Forecasting rainfall based on the Southern Oscillation Index phases at longer lead-times in Australia

Under the extensive grazing conditions experienced in Australia, pastoralists would benefit from a long leadtime seasonal forecast issued for the austral warm season (November–March). Currently operational forecasts are issued publicly for rolling 3-month periods at lead-times of 0 or 1 month, usually without an indication of forecast quality. The short lag between the predictor and predictand limits use of forecasts because pastoralists operating large properties have insufficient time to implement key management decisions. The ability to forecast rainfall based on the Southern Oscillation Index (SOI) phase system was examined at 0–5-month lead-times for Australian rainfall. The SOI phase system provided a shift of adequate magnitude in the rainfall probabilities (–40 to +30%) and forecast quality for the 5-month austral warm season at lead-times >0 months. When data used to build the forecast system were used in verification, >20% of locations had a significant linear error in probability space (LEPS) and Kruskal–Wallis (KW) test for lead-times of 0–2 months. The majority of locations showing forecast quality were in northern Australia (north of 25 degrees S), predominately in north-eastern Australia (north of 25 degrees S, east of 140 degrees E). Pastoralists in these areas can now apply key management decisions with more confidence up to 2 months before the November–March period. Useful lead-times of ≥3 months were not found

Integrating climate forecasts and geospatial systems to enhance grazing management in Northern Australia

Geospatial systems were a useful tool to assess climate variability and the impacts of climate variability on grazing management. They provided a mechanism for simplifying interpretation of highly variable and complex information, they provided a regional overview of spatial variability and useful interpolation between locations where no data was available. In this study we analyse daily rainfall data to determine the impacts of El Niño Southern Oscillation (ENSO) on the timing of break-of-season rain, follow-up rain and effective rain. In addition we use models to identify the impacts of ENSO on grazing management and we suggest how pastoralists can use the Southern Oscillation Index to increase profit, induce native pasture recovery, reduce the risk of overgrazing and reduce animal mortalities

Food shortages are associated with droughts, floods, frosts and ENSO in Papua New Guinea

In Papua New Guinea extreme climate events have occasionally led to the collapse of normal subsistence food production systems causing large scale food shortages that threaten human health and survival (e.g. during the 1997 El Niño drought). Production of staple foods (e.g. sweet potato) and cash crops (e.g. coffee) are adversely affected by drought,water logging and frost.We investigated the association between El Nino Southern Oscillation (ENSO), extreme climate events and reported food shortages. Over the 120 year period between 1890 and 2009, there have been 15 widespread droughts and 13 of these were associated with El Niño events, and eight of the 12 widespread floods were associated with La Niña events. On a national scale droughts were associated with El Niño systems and wet events were associated with La Niña systems. Since the early 1900s eleven major and widespread food shortages have been reported in the highlands but they have not been associated with drought alone but also with water surplus and frost. Eight of the eleven widespread food shortages were associated with El Niño years (1997, 1987, 1982, 1972, 1965, 1941, 1932, 1911–14) and four of these were preceded by La Niña events (1996, 1971, 1964, 1910). There was evidence of anomalous frosts at lower altitudes (1450 m) and more frequent frosts at higher altitudes (N2200 m) during clear skies in El Niño droughts that also contributed to food shortages. It is a combination of climatic extremes that causes the damage to crops that leads to a shortage of subsistence food in the highlands. The Standardised Precipitation Index provided a useful warning of success of more than 60% for El Niño droughts in 10 of the 18 locations; however the success rates of La Niña flood warnings at these locations was lower (b60%). Using seasonal climate forecasts based on ENSO and climate integrated crop models may provide early warning for farmers, industry agencies and government to help prepare for food shortages. Strategies that can help subsistence farmers cope with extreme climate events and the use, and value of seasonal climate forecast information are discussed

Methodology for producing the Drought Monitor

Drought is one of the most severe natural disasters Australia faces, inflicting serious impacts on the agricultural industry. An Australia-wide drought monitor has been developed to provide detailed and timely data regarding drought conditions that will aid producers and policy makers alike. The Drought Monitor development was an integral part of the Northern Australia Climate Program (NACP), a major partnership between Meat & Livestock Australia, the Queensland Government and the University of Southern Queensland. This document explains the methodology used to produce the monthly Drought Monitor

