Decrease In Snow Water Equivalent Research Articles

Snow Water Equivalent Monitoring—A Review of Large-Scale Remote Sensing Applications

Snow plays a crucial role in the global water cycle, providing water to over 20% of the world’s population and serving as a vital component for flora, fauna, and climate regulation. Changes in snow patterns due to global warming have far-reaching impacts on water management, agriculture, and other economic sectors such as winter tourism. Additionally, they have implications for environmental stability, prompting migration and cultural shifts in snow-dependent communities. Accurate information on snow and its variables is, thus, essential for both scientific understanding and societal planning. This review explores the potential of remote sensing in monitoring snow water equivalent (SWE) on a large scale, analyzing 164 selected publications from 2000 to 2023. Categorized by methodology and content, the analysis reveals a growing interest in the topic, with a concentration of research in North America and China. Methodologically, there is a shift from passive microwave (PMW) inversion algorithms to artificial intelligence (AI), particularly the Random Forest (RF) and neural network (NN) approaches. A majority of studies integrate PMW data with auxiliary information, focusing thematically on remote sensing and snow research, with limited incorporation into broader environmental contexts. Long-term studies (>30 years) suggest a general decrease in SWE in the Northern Hemisphere, though regional and seasonal variations exist. Finally, the review suggests potential future SWE research directions such as addressing PMW data issues, downsampling for detailed analyses, conducting interdisciplinary studies, and incorporating forecasting to enable more widespread applications.

Snow conditions in northern Europe: the dynamics of interannual variability versus projected long-term change

Abstract. Simulations by the EURO-CORDEX (European branch of the Coordinated Regional Climate Downscaling Experiment) regional climate models indicate a widespread future decrease in snow water equivalent (SWE) in northern Europe. This concurs with the negative interannual correlation between SWE and winter temperature in the southern parts of the domain but not with the positive correlation observed further north and over the Scandinavian mountains. To better understand these similarities and differences, interannual variations and projected future changes in SWE are attributed to anomalies or changes in three factors: total precipitation, the snowfall fraction of precipitation and the fraction of accumulated snowfall that remains on the ground (the snow-on-ground fraction). In areas with relatively mild winter climate, the latter two terms govern both the long-term change and interannual variability, resulting in less snow with higher temperatures. In colder areas, however, interannual SWE variability is dominated by variations in total precipitation. Since total precipitation is positively correlated with temperature, more snow tends to accumulate in milder winters. Still, even in these areas, SWE is projected to decrease in the future due to the reduced snowfall and snow-on-ground fractions in response to higher temperatures. Although winter total precipitation is projected to increase, its increase is smaller than would be expected from the interannual covariation of temperature and precipitation and is therefore insufficient to compensate the lower snowfall and snow-on-ground fractions. Furthermore, interannual SWE variability in northern Europe in the simulated warmer future climate is increasingly governed by variations in the snowfall and snow-on-ground fractions and less by variations in total precipitation.

Are the effects of vegetation and soil changes as important as climate change impacts on hydrological processes?

Abstract. Hydrological processes are widely understood to be sensitive to changes in climate, but the effects of concomitant changes in vegetation and soils have seldom been considered in snow-dominated mountain basins. The response of mountain hydrology to vegetation/soil changes in the present and a future climate was modeled in three snowmelt-dominated mountain basins in the North American Cordillera. The models developed for each basin using the Cold Regions Hydrological Modeling platform employed current and expected changes to vegetation and soil parameters and were driven with recent and perturbed high-altitude meteorological observations. Monthly perturbations were calculated using the differences in outputs between the present- and a future-climate scenario from 11 regional climate models. In the three basins, future climate change alone decreased the modeled peak snow water equivalent (SWE) by 11 %–47 % and increased the modeled evapotranspiration by 14 %–20 %. However, including future changes in vegetation and soil for each basin changed or reversed these climate change outcomes. In Wolf Creek in the Yukon Territory, Canada, a statistically insignificant increase in SWE due to vegetation increase in the alpine zone was found to offset the statistically significant decrease in SWE due to climate change. In Marmot Creek in the Canadian Rockies, the increase in annual runoff due to the combined effect of soil and climate change was statistically significant, whereas their individual effects were not. In the relatively warmer Reynolds Mountain in Idaho, USA, vegetation change alone decreased the annual runoff volume by 8 %, but changes in soil, climate, or both did not affect runoff. At high elevations in Wolf and Marmot creeks, the model results indicated that vegetation/soil changes moderated the impact of climate change on peak SWE, the timing of peak SWE, evapotranspiration, and the annual runoff volume. However, at medium elevations, these changes intensified the impact of climate change, further decreasing peak SWE and sublimation. The hydrological impacts of changes in climate, vegetation, and soil in mountain environments were similar in magnitude but not consistent in direction for all biomes; in some combinations, this resulted in enhanced impacts at lower elevations and latitudes and moderated impacts at higher elevations and latitudes.

