Timing Of Snowmelt Research Articles

A critical assessment of geological weighing lysimeters: Part 2—Modelling field scale soil moisture storage and hydrological fluxes

AbstractLand surface models (LSMs) are used to simulate the terrestrial component of water, energy, and biogeochemical cycles. These simulations are useful for water resources management, drought and flood prediction, and numerical climate/weather prediction. However, the usefulness of LSMs are dependent by their ability to reproduce states and fluxes realistically. Accurate measurements of water storage are useful to calibrate and validate LSMs outputs. Geological weighing lysimeters (GWLs) are instruments that can provide field‐scale estimates of integrated total water storage within a soil profile. We use field estimates of total water storage and subsurface storage to critically evaluate two different land surface models: the Modélisation Environnementale communautaire—Surface Hydrology (MESH) which uses the Canadian Land Surface Scheme (CLASS), and the Structure for Unifying Multiple Modeling Alternatives: (SUMMA). These models have differences in how the processes and properties of the land surface are represented. We attempted to parameterize each model in an equivalent manner, to minimize model differences. Both models were able to reproduce observations of total water storage and subsurface storage reasonably well. However, there were inconsistencies in the simulated timing of snowmelt; depth of soil freezing; total evapotranspiration; partitioning of evaporation between soil evaporation and evaporation of intercepted water; and soil drainage. No one model emerged as better overall, though each model had specific strengths and weaknesses that we describe. Insights from this study can be used to improve model physics and performance.

Applicability of Relatively Low-Cost Multispectral Uncrewed Aerial Systems for Surface Characterization of the Cryosphere

This paper investigates the ability of a relatively low cost, commercially available uncrewed aerial vehicle (UAV), the DJI Mavic 3 Multispectral, to perform cryospheric research. The performance of this UAV, where applicable, is compared to a similar but higher cost system, the DJI Matrice 350, equipped with a Micasense RedEdge-MX Multispectral dual-camera system. The Mavic 3 Multispectral was tested at three field sites: the Lemon Creek Glacier, Juneau Icefield, AK; the Easton Glacier, Mt. Baker, WA; and Bagley Basin, Mt. Baker, WA. This UAV proved capable of mapping the spatial distribution of red snow algae on the surface of the Lemon Creek Glacier using both spectral indices and a random forest supervised classification method. The UAV was able to assess the timing of snowmelt and changes in suncup morphology on snow-covered areas within the Bagley Basin. Finally, the UAV was able to classify glacier surface features using a random forest algorithm with an overall accuracy of 68%. The major advantages of this UAV are its low weight, which allows it to be easily transported into the field, its low cost compared to other alternatives, and its ease of use. One limitation would be the omission of a blue multispectral band, which would have allowed it to more easily classify glacial ice and snow features.

Energy‐Water Asynchrony Principally Determines Water Available for Runoff From Snowmelt in Continental Montane Forests

ABSTRACTChanges in the volume, rate, and timing of the snowmelt water pulse have profound implications for seasonal soil moisture, evapotranspiration (ET), groundwater recharge, and downstream water availability, especially in the context of climate change. Here, we present an empirical analysis of water available for runoff using five eddy covariance towers located in continental montane forests across a regional gradient of snow depth, precipitation seasonality, and aridity. We specifically investigated how energy‐water asynchrony (i.e., snowmelt timing relative to atmospheric demand), surface water input intensity (rain and snowmelt), and observed winter ET (winter AET) impact multiple water balance metrics that determine water available for runoff (WAfR). Overall, we found that WAfR had the strongest relationship with energy‐water asynchrony (adjusted r2 = 0.52) and that winter AET was correlated to total water year evapotranspiration but not to other water balance metrics. Stepwise regression analysis demonstrated that none of the tested mechanisms were strongly related to the Budyko‐type runoff anomaly (highest adjusted r2 = 0.21). We, therefore, conclude that WAfR from continental montane forests is most sensitive to the degree of energy‐water asynchrony that occurs. The results of this empirical study identify the physical mechanisms driving variability of WAfR in continental montane forests and are thus broadly relevant to the hydrologic management and modelling communities.

