - Climate forecasting
6 seasonal forecasting by Janet Paterson to Make a weather forecast, meteorologists gather millions of pieces of weather information from ground stations, weather balloons, aeroplanes, satellites, ships, buoys and other observational points, which are then fed into computers, checked for accuracy and mapped onto a three- dimensional grid that covers australia. each grid point represents a snapshot of atmospheric pressure, temperature, moisture and wind speed for that area. in the 1970s, meteorological modellers divided the country into a 500-kilometre new approach models seasonal weather weather is influenced by many interconnected systems in the atmosphere, ocean and on land; small changes in one part of the world can impact on the weather in another part – days, weeks and even years later grid and performed calculations at nine levels of the atmosphere. today, they use a 75km grid and about 30 levels of atmospheric calculations are performed. the science underpinning weather forecasting has advanced considerably in the past 30 years and weather forecasts are now fairly accurate five to seven days ahead. CoMputer poWer this improvement is partly linked to advances in computer technology. faster computers enable more grid points to be used and finer-scale weather features to be modelled. However, it will still be many years before the grid can be reduced nationally to 5 to 10km – the size of a large thunderstorm and most relevant to the average grower. it will never be possible to predict individual weather events with total accuracy beyond about 14 days because it is not possible to accurately measure the current state of the atmosphere, land and oceans. Beyond about 14 days climate forecasts need to rely on average weather conditions, such as those used by the new dynamical climate model the Predictive ocean atmosphere Model for australia (PoaMa). neW ForeCastIng tool PoaMa is a dynamical climate model designed to predict climate up to nine months ahead. unlike statistical climate models, which use history to guide climate outlooks, the dynamical model combines climate data with physics knowledge about the atmosphere, oceans, land and ice to calculate climate conditions over australia for the coming three months. to provide a requested outlook the system uses a supercomputer to generate calculations on more than 40 million pieces of weather data sourced from around the globe. the seasonal climate outlooks generated by PoaMa are general statements about the likelihood of wetter- than-average or drier-than-average weather over a three-month season. as these are probabilistic outlooks (not categorical ‘yes/no’ forecasts) they are best used as part of a suite of farm risk-management tools. PoaMa provides better forecasts in autumn than the old statistical model. photo:CsIro Oceans store a wealth of climate information and are a key component of seasonal prediction. Argo floats (pictured) allow the continuous monitoring of the temperature, salinity and velocity of the upper 2000 metres of the ocean. There are more than 3500 Argo floats free-drifting in the world’s oceans. Information from the Argo floats is fed into computer models such as POAMA to generate seasonal weather forecasts. by understanding how climate drivers interact with rossby waves and blocking highs researchers will be able to improve the accuracy of five to seven-day forecasts, as well as the multi-week forecasts being made by Poama.
GC Supplement - Grain and Graze
GC Supplement - Profitable pulses and pastures