Effects of climate dataset type on tree-ring analysis: A case study for Siberian forests

• Published in: Polar Science
• Format: Article in Journal/Newspaper
• Language: English
• Published: 2019
• Subjects: Tree rings; Climate change; Boreal forests; Arctic; Gridded data; Polar Science
• Online Access: https://nipr.repo.nii.ac.jp/?action=repository_uri&item_id=15925; http://id.nii.ac.jp/1291/00015819/

Tree-ring width indices (RWI) are widely used as long-term indicators of past forest ecosystem response to climate change. Due to their larger spatial scales, gridded climate data have been preferred over station data. However, it is not clear how climate dataset type affects correlations between climate variables (e.g., temperature and precipitation) and RWI. To answer this question, RWI was compared to both gridded and station climate datasets over the Siberian forests. Correlation patterns between RWI and seasonal climate variables were mostly similar regardless of dataset. However, some dependence on climate dataset was observed for summer temperatures and previous autumn-winter precipitation. The extent of dataset impacts depends on the similarity of climate variables between datasets, which was related to the distance between the nearest climate station to each RWI site/climate grid point. On the other hand, dataset effects primarily impact statistical significance, and opposite correlations between RWI and climate variables have not been observed for different climate datasets. Therefore, the impacts of climate dataset type on RWI to estimate the forest ecosystem response to climate change are not major, emphasizing the relevance of previous RWI studies that used gridded climate datasets.