Modeling study of the impact of complex terrain on the surface energy and hydrology over the Tibetan Plateau

The long-term effects of complex terrain on solar energy distributions and surface hydrology over the Tibetan Plateau (TP) are investigated using the 4th version of the global Community Climate System Model (CCSM4) coupled with a 3-D radiative transfer (RT) parameterization. We examine the differences between the results from CCSM4 with the 3-D RT parameterization and the results from CCSM4 with the plane-parallel RT scheme. In January (winter), the net surface solar flux (FSNS) displays negative deviations over valleys and the north slopes of mountains, especially in the northern margin of the TP, as a result of the 3-D shadow effect. Positive deviations in FSNS in January are found over the south slopes of mountains and over mountain tops, where more solar flux is intercepted. The deviations in total cloud fraction and snow water equivalent (SWE) exhibit patterns opposite to that of FSNS. The SWE decreases due to the 3-D mountain effect in spring and the magnitude of this effect depends on the terrain elevations. The SWE is reduced by 1–17 mm over the TP in April, with the largest decrease in SWE at an elevation of 3.5–4.5 km. Negative deviations in precipitation are found throughout the year, except in May and December, and they follow the seasonal variations in the deviations in total cloud fraction. The total liquid runoff at 3.5–4.5 km elevation increases in April due to earlier (March) snowmelt caused by increased downward solar radiation. The possible deviations in surface energy and SWE over the TP, caused by plane-parallel assumption in most climate models may result in biases in the liquid runoff and the river water resources over the TP and downstream.

Monitoring snowbank processes and cornice fall avalanches with time-lapse photography

Time-lapse photography was employed to monitor a snowbank at 3640 m above sea level in the Uinta Mountains, Utah, USA. The snowbank forms against a 35-m high, east-facing escarpment and is nourished by wind redistribution of snow from an alpine plateau. The snowbank is capped by a large cornice, and its central core persists through the summer in most years. An automated, solar-powered digital camera was deployed between October 2016 and June 2017, and programmed to capture 5 photographs each day between 8:00 and 16:00, local time. Although cold temperatures affected the batteries during the winter, a total of 812 photographs were collected, for an overall average of 3.4 per day. These images were combined in an animation displaying the growth of the snowbank and associated cornice over the course of the winter. The debris fields resulting from nineteen cornice fall avalanches were noted in the sequence of photographs. Data collected at a nearby automated weather station reveal that 12 avalanches (between early December and early April) were preceded by significant increases in snow depth, snow water equivalent, and precipitation, with sustained windspeeds above the winter average. In contrast, six of the last seven events (between late April and early June) occurred in the absence of new snowfall, but were associated with rapid rises in temperature and notable decreases in snow water equivalent. The average interval between recorded avalanches is 10 days, with a maximum of 29 days and a minimum of 2 h. Recurrence intervals were shorter in December/January, in late March/early April, and in late April/early May. Only one avalanche occurred in the 56 days between 27 January and 24 March. Time-lapse photography is a powerful tool for monitoring nival processes.

