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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.

The Northern Australia Climate Program (NACP) is a fully integrated research, development and extension (RDandE) program operating across extensive pastoral regions of northern Australia. The NACP aims to improve existing climate models and forecast tools, develop new products to meet user needs and build the capacity of rangeland producers to manage the challenges posed by droughts (or failed wet seasons) and climate variability. Climate information gaps identified through earlier surveys of graziers and communities in rural and remote Australia informed the design of the research component of the NACP, which aims to address the low and variable accuracy of seasonal climate forecasts in many regions, the need for proof of value of forecasts and relevance of existing forecast systems and technologies, and perceived lack of effective support from climate experts for the use of climate resources and technologies in agricultural decision making. The development and extension components of the program aim to improve climate literacy and the use of climate information. Building on the research program, they deliver a climate service that provides local extension and technical support, with a focus on building trust in climate information through locally sourced, industry connected NACP trained and supported extension advisers called Climate Mates. Two-way information flow between decision makers and researchers, facilitated by the Climate Mates, ensures that forecasts and decision- and discussion-support tools developed through the program are regionally relevant and targeted to the needs of end users. Monitoring and evaluation of the program indicates that this approach is contributing to positive outcomes in terms of awareness and knowledge of climate forecasting and products, and their adoption and use in decision making (i.e. practice change). In the longer term, the Climate Mates have potential for enduring impact beyond the program, leaving a knowledgeable and trusted climate resource across regional northern Australia.

Year-to-year variability in rainfall has long been recognised as a major issue in managing livestock enterprises across Australia’s grazing lands. Extension products documenting rainfall variability have been developed over the last 30 years and have been keenly sought by producers and their advisors. This paper describes multi-year rainfall variability from 1889 to 2020 and provides the basis for classifying the 131 years of rainfall into 18 discrete Wet (7), Average (2) and Dry (9) periods as presented in the ‘Queensland’s Extended Wet and Dry Periods’ poster. The classification was consistent with: analysis of fluctuations and trends in the long-term time series of reported livestock numbers; drought declarations for government assistance; and documented periods of pasture resource degradation and recovery. Rainfall during the nine Wet and Average periods was +18% above the long-term average annual rainfall (LTAAR), in contrast to the Dry periods with −17% below LTAAR. Wet periods (including Average) were on average 7 years in duration, ranging from 5 to 9 years. Dry periods were on average 8 years in duration and ranged from 5 to 13 years. Detailed analysis of the effects of the El Niño Southern Oscillation (ENSO) phenomenon indicated that: (a) the Wet/Dry periods were dominated by different frequencies and amounts of rainfall in La Niña/El Niño years; (b) rainfall in ENSO neutral years was generally above and below average rainfall for the Wet or Dry periods respectively; (c) the frequency of ENSO year-types was less important than the overall rainfall surplus (or deficit) in La Niña (or El Niño) years within the Wet (or Dry) periods respectively; and (d) the timing of Wet and Dry periods was correlated with indices of quasi-decadal and inter-decadal variability in components (sea surface temperatures and atmospheric pressures) of the global climate system. Climatic risk assessment systems for grazing management at multi-year timescales are yet to be developed.

Seasonal climate forecasts (forecasts) aim to reduce climate-related productivity risk by helping farmers make decisions that minimise losses in poor years and maximise profits in good years. Most Australian forecast valuations have focused on fertiliser decisions to wheat operations, and few assessments have evaluated the benefit of incremental improvements of forecast skill. These gaps have limited our understanding of forecast value to the broader agriculture sector and the benefit of investments to improve forecast skill. To address these gaps, we consistently assessed forecast value for seven Australian case studies (southern grains, northern grains, southern beef, northern beef, lamb, cotton, and sugar). We implemented a three-stage methodology which consisted of engagement with industry practitioners; modelling production under different climatic and environmental conditions; and economic modelling to evaluate forecast value for eleven levels of forecast skill. Our results show that forecast value was often low and highly variable. Value was found to vary based on forecast attributes (forecast skill, resolution and state), industry application and prevailing conditions (environmental and market). This is the first Australian valuation study where the same methodological approach was applied across multiple industries, incremental improvements in skill were valued, and prevailing conditions were explicitly evaluated for impact on value.

