Climate variability and change implications for cat insurance and weather risk management
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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.

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

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Climate variability and change implications for cat insurance and weather risk management

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: [email protected]


Climate variability

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.


Use of seasonal predictions

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.


Climate variability cont d

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


Climate variability cont d1

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.


Climate change

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.


Climate change cont d

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.


Climate change cont d1

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.


Summary implications

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


Climate variability and change implications for cat insurance and weather risk management

Thank you for listening.

….any questions?


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