Natural selection on floral volatiles and other traits can change with snowmelt timing and summer precipitation.

Climate change is disrupting floral traits that mediate mutualistic and antagonistic species interactions. Plastic responses of these traits to multiple shifting conditions may be adaptive, depending on natural selection in new environments. We manipulated snowmelt date over three seasons (3-11 d earlier) in factorial combination with growing-season precipitation (normal, halved, or doubled) to measure plastic responses of volatile emissions and other floral traits in Ipomopsis aggregata. We quantified how precipitation and early snowmelt affected selection on traits by seed predators and pollinators. Within years, floral emissions did not respond to precipitation treatments but shifted with snowmelt treatment depending on the year. Across 3 yr, emissions correlated with both precipitation and snowmelt date. These effects were driven by changes in soil moisture. Selection on several traits changed with earlier snowmelt or reduced precipitation, in some cases driven by predispersal seed predation. Floral trait plasticity was not generally adaptive. Floral volatile emissions shifted in the face of two effects of climate change, and the new environments modulated selection imposed by interacting species. The complexity of the responses underscores the need for more studies of how climate change will affect floral volatiles and other floral traits.

Study on physical properties and snow-melting performance of multilayer composite conductive-pervious concrete for improving the snow-melting efficiency and energy consumption of ECON

One of the most significant challenges facing transport networks in cold regions is snow accumulation on road surfaces. This can lead to traffic congestion and safety issues. While electrically conductive concrete (ECON) heated pavement systems (HPS) offer several advantages, including stability, and low environmental impact, they also present certain limitations, such as low snow-melting efficiency and high snow-melting energy consumption. In this study, a SiO2 aerogel mortar thermal-insulation layer and a self-compacting concrete structural layer were set underneath the reduced graphene oxide (RGO) composite conductive concrete, and the straight pervious channels were prefabricated, to reduce the snow-melting efficiency and energy consumption through the preparation of multilayer composite conductive-pervious concrete integrated specimen. The initial objective was to investigate the influence of SiO2 aerogel substitution rate on the mechanical properties and thermal conductivity of thermal-insulation mortar. Secondly, the impact of the thickness of the conductive layer and thermal-insulation layer on the mechanical properties of the integrated specimen was analyzed. Finally, the impact of SiO2 aerogel thermal-insulation mortar and straight pervious channels on the integrated specimen's snow-melting performance was evaluated through a snow-melting test, which assessed the efficiency and energy consumption of the snow-melting process. The results indicate that when the SiO2 aerogel substitution rate was 40 %, the thermal-insulation mortar exhibited favorable mechanical and thermal-insulation properties. The 5 cm conductive layer and the 1 cm thermal-insulation layer achieved good mechanical properties of the integrated specimen. In comparison to single-layer composite conductive concrete, the snow-melting time and energy consumption of multilayer composite conductive-pervious concrete integrated specimen were reduced by 23.05 % and 21.30 %, respectively. The straight pervious channels permit the immediate discharge of water produced by snow melting, thereby reducing the heat transfer from the snow-melting board to the water film. The setting of SiO2 aerogel thermal-insulation mortar enables the retention of heat for the heating of the snow-melting board and snow melting, which improves the snow-melting performance.

Increase in gross primary production of boreal forests balanced out by increase in ecosystem respiration