Impacts of aerosols on seasonal precipitation and snowpack in California based on convection-permitting WRF-Chem simulations

Abstract. A version of the WRF-Chem model with fully coupled aerosol–meteorology–snowpack is employed to investigate the impacts of various aerosol sources on precipitation and snowpack in California. In particular, the impacts of locally emitted anthropogenic and dust aerosols, and aerosols transported from outside California are studied. We differentiate three pathways of aerosol effects: aerosol–radiation interaction (ARI), aerosol–snow interaction (ASI), and aerosol–cloud interaction (ACI). The convection-permitting model simulations show that precipitation, snow water equivalent (SWE), and surface air temperature averaged over the whole domain (34–42∘ N, 117–124∘ W, not including ocean points) are reduced when aerosols are included, therefore reducing large biases in these variables due to the absence of aerosol effects in the model. Aerosols affect California water resources through the warming of mountaintops and the reduction of precipitation; however, different aerosol sources play different roles in changing surface temperature, precipitation, and snowpack in California by means of various weights of the three pathways. ARI by all aerosols mainly cools the surface, leading to slightly increased SWE over the mountains. Locally emitted dust aerosols warm the surface of mountaintops through ASI, in which the reduced snow albedo associated with dusty snow leads to more surface absorption of solar radiation and reduced SWE. Transported aerosols and local anthropogenic aerosols play a dominant role in increasing nonprecipitating clouds but reducing precipitation through ACI, leading to reduced SWE and runoff on the Sierra Nevada, as well as the warming of mountaintops associated with decreased SWE and hence lower surface albedo. The average changes in surface temperature from October 2012 to June 2013 are about −0.19 and 0.22 K for the whole domain and over mountaintops, respectively. Overall, the averaged reduction during October to June is about 7 % for precipitation, 3 % for SWE, and 7 % for surface runoff for the whole domain, while the corresponding numbers are 12, 10, and 10 % for the mountaintops. The reduction in SWE is more significant in a dry year, with 9 % for the whole domain and 16 % for the mountaintops. The maximum reduction of ∼ 20 % in precipitation occurs in May and is associated with the maximum aerosol loading, leading to the largest decrease in SWE and surface runoff over that period. It is also found that dust aerosols can cause early snowmelt on the mountaintops and reduced surface runoff after April.

Changes in seasonal snow water equivalent distribution in High Mountain Asia (1987 to 2009).

Snow meltwaters account for most of the yearly water budgets of many catchments in High Mountain Asia (HMA). We examine trends in snow water equivalent (SWE) using passive microwave data (1987 to 2009). We find an overall decrease in SWE in HMA, despite regions of increased SWE in the Pamir, Kunlun Shan, Eastern Himalaya, and Eastern Tien Shan. Although the average decline in annual SWE across HMA (contributing area, 2641 × 103 km2) is low (average, -0.3%), annual SWE losses conceal distinct seasonal and spatial heterogeneities across the study region. For example, the Tien Shan has seen both strong increases in winter SWE and sharp declines in spring and summer SWE. In the majority of catchments, the most negative SWE trends are found in mid-elevation zones, which often correspond to the regions of highest snow-water storage and are somewhat distinct from glaciated areas. Negative changes in SWE storage in these mid-elevation zones have strong implications for downstream water availability.

Assimilation of snow cover and snow depth into a snow model to estimate snow water equivalent and snowmelt runoff in a Himalayan catchment

Abstract. Snow is an important component of water storage in the Himalayas. Previous snowmelt studies in the Himalayas have predominantly relied on remotely sensed snow cover. However, snow cover data provide no direct information on the actual amount of water stored in a snowpack, i.e., the snow water equivalent (SWE). Therefore, in this study remotely sensed snow cover was combined with in situ observations and a modified version of the seNorge snow model to estimate (climate sensitivity of) SWE and snowmelt runoff in the Langtang catchment in Nepal. Snow cover data from Landsat 8 and the MOD10A2 snow cover product were validated with in situ snow cover observations provided by surface temperature and snow depth measurements resulting in classification accuracies of 85.7 and 83.1 % respectively. Optimal model parameter values were obtained through data assimilation of MOD10A2 snow maps and snow depth measurements using an ensemble Kalman filter (EnKF). Independent validations of simulated snow depth and snow cover with observations show improvement after data assimilation compared to simulations without data assimilation. The approach of modeling snow depth in a Kalman filter framework allows for data-constrained estimation of snow depth rather than snow cover alone, and this has great potential for future studies in complex terrain, especially in the Himalayas. Climate sensitivity tests with the optimized snow model revealed that snowmelt runoff increases in winter and the early melt season (December to May) and decreases during the late melt season (June to September) as a result of the earlier onset of snowmelt due to increasing temperature. At high elevation a decrease in SWE due to higher air temperature is (partly) compensated by an increase in precipitation, which emphasizes the need for accurate predictions on the changes in the spatial distribution of precipitation along with changes in temperature.

