Optimal surface temperature reconstructions using terrestrial borehole data

Michael E. Mann, Scott Rutherford, Raymond S. Bradley, Malcolm K. Hughes, Frank T. Keimig

Research output: Contribution to journalArticlepeer-review

54 Scopus citations

Abstract

We derive an optimal Northern Hemisphere mean surface temperature reconstruction from terrestrial borehole temperature profiles spanning the past five centuries. The pattern of borehole ground surface temperature (GST) reconstructions displays prominent discrepancies with instrumental surface air temperature (SAT) estimates during the 20th century, suggesting the presence of a considerable amount of noise and/or bias in any underlying spatial SAT signal. The vast majority of variance in the borehole dataset is efficiently retained by its two leading eigenvectors. A sizable share of the variance in the first eigenvector appears to be associated with non-SAT related bias in the borehole data. A weak but detectable SAT signal appears to be described by a combination of the first two eigenvectors. Exploiting this eigendecomposition, application of optimal signal estimation methods yields a hemispheric borehole SAT reconstruction that is largely consistent with instrumental data available in past centuries, and is indistinguishable in it smajor features from several published long-term temperature estimates based on both climate proxy data and model simulations.

Original languageEnglish (US)
Pages (from-to)ACL 1-1 ACL 1-11
JournalJournal of Geophysical Research: Atmospheres
Volume108
Issue number7
DOIs
StatePublished - Apr 16 2003

All Science Journal Classification (ASJC) codes

  • Geophysics
  • Forestry
  • Oceanography
  • Aquatic Science
  • Ecology
  • Water Science and Technology
  • Soil Science
  • Geochemistry and Petrology
  • Earth-Surface Processes
  • Atmospheric Science
  • Earth and Planetary Sciences (miscellaneous)
  • Space and Planetary Science
  • Palaeontology

Fingerprint Dive into the research topics of 'Optimal surface temperature reconstructions using terrestrial borehole data'. Together they form a unique fingerprint.

Cite this