Climate change will significantly impact the future viability and security of food production systems, with increased frequency and intensity of droughts, floods, storms and other extreme climatic events predicted in many regions. In order for food production systems to remain viable and resilient under a changing climate, novel approaches, which integrate risk management (i.e. adaptation) and risk transfer strategies, such as insurance, are required. We argue that the coordinated integration of risk management and risk transfer approaches will support greater resilience of food production systems under climate change. Conversely, if risk management and risk transfer strategies are not carefully integrated, there is potential to undermine adaptive capacity (e.g. insurance subsidies may dissuade farmers from investing in climate adaptation) and ultimately reduce the capacity of food production systems to cope with and recover from the adverse impacts of climate change. Here we propose a resilience-based conceptual framework for integrating risk management and risk transfer strategies along with four key principles, which we believe could underlie their successful integration and thus enhance food production system resilience under climate change. These are as follows: (1) pro-active investments in farmer climate adaptation rather than re-active disaster relief, (2) structuring of government subsidies around insurance and climate disaster relief to incentivise farmer climate adaptation, (3) rewarding farmer efforts towards climate adaptation with cheaper insurance premiums for those farmers that invest resources into climate adaptation and (4) recognising investments in the integration of farm climate adaptation and risk transfer schemes within the broader context of future climate disaster risk management and global food security. Such an integrated investment approach could substantially reduce future economic losses for farmers while also enhancing food security under climate change.

In recent decades Australia has experienced warmer temperatures and, in southern Australia declining rainfall, and climate change projections indicate that these trends are likely to continue. In southern Australia pasture growth patterns have changed with increased winter production but a contraction of the spring growing season and increased inter-annual variability of production. A range of options have been investigated to adapt farm businesses to the changing climate including feedbase, livestock management and diversification. The challenge for adaptation research is to better understand impacts and adaptation options for increases in extreme climate events, such as heatwaves, drought and intense rainfall events.

Seasonal climate forecasts (SCFs) provide opportunities for pastoralists to align production decisions to climatic conditions, as SCFs offer economic value by increasing certainty about future climatic states at decision-making time. Insufficient evidence about the economic value of SCFs was identified as a major factor limiting adoption of SCFs in Australia and abroad. This study examines the value of SCFs to beef production system management in northern Australia by adopting a theoretical probabilistic climate forecast system. Stocking rate decisions in October, before the onset of the wet season, were identified by industry as a key climate sensitive decision. The analysis considered SCF value across economic drivers (steer price in October) and environmental drivers (October pasture availability). A range in forecast value was found ($0–$14 per head) dependent on pasture availability, beef price, and SCF skill. Skillful forecasts of future climate conditions offered little value with medium or high pasture availability, as in these circumstances pastures were rarely overutilized. In contrast, low pasture availability provided conditions for alternative optimal stocking rates and for SCFs to be valuable. Optimal stocking rates under low pasture availability varied the most with climate state (i.e., wet or dry), indicating that producers have more to gain from a skillful SCF at these times. Although the level of pasture availability in October was the major determinant of stocking rate decisions, beef price settings were also found to be important. This analysis provides insights into the potential value of SCFs to extensive beef enterprises and can be used by pastoralists to evaluate the cost benefit of using a SCF in annual management.

Seasonal climate forecasts (SCFs) have potential to improve productivity and profitability in the sugar industry. However, they are often underutilised due to insufficient evidence of the economic value of the forecasts, especially when there is a level of uncertainty associated with SCFs. Here, we demonstrate the value of integrating SCFs at various forecast quality (skill) levels into seasonal irrigation planning for sugarcane farming. A seasonal forecast system based on ENSO (El Nino Southern Oscillation) phases was parameterised by forecast quality to predict seasonal precipitation tercile (i.e. wet, neutral and dry) categories. A bio-economic model was developed to determine water-yield-profit relationships. Sugarcane production under different climatic conditions and irrigation scheduling scenarios was simulated using the Agricultural Production Systems sIMulator (APSIM)-Sugar, calibrated using case study information from one of Australia’s major irrigated sugarcane growing regions. We then employed an expected profit approach to achieve an optimal profit, rather than the more conventional optimal yield, for plant and ratoon crops to quantify the potential value of using SCFs in sugarcane irrigation decision making. The results show that using skilled SCF systems in sugarcane irrigation decision making can help growers improve their gross margin compared to that achieved in the absence of climate information (economic value). With a perfect forecast of moderate climatic conditions, an average economic value of up to AUD 27 ha−1 per annum was achieved, while forecasts of moderate wet or dry conditions indicated gains of up to AUD 40 and 43 ha−1 per annum, respectively, and forecasts of extreme wet or dry conditions delivered economic gains of up to AUD 150 and 260 ha−1 per annum, respectively. With the current seasonal climate forecast skill of 60% (based on the ENSO phases forecasting system) in the case study region, an average gain of up to AUD 4.5 ha−1 per annum was realised, with up to AUD 6.2 and 7.1 ha−1 per annum, respectively, for moderate wet and dry forecasting and up to AUD 92 and 43 ha−1 per annum, respectively, for extreme wet and dry forecasting. Improvements in the skill and reliability of SCFs will be important for achieving greater productivity and/or profitability and the wider uptake of climate forecasts in agricultural decision making.

