Summer Snow Cover Research Articles

Summer snow on Arctic sea ice modulated by the Arctic Oscillation

Since the 1970s, Arctic sea ice has undergone unprecedented change, becoming thinner, less extensive and less resilient to summer melt. Snow’s high albedo greatly reduces solar absorption in sea ice and the upper ocean, which mitigates sea–ice melt and ocean warming. However, the drivers of summertime snow depth variability are unknown. The Arctic Oscillation is a mode of natural climate variability, influencing Arctic snowfall and air temperatures. Thus, it may affect summertime snow conditions on Arctic sea ice. Here we examine the role of the Arctic Oscillation in summer snow depth variability on Arctic sea ice in 1980–2020 using atmospheric reanalysis, snow modelling and satellite data. The positive phase leads to greater snow accumulation, ranging up to ~4.5 cm near the North Pole, and higher surface albedo in summer. There are more intense, frequent Arctic cyclones, cooler temperatures aloft and greater snowfall relative to negative and neutral phases; these conditions facilitate a more persistent summer snow cover, which may lessen sea-ice melt and ocean warming. The Arctic Oscillation influence on summertime snow weakens after 2007, which suggests that future warming and Arctic sea-ice loss might modify the relationship between the Arctic Oscillation and snow on Arctic sea ice.

Analysis of rapid snow and ice cover loss in mountain glaciers of arid and semi-arid regions using remote sensing data

This article investigates the effects of climate change on snow cover and glacier in mountainous glacial areas in northern region of Iran. Due to the lack of glacier measuring stations, accurately assessing changes in snow cover over the past two decades is a challenge for water experts. This research instead utilized remote sensing data from the MODIS sensor on the Terra satellite in Google Earth Engine (GEE) system covering the period from 2000 to 2020. The annual temperature changes near the Earth's surface, using ERA5 data, showed a significant increase of 1.5 °C in average temperature over the past thirty years. The Mann-Kendall test confirms the statistical significance of the temperature rise, with a significance value of 3.5 and a p-value of 0.002. For MODIS data validation, two methods of overall accuracy and the Kappa coefficient were used with 93% and 85% of accuracy. While the annual snowfall and volume have remained relatively stable over the past 20 years, the findings indicate a decreasing trend of snow cover during warmer months (summer) due to rising air temperatures. The findings show a strong negative correlation coefficient of −0.8 between snow cover and annual average temperature. The results indicate a 30% decrease in summer snow cover compared to the spatial extent of two decades ago. The rapid snowmelt poses a significant threat to permanent glaciers in the region as the protective snow cover diminishes, putting these glaciers at risk of completely melting in the future. The loss of these glaciers will have severe consequences for the environment, including impacts on local water supplies, river flows, and the ecosystem.

Impact of summer Tibetan Plateau snow cover on the variability of concurrent compound heatwaves in the Northern Hemisphere

Concurrent compound heatwaves (CCHWs) occurring simultaneously in multiple regions in the Northern Hemisphere (NH) pose high-end risks to human health and global supply chains. Over the past decade, CCHWs related to human health have substantially increased in occurrence. However, the mechanisms of the CCHWs remain uncertain. This work has revealed a significant relationship between the variability of summer CCHWs in the NH and changes in quasi-stationary waves during 1979–2021, which can be attributed to the variation of summer snow cover over the western Tibetan Plateau (SC_WTP). Excessive SC_WTP causes diabatic cooling by modulating the surface energy budget and stimulating a tripolar Rossby wave source. The atmospheric response to the SC_WTP-driven disturbance manifests as a circumglobal circulation pattern, weakening the meridional temperature gradients and causing a ‘double jet stream’ in the NH. These changes modulate the phase, amplitude and proportion of quasi-stationary waves with wavenumbers 4–6, leading to an increase in CCHWs in the NH. In addition, population exposure to CCHWs reaches 4.91 billion person-day when the SC_WTP increases by one standard deviation. Our study highlights the significance of early warning and forecasting implications related to SC_WTP for CCHWs that impact human health within the context of climate change.

