Extreme Snowfall Events Research Articles

An extreme precipitation event over Dronning Maud Land, East Antarctica - A case study of an atmospheric river event using the Polar WRF Model

Extreme precipitation events (EPEs) are crucial in Antarctica, impacting the Antarctic ice sheet's surface mass balance and stability. Comprehensive case studies are essential for better understanding these events and the underlying processes driving them. Here, we investigate an extreme snowfall event in Dronning Maud Land (DML), East Antarctica on November 8 and 9, 2015. This event contributed approximately 22 % of the annual accumulation in less than two days and exhibited high spatial variability in precipitation distribution. We employed a high-resolution atmospheric model specifically optimized for the polar regions (Polar WRF) and ERA5 reanalysis data to analyze the event in detail. Our findings highlight the importance of a blocking high-pressure ridge of record strength that effectively blocked and diverted a strong extratropical cyclone into DML, ultimately leading to the heavy snowfall event. The sudden deepening of the cyclone was initiated by a ‘jet streak’ in the upper atmosphere that steered the system southeastwards towards the Antarctic coast. Notably, we observed an anomalously high poleward moisture transport in the form of a strong atmospheric river on November 7, 2015. This atmospheric river originated in the South Atlantic Ocean and tracked poleward from the 30°S-40°S latitude band. Vertical cross-sections of the model outputs indicate that most of the precipitation was concentrated in regions with steep orography along the path of the atmospheric river. This interaction between the atmospheric river and the steep terrain led to the uplift of maritime air, resulting in heavy snowfall. This study highlights the significance of extreme upper and lower atmospheric conditions in driving intense moisture transport towards coastal DML. The interaction between the atmospheric river and the steep orography contributed to heavy snowfall, underscoring the importance of considering orographic influences in understanding EPEs in Antarctica.

Extreme snowfall variations in the Southeastern Tibetan Plateau under warming climate

Snowfall is a critical component of the Earth system and an important indicator and amplifier of climate change. Climate warming is reducing the seasonal snowpack globally, which could have catastrophic consequences for the regions in high dependence on snow for water recharge. However, the climate influences on extreme snowfall events, which significantly impact humans, are still poorly understood. This study uses the Tibetan Plateau snowpack observation dataset combined with NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP-CMIP6) climate data to investigate the spatial and temporal characteristics of snowfall, and to explore its response mechanism to climate change and future change trends across the Lower Yarlung Zangbo River (LYZR) in Southeastern Tibetan Plateau (SETP). Annual snowfall decreased at a rate of 1.05 mm per decade (P < 0.05) during the historical period (1960–2014). Relative to 1960–2014, annual snowfall would decline of ∼38 % and ∼ 73 % by the end of the 21st century under the SSP245 and SSP585 scenarios, respectively. At the same time, a general decrease in extreme snowfall averaged the LYZR is expected for historical and future periods, but it showed notable spatial variations. The regional increase in extreme snowfall is mainly distributed along the valley of Brahmaputra-Yarlung Zangbo. In addition, precipitation accounted for 66.5 % of the snowfall variations during the historical period. Meanwhile, according to future warming, temperature would dominate snowfall variations, contributing 56.66 % to 72.92 % during 2015–2100. The projected response of mean and extreme snowfall to climate change indicates that it is a double-edged sword. To scientifically address the risks and challenges posed by snowfall changes in alpine regions, it is imperative to limit future climate warming.

Snowpack variations and their hazardous effects under climate warming in the central Tianshan Mountains

Climate change alters snowpack evolution, which in turn influences the likelihood of snow avalanches and flood risks. The lack of systemic observational data on key snow characteristics in high mountains remains a scientific challenge in terms of systematically elucidating the dynamic chain of variations in climate–snowpack–snow disasters. This restricts our understanding and poses challenges in the prediction of snow-related disaster risks. As such, this study analysed the variations of temperature and snowfall and the physical characteristics of snowpacks based on ground-based observations from the Kunse River Valley situated in the Tianshan Mountains from 1967 to 2021. The results reveal that the temperature increased significantly by 0.32 °C per decade (p < 0.01) during the snow season, along with more extreme snowfall events. The snow-cover duration was observed to have been shortened by 4.77 d per decade (p < 0.01) from 1967 to 2021, which is characterised by later snow-cover onset and earlier snowmelt. Concurrently, average and maximum snow depths increased along with an increase in peak snow water equivalent, thus indicating a higher frequency of extremely scarce or abundant snow years. The low snowpack temperature gradient and earlier snowmelt dates in spring lead to earlier occurrences of snowmelt floods and wet avalanches. As the risks of these events increase, they pose greater threats to farmlands, road transportation, water–electricity infrastructure and several other human activities. Therefore, these insights are critical for providing vital information that can deepen our understanding of the impact of climate change on snowpack characteristics and improve management strategies for snow-related disaster prevention and mitigation.

