Annual Snowfall Research Articles

Simulating future climate change impacts on snow- and ice-related driving hazards in Arctic-boreal regions

As Arctic and boreal regions rapidly warm, the frequency and seasonal timing of hazardous driving conditions on all-season Arctic-boreal roads are likely to change. Because these roads link remote Arctic areas to the rest of the North American road system, climate change may substantially affect safety and quality of life for northern residents and commercial enterprises. To gain insight into future hazardous driving conditions, we built Random Forest models that predict the occurrence of hazardous driving conditions by linking snow, ice, and weather simulated by a spatially explicit modeling system (SnowModel) to archived road condition reports from two highly trafficked all-season northern roads: the Dalton Highway (Alaska, USA) and Dempster Highway (Yukon, Canada). We applied these models to downscaled future climate trajectories for the study period of 2006–2100. We estimated future trends in the frequency and timing of icy, wet-icy, and snowy road surfaces, blowing and drifting snow, and high winds. We found that as the climate warms, and the portion of the year when snow and ice occur becomes shorter, overall frequency of snow storms and ice- and snow-related driving hazards decreased. For example, the mean number of days per year when roads are covered in snow or ice decreased by 51 d (−21%) on the Dalton Highway between the 2006–2020 and 2081–2100 time periods. However, the intensity of storms was predicted to increase, resulting in higher mean annual storm wind speeds (Dalton +0.56 m s−1 [+17%]) and snowfall totals (Dalton +0.3 cm [+36%]). Our models also predicted increasing frequency of wet-icy driving conditions during November, December, January, and February, when daylength is short and hazardous conditions may be more difficult to perceive. Our findings may help road managers and drivers adapt their expectations and behaviors to minimize accident risk on Arctic-boreal roads in the future.

Maternal effects and the legacy of extreme environmental events for wild mammals.

Maternal effects and the legacy of extreme environmental events for wild mammals.

Elevation impact on seed germination requirements for two Asteraceae species

Elevation and latitude correlate with environmental factors that drive natural selection. Climate-change projections in the Great Basin suggest higher temperatures and increasingly lower annual winter snowfall, especially at low elevations. The transition from dormancy to germination represents a vulnerable stage of plant phenology, given the high susceptibility to death in newly germinated seedlings. Consequently, mechanisms involved with this phenomenon and its timing play an essential role in plant population fitness. This study investigates seed dormancy and germination for 2 co-occurring Asteraceae/Compositae species: arrowleaf balsamroot (<i>Balsamorhiza sagittata</i> (Pursh) Nutt.) and shiny mule’s ear (<i>Wyethia amplexicaulis</i> (Nutt.) Nutt.) from the same geographic area (near Provo Canyon, Utah) across an elevation gradient of 1584 m to 2438 m (5200–8000 ft). In laboratory experiments, seeds received increasing periods of cold stratification at 2 °C (35.6 °F) (from 4–20 wk) followed by incubation at 10 to 20 °C (50–68 °F). Shiny mule’s ear seeds from low (1584 m [5200 ft]) and mid (2011 m [6600 ft]) elevations required 8 wk of cold stratification while seeds from the highest elevation required 12 wk to reach 50% germination. Seeds of arrowleaf balsamroot from all elevations reached 50% germination after 16 wk of cold stratification although germination rate varied by elevation. These results suggest that selection pressure in contrasting environments results in variable dormancy-breaking durations, with implications for propagation, projected climate change, and seed sourcing in restoration efforts. Brown A, Allen PS. 2023. Elevation impact on seed germination requirements for two Asteraceae species. Native Plants Journal 24(1):45–53.

