Seasonal Snow Research Articles

Spatial patterns of climate change across the Paleocene–Eocene Thermal Maximum

The Paleocene-Eocene Thermal Maximum (PETM; 56 Ma) is one of our best geological analogs for understanding climate dynamics in a "greenhouse" world. However, proxy data representing the event are only available from select marine and terrestrial sedimentary sequences that are unevenly distributed across Earth's surface, limiting our view of the spatial patterns of climate change. Here, we use paleoclimate data assimilation (DA) to combine climate model and proxy information and create a spatially complete reconstruction of the PETM and the climate state that precedes it ("PETM-DA"). Our data-constrained results support strong polar amplification, which in the absence of an extensive cryosphere, is related to temperature feedbacks and loss of seasonal snow on land. The response of the hydrological cycle to PETM warming consists of a narrowing of the Intertropical Convergence Zone, off-equatorial drying, and an intensification of seasonal monsoons and winter storm tracks. Many of these features are also seen in simulations of future climate change under increasing anthropogenic emissions. Since the PETM-DA yields a spatially complete estimate of surface air temperature, it yields a rigorous estimate of global mean temperature change (5.6 ∘C; 5.4 ∘C to 5.9 ∘C, 95% CI) that can be used to calculate equilibrium climate sensitivity (ECS). We find that PETM ECS was 6.5 ∘C (5.7 ∘C to 7.4 ∘C, 95% CI), which is much higher than the present-day range. This supports the view that climate sensitivity increases substantially when greenhouse gas concentrations are high.

Characteristics of Snow Depth and Snow Phenology in the High Latitudes and High Altitudes of the Northern Hemisphere from 1988 to 2018

Snow cover is an important part of the Earth’s surface and its changes affect local and even global climates due to the high albedo and heat insulation. However, it is difficult to directly compare the results of previous studies on changes in snow cover in the Northern Hemisphere mainland (NH) due to the use of different datasets, research methods, or study periods, and a lack comparison in terms of the differences and similarities at high latitudes and high altitudes. By using snow depth datasets, we analyzed the spatio-temporal distributions and variations in snow depth (SD) and snow phenology (SP) in the NH and nine typical areas. This study revealed that SD in the NH generally decreased significantly (p < 0.01) from 1988 to 2018, with a rate of −0.55 cm/decade. Changes in SD were insignificant at high altitudes, but significant decreases were found at high latitudes. With regard to SP, the snow cover onset day (SCOD) advanced in 31.57% of the NH and was delayed in 21.10% of the NH. In typical areas such as the Rocky Mountains, the West Siberian Plain, and the Central Siberian Plateau, the SCOD presented significant advancing trends, while a significant delay was the trend observed in the Eastern European Plain. The snow cover end day (SCED) advanced in 37.29% of the NH and was delayed in 14.77% of the NH. Negative SCED trends were found in most typical areas. The snow cover duration (SCD) and snow season length (SSL) showed significant positive trends in the Rocky Mountains, while significant negative trends were found in the Qinghai–Tibet Plateau. The results of this comprehensive comparison showed that most typical areas were characterized by decreased SD, advanced SCOD and SCED, and insignificantly increasing SCD and SSL trends. The SCD and SSL values were similar at high latitudes, while the SSL value was larger than the SCD value at high altitudes. The SD exhibited similar interannual fluctuation characteristics as the SCD and SSL in each typical area. The SCD and SSL increased (decreased) with advanced (delayed) SCODs.

