Amount Of Snowfall Research Articles

Pastoral yak rearing system is changing with change in climate: an exploration of North Sikkimin Eastern Himalaya

Yak is an integral part of the livelihood of highlanders in Indian Eastern Himalaya where only subsistence agriculture is possible due to its difficult terrain and harsh climate. The tribal households of Lachen and Lachung in North Sikkim rear yaks at an altitude of 3000 to 5000 m in semi-pastoral system which is highly dependent on temperature and snowfall pattern. Any change in climatic factors is expected to affect the yaks and livelihood of the yak herders. Hence, an explorative study was conducted to understand how the pastoral yak rearing system is changing in the region with change in climate. The estimated temperature increment was 0.03–0.04 °C/annum which is corroborated by herders’ perceptions. They observed that the amount of snowfall has receded, especially in lower altitudes and the snowfall period shifted from November–December to January–March. The commencement of upward migration of yak herders advanced by 15–30 days due to increase in March temperature and the migration span extended by 45 days now. The downward migration is restricted to mid alleviation (2750–3000 m) now which was earlier about 2000 m whereas the upward migration has gone up farther about 500 m due to increasing temperature and unavailability of quality pasture. The study revealed that the pastoral yak rearing in North Sikkim is transforming to cope the impending climate change. However, to reduce the vulnerability of yak, research and extension efforts/policies should be concentrated on fodder production and pasture management suiting to the awaiting climate change.

Microsites and Climate Zones: Seedling Regeneration in the Alpine Treeline Ecotone Worldwide

Microsites, local features having the potential to alter the environment for seedling regeneration, may help to define likely trends in high-elevation forest regeneration pattern. Although multiple microsites may exist in any alpine treeline ecotone (ATE) on any continent, some microsites appear to enhance density of seedling regeneration better than others. Known seedling regeneration stresses in the ATE include low temperature, low substrate moisture, high radiation, drought, wind, and both high and low snowfall amount. Relationships among various microsite types, annual temperature, annual precipitation, and tree genera groups were assessed by synthesizing 52 studies from 26 countries spanning six continents. By categorization of four main microsite types (convex, concave, object, and wood) by mean annual precipitation and temperature, four major climatic zone associations were distinguished: cold & dry, cold & wet, warm & dry, warm & wet. Successful tree recruitment varied among microsite types and by climatic zones. In general, elevated convex sites and/or decayed wood facilitated earlier snow melt for seedlings located in cold & wet climates with abundant snowfall, depressions or concave sites enhanced summer moisture and protected seedlings from wind chill exposure for seedlings growing in cold & dry locations, and objects protected seedlings from excessive radiation and wind in warm & dry high locations. Our study results suggest that climate change will most benefit seedling regeneration in cold & wet locations and will most limit seedling regeneration in warm & dry locations given likely increases in fire and drought. Study results suggest that high-elevation mountain forests with water-limited growing seasons are likely to experience recruitment declines or, at best, no new recruitment advantage as climate warms. Climate envelope models, generally focusing on adult trees rather than seedling requirements, often assume that a warming climate will move tree species upward. Study results suggest that climate models may benefit from more physically-based considerations of microsites, climate, and current seedling regeneration limitations.

Bias Correction of Gauge Data and its Effect on Precipitation Climatology over Mainland China

AbstractTypical rain gauge measurements have long been recognized to underestimate actual precipitation. Long-term daily precipitation records during 1961–2013 from a dense national network of 2379 gauges were corrected to remove systematic errors caused by trace precipitation, wetting losses, and wind-induced undercatch. The corrected percentage was higher in cold seasons and lower in warm seasons. Both trace precipitation and wetting loss corrections were more important in arid regions than in wet regions. A greater correction percentage for wind-induced error could be found in cold and arid regions, as well as high wind speed areas. Generally, the annual precipitation amounts as well as the annual precipitation intensity increased to varying degrees after bias correction with the maximum percentage being about 35%. More importantly, the bias-corrected snowfall amount as well as the rainstorm amount increased remarkably by percentages of more than 50% and 18%, respectively. Remarkably, the total number of actual rainstorm events during the past 53 years could be 90 days more than the observed rainstorm events in some coastal areas of China. Therefore, the actual amounts of precipitation, snowfall, and intense rainfall were much higher than previously measured over China. Bias correction is thus needed to obtain accurate estimates of precipitation amounts and precipitation intensity.