Spatio-temporal snowmelt variability across the headwaters of the Southern Rocky Mountains

Understanding the rate of snowmelt helps inform how water stored as snow will transform into streamflow. Data from 87 snow telemetry (SNOTEL) stations across the Southern Rocky Mountains were used to estimate spatio-temporal melt factors. Decreases in snow water equivalent were correlated to temperature at these monitoring stations for eight half-month periods from early March through late June. Time explained 70% of the variance in the computed snow melt factors. A residual linear correlation model was used to explain subsequent spatial variability. Longitude, slope, and land cover type explained further variance. For evergreen trees, canopy density was relevant to find enhanced melt rates; while for all other land cover types, denoted as non-evergreen, lower melt rates were found at high elevation, high latitude and north facing slopes, denoting that in cold environments melting is less effective than in milder sites. A change in the temperature sensor about mid-way through the time series (1990 to 2013) created a discontinuity in the temperature dataset. An adjustment to the time series yield larger computed melt factors.

Future Climate Change Impacts on Snow and Water Resources of the Fraser River Basin, British Columbia

Abstract Changes in air temperature and precipitation can modify snowmelt-driven runoff in snowmelt-dominated regimes. This study focuses on climate change impacts on the snow hydrology of the Fraser River basin (FRB) of British Columbia (BC), Canada, using the Variable Infiltration Capacity model (VIC). Statistically downscaled forcing datasets based on 12 models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) are used to drive VIC for two 30-yr time periods, a historical baseline (1980–2009) and future projections (2040–69: 2050s), under representative concentration pathways (RCPs) 4.5 and 8.5. The ensemble-based VIC simulations reveal widespread and regionally coherent spatial changes in snowfall, snow water equivalent (SWE), and snow cover over the FRB by the 2050s. While the mean precipitation is projected to increase slightly, the fraction of precipitation falling as snow is projected to decrease by nearly 50% in the 2050s compared to the baseline. Snow accumulation and snow-covered area are projected to decline substantially across the FRB, particularly in the Rocky Mountains. Onset of springtime snowmelt in the 2050s is projected to be nearly 25 days earlier than historically, yielding more runoff in the winter and spring for the Fraser River at Hope, BC, and earlier recession to low-flow volumes in summer. The ratio of snowmelt contribution to runoff decreases by nearly 20% in the Stuart and Nautley subbasins of the FRB in the 2050s. The decrease in SWE and loss of snow cover is greater from low to midelevations than in high elevations, where temperatures remain sufficiently cold for precipitation to fall as snow.

Regional hydrologic response to climate change in the conterminous United States using high-resolution hydroclimate simulations

Despite the fact that Global Climate Model (GCM) outputs have been used to project hydrologic impacts of climate change using off-line hydrologic models for two decades, many of these efforts have been disjointed — applications or at least calibrations have been focused on individual river basins and using a few of the available GCMs. This study improves upon earlier attempts by systematically projecting hydrologic impacts for the entire conterminous United States (US), using outputs from ten GCMs from the latest Coupled Model Intercomparison Project phase 5 (CMIP5) archive, with seamless hydrologic model calibration and validation techniques to produce a spatially and temporally consistent set of current hydrologic projections. The Variable Infiltration Capacity (VIC) model was forced with ten-member ensemble projections of precipitation and air temperature that were dynamically downscaled using a regional climate model (RegCM4) and bias-corrected to 1/24° (~4km) grid resolution for the baseline (1966–2005) and future (2011–2050) periods under the Representative Concentration Pathway 8.5. Based on regional analysis, the VIC model projections indicate an increase in winter and spring total runoff due to increases in winter precipitation of up to 20% in most regions of the US. However, decreases in snow water equivalent (SWE) and snow-covered days will lead to significant decreases in summer runoff with more pronounced shifts in the time of occurrence of annual peak runoff projected over the eastern and western US. In contrast, the central US will experience year-round increases in total runoff, mostly associated with increases in both extreme high and low runoff. The projected hydrological changes described in this study have implications for various aspects of future water resource management, including water supply, flood and drought preparation, and reservoir operation.

