david s. chapman, robert n. harris and michael g. davis
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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. I t*. Concept: surface temperature - PowerPoint PPT PresentationTRANSCRIPT
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Surface Temperature Anomalies for the Medieval Warm Period, Little Ice Age, and 20th Century Warming Determined from Borehole
Temperatures
David S. Chapman, Robert N. Harrisand Michael G. Davis
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Concept:surface temperaturehistories have distinctive borehole temperature signatures.
It*
Snapshot at t*
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Mann et al. [2009], Global Signatures and Dynamical Origins of the Little Ice Age and Medieval Climate Anomaly, Science, 326, 1256 – 1260.
Medieval Climate Anomaly (MCA)
Little Ice Age (LIA)
Background I
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Mann et al. [2009], Science, 326.
MCA – LIA Temperature Difference in Proxy-based Temperature Reconstruction
Background II
1. Temp differences avoid “zero problem”2. Mean difference 0.24 °C3. Local differences > 1 °C4. Variability
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LIA MCA -0.5 0.0
LIA MCA-0.5 +0.25
Amplitude (oC) LIA MCA -0.5 +0.5
LIA MCA-0.25 +0.5
LIA MCA 0.0 +0.5
Temperature Anomaly (°C)
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Regions having multiple boreholes with depth > 600m
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N = 45
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N = 12
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N = 45
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Problems:Small sampleSuspicious profilesLack of thermal conductivity info.
N = 5
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Chapman & DavisEos, Sept 14, 2010
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Conclusions1. Borehole T(z) useful complement to multiproxy methods.
2. MCA, LIA, and recent warming have distinctive signatures in borehole temperature profiles (shape, amplitude, depth extent).
3. Four regions (NE N. America; S. Africa; Cent. Europe; Cent. Asia) do not have borehole T(z) anomalies identifiable as MCA, LIA.
a) Amplitudes no greater than suggested by Mann et al.
b) MCA/LIA stronger seasonal rather than annual signal?
c) Borehole temperature noise level too great.
4. Extensive warm period prior to 1000 CE inconsistent with baseline temperature from borehole studies
5. More deep (> 600 m) boreholes with thermal conductivity information needed.
6. If geog. variability real, less reliance on stacking.