Diverse Characteristics of Extreme Orographic Snowfall Events in Little Cottonwood Canyon, Utah

Abstract Heavy orographic snowfall can disrupt transportation and threaten lives and property in mountainous regions but benefits water resources, winter sports, and tourism. Little Cottonwood Canyon (LCC) in northern Utah’s Wasatch Range is one of the snowiest locations in the interior western United States and frequently observes orographic snowfall extremes with threats to transportation, structures, and public safety due to storm-related avalanche hazards. Using manual new-snow and liquid precipitation equivalent (LPE) observations, ERA5 reanalyses, and operational radar data, this paper examines the characteristics of cool-season (October–April) 12-h snowfall extremes in upper LCC. The 12-h extremes, defined based on either 95th percentile new snow or LPE, occur for a wide range of crest-level flow directions. The distribution of LPE extremes is bimodal with maxima for south-southwest or north-northwest flow, whereas new-snow extremes occur most frequently during west-northwest flow, which features colder storms with higher snow-to-liquid ratios. Both snowfall and LPE extremes are produced by diverse synoptic patterns, including inland-penetrating or decaying atmospheric rivers from the south through northwest that avoid the southern high Sierra Nevada, frontal systems, post-cold-frontal northwesterly flow, south-southwesterly cold-core flow, and closed low pressure systems. Although often associated with heavy precipitation in other mountainous regions, the linkages between local integrated water vapor transport (IVT) and orographic precipitation extremes in LCC are relatively weak, and during post-cold-frontal northwesterly flow, highly localized and intense snowfall can occur despite low IVT. These results illustrate the remarkable diversity of storm characteristics producing orographic snowfall extremes at this interior continental mountain location. Significance Statement Little Cottonwood Canyon in northern Utah’s central Wasatch Range frequently experiences extreme snowfall events that pose threats to lives and property. In this study, we illustrate the large diversity of storm characteristics that produce this extreme snowfall. Meteorologists commonly use the amount of water vapor transport in the atmosphere to predict heavy mountain precipitation, but that metric has limited utility in Little Cottonwood Canyon where heavy snowfall can occur with lower values of such transport. Our results can aid weather forecasting in the central Wasatch Range and have implications for understanding precipitation processes in mountain ranges throughout the world.

The influence of Urmia Lake desiccation on an extreme snowfall event: A case study using the WRF-Lake model

Urmia Lake in the northwest Iran has undergone significant desiccation in recent decades, shrinking to a much smaller size than its original. This study implements the WRF-Lake coupled modeling system to examine the impacts of the observed physical changes over the Lake during a heavy snowfall event occurred February 1–2, 2017. Modifications are introduced to represent the shrunken, salt-encrusted lake surface and surrounding arid environment through updating land use, soil characteristics, lake size and depth, and albedo data. Experiments incorporating lake-atmosphere coupling and land surface refinements (Lake_CTL, Lake_LULC, Lake_AL) outperform simulations without a lake (WRF_noLake) in reproducing observed precipitation patterns at stations surrounding the Urmia Lake. All simulations underestimate the extreme 290 mm snowfall recorded at the Urmia station; however, the Lake_LULC and Lake_AL improve snowfall representation at other stations around the lake. Regarding snow cover validation, Lake_LULC and Lake_AL exhibit a higher correlation with satellite observations and show a significant improvement in snow detection near Urmia Lake. They have a Probability of Detection (POD) of 0.94 and a Critical Success Index (CSI) of 0.91, compared to a POD of 0.79–0.80 and a CSIs of ∼0.77 for the default lake model (Lake_CTL) and the WRF_noLake experiments, respectively. Additionally, adjusting the initial lake surface temperature to match observations substantially reduces cold biases in near-surface air temperatures over Urmia Lake. The lack of lake temperature updating in WRF-Lake poses ongoing challenges in the model, though. In summary, this study demonstrates that refining the representations of desiccated lakes and their surroundings in high-resolution coupled models would improve simulations of meteorological processes influenced by lake-atmosphere interactions.