Interannual Variation in Top-of-Atmosphere Upward Shortwave Flux over the Arctic Related to Sea Ice, Snow Cover, and Land Cloud Cover in Spring and Summer

Abstract We investigated the interannual variations in the annual mean and seasonal cycle of upward shortwave radiation at the top of the atmosphere (TOA SW↑) over the Arctic using the Clouds and the Earth’s Radiant Energy System (CERES) observation data during 2001–20. The annual mean TOA SW↑ over the Arctic showed a decreasing trend from 2001 to 2012 (−2.5 W m−2 decade−1) and had a large interannual variability after 2012. The standard deviation of detrended TOA SW↑ increased from 0.4 W m−2 in 2001–12 to 1.1 W m−2 in 2012–20. Over land, TOA SW↑ variation was related to snow cover in May; snow cover, cloud fraction, and cloud optical depth (COD) in June; and cloud fraction and COD in July. Over ocean, TOA SW↑ variation in June and July was linked to sea ice cover. TOA SW↑ variation over ocean in June and July after 2012 was highly related to the North Atlantic Oscillation (NAO). This study suggests that changes in the large annual mean TOA SW↑ variability after 2012 are explained by the timing of land snow and sea ice melt in spring and summer and cloud variability over land in summer.

Decline of Late Spring and Summer Snow Cover in the Scottish Highlands from 1984 to 2022: A Landsat Time Series

Late spring and summer snow cover, the remnants of winter and early spring snowfall, not only possess an intrinsic importance for montane flora and fauna, but also act as a sensitive indicator for climate change. The variability and potential trends in late spring and summer (snowmelt season) snow cover in mountain regions are often poorly documented. May to mid-September Landsat imagery from 1984 to 2022 was used to quantify changes in the snow-covered area of upland regions in the Scottish Highlands. There was substantial annual variability in the area of May to mid-September snow cover combined with a significant decline over the 39-year study period (p = 0.02). Long-term climate data used to show variability in May to mid-September snow cover was positively related to winter snowfall and negatively related to winter and April temperatures. The results from a long-running field survey counting the number of snow patches that survive until the following winter were used to check the veracity of the study. Further, accuracy was estimated through comparison with higher resolution Sentinel-2 imagery, giving a user and producer accuracy rate of 99.8% and 87%, respectively. Projected future warming will further diminish this scarce, valuable habitat, along with its associated plant communities, thus threatening the biodiversity and scenic value of the Scottish Highlands.

Identifying the paths and contributions of climate impacts on the variation in land surface albedo over the Arctic

Understanding historical changes in land surface albedo (ALB) is critical for projecting future climate changes over the Arctic. Previous studies have reported the important role of snow cover and vegetation growth in regulating Arctic land ALB, but their main influencing paths and separate contributions remain underexamined. In this study, the partial least squares path model (PLS-PM) and random forest model (RFM) are adopted to explore the dominant paths of three climate variables—temperature (Tem), precipitation (Pre) and wet days (WD)—in influencing the interannual variations in ALB (IVA) by regulating vegetation and snow cover. The results show that ALB in October and December exhibit significant (p < 0.05) upward and downward trends, respectively. ALB in the Northwest Territories, Victoria Island and Nunavut of the Arctic significantly (p < 0.05) increase in summer and October. The summer snow cover fraction (SCF) shows a significant positive correlation with ALB (R: 0.60‒0.78), while significant negative (R = -0.60) and positive (R = 0.50) relations are found between the enhanced vegetation index (EVI) and ALB during July and September, respectively. According to PLS−PM, the dominant paths that affect the IVA exhibit a prominent seasonal feature. Pre → EVI → ALB and Tem → SCF → ALB are identified as the main paths for ALB changes during spring, while in summer, the only significant path is Tem → SCF → ALB. In autumn, nonsignificant impacts on the variations in EVI and SCF (p > 0.05) are observed, while a significant path WD → SCF → ALB is found in winter. Based on RFM, the relative contribution (RC) of vegetation change to March IVA can reach 52.1 ± 9.2%, while snow variations play a dominant role in April and May, with contributions of 57.8 ± 8.4% and 68.4 ± 4.1%, respectively. Seasonally, summer IVA is mainly impacted by snow (RC from 50.5 ± 4.5% to 65.9 ± 4.5%), while vegetation exerts the dominant influence on IVA in autumn except for September. In winter, however, the dominant strength of vegetation is weakened except in December, with IVA mainly controlled by snow (RC above 50%).