Projected 21st century changes in snow water equivalent over Northern Hemisphere landmasses from the CMIP5 model ensemble

Abstract. Changes in snow water equivalent (SWE) over Northern Hemisphere (NH) landmasses are investigated for the early (2016–2035), middle (2046–2065) and late (2080–2099) 21st century using a multi-model ensemble from 20 global climate models from the Coupled Model Intercomparison Project Phase 5 (CMIP5). The multi-model ensemble was found to provide a realistic estimate of observed NH mean winter SWE compared to the GlobSnow product. The multi-model ensemble projects significant decreases in SWE over the 21st century for most regions of the NH for representative concentration pathways (RCPs) 2.6, 4.5 and 8.5. This decrease is particularly evident over the Tibetan Plateau and North America. The only region with projected increases is eastern Siberia. Projected reductions in mean annual SWE exhibit a latitudinal gradient with the largest relative changes over lower latitudes. SWE is projected to undergo the largest decreases in the spring period where it is most strongly negatively correlated with air temperature. The reduction in snowfall amount from warming is shown to be the main contributor to projected changes in SWE during September to May over the NH.

The Changing Face of Arctic Snow Cover: A Synthesis of Observed and Projected Changes

Analysis of in situ and satellite data shows evidence of different regional snow cover responses to the widespread warming and increasing winter precipitation that has characterized the Arctic climate for the past 40–50 years. The largest and most rapid decreases in snow water equivalent (SWE) and snow cover duration (SCD) are observed over maritime regions of the Arctic with the highest precipitation amounts. There is also evidence of marked differences in the response of snow cover between the North American and Eurasian sectors of the Arctic, with the North American sector exhibiting decreases in snow cover and snow depth over the entire period of available in situ observations from around 1950, while widespread decreases in snow cover are not apparent over Eurasia until after around 1980. However, snow depths are increasing in many regions of Eurasia. Warming and more frequent winter thaws are contributing to changes in snow pack structure with important implications for land use and provision of ecosystem services. Projected changes in snow cover from Global Climate Models for the 2050 period indicate increases in maximum SWE of up to 15% over much of the Arctic, with the largest increases (15–30%) over the Siberian sector. In contrast, SCD is projected to decrease by about 10–20% over much of the Arctic, with the smallest decreases over Siberia (<10%) and the largest decreases over Alaska and northern Scandinavia (30–40%) by 2050. These projected changes will have far-reaching consequences for the climate system, human activities, hydrology, and ecology.

Changes in Spring Snowpack for Selected Basins in the United States for Different Climate-Change Scenarios

Abstract Spring snowpack is an important water resource in many river basins in the United States in areas where snowmelt comprises a large part of the annual runoff. Increasing temperatures will likely reduce snowpacks in the future, resulting in more winter runoff and less available water during the summer low-flow season. As part of the National Climate Change Modeling Project by the U.S. Geological Survey, distributed watershed-model output was analyzed to characterize areal extent and water-equivalent volumes of spring snowpack for a warming climate. The output from seven selected watershed models from the mountainous western United States and one model from coastal Maine in the northeastern United States shows a future of declining spring snowpack. Snow-cover area (SCA) and snow-water equivalent (SWE) were used to compare the spring snowpack for current conditions (2006) with three time periods in the future (2030, 2060, and 2090) using three Intergovernmental Panel on Climate Change (IPCC) emission scenarios published in the 2007 Special Report on Emission Scenarios (SRES): A2, B1, and A1B. Distributed SWE and SCA values were sorted into elevation zones in each basin. The change in spring snowpack over time was greater than the change among different emission scenarios, suggesting that, even for a globally reduced carbon emission scenario, large decreases in SWE are likely to occur. The SRES A2 scenario resulted in the greatest decrease in SWE for six of the basins, and the SRES B1 and A1B scenarios resulted in the greatest decrease in one basin each.

