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Evaluating WorldClim Version 1 (1961–1990) as the Baseline for Sustainable Use of Forest and Environmental Resources in a Changing Climate

Author

Listed:
  • Maurizio Marchi

    (CREA—Research Centre for Forestry and Wood, I-52100 Arezzo, Italy)

  • Iztok Sinjur

    (Slovenian Forestry Institute, Vecna pot 2, 1000 Ljubljana, Slovenia)

  • Michele Bozzano

    (European Forest Institute, 53113 Bonn, Germany)

  • Marjana Westergren

    (Slovenian Forestry Institute, Vecna pot 2, 1000 Ljubljana, Slovenia)

Abstract

WorldClim version 1 is a high-resolution, global climate gridded dataset covering 1961–1990; a “normal” climate. It has been widely used for ecological studies thanks to its free availability and global coverage. This study aims to evaluate the quality of WorldClim data by quantifying any discrepancies by comparison with an independent dataset of measured temperature and precipitation records across Europe. BIO1 (mean annual temperature, MAT) and BIO12 (mean total annual precipitation, MAP) were used as proxies to evaluate the spatial accuracy of the WorldClim grids. While good representativeness was detected for MAT, the study demonstrated a bias with respect to MAP. The average difference between WorldClim predictions and climate observations was around +0.2 °C for MAT and −48.7 mm for MAP, with large variability. The regression analysis revealed a good correlation and adequate proportion of explained variance for MAT (adjusted R 2 = 0.856) but results for MAP were poor, with just 64% of the variance explained (adjusted R 2 = 0.642). Moreover no spatial structure was found across Europe, nor any statistical relationship with elevation, latitude, or longitude, the environmental predictors used to generate climate surfaces. A detectable spatial autocorrelation was only detectable for the two most thoroughly sampled countries (Germany and Sweden). Although further adjustments might be evaluated by means of geostatistical methods (i.e., kriging), the huge environmental variability of the European environment deeply stressed the WorldClim database. Overall, these results show the importance of an adequate spatial structure of meteorological stations as fundamental to improve the reliability of climate surfaces and derived products of the research (i.e., statistical models, future projections).

Suggested Citation

  • Maurizio Marchi & Iztok Sinjur & Michele Bozzano & Marjana Westergren, 2019. "Evaluating WorldClim Version 1 (1961–1990) as the Baseline for Sustainable Use of Forest and Environmental Resources in a Changing Climate," Sustainability, MDPI, vol. 11(11), pages 1-14, May.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:11:p:3043-:d:235447
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    References listed on IDEAS

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    1. Ray, Duncan & Petr, Michal & Mullett, Martin & Bathgate, Stephen & Marchi, Maurizio & Beauchamp, Kate, 2019. "A simulation-based approach to assess forest policy options under biotic and abiotic climate change impacts: A case study on Scotland's National Forest Estate," Forest Policy and Economics, Elsevier, vol. 103(C), pages 17-27.
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    3. Maurizio Marchi & Carlotta Ferrara & Rita Biasi & Rosanna Salvia & Luca Salvati, 2018. "Agro-Forest Management and Soil Degradation in Mediterranean Environments: Towards a Strategy for Sustainable Land Use in Vineyard and Olive Cropland," Sustainability, MDPI, vol. 10(7), pages 1-8, July.
    4. Lei Zhang & Shirong Liu & Pengsen Sun & Tongli Wang & Guangyu Wang & Xudong Zhang & Linlin Wang, 2015. "Consensus Forecasting of Species Distributions: The Effects of Niche Model Performance and Niche Properties," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-18, March.
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