This research analyses the observed relationship between eastern and central Pacific El Niño Southern Oscillation (ENSO) events and Australian monsoon rainfall (AUMR) on a decadal timescale during the December to March monsoon months. To assess the decadal influence of the different flavours of ENSO on the AUMR, we focus on the phases of the Interdecadal Pacific Oscillation (IPO) over the period 1920 to 2020. The AUMR is characterized by substantial decadal variability, which appears to be linked to the positive and negative phases of the IPO. During the past two historical negative IPO phases, significant correlations have been observed between central Pacific sea surface temperature (SST) anomalies and AUMR over both the northeast and northwest of Australia. This central Pacific SST-AUMR relationship has strengthened from the first negative IPO phase (mid-1940s to the mid-1970s) to the second (late 1990s to mid-2010s), while the eastern Pacific SST-AUMR influence has weakened. Composite rainfall anomalies over Australia reveal a different response of AUMR to central Pacific El Niño/La Niña and eastern Pacific La Niña events during positive IPO and negative IPO phases. This research clearly shows that ENSO's influence on AUMR is modulated by Pacific decadal variability, however this teleconnection, in itself, can change between similar decadal Pacific states. Going forward, as decadal prediction systems improve and become more mainstream, the IPO phase could be used as a potential source for decadal predictability of the tendency of AUMR.

International audience; AbstractClimate strongly influences agricultural profitability. Climate risks on agriculture can be managed by moving production to other areas, but this may be costly and reduce profitability if climatic conditions are dynamic. Here, we test whether integrating spatial diversification and climate information could minimize climate risk, while not sacrificing profitability. We use 27 years of farm business profit and climate data (1991–2018) from four of Australia’s most climatically diverse regions where grazing underpins socioeconomic activity. We show that spatial diversification coupled with seasonal climate information from El Niño-Southern Oscillation (ENSO) provides better estimates of optimized risk-profit tradeoffs in different ENSO years compared to estimates without climate information. Conditional Value-at-Risk (CVaR) (a measure of financial risk) is lower when climate information is used in El Niño (1.23 $/ha), La Niña (1.19 $/ha), and Neutral years (1.22 $/ha), compared to when no climate information (1.57 $/ha) is used. When targeting high profits, CVaR is reduced by 15, 86, and 22% in El Niño, La Niña, and Neutral years, respectively, compared to a 5% reduction when no climate information is used. When aiming to minimize CVaR in drought (El Niño), profit is higher using climate-informed spatial diversification (expected profits of 2.71 $/ha), relative to when it is not (expected profits of 2.30 $/ha). Climate-informed spatial diversification also provides options to graziers to achieve much higher gains (expected profits of up to ~ 4.13 $/ha) under La Niña versus 2.62 $/ha when no climate information is used. Here, we show for the first time that seasonal climate information coupled with spatial diversification can provide strategies to help graziers reduce risk and increase profitability. Our approach is applicable to other parts of the world and could be used to decrease climate risk and increase profitability for other agricultural sectors exposed to variable climatic conditions.