Impacts of the East Asian Winter Monsoon and Local Sea Surface Temperature on Heavy Snowfall over the Yeongdong Region

AbstractThis research investigates the impact of local sea surface temperature (SST) on the 2-month (January and February) accumulated snowfall over the Yeongdong (YD) region. The YD region is strongly affected by synoptic-scale factors such as the East Asian winter monsoon (EAWM). The relationships of snowfall over the YD region to the EAWM and local SST are examined based on observational analyses and sensitivity experiments using a regional climate model. In the sensitivity experiments, local SST is replaced with the 33-yr mean winter SST (1982–2014). The observational analysis shows that both the synoptic environment and local SST are important factors for the occurrence of anomalous heavy snowfall over the YD region. The favorable synoptic environments can be characterized by eastward expansion of the Siberian high over Manchuria and corresponding enhancement of easterly anomalies over the YD region. These conditions are more frequently observed during the weak EAWM years than during the strong EAWM. Furthermore, warm SST over the East Sea contributes to heavy snowfall over the YD region by providing heat and moisture in the lower troposphere, which are important sources of energy for the formation of heavy snowfall. Warm SST anomalies over the East Sea enhance low-level moisture convergence over the YD region, while cold SST anomalies lead to reduced moisture convergence. Sensitivity experiments indicate that local SST can significantly affect snowfall amount over the YD region when the synoptic environments are favorable. However, without these synoptic conditions (expansion of the Siberian high and easterly inflow), the impact of local SST on the snowfall over the YD region is not significant.

Nitrogen Deposition and Responses of Forest Structure to Nitrogen Deposition in a Cool-Temperate Deciduous Forest

Few studies have reported the estimation of nitrogen (N) deposition, including dissolved organic N (DON) fluxes, through water flows and the contribution of snowfall in Asia. In this study, the concentrations and fluxes of DON and dissolved inorganic N (DIN) in bulk precipitation (BP), the throughfall (TF) of trees and understory dwarf bamboo, and stemflow (SF) were evaluated in a cool-temperate forest over three years to clarify N fluxes via precipitation and responses of trees and understory canopies to N deposition. The input of N to the study site in BP was 11.1 ± 1.71 kg N ha−1 year−1, with a significant contribution from DON (78%). Snowfall fluxes contributed up to 46% of the total N input, with variations related to the amount of snowfall (2.08–5.52 kg N ha−1 year−1). The forest canopy enriched DON (2.11 ± 0.42 kg N ha−1 year−1) but consumed NO3 + NO2–N (−0.73 ± 0.19 kg N ha−1 year−1). In contrast, through the understory bamboo canopy, DON (−1.02 ± 0.55 kg N ha−1 year−1) decreased while DIN (0.35 ± 0.44 kg N ha−1 year−1) increased. This study indicates that DON and snowfall should not be neglected when evaluating total N deposition into forest ecosystems, especially in remote regions. The canopy processes related to the dissolved N in the presence of understory plants might have significant implications for the internal N cycle in forest ecosystems.

A Self-Predictable Crop Yield Platform (SCYP) Based On Crop Diseases Using Deep Learning

This paper proposes a self-predictable crop yield platform (SCYP) based on crop diseases using deep learning that collects weather information (temperature, humidity, sunshine, precipitation, etc.) and farm status information (harvest date, disease information, crop status, ground temperature, etc.), diagnoses crop diseases by using convolutional neural network (CNN), and predicts crop yield based on factors such as climate change, crop diseases, and others by using artificial neural network (ANN). The SCYP consists of an image preprocessing module (IPM) to determine crop diseases through the Google Vision API and image resizing, a crop disease diagnosis module (CDDM) based on CNN to diagnose the types and extent of crop diseases through photographs, and a crop yield prediction module (CYPM) based on ANN by using information of crop diseases, remaining time until harvest (based on the date), current temperature, humidity and precipitation (amount of snowfall) in the area, sunshine amount, ground temperature, atmospheric pressure, moisture evaporation in the ground, etc. Four experiments were conducted to verify the efficiency of the SCYP. In the CDMM, the accuracy and operation time of each model were measured using three neural network models: CNN, region-CNN(R-CNN), and you only look once (YOLO). In the CYPM, rectified linear unit (ReLU), Sigmoid, and Step activation functions were compared to measure ANN accuracy. The accuracy of CNN was about 3.5% higher than that of R-CNN and about 5.4% higher than that of YOLO. The operation time of CNN was about 37 s less than that of R-CNN and about 72 s less than that of YOLO. The CDDM had slightly less operation time, but in this paper, we prefer accuracy over operation time to diagnose crop diseases efficiently and accurately. When the activation function of the ANN used in the CYPM was ReLU, the accuracy of the ANN was 2% higher than that of Sigmoid and 7% higher than that of Step. The CYPM prediction was about 34% more accurate when using multiple diseases than when not using them. Therefore, the SCYP can predict farm yields more accurately than traditional methods.