Changes in the net carbon sink of boreal forests constitute a major source of uncertainty in the future global carbon budget and, hence, climate change projections. The annual net ecosystem exchange of carbon dioxide (CO2) controlling the terrestrial carbon stock results from the small difference between respiratory CO2 release and the photosynthetic CO2 uptake by vegetation. The boreal forest, and the boreal biome in general, is regarded as a persistent and even increasing net carbon sink. However, decreases in photosynthetic CO2 uptake and/or concurrent increases in respiratory CO2 release under a changing climate may turn boreal forests from a net sink to a net source of CO2. Here, we assessed the interannual variability of the boreal forest net CO2 sink-source strength and its two component fluxes from 1981 to 2018. Our remote sensing approach - trained by net CO2 flux observations at eddy covariance sites across the circumpolar boreal forests - employs satellite-derived retrievals of snowmelt timing, landscape freeze-thaw status, and yearly maximum estimates of the normalized difference vegetation index as a proxy for peak vegetation productivity. Our results suggest that for the period 2000–2018, the mean annual evergreen boreal forest CO2 photosynthetic uptake (gross primary productivity) was 2.8±0.2 Pg C y−1 (1.6±0.1 Pg C y−1 for Eurasia and 1.2±0.1 Pg C y−1 for North America). In contrast to earlier studies results obtained here do not indicate a clear increasing trend in the circumpolar evergreen boreal forest CO2 sink. The increase in photosynthetic CO2 uptake is compensated by increasing respiratory releases with both component fluxes showing considerable interannual variabilities.

Snowpack permanence shapes the growth and dynamic of non-structural carbohydrates in Juniperus communis in alpine tundra

Climate warming is altering snowpack permanence in alpine tundra, modifying shrub growth and distribution. Plant acclimation to snowpack changes depends on the capability to guarantee growth and carbon storage, suggesting that the content of non-structural carbohydrates (NSC) in plant organs can be a key trait to depict the plant response under different snow regimes.To test this hypothesis, we designed a 3-years long manipulative experiment aimed at evaluating the effect of snow melt timing (i.e., early, control, and late) on NSC content in needles, bark and wood of Juniperus communis L. growing at high elevation in the Alps.Starch evidenced a general decrease from late spring to summer in control and early melting, while starch was low but stable in plants subjected to a late snow melt. Leaves, bark and wood have different level of soluble NSC changing during growing season: in bark, sugars content decreased significantly in late summer, while there was no seasonal effect in needles and wood. Soluble NSC and starch were differently related with the plant growth, when considering different tissues and snow treatment. In leaf and bark we observed a starch depletion in control and early melting plants, consistently to a higher growth (i.e., twig elongation), while in late snow melt, we did not find any significant relationship between growth and NSC concentration.Our findings confirmed that snowpack duration affects the onset of the growing season promoting a change in carbon allocation in plant organs and, between bark and wood in twigs. Finally, our results suggest that plants, at this elevation, could take advantage from an early snow melt caused by climate warming, most likely due to photosynthetic activity by maintaining the level of reserves and enhancing the carbon investment for growth.

Phase-Change/Salt-Based Slow-Release Composite Material for Anti-Icing and Snow-Melting

Currently, self-desiccating asphalt mixtures on roads mainly incorporate phase-change materials or salt-based slow-release agents individually for de-icing. However, pure phase-change material mixtures have limited anti-freezing efficiency and short heat-release duration, making them impractical for large-scale snow melting; meanwhile, salt-based slow-release agents suffer from rapid deterioration in de-icing performance. To address these issues encountered, herein, we introduce the phase-change/salt-based slow-release composite materials via the integration of these two materials and investigate their pavement and de-icing performance with the asphalt mixture. For the pavement performance, the optimal asphalt–aggregate ratio for the anti-icing asphalt mixture was found to be 5.1% For anti-bonding and de-icing performance, the electrical conductivity tests, bonding pull-off tests, and interfacial contact melting experiments were conducted. The results indicate that the latent heat of the TH-ME5 (phase-change material) can delay the decrease in environmental temperature and inhibit salt release from T-SEN (salt-based slow-release material), thereby extending the lifespan of the anti-icing asphalt mixture. These results demonstrate that the synergistic effect between the two components of the composite material not only enhance the snow-melting and de-icing performance of the asphalt pavement but also prolong the snow-melting time of the pavement in a low-temperature environment.