THE HEAVY SNOWFALL IN THE LVIV REGION

The relevance of determining the type of circulation and thermodynamic conditions of heavy snowfall in the Lviv region is due to the significant complication of meteorological conditions for aircraft flight due to heavy snowfall. Revealed the significant annual snowfall in the Lviv region from 2011 to 2021 at each station of the region with an increase in the number of cases towards the Carpathian Mountains. Established that heavy snowfall was observed at the stations of the Lviv region once every 3-5 years, with an increase in the number of cases after 2016, and the maximum of the annual flow occurred in February and December. Determined that heavy snowfalls were mainly formed under the influence of the occluded front during the movement or formation of the cyclone center over the northwest of Ukraine within the cold high-altitude baric basin at the level of 500 hPa during the north-west transport of air masses at altitudes from 750 to 3000 m.

Impact of the COVID-19 Pandemic on the 2020 Diurnal Temperature Range (DTR) in the Contiguous USA

Following the emergence of COVID-19, nations around the world implemented effective restrictions that limited people’s movements and economic activity, which reportedly led to environmental improvements. The lowering of air emissions is one environmental indicator that has been connected to the pandemic. The diurnal temperature range (DTR) is one environmental indicator that has been linked to air pollution. In this study, it was hypothesized that because of the pandemic restrictions and slowdowns, the DTR in 2020 for a country that implemented major restrictive measures in reaction to the pandemic would be higher than in previous years, despite or in addition to background climatic forcings. Based on information from weather stations in the contiguous United States of America (USA), the DTR for the year 2020 was compared to the five years before it as a test of this hypothesis. It was verified that the annual mean DTR of 2020 was higher than the three years prior (2017–2019), but lower than the DTR of 2015 and 2016. Compared to historical trends (since 1911), the DTR change in 2020 is within past mean DTR variations that occurred over approx. 12-year cycles, linked to sunspot activity (Schwabe solar cycle). Moreover, climatic effects such as El Niño, La Niña and the prolonged trend of global warming reduce the confidence in the perceived effect of the pandemic. To determine if or how anthropogenic and environmental factors can magnify the impact of the COVID-19 restrictions on the regional mean DTR, five other parameters (annual snowfall quantities, gross domestic product per capita, population density, latitude (northern/southern), and longitude (coastal/inner)) were also examined against changes in DTR from 2015 to 2020. This analysis pointed to the environmental and industrial factors being more strongly correlated with short-term climate changes than societal factors and geographical location.

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 &amp;gt;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.

Evaluating seasonal and regional distribution of snowfall in regional climate model simulations in the Arctic

Abstract. In this study, we investigate how the regional climate model HIRHAM5 reproduces the spatial and temporal distribution of Arctic snowfall when compared to CloudSat satellite observations during the examined period of 2007–2010. For this purpose, both approaches, i.e., the assessments of the surface snowfall rate (observation-to-model) and the radar reflectivity factor profiles (model-to-observation), are carried out considering spatial and temporal sampling differences. The HIRHAM5 model, which is constrained in its synoptic representation by nudging to ERA-Interim, represents the snowfall in the Arctic region well in comparison to CloudSat products. The spatial distribution of the snowfall patterns is similar in both identifying the southeastern coast of Greenland and the North Atlantic corridor as regions gaining more than twice as much snowfall as the Arctic average, defined here for latitudes between 66 and 81∘ N. Excellent agreement (difference less than 1 %) in the Arctic-averaged annual snowfall rate between HIRHAM5 and CloudSat is found, whereas ERA-Interim reanalysis shows an underestimation of 45 % and significant deficits in the representation of the snowfall rate distribution. From the spatial analysis, it can be seen that the largest differences in the mean annual snowfall rates are an overestimation near the coastlines of Greenland and other regions with large orographic variations as well as an underestimation in the northern North Atlantic Ocean. To a large extent, the differences can be explained by clutter contamination, blind zone or higher resolution of CloudSat measurements, but clearly HIRHAM5 overestimates the orographic-driven precipitation. The underestimation of HIRHAM5 within the North Atlantic corridor south of Svalbard is likely connected to a poor description of the marine cold air outbreaks which could be identified by separating snowfall into different circulation weather type regimes. By simulating the radar reflectivity factor profiles from HIRHAM5 utilizing the Passive and Active Microwave TRAnsfer (PAMTRA) forward-modeling operator, the contribution of individual hydrometeor types can be assessed. Looking at a latitude band at 72–73∘ N, snow can be identified as the hydrometeor type dominating radar reflectivity factor values across all seasons. The largest differences between the observed and simulated reflectivity factor values are related to the contribution of cloud ice particles, which is underestimated in the model, most likely due to the small sizes of the particles. The model-to-observation approach offers a promising diagnostic when improving cloud schemes, as illustrated by comparison of different schemes available for HIRHAM5.

