Testing Snow Melt Algorithms in High Relief Topography Using Calibrated Enhanced-Resolution Brightness Temperatures, Hunza River Basin, Pakistan

NASA Astrophysics Data System (ADS)

Ramage, J. M.; Brodzik, M. J.; Hardman, M.; Troy, T. J.

2017-12-01

Snow is a vital part of the terrestrial hydrological cycle, a crucial resource for people and ecosystems. In mountainous regions snow is extensive, variable, and challenging to document. Snow melt timing and duration are important factors affecting the transfer of snow mass to soil moisture and runoff. Passive microwave brightness temperature (Tb) changes at 36 and 18 GHz are a sensitive way to detect snow melt onset due to their sensitivity to the abrupt change in emissivity. They are widely used on large icefields and high latitude watersheds. The coarse resolution ( 25 km) of historically available data has precluded effective use in high relief, heterogeneous regions, and gaps between swaths also create temporal data gaps at lower latitudes. New enhanced resolution data products generated from a scatterometer image reconstruction for radiometer (rSIR) technique are available at the original frequencies. We use these Calibrated Enhanced-resolution Brightness (CETB) Temperatures Earth System Data Records (ESDR) to evaluate existing snow melt detection algorithms that have been used in other environments, including the cross polarized gradient ratio (XPGR) and the diurnal amplitude variations (DAV) approaches. We use the 36/37 GHz (3.125 km resolution) and 18/19 GHz (6.25 km resolution) vertically and horizontally polarized datasets from the Special Sensor Microwave Imager (SSM/I) and Advanced Microwave Radiometer for EOS (AMSR-E) and evaluate them for use in this high relief environment. The new data are used to assess glacier and snow melt records in the Hunza River Basin [area 13,000 sq. km, located at 36N, 74E], a tributary to the Upper Indus Basin, Pakistan. We compare the melt timing results visually and quantitatively to the corresponding EASE-Grid 2.0 25-km dataset, SRTM topography, and surface temperatures from station and reanalysis data. The new dataset is coarser than the topography, but is able to differentiate signals of melt/refreeze timing for

Snow Melt Chemistry: Major and Trace Cation Contributions to Downstream Systems from the Llewellyn and Matthes Glaciers, Juneau Icefield

NASA Astrophysics Data System (ADS)

Huston, K.; Gianotti, Z.; Fortner, S. K.; John, C.; Kehrwald, N. M.; Kennedy, J.

2017-12-01

Previous work has revealed very little information on melt chemistry of the temperate Juneau Icefield. Improving this understanding is central to evaluating how current changes in climate will impact nutrient delivery to downstream ecosystems. The study focused on evaluating late melt season concentrations of major and trace cations on the Juneau Icefield. During the 2016 season, 30 supraglacial stream samples from the Llewellyn Glacier had K, Mg, Ca, and Na concentrations that varied across two to three orders of magnitude. For example, Ca ranged from 2-2023 ug/L. We collected surface snow from a transect across the Matthes and Llewellyn glaciers in late July and early August 2017 to retrieve data on actively melting snow of the Juneau Icefield. We collected these samples across a glacial flow divide to assess spatial variation in surface chemistry. We have used physical observations and chemical signatures (e.g. sea salt, eolian deposits) to identify the source and post-depositional fate of glacier chemistry. Additionally, we have compared our chemical results with existing datasets for greater understanding of chemical cycling through glacier systems.

Potential genotoxic effects of melted snow from an urban area revealed by the Allium cepa test.

PubMed

Blagojević, Jelena; Stamenković, Gorana; Vujosević, Mladen

2009-09-01

The presence of well-known atmospheric pollutants is regularly screened for in large towns but knowledge about the effects of mixtures of different pollutants and especially their genotoxic potential is largely missing. Since falling snow collects pollutants from the air, melted snow samples could be suitable for evaluating potential genotoxicity. For this purpose the Allium cepa anaphase-telophase test was used to analyse melted snow samples from Belgrade, the capital city of Serbia. Samples of snow were taken at two sites, characterized by differences in pollution intensity, in three successive years. At the more polluted site the analyses showed a very high degree of both toxicity and genotoxicity in the first year of the study corresponding to the effects of the known mutagen used as the positive control. At the other site the situation was much better but not without warning signals. The results showed that standard analyses for the presence of certain contaminants in the air do not give an accurate picture of the possible consequences of urban air pollution because the genotoxic potential remains hidden. The A. cepa test has been demonstrated to be very convenient for evaluation of air pollution through analyses of melted snow samples.

Optical Benson: Following the Impact of Melt Season Progression Using Landsat and Sentinel 2 - Snow Zone Formation Imaged

NASA Astrophysics Data System (ADS)

Fahnestock, M. A.; Shuman, C. A.; Alley, K. E.

