Abstract <p>Intra-annual climate variations and their effects on radial tree growth have received increasing attention in recent decades. Tracheidograms have been widely used for analyzing xylem cell parameters within one year. This paper describes steps for creating tracheidograms based on high-resolution images using edge detection methods through artificial neural networks (ANNs), computer vision library (OpenCV), and tracheidogram libraries (RAPTOR and tracheideR). To identify the climate-related features of the intra-annual xylem growth of Scots pine <i>Pinus sylvestris</i> L. on Sredniy Island, Keret Archipelago, White Sea, we have determined the parameters of 43 754 xylem cells for seven trees; 23 091 of these cells have been grouped into radial files for the period from 2009 to 2018. Areas under the tracheidogram curves of different xylem cell parameters (lumen radial diameter, lumen perimeter, cell wall thickness, lumen area, ratio of lumen diameter to cell wall thickness, and ratio of lumen area to lumen perimeter) have been calculated as an integral metric of annual ring structure. Pearson’s correlation coefficient has been estimated between these metrics and average temperature and precipitation from May to August. The strongest identified relationships were as follows: the inverse relationship between the amount of precipitation and cell wall thickness, the direct relationship between temperature and cell wall thickness, and the inverse relationship between temperature and lumen size.</p>