Temporal and spatial variation in the direct and indirect effects of climate on reproduction in alpine populations of Ranunculus acris L

AbstractPlant reproduction in alpine environments is affected by climate both directly through climate impacts on growth and phenology, and indirectly through impacts on the biotic interactions affecting pollination success. These effects can be highly variable in time and space. In this study we investigated how different abiotic and biotic factors influence reproductive investment and success in populations of Ranunculus acris across an alpine landscape over a two-year period. In an alpine area at Finse, southern Norway, we measured reproductive investment (total seed mass) and reproductive success (seed-set rate) in 38 sites differing in temperature (related to elevation) and length of the growing season (related to time of snowmelt). To assess biotic interactions, we measured floral density and pollinator visits and conducted a supplemental pollen experiment. Reproductive investment and success increased with temperature, but only when floral density and/or number of pollinator visits was high, and only in the warmer year (2016). Reproduction in R. acris was pollen-limited in both years, especially at warmer temperature and in sites with early snowmelt. Pollinator visits increased with temperature and with higher floral density, suggesting a shift in relative importance of the biotic factors (from plants to pollinators) in limiting reproduction with increasing temperature. Our study shows that reproductive investment and success in R. acris is affected by climate through the interactive effects of abiotic and biotic processes. These effects vary between years and across the landscape, suggesting a potential for larger-scale buffering of climate change effects in heterogeneous landscapes.

Phenological responses of alpine snowbed communities to advancing snowmelt.

Climate change is leading to advanced snowmelt date in alpine regions. Consequently, alpine plant species and ecosystems experience substantial changes due to prolonged phenological seasons, while the responses, mechanisms and implications remain widely unclear. In this 3-year study, we investigated the effects of advancing snowmelt on the phenology of alpine snowbed species. We related microclimatic drivers to species and ecosystem phenology using in situ monitoring and phenocams. We further used predictive modelling to determine whether early snowmelt sites could be used as sentinels for future conditions. Temperature during the snow-free period primarily influenced flowering phenology, followed by snowmelt timing. Salix herbacea and Gnaphalium supinum showed the most opportunistic phenology, while annual Euphrasia minima struggled to complete its phenology in short growing seasons. Phenological responses varied more between years than sites, indicating potential local long-term adaptations and suggesting these species' potential to track future earlier melting dates. Phenocams captured ecosystem-level phenology (start, peak and end of phenological season) but failed to explain species-level variance. Our findings highlight species-specific responses to advancing snowmelt, with snowbed species responding highly opportunistically to changes in snowmelt timings while following species-specific developmental programs. While species from surrounding grasslands may benefit from extended growing seasons, snowbed species may become outcompeted due to internal-clock-driven, non-opportunistic senescence, despite displaying a high level of phenological plasticity.

Modelling postfire recovery of snow albedo and forest structure to understand drivers of decades of reduced snow water storage and advanced snowmelt timing

AbstractForest fires darken snow albedo and degrade forest structure, ultimately reducing peak snow–water storage, and advancing snowmelt timing for up to 15 years following fire. To date, no volumetric estimates of watershed‐scale postfire effects on snow–water storage and snowmelt timing have been quantified over decades of postfire recovery. Using postfire parameterizations in a spatially‐distributed snow mass and energy balance model, SnowModel, we estimated postfire recovery of forest fire effects on snow–water equivalent (SWE) and snowmelt timing over decades following fire. Using this model, we quantified volumetric recovery of forest fire effects on snow hydrology across a chronosequence of eight sub‐alpine forests burned between 2000 and 2019 in the Triple Divide of western Wyoming. We found that immediately following fire, forest fire effects reduced snow–water storage by 6.8% (SD = 11.2%) and advanced the snow disappearance date by 31 days (SD = 9 days). Across the 15‐year recovery following fire, forest fire effects reduced snow–water storage by 4.5% (SD = 11.4%). Postfire effects on snow hydrology generally recovered over time, but still persisted beyond 15‐years following fire due to the observed postfire shift from forest to open meadow. Estimates of postfire reductions on peak SWE summed over the entire 15‐year postfire recovery period were 18 times greater than the immediate losses in the first winter following fire alone. These lasting effects of forest fires on snow hydrology decades following fire highlight the importance of postfire parameterizations for more accurate watershed‐scale volumetric estimates of forest fire effects on snow–water resources.