Representation of Lake–Atmosphere Interactions and Lake-Effect Snowfall in the Laurentian Great Lakes Basin among HighResMIP Global Climate Models

Abstract Credible modeling, tools, and guidance, regarding the changing Laurentian Great Lakes and the climatic impacts, are needed by local decision-makers to inform their management and planning. The present study addresses this need through a model evaluation study of the representation of lake–atmosphere interactions and resulting lake-effect snowfall in the Great Lakes region. Analysis focuses on an extensive ensemble of 74 historical simulations generated by 23 high-resolution global climate models (GCMs) from the High-Resolution Model Intercomparison Project (HighResMIP). The model assessment addresses the modeling treatment of the Great Lakes, the spatial distribution and seasonality of climatological snowfall, the seasonal cycle of lake-surface temperatures and overlake turbulent fluxes, and the lake-effect ratio between upwind and downwind precipitation. A deeper understanding of model performance and biases is achieved by partitioning results between HighResMIP GCMs that are 1) coupled to 1D lake models versus GCMs that exclude lake models, 2) between prescribed-ocean model configurations versus fully coupled configurations, and 3) between deep Lake Superior versus relatively shallow Lake Erie. While the HighResMIP GCMs represent the Great Lakes by a spectrum of approaches that include land grid cells, ocean grid cells (with lake surface temperature and ice cover boundary conditions provided by the Met Office Hadley Center Sea Ice and Sea Surface Temperature Dataset), and 1D lake models, the current investigation demonstrates that none of these rudimentary approaches adequately represent the complex nature of seasonal lake temperature and ice cover evolution and its impact on lake–atmosphere interactions and lake-effect precipitation in the Great Lakes region. Significance Statement The purpose of this study is to evaluate the capability of high-resolution global climate models to simulate lake–atmosphere interactions and lake-effect snowfall in the Great Lakes region, given the critical influence of the lakes on regional climate and vast societal and environmental impacts of lake-effect snowfall. It is determined that the models inadequately represent lake temperatures and ice cover, often leading to insufficient annual snowfall in the lake-effect zones. More advanced, three-dimensional lake models need to be coupled to climate models to support greater credibility in regional lake and climate simulations and future climate projections.

Analyses of a Lake Dust Source in the Middle East through Models Performance

Drying lakes have become a new source of dust, causing severe problems in surrounding areas. From 2000 to 2017, a statistical study was conducted on Lake Urmia in Iran in the Middle East. The results indicated a significant increase in the annual number of dusty days in stations around the lake and the mean annual aerosol optical depth (AOD) at 550 nm. The sharp decrease in annual snowfall rate over the Lake Urmia area since 2007 has been linked to the lake’s decreasing water level and drying. During a dust storm event from 27 October to 31 October 2017, a local dust storm originated from Lake Urmia before another large-scale dust storm originated from the An-Nafud desert. According to MODIS true-color images, dust particles were lifted from Lake Urmia and transported eastward to the Caspian Sea and the HYSPLIT model. The comparison of the four models under the Sand and Dust Storm Warning Advisory and Assessment System (SDS-WAS) revealed that the models overestimated surface dust concentrations compared to ground-based PM10 measurements. Nevertheless, the NOAA/WRF-Chem and DREAMABOL models simulated higher dust concentrations during the dust period. More emphasis should be placed on the development of dust models for SDS-WAS models in Lake Urmia.

