Technologies for climate risk management

Technologies for climate risk management

Australian businesses and public investments have largely been managed without reliable reference to the
extreme variability of our climate. Indeed, business decisions in climate sensitive industries have mostly
been driven by the expectations of average climatic conditions. This means that business decisions in
Australia generally do not factor the more sophisticated risk management knowledge and tools in climate risk that are becoming available. Additionally, we know Australia’s landscapes are unique and the related processes are very significantly driven by climate variability. This means that the management of natural resource issues such as salinity, water quality and water yield are significantly affected by our capacity to take into account climate variability and climate change.
We believe there is need to provide a major shift in our capability to cope with climate variability and
the potential further influence of long-term climate change. This may be achieved through a dedicated research program, preferably under a cooperative research centre model, to achieve the following:
• Foster strategically targeted research in climate science that underpins the development of new risk
management tools and improved climate related services.
• Create research programs in technology development that would be commercially driven to produce climate
risk technologies to meet the needs of service industries, rural industries, resource and environmental
industries.
• Develop research programs to build capacity that encompasses learning, extension, training, formal
education, knowledge management and communication. This would also incorporate R&D on the social
and economic context of climate risk management decision-making.
A major focus would be to add value to existing national infrastructure associated with the Bureau of
Meteorology Research Centre/CSIRO climate forecast system. Of prime importance will be to ensure that forecasts from the 'new generation' of climate models that can be readily used as input to the risk management technologies developed for a range of industry users.
There is need to focus on applying climate systems in key rural sectors such as dryland cropping, grazing,
forestry, and agri-business to improve profitability in those sectors and to reduce risk and inform policy
options. Additionally, climate risk technologies need to be incorporated into the whole value chain of production. Finally, there is need for better policy advice leading to more appropriate and responsive policies.
In terms of natural resource management issues there is need to focus on using climate risk knowledge and applying it to four key natural resource management (NRM) issues: water resource management, dryland salinity, soil erosion, and vegetation management. This should also lead to improved risk management of urban water resources through the application of climate knowledge so as to more efficiently provide water to users at lower risk of restrictions, to help defer construction of new storages and to improve environmental outcomes. There is need for enhanced capacity in making operational and strategic decisions by the water providers and a better informed user-community with a stronger rationale for altering their usage patterns in periods of water shortage.
Development of technologies for the quantification of property damage and the financial impact to
industries and regions susceptible to climate variability remain an elusive goal. Thus there is need to provide
R&D support to the insurance and lending industries to enable better quantification of the financial risk of
customers and support the development of risk-sharing, forward and options contracts to allow industries
to better manage their financial risk associated with climate variability and change. We need to focus
particularly on technologies for adaptive management. Better assessment of risk by industry and region will allow better credit risk assessment in lending and better quantification of the likely claims across local regions for insurance. This ability will allow better structuring of reinsurance programs, resulting in lower premiums and less cross subsidisation for customers.

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