Synthetic Aperture Radar Monitoring of Snow in a Reindeer-Grazing Landscape

Snow cover and runoff play an important role in the Arctic environment, which is increasingly affected by climate change. Over the past 30 years, winter temperatures in northern Sweden have risen by 2 °C, accompanied by an increase in precipitation. This has led to a higher incidence of thaw–freeze and rain-on-snow events. Snow properties, such as the snow depth and longevity, and the timing of snowmelt in spring significantly impact the alpine tundra vegetation. The emergent vegetation at the edge of the snow patches during spring and summer constitutes an essential nutrient supply for reindeer. We have used Sentinel-1 synthetic aperture radar (SAR) to determine the onset of the surface melt and the end of the snow cover in the core reindeer grazing area of the Laevás Sámi reindeer-herding community in northern Sweden. Using SAR data from March to August during the period 2017 to 2021, the start of the surface melt is identified by detecting the season’s backscatter minimum. The end of the snow cover is determined using a threshold approach. A comparison between the results of the analysis of the end of the snow cover from Sentinel-1 and in situ measurements, for the years 2017 to 2020, derived from an automatic weather station located in Laevásvággi reveals a 2- to 10-day difference in the snow-free ground conditions, which indicates that the method can be used to investigate when the ground is free of snow. VH data are preferred to VV data due to the former’s lower sensitivity to temporary wetting events. The outcomes from the season backscatter minimum demonstrate a distinct 25-day difference in the start of the runoff between the 5 investigated years. The backscatter minimum and threshold-based method used here serves as a valuable complement to global snowmelt monitoring.

Female‐biased population sex ratios caused by genetic rather than ecological mechanisms in dwarf willow (Salix herbacea L.)

Abstract Biased sex ratios among reproductive individuals are common in plants, but the underlying mechanisms, as well as the evolutionary consequences, are not well understood. The classical theory of Düsing and Fisher predicts an equal primary sex ratio at seed production, based on the selective advantage of the rare sex. Biased sex ratios among reproductive plants can arise from sexual dimorphism in survival and flowering. Sex ratio biases can also be present from the seed stage; in these cases, assumptions of Düsing's and Fisher's theory, for example, random mating or demographic equilibrium, are thought to be violated. We investigated mechanisms leading to female‐biased sex ratios in the arctic‐alpine dwarf willow Salix herbacea L. We studied sex ratios in three natural populations over 3 years as well as in 29 crosses (full‐sib families) under controlled conditions over four growth periods. We tested whether sex ratio was associated with habitat parameters (elevation and snowmelt time), or with germination, survival or flowering, and whether females and males differed in size or flowering that may cause observation bias. We detected a strong and consistent female bias, both in natural populations (sex ratio [proportion of females]: 0.71–0.82) and in our controlled experiment (overall sex ratio: 0.70–0‐72). Female bias became more pronounced with increasing elevation. Our data did not support sexual dimorphism in size or flowering. Family sex ratios varied largely (from 0.25 to 1), including many female‐biased families, unbiased families and two male‐biased families. Families with lower germination, seedling establishment, survival or flowering did not have stronger female bias, indicating that intrinsically higher survival or flowering in females does not explain overall female bias. Synthesis. Our results suggest that sex ratio bias in S. herbacea is already present in seeds and does not arise through intrinsic differences between sexes. Candidate mechanisms that can lead to both overall female bias and variation in sex ratio among families are meiotic drive or cyto‐nuclear interactions. The pioneer habit of Salix may lead to non‐equilibrium population dynamics that allow for the long‐term persistence of variable genetic sex ratio distortion systems that arise from genetic conflict.