2017-12-01

Snow pit observations on a glaciologically-focussed surface traverse in Greenland allowed Benson [1962, SIPRE (now CRREL) Research Report 70] to define a series of snow zones based on the extent of post-depositional diagenesis of the snowpack. At high elevations, Benson found fine-grained "dry snow" where melt (at that time) was absent year-round, followed down-elevation by a "percolation zone" where surface melt penetrated the snowpack, then a "wet snow zone" where firn became saturated during the peak of the melt season, and finally "superimposed ice" and "bare ice" zones where refrozen surface melt and glacier ice were exposed in the melt season. These snow zones can be discriminated in winter synthetic aperture radar (SAR) imagery of the ice sheet (e.g. Fahnestock et al. 2001), but summer melt reduces radar backscatter and makes it difficult to follow the progression of diagenesis beyond the initial indications of surface melting. While some of the impacts of surface melt (especially bands of blue water-saturated firn) are observed from time to time in optical satellite imagery, it has only become possible to map effects of melt over the course of a summer season with the advent of large-data analysis tools such as Google Earth Engine and the inclusion of Landsat and Sentinel-2 data streams in these tools. A map of the maximum extent of this blue saturated zone through the 2016 melt season is shown in the figure. This image is a true color (RGB) composite, but each pixel in the image shows the color of the surface when the "blueness" of the pixel was at a maximum. This means each pixel can be from a different satellite image acquisition than adjacent pixels - but it also means that the maximum extent of the saturated firn (Benson's wet snow zone) is visible. Also visible are percolation, superimposed and bare ice zones. This analysis, using Landsat 8 Operational Land Imager data, was performed using Google Earth Engine to access and analyze the entire melt

Investigating the effect and uncertainties of light absorbing impurities in snow and ice on snow melt and discharge generation using a hydrologic catchment model and satellite data

NASA Astrophysics Data System (ADS)

Matt, Felix; Burkhart, John F.

2017-04-01

Light absorbing impurities in snow and ice (LAISI) originating from atmospheric deposition enhance snow melt by increasing the absorption of short wave radiation. The consequences are a shortening of the snow cover duration due to increased snow melt and, with respect to hydrologic processes, a temporal shift in the discharge generation. However, the magnitude of these effects as simulated in numerical models have large uncertainties, originating mainly from uncertainties in the wet and dry deposition of light absorbing aerosols, limitations in the model representation of the snowpack, and the lack of observable variables required to estimate model parameters and evaluate the simulated variables connected with the representation of LAISI. This leads to high uncertainties in the additional energy absorbed by the snow due to the presence of LAISI, a key variable in understanding snowpack energy-balance dynamics. In this study, we assess the effect of LAISI on snow melt and discharge generation and the involved uncertainties in a high mountain catchment located in the western Himalayas by using a distributed hydrological catchment model with focus on the representation of the seasonal snow pack. The snow albedo is hereby calculated from a radiative transfer model for snow, taking the increased absorption of short wave radiation by LAISI into account. Meteorological forcing data is generated from an assimilation of observations and high resolution WRF simulations, and LAISI mixing ratios from deposition rates of Black Carbon simulated with the FLEXPART model. To asses the quality of our simulations and the related uncertainties, we compare the simulated additional energy absorbed by the snow due to the presence of LAISI to the MODIS Dust Radiative Forcing in Snow (MODDRFS) algorithm satellite product.

A coupled melt-freeze temperature index approach in a one-layer model to predict bulk volumetric liquid water content dynamics in snow

NASA Astrophysics Data System (ADS)

Avanzi, Francesco; Yamaguchi, Satoru; Hirashima, Hiroyuki; De Michele, Carlo

2016-04-01

Liquid water in snow rules runoff dynamics and wet snow avalanches release. Moreover, it affects snow viscosity and snow albedo. As a result, measuring and modeling liquid water dynamics in snow have important implications for many scientific applications. However, measurements are usually challenging, while modeling is difficult due to an overlap of mechanical, thermal and hydraulic processes. Here, we evaluate the use of a simple one-layer one-dimensional model to predict hourly time-series of bulk volumetric liquid water content in seasonal snow. The model considers both a simple temperature-index approach (melt only) and a coupled melt-freeze temperature-index approach that is able to reconstruct melt-freeze dynamics. Performance of this approach is evaluated at three sites in Japan. These sites (Nagaoka, Shinjo and Sapporo) present multi-year time-series of snow and meteorological data, vertical profiles of snow physical properties and snow melt lysimeters data. These data-sets are an interesting opportunity to test this application in different climatic conditions, as sites span a wide latitudinal range and are subjected to different snow conditions during the season. When melt-freeze dynamics are included in the model, results show that median absolute differences between observations and predictions of bulk volumetric liquid water content are consistently lower than 1 vol%. Moreover, the model is able to predict an observed dry condition of the snowpack in 80% of observed cases at a non-calibration site, where parameters from calibration sites are transferred. Overall, the analysis show that a coupled melt-freeze temperature-index approach may be a valid solution to predict average wetness conditions of a snow cover at local scale.

Transport of intercepted snow from trees during snow storms

Treesearch

David H. Miller

1966-01-01

Five principal processes by which intercepted snow in trees is removed during snow storms are described and evaluated as far as data permit: vapor flux from melt water, vapor flux from bodies of snow, stem flow and dripping of melt water, sliding of bodies of intercepted snow from branches, and wind erosion and transport of intercepted snow. Further research is...