From late January to early February 2019, a quasi-stationary monsoon depression situated over northeast Australia caused devastating floods, killing an estimated 625,000 head of cattle in northwest Queensland, and inundating over 3 000 homes in the coastal city of Townsville. The monsoon depression lasted ~10 days, driving daily rainfall accumulations exceeding 200 mm/day, maximum temperatures 8–10 °C below normal, and wind gusts above 70 km/h. In this study, the atmospheric conditions during the event and its predictability on the weekly to subseasonal range are investigated. Results show that during the event, the tropical convective signal of the Madden-Julian Oscillation was over the western Pacific, and likely contributed to the heavy rainfall, however the El Niño-Southern Oscillation was not in the usual phase for increased rainfall over Queensland. Over the northern Tasman Sea, an anticyclone helped maintain a positive phase of the Southern Annular Mode and promote onshore easterly flow. Somewhat consistent with these climate drivers, the monthly rainfall outlook for February issued by the Australian Bureau of Meteorology on 31 January provided no indication of the event, yet forecasts, not available to the public, of weekly-averaged conditions by the Bureau's dynamical subseasonal-to-seasonal (S2S) prediction system were more successful. For the week of 31 January to 6 February the prediction system forecast a more than doubling of the probability of extreme (highest quintile) weekly rainfall a week prior to the event, along with increased probabilities of extremely low (lowest quintile) maximum temperatures and extreme (highest quintile) wind speeds. Ensemble-mean weekly rainfall amounts, however, were considerably underestimated by the prediction system, even in forecasts initialised at the start of the peak flooding week, consistent with other state-of-the-art dynamical S2S prediction systems. Despite this, one of the individual ensemble members of the Bureau's prediction system did manage to forecast close to 85% of the magnitude of the rainfall across the most heavily impacted region of northwest Queensland a week before the event. Predicting this exceptional event beyond two weeks appears beyond our current capability despite the dynamical system forecasts showing good skill in forecasting the broad-scale atmospheric conditions north of Australia a week prior. Keywords: Extreme, Rainfall, Temperature, Flood, Forecast, Skill, Madden-Julian Oscillation, Subseasonal

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.

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 Nino 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 Nino events, and eight of the 12 widespread floods were associated with La Nina events. On a national scale droughts were associated with El Nino systems and wet events were associated with La Nina 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 Nino years (1997, 1987, 1982, 1972, 1965, 1941, 1932, 1911–14) and four of these were preceded by La Nina events (1996, 1971, 1964, 1910). There was evidence of anomalous frosts at lower altitudes (1450 m) and more frequent frosts at higher altitudes (> 2200 m) during clear skies in El Nino 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 Nino droughts in 10 of the 18 locations; however the success rates of La Nina flood warnings at these locations was lower (

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.

In Australia, as in other parts of the world, drought is a common climatic phenomenon causing significant social, economic, and environmental impact [37,91,107]. However, perhaps uniquely, drought in Australia has also driven significant adaptation. Australia’s agricultural production systems operate under a high level of uncertainty in terms of climate variability [82] and are renowned as some of the most resourceefficient, globally [25,65]. Australia has developed high-level research expertise in understanding climate systems and, to some extent, the drivers of drought [66,123]. It is also one of the few countries to have legislated a national drought policy aimed at managing drought risk [16,123]. This chapter provides an overview of Australia’s drought history, the ways in which drought risk and associated water scarcity have been managed over time, and the impact of drought on Australian landscapes, production systems, and communities. It looks at responses to drought from prehistorical evidence of Aboriginal Australians’ land use systems developed over thousands of years, through the challenges faced by European settlers in modifying conventional farming systems and adapting to the extremes of climate variability over the last 230 years, to current-day drought risk management and regional, state, and national governance around mitigating the impact of drought events and managing water scarcity. It starts by considering the role that research has taken in enhancing the understanding of the geophysical systems that influence climate variability, including drought, in Australia and concludes by considering the challenges Australia will face under future climates.

Seasonal climate forecasts (SCFs) have the potential to improve productivity and profitability in agricultural industries, but are often underutilised due to insufficient evidence of the economic value of forecasts and uncertainty about their reliability. In this study we developed a bio-economic model of forecast use, explicitly incorporating forecast uncertainty. Using agricultural systems (ag-systems) production simulation software calibrated with case study information, we simulated pasture growth, herd dynamics and annual economic returns under different climatic conditions. We then employed a regret and value function approach to quantify the potential economic value of using SCFs (at both current and improved accuracy levels) in decision making for a grazing enterprise in north-eastern Queensland, Australia – a region subject to significant seasonal and intra-decadal climate variability. Applying an expected utility economic modelling approach, we show that skilled SCF systems can contribute considerable value to farm level decision making. At the current SCF skill of 62% (derived by correlating the El Niño Southern Oscillation (ENSO) signal and historical climate data) at Charters Towers, an average annual forecast value of AU$4420 (4.25%) was realised for the case study average annual net profit of AU$104000, while a perfect (no regret) forecast system could result in an increased return of AU$13475 per annum (13% of the case study average annual net profit). Continued improvements in the skill and reliability of SCFs is likely to both increase the value of SCFs to agriculture and drive wider uptake of climate forecasts in on-farm decision making. We also anticipate that an integrated framework, such as that developed in this study, may provide a pathway for better communication with end users to support improved understanding and use of forecasts in agricultural decision making and enhanced sustainability of agricultural enterprises.

