Amount Of Snowfall Research Articles

Comparison of Snowfall Variations over China Identified from Different Snowfall/Rainfall Discrimination Methods

Based on the snowfall observations at 836 surface weather stations in China and the Daily Surface Climate Variables of China version 3.0 dataset for 1961–2013, capability of five methods with different objective criteria for identifying wintertime snowfall is evaluated, to provide reference for application of these methods in snowfall/rainfall discrimination. Methods I, II, III, IV, and V use the daily average surface air temperature (Ta), wet-bulb temperature (Tw), dynamic threshold Tw, 0-cm ground temperature, and 700–850-hPa thickness, respectively, to identify the snowfall. The results show that the climatological distribution of snowfall can be well produced by Methods I, II, and III. Method IV underestimates the snowfall days in eastern Tibetan Plateau (ETP), and Method V cannot yield the actual large numbers of snowfall days and amounts. Accordingly, the linear trends of snowfall days estimated from Methods I, II, and III largely agree with the observations, while a discrepancy is found in the linear trend of snowfall amounts over southeastern China (SEC). For interannual and decadal variations of snowfall, Method V shows the worst performance. It is more reasonable to use Tw to distinguish snowfall from rainfall instead of Ta, 0-cm ground temperature, and 700–850-hPa thickness; and the reference thresholds of Tw in northeastern China (NEC), northwestern China (NWC), ETP, and SEC are −1.5, −1.5, −0.4, and −0.3°C, respectively. The above results are beneficial to identifying snowfall in short-term climate prediction.

Dynamical Downscaling for Southeast Alaska: Historical Climate and Future Projections

AbstractWarming temperatures across southeast Alaska are affecting the region’s energy and transportation sectors, marine ecosystems, and forest health. More frequent above-freezing temperatures lead a transition from snow- to rain-dominant precipitation regimes, accelerating glacial mass balance loss and a leading to a greater risk for warm-season drought. Southeast Alaska has steep topographical gradients, which necessitate the use of downscaled climate information to study historical and projected periods. This study used regional dynamical downscaling at 4-km spatial resolution with the Weather Research and Forecasting Model to assess historical (1981–2010) and projected (2031–60) climate states for southeast Alaska. These simulations were driven by one reanalysis (i.e., the Climate Forecast System Reanalysis) and two climate models (i.e., the Geophysical Fluid Dynamics Laboratory Climate Model, version 3, and the NCAR Community Climate System Model, version 4), which each included a historical simulation and a projected simulation. The future simulations used the representative concentration pathway 8.5 emissions scenario. Bias-corrected projections (2031–60 minus 1981–2010) indicated seasonal warming of 1°–3°C, increased precipitation during autumn (4%–12%) and winter (7%–12%), and decreased snowfall in all seasons (up to 60% in autumn). The average number of days annually with a minimum temperature below freezing dropped by more than 30. The average annual maximum consecutive 3-day precipitation amounts increased by 11%–16%, but analogous extreme snowfall amounts dropped by 5%–11%. The most substantial snow losses occurred at low-elevation and coastal locations; at many high elevations (e.g., above 1000 m), extreme snowfall amounts increased.

Evaluation and projection of snowfall changes in High Mountain Asia based on NASA’s NEX-GDDP high-resolution daily downscaled dataset

High Mountain Asia (HMA), which includes the Tibetan Plateau, Tienshan Mountains and surrounding region, has abundant snowfall and a long period of snow cover annually. The headwaters of many prominent Asian rivers depend in part on HMA meltwater. In this study, we evaluate projected changes in mean snowfall (Smean), snowfall days (Sd), and snowfall fraction (Sf) for the years 2070–2099 relative to 1976–2005, under the Representative Concentration Pathway 4.5 (RCP4.5) and 8.5 (RCP8.5) emission scenarios. An evaluation of the results shows that while NASA’s NEX-GDDP (National Aeronautics and Space Administration Earth Exchange Global Daily Downscaled Projections) high-resolution daily downscaled dataset can successfully capture the distribution of mean snowfall climatology, it has a strong bias for extreme snowfall indices. In general, the projected increase of temperature under RCP4.5 and RCP8.5—especially in winter—will result in a decrease in snowfall amount (−18.9%, −32.8%), fewer snowfall days (−29.6%, −47.3%), and less precipitation falling as snow (−26.7%, −42.3%). Furthermore, under high emission scenarios, rain-dominated regions are projected to expand 53.9%, while snow-dominated areas will only account for 17.9% of the entire HMA. Spatially, snowfall shows a more robust decline in eastern HMA (e.g. East Tienshan, East Kun Lun, Qilian, South and Eastern Tibet, and Hengduan) than in western HMA (e.g. Hissar Alay, Pamir, and Karakoram). This difference can be attributed to various environmental factors, such as climatology, elevation influences, and the unique seasonal recycle between the two regions.