Improvement of distributed snowmelt energy balance modeling with MODIS‐based NDSI‐derived fractional snow‐covered area data

AbstractDescribing the spatial variability of heterogeneous snowpacks at a watershed or mountain‐front scale is important for improvements in large‐scale snowmelt modelling. Snowmelt depletion curves, which relate fractional decreases in snow‐covered area (SCA) against normalized decreases in snow water equivalent (SWE), are a common approach to scale‐up snowmelt models. Unfortunately, the kinds of ground‐based observations that are used to develop depletion curves are expensive to gather and impractical for large areas. We describe an approach incorporating remotely sensed fractional SCA (FSCA) data with coinciding daily snowmelt SWE outputs during ablation to quantify the shape of a depletion curve. We joined melt estimates from the Utah Energy Balance Snow Accumulation and Melt Model (UEB) with FSCA data calculated from a normalized difference snow index snow algorithm using NASA's moderate resolution imaging spectroradiometer (MODIS) visible (0·545–0·565 µm) and shortwave infrared (1·628–1·652 µm) reflectance data. We tested the approach at three 500 m2 study sites, one in central Idaho and the other two on the North Slope in the Alaskan arctic. The UEB‐MODIS‐derived depletion curves were evaluated against depletion curves derived from ground‐based snow surveys. Comparisons showed strong agreement between the independent estimates. Copyright © 2010 John Wiley &amp; Sons, Ltd.

Spatial heterogeneity in snow water equivalent induced by forest canopy in a mixed beech–fir stand in the Pyrenees

AbstractThis paper analyzes the effect of forest canopy on snow water equivalent during two consecutive snow seasons in a mixed beech–fir stand in the Pyrenees. The results confirm that the forest canopy is a dominant influence on snowpack distribution during the accumulation and melting periods. In general, a noticeable decrease in snow water equivalent and an increase in variability among observations are detected with increasing density of the forest canopy. The influence of the forest canopy on melting rates is complex and highly dependent on the dominant climatic conditions. Similar conclusions are reached for both of the snow seasons for which measurements are available, but several differences are also recorded. This study highlights the important influence of climatic conditions observed during the snow season on the relationship between stand characteristics and snowpack dynamics.

Seasonal Cycle Shifts in Hydroclimatology over the Western United States

Abstract Analyses of streamflow, snow mass temperature, and precipitation in snowmelt-dominated river basins in the western United States indicate an advance in the timing of peak spring season flows over the past 50 years. Warm temperature spells in spring have occurred much earlier in recent years, which explains in part the trend in the timing of the spring peak flow. In addition, a decrease in snow water equivalent and a general increase in winter precipitation are evident for many stations in the western United States. It appears that in recent decades more of the precipitation is coming as rain rather than snow. The trends are strongest at lower elevations and in the Pacific Northwest region, where winter temperatures are closer to the melting point; it appears that in this region in particular, modest shifts in temperature are capable of forcing large shifts in basin hydrologic response. It is speculated that these trends could be potentially a manifestation of the general global warming trend in recent decades and also due to enhanced ENSO activity. The observed trends in hydroclimatology over the western United States can have significant impacts on water resources planning and management.

FOREST GROWTH IMPACT ON PEAK SNOW PACK MEASUREMENTS AT LONG TERM SNOW COURSES1

ABSTRACT: Snow course surveys in late winter provide stream‐flow forecasters with their best information for making water supply and flood forecasts for the subsequent spring and summer runoff period in mountainous regions of western North America. Snow survey data analyses are generally based on a 30‐year “normal” period. It is well documented that forest cover changes over time will affect snow accumulation on the ground within forests. This paper seeks to determine if forest cover changes over decades at long term snow courses decrease measured peak snow water equivalent (SWE) enough to affect runoff prediction. Annual peak SWE records were analyzed at four snow courses in two different forest types having at least 25 years of snowpack data to detect any decreases in SWE due to forest growth. No statistically significant decreases in annual peak SWE over time were found at any of these four snow courses. The wide range of annual winter precipitation and correspondingly highly variable peak snowpack accumulation, as well as many other weather and site variables, masked any minor trends in the data.