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Title:Evaluating WorldClim version 1 (1961-1990) as the baseline for sustainable use of forest and environmental resources in a changing climate
Authors:Marchi, Maurizio (Author)
Sinjur, Iztok (Author)
Bozzano, Michele (Author)
Westergren, Marjana (Author)
Language:English
Tipology:1.01 - Original Scientific Article
Organisation:Logo SciVie - Slovenian Forestry Institute
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 R2 = 0.856) but results for MAP were poor, with just 64% of the variance explained (adjusted R2 = 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).
Keywords:spatial analysis, spatial interpolation, geostatistics, ecological mathematics
Year of publishing:2019
COBISS_ID:5403046 Link is opened in a new window
UDC:630*18:630*51
ISSN on article:2071-1050
OceCobissID:5324897 Link is opened in a new window
DOI:10.3390/su11113043 Link is opened in a new window
Note:Nasl. z nasl. zaslona; Opis vira z dne 6. 6. 2019; Soavtorji: Iztok Sinjur, Michele Bozzano, Marjana Westergren;
Views:1196
Downloads:650
Files:URL URL - Presentation file, visit https://www.mdpi.com/2071-1050/11/11/3043
.pdf PDF - Presentation file, download (2,62 MB)
 
Journal:Sustainability
MDPI
 
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Licences

License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Licensing start date:19.10.2020

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