An attempt to explain recent changes in European snowfall extremes

Abstract. The goal of this work is to investigate and explain recent changes in total and maximum yearly snowfall from daily data in light of current global warming or the interdecadal variability of atmospheric circulation. We focus on the period 1979–2018 and compare two different datasets: the ERA5 reanalysis data and the E-OBSv20.0 data, where snowfall is identified from rainfall by applying a threshold to temperature. We compute changes as differences from quantities computed for the periods 1999–2018 and 1979–1998. On the one hand, we show that the decline in average snowfall observed in almost all European regions is coherent with previous findings and can be linked to global warming. On the other hand, we observe contrasting changes in maxima and sometimes disagreement in the sign of changes in the two datasets. Coherent positive trends are found for a few countries in the Balkans. These have been investigated in details by looking at modifications in the atmospheric weather patterns as well as local thermodynamic factors concurring to large snowfall events. We link these changes to the stronger prevalence of Atlantic Ridge or blocking patterns associated with deeper cyclonic structures over the Adriatic and Tyrrhenian seas. These cyclones find warmer surfaces and large availability of humidity and convective available potential energy (CAPE), thus producing large snowfall amounts, enhanced by the Stau effect on the Balkan topography.

Rain-on-Snow events in Japan as projected by a large ensemble of regional climate simulations

Rain-on-Snow (ROS) events can cause severe snowmelt hazards such as river flooding, avalanches, and landslides that have significant impacts on various sectors. The influence of climate change on the frequency of ROS events in Japan was investigated using climate projections obtained from the Database for Policy Decision making for Future climate change (d4PDF). The projected future climate in the regional model simulations showed an increase in the ROS events over the mountainous areas in Hokuriku (Sea of Japan side of Central Japan) and Hokkaido (Northern Japan) regions, where a higher amount of snowfall will still occur in the future. Characteristics of ROS events such as rainfall, snowmelt, and related runoff were also enhanced in these regions. Self-organizing maps (SOMs) were applied using the surface atmospheric circulation data to determine the dominant ROS-related weather patterns (WPs) in the present and future climate. The SOMs showed that some WPs had a significant effect on the cause of the ROS events. The differences in the impacts of climate change between the WPs were evaluated to understand the future changes in runoff and snowmelt associated with ROS events. The SOM analysis suggests that the increase in the occurrence of ROS events and the resultant enhancement in their characteristics in the future-climate projection can be attributed to the changes in the dominant ROS-related WPs (from cyclonic to cold-surge type) corresponding to variations in the freezing point line. These findings can inform water hazard and water resource management plans that aim to withstand regional climate change.

Solidification effects of snowfall on sea-ice freeze-up: results from an onsite experimental study

AbstractAlthough the effects of snow during sea-ice growth have been investigated for sea ice which is thick enough to accommodate dry snow, those for thin sea ice have not been paid much attention due to the difficulty in observing them. Observations are complicated by the presence of slush and its subsequent freeze-up, and the surface heat budget might be sensitive to the additional ice thickness. An onsite short-term land fast sea-ice freeze-up experiment in the Saroma-ko Lagoon, Hokkaido, Japan was carried out to examine the effects of snowfall on the structure and surface heat budget of thin sea ice, based on observational results and a 1-D thermodynamic model. We found that snowfall contributes to the solidification of the surface slush layer, contributing ice thickness that is comparable to the snowfall amount and affecting the crystal texture significantly. On the other hand, the basal ice growth rate and turbulent heat flux were not significantly affected, being <3.1 × 10−8m s−1and 3 W m−2, respectively. This finding may validate the omission in past studies of snow effect in estimating ice production rates in polynyas and has implications about the reconstruction of growth history from sample analysis.

Warming shrivels future snowstorms

The influence of the changing climate on individual snowstorms has been uncertain, in part due to the use of coarse model simulations. Now, research employing more detailed simulations finds fewer and smaller snowstorms as a result of warming, with a reduction in the amount and extent of extreme snowfall.