Performances of the snow accumulation melting model SAMM: results in the Northern Apennines test area

NASA Astrophysics Data System (ADS)

Lagomarsino, Daniela; Martelloni, Gianluca; Segoni, Samuele; Catani, Filippo; Fanti, Riccardo

2013-04-01

In this work we propose a snow accumulation-melting model (SAMM) to forecast the snowpack height and we compare the results with a simple temperature index model and an improved version of the latter.For this purpose we used rainfall, temperature and snowpack thickness 5-years data series from 7 weather stations in the Northern Apennines (Emilia Romagna Region, Italy). SAMM is based on two modules modelling the snow accumulation and the snowmelt processes. Each module is composed by two equations: a mass conservation equation is solved to model snowpack thickness and an empirical equation is used for the snow density. The processes linked to the accumulation/depletion of the snowpack (e.g. compression of the snowpack due to newly fallen snow and effects of rainfall) are modelled identifying limiting and inhibitory factors according to a kinetic approach. The model depends on 13 empirical parameters, whose optimal values were defined with an optimization algorithm (simplex flexible) using calibration measures of snowpack thickness. From an operational point of view, SAMM uses as input data only temperature and rainfall measurements, bringing the additional advantage of a relatively easy implementation. In order to verify the improvement of SAMM with respect to a temperature-index model, the latter was applied considering, for the amount of snow melt, the following equation: M = fm(T-T0), where M is hourly melt, fm is the melting factor and T0 is a threshold temperature. In this case the calculation of the depth of the snowpack requires the use of 3 parameters: fm, T0 and ?0 (the mean density of the snowpack). We also performed a simulation by replacing the SAMM melting module with the above equation and leaving unchanged the accumulation module: in this way we obtained a model with 9 parameters. The simulations results suggest that any further extension of the simple temperature index model brings some improvements with a consequent decrease of the mean error

Modulation of Sea Ice Melt Onset and Retreat in the Laptev Sea by the Timing of Snow Retreat in the West Siberian Plain

NASA Astrophysics Data System (ADS)

Crawford, A. D.; Stroeve, J.; Serreze, M. C.; Rajagopalan, B.; Horvath, S.

2017-12-01

As much of the Arctic Ocean transitions to ice-free conditions in summer, efforts have increased to improve seasonal forecasts of not only sea ice extent, but also the timing of melt onset and retreat. This research investigates the potential of regional terrestrial snow retreat in spring as a predictor for subsequent sea ice melt onset and retreat in Arctic seas. One pathway involves earlier snow retreat enhancing atmospheric moisture content, which increases downwelling longwave radiation over sea ice cover downstream. Another pathway involves manipulation of jet stream behavior, which may affect the sea ice pack via both dynamic and thermodynamic processes. Although several possible connections between snow and sea ice regions are identified using a mutual information criterion, the physical mechanisms linking snow retreat and sea ice phenology are most clearly exemplified by variability of snow retreat in the West Siberian Plain impacting melt onset and sea ice retreat in the Laptev Sea. The detrended time series of snow retreat in the West Siberian Plain explains 26% of the detrended variance in Laptev Sea melt onset (29% for sea ice retreat). With modest predictive skill and an average time lag of 53 (88) days between snow retreat and sea ice melt onset (retreat), West Siberian Plains snow retreat is useful for refining seasonal sea ice predictions in the Laptev Sea.

Spring Snow Melt Timing and Changes over Arctic Lands

NASA Technical Reports Server (NTRS)

Foster, J. L.; Robinson, D. A.; Hall, D. K.; Estilow, T. W.

2006-01-01

Spring snow cover over Arctic lands has, on average, melted approximately 4-7 days earlier since the late 1980s compared to the previous 20 years. The earlier disappearance of snow has been identified in non-mountainous regions at the 60 deg and 70 deg N parallels over Eurasia and North America using visible satellite observations of continental snow cover extent (SCE) mapped by the National Oceanic and Atmospheric Administration. The change was greater in the farthest north continental locations. Northern hemisphere SCE declined by almost 10% (May) to 20% (June) between the two intervals. At latitude 70 deg N, eight segments of longitude (each 10 deg in width) show significant (negative) trends. However, only two longitudinal segments at 60 deg N show significant trends, (one positive and one negative). SCE changes coincide with increasing spring warmth and the earlier diminution of sea ice in the last several decades. However, while sea ice has continued to decrease during this recent interval, snowmelt dates in the Arctic changed in a step-like fashion during the mid to late 1980s and have remained much the same since that time.

Investigating the Impact of Aerosol Deposition on Snow Melt over the Greenland Ice Sheet Using a New Kernel

NASA Astrophysics Data System (ADS)

Li, Y.; Flanner, M.

