Snow Flux Research Articles

Elucidation of spatiotemporal structures from high-resolution blowing-snow observations

Abstract. Systematic observations were conducted to investigate the spatiotemporal structures of blowing snow. Along a line perpendicular to the dominant wind direction on the lee side of a flat field, 15 snow particle counters (SPCs) and ultrasonic anemometers (USAs) were placed 1.5 m apart. Data were recorded at high frequencies of 100 kHz for SPCs and 1 kHz for USAs. The horizontal mass flux distributions, representing the spatiotemporal variability of blowing snow, exhibited non-uniformity in both time and space and manifested periodic changes akin to snow waves. Additionally, the presence of “snow snakes”, meandering near the snow surface, was observed. Quadrant analysis revealed predominant snow fluxes in quadrants Q1 (u′>0, w′>0) and Q4 (u′>0, w′<0). However, a more detailed parametric curve analysis indicated the existence of ejection events in Q2 (u′<0, w′>0) before snow waves and in front of snow snakes, shifting to Q1 and Q4 afterward, implying the consideration of both top-down and bottom-up mechanisms for burst sweep events.

Climate warming impacts on ringed seal breeding habitat in Svalbard

Global warming is occurring at an accelerated rate in the Arctic compared to other parts of the planet with sea-ice declines being among the most striking manifestations of Arctic climate-related changes. Impacts of ongoing Arctic environmental change have been documented for biota throughout marine ecosystems from protists to top predators. Ice-dependent species with specific habitat needs are particularly vulnerable to the ongoing changes. The ringed seal (Pusa hispida) is an ice-associated Arctic endemic species that gives birth and rests in snow caves built in drifts of snow over holes in the sea ice created and maintained by these seals. In this study we create a snow-on-sea-ice reproductive lair habitat model for ringed seals in the Svalbard Archipelago (Norway), a hot-spot of Arctic warming. We use SnowModel, a physics-based snow distribution and evolution simulation system, as the core for a lair habitat model. The model quantifies snow depth and blowing snow fluxes and also relates these variables to snow availability for seal lair habitat. This was accomplished by developing an ecologically informed snow variable that quantifies potential seal lair habitat availability as a function of blowing snow fluxes. Model simulations were performed for the period September 1987 – August 2021 (34 years) on a 500 m × 500 m grid using a daily time-step. Field observations of snow depth and gridded analyses of sea-ice concentration and near-surface (+10 m) atmospheric forcing (air temperature, relative humidity, precipitation, and wind speed and direction) were incorporated within the model simulations. The results show that both snow depth and potential seal lair habitat have been decreasing in Svalbard for the last two decades. If current trends continue, as expected, ringed seal lair habitat will cease to exist across much of the Svalbard Archipelago in the next decade, putting this important Arctic species at risk of regional extirpation.

Central Arctic Ocean surface–atmosphere exchange of CO2 and CH4 constrained by direct measurements

Abstract. The central Arctic Ocean (CAO) plays an important role in the global carbon cycle, but the current and future exchange of the climate-forcing trace gases methane (CH4) and carbon dioxide (CO2) between the CAO and the atmosphere is highly uncertain. In particular, there are very few observations of near-surface gas concentrations or direct air–sea CO2 flux estimates and no previously reported direct air–sea CH4 flux estimates from the CAO. Furthermore, the effect of sea ice on the exchange is not well understood. We present direct measurements of the air–sea flux of CH4 and CO2, as well as air–snow fluxes of CO2 in the summertime CAO north of 82.5∘ N from the Synoptic Arctic Survey (SAS) expedition carried out on the Swedish icebreaker Oden in 2021. Measurements of air–sea CH4 and CO2 flux were made using floating chambers deployed in leads accessed from sea ice and from the side of Oden, and air–snow fluxes were determined from chambers deployed on sea ice. Gas transfer velocities determined from fluxes and surface-water-dissolved gas concentrations exhibited a weaker wind speed dependence than existing parameterisations, with a median sea-ice lead gas transfer rate of 2.5 cm h−1 applicable over the observed 10 m wind speed range (1–11 m s−1). The average observed air–sea CO2 flux was −7.6 mmolm-2d-1, and the average air–snow CO2 flux was −1.1 mmolm-2d-1. Extrapolating these fluxes and the corresponding sea-ice concentrations gives an August and September flux for the CAO of −1.75 mmolm-2d-1, within the range of previous indirect estimates. The average observed air–sea CH4 flux of 3.5 µmolm-2d-1, accounting for sea-ice concentration, equates to an August and September CAO flux of 0.35 µmolm-2d-1, lower than previous estimates and implying that the CAO is a very small (≪ 1 %) contributor to the Arctic flux of CH4 to the atmosphere.