Decreasing trends of mean and extreme snowfall in High Mountain Asia

Intense warming profoundly alters precipitation phase patterns and intensity in High Mountain Asia (HMA). While snowfall climatology and precipitation extremes have been studied, there is a lack of understanding of snowfall extremes within HMA. Here, we investigate the spatial and temporal variability of non-extreme and extreme snowfall in hydrological years 1979–2020 using multi-source meteorological data, compare weather systems during extreme and non-extreme snowfall events, and identify key circulation factors that influence fluctuations in mean annual snowfall and extreme snowfall. The snowfall amount (−0.13 d/mm), days (−0.56 d/a), and fraction (−0.0012) were significantly reduced in HMA, with a shorter snowfall season (−0.52 d/a). Some extreme snowfall metrics (maximum 1-day snowfall and maximum 3-day snowfall) were insensitive to climate change, whereas the maximum consecutive snowfall days (−0.007 d/a), snowfall amount (−0.0023 mm/a), heavy snowfall days (S95pD; 0.0087 d/a), and extremely heavy snowfall days (S99pD; −0.1019 d/a) showed significant decreases. Synthetic analyses show that extreme snowfall events were more likely to occur within a narrow temperature range (−5 °C to 3 °C) with higher relative humidity and precipitation compared to non-extreme events. A stepwise regression method was used to determine that the fluctuation in the average annual snowfall was closely related to the Atlantic Multidecadal Oscillation, whereas the variation in extreme snowfall was mainly influenced by the Southern Oscillation Index. Our research provides a reference for assessing the potential impacts of climate change on a regional scale for risk management and disaster adaptation.

Differences in spatial niche of terrestrial mammals when facing extreme snowfall: the case in east Asian forests

BackgroundRecent climate changes have produced extreme climate events. This study focused on extreme snowfall and intended to discuss the vulnerability of temperate mammals against it through interspecies comparisons of spatial niches in northern Japan. We constructed niche models for seven non-hibernating species through wide-scaled snow tracking on skis, whose total survey length was 1144 km.ResultsWe detected a low correlation (rs < 0.4) between most pairs of species niches, indicating that most species possessed different overwintering tactics. A morphological advantage in locomotion cost on snow did not always expand niche breadth. In contrast, a spatial niche could respond to (1) drastic landscape change by a diminishing understory due to snow, possibly leading to changes in predator-prey interactions, and (2) the mass of cold air, affecting thermoregulatory cost and food accessibility. When extraordinary snowfall occurred, the nonarboreal species with larger body sizes could niche shift, whereas the smaller-sized or semi-arboreal mammals did not. In addition, compared to omnivores, herbivores were prone to severe restriction of niche breadth due to a reduction in food accessibility under extreme climates.ConclusionsDietary habits and body size could determine the redundancy of niche width, which may govern robustness/vulnerability to extreme snowfall events.

Effects of extreme precipitation on bacterial communities and bioaerosol composition: Dispersion in urban outdoor environments and health risks

Concerns about contaminants dispersed by seasonal precipitation have grown due to their potential hazards to outdoor environments and human health. However, studies on the crucial environmental factors influencing dispersion changes in bacterial communities are limited. This research adopted four-season in situ monitoring and sequencing techniques to examine the regional distribution profiles of bioaerosols, bacterial communities, and risks associated with extreme snowfall versus rainfall events in two monsoon cities. In the early-hours of winter snowfall, airborne cultivable bioaerosol concentrations were 4.1 times higher than the reference exposure limit (500 CFU/m3). The concentration of ambient particles (2.5 μm) exceeded 24,910 particles/L (97 μg/m3), positively correlating with the prevalence of cultivable bioaerosols. These bioaerosols contained cultivable bacterial species such as pathogenic Staphylococcus aureus, Staphylococcus epidermidis, Streptococcus pneumoniae, and Escherichia coli. Bioaerosol concentrations increased by 53.0% during 50-mm snow extremes. Taxonomic analysis revealed that Pseudomonas, Staphylococcus, and Veillonella were the most abundant bacterial taxa in the initial snowmelt samples during winter precipitation. However, their abundance decreased by 87.6% as snowing continued (24 h). Reduced water base cation concentration also led to a 1.15-fold increase in the Shannon index, indicating a similar yet heightened bacterial diversity. Seasonally, Pedobacter and Massilia showed higher relative abundance (25% and 18%, respectively), presenting increased bacterial transmission to the soil. Furthermore, Pseudomonas was identified in 60% of spring snowstorm samples, suggesting long-distance dispersal of pathogenic bacteria. When these atmospheric aerosol particles carrying biological entities (0.65–1.1 μm) penetrated human alveoli, the calculated hazard ratio was 0.55, which as observed in inhalation exposures. Consequently, this study underscores the risk of seasonal precipitation-enhanced ambient bacterial transmission.