2017-12-01

Accelerating surface melt on the Greenland Ice Sheet (GrIS) has led to a doubling of Greenland's contribution to global sea level rise during recent decades. The darkening effect due to black carbon (BC), dust, and other light absorbing impurities (LAI) enhances snow melt by boosting its absorption of solar energy. It is therefore important for coupled aerosol-climate and ice sheet models to include snow darkening effects from LAI, and yet most do not. In this study, we develop an aerosol deposition—snow melt kernel based on the Community Earth System Model (CESM) to investigate changes in melt flux due to variations in the amount and timing of aerosol deposition on the GrIS. The Community Land Model (CLM) component of CESM is driven with a large range of aerosol deposition fluxes to determine non-linear relationships between melt perturbation and deposition amount occurring in different months and location (thereby capturing variations in base state associated with elevation and latitude). The kernel product will include climatological-mean effects and standard deviations associated with interannual variability. Finally, the kernel will allow aerosol deposition fluxes from any global or regional aerosol model to be translated into surface melt perturbations of the GrIS, thus extending the utility of state-of-the-art aerosol models.

On the exchange of sensible and latent heat between the atmosphere and melting snow

USGS Publications Warehouse

Stoy, Paul C.; Peitzsch, Erich H.; Wood, David J. A.; Rottinghaus, Daniel; Wohlfahrtd, Georg; Goulden, Michael; Ward, Helen

2018-01-01

The snow energy balance is difficult to measure during the snowmelt period, yet critical for predictions of water yield in regions characterized by snow cover. Robust simplifications of the snowmelt energy balance can aid our understanding of water resources in a changing climate. Research to date has demonstrated that the net turbulent flux (FT) between a melting snowpack and the atmosphere is negligible if the sum of atmospheric vapor pressure (ea) and temperature (Ta) equals a constant, but it is unclear how frequently this situation holds across different sites. Here, we quantified the contribution of FT to the snowpack energy balance during 59 snowmelt periods across 11 sites in the FLUXNET2015 database with a detailed analysis of snowmelt in subarctic tundra near Abisko, Sweden. At the Abisko site we investigated the frequency of occurrences during which sensible heat flux (H) and latent heat flux (λE) are of (approximately) equal but opposite sign, and if the sum of these terms, FT, is therefore negligible during the snowmelt period. H approximately equaled -λE for less than 50% of the melt period and FT was infrequently a trivial term in the snowmelt energy balance at Abisko. The reason is that the relationship between observed ea and Ta is roughly orthogonal to the “line of equality” at which H equals -λE as warmer Ta during the melt period usually resulted in greater ea. This relationship holds both within melt periods at individual sites and across different sites in the FLUXNET2015 database, where FTcomprised less than 20% of the energy available to melt snow, Qm, in 44% of the snowmelt periods studied here. FT/Qm was significantly related to the mean ea during the melt period, but not mean Ta, and FT tended to be near 0 W m−2 when ea averaged ca. 0.5 kPa. FT may become an increasingly important term in the snowmelt energy balance across many global regions as warmer temperatures are projected to cause snow

Combining model and satellite data to investigate the effect of light absorbing impurities on snow melt and discharge generation

NASA Astrophysics Data System (ADS)

Matt, F.; Burkhart, J. F.

2017-12-01

Light absorbing impurities in snow and ice (LAISI) originating from atmospheric deposition enhance snow melt by increasing the absorption of solar radiation. The consequences are a shortening of the snow cover duration due to increased snow melt and, with respect to hydrologic processes, a temporal shift in the discharge generation. However, the effects as simulated in numerical models have large uncertainties. These uncertainties originate mainly from uncertainties in the wet and dry deposition of light absorbing aerosols, limitations in the model representation of the snowpack, and the lack of observable variables required to estimate model parameters. This leads to high uncertainties in the additional energy absorbed by the snow due to the presence of LAISI (the so called radiative forcing of LAISI), a key variable in understanding snowpack energy-balance dynamics. In this study, we present an approach combining distributed model simulations on the catchment scale and remotely sensed radiative forcing from LAISI in order to evaluate and improve model predictions. In a case study, we assess the effect of LAISI on snow melt and discharge generation in a high mountain catchment located in the western Himalaya using the distributed hydrologic model, Shyft. The snow albedo is hereby calculated from a radiative transfer model for snow, taking the increased absorption of solar radiation by LAISI into account. LAISI mixing ratios in snow are determined from atmospheric aerosol deposition rates. To asses the quality of our simulations, we model the instantaneous clear sky radiative forcing at MODIS overpass times, and compare it to the MODIS Dust Radiative Forcing in Snow (MODDRFS) satellite product. By scaling the deposition input to the model, we can optimize the simulated radiative forcing towards the satellite observations.

Pitted rock surfaces on Mars: A mechanism of formation by transient melting of snow and ice

NASA Astrophysics Data System (ADS)

Head, James W.; Kreslavsky, Mikhail A.; Marchant, David R.

