Climate variability and change: implications for CAT insurance and weather risk management

1. Climate variability and change: implications for CAT insurance and weather risk management Dr William Wright Team Leader ET1.2 - Expert Team on Observing requirements and standards for climate, National Climate Centre, Bureau of Meteorology, 700 Collins St, Melbourne 3001 Australia. Ph: (61 3) 9669 4457 e-mail: w.wright@bom.gov.au

2. CLIMATE VARIABILITY • Climate of Australia & Pacific dominated by ENSO on year to year time-scales • Leads to opportunities for seasonal prediction as basis for decision-making in climate-sensitive activities • Well-established system in Australia, providing 3-month temperature and rainfall outlooks. • Predictions issued as probabilities. This has caused some problems with target audience. • Predictions not always correct. - loss of faith among some, but - some take view that, given decisions needed anyway, good to have even imperfect guidance.

3. USE OF SEASONAL PREDICTIONS • Practical: change decisions to minimise adverse phases/capitalise on favorable • Government policy on, e.g., drought relief informed partly by predictions, but mainly be antecedent conditions • Hedging/weather derivatives: In Australia, there’s been some limited work on offsetting seasonal climate risk, including the risk of inaccurate predictions, via weather derivatives.

4. CLIMATE VARIABILITY (Cont’d) • Project funded by AusAID to extend Australian prediction capacity to Pacific Island countries. • Project provided specially-tailored PC software. • Good results obtained, and lessons learned, from in-country training programs, and then facilitating NMS-Stakeholder workshops. • First phase – nine countries. Now being funded for another three years, and extended to Papua-New Guinea. Focus in Phase 2 is on pilot projects

5. CLIMATE VARIABILITY (Cont’d) Pacific Decadal Oscillation: More El Nino-like or La Nina-like behaviour for periods up to 20-30 years. Strong influence in Aust-New Zealand in 20th Century. No practical predictability. However, interannual (ENSO) predictability adversely affected during “warm” phase of PDO. Other influence on longer-term time-scales is Southern Annular Mode (SAM) – affects position of subtropical ridge, therefore southern Australian rainfall. Decadal time-scales, possibly long-term trend.

6. CLIMATE CHANGE • Well accepted that anthropogenic (human-influenced) CC is happening, and will continue to increase. • Major potential impacts in Australia (increased drought, severe storms, less water, more fires and land degradation, fewer frosts). Similar in Pacific plus sea-level rise. • Broadscale scenarios produced,based on IPCC scenarios. • Attempts to downscale to regional scales not yet well developed.

7. CLIMATE CHANGE (Cont’d) • Climate change is not necessarily gradual – could jump suddenly from one state to another. Not well captured in current models • Climate change affects not just temp/rainfall, but broadscale circulation patterns, giving regionally-different outcomes.

8. CLIMATE CHANGE (CONT’d) • To support UNFCCC goals re CC adaptation, require adequate observations for: - monitoring & attribution; - defining extremes; - adaptation, especially to support models, including downscaling - observations must support major climate zones, significant socio-economic regions, and vulnerable areas. Unfortunately WMO have concluded that the observational base to support this is in many cases inadequate.

9. SUMMARY/IMPLICATIONS • El Nino, etc influence climate variability – can potentially be used to manage risk • Climate change (& decadal variability) can affect the long-term statistical relationships (e.g., ENSO-climate) • Climate change monitoring & adaptation requires good data • Therefore, there is a clear need to resource: - data rescue; - data availability; - sustainable observational networks

10. Thank you for listening. ….any questions?