Geomatic Techniques Applied to the Dynamic Study (2001–2019) of the Rock Glacier in the Veleta Cirque (Sierra Nevada, Spain)

During the Little Ice Age (LIA), Corral del Veleta (Sierra Nevada) housed a small glacier of which relict glacial ice and permafrost still remain under packets of ice blocks. Currently, it is considered the southernmost rock glacier in Europe. The analysis and results of monitoring carried out on this rock glacier reveal it to be in an accelerated process of immobilization and that the relict glacial ice blocks and permafrost on which it lies are in a continual process of degradation. The rock glacier was monitored from 2001 to 2019 using diverse geomatic techniques, to which geophysical and thermal techniques were added. The results obtained during the observation period shed light on the dynamic of the rock glacier (morpho-topographic movements and deformations) as well as the physical state of the underlying frozen bodies (volumetric reduction and spatial distribution). The changes observed are related to variations in the dominant high-mountain climate of Sierra Nevada, particularly since the end of the 20th century, the general tendencies of which are increasing temperatures, decreasing annual snowfall, and a shorter duration of snow on the ground.

Possible Causes of Anomalous Glacier Mass Balance in the Western Kunlun Mountains

AbstractUnder current global warming, most glaciers on the Tibetan Plateau have shown significant mass loss during 2000–2019. However, the average glacier mass balance in the western Kunlun Mountains (WKM) was positive during this period. The causes of these opposing average status and the temporal glacier mass changes over the last several decades in the WKM continue to be the subject of active debate. The long‐term mass balance of the Guliya Ice Cap (Guliya) in the WKM during 1970–2019 was reconstructed using an energy and mass balance model and calibrated ERA5 data, which was calibrated and validated by in situ measurements and geodetic mass balances. Guliya showed a positive mean mass balance during 2000–2019 because annual snowfall was larger than low ablation‐season meltwater caused by low air temperature (T a ). At interannual scales, annual mass balances were equally controlled by ablation‐season precipitation and T a during 1970–2019. From 1970s–1990s to 1990s–2010s, most Tibetan glaciers showed decreased mass balance due to increased ablation season T a , while the WKM glaciers experienced increased mass balance due to increased ablation‐season precipitation related to changes in the Silk Road Pattern. However, during 2000–2019, the annual mass balance of Guliya followed a decreasing trend due to increasing ablation‐season T a . The positive mass balance of the WKM glaciers will cease under future warming due to annual snowfall decreasing below ablation‐season meltwater. These changes will threaten lives and livelihoods in the Tarim Basin, whilst also jeopardizing ice core‐derived climate histories from the WKM glaciers.

The Contribution of Lake-Effect Snow to Annual Snowfall Totals in the Vicinity of Lakes Erie, Michigan, and Ontario

In the Great Lakes region, total cold-season snowfall consists of contributions from both lake-effect systems (LES) and non-LES snow events. To enhance understanding of the regional hydroclimatology, this research examined these separate contributions with a focus on the cold seasons (October–March) of 2009/2010, a time period with the number of LES days substantially less than the mean, and 2012/2013, a time period with the number of LES days notably greater than the mean, for the regions surrounding Lakes Erie, Michigan, and Ontario. In general, LES snowfall exhibited a maximum contribution in near-shoreline areas surrounding each lake while non-LES snowfall tended to provide a more widespread distribution throughout the entire study regions with maxima often located in regions of elevated terrain. The percent contribution for LES snowfall to the seasonal snowfall varied spatially near each lake with localized maxima and ranged in magnitudes from 10% to over 70%. Although total LES snowfall amounts tended to be greater during the cold season with the larger number of LES days, the percent of LES snowfall contributing to the total cold-season snowfall was not directly dependent on the number of LES days. The LES snowfall contributions to seasonal totals were found to be generally larger for Lakes Erie and Ontario during the cold season with a greater number of LES days; however, LES contributions were similar or smaller for areas in the vicinity of Lake Michigan during the cold season with a smaller number of LES days.