Snow accretion on a model train: Climate wind tunnel experiments

Snow and ice accumulation on the main parts of rolling stock can lead to malfunctions and safety issues. This paper presents the results of snow accretion tests conducted in a climate wind tunnel to investigate the icing process on a model train at various ambient temperatures. A simplified 2/3-scale EMU-320 high-speed Korean train model was used without electrical power or heat sources. Before testing, the snow flux and liquid water content of snow were measured to enable their use as input conditions in future simulations and to inform further analysis of the icing process. Both qualitative and quantitative data from the tests were analyzed, including photographs and snow density and thickness measurements. Snow accretion was broader at higher ambient temperatures, and snow accretion on the nose tended to be thicker further away from the stagnation point at higher temperatures. Snow accreted on all components of the bogie, and the thickest snow accretion on the wheels occurred at arc angles of 15–40° for cases of lower temperature while occurring at a larger angle at the highest temperature. The comprehensive data from these experiments is expected to support future analysis and development of anti-icing systems.

가열 표면의 착설량 추정에 관한 수치적 연구

In railway vehicles, snowpack on the bogies and underframe caused by the snow accretion can result in damage and performance degradation. To obtain reliable simulation results about snow accretion for railway vehicle, surface heat transfer should be considered. This paper shows how to predict the snow accretion on a heated surface by applying a model established on the basis of thermodynamic methodology to boundary conditions. The motion of the snow was described by adopting the Eulerian method which consists of continuity and momentum equations for snow concentration. The performance of this methodology was demonstrated by comparing the numerical and experimental results for wind tunnel testing of snow accumulation on heated surfaces. Result shows that it can be applied to various meteorological conditions of flow speed, air temperature as well as snow flux.

Wind tunnel experiment and thermodynamic modeling for dry-snow accretion on a heated surface

Wind tunnel experiments and modeling of dry-snow accretion on a heated surface were performed to estimate the characteristics of dry-snow accretion occurring in sub-freezing temperatures by using cold-climate facilities. The experiments encompassed a wide range of meteorological conditions—air temperature, wind speed, and snow flux—and were conducted over a surface heat flux range of 300–1800 W/m2. The measurements were performed with respect to the snow properties, including growth rate, sticking efficiency, and liquid water content (LWC), and were used to analyze the impact of dry-snow accretion on a heated surface. The experimental results demonstrated the distinct influence of the surface heat flux on the snow accretion process. The sticking efficiency was found to highly correlate with the LWC of the accreted snow and meteorological parameters, and the accreted snow layer was shed from the surfaces when the LWC was slightly above 40%. Moreover, on the basis of heat and mass transfer during the accretion process, models for estimating sticking efficiency and LWC were developed for dry-snow accretion on a heated surface. The effects of convective cooling and evaporation of liquid water inside the accreted snow were incorporated, and the models were cross-validated with the experimental results. The equation was applied to the determination of the minimum value for sticking efficiency, and a linear proportional relation between sticking efficiency and meteorological parameters was demonstrated.