Dynamic changes in snowfall extremes in the Songhua River Basin, Northeastern China

AbstractRainfall and snowfall differ greatly in terms of their effects on hydrological processes. Snowfall is usually regarded as snow water equivalent in studying precipitation extremes, without considering the difference between snowfall and rainfall. Although snowfall is a key indicator of global change, no generally accepted and no unified indices for the assessment of snowfall extremes currently exist. The objectives of this study are to identify a suite of extreme snowfall indices that can be used to describe extreme snowfall events, and to analyse the dynamic changes in the extreme snowfall indices that have occurred in the Songhua River Basin (SRB), China. The study employs a dataset that contains daily data from 60‐meteorological stations that cover a 55‐year period. The results include a suite of extreme snowfall indices that can be used to assess extreme snowfall events. These extreme snowfall indices include four comprehensive indices, four intensity indices, four grade indices and two date indices. The total snowfall, the number of snowfall days, the ratio of snowfall to total precipitation, the snowfall intensity (SNI), the amounts of extreme snowfall and very extreme snowfall display insignificant trends over the entire SRB. The changes in the ending snowfall date exhibit a significant advancing trend (p < .001), while the changes in beginning snowfall date display a significant delaying trend (p < .05), which have led to a reduced snowfall season length (p < .001). These results provide a series of reference indices in describing snowfall extremes and they can enhance our understanding of the variations in snowfall that occur under global warming.

Application of Bias- and Variance-Corrected SST on Wintertime Precipitation Simulation of Regional Climate Model over East Asian Region

In this study, the regional climate of East Asia was dynamically downscaled using Hadley Centre Global Environmental Model version 3-Regional Atmosphere (HadGEM3-RA) forced by the historical simulation data (1979–2005) of HadGEM2-AO produced by the National Institute of Meteorological Sciences (NIMS). To understand the impact of corrected SST on regional climate simulation, we integrated the experiments using uncorrected (UC_SST) and Bias- and Variance-corrected (BCVC_SST) HadGEM2-AO SST and used the simulated data driven by the ERA-Interim reanalysis data and HadGEM2-AO data. Examination of the spatial distribution, statistics, and interannual variation on wintertime precipitation over East Asia indicates that BCVC_SST reduced the overestimation of the climatological mean precipitation. In order to understand the impact of corrected SST on variability, we investigated the relationship between winter snowfall in South Korea and SST over East Asia. The negative correlation coefficient between the winter precipitation and the SST of the seas surrounding Korea appears in the result of observation data. The experiment result using BCVC_SST simulated the negative correlation between the winter snowfall and the SST around Korea more realistically than that of the simulations using UC_SST and HadGEM2-AO data. These results indicate that corrected SST helps to improve the variability of snowfall and SST simulated by HadGEM3-RA. However, time lag about the years when had peak point of SST appeared in the results compared between BCVC_SST experiment and observation data. The peak years shown in the result of the BCVC_SST experiment were similar to that of HadGEM2-AO data. At these results, even though the corrected SST improves climatological mean and variability of simulated data, it has the limitation not to overcome the error such as time lag showed in GCM SST. Additionally, the analysis of the snowfall in South Korea describes that SST is passively used for the source of snowfall and atmospheric variables mainly lead the intensity and the amount of snowfall.

Atmospheric Black Carbon and Surface Albedo in the Russian Arctic during Spring

We study the statistical relations between the black carbon (BC) content in the atmospheric column and the surface albedo (A), the values of which are available from MERRA-2 reanalysis data for four test areas near the Arctic coast of Russia in April 2010–2016. We also analyze the atmospheric meteorological parameters: air temperature and rainfall and snowfall amounts. The statistical analysis has been carried out using diurnally averaged parameters. An increase in the air temperature is accompanied everywhere by a decrease in the surface albedo, both on a monthly scale and in daily variations. Precipitation in the form of fresh snow increases the surface albedo. On the whole over 7 years, a significant negative correlation between BC and A in April was found in Nenets Autonomous okrug and on the Gydan Peninsula. Separate years (generally diverse for different areas) are revealed when day-to-day variations in A and BC correlate within a month, again with negative coefficients. We estimated possible albedo variations due to changes in different parameters, as well as variations in albedo radiative forcing.