2011-09-01

Pits in rocks on the surface of Mars have been observed at several locations. Similar pits are observed in rocks in the Mars-like hyperarid, hypothermal stable upland zone of the Antarctic Dry Valleys; these form by very localized chemical weathering due to transient melting of small amounts of snow on dark dolerite boulders preferentially heated above the melting point of water by sunlight. We examine the conditions under which a similar process might explain the pitted rocks seen on the surface of Mars (rock surface temperatures above the melting point; atmospheric pressure exceeding the triple point pressure of H2O; an available source of solid water to melt). We find that on Mars today each of these conditions is met locally and regionally, but that they do not occur together in such a way as to meet the stringent requirements for this process to operate. In the geological past, however, conditions favoring this process are highly likely to have been met. For example, increases in atmospheric water vapor content (due, for example, to the loss of the south perennial polar CO2 cap) could favor the deposition of snow, which if collected on rocks heated to above the melting temperature during favorable conditions (e.g., perihelion), could cause melting and the type of locally enhanced chemical weathering that can cause pits. Even when these conditions are met, however, the variation in heating of different rock facets under Martian conditions means that different parts of the rock may weather at different times, consistent with the very low weathering rates observed on Mars. Furthermore, as is the case in the stable upland zone of the Antarctic Dry Valleys, pit formation by transient melting of small amounts of snow readily occurs in the absence of subsurface active layer cryoturbation.

Relationship between RADARSAT-2 Derived Snow Thickness on Winter First Year Sea-Ice and Aerial Melt-Pond Distribution using Geostatistics and GLCM Texture

NASA Astrophysics Data System (ADS)

Ramjan, S.; Geldsetzer, T.; Yackel, J.

2016-12-01

A contemporary shift from primarily thicker, older multi-year sea ice (MYI) to thinner, smoother first-year sea ice (FYI) has been attributed to increased atmospheric and oceanic warming in the Arctic, with a steady diminishing of Arctic sea ice thickness due to a reduction of thick MYI compared to FYI. With an increase in FYI fraction, increased melting takes place during the summer months, exposing the sea ice to additional incoming solar radiation. With this change, an increase in melt pond fraction has been observed during the summer melt season. Prior research advocated that thin/thick snow leads to dominant surface flooding/snow patches during summer because of an enhanced ice-albedo feedback. For instance, thin snow cover areas form melt ponds first. Therefore, aerial measurements of melt pond fraction provide a proxy for relative snow thickness. RADARSAT-2 polarimetric SAR data can provide enhanced information about both surface scattering and volume scattering mechanisms, as well as recording the phase difference between polarizations. These polarimetric parameters can be computed that have a useful physical interpretation. The principle research focus is to establish a methodology to determine the relationship between selected geostatistics and image texture measures of pre-melt RADARSAT-2 parameters and aerially-measured melt pond fraction. Overall, the notion of this study is to develop an algorithm to estimate relative snow thickness variability in winter through an integrated approach utilizing SAR polarimetric parameters, geostatistical analysis and texture measures. Results are validated with test sets of melt pond fractions, and in situ snow thickness measurements. Preliminary findings show significant correlations with pond fraction for the standard deviation of HH and HV parameters at small incidence angles, and for the mean of the co-pol phase difference parameter at large incidence angles.

Global Snow-Cover Evolution from Twenty Years of Satellite Passive Microwave Data

USGS Publications Warehouse

Mognard, N.M.; Kouraev, A.V.; Josberger, E.G.

2003-01-01

Starting in 1979 with the SMMR (Scanning Multichannel Microwave Radiometer) instrument onboard the satellite NIMBUS-7 and continuing since 1987 with the SSMI (Special Sensor Microwave Imager) instrument on board the DMSP (Defence Meteorological Satellite Program) series, more then twenty years of satellite passive microwave data are now available. This dataset has been processed to analyse the evolution of the global snow cover. This work is part of the AICSEX project from the 5th Framework Programme of the European Community. The spatio-temporal evolution of the satellite-derived yearly snow maximum extent and the timing of the spring snow melt were estimated and analysed over the Northern Hemisphere. Significant differences between the evolution of the yearly maximum snow extent in Eurasia and in North America were found. A positive correlation between the maximum yearly snow cover extent and the ENSO index was obtained. High interannual spatio-temporal variability characterises the timing of snow melt in the spring. Twenty-year trends in the timing of spring snow melt have been computed and compared with spring air temperature trends for the same period and the same area. In most parts of Eurasia and in the central and western parts of North America the tendency has been for earlier snow melt. In northeastern Canada, a large area of positive trends, where snow melt timing starts later than in the early 1980s, corresponds to a region of positive trends of spring air temperature observed over the same period.

Response of Alpine Grassland Vegetation Phenology to Snow Accumulation and Melt in Namco Basin

NASA Astrophysics Data System (ADS)

Chen, S.; Cui, X.; Liang, T.

2018-04-01

Snow/ice accumulation and melt, as a vital part of hydrological processes, is close related with vegetation activities. Taking Namco basin for example, based on multisource remote sensing data and the ground observation data of temperature and precipitation, phenological information was extracted by S-G filtering and dynamic threshold method. Daily snow cover fraction was calculated with daily cloud-free snow cover maps. Evolution characteristics of grassland vegetation greening, growth length and daily snow cover fraction and their relationship were analyzed from 2001 to 2013. The results showed that most of grassland vegetation had advanced greening and prolong growth length trend in Namco basin. There were negative correlations between snow cover fraction and vegetation greening or growth length. The response of vegetation phenology to snow cover fraction is more sensitive than that to temperature in spring. Meanwhile, vegetation growth condition turned worse with advanced greening and prolong growth length. To a certain extent, our research reveals the relationship between grassland vegetation growth cycle and snow in alpine ecosystem. It has provided reference to research the response mechanism of alpine grassland ecosystem to climate changes.