<b>Method for Estimating Snow Accretion on Shinkansen Bogies using Weather Data</b>

Shinkansen trains operating in snowy areas accumulate snow on their bogies, which can sometimes lead to damage to ground facilities. To prevent this type of damage, snow is removed from trains in stations. We developed a method to estimate the amount of snow accretion on bogies: first, snow density on the railway track is estimated using weather data, then, flying up snow flux is estimated. This is then used to predict the accumulated snow amount under the bogies. Our research confirmed that snow accretion under a bogie upon arrival at a station can be estimated to within 3 cm.

An empirical model of snowdrift based on field measurements: Profiles of the snow particle size and mass flux

Snowdrift often occurs in cold regions due to the combination of wind and snowfall. The drift formation and movement processes are complex due to the mixture of air, snow and sometimes water as well as the interaction of the temperature, humidity, pressure and flow. To better understand the relevant motion of blowing snow and the vertical snow distribution at an open terrain, the present study creates an empirical model of blowing snow, with the snow particle size and snow flux profile obtained by field measurements in Xinjiang autonomous region in northwest China. Based on the current data, we summarize and analyze the snow particle size probability distribution, the mean equivalent diameter profile and the snow mass flux profile in drifting snow. The results show that the probability distribution of the equivalent diameter of different snow particles (e.g., new snow, deposited snow, and blowing snow) follows the gamma distribution, and these parameters significantly vary for different types of snow particles. The mean equivalent diameter and mass flux of blowing snow considerably decrease with height. The friction velocity is an important factor that affects the profiles of the snow particle size and snow mass flux. The empirical model of the distribution of the particle diameter and mass flux proposed in the present study considering the friction velocity agrees well with field measurements.

Linking rain into ice microphysics across the melting layer in stratiform rain: a closure study

Abstract. This study investigates the link between rain and ice microphysics across the melting layer in stratiform rain systems using measurements from vertically pointing multi-frequency Doppler radars. A novel methodology to examine the variability of the precipitation rate and the mass-weighted melted diameter (Dm) across the melting region is proposed and applied to a 6 h long case study, observed during the TRIPEx-pol field campaign at the Jülich Observatory for Cloud Evolution Core Facility and covering a gamut of ice microphysical processes. The methodology is based on an optimal estimation (OE) retrieval of particle size distributions (PSDs) and dynamics (turbulence and vertical motions) from observed multi-frequency radar Doppler spectra applied both above and below the melting layer. First, the retrieval is applied in the rain region; based on a one-to-one conversion of raindrops into snowflakes, the retrieved drop size distributions (DSDs) are propagated upward to provide the mass-flux-preserving PSDs of snow. These ice PSDs are used to simulate radar reflectivities above the melting layer for different snow models and they are evaluated for a consistency with the actual radar measurements. Second, the OE snow retrieval where Doppler spectra are simulated based on different snow models, which consistently compute fall speeds and electromagnetic properties, is performed. The results corresponding to the best-matching models are then used to estimate snow fluxes and Dm, which are directly compared to the corresponding rain quantities. For the case study, the total accumulation of rain (2.30 mm) and the melted equivalent accumulation of snow (1.93 mm) show a 19 % difference. The analysis suggests that the mass flux through the melting zone is well preserved except the periods of intense riming where the precipitation rates were higher in rain than in the ice above. This is potentially due to additional condensation within the melting zone in correspondence to high relative humidity and collision and coalescence with the cloud droplets whose occurrence is ubiquitous with riming. It is shown that the mean mass-weighted diameter of ice is strongly related to the characteristic size of the underlying rain except the period of extreme aggregation where breakup of melting snowflakes significantly reduces Dm. The proposed methodology can be applied to long-term observations to advance our knowledge of the processes occurring across the melting region; this can then be used to improve assumptions underpinning spaceborne radar precipitation retrievals.