Empirical modelling of snow cover duration patterns in complex terrains of Italy

Snow cover duration is a crucial climate change indicator. However, measurements of days with snow cover on the ground (DSG) are limited, especially in complex terrains, and existing measurements are fragmentary and cover only relatively short time periods. Here, we provide observational and modelling evidence that it is possible to produce reliable time-series of DSG for Italy based on instrumental measurements, and historical documentary data derived from various sources, from a limited set of stations and areas in the central-southern Apennines (CSA) of Italy. The adopted modelling approach reveals that DSG estimates in most settings in Italy can be driven by climate factors occurring in the CSA. Taking into account spatial scale-dependence, a parsimonious model was developed by incorporating elevation, winter and spring temperatures, a large-scale circulation index (the Atlantic Multidecadal Variability, AMV) and a snow-severity index, with in situ DSG data, based on a core snow cover dataset covering 97 years (88% coverage in the 1907–2018 period and the rest, discontinuously from 1683 to 1895, from historical data of the Benevento station). The model was validated on the basis of the identification of contemporary snow cover patterns and historical evidence of summer snow cover in high massifs. Beyond the CSA, validation obtained across terrains of varying complexity in both the northern and southern sectors of the peninsula indicate that the model holds potential for applications in a broad range of geographical settings and climatic situations of Italy. This article advances the study of past, present and future DSG changes in the central Mediterranean region.

Decreasing Influence of Summer Snow Cover Over the Western Tibetan Plateau on East Asian Precipitation Under Global Warming

In recent years, some studies emphasized the influence of western Tibetan Plateau summer snow on the East Asian summer precipitation. With the temperature rise in the past decades, the snow cover over the western Tibetan Plateau in summer has significantly decreased. This raises the question whether the impact of the Tibetan Plateau snow has changed. The present study identifies a prominent change in the influence of the western Tibetan Plateau snow cover on the East Asian summer precipitation. Before the early 2000’s, positive precipitation anomalies extend from the southeastern Tibetan Plateau through the Yangtze River to Japan and Korea and negative anomalies cover southeast China corresponding to more Tibetan Plateau snow cover. After the early 2000’s, with the reduction of snow cover variability, below-normal and above-normal summer precipitation occurs over northern China-Mongolia and northeast Asia, respectively, corresponding to more Tibetan Plateau snow cover. The change in the influence of the Tibetan Plateau snow on the East Asian summer precipitation is associated with an obvious change in the atmospheric circulation anomaly pattern. Before the early 2000’s, the wind anomalies display a south-north contrast pattern with anomalous convergence along the Yangtze River. After the early 2000’s, an anomalous cyclone occupies Northeast China with anomalous southerlies and northerlies over northeast Asia and northern China, respectively. The Tibetan Plateau snow cover variation after the early 2000’s is associated with the northeast Indian summer precipitation. The model experiments confirm that the weakened influence of summer western Tibetan Plateau snow cover on the East Asian atmospheric circulation and precipitation with the reduced snow cover anomalies.

