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Cited by 2,040Climate variability and modelsClimate Change and Environmental ImpactGeology and Paleoclimatology Research

Uncertainty estimates in regional and global observed temperature changes: A new data set from 1850

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Brohan, P., Kennedy, J. J., Harris, I., Tett, S. F. B., Jones, P. D.·2006·Journal of Geophysical Research: Atmospheres
DOI 10.1029/2005jd006548
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Abstract

The historical surface temperature data set HadCRUT provides a record of surface temperature trends and variability since 1850. A new version of this data set, HadCRUT3, has been produced, benefiting from recent improvements to the sea surface temperature data set which forms its marine component, and from improvements to the station records which provide the land data. A comprehensive set of uncertainty estimates has been derived to accompany the data: Estimates of measurement and sampling error, temperature bias effects, and the effect of limited observational coverage on large‐scale averages have all been made. Since the mid twentieth century the uncertainties in global and hemispheric mean temperatures are small, and the temperature increase greatly exceeds its uncertainty. In earlier periods the uncertainties are larger, but the temperature increase over the twentieth century is still significantly larger than its uncertainty.

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  • Our approach to building an uncertainty budget for GHCNm v4 temperatures broadly follows methods described in Brohan et al. (2006) and Morice et al. (2012) that have been applied to the CRUTEM dataset.

    “Our approach to building an uncertainty budget for GHCNm v4 temperatures broadly follows methods described in Brohan et al. (2006) and Morice et al. (2012) that have been applied to the CRUTEM dataset (Jones et al. 2012).”

    From The Global Historical Climatology Network Monthly Temperature Dataset, Version 4 (2018) · cites this paper as Brohan et al. 2006

  • The sampling distribution of the base period mean (climatological normal) has a standard deviation of s_w / sqrt(P), where s_w is the standard deviation of the monthly temperatures for a particular calendar month and P is the number of years in the base period.

    “As Brohan et al. (2006) note, the sampling distribution of the base period mean (climatological normal) has a standard deviation of s w / ffiffiffi P p , where s w is the standard deviation of the monthly temperatures for a particular calendarmonthand P is the number of years in the base period.”

    From The Global Historical Climatology Network Monthly Temperature Dataset, Version 4 (2018) · cites this paper as Brohan et al. (2006)

  • The inability of the PHA (or other algorithms) to resolve small systematic shifts in the temperature series is evident in Fig. 3 and has been discussed in previous analyses.

    “The inability of the PHA (or other algorithms) to resolve small systematic shifts in the temperature series is evident in Fig. 3 and has been discussed in previous analyses (e.g., Brohan et al. 2006; Menne and Williams 2009; Menne et al. 2009).”

    From The Global Historical Climatology Network Monthly Temperature Dataset, Version 4 (2018) · cites this paper as Brohan et al. 2006

  • Brohan et al. (2006) reckoned that undetected shifts in the CRUTEM dataset roughly follow a Gaussian distribution with a mean of zero and a standard deviation of 0.4 and that the average interval between undetected shifts was on the order of 40 years.

    “Using some national homogenization efforts as case studies, Brohan et al. (2006) reckoned that undetected shifts in the CRUTEM dataset roughly follow a Gaussian distribution with a mean of zero and a standard deviation of 0.4 and that the average interval between undetected shifts was on the order of 40 years.”

    From The Global Historical Climatology Network Monthly Temperature Dataset, Version 4 (2018) · cites this paper as Brohan et al. (2006)

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Authors
Brohan, P., Kennedy, J. J., Harris, I., Tett, S. F. B., & Jones, P. D.
Affiliations
  • Met Office (GB)
  • University of East Anglia (GB)
ORCID
Venue
Journal of Geophysical Research: Atmospheres
Publisher
American Geophysical Union (AGU)
Published
2006-06-24
Volume
111
Issue
D12
ISSN
0148-0227 (ISSN-L)
DOI
10.1029/2005jd006548
OpenAlex
W1979440117
Cited by
2,040
References
0
Citations by year
2026: 19 · 2025: 34 · 2024: 42 · 2023: 47 · 2022: 45 · 2021: 63 · 2020: 55 · 2019: 80 · 2018: 69 · 2017: 62 · 2016: 85 · 2015: 101 · 2014: 130 · 2013: 196 · 2012: 238
FWCI
112.85
Type
journal article
Language
en
Open access
Licence
onlinelibrary.wiley.com/termsAndConditions#vor (vor)
Locations
  • Journal of Geophysical Research Atmospheres (publishedVersion)
  • Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, other-oa)
  • UEA Digital Repository (University of East Anglia) (submittedVersion)
Funders
  • U.S. Department of Energy
  • Department for Environment, Food and Rural Affairs, UK Government
  • Office of Science
Topics
  • Physical Sciences › Environmental Science › Global and Planetary Change › Climate variability and models
  • Physical Sciences › Environmental Science › Global and Planetary Change › Climate Change and Environmental Impact
  • Physical Sciences › Earth and Planetary Sciences › Atmospheric Science › Geology and Paleoclimatology Research
Keywords
surface temperature, temperature uncertainty, sea surface temperature, measurement error, sampling error, temperature bias, global mean temperature, historical temperature records

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