Snowdrift Landscape Patterns: An Arctic Investigation

AbstractBetween 2012 and 2018 we mapped near‐peak seasonal snow depths across two swaths covering 126 km2 in Northern Alaska using aerial structure‐from‐motion photogrammetry and lidar surveys. The surveys were validated by over a hundred thousand ground‐based depth measurements. Using a quantitative method for identifying drift areas, we conducted a snowdrift census that showed on average 18% of the study area is covered by snowdrifts each winter, with 40% of the snow‐water‐equivalent contained in the drifts. Within the census we identified six types of drifts, some of which fill each winter, others which do not. The seasonal drift evolution was distinctly different in the two swaths, a result largely explained by topographic differences. Using four metrics from the field of image quality analysis, we tested the year‐to‐year fidelity of these drift patterns, finding overall high year‐to‐year similarity, but with higher similarity values for filling drifts, and higher similarity values in one swath versus the other, again a function of the topography. These high drift fidelity values are best explained by climatically convergent winter‐cumulative windblown snow fluxes interacting with drift traps to produce the same drifts year after year. However, due to the existence of filling versus nonfilling drifts, and a predicted increasing frequency of rain‐on‐snow events in the Arctic, future snowdrift patterns and drift evolution pathways in the Arctic could diverge from those of today, with direct hydrologic impacts.

Evaluation for characteristics of wet snow accretion on transmission lines - Establishment of an experimental method using a vertical plate

It is of primary importance to decrease risks of snow damages on electric transmission lines to ensure a stable supply of electricity. For the acquisition of reliable data to clarify characteristics of snow accreted on a transmission line, it is effective to conduct an indoor experiment. The present report describes an experimental method for snow accretion on a vertical plate by using a wind tunnel including measurements of snow properties such as snow density and liquid water content, which can be extended to measure a shear adhesive stress of accreted snow. These measurements are systematically applied to different conditions of the wind speed, the air temperature, as well as the snow flux particularly focusing on wet snow accretion. Based on measurement data, the influence of the wind speed, the air temperature, and the snow flux on the snow density and the liquid water content is investigated. The analysis is further extended to include a parametric evaluation of the snow density and the liquid water content to examine their dependency on atmospheric parameters. As a result of analytical considerations of the consolidation effect by wind and melting of snow by heat exchanges, equations to estimate the snow density and the liquid water content by the wind speed, the air temperature, as well as the accreted snow mass are derived. The experimental results validate these equations, which enable the acquisition of desired snow properties by adjusting experimental parameters. The successful evaluation of snow properties in the presented experiments can substantially contribute to the establishment of practical data-set for further investigations to characterize wet snow accretion.

Rates of rockwall slope erosion in the upper Bhagirathi catchment, Garhwal Himalaya

ABSTRACTRockwall slope erosion is defined for the upper Bhagirathi catchment using cosmogenic Beryllium‐10 (10Be) concentrations in sediment from medial moraines on Gangotri glacier. Beryllium‐10 concentrations range from 1.1 ± 0.2 to 2.7 ± 0.3 × 104 at/g SiO2, yielding rockwall slope erosion rates from 2.4 ± 0.4 to 6.9 ± 1.9 mm/a. Slope erosion rates are likely to have varied over space and time and responded to shifts in climate, geomorphic and/or tectonic regime throughout the late Quaternary. Geomorphic and sedimentological analyses confirm that the moraines are predominately composed of rockfall and avalanche debris mobilized from steep relief rockwall slopes via periglacial weathering processes. The glacial rockwall slope erosion affects sediment flux and storage of snow and ice at the catchment head on diurnal to millennial timescales, and more broadly influences catchment configuration and relief, glacier dynamics and microclimates. The slope erosion rates exceed the averaged catchment‐wide and exhumation rates of Bhagirathi and the Garhwal region on geomorphic timescales (103−105 years), supporting the view that erosion at the headwaters can outpace the wider catchment. The 10Be concentrations of medial moraine sediment for the upper Bhagirathi catchment and the catchments of Chhota Shigri in Lahul, northern India and Baltoro glacier in Central Karakoram, Pakistan show a tentative relationship between 10Be concentration and precipitation. As such there is more rapid glacial rockwall slope erosion in the monsoon‐influenced Lesser and Greater Himalaya compared to the semi‐arid interior of the orogen. Rockwall slope erosion in the three study areas, and more broadly across the northwest Himalaya is likely governed by individual catchment dynamics that vary across space and time. © 2019 The Authors. Earth Surface Processes and Landforms Published by John Wiley & Sons, Ltd.