Risk matrix approach useful in adapting agriculture to climate change

A risk management approach to assessing climate change impacts was completed for grazing, wheat and sorghum production systems in eastern Australia. This ‘risk matrix’ approach for wheat and sorghum was compared to results from simulation modelling of the impacts of projected climate change from general circulation models (GCM’s). In the modelling we used five GCM’s, the A1FI emissions scenario and a baseline climate (historical, 1960–2010); both the ‘risk matrix’ approach and modelling used a time horizon of 2030. While some people find the risk matrix process a highly effective tool for assessing climate change impacts others question its utility without the support of quantitative data such as that produced from integrated climate and agricultural models. Here we show the impacts of climate change on wheat and sorghum production systems using both approaches, and also show the risk, adaptation responses and vulnerability of all three production systems using the ‘risk matrix’ approach. Advantages and disadvantages of each approach are identified. The independent assessment showed the two approaches produced similar results. The ‘risk matrix’ showed little overall impact, risk or vulnerability for the central slopes from climate change using the adaptation strategies currently available for yield, protein levels, pests and disease, weeds and soil condition. The simulation modelling showed no statistically significant impact on yield, drainage, erosion and runoff, although more high-end extremes were evident. The risks to 2030 from anthropogenic climate change can largely be managed by continuing to implement best management practice and managing the risks already posed by climate variability. The ‘risk matrix’ approach was a useful tool under these circumstances to assess the impacts, adaptation, risk and vulnerability of climate change in the absence of local modelling information, and demonstrates the power of expert opinion to help understand and respond to climate change at the regional scale

Native pastures and beef cattle show a spatially variable response to a changing climate in Queensland, Australia

Queensland's rangelands are an important source for Australia's pastoral food production. However, they are subject to significant climate variability and will be under increasing pressure as the climate changes, potentially leading to loss of productivity. Pasture growth fluctuates greatly due to rainfall variability, which unfortunately is the climate variable with the largest uncertainties in future projections for northern and eastern Australia. This sensitivity study examines the effect of climate change and its interaction with soil fertility and trees on pasture and livestock production in Queensland. Nine climate change sensitivities were tested in various combinations; an increase in air temperatures by a median projected value of +3 °C, rainfall changes of -20 %, -10 % and +10 % and an increase of carbon dioxide concentrations to 700 ppm. The GRASP model was used to assess the responses of pasture growth, pasture quality and cattle liveweight change per head. The most arid areas in western and south-western Queensland were the most sensitive to changes in rainfall. In contrast, the tropical north was the most resilient region. Southern and south-eastern Queensland benefitted from higher air temperatures producing greater pasture growth, quality and liveweight gain per head by extending the growing season and reducing frost during the winter months. The presence of trees competing for water and nitrogen increased the sensitivity of pasture to climate change, especially at higher carbon dioxide levels and lower rainfall. Increased carbon dioxide enhanced pasture growth and mitigated rainfall reductions by improving the water use efficiency of the plants. Thus, a warmer climate may create new opportunities in the south and south-east, but a warmer and drier climate in the western regions of Queensland is likely to reduce pasture and livestock production

Potential Climate Change Impacts on Beef Production Systems in Australia

There is increasing evidence suggesting that Australia\u27s climate is changing due to enhanced levels of greenhouse gases and that it will continue to change (Pittock 2003). Climate changes are partly established, however the impact on systems, industries and process are unclear. Industry distribution reflects climatically imposed boundaries and the relative profitability of alternative land use. Climate change may negatively impact some existing industries but create opportunities for others. This study provides an assessment of the likely impacts of plausible climate change on the beef industry in central Queensland

The Influence of Interannual and Decadal Indo-Pacific Sea Surface Temperature Variability on Australian Monsoon Rainfall

Monsoonal rainfall in northern Australia (AUMR) varies substantially on interannual, decadal, and longer time scales, profoundly impacting natural systems and agricultural communities. Some of this variability arises in response to sea surface temperature (SST) variability in the Indo-Pacific linked to both El Niño–Southern Oscillation (ENSO) and the interdecadal Pacific oscillation (IPO). Here we use observations to investigate unresolved issues regarding the influence of the IPO and ENSO on AUMR. Specifically, we show that during negative IPO phases, central Pacific (CP) El Niño events are associated with below-average rainfall over northeast Australia, an anomalous anticyclonic pattern to the northwest of Australia, and eastward moisture advection toward the date line. In contrast, CP La Niña events (distinct from eastern Pacific La Niña events) during negative IPO phases drive significantly wet conditions over much of northern Australia, a strengthened Walker circulation, and large-scale moisture flux convergence. During positive IPO phases, the impact of CP El Niño and CP La Niña events on AUMR is weaker. The influence of central Pacific SSTs on AUMR has been stronger during the recent (post-1999) negative IPO phase. The extent to which this strengthening is associated with climate change or merely natural internal variability is not known