Identification of target market transformation efforts for solar energy adoption

In recent years, solar energy has been increasing in usage throughout the world, especially in the United States. Market transformation (a concept based on collaborative efforts between industry advocates and policy-makers to increase adoption through economies of scale) plays a fundamental role in expanding the adoption of solar energy. However, there are currently limited resources to identify the optimal locations for increasing the likelihood of industry advocates interested in exploiting opportunities related to solar energy technologies. This study aims to showcase a visual mapping tool to assist with solar energy market transformation. By combining data from different sources, a unique process and output were created. The factors considered in this study include cost of electricity, net metering policies study, cost of solar energy systems, solar irradiance, annual sunshine rates, annual snowfall rates, and annual precipitation rates. All the factors were considered on both a residential and commercial level. The findings rank states from most viable to least viable with respect to the combined input factors. The results show that states with a high likelihood of market transformation at the residential level also have a high likelihood of market transformation at the commercial level.

Estimated changes in different forms of precipitation (snow, sleet, and rain) across China: 1961–2016

Different forms of precipitation (snow, sleet, and rain) have divergent effects on the Earth's surface water and energy fluxes. Therefore, discriminating between these forms, and exploring their climatology and variations are of significant importance, especially under a changing climate. In this study, a state-of-the-art parameterization scheme with wet-bulb temperature (Tw), relative humidity (RH), surface air pressure, and elevation as inputs was used to estimate the climatologies and trends of the different forms of precipitation and their temperature thresholds across China mainland from 1961 to 2016. The results indicate that on average, only 9.6% and 0.8% of the total precipitation (602.9 mm) over China during 1961–2016 occurred as snow and sleet. The trends of the different forms of precipitation varied greatly from region to region and from season to season. The regionally averaged annual precipitation, rainfall, and snowfall across China significantly increased at rates of 11.4 mm/decade, 11.0 mm/decade, and 1.0 mm/decade, respectively, whereas the annual sleet decreased at a rate of −0.3 mm/decade. The region-wide snow (rain) fraction significantly increased (decreased) in Northwestern China (NWC) and Northern China (NC) but significantly decreased (increased) on the Tibetan Plateau (TP). Given the heterogeneous RH and complex topography, the Tw values at which snow-sleet and sleet-rain occurred with equal frequency—that is, Ts and Tr, varied significantly across China, averaging 0.1 °C and 0.3 °C, respectively. However, most regions experienced significant decreases in the temperature thresholds (especially Tr), with decreasing RH. Almost all of the regions also experienced significant increases in Tw, especially on the TP and during the winter and spring. The adverse combination of the increase in Tw and the decrease in the temperature thresholds resulted in more precipitation falling as rain, although the snowfall slightly increased in some regions.

Proportion and Distribution of Rain and Snow in China from 1960 to 2018

AbstractRainfall and snowfall have different effects on energy balance calculations and land–air interactions in terrestrial models. The identification of precipitation types is crucial to understand climate change dynamics and the utilization of water resources. However, information regarding precipitation types is not generally available. The precipitation obtained from meteorological stations across China recorded types only before 1979. This study parameterized precipitation types with air temperature, relative humidity, and atmospheric pressure from 1960 to 1979, and then identified precipitation types after 1980. Results show that the main type of precipitation in China was rainfall, and the average annual rainfall days (amounts) across China accounted for 83.08% (92.55%) of the total annual precipitation days (amounts). The average annual snowfall days (amounts) in the northwestern region accounted for 32.27% (19.31%) of the total annual precipitation days (amounts), which is considerably higher than the national average. The average annual number of rainfall and snowfall days both displayed a downward trend while the average annual amounts of these two precipitation types showed an upward trend, but without significance at 0.1 levels. The annual number of rainfall and snowfall days in the southwestern region decreased significantly (−2.27 and −0.31 day decade−1,p&lt; 0.01). The annual rainfall amounts in the Jianghuai region increased significantly (40.70 mm decade−1,p&lt; 0.01), and the areas with the most significant increase in snowfall amounts were the northwestern (3.64 mm decade−1,p&lt; 0.01). These results can inform our understanding of the distribution and variation of precipitation with different types in China.

