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A Global Merged Land–Air–Sea Surface Temperature Reconstruction Based on Historical Observations (1880–1997)

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  • 1 NOAA/NESDIS/National Climatic Data Center, Asheville, North Carolina, and CICS/ESSIC, University of Maryland, College Park, College Park, Maryland
  • | 2 NOAA/NESDIS/National Climatic Data Center, Asheville, North Carolina
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Abstract

A merged land–air–sea surface temperature reconstruction analysis is developed for monthly anomalies. The reconstruction is global and spatially complete. Reconstructed anomalies damp toward zero in regions with insufficient sampling. Error estimates account for the damping associated with sparse sampling, and also for bias uncertainty in both the land and sea observations. Averages of the reconstruction are similar to simple averages of the unanalyzed data for most of the analysis period. For the nineteenth century, when sampling is most sparse and the error estimates are largest, the differences between the averaged reconstruction and the simple averages are largest. Sampling is always sparse poleward of 60° latitude, and historic reconstructions for the polar regions should be used with caution.

Corresponding author address: Dr. Thomas M. Smith, National Climatic Data Center, ESSIC, 4115 Computer and Space Sciences Bldg., University of Maryland, College Park, College Park, MD 20742-2465. Email: tom.smith@noaa.gov

Abstract

A merged land–air–sea surface temperature reconstruction analysis is developed for monthly anomalies. The reconstruction is global and spatially complete. Reconstructed anomalies damp toward zero in regions with insufficient sampling. Error estimates account for the damping associated with sparse sampling, and also for bias uncertainty in both the land and sea observations. Averages of the reconstruction are similar to simple averages of the unanalyzed data for most of the analysis period. For the nineteenth century, when sampling is most sparse and the error estimates are largest, the differences between the averaged reconstruction and the simple averages are largest. Sampling is always sparse poleward of 60° latitude, and historic reconstructions for the polar regions should be used with caution.

Corresponding author address: Dr. Thomas M. Smith, National Climatic Data Center, ESSIC, 4115 Computer and Space Sciences Bldg., University of Maryland, College Park, College Park, MD 20742-2465. Email: tom.smith@noaa.gov

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