Climate change in the High Mountain Asia in CMIP6

Abstract. Climate change over High Mountain Asia (HMA, including the Tibetan Plateau) is investigated over the period 1979–2014 and in future projections following the four Shared Socioeconomic Pathways: SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5. The skill of 26 Coupled Model Intercomparison Project phase 6 (CMIP6) models is estimated for near-surface air temperature, snow cover extent and total precipitation, and 10 of them are used to describe their projections until 2100. Similarly to previous CMIP models, this new generation of general circulation models (GCMs) shows a mean cold bias over this area reaching −1.9 [−8.2 to 2.9] ∘C (90 % confidence interval) in comparison with the Climate Research Unit (CRU) observational dataset, associated with a snow cover mean overestimation of 12 % [−13 % to 43 %], corresponding to a relative bias of 52 % [−53 % to 183 %] in comparison with the NOAA Climate Data Record (CDR) satellite dataset. The temperature and snow cover model biases are more pronounced in winter. Simulated precipitation rates are overestimated by 1.5 [0.3 to 2.9] mm d−1, corresponding to a relative bias of 143 % [31 % to 281 %], but this might be an apparent bias caused by the undercatch of solid precipitation in the APHRODITE (Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation of Water Resources) observational reference. For most models, the cold surface bias is associated with an overestimation of snow cover extent, but this relationship does not hold for all models, suggesting that the processes of the origin of the biases can differ from one model to another. A significant correlation between snow cover bias and surface elevation is found, and to a lesser extent between temperature bias and surface elevation, highlighting the model weaknesses at high elevation. The models with the best performance for temperature are not necessarily the most skillful for the other variables, and there is no clear relationship between model resolution and model skill. This highlights the need for a better understanding of the physical processes driving the climate in this complex topographic area, as well as for further parameterization developments adapted to such areas. A dependency of the simulated past trends on the model biases is found for some variables and seasons; however, some highly biased models fall within the range of observed trends, suggesting that model bias is not a robust criterion to discard models in trend analysis. The HMA median warming simulated over 2081–2100 with respect to 1995–2014 ranges from 1.9 [1.2 to 2.7] ∘C for SSP1-2.6 to 6.5 [4.9 to 9.0] ∘C for SSP5-8.5. This general warming is associated with a relative median snow cover extent decrease from −9.4 % [−16.4 % to −5.0 %] to −32.2 % [−49.1 % to −25.0 %] and a relative median precipitation increase from 8.5 % [4.8 % to 18.2 %] to 24.9 % [14.4 % to 48.1 %] by the end of the century in these respective scenarios. The warming is 11 % higher over HMA than over the other Northern Hemisphere continental surfaces, excluding the Arctic area. Seasonal temperature, snow cover and precipitation changes over HMA show a linear relationship with the global surface air temperature (GSAT), except for summer snow cover which shows a slower decrease at strong levels of GSAT.

Snow Cover and Snow Persistence Changes in the Mocho-Choshuenco Volcano (Southern Chile) Derived From 35 Years of Landsat Satellite Images

Mountain regions have experienced above-average warming in the 20th century and this trend is likely to continue. These accelerated temperature changes in alpine areas are causing reduced snowfall and changes in the timing of snowfall and melt. Snow is a critical component of alpine areas - it drives hibernation of animals, determines the length of the growing season for plants and the soil microbial composition. Thus, changes in snow patterns in mountain areas can have serious ecological consequences. Here we use 35 years of Landsat satellite images to study snow changes in the Mocho-Choshuenco Volcano in the Southern Andes of Chile. Landsat images have 30 m pixel resolution and a revisit period of 16 days. We calculated the total snow area in cloud-free Landsat scenes and the snow frequency per pixel, here called “snow persistence” for different periods and seasons. Permanent snow cover in summer was stable over a period of 30 years and decreased below 20 km2 from 2014 onward at middle elevations (1,530–2,000 m a.s.l.). This is confirmed by negative changes in snow persistence detected at the pixel level, concentrated in this altitudinal belt in summer and also in autumn. In winter and spring, negative changes in snow persistence are concentrated at lower elevations (1,200–1,530 m a.s.l.). Considering the snow persistence of the 1984–1990 period as a reference, the last period (2015–2019) is experiencing a −5.75 km2 reduction of permanent snow area (snow persistence &amp;gt; 95%) in summer, −8.75 km2 in autumn, −42.40 km2 in winter, and −18.23 km2 in spring. While permanent snow at the high elevational belt (&amp;gt;2,000 m a.s.l.) has not changed through the years, snow that used to be permanent in the middle elevational belt has become seasonal. In this study, we use a probabilistic snow persistence approach for identifying areas of snow reduction and potential changes in alpine vegetation. This approach permits a more efficient use of remote sensing data, increasing by three times the amount of usable scenes by including images with spatial gaps. Furthermore, we explore some ecological questions regarding alpine ecosystems that this method may help address in a global warming scenario.

Effect of summer snow cover on the active layer thermal regime and thickness on CALM-S JGM site, James Ross Island, eastern Antarctic Peninsula

This study aims to assess the role of ephemeral snow cover on ground thermal regime and active layer thickness in two ground temperature measurement profiles on the Circumpolar Active Layer Monitoring Network – South (CALM-S) JGM site on James Ross Island, eastern Antarctic Peninsula during the high austral summer 2018. The snowstorm of 13–14 January created a snowpack of recorded depth of up to 38 cm. The snowpack remained on the study site for 12 days in total and covered 46% of its area six days after the snowfall. It directly affected ground thermal regime as indicates temperature record at snow-covered profile AWS-JGM which subsurface section was nearly 5 °C colder compared to the snow-free AWS-CALM profile. The thermal insulation effect of snow cover is also reflected in the mean monthly (January) and summer (DJF) ground temperatures on AWS-JGM that decreased by ca 1.1 and 0.7 °C, respectively. Summer thawing degree days at a depth of 5 cm decreased by ca 10% and active layer was ca 5–10 cm thinner when compared to previous snow-free summer seasons. Surveying by ground penetrating radar revealed a general active layer thinning of up to 20% in those parts of the CALM-S which were covered by snow of >20 cm depth for at least six days.

