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    Benchmarking the performance of pairwise homogenization of surface temperatures in the United States


    Williams Jr., C.N. and Menne, M.J. and Thorne, Peter (2012) Benchmarking the performance of pairwise homogenization of surface temperatures in the United States. Journal of Geophysical Research, 117 (D05116). ISSN 0148-0227

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    Abstract

    Changes in the circumstances behind in situ temperature measurements often lead to biases in individual station records that, collectively, can also bias regional temperature trends. Since these biases are comparable in magnitude to climate change signals, homogeneity “corrections” are necessary to make the records suitable for climate analysis. To quantify the effectiveness of U.S. surface temperature homogenization, a randomized perturbed ensemble of the USHCN pairwise homogenization algorithm was run against a suite of benchmark analogs to real monthly temperature data. Results indicate that all randomized versions of the algorithm consistently produce homogenized data closer to the true climate signal in the presence of widespread systematic errors. When applied to the real-world observations, the randomized ensemble reinforces previous understanding that the two dominant sources of bias in the U.S. temperature records are caused by changes to time of observation (spurious cooling in minimum and maximum) and conversion to electronic resistance thermometers (spurious cooling in maximum and warming in minimum). Error bounds defined by the ensemble output indicate that maximum temperature trends are positive for the past 30, 50 and 100 years, and that these maximums contain pervasive negative biases that cause the unhomogenized (raw) trends to fall below the lower limits of uncertainty. Moreover, because residual bias in the homogenized analogs is one-tailed under biased errors, it is likely that maximum temperature trends have been underestimated in the USHCN. Trends for minimum temperature are also positive over the three periods, but the ensemble error bounds encompass trends from the unhomogenized data.

    Item Type: Article
    Keywords: Benchmarking; performance; pairwise homogenization; surface temperatures; United States;
    Academic Unit: Faculty of Social Sciences > Geography
    Faculty of Social Sciences > Research Institutes > Irish Climate Analysis and Research Units, ICARUS
    Item ID: 6495
    Identification Number: https://doi.org/10.1029/2011JD016761
    Depositing User: Peter Thorne
    Date Deposited: 22 Oct 2015 10:27
    Journal or Publication Title: Journal of Geophysical Research
    Publisher: American Geophysical Union (AGU)
    Refereed: Yes
    URI:

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