Rapid increase in extreme snowfall events over the last 40 years in Northeast China

Rapid increase in extreme snowfall events over the last 40 years in Northeast China

Projected changes in extreme snowfall events over the Tibetan Plateau based on a set of RCM simulations

Extreme snowfall events over the Tibetan Plateau (TP) cause considerable damage to local society and natural ecosystems. In this study, the authors investigate the projected changes in such events over the TP and its surrounding areas based on an ensemble of a set of 21st century climate change projections using a regional climate model, RegCM4. The model is driven by five CMIP5 global climate models at a grid spacing of 25 km, under the RCP4.5 and RCP8.5 pathways. Four modified ETCCDI extreme indices—namely, SNOWTOT, S1mm, S10mm, and Sx5day—are employed to characterize the extreme snowfall events. RegCM4 generally reproduces the spatial distribution of the indices over the region, although with a tendency of overestimation. For the projected changes, a general decrease in SNOWTOT is found over most of the TP, with greater magnitude and better cross-simulation agreement over the eastern part. All the simulations project an overall decrease in S1mm, ranging from a 25% decrease in the west and to a 50% decrease in the east of the TP. Both S10mm and Sx5day are projected to decrease over the eastern part and increase over the central and western parts of the TP. Notably, S10mm shows a marked increase (more than double) with high cross-simulation agreement over the central TP. Significant increases in all four indices are found over the Tarim and Qaidam basins, and northwestern China north of the TP. The projected changes show topographic dependence over the TP in the latitudinal direction, and tend to decrease/increase in low-/high-altitude areas.摘要基于RegCM4区域气候模式的气候变化预估试验数据, 开展了青藏高原及其周边地区极端降雪事件的未来变化研究. 结果表明, 总降雪量在高原大部分地区呈减少趋势, 降雪日数在高原也将明显减少, 尤其是在东部. 大雪日数和五日最大降雪量在高原东部将减少, 而在中部和西部明显增加. 在高原周边的塔里木和柴达木盆地及中国西北地区, 极端降雪事件同样增加显著. 极端降雪事件在高原上呈现出东西方向上的地形依赖性, 在低/高海拔地区呈减少/增加趋势.

Investigating the occurrence of blizzard events over the contiguous United States using observations and climate projections

Over previous decades, the United States has been plagued by severe winter storms or blizzards, which caused millions of dollars in damages. However, the historical trend of blizzard events and the possible impacts of future global climate change on blizzard occurrences remain unclear. In this study, we analyzed historical blizzard occurrences using the observed storm event database, which shows that the Northern Plains, such as North Dakota, South Dakota, and Minnesota, had the most blizzard activities over the past 25 years. No significant trend in blizzard occurrence is found in those regions. When considering blizzards as compound events of strong wind and extreme snowfall, we estimated blizzard occurrences based on wind speed and snowfall in climate datasets, including Automated Surface Observing Systems wind speed, national gridded snowfall analysis, ERA5 reanalysis and historical simulations of 19 models in Coupled Model Intercomparison Project phase 6 (CMIP6), which show a good agreement with the observations with respect to the climatology of blizzard occurrence. In the near-term and long-term future under two emission scenarios, CMIP6 projections suggest decreases in both strong wind and extreme snowfall events, eventually leading to a significantly reduced frequency of compound events. Significant decreases in blizzard occurrence are found in the Northern Plains and Upper Midwest, suggesting potentially reducing the risk of winter hazards over those regions in a warming climate.

