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Supplementary file 1_Decomposing complex local wind patterns in mountainous terrain utilizing a mountain meteorological observation network.docx

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NIAID Data Ecosystem2026-05-10 收录
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https://figshare.com/articles/dataset/Supplementary_file_1_Decomposing_complex_local_wind_patterns_in_mountainous_terrain_utilizing_a_mountain_meteorological_observation_network_docx/31994220
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Wind regulates diverse ecological processes, generates natural hazards, and provides renewable energy. Among the various environmental factors that shape and interact with forest ecosystems, wind remains among the least studied due to its inherent spatiotemporal complexity. This complexity is amplified in mountainous forest ecosystems, where wind flow is transformed by the topography and canopy structure. In such regions, spatiotemporal wind flow patterns are difficult to analyze using conventional meteorological observation systems, which are typically located in human settlements. In South Korea, a mountain meteorological observation network has been established over the past decade; however, wind data from these stations have rarely been analyzed. This study presents a pioneering local-scale wind analysis using this network, employing data from 16 mountainous and 5 standard (non-mountainous) meteorological stations in a mountainous coastal region in South Korea spanning from 2020 to 2024. Mean wind speeds at the mountainous stations ranged from 0.93 to 5.73 m s−1. Compared to the standard stations, significantly higher wind speeds were observed at the top-slope mountainous stations, whereas the mid- and bottom-slope stations exhibited similar or lower wind speeds. Seasonal wind patterns were consistently observed—namely, stronger in winter and weaker in summer—probably influenced by mid-latitude seasonal winds in winter and canopy phenology. Daily wind characteristics—speed, direction, and recirculation—were clustered into four groups based on combinations of westerly/northerly synoptic flows and local wind intensity. These spatial variations in wind speed were explained using generalized linear models incorporating geographical, forest, and temporal variables. The model performance improved with broader temporal scales, from minute-level to monthly means. To our knowledge, this is the first empirical report of spatiotemporal wind patterns in this mountain meteorological observation network in South Korea. The ground-level findings support previous results from synoptic and mesoscale simulations. The descriptive, regression, and cluster analyses performed in this study offer valuable insights into local wind variability in mountainous areas and lay the groundwork for the forecasting and management of wind-related processes in forest ecosystems.
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2026-04-13
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