Hydrometeor Lofting and Mesoscale Snowbands

Abstract Environments that accompany mesoscale snowbands in extratropical cyclones feature strong midlevel frontogenesis and weak symmetric stability, conditions conducive to vigorous ascent. Prior observational and numerical studies document the occurrence of upward vertical velocities in excess of 1 m s−1 near the comma head of winter cyclones. These values roughly correspond to the terminal fall velocity of snow; snow lofting has been measured directly with vertically pointing radars. Here, we investigate the occurrence of lower-tropospheric snow lofting near mesoscale bands and its contribution to snowfall heterogeneity. We test the hypothesis that hydrometeor lofting substantially influences snowfall distributions by analyzing the vertical snow flux in case-study simulations, by computing snow trajectories, and by testing sensitivity of simulated snowbands to parameterized snow terminal fall velocity and advection. These experiments confirm the presence of upward snow flux in the lower troposphere upstream of simulated mesoscale snowbands for two events (27 January 2015 and 2 February 2016). The band of lower-tropospheric lofting played a more important role in the January 2015 case relative to the February 2016 event. Lofting enhances the horizontal advection of snow by increasing hydrometeor residence time aloft, influencing the surface snowfall distribution. Experimental simulations illustrate that while lofting and advection influence the snow distribution, these processes reduce snowfall heterogeneity, contrary to our initial hypothesis. Our findings indicate that considerable horizontal displacement can occur between the locations of strongest ascent and heaviest surface snowfall. Numerical forecasts of snowbands are sensitive to formulations of terminal fall velocity of snow in microphysical parameterizations due to this lofting and transport process.

The Role of Melting Snow in the Ocean Surface Heat Budget

AbstractWe estimate the cooling flux from snow melting in the ocean through CloudSat satellite snowfall retrievals and reanalysis data. For snowfall events with less than 0.01 mm/hr, this flux is inconsequential. Melting snow begins to compete with other ocean surface heat fluxes as snowfall rates increase beyond 0.1 mm/hr, and it may often become the dominant heat flux as snowfall rates approach and exceed 1 mm/hr. The largest monthly average values of the melting snow cooling flux occur in winter months, approaching −10 W/m2 in both hemispheres. To determine the regional influence of melting snow on a seasonal basis, we calculate an impact metric that gauges the cooling flux of melting snow against the net flux in the ocean. This metric can be between 20% and 30% in the Northern Hemisphere during March, April, May; the Southern Ocean during March, April, May and September, October, November; and in high‐latitude polar oceans during sea ice freeze up seasons.

Merging a terrain-based parameter with blowing snow fluxes for assessing snow redistribution in alpine terrain

Wind and the associated snow transport are dominating factors determining the snow distribution and accumulation in alpine areas. These factors result in a high spatial variability of snow heights that is difficult to quantify. In this study, we propose an efficient method for estimations of changes in snow heights during blowing snow events. We merge a terrain-based parameter Sx, which characterizes the degree of shelter or exposure of a point provided by the upwind terrain, with estimations of quantity of snow transported by the wind. This estimation is provided by snow particle counters (SPC) that estimate the snow flux, the mass of drifting snow particles per time and area. A modified terrain-based parameter Sxm is then used to distribute snow over the terrain. The results are compared with measured changes in snow heights resulting from blowing snow events, obtained with terrestrial laser scanning (TLS). Data and results are from the Col du Lac Blanc research site in the French Alps. We use a high raster resolution of 1 m, which is required when assessing the snow-redistribution situation in highly structured terrain or in the starting zones of small and medium-sized avalanches. Results show that the proposed method can estimate snow distributions based on a modified terrain parameter Sxm and measured snow flux data. It can reproduce patterns of snow redistribution and estimate changes in snow heights reasonably well, as shown by correlation coefficients (R) of 0.78 to 0.86. The derivation of the modified terrain parameter Sxm and snow flux are specific to the research site and not yet generally applicable. The formulations require the calibration and alteration of two parameters only for use in studies with other terrain and weather characteristics.