Decreases in Mean Annual Streamflow and Interannual Streamflow Variability Across Snow‐Affected Catchments Under a Warming Climate

AbstractIt has been found that a decreased fraction of precipitation falling as snow in a warmer climate significantly affects streamflow. Here, based on observations from 631 catchments over the contiguous United States, we proposed a framework to investigate the first‐order and second‐order hydro‐climatic relationships between annual streamflow and snowfall fraction. Results show that in addition to the mean annual streamflow, the interannual streamflow variability will also decrease with lower snowfall fraction in the context of warming. The positive relationship between streamflow variability and snowfall fraction may result from the asymmetric hydrological effects of snowfall in the wet and dry years. To our knowledge, it is the first attempt to detect the role of snowfall on the streamflow variability. This study provides new understandings of the second‐order hydro‐climatic effects, and these findings will facilitate decisions for water resource management in a changing climate.

The role minor and major snowfall events play in New Jersey snowfall over the past 126 years

Climate records indicate that there has been a trend of decreasing annual snowfall totals throughout the United States during the peak winter season. However, some states do not fit this trend. For example, New Jersey has seen a significant increase in snowfall over the past 126 years of recorded observations. This snowfall increase does not fit with the trend of increasing temperatures in New Jersey. One reason for this disconnect may be that annual snowfall may not tell the full story. We hypothesize that although annual snowfall has remained the same on average, the frequencies of major and minor snowfall events have noticeably increased. To examine this, we used the New Brunswick, NJ Cooperative Weather Station daily data, which consists of snowfall, precipitation, and temperature observations dating back to 1895. We utilized statistical tests to identify significant trends and predict future trends. In summary, we found that there was no significant evidence for an increase in the frequency of minor events (1.1-inch to 4.0-inch events), but there was evidence for an increase in the frequency of major events (4.1+ inch events). The results imply that a warming climate might be opening up opportunities for more snowfall.

Projections of Hydroclimatic Extremes in Southeast Alaska under the RCP8.5 Scenario

Abstract Parts of southeast Alaska experienced record drought in 2019, followed by record daily precipitation in late 2020 with substantial impacts to human health and safety, energy resources, and fisheries. To help ascertain whether these types of events can be expected more frequently, this study investigated observed trends and projected changes of hydroclimatic extremes indices across southeast Alaska, including measures of precipitation variability, seasonality, magnitude, and type. Observations indicated mixed tendencies of interannual precipitation variability, but there were consistent trends toward warmer and wetter conditions. Projected changes were assessed using dynamically downscaled climate model simulations at 4-km spatial resolution from 2031 to 2060 that were compared with a historical period from 1981 to 2010 using two models—NCAR CCSM4 and GFDL CM3. Consistent directional changes were found for five of the analyzed indices. The CCSM indicated increased maximum 1-day precipitation (RX1; 12.6%), increased maximum consecutive 5-day precipitation (RX5; 7.4%), longer periods of consecutive dry days (CDD; 11.9%), fewer snow cover days (SNC; −21.4%) and lower snow fraction (SNF; −24.4%); for GFDL these changes were 19.8% for RX1, 16.0% for RX5, 20.1% for CDD, −21.9% for SNC, and −26.5% for SNF. Although both models indicated substantial snow losses, they also projected annual snowfall increases at high elevations; this occurred above 1500 m for CCSM and above 2500 m for GFDL. Significance testing was assessed at the 95% confidence level using Theil–Sen’s slope estimates for the observed time series and the Wilcoxon–Mann–Whitney U test for projected changes of the hydroclimatic extremes indices relative to their historical distributions.