Glacier albedo reduction and drought effects in the extratropical Andes, 1986–2020

AbstractSurface albedo typically dominates the mass balance of mountain glaciers, though long-term trends and patterns of glacier albedo are seldom explored. We calculated broadband shortwave albedo for glaciers in the central Chilean Andes (33–34°S) using end-of-summer Landsat scenes between 1986 and 2020. We found a high inter-annual variability of glacier-wide albedo that is largely a function of the glacier fractional snow-covered area and the total precipitation of the preceding hydrological year (up to 69% of the inter-annual variance explained). Under the 2010–2020 ‘Mega Drought’ period, the mean albedo, regionally averaged ranging from ~0.25–0.5, decreased by −0.05 on average relative to 1986–2009, with the greatest reduction occurring 3500–5000 m a.s.l. In 2020, differences relative to 1986–2009 were −0.14 on average as a result of near-complete absence of late summer snow cover and the driest hydrological year since the Landsat observation period began (~90% reduction of annual precipitation relative to the 1986–2009 period). We found statistically significant, negative trends in glacier ice albedo of up to −0.03 per decade, a trend that would have serious implications for the future water security of the region, because glacier ice melt acts to buffer streamflow shortages under severe drought conditions.

Surface roughness signatures of summer arctic snow-covered sea ice in X-band dual-polarimetric SAR

ABSTRACT Surface roughness of sea ice is primary information for understanding sea ice dynamics and air–ice–ocean interactions. Synthetic aperture radar (SAR) is a powerful tool for investigating sea ice surface roughness owing to the high sensitivity of its signal to surface structures. In this study, we explored the surface roughness signatures of the summer Arctic snow-covered first-year sea ice in X-band dual-polarimetric SAR in terms of the root mean square (RMS) height. Two ice campaigns were conducted for the first-year sea ice with dry snow cover in the marginal ice zone of the Chukchi Sea in August 2017 and August 2018, from which high-resolution (4 cm) digital surface models (DSMs) of the sea ice were derived with the help of a terrestrial laser scanner to obtain the in situ RMS height. X-band dual-polarimetric (HH and VV) SAR data (3 m spatial resolution) were obtained for the 2017 campaign, at a high incidence angle (49.5°) of TerraSAR-X, and for the 2018 campaign, at a mid-incidence angle (36.1°) of TanDEM-X 1–2 days after the acquisition of the DSMs. The sea ice drifted during the time between the SAR and DSM acquisitions. As it is difficult to directly co-register the DSM to SAR owing to the difference in spatial resolution, the two datasets were geometrically matched using unmanned aerial vehicle (4 cm resolution) and helicopter-borne (30 cm resolution) photographs acquired as part of the ice campaigns. A total of five dual-polarimetric SAR features―backscattering coefficients at HH and VV polarizations, co-polarization ratio, co-polarization phase difference, and co-polarization correlation coefficient ―were computed from the dual-polarimetric SAR data and compared to the RMS height of the sea ice, which showed macroscale surface roughness. All the SAR features obtained at the high incidence angle were statistically weakly correlated with the RMS height of the sea ice, possibly influenced by the low backscattering close to the noise level that is attributed to the high incidence angle. The SAR features at the mid-incidence angle showed a statistically significant correlation with the RMS height of the sea ice, with Spearman’s correlation coefficient being higher than 0.7, except for the co-polarization ratio. Among the intensity-based and polarimetry-based SAR features, HH-polarized backscattering and co-polarization phase difference were analyzed to be the most sensitive to the macroscale RMS height of the sea ice. Our results show that the X-band dual-polarimetric SAR at mid-incidence angle exhibits potential for estimation of the macroscale surface roughness of the first-year sea ice with dry snow cover in summer.

Seeking snow and breathing hard - Behavioral tactics in high elevation mammals to combat warming temperatures.