Interannual rainfall variability in Australia is a source of risk within agricultural industries. Insights into changes to rainfall and pasture-growth variabilities are essential to inform adaptation strategies for climate risk management within the grazing industry. We investigated shifts in rainfall and pasture-growth variabilities between the periods 1910–1960 and 1961–2010 for the pastoral zone in Australia. Rainfall variability was also assessed for the high-rainfall and wheat–sheep zones. An index of variability was calculated by using gridded rainfall and pasture-growth data for both periods. The percentage change was then calculated as the difference in variation between the two periods. Overall, the variability of annual rainfall has significantly increased (P < 0.01) between the two periods for the pastoral zone. Pastoral regions in the Northern Territory had the greatest increases in pasture-growth variability, with 62–85% of the area affected by a significant increase in variability. Between the periods 1910–1960 and 1961–2010 across the wheat–sheep zone, annual rainfall variability significantly decreased (P < 0.01), with 70% of the area having a negative change, whereas for the high-rainfall zone, the variability did not change significantly. Monitoring ongoing trends in rainfall and pasture-growth variability is important to inform strategic grazing management. Management practices to mitigate the impacts of increased variability in pastoral regions are discussed.

The grazing industries based on beef cattle and sheep are the major land use by area in Queensland, occupying greater than 80% of the State and contributing over 30% of total value of agricultural products in terms of meat, live animals and wool. Animals feed mostly on native and sown perennial grass pastures growing across a range of climates, soils and vegetation types. At both a location and regional scale, year-to-year variability in rainfall and other climatic variables is high, with the El Nino/Southern Oscillation phenomenon as a major cause.

Under the extensive grazing conditions experienced in Australia, pastoralists would benefit from a long lead- time 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 of0-2months.ThemajorityoflocationsshowingforecastqualitywereinnorthernAustralia(northof258S),predominately innorth-easternAustralia(northof258S,eastof1408E).Pastoralistsintheseareascannowapplykeymanagementdecisions withmoreconfidenceupto2monthsbeforetheNovember-Marchperiod.Usefullead-timesof3monthswerenotfound. Additional keywords: El Nino Southern Oscillation, forecast quality, hindcasting, Inter-decadal Pacific Oscillation, pastoralists.

The complexity, variability and vastness of the northern Australian rangelands make it difficult to assess the risks associated with climate change. In this paper we present a methodology to help industry and primary producers assess risks associated with climate change and to assess the effectiveness of adaptation options in managing those risks. Our assessment involved three steps. Initially, the impacts and adaptation responses were documented in matrices by ‘experts’ (rangeland and climate scientists). Then, a modified risk management framework was used to develop risk management matrices that identified important impacts, areas of greatest vulnerability (combination of potential impact and adaptive capacity) and priority areas for action at the industry level. The process was easy to implement and useful for arranging and analysing large amounts of information (both complex and interacting). Lastly, regional extension officers (after minimal ‘climate literacy’ training) could build on existing knowledge provided here and implement the risk management process in workshops with rangeland land managers. Their participation is likely to identify relevant and robust adaptive responses that are most likely to be included in regional and property management decisions. The process developed here for the grazing industry could be modified and used in other industries and sectors. By 2030, some areas of northern Australia will experience more droughts and lower summer rainfall. This poses a serious threat to the rangelands. Although the impacts and adaptive responses will vary between ecological and geographic systems, climate change is expected to have noticeable detrimental effects: reduced pasture growth and surface water availability; increased competition from woody vegetation; decreased production per head (beef and wool) and gross margin; and adverse impacts on biodiversity. Further research and development is needed to identify the most vulnerable regions, and to inform policy in time to facilitate transitional change and enable land managers to implement those changes.

