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David S. Chapman, Robert N. Harris and Michael G. Davis PowerPoint Presentation
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David S. Chapman, Robert N. Harris and Michael G. Davis

David S. Chapman, Robert N. Harris and Michael G. Davis

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David S. Chapman, Robert N. Harris and Michael G. Davis

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  1. Surface Temperature Anomalies for the Medieval Warm Period, Little Ice Age, and 20th Century Warming Determined from Borehole Temperatures David S. Chapman, Robert N. Harris and Michael G. Davis

  2. I t* Concept: surface temperature histories have distinctive borehole temperature signatures. Snapshot at t*

  3. Medieval Climate Anomaly (MCA) Background I Mann et al. [2009], Global Signatures and Dynamical Origins of the Little Ice Age and Medieval Climate Anomaly, Science, 326, 1256 – 1260. Little Ice Age (LIA)

  4. MCA – LIA Temperature Difference in Proxy-based Temperature Reconstruction Background II 1. Temp differences avoid “zero problem” 2. Mean difference 0.24 °C 3. Local differences > 1 °C 4. Variability Mann et al. [2009], Science, 326.

  5. Temperature Anomaly (°C) Amplitude (oC) LIA MCA -0.5 +0.5 LIA MCA -0.5 0.0 LIA MCA -0.5 +0.25 LIA MCA -0.25 +0.5 LIA MCA 0.0 +0.5

  6. Regions having multiple boreholes with depth > 600m

  7. N = 45

  8. N = 12

  9. N = 45

  10. N = 5 Problems: Small sample Suspicious profiles Lack of thermal conductivity info.

  11. Chapman & Davis Eos, Sept 14, 2010

  12. Conclusions • Borehole T(z) useful complement to multiproxy methods. • MCA, LIA, and recent warming have distinctive signatures in borehole temperature profiles (shape, amplitude, depth extent). • Four regions (NE N. America; S. Africa; Cent. Europe; Cent. Asia) do not have borehole T(z) anomalies identifiable as MCA, LIA. • Amplitudes no greater than suggested by Mann et al. • MCA/LIA stronger seasonal rather than annual signal? • Borehole temperature noise level too great. • Extensive warm period prior to 1000 CE inconsistent with baseline temperature from borehole studies • More deep (> 600 m) boreholes with thermal conductivity information needed. • If geog. variability real, less reliance on stacking.