Winter runoff events pose an unquantified continental-scale risk of high wintertime nutrient export

Winters in snow-covered regions have warmed, likely shifting the timing and magnitude of nutrient export, leading to unquantified changes in water quality. Intermittent, seasonal, and permanent snow covers more than half of the global land surface. Warming has reduced the cold conditions that limit winter runoff and nutrient transport, while cold season snowmelt, the amount of winter precipitation falling as rain, and rain-on-snow have increased. We used existing geospatial datasets (rain-on-snow frequency overlain on nitrogen and phosphorous inventories) to identify areas of the contiguous United States (US) where water quality could be threatened by this change. Next, to illustrate the potential export impacts of these events, we examined flow and turbidity data from a large regional rain-on-snow event in the United States’ largest river basin, the Mississippi River Basin. We show that rain-on-snow, a major flood-generating mechanism for large areas of the globe (Berghuijs et al 2019 Water Resour. Res. 55 4582–93; Berghuijs et al 2016 Geophys. Res. Lett. 43 4382–90), affects 53% of the contiguous US and puts 50% of US nitrogen and phosphorus pools (43% of the contiguous US) at risk of export to groundwater and surface water. Further, the 2019 rain-on-snow event in the Mississippi River Basin demonstrates that these events could have large, cascading impacts on winter nutrient transport. We suggest that the assumption of low wintertime discharge and nutrient transport in historically snow-covered regions no longer holds. Critically, however, we lack sufficient data to accurately measure and predict these episodic and potentially large wintertime nutrient export events at regional to continental scales.

Hydrological process controls on streamflow variability in a glacierized headwater basin

AbstractMountain glacierized headwaters are currently witnessing a transient shift in their hydrological and glaciological systems in response to rapid climate change. To characterize these changes, a robust understanding of the hydrological processes operating in the basin and their interactions is needed. Such an investigation was undertaken in the Peyto Glacier Research Basin, Canadian Rockies over 32 years (1988–2020). A distributed, physically based, uncalibrated glacier hydrology model was developed using the modular, object‐oriented Cold Region Hydrological Modelling Platform to simulate both on and off‐glacier high mountain processes and streamflow generation. The hydrological processes that generate streamflow from this alpine basin are characterized by substantial inter‐annual variability over the 32 years. Snowmelt runoff always provided the largest fraction of annual streamflow (44% to 89%), with smaller fractional contributions occurring in higher streamflow years. Ice melt runoff provided 10% to 45% of annual streamflow volume, with higher fractions associated with higher flow years. Both rainfall and firn melt runoff contributed less than 13% of annual streamflow. Years with high streamflow were on average 1.43°C warmer than low streamflow years, and higher streamflow years had lower seasonal snow accumulation, earlier snowmelt and higher summer rainfall than years with lower streamflow. Greater ice exposure in warmer, low snowfall (high rainfall) years led to greater streamflow generation. The understanding gained here provides insight into how future climate and increased meteorological variability may impact glacier meltwater contributions to streamflow and downstream water availability as alpine glaciers continue to retreat.

Sensitivity of Sea Ice Growth to Snow Properties in Opposing Regions of the Weddell Sea in Late Summer

AbstractThe sensitivity of sea ice to the contrasting seasonal and perennial snow properties in the southeastern and northwestern Weddell Sea is not yet considered in sea ice model and satellite remote sensing applications. However, the analysis of physical snowpack properties in late summer in recent years reveals a high fraction of melt‐freeze forms resulting in significant higher snow densities in the northwestern than in the eastern Weddell Sea. The resulting lower thermal conductivity of the snowpack, which is only half of what has been previously assumed in models in the eastern Weddell Sea, reduces the sea ice bottom growth by 18 cm during winter. In the northwest, however, the potentially formed snow ice thickness of 22 cm at the snow/ice interface contributes to additional 7 cm of thermodynamic ice growth at the bottom. This sensitivity study emphasizes the enormous impact of unappreciated regional differences in snowpack properties on the thermodynamic ice growth.

Moderate and Severe Hydrological Droughts in Europe Differ in Their Hydrometeorological Drivers