Early snowmelt advances flowering phenology and disrupts the drivers of pollinator visitation in an alpine ecosystem

AbstractClimate change is altering interactions among plants and pollinators. In alpine ecosystems, where snowmelt timing is a key driver of phenology, earlier snowmelt may generate shifts in plant and pollinator phenology that vary across the landscape, potentially disrupting interactions. Here we ask how experimental advancement of snowmelt timing in a topographically heterogeneous alpine-subalpine landscape impacts flowering, insect pollinator visitation, and pathways connecting key predictors of plant-pollinator interaction. Snowmelt was advanced by an average of 13.5 days in three sites via the application of black sand over snow in manipulated plots, which were paired with control plots. For each forb species, we documented flowering onset and counted flowers throughout the season. We also performed pollinator observations to measure visitation rates. The majority (79.3%) of flower visits were made by dipteran insects. We found that plants flowered earlier in advanced snowmelt plots, with the largest advances in later-flowering species, but flowering duration and visitation rate did not differ between advanced snowmelt and control plots. Using piecewise structural equation models, we assessed the interactive effects of topography on snowmelt timing, flowering phenology, floral abundance, and pollinator visitation. We found that these factors interacted to predict visitation rate in control plots. However, in plots with experimentally advanced snowmelt, none of these predictors explained a significant amount of variation in visitation rate, indicating that different predictors are needed to understand the processes that directly influence pollinator visitation to flowers under future climate conditions. Our findings demonstrate that climate change-induced early snowmelt may fundamentally disrupt the predictive relationships among abiotic and biotic drivers of plant-pollinator interactions in subalpine-alpine environments.

Limited sensitivity of permafrost soils to heavy rainfall across Svalbard ecosystems

Together with warming air temperatures, Arctic ecosystems are expected to experience increases in heavy rainfall events. Recent studies report accelerated degradation of permafrost under heavy rainfall, which could put significant amounts of soil carbon and infrastructure at risk. However, controlled experimental evidence of rainfall effects on permafrost thaw is scarce. We experimentally tested the impact and legacy effect of heavy rainfall events in early and late summer for five sites varying in topography and soil type on the High Arctic archipelago of Svalbard. We found that effects of heavy rainfall on soil thermal regimes are small and limited to one season. Thaw rates increased under heavy rainfall in a loess terrace site, but not in polygonal tundra soils with higher organic matter content and water tables. End-of-season active layer thickness was not affected. Rainfall application did not affect soil temperature trends, which appeared driven by timing of snowmelt and organic layer thickness, particularly during early summer. Late summer rainfall was associated with slower freeze-up and colder soil temperatures the following winter. This implies that rainfall impacts on Svalbard permafrost are limited, locally variable and of short duration. Our findings diverge from earlier reports of sustained increases in permafrost thaw following extreme rainfall, but are consistent with observations that maritime permafrost regions such as Svalbard show lower rainfall sensitivity than continental regions. Based on our experiment, no substantial in-situ effects of heavy rainfall are anticipated for thawing of permafrost on Svalbard under future warming. However, further work is needed to quantify permafrost response to local redistribution of active layer flow under natural rainfall extremes. In addition, replication of experiments across variable Arctic regions as well as long-term monitoring of active layers, soil moisture and local climate will be essential to develop a panarctic perspective on rainfall sensitivity of permafrost.

Multi-decadal floodplain classification and trend analysis in the Upper Columbia River valley, British Columbia

