Virtual world technologies to enhance climate risk management on Australian sugar cane farms

Improved climate risk decision-making and management in agriculture is critical to the well-being and long-term sustainability of farming communities and future global food security. Decision-making on farms often makes assumptions about seasonal conditions and weather events over the cropping season. Projected climate change and increasing climate variability are likely to pose increasing challenges to the productivity and profitability of farming systems. Hence, better understanding of climate information may improve farmers' ability to plan for climate risk. Digital technologies offer an important alternative in the delivery and communication of agricultural information, complementing and expanding the reach of conventional face-to-face agricultural extension services, particularly where these are subject to declining levels of investment. Sophisticated digital platforms and their applications in learning environments also offer new opportunities which may influence and significantly enhance agricultural knowledge exchange. This paper reports on a project undertaken by the University of Southern Queensland's Australian Digital Futures Institute and International Centre for Applied Climate Sciences to develop and evaluate a web-based virtual 'discussion-support' system that integrates climate information with practical farming operations in Australian sugar farming systems. Customized video clips (machinima), created in the Second Life virtual world environment, use lifelike avatar actors to model conversations about climate risk and key farm operational decisions relevant to sugarcane farmers. Designed to be readily available online, this innovative approach is designed to provide more equitable and cost-effective access to targeted climate information as well as improved learning and decision-making opportunities at local, regional, national and even global scales

Sweet success: virtual world tools enhance real world decision making in the Australian sugar industry

Investigating the impact of a web-based, ‘discussion-support’, agricultural-climate information system on Australian farmers’ operational decision making

Spatial and temporal scales of future climate information for climate change adaptation in viticulture: A case study of User needs in the Australian winegrape sector

Background and Aims: Which characteristics make future climate change information valuable for on-ground decision making for adaptation in the winegrape sector? And at what spatial and temporal scales will it be needed by Users? Methods and Results: Thi

Linear and nonlinear statistical analysis of the impact of sub-tropical ridge intensity and position on south-east Australian rainfall

The intensity and position of the sub-tropical ridge (STR) have strong relationships with rainfall variability in southern Australia. The combined effect of intensity and position in March-April-May (MAM) and June-July-August (JJA) is the focus of this research. Linear statistics were used first: area-averaged and Australia-wide spatial correlations of STR intensity and position with precipitation in south-west eastern Australia reveal that STR intensity has a much stronger and more widespread relationship with precipitation in both seasons. Over time, these relationships vary in magnitude and spatial extent with the sign of the correlation changing between two 50-year epochs. These nonlinearities were investigated further using classification trees. Area-averaged precipitation data (terciles) for south-west eastern Australia was classified on the basis of STR intensity and position. In both seasons the classification trees identify STR intensity as the primary partition defining the dry group, supporting the linear analysis. In the transition season of MAM, the time of year when the mean position of the STR is more southerly, STR position is important in distinguishing between a 'winter-like' and a 'summer-like' wet groups, providing STR intensity is low. Vector wind analyses were computed to explain the composite seasonal precipitation anomaly results in terms of different circulation patterns associated with these two wet groups. The frequency of wet and dry cases in each group was examined with changes evident over the recent years. The research confirms that STR intensity is more important than STR position in explaining inter-annual rainfall variability across southern Australia but also demonstrates the additional role of STR position in MAM. These results explain the low correlation between rainfall and STR position and why this relationship has evolved during the 20th century as the mean location of the STR has shifted south in MAM

The Potential of Tree Rings in Eucalyptus pauciflora for Climatological and Hydrological Reconstruction

We investigate the causes of variability in a tree-ring chronology comprising data from Eucalyptus pauciflora Sieb. Ex. Spreng. at the alpine treeline on the Kosciuszko Plateau in New South Wales, Australia. Following verification of crossdating in a subset of the available data, we found that ring width correlates significantly with net radiation, precipitation and mean minimum and maximum air temperature during the preceding winter and spring of the growing season. Our results for spring are consistent with the impact of climate on tree growth in alpine woodlands reported in previous studies. Analyses of snow-depth data revealed negative correlations with ring width throughout winter and spring. Our results indicate that low temperature and high precipitation during winter negatively affect the growth of E. pauciflora by prolonging spring snow cover. Ring width also correlates significantly with an index of soil dryness and flow in rivers with their headwaters in the Kosciuszko plateau. Given the apparent sensitivity of our chronology to climate and snow conditions, our results suggest that tree-ring chronologies comprising data from E. pauciflora at the alpine treeline have potential for climatological and hydrological reconstruction in southeast Australia

How potentially predictable is northern European winter climate a season ahead?

We estimate the potential predictability of European winter temperature using factors based on physical studies of their influences on European winter climate. These influences include sea surface temperature patterns in different oceans, major tropical volcanoes, the quasi-biennial oscillation in the tropical stratosphere, and anthropogenic climate change. We first assess the predictive skill for winter mean temperature in northern Europe by evaluating statistical hindcasts made using multiple regression models of temperature for Europe for winter and the January-February season. We follow this up by extending the methodology to all of Europe on a 5° × 5° grid and include rainfall for completeness. These results can form the basis of practical prediction methods. However, our main aim is to develop ideas to act as a benchmark for improving the performance of dynamical climate models. Because we consider only potential predictability, many of the predictors have estimated values coincident with the winter season being forecast. However, in each case, these values are predictable on average with considerable skill in advance of the winter season. A key conclusion is that to reproduce the results of this paper, dynamical forecasting models will require a fully resolved stratosphere

Extending extension: virtual shed meetings in a digital age

There are many important decisions that need to be made to ensure the economic and environmental viability of farming enterprises and farming communities. These include farm-level decisions about cropping patterns, investment in fertilizers and pesticides, plant population densities, irrigation regimes and the timing of planting and harvesting activities. Such decisions are predominantly aimed at optimising farm production, profitability and sustainability; however, their outcome can be influenced by seasonal conditions and weather events over the growing season. Ready access to improved regional climate information at time scales appropriate to on-farm decision making is likely to be of growing importance, particularly in regions subject to increasing climatic variability. Advances in digital technologies, their development and application in learning environments, and the steadily spreading web of the NBN across Australia suggest that web-based platforms may provide a valuable approach to the cost-effective extension of agricultural-climate information. This paper reports on the development and deployment of a web-based 'virtual' discussion-support system for integrating climate information with practical farming operations. It utilises cutting-edge developments in educational web-based tools, such as video clips created in the virtual world of Second Life, to inform sugarcane farmers' decisions around sustainable farming practices. These videos will use lifelike avatar actors and real-world, climate-based scenarios relevant to the lives and practices of sugarcane farmers to stimulate discussion amongst farmers around how to incorporate an understanding of climate risk into their decision-making. The video clips will be housed on a web portal designed around the notion of 'discussion support' and accessible by a range of mobile digital devices. The project will take an interactive research design-based approach to evaluating and further developing the web portal and digital tools to optimise their value to on-farm operational decision-making. It is envisaged that this web-based 'virtual' discussion-support system has potential to be extended to provide regionally-customised support to farmers around the world for improved decision-making and climate risk management