Asymmetries in Snowfall, Emissivity, and Albedo of Mars' Seasonal Polar Caps: Mars Climate Sounder Observations

AbstractThe stability of the residual carbon dioxide cap near the south pole of Mars is currently not well understood. The cap's survival depends on its radiation budget, controlled by the visible albedo and infrared emissivity. We investigated the role of CO2 snowfall in altering the albedo and emissivity, leading to the observed asymmetry in the net CO2 accumulation at the two poles. Uncontaminated snowfall increases albedo, and lowers emissivity, due to scattering by optically thick clouds and granular surface deposits. Data from the Mars Climate Sounder (MCS) show that fall and winter snowfall is correlated with higher springtime albedo at both poles. For the seasonal CO2 deposits in each polar region >60° latitude, we find mean albedo values of 0.39 in the north and 0.51 in the south, and winter 32‐μm emissivity values of 0.84 in the north and 0.87 in the south. Using a radiative transfer model and the MCS data, we find that the north polar deposits have ∼10× higher dust content than those in the south, explaining the ∼31% lower albedo of the north seasonal cap during spring. Our model shows that greater amounts of snowfall can explain the ∼4% lower emissivity of the north polar seasonal cap. These findings demonstrate that winter snowfall and dust transport affect the composition of Mars' seasonal ice caps and polar energy balance. Snowfall and dust loading are therefore important in modeling the CO2 cycle on Mars, as well as the planet's long‐term climate variations.

An Examination of Physical Processes That Trigger the Albedo-Feedback on Glacier Surfaces and Implications for Regional Glacier Mass Balance Across High Mountain Asia

Due to their high sensitivity to changes in climate, glaciers are one of the best natural indicators of climate change. Despite this, many underlying processes that control glacier response to climate change are poorly understood. One potentially important set of such processes are feedback mechanisms that can amplify or dampen glacier melt in response to a change in climate. Though feedbacks are recognized as important processes affecting glacier mass balances, little has been done to systematically quantify their effects. This study develops a surface energy and mass balance model to quantify the contribution of the albedo-feedback to glacier mass balance. Specifically, we quantify the roles of three trigger processes that initiate the albedo-feedback: snowpack thickness, snowfall event frequency, and heat flux supplied by precipitation. The model follows common energy balance methods but includes “switches” to turn these trigger processes off. The model is applied to Chhota Shigri Glacier using meteorological inputs from three different climate regions in High Mountain Asia (HMA). The results show that up to 80% of the average glacier melt increase from a +1°C temperature change can be attributed to the albedo-feedback. Furthermore, the system gain due to the albedo-feedback depends most on snowfall event frequency and the availability of incoming shortwave radiation during the melt season, and are thus generally largest in summer accumulation settings of HMA. This sensitivity to snowfall timing and frequency results in system gains being highest near the equilibrium line altitude, where a small change in temperature can shift precipitation phase from snow to rain. Regional analysis using climatological estimates suggests that many glaciers in the monsoonal Himalayas and southern Tibetan Plateau are likely to exhibit particularly strong albedo feedbacks. These results contribute to a growing body of literature suggesting that the mass balance of summer-accumulation type glaciers is strongly controlled by summer snowfall amount and frequency, which is closely linked with changes in air temperature. It also highlights the significance of the albedo feedback on glacier mass balance and the need to further explore feedbacks associated with glacier surface processes.

The Role of Moisture Pathways on Snowfall Amount and Distribution in the Payette Mountains of Idaho

AbstractThe pathways air travels from the Pacific Ocean to the Intermountain West of the United States are important for understanding how air characteristics change and how this translates to the amount and distribution of snowfall. Recent studies have identified the most common moisture pathways in the Intermountain West, especially for heavy precipitation events. However, the role of moisture pathways on snowfall amount and distribution in specific regions remains unclear. Here, we investigate 24 precipitation events in the Payette Mountains of Idaho during January–March 2017 to understand how local atmospheric conditions are tied to three moisture pathways and how it impacts snowfall amount and distribution. During one pathway, southwesterly, moist, tropical air is directed into the Central Valley of California where the air is blocked by the Sierra Nevada, redirected northward and over lower terrain north of Lake Tahoe into the Snake River Plain of Idaho. Other pathways consist of unblocked flows that approach the coast of California from the southwest and then override the northern Sierra Nevada and southern Cascades, and zonal flows approaching the coast of Oregon overriding the Oregon Cascades. Air masses in the Payette Mountains of Idaho associated with Sierra-blocked flow were observed to be warmer, moister, and windier compared to the other moisture pathways. During Sierra-blocked flow, higher snowfall rates, in terms of mean reflectivity, were observed more uniformly distributed throughout the region compared to the other flows, which observed lower snowfall rates that were predominantly collocated with areas of higher terrain. Of the total estimated snowfall captured in this study, 67% was observed during Sierra-blocked flow.

