Cited by 56Climate variability and modelsMeteorological Phenomena and SimulationsAtmospheric Ozone and Climate

Assessing bias and uncertainty in the HadAT-adjusted radiosonde climate record.

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McCarthy, Mark P., Titchner, H. A., Thorne, P. W., Tett, S. F. B., Haimberger, L., Parker, D. E.·2008·Journal of Climate

Abstract

Uncertainties in observed records of atmospheric temperature aloft remain poorly quantified. This has resulted in considerable controversy regarding signals of climate change over recent decades from temperature records of radiosondes and satellites. This work revisits the problems associated with the removal of inhomogeneities from the historical radiosonde temperature records, and provides a method for quantifying uncertainty in an adjusted radiosonde climate record due to the subjective choices made during the data homogenization. This paper presents an automated homogenization method designed to replicate the decisions made by manual judgment in the generation of an earlier radiosonde dataset [i.e., the Hadley Centre radiosonde temperature dataset (HadAT)]. A number of validation experiments have been conducted to test the system performance and impact on linear trends. Using climate model data to simulate biased radiosonde data, the authors show that limitations in the homogenization method are sufficiently large to explain much of the tropical trend discrepancy between HadAT and estimates from satellite platforms and climate models. This situation arises from the combination of systematic (unknown magnitude) and random uncertainties (of order 0.05 K decade−1) in the radiosonde data. Previous assessment of trends and uncertainty in HadAT is likely to have underestimated the systematic bias in tropical mean temperature trends. This objective assessment of radiosonde homogenization supports the conclusions of the synthesis report of the U.S. Climate Change Science Program (CCSP), and associated research, regarding potential bias in tropospheric temperature records from radiosondes.

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Authors
McCarthy, M. P., Titchner, H. A., Thorne, P. W., Tett, S. F. B., Haimberger, L., & Parker, D. E.
Affiliations
  • Met Office (GB)
  • University of Vienna (AT)
Corresponding author
McCarthy, Mark P.
Venue
Journal of Climate
Published
2008-02-15
Volume
21
Issue
4
Pages
817-832
ISSN
  • 0894-8755 (ISSN-L)
  • 1520-0442
OpenAlex
W2097702152
Cited by
56
References
31
Citations by year
2026: 1 · 2022: 1 · 2021: 3 · 2020: 2 · 2019: 1 · 2018: 2 · 2016: 4 · 2015: 4 · 2014: 1 · 2013: 5 · 2012: 5
FWCI
7.47
Type
journal article
Language
en
Open access
Locations
  • Journal of Climate (publishedVersion)
  • Maynooth University ePrints and eTheses Archive (Maynooth University) (acceptedVersion)
  • Phaidra (Universität Wien) (submittedVersion, cc-by-nc-nd)
  • Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, other-oa)
Funders
  • Department for Environment, Food and Rural Affairs, UK Government (GA01101)
  • Austrian Science Fund
  • Ministry of Defense
Topics
  • Physical Sciences › Environmental Science › Global and Planetary Change › Climate variability and models
  • Physical Sciences › Earth and Planetary Sciences › Atmospheric Science › Meteorological Phenomena and Simulations
  • Physical Sciences › Earth and Planetary Sciences › Atmospheric Science › Atmospheric Ozone and Climate
Keywords
data homogenization, uncertainty quantification, systematic bias, tropospheric temperature, climate change detection

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