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Statistiske metoder i klimaforskning24. April,
2008, HCØ.

• Climate reconstructions using Proxy Data
• Peter Thejll
• Torben Schmith
• Bo Christiansen

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What are 'proxies'?

• Proxies are data that tell us about something
  else
• tree rings
• corals
• speleothemes
• sediment layers in lakes and oceans
• ice cores
• documentary information
• local (p,T,...) observations
• proxies of forcings

Pick your proxies based on what you want to
reconstruct
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How do you use proxies?

• 'Cook' the proxies to extract the relevant
  information
• 'Train' on some target series, often instrumental
  present-day data
• use
• averaging, weighting OLS!
• eigenmode-extraction from fields of proxies
  OLS!
• being careful with
• cross-correlated proxies
• auto-correlated proxies
• local proxies that by chance correlate with
  training series ('stationarity of patterns')

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Climate reconstructions are important because

• They tell us about the past
• Interpreting History (Vikings in Greenland,
  Decline of the Pueblo, Mayas )
• Interpreting the present climate (Medieval
  Warming was large/small) politics!
• If related to forcings they tell us about
• Climate Sensitivity
• Physics interest
• Prediction from Scenarios
• Internal or natural variability

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Our own effort to understand various
reconstruction techniques

• 6 or more reconstruction techniques tested on
  sandbox or surrogate data worlds, enabling
• know the answer testing purposes
• same input data reduce confusion
• Found
• Large variability among all methods
• No best method
• Importrace of training period

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Two tries, two results
Training on 1900s
Training on 1500s
Reconstructions of one realization of the
surrogate temperature fields with the six
different methods. Reconstructions are based on
57 white noise proxies, and the calibration
period is the last 100 years.
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Challenge

• Need to use first principles to design an
  optimum climate reconstruction method
• Consider climate system
• couplings
• Redundant data
• Help or obstruction?
• Forcings/Internal variability
• What causes climate to change?
• Better understanding of forcing mechanisms and
  internal variability gives better chance to
  understand which proxies can be used
• Can econometric methods help?
• Role of trends in training periods?
  (nonstationarity)
• Co-integration? (Proxies and climate should be
  intertwined, but are they I(1)?)