Anticipated changes to the snow season in Alaska: Elevation dependency, timing and extremes

AbstractSnowfall and snow season length across Alaska control the surface hydrology and underlying soil properties and also influence near‐surface air temperature by changing the energy balance. Current projections of warming suggest that considerable change will occur to key snow parameters, possibly contributing to extensive infrastructure damage from thawing permafrost, an increased frequency of rain‐on‐snow events and reduced soil recharge in the spring due to shallow end‐of‐winter snowpack. This study investigates projected changes to mean annual snowfall, dates of snow onset and snowmelt and extreme snowfall for Alaska, using dynamically downscaled reanalysis and climate model simulations. These include the ERA‐Interim reanalysis from 1981 to 2010, and two Coupled Model Intercomparison Project Phase 5 models: Community Climate System Model version 4 (CCSM4) and Geophysical Fluid Dynamics Laboratory Climate Model version 3 (GFDL‐CM3) from 1981 to 2100. The analysis is presented in 30‐year periods (i.e., 1981–2010, 2011–2040, 2041–2070 and 2071–2100) with the future scenarios from Representative Concentration Pathway 8.5. Late‐century projections of average annual snowfall at low elevations (0–1,000 m) show decreases of 41.3 and 40.6% for CCSM4 and GFDL‐CM3, respectively. At high elevations (1,000–2,000 m), the reductions are smaller at 13.5 and 14.2%, respectively. End‐of‐winter snow‐water equivalent displays reductions at all elevations in the future periods. Snow season length is shortened due to later snow onset and earlier snowmelt; many locations in southwest Alaska no longer experience continuous winter snowpack by the late‐century period. Maximum 2‐day snowfall amounts are projected to decrease near Anchorage and Nome, while Fairbanks and Utqiaġvik (Barrow) show no significant trend.

Satellite Estimation of Falling Snow: A Global Precipitation Measurement (GPM) Core Observatory Perspective.

Retrievals of falling snow from space-based observations represent key inputs for understanding and linking Earth's atmospheric, hydrological, and energy cycles. This work quantifies and investigates causes of differences among the first stable falling snow retrieval products from the Global precipitation Measurement (GPM) Core Observatory satellite and CloudSat's Cloud Profiling Radar (CPR) falling snow product. An important part of this analysis details the challenges associated with comparing the various GPM and CloudSat snow estimates arising from different snow-rain classification methods, orbits, resolutions, sampling, instrument specifications, and algorithm assumptions. After equalizing snow-rain classification methodologies and limiting latitudinal extent, CPR observes nearly 10 (3) times the occurrence (accumulation) of falling snow as GPM's Dual-Frequency Precipitation Radar (DPR). The occurrence disparity is substantially reduced if CloudSat pixels are averaged to simulate DPR radar pixels and CPR observations are truncated below the 8-dBZ reflectivity threshold. However, even though the truncated CPR- and DPR-based data have similar falling snow occurrences, average snowfall rate from the truncated CPR record remains significantly higher (43%) than the DPR, indicating that retrieval assumptions (microphysics and snow scattering properties) are quite different. Diagnostic reflectivity (Z)-snow rate (S) relationships were therefore developed at Ku and W band using the same snow scattering properties and particle size distributions in a final effort to minimize algorithm differences. CPR-DPR snowfall amount differences were reduced to ~16% after adopting this diagnostic Z-S approach.