Abstract. Floodplain wetland ecosystems experience significant seasonal water fluctuation over the year, resulting in a dynamic hydroperiod, with a range of vegetation community responses. This paper assesses trends and changes in land cover and hydroclimatological variables, including air temperature, river discharge, and water level in the Upper Columbia River Wetlands (UCRW), British Columbia, Canada. A land cover classification time series from 1984 to 2022 was generated from the Landsat image archive using a random forest algorithm. Peak river flow timing, duration, and anomalies were examined to evaluate temporal coincidence with observed land cover trends. The land cover classifier used to segment changes in wetland area and open water performed well (kappa of 0.82). Over the last 4 decades, observed river discharge and air temperature have increased, precipitation has decreased, the timing of peak flow is earlier, and the flow duration has been reduced. The frequency of both high-discharge events and dry years have increased, indicating a shift towards more extreme floodplain flow behavior. These hydrometeorological changes are associated with a shift in the timing of snowmelt, from April to mid-May, and with seasonal changes in the vegetative communities over the 39-year period. Thus, woody shrubs (+6 % to +12 %) have expanded as they gradually replaced marsh and wet-meadow land covers with a reduction in open-water area. This suggests that increasing temperatures have already impacted the regional hydrology, wetland hydroperiod, and floodplain land cover in the Upper Columbia River valley. Overall, there is substantial variation in seasonal and annual land cover, reflecting the dynamic nature of floodplain wetlands, but the results show that the wetlands are drying out with increasing areas of woody/shrub habitat and loss of aquatic habitat. The results suggest that floodplain wetlands, particularly marsh and open-water habitats, are vulnerable to climatic and hydrological changes that could further reduce their areal extent in the future.

How three-dimensional forest structure regulates the amount and timing of snowmelt across a climatic gradient of snow persistence

Across the western United States, forests are changing rapidly, with uncertain impacts on snowmelt water resources. Snow partitioning is controlled by forest effects on interception, radiation, and sublimation. Yet, models often lack snow measurements with sufficiently high spatial and temporal resolution across gradients of forest structure to accurately represent these fine-scale processes. Here, we utilize four Snowtography stations in Arizona, in the lower Colorado River Basin, with daily measurements over 3–5 years at ~110 positions distributed across gradients of forest structure resulting from wildfires and mechanical thinning. We combine Snowtography with lidar snapshots of forest and snow to train a high-resolution snow model and run it for 6 years to quantify how forest structure regulates snowpack and snowmelt. These study sites represent a climate gradient from lower/warmer ephemeral snowpack (~2,100 m asl) to higher/colder seasonal snowpack (~2,800 m asl). Forest cover reduced snowpack and snowmelt through canopy sublimation. Forest advanced snowmelt timing at lower/warmer sites but delayed it at higher/colder sites. Within canopy gaps, shaded cool edges had the greatest peak snow water equivalent (SWE). Surprisingly, sunny/warm gap edges produced more snowmelt than cool edges, because high radiation melted snow quickly, reducing exposure to sublimation. Therefore, peak SWE is not an ideal proxy for snowmelt volume from ephemeral snowpacks, which are becoming more prevalent due to warming. The results imply that forest management can influence the amount and timing of snowmelt, and that there may be decision trade-offs between enhancing forest resilience through delayed snowmelt and maximizing snowmelt volumes for downstream water resources.

Interannual Variations in Spring Snowmelt Timing of Alaskan Black Spruce Forests Using a Bulk‐Surface Energy Balance Approach

AbstractSpring snowmelt occurs for a short duration on an annual time scale, but their timings considerably affect the carbon and hydrological cycle in high‐latitude ecosystems. Here, we developed a simple snowmelt model, treating the ecosystem surface as a bulk‐surface layer. Energy fluxes across this bulk surface and the snow‐soil boundary determine snow temperature and the energy utilized for snowmelt. Parameterizing the bulk surface using decade‐long eddy covariance site data from two Alaskan open black spruce forests offered an opportunity to quantitatively evaluate meteorological drivers affecting snowmelt timings without the needs for detailed canopy information. The sensitivity analysis suggested that the total snowfall on the forest floor, ranging from 0.35 m in 2016 to about 1 m in 2018 and 2020, was the most crucial driver for snowmelt timing. This factor accounted for a 10‐day difference in the interannual variations in snow disappearance dates. The importance of the snowfall varied from year to year, and in 2013, the late snowmelt was characterized by low air temperatures, which increased sensible heat loss from the snowpack. The importance of atmospheric radiation was revealed in relatively warm years, such as 2016 and 2019. Our modeling approach necessitates adjusting one empirical parameter that reflects the heat conductivity from the bulk surface to the snow, based on observations. Nevertheless, despite this need for adjustment, the bulk‐surface approach helps identify important meteorological drivers underlying observed snowmelt within a simple theoretical framework.