Grazing is a major land use in Australia’s rangelands. The ‘safe’ livestock carrying capacity (LCC) required to maintain resource condition is strongly dependent on climate. We reviewed: the approaches for quantifying LCC; current trends in climate and their effect on components of the grazing system; implications of the ‘best estimates’ of climate change projections for LCC; the agreement and disagreement between the current trends and projections; and the adequacy of current models of forage production in simulating the impact of climate change. We report the results of a sensitivity study of climate change impacts on forage production across the rangelands, and we discuss the more general issues facing grazing enterprises associated with climate change, such as ‘known uncertainties’ and adaptation responses (e.g. use of climate risk assessment). We found that the method of quantifying LCC from a combination of estimates (simulations) of long-term (>30 years) forage production and successful grazier experience has been well tested across northern Australian rangelands with different climatic regions. This methodology provides a sound base for the assessment of climate change impacts, even though there are many identified gaps in knowledge. The evaluation of current trends indicated substantial differences in the trends of annual rainfall (and simulated forage production) across Australian rangelands with general increases in most of western Australian rangelands (including northern regions of the Northern Territory) and decreases in eastern Australian rangelands and south-western Western Australia. Some of the projected changes in rainfall and temperature appear small compared with year-to-year variability. Nevertheless, the impacts on rangeland production systems are expected to be important in terms of required managerial and enterprise adaptations. Some important aspects of climate systems science remain unresolved, and we suggest that a risk-averse approach to rangeland management, based on the ‘best estimate’ projections, in combination with appropriate responses to short-term (1–5 years) climate variability, would reduce the risk of resource degradation. Climate change projections – including changes in rainfall, temperature, carbon dioxide and other climatic variables – if realised, are likely to affect forage and animal production, and ecosystem functioning. The major known uncertainties in quantifying climate change impacts are: (i) carbon dioxide effects on forage production, quality, nutrient cycling and competition between life forms (e.g. grass, shrubs and trees); and (ii) the future role of woody plants including effects of fire, climatic extremes and management for carbon storage. In a simple example of simulating climate change impacts on forage production, we found that increased temperature (3°C) was likely to result in a decrease in forage production for most rangeland locations (e.g. –21% calculated as an unweighted average across 90 locations). The increase in temperature exacerbated or reduced the effects of a 10% decrease/increase in rainfall respectively (–33% or –9%). Estimates of the beneficial effects of increased CO2 (from 350 to 650 ppm) on forage production and water use efficiency indicated enhanced forage production (+26%). The increase was approximately equivalent to the decline in forage production associated with a 3°C temperature increase. The large magnitude of these opposing effects emphasised the importance of the uncertainties in quantifying the impacts of these components of climate change. We anticipate decreases in LCC given that the ‘best estimate’ of climate change across the rangelands is for a decline (or little change) in rainfall and an increase in temperature. As a consequence, we suggest that public policy have regard for: the implications for livestock enterprises, regional communities, potential resource damage, animal welfare and human distress. However, the capability to quantify these warnings is yet to be developed and this important task remains as a challenge for rangeland and climate systems science.

Survey methods were engaged to measure the change in use and knowledge of climate information by pastoralists in western Queensland. The initial mail survey was undertaken in 2000–01 (n = 43) and provided a useful benchmark of pastoralists climate knowledge. Two years of climate applications activities were completed and clients were re-surveyed in 2003 (n = 49) to measure the change in knowledge and assess the effectiveness of the climate applications activities. Two methods were used to assess changes in client knowledge, viz., self-assessment and test questions. We found that the use of seasonal climate forecasts in decision making increased from 36% in 2001 (n = 42) to 51% in 2003 (n = 49) (P = 0.07). The self-assessment technique was unsatisfactory as a measure of changing knowledge over short periods (1–3 years), but the test question technique was successful and indicated an improvement in climate knowledge among respondents. The increased levels of use of seasonal climate forecasts in management and improved knowledge was partly attributed to the climate applications activities of the project. Further, those who used seasonal forecasting (n = 25) didn’t understand key components of forecasts (e.g. probability, median) better than those who didn’t use seasonal forecasts (n = 24) (P > 0.05). This identifies the potential for misunderstanding and misinterpretation of forecasts among users and highlights the need for providers of forecasts to understand the difficulties and prepare simply written descriptions of forecasts and disseminate these with the maps showing probabilities. The most preferred means of accessing climate information were internet, email, ‘The Season Ahead’ newsletter and newspaper. The least preferred were direct contact with extension officers and attending field days and group meetings. Eighty-six percent of respondents used the internet and 67% used ADSL broadband internet (April 2003). Despite these findings, extension officers play a key role in preparing and publishing the information on the web, in emails and newsletters. We also believe that direct contact with extension officers trained in climate applications is desirable in workshop-like events to improve knowledge of the difficult concepts underpinning climate forecasts, which may then stimulate further adoption.

