Evaluation of the accuracy of climatic data from the WorldClim and Chelsa databases in three northern provinces of Iran

Document Type : Scientific article

Authors

1 PhD Student of Forest Management, Department of Forest Science, Faculty of Natural Resources and marine science, Tarbiat Modares University, Nur, Mazandaran, I. R. Iran

2 Associate Prof., Department of Forest Science, Faculty of Natural Resources and marine science, Tarbiat Modares University, Nur, Mazandaran, I. R. Iran

Abstract

Background and Objective: Environmental and climatic data are essential inputs for modeling species distribution and creating habitat suitability maps for both plant and animal species. Given the pivotal role of climate in shaping vegetation patterns at the regional scale, the use of high-resolution and accurate climate data—especially when supported by robust statistical classification—can effectively substitute for ground-based assessments of ecological constraints, thresholds, and the potential distribution of forests across broad landscapes. This study aims to evaluate the accuracy of two widely used global climate databases, WorldClim and CHELSA, by comparing their data with that from meteorological stations located within the Hyrcanian forests.
Material and Methods: Climate data were obtained from the WorldClim and CHELSA databases for the periods 1970–2000 and 1980–2010, respectively. Observational data from 38 synoptic weather stations across the provinces of Guilan, Mazandaran, and Golestan were also analyzed. To extract the values of each bioclimatic variable (Bio) at the station locations, R software was used. Of the 19 available bioclimatic variables, two—Bio1 (annual mean temperature) and Bio12 (annual precipitation)—were selected for detailed comparison with station data.
Results: The results showed that precipitation data from both databases generally aligned with observations from meteorological stations, though some discrepancies were evident. CHELSA's precipitation data, while displaying a high correlation with ground observations (r = 0.84), were found—based on paired t-tests—to systematically underestimate actual precipitation levels. In contrast, WorldClim's precipitation data demonstrated stronger consistency with ground-based measurements, showing a correlation coefficient of 0.85 and no statistically significant difference in the paired t-test, indicating high predictive reliability. For annual mean temperature, CHELSA outperformed WorldClim, exhibiting a stronger correlation with station data (r = 0.91 vs. 0.65), suggesting higher accuracy in the study area. Based on these findings, CHELSA is more suitable for temperature-related studies, while WorldClim is preferable for precipitation-focused research in the Hyrcanian forest region.
Conclusion: This study demonstrates that WorldClim and CHELSA offer reliable data for precipitation and temperature variables, respectively, and often correspond well with ground-based measurements. However, some differences stem from varying interpolation methods, spatial resolutions, and data integration approaches—particularly in regions with abrupt climatic shifts. Given the widespread accessibility of both datasets, they can serve as practical alternatives to ground observations in species distribution modeling and other environmental assessments. Their use can be especially beneficial in ecological research, natural resource management, and climate modeling in data-scarce regions. Overall, this study highlights the value of global climate databases as useful tools in areas with limited meteorological infrastructure. For future research, it is recommended to assess the accuracy and applicability of these datasets in diverse regions and to integrate them into species distribution models and climate analyses where ground data are lacking. Additionally, improving data monitoring and refining interpolation techniques may further enhance the precision and reliability of these resources. Finally, selecting the most appropriate dataset for each climatic variable—based on the specific findings of this study—can improve the quality and reliability of future research in the Hyrcanian forest region.

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References

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Forest Research and Development
Volume 11, Issue 1
June 2025
Pages 109-132

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