Meteorological and evaluation datasets for snow modelling at 10 reference sites: description of in situ and bias-corrected reanalysis data

Abstract. This paper describes in situ meteorological forcing and evaluation data, and bias-corrected reanalysis forcing data, for cold regions' modelling at 10 sites. The long-term datasets (one maritime, one arctic, three boreal, and five mid-latitude alpine) are the reference sites chosen for evaluating models participating in the Earth System Model-Snow Model Intercomparison Project. Periods covered by the in situ data vary between 7 and 20 years of hourly meteorological data, with evaluation data (snow depth, snow water equivalent, albedo, soil temperature, and surface temperature) available at varying temporal intervals. Thirty-year (1980–2010) time series have been extracted from a global gridded surface meteorology dataset (Global Soil Wetness Project Phase 3) for the grid cells containing the reference sites, interpolated to 1 h time steps and bias-corrected. Although the correction was applied to all sites, it was most important for mountain sites hundreds of metres higher than the grid elevations and for which uncorrected air temperatures were too high and snowfall amounts too low. The discussion considers the importance of data sharing to the identification of errors and how the publication of these datasets contributes to good practice, consistency, and reproducibility in geosciences. The Supplement provides information on instrumentation, an estimate of the percentages of missing values, and gap-filling methods at each site. It is hoped that these datasets will be used as benchmarks for future model development and that their ease of use and availability will help model developers quantify model uncertainties and reduce model errors. The data are published in the repository PANGAEA and are available at https://doi.pangaea.de/10.1594/PANGAEA.897575.

Contrasting Meteorological Drivers of the Glacier Mass Balance Between the Karakoram and Central Himalaya

There is strong variation in glacier mass balances in High Mountain Asia. Particularly interesting is the fact that glaciers are in equilibrium or even gaining mass in the Karakoram and Kunlun Shan ranges, which is in sharp contrast with the negative mass balances in the rest of High Mountain Asia. To understand this difference, an in-depth understanding of the meteorological drivers of the glacier mass balance is required. In this study, two catchments in contrasting climatic regions, one in the central Himalaya (Langtang) and one in the Karakoram (Shimshal), are modeled at 1 km grid spacing with the numerical atmospheric model WRF for the period of 2011–2013. Our results show that the accumulation and melt dynamics of both regions differ due to contrasting meteorological conditions. In Shimshal, 92% of the annual precipitation falls in the form of snow, in contrast with 42% in Langtang. In addition, 80% of the total snow falls above an altitude of 5000 m a.s.l, compared with 35% in Langtang. Another prominent contrast is that most of the annual snowfall falls between December and May (71%), compared with 52% in Langtang. The melt regimes are also different, with 41% less energy available for melt in Shimshal. The melt in the Karakoram is controlled by net shortwave radiation (r = 0.79 ± 0.01) through the relatively low glacier albedo in summer, while net longwave radiation (clouds) dominates the energy balance in the Langtang region (r = 0.76 ± 0.02). High amounts of snowfall and low melt rates result in a simulated positive glacier surface mass balance in Shimshal (+0.31 ± 0.06 m w.e. year−1) for the study period, while little snowfall, and high melt rates lead to a negative mass balance in Langtang (−0.40 ± 0.09 m w.e. year−1). The melt in Shimshal is highly variable between years, and is especially sensitive to summer snow events that reset the surface albedo. We conclude that understanding glacier mass balance anomalies requires quantification and insight into subtle shifts in the energy balance and accumulation regimes at high altitude and that the sensitivity of glaciers to climate change is regionally variable.

Hydrological Responses of Headwater Basins to Monthly Perturbed Climate in the North American Cordillera

Abstract How mountain hydrology at different elevations will respond to climate change is a challenging question of great importance to assessing changing water resources. Here, three North American Cordilleran snow-dominated basins—Wolf Creek, Yukon; Marmot Creek, Alberta; and Reynolds Mountain East, Idaho—each with good meteorological and hydrological records, were modeled using the physically based, spatially distributed Cold Regions Hydrological Model. Model performance was verified using field observations and found adequate for diagnostic analysis. To diagnose the effects of future climate, the monthly temperature and precipitation changes projected for the future by 11 regional climate models for the mid-twenty-first century were added to the observed meteorological time series. The modeled future was warmer and wetter, increasing the rainfall fraction of precipitation and shifting all three basins toward rainfall–runoff hydrology. This shift was largest at lower elevations and in the relatively warmer Reynolds Mountain East. In the warmer future, there was decreased blowing snow transport, snow interception and sublimation, peak snow accumulation, and melt rates, and increased evapotranspiration and the duration of the snow-free season. Annual runoff in these basins did not change despite precipitation increases, warming, and an increased prominence of rainfall over snowfall. Reduced snow sublimation offset reduced snowfall amounts, and increased evapotranspiration offset increased rainfall amounts. The hydrological uncertainty due to variation among climate models was greater than the predicted hydrological changes. While the results of this study can be used to assess the vulnerability and resiliency of water resources that are dependent on mountain snow, stakeholders and water managers must make decisions under considerable uncertainty, which this paper illustrates.