Operational implementation and evaluation of a blowing snow scheme for avalanche hazard forecasting

In alpine terrain, blowing snow events strongly affect the local evolution of the avalanche danger and must be taken into account by avalanche hazard forecasters. This study presents the implementation and the evaluation of the blowing snow scheme Sytron into the operational chain for avalanche hazard forecasting (named S2M) used in the main French mountain ranges. S2M-Sytron provides information on blowing snow occurrence and intensity per 300-m elevation bands and aspects for several regions of the French mountains. The wind forcing is provided by the meteorological analysis system SAFRAN. S2M-Sytron was evaluated for winter 2015/16 at 11 automatic stations measuring wind speed and blowing snow fluxes in the French Alps. The system detects 55% of blowing snow days with less than 10% of false alarms. S2M-Sytron captures the occurrence of blowing snow events with and without concurrent snowfall. Improvements are obtained when considering an updated parameterization for the properties of falling snow which reduces the threshold velocity for freshly fallen snow. Using observed wind speed instead of SAFRAN wind speed to drive Sytron shows further improvements at stations where SAFRAN wind speed differs from the observations due to local topographic features. Overall, S2M-Sytron provides a regional blowing snow assessment but cannot fully reproduce the local intensity of blowing snow events.

Characterization and flux of marine oil snow settling toward the seafloor in the northern Gulf of Mexico during the Deepwater Horizon incident: Evidence for input from surface oil and impact on shallow shelf sediments

Sediment trap samples from the shelf edge area (400-450m water depth), 58km northeast of the failed Macondo well, were collected before, during and after the Deepwater Horizon oil spill. Detailed chemical analyses of particulates revealed that fluxes of spill-derived TPH (2356μg/m2/day), total PAH (5.4μg/m2/day), and hopane (0.89μg/m2/day) settling to the seafloor directly beneath the surface-plume were 19- to 44-times higher during the active spill than pre- and post-spill background values. The oil was variably biodegraded, evaporated and photo-oxidized indicating that it derived from the sinking of surface oil. The hopane-based oil flux that we calculate (10bbl/km2) indicates that at least 76,000bbl of Macondo oil that reached the ocean surface subsequently sank over an area of approximately 7600km2. We explore how this flux of sunken surface oil contributed to the total volume of oil deposited on the seafloor following the Deepwater Horizon incident.

A New Formula for Estimating the Threshold Wind Speed for Snow Movement

AbstractThreshold wind speed for snow movement is one of the most important parameters describing the wind‐transport snow process. A majority of previous studies used empirical and constant threshold wind speeds while the variations of atmosphere condition and snow age seem to greatly affect the snow settlement process. This study tested the hypothesis that the threshold wind speed for snow transport increases as deposition time passed since last snowfall by introducing a new formula of the threshold wind speed for snow movement. It was theoretically derived based on the sintering process modeling and the moment balance of a snow particle. Through this formula, the influences of snow particle size, temperature, and deposition time on the threshold wind speed were explicitly taken into consideration. However, two empirical parameters in the sintering process modeling remained in the new formula, and they were determined by a calibration‐validation procedure using the field observed snow flux data. The snow flux and meteorological data collected at the ISAW stations (http://www.iav.ch) including large number of snow transport events during five winter seasons were used to test this formula. It was shown that the new formula qualitatively described the threshold wind speed required for the incipient motion of snow under various conditions in the natural environment of the Alps.