AbstractHydrological extreme events are generated by different sequences of hydrometeorological drivers, the importance of which may vary within the sample of drought events. Here, we investigate how the importance of different hydrometeorological driver sequences varies by event magnitude using a large sample of catchments in Europe. To do so, we develop an automated classification scheme for streamflow drought events. The classification scheme standardizes a previous qualitative drought typology and assigns events to one of eight drought event types—each characterized by a set of single or compounding drivers—using information about seasonality, precipitation deficits, and snow availability. The objective event classification reveals how drought drivers vary not just in space and by season, but also with event magnitude. Specifically, we show that (a) rainfall deficit droughts and cold snow season droughts are the dominant drought event type in Western Europe and Eastern and Northern Europe, respectively; (b) rainfall deficit and cold snow season droughts are important from autumn to spring while snowmelt and wet‐to‐dry season droughts are important in summer; and (c) moderate droughts are mainly driven by rainfall deficits while severe events are mainly driven by snowmelt deficits in colder climates and by streamflow deficits transitioning from the wet to the dry season in warmer climates. These differences in sequences of drought generation mechanisms for severe and moderate events suggest that future changes in hydrometeorological drivers may affect moderate and severe events differently.

The understudied winter: Evidence of how precipitation differences affect stream metabolism in a headwater

Climate change is causing pronounced shifts during winter in the US, including shortening the snow season, reducing snowpack, and altering the timing and volume of snowmelt-related runoff. These changes in winter precipitation patterns affect in-stream freeze-thaw cycles, including ice and snow cover, and can trigger direct and indirect effects on in-stream physical, chemical, and biological processes in ~60% of river basins in the Northern Hemisphere. We used high-resolution, multi-parameter data collected in a headwater stream and its local environment (climate and soil) to determine interannual variability in physical, chemical, and biological signals in a montane stream during the winter of an El Niño and a La Niña year. We observed ~77% greater snow accumulation during the El Niño year, which caused the formation of an ice dam that shifted the system from a primarily lotic to a lentic environment. Water chemistry and stream metabolism parameters varied widely between years. They featured anoxic conditions lasting over a month, with no observable gross primary production (GPP) occurring under the ice and snow cover in the El Niño year. In contrast, dissolved oxygen and GPP remained relatively high during the winter months of the La Niña year. These redox and metabolic changes driven by changes in winter precipitation have significant implications for water chemistry and biological functioning beyond the winter. Our study suggests that as snow accumulation and hydrologic conditions shift during the winter due to climate change, hot-spots and hot-moments for biogeochemical processing may be reduced, with implications for the downstream movement of nutrients and transported materials.

A camera trap‐based assessment of climate‐driven phenotypic plasticity of seasonal moulting in an endangered carnivore

AbstractFor many species, the ability to rapidly adapt to changes in seasonality is essential for long‐term survival. In the Arctic, seasonal moulting is a key life‐history event that provides year‐round camouflage and thermal protection. However, increased climatic variability of seasonal events can lead to phenological mismatch. In this study, we investigated whether winter‐white (white morph) and winter‐brown (blue morph) Arctic foxes (Vulpes lagopus) could adjust their winter‐to‐summer moult to match local environmental conditions. We used camera trap images spanning an eight‐year period to quantify the timing and rate of fur change in a polymorphic subpopulation in south‐central Norway. Seasonal snow cover duration and temperature governed the phenology of the spring moult. We observed a later onset and longer moulting duration with decreasing temperature and longer snow season. Additionally, white foxes moulted earlier than blue in years with shorter periods of snow cover and warmer temperatures. These results suggest that phenotypic plasticity allows Arctic foxes to modulate the timing and rate of their spring moult as snow conditions and temperatures fluctuate. With the Arctic warming at an unprecedented rate, understanding the capacity of polar species to physiologically adapt to a changing environment is urgently needed in order to develop adaptive conservation efforts. Moreover, we provide the first evidence for variations in the moulting phenology of blue and white Arctic foxes. Our study underlines the different intraspecific selective pressures that can exist in populations where several morphs co‐occur, and illustrates the importance of integrating morph‐based differences in future management strategies of such polymorphic species.