Characteristics and simulation of snow interception by the canopy of primary spruce-fir Korean pine forests in the Xiaoxing'an Mountains of China.

Snow interception by the forest canopy is an important control on the forest hydrological cycle in the Xiaoxing'an Mountains within the northern temperate region of China. In this study, the effects of snowfall characteristics and stand structures on the snowfall redistribution of the canopies within primary spruce‐fir Korean pine forests are analyzed at the forest stand scale. Characteristics of snowfall, through‐canopy snowfall, and stand structure are continuously measured using positioning observations. A semiempirical theoretical model is used to conduct snow interception simulations in the Xiaoxing'an Mountain region. The results indicate that the snowfall, canopy density, slope gradient, and tree height have a significant effect on the through‐canopy snowfall. The interception efficiency gradually decreases with an increase in the amount of snowfall and is particularly sensitive to the snowfall and canopy density, although it shows no significant correlation with average diameter at breast height, tree height, basal area, canopy height, canopy width, leaf area, or slope gradient. Very similar results have been observed in Canada and Switzerland, suggesting the transferability of the results between North America, Western Europe, and China. However, although model results provide a satisfactory simulation of snow interception, further studies are required to optimize the model in this region.

Timber harvest jeopardize marten persistence in the heart of its range

Over the last decades, timber harvest has greatly reduced the quality of habitat for several species. To mitigate this problem, government authorities often try to support silvicultural practices that help forests recover faster to a natural state while supporting the economic development of forestry. The American marten is a carnivore species that is sensitive to forest disturbances, which is one of the main factors limiting its populations. For several years, trappers have warned that logging reduced the abundance of marten in several areas at the heart of its distribution. We used forest inventories and trapping effort on traplines collected by the Quebec government since 1970 to assess the relationship between habitat quality, capture success of marten and weather over a 25 years span in Quebec. Our results showed that the abundance of marten decreased, following the proportion of good quality habitat since 1990. Furthermore, we observed an increase in capture success with the amount of snowfall suggesting that marten are more numerous in habitats where snow is abundant as it gives them a competitive advantage over sympatric mesocarnivores such as fishers. Consequently, as climate models forecast less snow in the future, the negative effect of logging could be amplified for this species. Forest planning should consider marten needs and improve the quality and connectivity of habitats to ensure the persistence of the American marten with changing climate.

Climate change and finger millet: Perception, trend and impact on yield in different ecological regions in Central Nepal

The views of local people on climate change along different ecological regions are relatively unexplored in Nepal. This study was conducted in 13 villages in central Nepal at different altitudes to document the views of small holder farmers and compare their perception with trends of climatic variables, finger millet yield, natural disasters, plant phenology (flowering and fruiting), status of forest and wild life, as well as the spread of diseases and pests. Analysis on the climatic data of stations for 36–41 years between 1975 and 2016 showed significant increases in the minimum temperature in lower tropical climatic region (<500 m), upper tropical to subtropical climatic region (500–2000 m) and temperate climatic region (2000–3000 m) by 0.01, 0.026 and 0.054°C/year, respectively, and an increase of maximum temperature by 0.008, 0.018, and 0.019°C/year, respectively. Rainfall showed a strongly significant decreasing trend in all elevation regions. This result matches with the views of respondents except 38% respondent from temperate climatic region. People from the temperate climatic region also mentioned that current onset of snowfall is delayed but amount of snowfall remained the same. From the documented records, except events of wild fire, frequency of natural disasters events have increased in the recent years, which was in harmony with the views of local people. Multi-linear regression analysis showed that contribution of climatic variables on finger millet yield in lower tropical climatic region and upper tropical to subtropical regions was 23% and 57.3%, respectively, which was supported by increasing trend on average growing degree day (GDD) temperature at the rate of 0.01°C in upper tropical to subtropical region and 0.007°C in lower tropical climatic region yearly. Finger millet yield has been increasing at the rate of 7.39 and 36.9 kg/ha yearly in lower tropical climatic region and upper tropical to subtropical climatic region, respectively. This result provides deeper understanding of people’s perception of causes and effects of climate change on diverse variables along different elevation and related magnitude which can contribute to policy making in Nepal.