The Seasonal Snowfall Contributions of Different Snowstorm Types in Central New York State

Located at the eastern extent of the Great Lakes snowbelt, Central New York averages some of the highest annual snowfall totals east of the Rocky Mountains. This is in large part due to the variety of snowstorms that affect the region including lake-effect storms, coastal storms, and overrunning storms. Previous estimates suggest that lake-effect snowstorms account for approximately half of the seasonal snow in the Great Lakes basin, but ignore the spatial variability that exists within the region. Therefore, this study examines the seasonal snowfall contributions of the different snowstorm types to affect Central New York. Results suggest that although lake-effect snowstorms are the dominant snowstorm type in the region, their seasonal snowfall contributions vary between 13 and 48%. Although lake-effect snowstorms produce more snow during the peak and mid-seasons, their relative contribution is greatest during the early and mid-winter seasons. Generally, higher contributions occur near the Tug Hill Plateau, with lower contributions in southern Central New York. Instead, snowfall in southern Central New York is mostly dominated by Nor'easters (16–35%), with lesser contributions from Rocky lows (14–29%). Overrunning storms that originate in Canada (e.g., Alberta clippers) and non-cyclonic storms contribute the least to seasonal snowfall totals across Central New York; however, they are often the catalyst for lake-effect snowstorms in the region, as they advect continental polar air masses that destabilize across the lake. Understanding the actual snowfall contribution from different snowstorm types is needed for future climate predictions. Since the potential trajectory of future snowfall varies according to the type of storm, climate models must accurately predict the type of storm that is producing the snow.

Future changes in daily snowfall events over China based on CMIP6 models

China has been frequently affected by severe snowstorms in recent years that have particularly large economic and human impacts. It is thus of great importance to increase our understanding of the underlying mechanisms of and future changes in snowfall occurrences over China. In this study, the effects of anthropogenic influences on snowfall and the associated future changes are explored using new simulations from CMIP6 (phase 6 of the Coupled Model Intercomparison Project) models. Observational evidence reveals a decrease in the annual total snowfall days and an increase in intense snowfall days over the snowfall-dominated regions in China during recent decades. Fingerprints of anthropogenic influences on these changes are detectable, especially the impacts of increased greenhouse gas emissions. During the winter seasons, low temperatures still cover the regions of northern China, and the associated precipitation days show an increase due to anthropogenic warming, which substantially benefits the occurrence of snowfall over these regions, particularly for intense snowfall events. This is also true in the future, despite rapid warming being projected. By the end of this century, approximately 23% of grids centered over northern China are projected to still experience an increase in daily intense snowfall events in winters. Additionally, the length of the snowfall season is projected to narrow by nearly 41 days compared to the current climate. Thus, in the future, regions of China, especially northern China, are likely to experience more intense snowfall days over a more concentrated period of time during the winter seasons.摘要近年来, 中国部分地区频繁遭遇极端降雪事件袭击, 造成巨大经济损失和人员伤亡. 因此, 亟需深入理解中国地区极端降雪变化的物理机制及其未来演变趋势, 为国家防灾减灾及气候变化应对措施制定提供科学依据. 本文基于CMIP6模式结果, 深入开展人类活动对中国地区降雪变化的影响及其未来演变趋势预估研究. 观测显示, 过去几十年在中国降雪频发区, 其年降雪日数呈现减少趋势但强降雪日数增加; 在这些变化中能够检测到人类活动的痕迹, 尤其是温室气体排放的影响. 对于冬季, 全球变暖背景下中国北方地区降水日数明显增加, 但北方地区仍为低温控制, 这有利于降雪尤其是强降雪事件的发生; 到了本世纪末, 中国仍有约23%的区域 (主要集中在北方地区) 其冬季强降雪日数呈现增加趋势. 此外, 中国地区降雪季长度相比当前气候减少了约41天. 因此, 在未来持续变暖背景下, 中国北方部分地区冬季将经历更多更为集中的强降雪事件.