Evaluation of the snow loads on the snow galleries on the Iron Ore Line in Northern Sweden

AbstractThe Iron Ore Line is a railway in northern Sweden and Norway, crucial for iron ore transportation. Snow galleries safeguard this route, ensuring uninterrupted traffic for efficient operations. A snow gallery is a protective structure that shields roads and railways from heavy snowfall and avalanches. Reported damages to these structures caused by excessive snow loads have prompted an investigation to prevent further issues. This paper presents an analysis of the evolution of snow load calculations over time, though a comparison of Swedish design standards. The design snow loads required by current standards have increased up to 60% from the initial regulations, depending on the location of the structure. Besides, climate change is predicted to further increase snow loads due to more frequent winter precipitation, higher snow density, and extreme snowfall events. This analysis is part of a broader research project involving numerical simulations, live monitoring, and a digital twin monitoring system of some snow galleries in the Iron Ore Line.

Investigating Extreme Snowfall Changes in China Based on an Ensemble of High-Resolution Regional Climate Models

Anthropogenically induced global warming intensifies the water cycle around the world. As a critical sector of the water cycle, snow depth and its related extremes greatly impact agriculture, animal husbandry, and food security, yet lack investigation. In this study, five high-resolution climate models are selected to simulate and project snow depth and its extremes over China. The simulation capabilities of models in reproducing the basic climate variables in winter are gauged in terms of spatial and temporal patterns over nine subregions. It is found that the driving global climate model (GCM) can contribute to similar patterns, while the different regional climate model (RCM) schemes lead to large variations in the snowfall accumulating on the land surface. The warming magnitude is larger under a higher representative concentration pathway (RCP) scenario (2.5 °C greater under RCP8.5 than RCP4.5). The distribution of ensemble mean winter precipitation changes is more fragmented because of the relatively low skill in reproducing water-related content in the climate system. The projected precipitation change is larger under RCP8.5 than under RCP4.5 due to the amplification of the hydrological cycle by temperature warming. The projected changes in the ensemble mean snow depth mainly occur over the Tibetan Plateau with a decreasing trend. Only several grids over the Himalayas Mountains and the upper stream of the Yarlung Zangbo River are projected with a slight increase in snow depth. Both the intensity and frequency of extreme snow events are projected to increase in Northeast China and Inner Mongolia, which are important agricultural and animal husbandry production areas in China. The reason behind this projection can be explained by the fact that the hydrological cycle intensified by temperature warming leads to excessive snowfall stacking up during winter. The changes in extreme snowfall events in the future will have a significant impact on China’s agricultural and animal husbandry production and threaten food security.

Climatology and surface impacts of atmospheric rivers on West Antarctica

Abstract. Atmospheric rivers (ARs) transport large amounts of moisture from the mid- to high-latitudes and they are a primary driver of the most extreme snowfall events, along with surface melting, in Antarctica. In this study, we characterize the climatology and surface impacts of ARs on West Antarctica, focusing on the Amundsen Sea Embayment and Marie Byrd Land. First, we develop a climatology of ARs in this region, using an Antarctic-specific AR detection tool combined with the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) and the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5) atmospheric reanalyses. We find that while ARs are infrequent (occurring 3 % of the time), they cause intense precipitation in short periods of time and account for 11 % of the annual surface accumulation. They are driven by the coupling of a blocking high over the Antarctic Peninsula with a low-pressure system known as the Amundsen Sea Low. Next, we use observations from automatic weather stations on Thwaites Eastern Ice Shelf with the firn model SNOWPACK and interferometric reflectometry (IR) to examine a case study of three ARs that made landfall in rapid succession from 2 to 8 February 2020, known as an AR family event. While accumulation dominates the surface impacts of the event on Thwaites Eastern Ice Shelf (&gt; 100 kg m−2 or millimeters water equivalent), we find small amounts of surface melt as well (&lt; 5 kg m−2). The results presented here enable us to quantify the past impacts of ARs on West Antarctica's surface mass balance (SMB) and characterize their interannual variability and trends, enabling a better assessment of future AR-driven changes in the SMB.