Contribution of snowfall from diverse synoptic conditions in the Catskill/Delaware Watershed of New York State.

Snowfall in the six basins of the Catskill/Delaware Watershed in south‐central New York State historically contributes roughly 20–30% of the water resources derived from the watershed for use in the New York City water supply. The watershed regularly experiences snowfall from three distinctive weather patterns: coastal mid‐latitude cyclones, overrunning systems, and lake‐effect or Great Lakes enhanced storms. Using synoptic weather classification techniques, these distinct regional atmospheric patterns impacting the watershed are isolated and analysed in conjunction with daily snowfall observations from 1960 to 2009 to allow the influence of each synoptic weather pattern on snowfall to be evaluated independently.Results indicate that snowfall‐producing events occur on average approximately 63 days/year, or once every 4 days during the October–May season, leading to an average of 213 cm/year of snowfall within the watershed. Snowfall from Great Lakes enhanced storms and overrunning systems contribute nearly equally to seasonal totals, representing 38 and 39%, respectively. Coastal mid‐latitude cyclones, while producing the highest amount of snowfall per event on average, contribute only 16% to the watershed average total snowfall. Predicted climate change is expected to impact snowfall differently depending on the specific atmospheric pattern producing the snow. As such, quantifying the contribution of snowfall to the watershed by synoptic pattern can inform future water management and reservoir operation practices for the New York City Water Supply Management System.

Probabilistic Forecasting of Snowfall Amounts Using a Hybrid between a Parametric and an Analog Approach

Abstract Forecast uncertainty associated with the prediction of snowfall amounts is a complex superposition of the uncertainty about precipitation amounts and the uncertainty about weather variables like temperature that influence the snow-forming process. In situations with heavy precipitation, parametric, regression-based postprocessing approaches often perform very well since they can extrapolate relations between forecast and observed precipitation amounts established with data from more common events. The complexity of the relation between temperature and snowfall amounts, on the other hand, makes nonparametric techniques like the analog method an attractive choice. In this article we show how these two different methodologies can be combined in a way that leverages the respective advantages. Predictive distributions of precipitation amounts are obtained using a heteroscedastic regression approach based on censored, shifted gamma distributions, and quantile forecasts derived from them are used together with ensemble forecasts of temperature to find analog dates where both quantities were similar. The observed snowfall amounts on these dates are then used to compose an ensemble that represents the uncertainty about future snowfall. We demonstrate this approach with reforecast data from the Global Ensemble Forecast System (GEFS) and snowfall analyses from the National Operational Hydrologic Remote Sensing Center (NOHRSC) over an area within the northeastern United States and an area within the U.S. mountain states.

An Investigation of Cold-Season Short-Wave Troughs in the Great Lakes Region and Their Concurrence with Lake-Effect Clouds

AbstractThe downwind shores of the Laurentian Great Lakes region often receive prolific amounts of lake-effect snowfall during the cold season (October–March). The location and intensity of this snowfall can be influenced by upper-tropospheric features such as short-wave troughs. A 7-yr cold-season climatology of 500-hPa short-wave troughs was developed for the Great Lakes region. A total of 607 short-wave troughs were identified, with an average of approximately 87 short waves per cold season. Five classes of short-wave troughs were identified on the basis of their movement through the Great Lakes region. This short-wave trough dataset was subsequently compared with the lake-effect cloud-band climatology created by N. F. Laird et al. in 2017 to determine how frequently short-wave troughs occurred concurrently with lake-effect cloud bands. Of the 607 short-wave troughs identified, 380 were concurrent with lake-effect clouds. Over 65% of these 380 short-wave troughs occurred with a lake-effect cloud band on at least four of the five Great Lakes. Short-wave troughs that rotated around the base of a long-wave trough were found to have the highest frequency of concurrence. In general, concurrence was most likely during the middle cold-season months. Further, Lake Michigan featured the highest number of concurrent events, and Lake Erie featured the fewest. It is evident that short-wave troughs are a ubiquitous feature near the Great Lakes during the cold season and have the potential to impart substantial impacts on lake-effect snowbands.