Tracking the impacts of precipitation phase changes through the hydrologic cycle in snowy regions: From precipitation to reservoir storage

Cool season precipitation plays a critical role in regional water resource management in the western United States. Throughout the twenty-first century, regional precipitation will be impacted by rising temperatures and changing circulation patterns. Changes to precipitation magnitude remain challenging to project; however, precipitation phase is largely dependent on temperature, and temperature predictions from global climate models are generally in agreement. To understand the implications of this dependence, we investigate projected patterns in changing precipitation phase for mountain areas of the western United States over the twenty-first century and how shifts from snow to rain may impact runoff. We downscale two bias-corrected global climate models for historical and end-century decades with the Weather Research and Forecasting (WRF) regional climate model to estimate precipitation phase and spatial patterns at high spatial resolution (9 km). For future decades, we use the RCP 8.5 scenario, which may be considered a very high baseline emissions scenario to quantify snow season differences over major mountain chains in the western U.S. Under this scenario, the average annual snowfall fraction over the Sierra Nevada decreases by >45% by the end of the century. In contrast, for the colder Rocky Mountains, the snowfall fraction decreases by 29%. Streamflow peaks in basins draining the Sierra Nevada are projected to arrive nearly a month earlier by the end of the century. By coupling WRF with a water resources model, we estimate that California reservoirs will shift towards earlier maximum storage by 1–2 months, suggesting that water management strategies will need to adapt to changes in streamflow magnitude and timing.

Impacts of snow cover on the pattern and velocity of air flow in air convection embankments of sub-Arctic regions

In northern regions, air convection embankment (ACE) has been implemented to mitigate road subsidence caused by permafrost degradation. The seasonal snow cover largely alters the surface energy balance and adversely affects the thermal stability of the road. However, thermal characteristics of a closed ACE and the quantification of their impacts on talik development remain largely unknown, especially in the present and future context of global warming. Here, impacts of snow cover on the pattern and strength of the air circulation were investigated and quantified. Snow cover greatly weakened the cooling effect of the closed ACE side slopes. The pore air velocity of the crushed-rock layer was reduced by half and the mean annual heat flux increased by approximately 1.6 W/m2, in comparison to the snow-free case. Conversely, the U-shape closed ACE had a better cooling performance due to a stronger air convection in winter, which increased heat loss from the snow-free surface of the embankment center. Our simulations suggest that the U-shape ACE embankment is a potential long-term solution to mitigate permafrost thaw over the life service (50 years) of road embankments in sub-arctic regions. The net results of this study are imperative to improve engineered design and road maintenance in cold regions.

Review article: Global monitoring of snow water equivalent using high-frequency radar remote sensing

Abstract. Seasonal snow cover is the largest single component of the cryosphere in areal extent, covering an average of 46 × 106 km2 of Earth's surface (31 % of the land area) each year, and is thus an important expression and driver of the Earth's climate. In recent years, Northern Hemisphere spring snow cover has been declining at about the same rate (∼ −13 % per decade) as Arctic summer sea ice. More than one-sixth of the world's population relies on seasonal snowpack and glaciers for a water supply that is likely to decrease this century. Snow is also a critical component of Earth's cold regions' ecosystems, in which wildlife, vegetation, and snow are strongly interconnected. Snow water equivalent (SWE) describes the quantity of water stored as snow on the land surface and is of fundamental importance to water, energy, and geochemical cycles. Quality global SWE estimates are lacking. Given the vast seasonal extent combined with the spatially variable nature of snow distribution at regional and local scales, surface observations are not able to provide sufficient SWE information. Satellite observations presently cannot provide SWE information at the spatial and temporal resolutions required to address science and high-socio-economic-value applications such as water resource management and streamflow forecasting. In this paper, we review the potential contribution of X- and Ku-band synthetic aperture radar (SAR) for global monitoring of SWE. SAR can image the surface during both day and night regardless of cloud cover, allowing high-frequency revisit at high spatial resolution as demonstrated by missions such as Sentinel-1. The physical basis for estimating SWE from X- and Ku-band radar measurements at local scales is volume scattering by millimeter-scale snow grains. Inference of global snow properties from SAR requires an interdisciplinary approach based on field observations of snow microstructure, physical snow modeling, electromagnetic theory, and retrieval strategies over a range of scales. New field measurement capabilities have enabled significant advances in understanding snow microstructure such as grain size, density, and layering. We describe radar interactions with snow-covered landscapes, the small but rapidly growing number of field datasets used to evaluate retrieval algorithms, the characterization of snowpack properties using radar measurements, and the refinement of retrieval algorithms via synergy with other microwave remote sensing approaches. This review serves to inform the broader snow research, monitoring, and application communities on progress made in recent decades and sets the stage for a new era in SWE remote sensing from SAR measurements.