Effect of snow cover on water and heat transfer in alpine meadows in the source region of Yellow River

Extreme snowfall events have been increasing in the Tibetan Plateau, causing greater variations in the snow cover conditions. However, the soil water-heat transfer under different snow conditions has rarely been characterized in detail. Here, by using the multi-source observation data of five years, we analyzed the influences of snow cover on water-heat transfer in alpine meadows of the source region of the Yellow River. The main findings are as follows: In the deep soil, the yearly warming rate from spring to summer was much faster than the cooling rate from autumn to winter, while in the shallow soil, conversely, the former was slower than the latter. Snow cover not only decreased the average soil temperature but also inhibited the occurrence of extremely low temperatures in the soil. The insulation effect of snow was mainly in the mid-frozen period. It was insufficient to balance out the heat lost by the high albedo during early and late frozen periods. In years with more snow, different depths of the soil featured similar thawing dates and plenty of soil voids due to small solid water content and high gravel content, together creating favorable conditions for the snowmelt infiltration, which passed through the frozen layer and infiltrated into the soil of 3.20 m or deeper. In years with less snow, the long-term freezing-thawing cycles aggravated the evaporation and loss of surface soil water in spring. Under different snow cover conditions, the difference in the sensible heat flux was much larger than the latent heat flux in winter and early spring. This study provides a refined physical image of soil water-heat transfer under extreme snow cover conditions in the Tibetan Plateau, which is expected to light the snow cover-frozen soil interaction in the mid-latitude and high-elevation areas.

Adjustment of Solid Precipitation during the Filomena Extreme Snowfall Event in Spain: From Observations to “True Precipitation”

Abstract On January 2021, the heaviest snowfall in five decades hit central Spain, especially affecting Madrid. The city’s Barajas International Airport closed, along with a number of roads, and all trains to and from Madrid were cancelled. This storm was named Filomena by the Spanish Meteorological Agency (AEMET), and produced continuous snowfall in Spain on 7–10 January. The observed snow depth was around 50 cm in 24 h in Madrid, and even higher in other areas of Spain. However, the measured accumulation of national precipitation gauges was not consistent with the observed accumulated snow on the ground and with the modeled weather forecast. The undercatch of solid precipitation was the primary reason for this inconsistency. This undercatch was quantified using transfer functions developed from the World Meteorological Organization (WMO) Solid Precipitation Intercomparison Experiment (SPICE). Results show that an underestimation of 20%–30% of solid precipitation in large areas of Spain was observed, with some areas experiencing even larger differences. Without adjustments, it was impossible to accurately validate the model forecast. The adjusted precipitation was also more realistically distributed, and it was more consistent with all the damage that occurred. The same methods can be applied to other snowfall events occurring anywhere in the world, and also using different precipitation gauges and/or models. This an example of the type of extreme events that modelers, forecasters, and climatologists should be aware of to avoid misinterpreting differences between modeled precipitation, observed precipitation, and nowcasting.

Effects of Lake Nam Co and Surrounding Terrain on Extreme Precipitation Over Nam Co Basin, Tibetan Plateau: A Case Study

AbstractThousands of lakes and complex topography on Tibetan Plateau (TP) have important impacts on the local weather and climate, especially extreme weather events. In this study, the Weather Research and Forecasting model was adopted to quantify the impacts of Lake Nam Co (LNC) and surrounding topography on the extreme snowfall event over Nam Co basin on 24 October 2006 based on numerical experiments. The accumulated precipitation of 12 hr in this event is characterized by a maximum precipitation center with an intensity exceeding 20 mm over eastern LNC and downwind regions. Results show that the precipitation regionally averaged over eastern LNC and downstream regions can be reduced by 53%, 26%, and 68% when LNC, surrounding terrain, and both of them are absent, respectively, suggesting that LNC plays a dominant role in the formation of this event while the surrounding mountains further amplify the lake effect precipitation/snow over the downwind of LNC. Mechanism analysis indicates that the low‐level convective instability and water vapor convergence induced by LNC are essential for the formation of this extreme snowfall event, while the wind deflection and topographic lifting further strengthen the precipitation over the downwind of LNC and shift the snow belt distribution. This study is not only important to deepen the understanding of the complex interactions between the lake and orography and their combined influences on regional extreme precipitation, but also helpful for further improving the refined forecasting of the extreme precipitation induced by the lake and surrounding terrain in other regions over TP.