Snow Water Equivalent Pressure Sensor Performance in a Deep Snow Cover

NASA Astrophysics Data System (ADS)

Johnson, J. B.; Gelvin, A. B.; Schaefer, G. L.

2006-12-01

Accurate measurements of snow water equivalent are important for a variety of water resource management operations. In the western US, real-time SWE measurements are made using snow pillows that can experience errors from snow-bridging, poor installation configuration, and enhanced solar radiation absorption. Snow pillow installations that place the pillow abnormally above or below the surrounding terrain can affect snow catchment. Snow pillows made from dark materials can preferentially absorb solar radiation penetrating the snow causing accelerated melt. To reduce these problems, the NRCS and CRREL developed an electronic SWE sensor to replace the snow pillow. During the winter of 2005-2006 the NRCS/CRREL electronic sensor was deployed at Hogg Pass, Oregon, with a total SWE accumulation of about 1000 mm. The NRCS/CRREL sensor consists of a center panel surrounded by eight outer panels whose purpose is to buffer snow bridging loads. By separately monitoring load cell outputs from the sensor, snow-bridging events are directly measured. A snow-bridging event associated with a 180 mm SWE accumulation in a 24-hour period exhibited a SWE over-measurement of 60% at the sensor edge while the center panel showed less than a 10% effect. Individual load cell outputs were used to determine the most representative SWE value, which was within 5% of the adjacent snow pillow value. During the spring melt the NRCS/CRREL sensor melt recession lagged that of the snow pillow by about a week. Physical examination of the Hogg Pass site indicated that the CRREL sensor results were consistent with snow-on-the-ground observations. The snow pillow experienced accelerated melt because it was installed on a mound above the surrounding terrain and absorbed solar radiation through the snow. SWE pressure sensor accuracy is significantly improved by using an active center panel surrounded by buffer panels, monitoring several individual load cell to detect and correct snow-bridging errors, and

Measurement of snow interception and canopy effects on snow accumulation and melt in a mountainous maritime climate, Oregon, United States

NASA Astrophysics Data System (ADS)

Storck, Pascal; Lettenmaier, Dennis P.; Bolton, Susan M.

2002-11-01

The results of a 3 year field study to observe the processes controlling snow interception by forest canopies and under canopy snow accumulation and ablation in mountain maritime climates are reported. The field study was further intended to provide data to develop and test models of forest canopy effects on beneath-canopy snowpack accumulation and melt and the plot and stand scales. Weighing lysimeters, cut-tree experiments, and manual snow surveys were deployed at a site in the Umpqua National Forest, Oregon (elevation 1200 m). A unique design for a weighing lysimeter was employed that allowed continuous measurements of snowpack evolution beneath a forest canopy to be taken at a scale unaffected by variability in canopy throughfall. Continuous observations of snowpack evolution in large clearings were made coincidentally with the canopy measurements. Large differences in snow accumulation and ablation were observed at sites beneath the forest canopy and in large clearings. These differences were not well described by simple relationships between the sites. Over the study period, approximately 60% of snowfall was intercepted by the canopy (up to a maximum of about 40 mm water equivalent). Instantaneous sublimation rates exceeded 0.5 mm per hour for short periods. However, apparent average sublimation from the intercepted snow was less than 1 mm per day and totaled approximately 100 mm per winter season. Approximately 72 and 28% of the remaining intercepted snow was removed as meltwater drip and large snow masses, respectively. Observed differences in snow interception rate and maximum snow interception capacity between Douglas fir (Pseudotsuga menziesii), white fir (Abies concolor), ponderosa pine (Pinus ponderosa), and lodgepole pine (Pinus contorta) were minimal.

Using ground penetrating radar to assess the variability of snow water equivalent and melt in a mixed canopy forest, Northern Colorado

NASA Astrophysics Data System (ADS)

Webb, Ryan W.

2017-09-01

Snow is an important environmental variable in headwater systems that controls hydrological processes such as streamflow, groundwater recharge, and evapotranspiration. These processes will be affected by both the amount of snow available for melt and the rate at which it melts. Snow water equivalent (SWE) and snowmelt are known to vary within complex subalpine terrain due to terrain and canopy influences. This study assesses this variability during the melt season using ground penetrating radar to survey multiple plots in northwestern Colorado near a snow telemetry (SNOTEL) station. The plots include south aspect and flat aspect slopes with open, coniferous (subalpine fir, Abies lasiocarpa and engelman spruce, Picea engelmanii), and deciduous (aspen, populous tremuooides) canopy cover. Results show the high variability for both SWE and loss of SWE during spring snowmelt in 2014. The coefficient of variation for SWE tended to increase with time during snowmelt whereas loss of SWE remained similar. Correlation lengths for SWE were between two and five meters with melt having correlation lengths between two and four meters. The SNOTEL station regularly measured higher SWE values relative to the survey plots but was able to reasonably capture the overall mean loss of SWE during melt. Ground Penetrating Radar methods can improve future investigations with the advantage of non-destructive sampling and the ability to estimate depth, density, and SWE.

