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Addressing the relocation bias in a long temperature record by means of land cover assessment

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Abstract

The meteorological measurements in Brno, Czech Republic, is among the world’s oldest measurements, operating since 1799. Like many others, station was initially installed in the city center, relocated several times, and currently operates at an airport outside the city. These geographical changes potentially bias the temperature record due to different station surroundings and varying degrees of urban heat island effects. Here, we assess the influence of land cover on spatial temperature variations in Brno, capitol of Moravia and the second largest city of the Czech Republic. We therefore use a unique dataset of half-hourly resolved measurements from 11 stations spanning a period of more than 3.5 years and apply this information to reduce relocation biases in the long-term temperature record from 1799 to the present. Regression analysis reveals a significant warming influence from nearby buildings and a cooling influence from vegetation, explaining up to 80% of the spatial variability within our network. The influence is strongest during the warm season and for land cover changes between 300 and 500 m around stations. Relying on historical maps and recent satellite data, it was possible to capture the building densities surrounding the past locations of the meteorological station. Using the previously established land cover–temperature relation, the anthropogenic warming for each measurement site could be quantified and hence eliminated from the temperature record accordingly, thereby increasing the long-term warming trend.

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Authors and Affiliations

  1. Laboratory for Climatology and Remote Sensing, Department of Geography, Philipps-University Marburg, Deutschhausstraße 10, 35032, Marburg, Germany

    Isabel Knerr

  2. Department of Geography, Johannes Gutenberg-University, Mainz, Germany

    Isabel Knerr, Manuel Dienst & Jan Esper

  3. IVL – Swedish Environmental Research Institute, Gothenburg, Sweden

    Jenny Lindén

  4. Department of Geography, Masaryk University, Brno, Czech Republic

    Petr Dobrovolný & Ulf Büntgen

  5. Institute of Computer Science, Czech Academy of Sciences, Brno, Czech Republic

    Jan Geletic & Ulf Büntgen

  6. Department of Geography, University of Cambridge, Cambridge, UK

    Ulf Büntgen

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  1. Isabel Knerr
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Correspondence to Isabel Knerr.

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Knerr, I., Dienst, M., Lindén, J. et al. Addressing the relocation bias in a long temperature record by means of land cover assessment. Theor Appl Climatol 137, 2853–2863 (2019). https://doi.org/10.1007/s00704-019-02783-2

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