• Phenological controls over aerodynamic resistance ( R ah ) were investigated. • R ah exhibits significant seasonal variability across a wide range of sites. • These shifts in R ah were caused by phenology in some ecosystems. • Accounting for variation in kB −1 is important for improving predictions of H . Surface roughness – a key control on land-atmosphere exchanges of heat and momentum – differs between dormant and growing seasons. However, how surface roughness shifts seasonally at fine time scales (e.g., days) in response to changing canopy conditions is not well understood. This study: (1) explores how aerodynamic resistance changes seasonally; (2) investigates what drives these seasonal shifts, including the role of vegetation phenology; and (3) quantifies the importance of including seasonal changes of aerodynamic resistance in “big leaf” models of sensible heat flux ( H ). We evaluated aerodynamic resistance and surface roughness lengths for momentum ( z 0m ) and heat ( z 0h ) using the kB −1 parameter (ln( z 0m / z 0h )). We used AmeriFlux data to obtain surface-roughness estimates, and PhenoCam greenness data for phenology. This analysis included 23 sites and ∼190 site years from deciduous broadleaf, evergreen needleleaf, woody savanna, cropland, grassland, and shrubland plant-functional types (PFTs). Results indicated clear seasonal patterns in aerodynamic resistance to sensible heat transfer ( R ah ). This seasonality tracked PhenoCam-derived start-of-season green-up transitions in PFTs displaying the most significant seasonal changes in canopy structure, with R ah decreasing near green-up transitions. Conversely, in woody savanna sites and evergreen needleleaf forests, patterns in R ah were not linked to green-up. Our findings highlight that decreases in kB −1 are an important control over R ah , explaining > 50% of seasonal variation in R ah across most sites. Decreases in kB −1 during green-up are likely caused by increasing z 0h in response to higher leaf area index. Accounting for seasonal variation in kB −1 is key for predicting H as well; assuming kB −1 to be constant resulted in significant biases that also exhibited strong seasonal patterns. Overall, we found that aerodynamic resistance can be sensitive to phenology in ecosystems having strong seasonality in leaf area, and this linkage is critical for understanding land-atmosphere interactions at seasonal time scales.

• Phenological controls over aerodynamic resistance ( R ah ) were investigated. • R ah exhibits significant seasonal variability across a wide range of sites. • These shifts in R ah were caused by phenology in some ecosystems. • Accounting for variation in kB −1 is important for improving predictions of H . Surface roughness – a key control on land-atmosphere exchanges of heat and momentum – differs between dormant and growing seasons. However, how surface roughness shifts seasonally at fine time scales (e.g., days) in response to changing canopy conditions is not well understood. This study: (1) explores how aerodynamic resistance changes seasonally; (2) investigates what drives these seasonal shifts, including the role of vegetation phenology; and (3) quantifies the importance of including seasonal changes of aerodynamic resistance in “big leaf” models of sensible heat flux ( H ). We evaluated aerodynamic resistance and surface roughness lengths for momentum ( z 0m ) and heat ( z 0h ) using the kB −1 parameter (ln( z 0m / z 0h )). We used AmeriFlux data to obtain surface-roughness estimates, and PhenoCam greenness data for phenology. This analysis included 23 sites and ∼190 site years from deciduous broadleaf, evergreen needleleaf, woody savanna, cropland, grassland, and shrubland plant-functional types (PFTs). Results indicated clear seasonal patterns in aerodynamic resistance to sensible heat transfer ( R ah ). This seasonality tracked PhenoCam-derived start-of-season green-up transitions in PFTs displaying the most significant seasonal changes in canopy structure, with R ah decreasing near green-up transitions. Conversely, in woody savanna sites and evergreen needleleaf forests, patterns in R ah were not linked to green-up. Our findings highlight that decreases in kB −1 are an important control over R ah , explaining > 50% of seasonal variation in R ah across most sites. Decreases in kB −1 during green-up are likely caused by increasing z 0h in response to higher leaf area index. Accounting for seasonal variation in kB −1 is key for predicting H as well; assuming kB −1 to be constant resulted in significant biases that also exhibited strong seasonal patterns. Overall, we found that aerodynamic resistance can be sensitive to phenology in ecosystems having strong seasonality in leaf area, and this linkage is critical for understanding land-atmosphere interactions at seasonal time scales.

A multitude of disturbance agents, such as wildfires, land use, and climate-driven expansion of woody shrubs, is transforming the distribution of plant functional types across Arctic–Boreal ecosystems, which has significant implications for interactions and feedbacks between terrestrial ecosystems and climate in the northern high-latitude. However, because the spatial resolution of existing land cover datasets is too coarse, large-scale land cover changes in the Arctic–Boreal region (ABR) have been poorly characterized. Here, we use 31 years (1984–2014) of moderate spatial resolution (30 m) satellite imagery over a region spanning 4.7 × 106 km2 in Alaska and northwestern Canada to characterize regional-scale ABR land cover changes. We find that 13.6 ± 1.3% of the domain has changed, primarily via two major modes of transformation: (a) simultaneous disturbance-driven decreases in Evergreen Forest area (−14.7 ± 3.0% relative to 1984) and increases in Deciduous Forest area (+14.8 ± 5.2%) in the Boreal biome; and (b) climate-driven expansion of Herbaceous and Shrub vegetation (+7.4 ± 2.0%) in the Arctic biome. By using time series of 30 m imagery, we characterize dynamics in forest and shrub cover occurring at relatively short spatial scales (hundreds of meters) due to fires, harvest, and climate-induced growth that are not observable in coarse spatial resolution (e.g., 500 m or greater pixel size) imagery. Wildfires caused most of Evergreen Forest Loss and Evergreen Forest Gain and substantial areas of Deciduous Forest Gain. Extensive shifts in the distribution of plant functional types at multiple spatial scales are consistent with observations of increased atmospheric CO2 seasonality and ecosystem productivity at northern high-latitudes and signal continental-scale shifts in the structure and function of northern high-latitude ecosystems in response to climate change.