Effects of forest cover and environmental variables on snow accumulation and melt

Treesearch

Mariana Dobre; William J. Elliot; Joan Q. Wu; Timothy E. Link; Ina S. Miller

2011-01-01

The goal of this study was to assess the effects of topography and forest cover resulting from different treatments on snow accumulation and melt in small watersheds in the western United States. A paired-watershed study was implemented at the Priest River Experimental Forest, Idaho, where 10 small watersheds with an average area of 4.5 ha were treated by: 1) control (...

Estimation of snow and glacier melt contribution to Liddar stream in a mountainous catchment, western Himalaya: an isotopic approach.

PubMed

Jeelani, Gh; Shah, Rouf A; Jacob, Noble; Deshpande, Rajendrakumar D

2017-03-01

Snow- and glacier-dominated catchments in the Himalayas are important sources of fresh water to more than one billion people. However, the contribution of snowmelt and glacier melt to stream flow remains largely unquantified in most parts of the Himalayas. We used environmental isotopes and geochemical tracers to determine the source water and flow paths of stream flow draining the snow- and glacier-dominated mountainous catchment of the western Himalaya. The study suggested that the stream flow in the spring season is dominated by the snowmelt released from low altitudes and becomes isotopically depleted as the melt season progressed. The tracer-based mixing models suggested that snowmelt contributed a significant proportion (5-66 %) to stream flow throughout the year with the maximum contribution in spring and summer seasons (from March to July). In 2013 a large and persistent snowpack contributed significantly (∼51 %) to stream flow in autumn (September and October) as well. The average annual contribution of glacier melt to stream flow is little (5 %). However, the monthly contribution of glacier melt to stream flow reaches up to 19 % in September during years of less persistent snow pack.

Skiing in the Eocene Uinta Mountains? Isotopic evidence in the Green River Formation for snow melt and large mountains

NASA Astrophysics Data System (ADS)

Norris, Richard D.; Jones, Lawrence S.; Corfield, Richard M.; Cartlidge, Julie E.

1996-05-01

Isotopic analysis of lacustrine carbonates from the Eocene Green River Formation suggests that lake waters were derived partly from snow melt. This evidence for cool climates is in marked contrast to paleontological and model evidence for mild temperatures in the continental interior. Oxygen isotope ratios of carbonates frequently reach -12‰ to nearly -16‰ (Peedee belemnite), which suggests that lake waters probably had δ18O of <-13‰ (standard mean ocean water). Consideration of the evaporative 18O enrichment that typically occurs in modern large saline lakes suggests that the source waters to the Green River basin had a δ18O of <-18‰. These ratios are consistent with snow melt and are too negative to be easily accounted for by distillation in the atmosphere during heavy rainfall. The Green River lakes formed in a closed basin encircled by large mountains; this suggests that the snow melt was locally produced. The mountains surrounding the lake must have been high enough to occasionally supply significant melt water to the much lower lake. Lapse rate calculations suggest minimum altitudes of >3000 m for the mountains encircling the Green River basin.

Quantifying changes in the contribution of upstream snow and glacier melt to downstream low flows in the River Rhine

NASA Astrophysics Data System (ADS)

Stahl, K.; Kohn, I.; Boehm, M.; Seibert, J.; Freudiger, D.; Gerlinger, K.; Weiler, M.

2016-12-01

Low flows impact river ecosystems and impair water use. In the mid- and downstream reaches of one of the largest rivers in Europe, the River Rhine, low flows can threaten a variety of ecosystem services and direct uses. Low flows in summer and fall are sustained by the snow and ice melt contribution from the glacierized mountain headwaters upstream. This study explores changes in the discharge components of rain, snowmelt and ice melt during extreme low flow events from a downstream perspective. Quantification of the discharge components is based on a novel method of runoff component tracking that was implemented into a model chain, consisting of the HBV model, which includes a glacier mass balance model allowing for areal glacier changes, for the headwaters and the distributed hydrological model LARSIM for the remaining Rhine basin. A transient model run at daily resolution was calibrated to glacier volume change, basin-wide snow cover and snow water equivalent and discharge variability at many gauging stations over the period 1901-2006. The analysis of the resulting discharge components revealed that over the course of the 20th Century, the loss of glacier volume and glacier area in the headwaters appears to have compensated an increasingly negative glacier mass balance, resulting in little long-term change to the ice melt component in summer streamflow - thus showing no clear `peak-water' trend. While the glacier ice melt component was less than two percent of the average annual discharge of the mid and lower reaches of the River Rhine, models suggest its fraction was much higher during extreme low flow events. The low flows of the summers of 1921, 1947, and 2003 were comprised of record daily ice melt fractions of more than one fifth of the daily discharge along the mid and lower reaches from Basel to the mouth. A scenario model run with suppressed glacier area change suggests that the ice melt discharge component would have doubled if the same meteorological

Unexpected Patterns in Snow and Dirt

NASA Astrophysics Data System (ADS)

Ackerson, Bruce J.

