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Cited by 325

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

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

Open access
Smith, Thomas M., Reynolds, Richard W.·2005·Journal of Climate

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.

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Crossref · 10.1175/jcli3362.1

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Metadata

Authors
Smith, T. M., & Reynolds, R. W.
Venue
Journal of Climate
Published
2005-06-15
Volume
18
Issue
12
Pages
2021-2036
ISSN
  • 0894-8755 (ISSN-L)
  • 1520-0442
OpenAlex
W2099336108
Cited by
325
References
1
FWCI
14.42
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: A Global Merged Land–Air–Sea Surface Temperature Reconstruction Based on Historical Observations (1880–1997). https://app.cochat.ai/papers/10.1175/jcli3362.1
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Smith, T. M., & Reynolds, R. W. (2005). A Global Merged Land–Air–Sea Surface Temperature Reconstruction Based on Historical Observations (1880–1997). Journal of Climate. https://doi.org/10.1175/jcli3362.1

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.