Effect of seasonal snow on the start of growing season of typical vegetation in Northern Hemisphere

Under global warming, seasonal snow takes faster melting rate than before, which greatly changes the hydrological cycle. In this study, by targeting three typical seasonal snow-covered land types (i.e., open shrubland, evergreen needleleaf forest and mixed forest) in the Northern Hemisphere, the start of growing season (SGS) has been found obviously advanced in the past years, greatly contributed by the faster melting rate of seasonal snow. It is manifested that significantly positive correlation has been found between SGS and May snow depth for open shrubs, March and April snow depth for evergreen needleleaf forests and March snow depth for mixed forests. However, such close association is not appeared in all the climate conditions of same vegetation. In the future, as the rate of melting snow becomes faster in the high emission of greenhouse gasses than the current situation, continuously advanced SGS will accelerate the change of vegetation distribution in the Northern Hemisphere. These findings offer insights into understanding the effect from seasonal snow on vegetation and promote the sustainable utilization of regional vegetation in the Northern Hemisphere.

Contrasting Fate of Western Third Pole's Water Resources Under 21st Century Climate Change

AbstractSeasonal melting of glaciers and snow from the western Third Pole (TP) plays important role in sustaining water supplies downstream. However, the future water availability of the region, and even today's runoff regime, are both hotly debated and inadequately quantified. Here, we characterize the contemporary flow regimes and systematically assess the future evolution of total water availability, seasonal shifts, and dry and wet discharge extremes in four most meltwater‐dominated basins in the western TP, by using a process‐based, well‐established glacier‐hydrology model, well‐constrained historical reference climate data, and the ensemble of 22 global climate models with an advanced statistical downscaling and bias correction technique. We show that these basins face sharply diverging water futures under 21st century climate change. In RCP scenarios 4.5 and 8.5, increased precipitation and glacier runoff in the Upper Indus and Yarkant basins more than compensate for decreased winter snow accumulation, boosting annual and summer water availability through the end of the century. In contrast, the Amu and Syr Darya basins will become more reliant on rainfall runoff as glacier ice and seasonal snow decline. Syr Darya summer river‐flows, already low, will fall by 16%–30% by end‐of‐century, and striking increases in peak flood discharge (by >60%), drought duration (by >1 month) and drought intensity (by factor 4.6) will compound the considerable water‐sharing challenges on this major transboundary river.

Evaluating GOES-16 ABI surface brightness temperature observation biases over the central Sierra Nevada of California

Thermal infrared imagery from NOAA's Geostationary Operational Environmental Satellites (GOES) R-series presents an opportunity to observe mountain surface temperatures at high temporal resolution. These observations are needed to better understand the transient surface energy balance, influenced by near-surface air temperatures and water fluxes ranging from evapotranspiration to snowmelt. From geostationary orbit, the GOES Advanced Baseline Imager (ABI) instrument views the Earth from a fixed longitude above the equator. ABI images therefore have increasingly off-nadir view angles and increasingly larger pixel dimensions the further a point on the Earth's surface is from the sub-satellite point. In thermal infrared imagery from ABI, these 2+ km pixels blur together the different surface temperatures of heterogeneous mountain landscapes. We compared GOES-16 ABI band 14 (11.2 μm) brightness temperatures to 90 m spatial resolution ASTER band 14 (11.3 μm) and 1 km spatial resolution MODIS band 31 (11.03 μm) brightness temperatures and investigated how differences change over space and time for a study region in the central Sierra Nevada of California for the 2017–2020 snow seasons. We demonstrated the necessity of orthorectifying ABI imagery of mountain terrain to correct for the parallax effect in off-nadir imagery. This reduced the mean difference between ABI and ASTER ~11 μm brightness temperatures from 1.6 °C to 1.0 °C and increased the r-squared value between ABI and ASTER thermal infrared brightness temperatures from 0.43 to 0.93. The ABI brightness temperatures were found to more closely match those of forest canopy temperatures than snow surface (with RMS differences of 1.2 °C and 3.0 °C respectively), and those of sunlit slopes as opposed to slopes facing away from the sun (with RMS differences of 1.6 °C and 3.4 °C respectively), in coincident ASTER imagery. This work demonstrates the use of GOES ABI, and associated challenges, for observing surface temperatures of forested mountain environments with seasonal snow.