The world glaciers and areas of persistent summer snowpack are being lost due to warming temperatures. For cold-adapted species, habitat features may offer opportunities for cooling during summer heat yet the loss of snow and ice may compromise derived thermoregulatory benefits. Herein we offer insights about habitat selection for snow and the extent to which other behavioral adjustments reduce thermal debt among high elevation mammals. Specifically, we concentrate on respiration in mountain goats (Oreamnos americanus), a species whose native distribution is currently tied to northern mountain ranges of North America, where large patches of persistent summer snow are declining, and which became extinct during geologically warmer epochs. To examine sensitivity to possible thermal stressors and use of summer snow cover, we tracked marked and unmarked mountain goats in Glacier National Park, Montana, USA, to test hypotheses about selection for cold microclimates including shade and snow during periods of relatively high temperature. To understand functional responses of habitat choices, we measured microhabitat temperatures and a component of goat physiology–breaths per minute–as an index for metabolic expenditure. Individuals 1) selected areas closer to snow on warmer summer days, and 2) on snow had a 15% mean reduction in respiration when accounting for other factors, which suggests remnant snow plays an important role in mediating effects of air temperature. The use of shade was not as an important variable in models explaining respiration. Despite the loss of 85% of glaciers in in Glacier National Park, summer’s remnant snow patches are an important reservoir by which animals reduce heat stress and potential hyperthermia. Our findings, when contextualized with behavioral strategies deployed by other high elevation mammalian taxa help frame how ambient temperatures may be modulated, and they offer a direct way by which to assess susceptibility to increasing heat in cold-adapted species.

Influence of Western Tibetan Plateau Summer Snow Cover on East Asian Summer Rainfall

AbstractThe influence of boreal winter‐spring eastern Tibetan Plateau snow anomalies on the East Asian summer rainfall variability has been the focus of previous studies. The present study documents the impacts of boreal summer western and southern Tibetan Plateau snow cover anomalies on summer rainfall over East Asia. Analysis shows that more snow cover in the western and southern Tibetan Plateau induces anomalous cooling in the overlying atmospheric column. The induced atmospheric circulation changes are different corresponding to more snow cover in the western and southern Tibetan Plateau. The atmospheric circulation changes accompanying the western Plateau snow cover anomalies are more obvious over the midlatitude Asia, whereas those corresponding to the southern Plateau snow cover anomalies are more prominent over the tropics. As such, the western and southern Tibetan Plateau snow cover anomalies influence the East Asian summer circulation and precipitation through different pathways. Nevertheless, the East Asian summer circulation and precipitation anomalies induced by the western and southern Plateau snow cover anomalies tend to display similar distribution so that they are more pronounced when the western and southern Plateau snow cover anomalies work in coherence. Analysis indicates that the summer snow cover anomalies over the Tibetan Plateau may be related to late spring snow anomalies due to the persistence. The late spring snow anomalies are related to an obvious wave train originating from the western North Atlantic that may be partly associated with sea surface temperature anomalies in the North Atlantic Ocean.

Low‐frequency snow changes over the Tibetan Plateau

ABSTRACTSnow change over the Tibetan Plateau may exert a large influence on climate variability in the surrounding regions. However, the characteristics of snow changes at different time scales and the factors for these changes are still not clear. The present study documents linear trends in snow cover and snow water equivalent over the Tibetan Plateau and their relationship to surface air temperature changes during 1979–2006 based on satellite data. The long‐term snow variations display a remarkable regional difference and an obvious seasonal dependence. A significant decreasing trend is observed in the western part for snow cover and snow water equivalent in summer and fall and in the southern part for snow cover in all the four seasons. A significant increasing trend is identified in the central‐eastern part for snow cover in fall, winter, and spring and in the eastern and far western parts for snow water equivalent in winter and spring. The relationship between snow and surface air temperature changes features regional disparity. The temperature increase is accompanied by snow cover decrease in the southern and western parts, but by snow cover and snow water equivalent increase in the central‐eastern part. The reasons for the snow changes vary with the season. The increase in snowmelt following the temperature increase may be the reason for the snow cover decrease in the western and southern parts in summer. The snowfall change induced by vertical motion change appears to be a factor for the snow water equivalent increase in the far western part and the snow cover decrease in the southern part in winter. The increase in snowfall induced by the increase in atmospheric moisture following the temperature increase and the enhanced upward motion may contribute to the snow increase in the eastern part in winter.

