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Transcript
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 of Australia & Pacific dominated by ENSO on
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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
• 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)
• 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 NMSStakeholder 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’d)
Pacific Decadal Oscillation: More El
Nino-like or La Nina-like
behaviour for periods up to 20-30
years. Strong influence in AustNew 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
• 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 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 regionallydifferent outcomes.
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
• 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:
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data rescue;
data availability;
sustainable observational networks
Thank you for
listening.
….any questions?