Synoptic and Climatic Conditions of an Extreme Snowstorm Event Over Northeast China and Its Climate Predictability

A blizzard struck Northeast China in November 2020, and the maximum daily snowfall broke its record since 1961. The synoptic and climatic conditions and the predictability of this extreme snowstorm event are examined by using the daily National Centers for Environmental Prediction (NCEP) reanalysis and the second version of the NCEP Climate Forecast System (CFSv2). The results show that an anomalous anticyclone over Japan and an anomalous cyclone in South China supplied abundant moisture and the rapidly enhanced Siberian high triggered the snowstorm. Before the snowstorm, the positive North Pacific Oscillation (NPO) and North Atlantic Oscillation (NAO) were essential for the accumulated water vapor. In addition, we find that the monthly NPO index and NAO index in November 2020 are both extremely strong compared to 1979–2019, and their combination converges to create the extreme snowstorm-related atmospheric circulation. The positive NPO and NAO together induce an anomalous anticyclone in Japan, which provides southerly water vapor transport to Northeast China. The midlatitude North Pacific warm sea surface temperature (SST) contributes to the positive NPO, and the Atlantic SST anomalies impact the positive NAO. However, the La Niña condition in 2020 might not be a key factor influencing the snowstorm. Finally, the subseasonal–seasonal skillful prediction of the snowfall can be made up to 3 days in advance. The CFSv2 had limited skill in forecasting the snowfall, NAO and NPO in November 2020. Improved predictability of extreme snowfall events is still needed.

Heavy Lake-Effect Snowfall Changes and Mechanisms for the Laurentian Great Lakes Region

Heavy lake-effect snowfall (HLES) events are snowfall events enhanced by interactions between lakes and overlying cold air. Significant snowfall rates and accumulations caused during such events disrupt socioeconomic activities and sometimes lead to lethal consequences. The aim of this study is to assess projected changes to HLES by the end of the century (2079–2100) using a regional climate model for the first time with 3D representation for the Laurentian Great Lakes. When compared to observations over the 1989–2010 period, the model is able to realistically reproduce key mechanisms and characteristics of HLES events, thus increasing confidence in future projections. Projected changes to the frequency and amount of HLES suggest decreasing patterns, during the onset, active and decline phases of HLES. Despite reduced lake ice cover that will allow enhanced lake–atmosphere interactions favouring HLES, the warmer temperatures and associated increase in liquid to solid precipitation ratio along with reduced cold air outbreaks contribute to reduced HLES in the future climate. Analysis of the correlation patterns for current and future climates further supports the weaker impact of lake ice fraction on HLES in future climates. Albeit the decreases in HLES frequency and intensity and projected increases in extreme snowfall events (resulting from all mechanisms) raise concerns for impacts on the transportation, infrastructure and hydropower sectors in the region.

The role of snowmelt discharge to runoff of an alpine watershed: Evidence from water stable isotopes

Snow is an important form of water storage which profoundly affects the hydrological processes in alpine watersheds, especially the runoff during snowmelt period. As the strong impact of climate change, the concern about snowmelt water to runoff in alpine watersheds is dramatically growing. However, the studies are mainly focused on arid and semi-arid areas, the research on semi-humid regions sensitive to the climate change need to be strengthened. In this study, for evaluating the contribution of snowmelt water to runoff in snowmelt period, we calculated the stable isotope values (δD, δ18O and d-excess) of different water bodies including river, snow, rain, groundwater, and snowmelt water in the Erdaobaihe River watershed of Changbai Mountains area. The results indicated that the δ18O values of snowmelt water showed an increasing trend with increasing temperature, while the d-excess values of snowmelt water showed a decreasing trend. During the snowmelt period, the snow cover ratio varied from 20.31% to 0.02%. The contribution ratio of snowmelt water to runoff was from 14.4% to 59.8% with average of 42.60% and the total contribution discharge was about 36.56 × 106 m3, which was higher than inland mountainous areas as different elevation and climate. As the stable water source of river, the groundwater contributed 19.2–61.6% with average of 43.88%. The snowmelt water plays an important role in regional water balance. Owing to climate change, the snowfall period in Changbai Mountains was gradually shortening and extreme snowfall events were increasing. The results will provide evidence for further hydrological studies and help to plan future water management strategies in the alpine watershed.