우리나라 여름철 월별 기온 변동성과 유라시아 봄철 눈덮임 간의 상관성 분석

우리나라 여름철 월별 기온 변동성과 유라시아 봄철 눈덮임 간의 상관성 분석

The summer snow cover anomaly over the Tibetan Plateau and its association with simultaneous precipitation over the mei-yu-baiu region

The summer snow anomalies over the Tibetan Plateau (TP) and their effects on climate variability are often overlooked, possibly due to the fact that some datasets cannot properly capture summer snow cover over high terrain. The satellite-derived Equal-Area Scalable Earth grid (EASE-grid) dataset shows that snow still exists in summer in the western part and along the southern flank of the TP. Analysis demonstrates that the summer snow cover area proportion (SCAP) over the TP has a significant positive correlation with simultaneous precipitation over the mei-yu-baiu (MB) region on the interannual time scale. The close relationship between the summer SCAP and summer precipitation over the MB region could not be simply considered as a simultaneous response to the Silk Road pattern and the SST anomalies in the tropical Indian Ocean and tropical central-eastern Pacific. The SCAP anomaly has an independent effect and may directly modulate the land surface heating and, consequently, vertical motion over the western TP, and concurrently induce anomalous vertical motion over the North Indian Ocean via a meridional vertical circulation. Through a zonal vertical circulation over the tropics and a Kelvin wave-type response, anomalous vertical motion over the North Indian Ocean may result in an anomalous high over the western North Pacific and modulate the convective activity in the western Pacific warm pool, which stimulates the East Asia-Pacific (EAP) pattern and eventually affects summer precipitation over the MB region.

Lasting effects of snow accumulation on summer performance of large herbivores in alpine ecosystems may not last

One of the clearest predictions from the IPCC is that we can expect much less snow cover due to global warming in the 21st century, especially in the lower alpine areas. In alpine ecosystems, snow accumulation in depressions gives rise to distinct snow-bed vegetation types, assumed to play a key role in ecosystem function. A delayed plant phenology yields high-quality forage in late summer for wild and domestic herbivores. Yet, the mechanistic pathways for how declining snow may affect future performance of large herbivores beyond the effect of phenology remain poorly documented. Here, we link unique individual-based data on diet choice, habitat selection and performance of domestic sheep over a 10-year period to manually GPS-recorded spatial positions of snow cover in early summer (0.57% to 43.3% in snow beds on 1st of July) in an alpine ecosystem. Snowy winters gave a higher proportion of easily digestible herbs in the diet and a more variable use of snow-bed and meadow vegetation types resulting in faster growing lambs. These patterns were consistent between two density treatment levels although slightly more marked for diet at low density, suggesting that effects of simple mitigation efforts such as managing population numbers will be meagre. Our study thus yields novel insight into the strong impact of melting snow on ecosystem function in alpine habitats, which are likely to affect productivity of both domestic and wild ungulate populations.

Discharge regime and simulation for the upstream of major rivers over Tibetan Plateau

The hydrological regimes for the major river basins in the Tibetan Plateau (TP), including the source regions of the Yellow (UYE), Yangtze (UYA), Mekong (UM), Salween (US), Brahmaputra (UB), and Indus (UI) rivers, were investigated through a land surface model and regression analyses between climate variables and runoff data. A hydrologic modeling framework was established across the TP to link the Variable Infiltration Capacity (VIC) land surface hydrology model with a degree‐day glacier‐melt scheme (VIC‐glacier model) at a 1/12° × 1/12°. The model performance was evaluated over the upper basins of the six rivers. The heterogeneity and scarcity of the meteorological stations are the major limitation for hydrological modeling over the TP. The relative contributions to streamflow from rainfall, snowmelt, and glacier melt for the six basins were quantified via the model framework and simulation. The results suggest that monsoon precipitation has a dominant role in sustaining seasonal streamflow over southeastern regions, contributing 65–78% of annual runoff among the UYE, UYA, UM, US, and UB basins. For the UI, the runoff regime is largely controlled by the glacier melt and snow cover in spring and summer. The contribution of glacier runoff is minor for the UYE and UM (less than 2% of total annual flow), and moderate for the UYA and US basins (5–7% of yearly flow), while glacier melt makes up about 12% and 48% of annual flow for the UB and UI basins, respectively.