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    A framework for benchmarking of homogenisation algorithm performance on the global scale


    Willette, K.M. and Williams, C. and Jolliffe, I.T. and Lund, R. and Alexender, L.V. and Brönnimann, S. and Vincent, L.S. and Easterbrook, S. and Venema, V.K.C. and Berry, D. and Warren, R.E. and Lopardo, G. and Auchmann, R. and Aguilar, E. and Menne, M.J. and Gallagher, C. and Hausfather, Z. and Thorarinsdottir, T. and Thorne, Peter (2014) A framework for benchmarking of homogenisation algorithm performance on the global scale. Geoscientific Instrumentation, Methods and Data Systems, 3 (2). pp. 187-200. ISSN 2193-0864

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    Abstract

    The International Surface Temperature Initiative (ISTI) is striving towards substantively improving our ability to robustly understand historical land surface air temperature change at all scales. A key recently completed first step has been collating all available records into a comprehensive open access, traceable and version-controlled databank. The crucial next step is to maximise the value of the collated data through a robust international framework of benchmarking and assessment for product intercomparison and uncertainty estimation. We focus on uncertainties arising from the presence of inhomogeneities in monthly mean land surface temperature data and the varied methodological choices made by various groups in building homogeneous temperature products. The central facet of the benchmarking process is the creation of global-scale synthetic analogues to the real-world database where both the "true" series and inhomogeneities are known (a luxury the real-world data do not afford us). Hence, algorithmic strengths and weaknesses can be meaningfully quantified and conditional inferences made about the real-world climate system. Here we discuss the necessary framework for developing an international homogenisation benchmarking system on the global scale for monthly mean temperatures. The value of this framework is critically dependent upon the number of groups taking part and so we strongly advocate involvement in the benchmarking exercise from as many data analyst groups as possible to make the best use of this substantial effort.

    Item Type: Article
    Keywords: framework; benchmarking; homogenisation algorithm performance; global scale;
    Academic Unit: Faculty of Social Sciences > Geography
    Faculty of Social Sciences > Research Institutes > Irish Climate Analysis and Research Units, ICARUS
    Item ID: 6474
    Identification Number: https://doi.org/10.5194/gi-3-187-2014
    Depositing User: Peter Thorne
    Date Deposited: 19 Oct 2015 14:15
    Journal or Publication Title: Geoscientific Instrumentation, Methods and Data Systems
    Publisher: European Geosciences Union (EGU)
    Refereed: Yes
    URI:

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