Improving Mountain Snow and Land Cover Mapping Using Very-High-Resolution (VHR) Optical Satellite Images and Random Forest Machine Learning Models

Very-high-resolution (VHR) optical imaging satellites can offer precise, accurate, and direct measurements of snow-covered areas (SCA) with sub-meter to meter-scale resolution in regions of complex land cover and terrain. We explore the potential of Maxar WorldView-2 and WorldView-3 in-track stereo images (WV) for land and snow cover mapping at two sites in the Western U.S. with different snow regimes, topographies, vegetation, and underlying geology. We trained random forest models using combinations of multispectral bands and normalized difference indices (i.e., NDVI) to produce land cover maps for priority feature classes (snow, shaded snow, vegetation, water, and exposed ground). We then created snow-covered area products from these maps and compared them with coarser resolution satellite fractional snow-covered area (fSCA) products from Landsat (~30 m) and MODIS (~500 m). Our models generated accurate classifications, even with limited combinations of available multispectral bands. Models trained on a single image demonstrated limited model transfer, with best results found for in-region transfers. Coarser-resolution Landsat and MODSCAG fSCA products identified many more pixels as completely snow-covered (100% fSCA) than WV fSCA. However, while MODSCAG fSCA products also identified many more completely snow-free pixels (0% fSCA) than WV fSCA, Landsat fSCA products only slightly underestimated the number of completely snow-free pixels. Overall, our results demonstrate that strategic image observations with VHR satellites such as WorldView-2 and WorldView-3 can complement the existing operational snow data products to map the evolution of seasonal snow cover.

Decline in Seasonal Snow during a Projected 20-Year Dry Spell

Snowpack loss in midlatitude mountains is ubiquitously projected by Earth system models, though the magnitudes, persistence, and time horizons of decline vary. Using daily downscaled hydroclimate and snow projections, we examine changes in snow seasonality across the U.S. Pacific Southwest region during a simulated severe 20-year dry spell in the 21st century (2051–2070) developed as part of the 4th California Climate Change Assessment to provide a “stress test” for water resources. Across California’s mountains, substantial declines (30–100% loss) in median peak annual snow water equivalent accompany changes in snow seasonality throughout the region compared to the historic period. We find that 80% of historic seasonal snowpacks transition to ephemeral conditions. Subsetting empirical-statistical wildfire projections for California by snow seasonality transition regions indicates a two-to-four-fold increase in the area burned, consistent with recent observations of high elevation wildfires following extended drought conditions. By analyzing six of the major California snow-fed river systems, we demonstrate snowpack reductions and seasonality transitions result in concomitant declines in annual runoff (47–58% of historical values). The negative impacts to statewide water supply reliability by the projected dry spell will likely be magnified by changes in snowpack seasonality and increased wildfire activity.

Wildfire impacts on western United States snowpacks

Mountain snowpacks provide 53–78% of water used for irrigation, municipalities, and industrial consumption in the western United States. Snowpacks serve as natural reservoirs during the winter months and play an essential role in water storage for human consumption and ecosystem functions. However, wildfires across the West are increasing in severity, size, and frequency, progressively putting snowpacks at risk as they burn further into the seasonal snow zone. Following a fire, snow disappears 4–23 days earlier and melt rates increase by up to 57%. In a high burn severity fire in the Oregon Cascades, the black carbon and charred woody debris shed from burned trees onto the snowpack decreased the snow albedo by 40%. Canopy cover loss causes a 60% increase in solar radiation reaching the snow surface. Together, these effects produce a 200% increase in net shortwave radiation absorbed by the snowpack. This mini-review synthesizes the implications of wildfire for snow hydrology in mountainous watersheds with the primary aim to characterize wildfires' varied influences on the volume and timing of water resources across time scales (daily to decadal), space (plot to watershed) and burn severity (low to high). The increase in the geographical overlap between fire and snow poses unique challenges for managing snow-dominated watersheds and highlights deficiencies in research and operational snow hydrologic modeling, emphasizing the need for additional field and remote-sensing observations and model experiments.

