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    Assessing potential of sparse-input reanalyses for centennial-scale land surface air temperature homogenisation

    Gillespie, Ian and Haimberger, L. and Compo, G.P. and Thorne, Peter (2020) Assessing potential of sparse-input reanalyses for centennial-scale land surface air temperature homogenisation. International Journal of Climatology, 41. ISSN 0899-8418

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    Observations from the historical meteorological observing network contain many artefacts of non-climatic origin which must be accounted for prior to using these data in climate applications. State-of-the-art homogenisation approaches use various flavours of pairwise comparison between a target station and candidate neighbour station series. Such approaches require an adequate number of neighbours of sufficient quality and comparability - a condition that is met for most station series since the mid-20th Century. However, pairwise approaches have challenges where suitable neighbouring stations are sparse, as remains the case in vast regions of the globe and is common almost everywhere prior to the early 20th Century. Modern sparse-input centennial reanalysis products continue to improve and offer a potential alternative to pairwise comparison, particularly where and when observations are sparse. They do not directly ingest or use land-based surface temperature observations, so they are a formally independent estimate. This may be particularly helpful in cases where structurally similar changes exist across broad networks, which challenges current techniques in the absence of metadata. They also potentially offer a valuable methodologically distinct method, which would help explore structural uncertainty in homogenisation techniques. The present study compares the potential of spatially-interpolated sparse-input reanalysis products to neighbour-based approaches to perform homogenisation of global monthly land surface air temperature records back to 1850 based upon the statistical properties of station-minus-reanalysis and station-minus-neighbour series. This shows that neighbour-based approaches likely remain preferable in data dense regions and epochs. However, the most recent reanalysis product, NOAA-CIRES-DOE 20CRv3, is potentially preferable in cases where insufficient neighbours are available. This may in particular affect long-term global average estimates where a small number of long-term stations in data sparse regions will make substantial contributions to global estimates and may contain missed data artefacts in present homogenisation approaches.

    Item Type: Article
    Keywords: homogeneity; reanalyses; surface temperatures;
    Academic Unit: Faculty of Social Sciences > Geography
    Faculty of Social Sciences > Research Institutes > Irish Climate Analysis and Research Units, ICARUS
    Item ID: 13952
    Identification Number:
    Depositing User: Peter Thorne
    Date Deposited: 05 Feb 2021 13:33
    Journal or Publication Title: International Journal of Climatology
    Publisher: Wiley
    Refereed: Yes
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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