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Large scale
climate variability influences
economics worldwide. The most
prominent example in this
context is the El Nino –
Southern Oscillation (ENSO)
phenomenon in the Central
Pacific. Recognizing and
understanding relationships
between climate and economics
may provide a valuable source of
information.
In this article we give a brief
description of work that we did
so far to develop a forecast
system useful for the
re-insurance industry. Climate
forecasts and socio-economic
variables are transformed into
predictions of insured damages.
Lead times range from 3 to 6
months. First results from a
feasibility study show that we
achieve significant predictive
skill on these time scales. The
system successfully predicts a
proxy for potential damages in
South-East-Asia over a period of
5 years.
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