Forest-floor respiration, N2O fluxes, and CH4 fluxes in a subalpine spruce forest: drivers and annual budgets

Abstract. Forest ecosystems play an important role in the global carbon (C) budget by sequestering a large fraction of anthropogenic carbon dioxide (CO2) emissions and by acting as important methane (CH4) sinks. The forest-floor greenhouse gas (GHG; CO2, CH4, and nitrous oxide (N2O)) flux, i.e., from soil and understory vegetation, is one of the major components to consider when determining the C or GHG budget of forests. Although winter fluxes are essential to determine the annual C budget, only very few studies have examined long-term, year-round forest-floor GHG fluxes. Thus, we aimed to (i) quantify seasonal and annual variations of forest-floor GHG fluxes; (ii) evaluate their drivers, including the effects of snow cover, timing, and amount of snowmelt; and (iii) calculate annual budgets of forest-floor GHG fluxes for a subalpine spruce forest in Switzerland. We measured GHG fluxes year-round during 4 years with four automatic large chambers at the ICOS Class 1 Ecosystem station Davos (CH-Dav). We applied random forest models to investigate environmental drivers and to gap-fill the flux time series. The forest floor emitted 2336 g CO2 m−2 yr−1 (average over 4 years). Annual and seasonal forest-floor respiration responded most strongly to soil temperature and snow depth. No response of forest-floor respiration to leaf area index or photosynthetic photon flux density was observed, suggesting a strong direct control of soil environmental factors and a weak, or even lacking, indirect control of canopy biology. Furthermore, the forest floor was a consistent CH4 sink (−0.71 g CH4 m−2 yr−1), with annual fluxes driven mainly by snow depth. Winter CO2 fluxes were less important for the CO2 budget (6.0 %–7.3 %), while winter CH4 fluxes contributed substantially to the annual CH4 budget (14.4 %–18.4 %). N2O fluxes were very low (0.007 g N2O m−2 yr−1), negligible for the forest-floor GHG budget at our site. In 2022, the warmest year on record with below-average precipitation at the Davos site, we observed a substantial increase in forest-floor respiration compared with other years. The mean forest-floor GHG budget indicated emissions of 2319 ± 200 g CO2 eq. m−2 yr−1 (mean ± standard deviation (SD) over all years), with respiration fluxes dominating and CH4 offsetting a very small proportion (0.8 %) of the CO2 emissions. Due to the relevance of snow cover, we recommend year-round measurements of GHG fluxes with high temporal resolution. In a future with increasing temperatures and less snow cover due to climate change, we expect increased forest-floor respiration at this subalpine site modulating the carbon sink of the forest ecosystem.

Impact of Wildfires on Land Surface Cold Season Climate in the Northern High-Latitudes: A Study on Changes in Vegetation, Snow Dynamics, Albedo, and Radiative Forcing

Anthropogenic climate change is increasing the occurrence of wildfires, especially in northern high latitudes, leading to a shift in land surface climate. This study aims to determine the predominant climatic effects of fires in boreal forests to assess their impact on vegetation composition, surface albedo, and snow dynamics. The influence of fire-induced changes on Earth’s radiative forcing is investigated, while considering variations in burn severity and postfire vegetation structure. Six burn sites are explored in central Alaska’s boreal region, alongside six control sites, by utilizing Moderate Resolution Imaging Spectroradiometer (MODIS)-derived albedo, Leaf Area Index (LAI), snowmelt timing data, AmeriFlux radiation, National Land Cover Database (NLCD) land cover, and Monitoring Trends in Burn Severity (MTBS) data. Key findings reveal significant postfire shifts in land cover at each site, mainly from high- to low-stature vegetation. A continuous increase in postfire surface albedo and negative surface shortwave forcing was noted even after 12 years postfire, particularly during the spring and at high-severity burn areas. Results indicate that the cooling effect from increased albedo during the snow season may surpass the warming effects of earlier snowmelt. The overall climate impact of fires depends on burn severity and vegetation composition.