Dropstones in Lacustrine Sediments as a Record of Snow Avalanches—A Validation of the Proxy by Combining Satellite Imagery and Varve Chronology at Kenai Lake (South-Central Alaska)

Snow avalanches cause many fatalities every year and damage local economies worldwide. The present-day climate change affects the snowpack and, thus, the properties and frequency of snow avalanches. Reconstructing snow avalanche records can help us understand past variations in avalanche frequency and their relationship to climate change. Previous avalanche records have primarily been reconstructed using dendrochronology. Here, we investigate the potential of lake sediments to record snow avalanches by studying 27 &lt; 30-cm-long sediment cores from Kenai Lake, south-central Alaska. We use X-ray computed tomography (CT) to image post-1964 varves and to identify dropstones. We use two newly identified cryptotephras to update the existing varve chronology. Satellite imagery is used to understand the redistribution of sediments by ice floes over the lake, which helps to explain why some avalanches are not recorded. Finally, we compare the dropstone record with climate data to show that snow avalanche activity is related to high amounts of snowfall in periods of relatively warm or variable temperature conditions. We show, for the first time, a direct link between historical snow avalanches and dropstones preserved in lake sediments. Although the lacustrine varve record does not allow for the development of a complete annual reconstruction of the snow avalanche history in the Kenai Lake valley, our results suggest that it can be used for long-term decadal reconstructions of the snow-avalanche history, ideally in combination with similar records from lakes elsewhere in the region.

Intraspecific differences in spring leaf phenology in relation to tree size in temperate deciduous trees.

Spring leaf phenology strongly influences plant productivity in temperate deciduous forests. Many studies have detected earlier budburst and leaf maturation in smaller trees within species, and have discussed the adaptive significance of increasing carbon gain before canopy closure in small trees. However, some previous studies have found the opposite pattern, and the physiological and environmental bases for this discrepancy are incompletely understood. We investigated the spring leaf phenology of 11 deciduous species in a cool-temperate forest in Japan for 2 years with different amounts of snowfall, and also gathered data on the day of budburst from multiple studies to assess whether and how the timing of budburst is related to tree size, phylogeny, temperature and annual snowfall of study sites. We found that differences in the timing of budburst and leaf maturation between saplings (<1 m height) and short trees (1-10 m height) are larger than those between short trees and tall trees (>10 m height), resulting in non-linear relationships between timing and height in most species. Cumulative degree-days to the day of budburst were smaller in saplings than in tall trees, probably because saplings are selected to outcompete the other individuals/species to become established. Moreover, phylogenetic relatedness did not explain the difference in spring leaf phenology between saplings and tall trees in the literature survey. In addition, our literature survey showed that budburst occurred earlier in saplings of most species in sites with less snowfall, whereas budburst occurred earlier in tall trees at sites with heavy snowfall. These results suggest that the opposite patterns found in some studies may be due to (i) differences in the target size, as saplings show larger phenological discrepancies than short and tall trees, and (ii) the microclimate experienced by the tree, as sites with heavy snow show delayed sapling phenology.

Factors explaining the yearly changes in minimum bottom dissolved oxygen concentrations in Lake Biwa, a warm monomictic lake

Vertical profiles of dissolved oxygen (DO) and water temperature (WT) measured bi-monthly for 36 years (1980–2015) near the deepest part of a warm monomictic lake were analyzed with special reference to yearly minimum DO at bottom (DOmin). DOmin changed yearly (3.0 ± 1.2 mg l−1) and significant differences in DOmin were not observed between Period I (1980–1993; cooler and worse in water quality) and Period II (1994–2015; warmer and better in water quality). This unclear trend in DOmin was probably due to the offsetting influences between warming induced by global warming and oligotrophication attempted by local governments etc. for the study period. DOmin was positively correlated with disturbance time (timing of last cold water intrusion observed from Mar to Aug), which could be related to the start of DO depletion at bottom. Thus, the linear model using this parameter could predict yearly DOmin fairly well for the entire study period (r2 = 0.60). In addition, DOmin and time of disturbance were correlated negatively with water density at bottom in Jan and positively with water density equilibrated to air temperature (AT) in Mar. Higher lake water density after full depth mixing advances the disturbance time. In contrast, lower AT in Mar and/or higher density of influent water after Mar delays the time likely due to the larger amount of snowfall in the watershed. Further, DOmin was positively correlated with maximum wind velocity in Sep which probably induced the recovery of DO. Multiple-regression models to predict DOmin using these meteorological and water quality parameters were developed (r2 ≥ 0.38, worse performances than the model using disturbance time) to forecast future trends of DOmin through global warming and/or climate change. Significant influences of water or sediment oxygen demands on DOmin were not detected. We also discuss the applicability of the proposed models.