High‐Resolution Large Eddy Simulation of Snow Accumulation in Alpine Terrain

AbstractSnow accumulation in alpine terrain is controlled by three main processes that act at different spatial scales: (i) orographic snowfall, (ii) preferential deposition of snowfall, and (iii) wind‐induced snow transport of deposited snow. The relative importance of these processes largely remains uncertain at small scale (10–100 m). This study presents how high‐resolution coupled snowpack/atmosphere simulations help quantifying the effects of these processes. The simulation system consists of the detailed snowpack model Crocus and the atmospheric model Meso‐NH used in Large Eddy Simulation mode. Dedicated routines allow the coupled system to explicitly simulate wind‐induced snow transport. Our case study is a snowfall event that occurred in February 2011 in the French Alps. Three nested domains at 450, 150 and 50 m grid spacing allow the model to simulate the complex 3D precipitation and wind fields down to fine scale. We firstly assess the ability of the coupled model to reproduce meteorological conditions during the event (wind speed and direction, snowfall amount, and blowing snow fluxes). The spatial variability of snowfall and snow accumulation is then considered. At 50 m grid spacing, snowfall presents local maxima associated with the formation of rimed snow aggregates and graupel in regions of sustained updrafts. Variograms show that the resultant spatial variability of snowfall is lower than the variability of snow accumulation when considering snow transport. Despite an overestimation of simulated blowing fluxes, our results suggest that wind‐induced snow transport is the main source of spatial variability of snow accumulation in our case study.

Hydrological Modelling and data assimilation of Satellite Snow Cover Area using a Land Surface Model, VIC

The snow cover plays an important role in Himalayan region as it contributes a useful amount to the river discharge. So, besides estimating rainfall runoff, proper assessment of snowmelt runoff for efficient management and water resources planning is also required. A Land Surface Model, VIC (Variable Infiltration Capacity) is used at a high resolution grid size of 1 km. Beas river basin up to Thalot in North West Himalayas (NWH) have been selected as the study area. At first model setup is done and VIC has been run in its energy balance mode. The fluxes obtained from VIC has been routed to simulate the discharge for the time period of (2003-2006). Data Assimilation is done for the year 2006 and the techniques of Data Assimilation considered in this study are Direct Insertion (D.I) and Ensemble Kalman Filter (EnKF) that uses observations of snow covered area (SCA) to update hydrologic model states. The meteorological forcings were taken from 0.5 deg. resolution VIC global forcing data from 1979-2006 with daily maximum temperature, minimum temperature from Climate Research unit (CRU), rainfall from daily variability of NCEP and wind speed from NCEP-NCAR analysis as main inputs and Indian Meteorological Department (IMD) data of 0.25 °. NBSSLUP soil map and land use land cover map of ISRO-GBP project for year 2014 were used for generating the soil parameters and vegetation parameters respectively. The threshold temperature i.e. the minimum rain temperature is -0.5°C and maximum snow temperature is about +0.5°C at which VIC can generate snow fluxes. Hydrological simulations were done using both NCEP and IMD based meteorological Forcing datasets, but very few snow fluxes were obtained using IMD data met forcing, whereas NCEP based met forcing has given significantly better snow fluxes throughout the simulation years as the temperature resolution as given by IMD data is 0.5°C and rainfall resolution of 0.25°C. The simulated discharge has been validated using observed data from BBMB (Bhakra Beas Management Board) and coefficient of Correlation(R<sup>2</sup>) measured for (2003-2006) was 0.67 and 0.61 for the year 2006.But as VIC does not consider snowmelt runoff as a part of the total discharge, snowmelt runoff has been estimated for the simulation both with and without D.A. The snow fluxes as generated from VIC gives basin average estimates of Snow Cover, SWE, Snow Depth and Snow melt. It has been observed to be overestimated when model predicted snow cover is compared with MODIS SCA of 500 m resolution from MOD10A2 for each year. So MODIS 8-day snow cover area has been assimilated directly into the model state as well as by using EnKF after every 8 days for the year 2006.D.I Technique performed well as compared to EnKF. R<sup>2</sup> between Model SCA and MODIS SCA is estimated as 0.73 after D.I with Root Mean Square Error (RMSE) of +0.19. After direct Insertion of D.A, SCA has been reduced comparatively which resulted in 7% reduction of annual snowmelt contribution to total discharge.The assimilation of MODIS SCA data hence improved the snow cover area (SCA) fraction and finally updated other snow components.