Using Gravity Recovery and Climate Experiment data to derive corrections to precipitation data sets and improve modelled snow mass at high latitudes

Abstract. The amount of lying snow calculated by a land surface model depends in part on the amount of snowfall in the meteorological data that are used to drive the model. We show that commonly used data sets differ in the amount of snowfall, and more generally precipitation, over four large Arctic basins. An independent estimate of the cold-season precipitation is obtained by combining water balance information from the Gravity Recovery and Climate Experiment (GRACE) with estimates of evaporation and river discharge and is generally higher than that estimated by four commonly used meteorological data sets. We use the Joint UK Land Environment Simulator (JULES) land surface model to calculate the snow water equivalent (SWE) over the four basins. The modelled seasonal maximum SWE is 38 % less than observation-based estimates on average, and the modelled basin discharge is significantly underestimated, consistent with the lack of snowfall. We use the GRACE-derived estimate of precipitation to define per-basin scale factors that are applied to the driving data and increase the amount of cold-season precipitation by 28 % on average. In turn this increases the modelled seasonal maximum SWE by 30 %, although this is still underestimated compared to observations by 19 % on average. A correction for the undercatch of precipitation by gauges is compared with the the GRACE-derived correction. Undercatch correction increases the amount of cold-season precipitation by 23 % on average, which indicates that some, but not all, of the underestimation can be removed by implementing existing undercatch correction algorithms. However, even undercatch-corrected data sets contain less precipitation than the GRACE-derived estimate in some regions, and it is likely that there are other biases that are not currently accounted for in gridded meteorological data sets. This study shows that revised estimates of precipitation can lead to improved modelling of SWE, but much more modest improvements are found in modelled river discharge. By providing methods to better define the precipitation inputs to the system, the current study paves the way for subsequent work on key hydrological processes in high-latitude basins.

Snowfall, Temperature, and the Risk of Death From Myocardial Infarction: A Case-Crossover Study.

Previous research has associated snowfall with risk of myocardial infarction (MI). Most studies have been conducted in regions with harsh winters; it remains unclear whether snowfall is associated with risk of MI in regions with milder or more varied climates. A case-crossover design was used to investigate the association between snowfall and death from MI in British Columbia, Canada. Deaths from MI among British Columbia residents between October 15 and March 31 from 2009 to 2017 were identified. The day of each death from MI was treated as the case day, and each case day was matched to control days drawn from the same day of the week during the same month. Daily snowfall amount was assigned to case and control days at the residential address, using weather stations within 15 km of the residence and 100 m in elevation. In total, 3,300 MI case days were matched to 10,441 control days. Compared with days that had no snowfall, odds of death from MI increased 34% (95% confidence interval: 0%, 80%) on days with heavy snowfall (≥5 cm). In stratified analysis of deaths from MI as a function of both maximum temperature and snowfall, risk was significantly increased on snowfall days when the temperature was warmer.