Topographical Impact on Snow Cover Distribution in the Trans-Himalayan Region of Ladakh, India

This article presents the distribution of seasonal snow cover in the Trans-Himalayan region of Ladakh over the observation period of 2000–2019. Seasonal snow cover area and duration have been monitored and mapped based on the MODIS Normalised Difference Snow Index (NDSI). Using different MODIS cloud removal algorithms, monthly mean cloud-covered areas have been reduced to 3%. Pixel-wise approaches using Mann–Kendall (MK) and Sen’s slope trend tests allow to assess seasonal and annual trends of snow cover days (SCD) and snow cover area (SCA) across seven delineated subregions of Ladakh. Analyses include the impact of topographical parameters (elevation, slope, aspect). Overall, the mean annual SCA amounts to 42%, varying from 15% in August to 71% in February. However, large differences of SCA have been detected between and within subregions. The trend analysis of SCA shows a non-significant, slight increase for summer as well as for the entire year and a decrease for spring and winter seasons. The SCD trend analysis indicates more pixels with a significant increase than a decrease. In total, 12% of all pixels show an increasing trend in summer, 6% over the entire year, 3% in autumn, and 2% in spring and winter, whereas less than 2% of all pixels show a decreasing trend in all seasons. The results are important for regional irrigated agricultural production and freshwater supply in the context of climate change.

Impacts of climate change on mountain tourism: a review

Mountain landscapes and communities are highly sensitive and vulnerable to climate change. Tourism in mountain regions is highly dependent on natural resources and attractions which are very sensitive to climatic changes. This systematic review analyzing 276 papers, provides a comprehensive analysis of scientific literature dealing with climate change impacts on mountain tourism. While the impacts on the snow season are predominantly negative, impacts to summer season activities range from positive to negative. Contradictory results and lack of research in some regions and tourism activities means the overall impact is far from clear. We identified seven key knowledge gaps: underrepresentation of studies for South America and Africa, lack of appropriate data and indicators, an all-season perspective and investigation of opportunities, economic and socio-political consequences for mountain communities, the need for better science communication, and a lack of studies addressing liability and regulatory risks. Increasing our multidisciplinary understanding of potential climate impacts on mountain tourism and engaging stakeholders to prepare for the projected changes will help local populations in mountain communities create applicable and effective climate adaptation strategies.

The impact of winter warming and more frequent icing events on reindeer herder occupational safety, health, and wellbeing.

Northern Finland, like the rest of the Arctic, has experienced increases in mean annual temperature, the number of winter rains, the number of thaw-freeze days, the number of extremely warm weather events, and a shortened snow season. These changes have produced numerous problems for reindeer herders whose livelihoods rely on a healthy ecosystem with predictable weather patterns. We performed a scoping literature review to assess how climate change induced extreme weather has negatively impacted reindeer herding as well as the health and wellbeing of reindeer herders. Late snow cover negatively impacts reindeer herding through a more widely dispersed herd that increases the work to gather reindeer, leads to reduced calf weight, and results in less meat for sale. This increased labor, especially in extreme cold conditions, can also negatively impact reindeer herder health. Icing due to thaw-freeze and rain-on-snow events makes it impossible for reindeer to dig through the snow to access lichens, increasing the need for reindeer herders to keep the herd in winter enclosures and provide supplemental feed. Climate change induced weather events such as late snow cover and icing increase reindeer herder efforts and expenses, put their livelihood at risk, and put their health at risk.