Search

Expanding shrubs in the Arctic trap blowing snow, increasing snow height and accelerating permafrost warming. Topography also affects snow height as snow accumulates in hollows. The respective roles of topography and erect vegetation in snow accumulation were investigated using a UAV-borne lidar at two nearby contrasted sites in northern Quebec, Canada. The North site featured tall vegetation up to 2.5 m high, moderate snow height, and smooth topography. The South site featured lower vegetation, greater snow height, and rougher topography. There was little correlation between topography and vegetation height at both sites. Vegetation lower than snow height had very little effect on snow height. When vegetation protruded above the snow, snow height was well correlated with vegetation height. The topographic position index (TPI) was well correlated with snow height when it was not masked by the effect of protruding vegetation. The North site with taller vegetation therefore showed a good correlation between vegetation height and snow height, R2 = 0.37, versus R2 = 0.04 at the South site. Regarding topography, the reverse was observed between TPI and snow height, with R2 = 0.29 at the North site and R2 = 0.67 at the South site. The combination of vegetation height and TPI improved the prediction of snow height at the North site (R2 = 0.59) but not at the South site because vegetation height has little influence there. Vegetation was therefore the main factor determining snow height when it protruded above the snow. When it did not protrude, snow height was mostly determined by topography. Significance Statement: Wind-induced snow drifting is a major snow redistribution process in the Arctic. Shrubs trap drifting snow, and drifting snow accumulates in hollows. Determining the respective roles of both these processes in snow accumulation is required to predict permafrost temperature and its emission of greenhouse gases, because thicker snow limits permafrost winter cooling. Using a UAV-borne lidar, we have determined snow height distribution over two contrasted sites in the Canadian low Arctic, with varied vegetation height and topography. When snow height exceeds vegetation height, topography is a good predictor of snow height, with negligible effect of buried vegetation. When vegetation protrudes above the snow, combining both topography and vegetation height is required for a good prediction of snow height. [ABSTRACT FROM AUTHOR]

Air temperature changes as a function of elevation were analyzed in a valley of the Spanish Pyrenees. We analyzed insolation, topography and meteorological conditions in order to understand how complex topoclimatic environments develop. Clustering techniques were used to define vertical patterns of air temperature covering more than 1000 m of vertical elevation change. Ten locations from the bottom of the valley to the summits were monitored from September 2016 to June 2019. The results show that (i) night-time lapse rates were between −4 and −2 °C km−1, while in the daytime they were from −6 to −4 °C km−1, due to temperature inversions and topography. Daily maximum temperature lapse rates were steeper from March to July, and daily minimum temperatures were weaker from June to August, and in December. (ii) Different insolation exposure within and between the two analyzed slopes strongly influenced diurnal air temperatures, creating deviations from the general lapse rates. (iii) Usually, two cluster patterns were found (i.e., weak and steep), which were associated with stable and unstable weather conditions, respectively, in addition to high-low atmospheric pressure and low-high relative humidity. The results will have direct applications in disciplines that depend on air temperature estimations (e.g., snow studies, water resources and sky tourism, among others). [ABSTRACT FROM AUTHOR]

The Sierra Nevada of Santa Marta (12°N) hosts a unique glaciated environment (6.5 km2) only 40 km distant from the Caribbean Sea. However, the remoteness of the glaciers and restricted access to the region has so far prevented onsite field work research from being undertaken. We worked with several very high resolution airborne and satellite images to delimit the extension of the glaciers during the maximum extension of the Little Ice Age (ca. 1850), when glaciers covered 81.6 km2, and the ice cover in four subsequent phases (1954, 1995, 2010 and 2016). Polar plots and Random Forest models enabled characterization of the spatial distribution of ice cover in the region, and how the impact of topographic and geographical variables changed over time. Results show that elevation was the most important variable in explaining the existence of glaciers during the LIA. Since then, the ice cover has gradually been receding to areas shielded from solar radiation, even though the solar angle at this latitude is very high. Thus, results clearly confirm that topography is increasing its importance to explain the glacier distribution over the study area, and the particular characteristics of where each ice body is found will gain importance. Nonetheless, the probability of ice being present as predicted by Random Forests in 2017 suggests that most of the ice cover located outside the most elevated areas of the Sierra is very likely to disappear in coming years. • A 90% of the glaciers have disappeared since the end of the Little Ice Age. • Results show a shift from a to a topoclimatic control of the glaciers in Santa Marta region. • Random Forests methodology suggests that most of the remaining ice will disappear in coming years. [ABSTRACT FROM AUTHOR]