Interview

Shamsodin Taheri Shamsodin Taheri, from the University of Quebec Outaouais, Canada, talks to us about his group's submission “Analysis of electrical behaviour of PV arrays covered with nonuniform snow” page 192. I am an Associate Professor of Electrical Engineering in the Department of Computer Science and Engineering at the Université du Québec en Outaouais (UQO). The expertise of my research group in the field of power energy has advanced our understanding of the performance of photovoltaic (PV) sources in cold-climate conditions. This research was inspired by the issues that PV plants in Canada experience during cold months. In recent years, we have collaborated with several industry partners, who own utility-scale PV plants, to evaluate the performance of their facilities. This ongoing research helps mitigate the technical challenges facing the integration of renewable energy sources into power grids in cold regions. PV systems have found different applications in cold areas for a long time, such as remote research facilities in the South and North Poles and space travelling. The majority of PV energy plants are presently installed in geographical cold locations with a considerable amount of snowfall every year. Furthermore, the solar energy industry is expanding competitively in cold climate regions. For example, in Canada, the installed capacity of solar PV grew from 95 MW to more than 2500 MW during 2009–2016. PV panel efficiency is not only influenced by PV technology, but environmental conditions can also influence their energy production. Accumulation of snow/ice decreases solar radiation reaching the PV panels, which results in a significant loss of power generation. Non-uniform snow accretion on PV panels often occurs due to ambient conditions such as wind, temperature variation, partial snow shedding and ground interference. This leads to power loss that is dependent on the configuration of the PV system. Owing to the increasing deployment of PV systems, there is a significant interest in optimal utilisation of PV potential in cold climate regions. A fundamental need for knowledge of the impact of nonuniform snow accretion on PV systems is therefore essential. This research has shown that the snow-covered PV panels can still produce a significant amount of energy depending on the pattern and depth of the snow accumulation. The portion of this energy that could be collected is decided by configuration of the PV array as well as the maximum power point tracking (MPPT) technique. Investigations concerning the effect of bypass diodes have shown that the PV string without bypass diodes generally experiences more power loss. In addition, the vertical and horizontal PV array layouts were tested to determine power loss due to nonuniform snow accretion. The horizontal PV array layout would be more effective in snowy climates. This work is helpful for PV system performance assessment, MPPT development and testing, power generation prediction, and proper arrangement of panels in cold regions. The accumulation of snow on PV modules weakens the intensity of incoming solar radiation and hence limits their ability to generate electricity during cold months. However, the true extent of such impact on the energy production of PV modules cannot be specified in a straightforward way, since it is not proportional to the snow-covered area. In some instances, snow covering only one cell can reduce the efficiency of a whole module by a noticeable amount. Snow is a complex phenomenon, and a quantitative characterisation of radiation transmittance through snow coverage requires knowledge of the physical properties of snow. In fact, the interaction of sunlight with snow to determine the influence of snow coverage on the PV modules is a challenge. This leads to changing the electrical characteristics of the PV array and producing multiple, local peaks on PV characteristics. Accurate modelling of the electric behaviour of PV modules and systems is a key element in improving system operation and efficiency. Hence, proper modelling approaches of the operation of PV generators under varying environmental conditions that improve their performance control and assist the design of PV converters and their MPPT controller have been achieved. Moreover, an appropriate tool has been proposed to determine the efficiency of PV farms under cold conditions. Furthermore, a high performance MPPT technique has been proposed to harvest the maximum energy of a PV array with multipeak characteristic under partial shading condition. Major progress must be made on the proper design and arrangement of PV arrays and power electronic interfaces, minimising the effects of snow on large-scale PV farms and the increasing the use of bifacial PV modules as a candidate for cold regions over the next ten years.

Hazard prediction and risk regionalization of snowstorms in northeast China

The hazard analysis of snowstorm disasters can provide a scientific understanding of their occurrence, development, and possible impact. Such knowledge can improve the efficiency of disaster alleviation efforts. The temporal and spatial distribution and variational patterns of snowfall amounts and the number of snowfall days in Northeast China in the future under different scenarios were analyzed. The analysis was based on the meteorological data for 2020–2099 under low and high radiative forcing scenarios (RCP4.5 (low emission) and RCP8.5 (high emission)) proposed by IPCC AR5 from the regional climate mode system in Northeast China. A snowstorm hazard index for Northeast China in the future was constructed. Under the RCP8.5 scenario, during 2020–2099 the snowfall amount and number of snowstorm days in Northeast China would be less than under the RCP4.5 scenario. The high emission mode mainly affects the snowfall amount and number of heavy and severe snowstorms, while no trend of snowfall amount or number of snowstorms increasing was observed with the increase in emissions. Under the future RCP4.5 and RCP8.5 scenarios, the spatial distribution characteristics of snowfall amount and number of snowfall days at all levels are similar, with the main characteristics being higher in the southeast and northwest regions and lower in the central region. Under the future RCP4.5 and RCP8.5 scenarios, the hazard indices of snowstorms in Northeast China have little difference; under the RCP4.5 scenario, the hazard index of snowstorms shows a decreasing trend, while under the RCP8.5 scenario, the hazard index shows an increasing trend. In addition, under the RCP4.5 and RCP8.5 scenarios, the spatial distributions of snowstorm hazards are similar, being highest in the southeast region and lowest in the central and western regions. Under the two scenarios, the areas of high-risk and light-risk regions would increase, while the area of low- and medium-risk regions would decrease. The risk of snowstorm hazards in the future is increasing in Northeast China.

Spring to summer nitrogen level in a brackish lake is higher in abundant snowmelt years: Correlation and causation.