The Gascoyne–Murchison region of Western Australia experiences an arid to semi-arid climate with a highly variable temporal and spatial rainfall distribution. The region has around 39.2 million hectares available for pastoral lease and supports predominantly cattle and sheep grazing leases. In recent years a number of climate forecasting systems have been available offering rainfall probabilities with different lead times and forecast periods; however, the extent to which these systems are capable of fulfilling the requirements of the local pastoralists is still ambiguous. Issues can range from ensuring forecasts are issued with sufficient lead time to enable key planning or decisions to be revoked or altered, to ensuring forecast language is simple and clear, to negate possible misunderstandings in interpretation. A climate research project sought to provide an objective method to determine which available forecasting systems had the greatest forecasting skill at times of the year relevant to local property management. To aid this climate research project, the study reported here was undertaken with an overall objective of exploring local pastoralists’ climate information needs. We also explored how well they understand common climate forecast terms such as ‘mean’, ‘median’ and ‘probability’, and how they interpret and apply forecast information to decisions. A stratified, proportional random sampling was used for the purpose of deriving the representative sample based on rainfall-enterprise combinations. In order to provide more time for decision-making than existing operational forecasts that are issued with zero lead time, pastoralists requested that forecasts be issued for May–July and January–March with lead times counting down from 4 to 0 months. We found forecasts of between 20 and 50 mm break-of-season or follow-up rainfall were likely to influence decisions. Eighty percent of pastoralists demonstrated in a test question that they had a poor technical understanding of how to interpret the standard wording of a probabilistic median rainfall forecast. This is worthy of further research to investigate whether inappropriate management decisions are being made because the forecasts are being misunderstood. We found more than half the respondents regularly access and use weather and climate forecasts or outlook information from a range of sources and almost three-quarters considered climate information or tools useful, with preferred methods for accessing this information by email, faxback service, internet and the Department of Agriculture Western Australia’s Pastoral Memo. Despite differences in enterprise types and rainfall seasonality across the region we found seasonal climate forecasting needs were relatively consistent. It became clear that providing basic training and working with pastoralists to help them understand regional climatic drivers, climate terminology and jargon, and the best ways to apply the forecasts to enhance decision-making are important to improve their use of information. Consideration could also be given to engaging a range of producers to write the climate forecasts themselves in the language they use and understand, in consultation with the scientists who prepare the forecasts.

Researchers developing climate-based forecasts, workshops, software tools and information to aid grazier decisions undertook an evaluation study to enhance planning and benchmark impact. One hundred graziers in Western Queensland were randomly selected from 7 shires and surveyed by mail and telephone (43 respondents) to explore levels of knowledge and use of climate information, practices and information needs. We found 36% of respondents apply the Southern Oscillation Index to property decisions but 92% were unaware El Niño Southern Oscillation's predictive signal in the region is greater for pasture growth than rainfall, suggesting they may not recognise the potential of pasture growth forecasts. Almost 75% of graziers consider they are conservative or risk averse in their attitude to managing their enterprise. Mail respondents (n = 20) if given a 68%, on average, probability of exceeding median rainfall forecast may change a decision; almost two-thirds vary stocking rate based on forage available, last year's pasture growth or the Southern Oscillation Index; the balance maintain a constant stocking rate strategy; 90% have access to a computer; 75% to the internet and 95% have a fax. This paper presents findings of the study and draws comparisons with a similar study of 174 irrigators in the Northern Murray–Darling Basin (Aust. J. Exp. Ag. 44, 247–257). New insights and information gained are helping the team better understand client needs and plan, design and extend tools and information tailored to grazier knowledge, practice, information needs and preferences. Results have also provided a benchmark against which to measure project impact and have influenced the team to make important changes to their project planning, activities and methods for transferring technology tailored to grazier preferences.