Eutrophication is an issue of concern in many brackish lakes with an agricultural watershed. The amount of snowfall in snowy areas is anticipated to decline because of global climate change. The aim of this study was to assess the impact of changes in the inflow of snowmelt on the nutrient concentrations of a downstream brackish lake. In Lake Ogawara, a brackish lake in a snow-covered agricultural area of Japan, we examined the relationships between inflowing river discharge (D/C) during spring and total nitrogen (TN) and total phosphorus (TP) concentrations in the mixolimnion of the lake ([TNmix ] and [TPmix ], respectively) using 29yr of monitoring data. In addition, we assessed the causal relationship between the D/C and the lake nutrient concentrations. There was large year-to-year variation in D/C during April (D/CApr ), which accounted for 7-31% of the mixolimnion volume. Significant positive correlations were observed between D/CApr and [TNmix ] from the ensuing April to September. On an annual basis, 49% of the interannual variation of the mean [TNmix ] during the ensuing April to September was explained by the interannual variation of D/CApr . Therefore, D/CApr could be useful as a simple index to [TNmix ] in the ensuing spring to summer. It is notable that the relationships between D/CApr and [TNmix ] from April to September was indicated to be acausal by statistical causal inference. Common climate conditions that increase D/CApr (i.e., a cold winter with a high level of precipitation) were found to drive other biogeochemical processes that increased [TNmix ] during the ensuing spring to summer.

Future Projection of Extreme Heavy Snowfall Events With a 5‐km Large Ensemble Regional Climate Simulation

AbstractWe have recently experienced several heavy snowfall events, but still do not sufficiently understand how global warming will impact changes in local extreme snowfall events. The analysis relevant to the extreme events requires ensemble experiments with high‐resolution regional climate modeling. In this study, we use a large number of ensemble warming projections downscaled dynamically to 5‐km grids to examine the differences in distribution and mechanism in extreme snowfall events over Japan between present and future climates. Japan has two typical snowfall patterns, the winter monsoon and the south coast cyclone patterns. The domain‐averaged amount of extreme snowfall in the south coast cyclone pattern regions appear to decrease with the rise in temperatures. Meanwhile, the winter monsoon pattern regions showed little change as the increases in extreme snowfall in the mountainous areas are canceled out by the decrease in the coastal areas. Based on the existing mechanism of normal snowfall, the increase in mountain snow is caused by a temporary intensification of cold air outbreaks. The amount of the cold air blowing from Japan Sea clearly increases only during the days preceding the extreme snowfall event, and as the cold dry air obtains more latent heat over the ocean, the precipitable water vapor increases. The winter monsoon then transports this air over land where the intensification of precipitation results from orographic updraft. This sequence of processes beginning with cold air outbreaks may have a stronger control over extreme snowfall phenomena on the warmer field.

Linking Global Changes of Snowfall and Wet-Bulb Temperature

AbstractSnowfall is one of the primary drivers of the global cryosphere and is declining in many regions of the world with widespread hydrological and ecological consequences. Previous studies have shown that the probability of snowfall occurrence is well described by wet-bulb temperatures below 1°C (1.1°C) over land (ocean). Using this relationship, wet-bulb temperatures from three reanalysis products as well as multisatellite and reanalysis precipitation data are analyzed from 1979 to 2017 to study changes in potential snowfall areas, snowfall-to-rainfall transition latitude, snowfall amount, and snowfall-to-precipitation ratio (SPR). Results are presented at hemispheric scales, as well as for three Köppen–Geiger climate classes and four major mountainous regions including the Alps, the western United States, High Mountain Asia (HMA), and the Andes. In all reanalysis products, while changes in the wet-bulb temperature over the Southern Hemisphere are mostly insignificant, significant positive trends are observed over the Northern Hemisphere (NH). Significant reductions are observed in annual-mean potential snowfall areas over NH land (ocean) by 0.52 (0.34) million km2 decade−1 due to an increase of 0.34°C (0.35°C) decade−1 in wet-bulb temperature. The fastest retreat in NH transition latitudes is observed over Europe and central Asia at 0.7° and 0.45° decade−1. Among mountainous regions, the largest decline in potential snowfall areas is observed over the Alps at 3.64% decade−1 followed by the western United States at 2.81% and HMA at 1.85% decade−1. This maximum decrease over the Alps is associated with significant reductions in annual snowfall of 20 mm decade−1 and SPR of 2% decade−1.