2018-01-01

For more than 30 years, Albert A. Bartlett published "Thermal patterns in the snow" in this journal. These are patterns produced by heat sources underneath the snow. Bartlett's articles encouraged me to pay attention to patterns in snow and to understanding them. At winter's end the last snow becomes dirty and is heaped into piles. This snow comes from the final clearing of sidewalks and driveways. The patterns observed in these piles defied my intuition. This melting snow develops edges where dirt accumulates, in contrast to ice cubes, which lose sharp edges and become more spherical upon melting. Furthermore, dirt absorbs more radiation than snow and yet doesn't melt and round the sharp edges of snow, where dirt accumulates.

NOHRSC Interactive Snow Information

Science.gov Websites

-present) RFC Basin Other (non-RFC) Basin State NSA region (Discussion) NSA subregion (Disc.) Basins by None Snow Water Equivalent Snow Depth Shallow SWE Shallow Snow Depth Snow Temperature Snow Density Snow Melt Snow Precipitation Non-Snow Precipitation Air Temperature Solar Radiation Relative Humidity

Snow depth evolution on sea ice from Snow Buoy measurement

NASA Astrophysics Data System (ADS)

Nicolaus, M.; Arndt, S.; Hendricks, S.; Hoppmann, M.; Katlein, C.; König-Langlo, G.; Nicolaus, A.; Rossmann, H. L.; Schiller, M.; Schwegmann, S.; Langevin, D.

2016-12-01

Snow cover is an Essential Climate Variable. On sea ice, snow dominates the energy and momentum exchanges across the atmosphere-ice-ocean interfaces, and actively contributes to sea ice mass balance. Yet, snow depth on sea ice is one of the least known and most difficult to observe parameters of the Arctic and Antarctic; mainly due to its exceptionally high spatial and temporal variability. In this study; we present a unique time series dataset of snow depth and air temperature evolution on Arctic and Antarctic sea ice recorded by autonomous instruments. Snow Buoys record snow depth with four independent ultrasonic sensors, increasing the reliability of the measurements and allowing for additional analyses. Auxiliary measurements include surface and air temperature, barometric pressure and GPS position. 39 deployments of such Snow Buoys were achieved over the last three years either on drifting pack ice, on landfast sea ice or on an ice shelf. Here we highlight results from two pairs of Snow Buoys installed on drifting pack ice in the Weddell Sea. The data reveals large regional differences in the annual cycle of snow depth. Almost no reduction in snow depth (snow melt) was observed in the inner and southern part of the Weddell Sea, allowing a net snow accumulation of 0.2 to 0.9 m per year. In contrast, summer snow melt close to the ice edge resulted in a decrease of about 0.5 m during the summer 2015/16. Another array of eight Snow Buoys was installed on central Arctic sea ice in September 2015. Their air temperature record revealed exceptionally high air temperatures in the subsequent winter, even exceeding the melting point but with almost no impact on snow depth at that time. Future applications of Snow Buoys on Arctic and Antarctic sea ice will allow additional inter-annual studies of snow depth and snow processes, e.g. to support the development of snow depth data products from airborne and satellite data or though assimilation in numerical models.

Snow deposition, melt, runoff, and chemistry in a small alpine watershed, Emerald Lake Basin, Sequoia National Park. Final report, 1 July 1984-31 March 1987

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dozier, J.; Melack, J.M.; Marks, D.

1987-03-01

The report describes the first two years of an investigation of the snow chemistry and hydrology of the Emerald Lake Watershed in Sequoia National Park. The investigation examined the impact of acid deposition on high-elevation ecosystems of the Sierra Nevada. The following aspects of snow deposition and melt were studied: energy inputs; pattern of snow deposition and ablation; snowpack, meltwater and runoff chemistry; stream hydrology during the melt period.

Snow farming: conserving snow over the summer season

NASA Astrophysics Data System (ADS)

Grünewald, Thomas; Wolfsperger, Fabian; Lehning, Michael

2018-01-01

Summer storage of snow for tourism has seen an increasing interest in the last years. Covering large snow piles with materials such as sawdust enables more than two-thirds of the initial snow volume to be conserved. We present detailed mass balance measurements of two sawdust-covered snow piles obtained by terrestrial laser scanning during summer 2015. Results indicate that 74 and 63 % of the snow volume remained over the summer for piles in Davos, Switzerland and Martell, Italy. If snow mass is considered instead of volume, the values increase to 83 and 72 %. The difference is attributed to settling and densification of the snow. Additionally, we adapted the one-dimensional, physically based snow cover model SNOWPACK to perform simulations of the sawdust-covered snow piles. Model results and measurements agreed extremely well at the point scale. Moreover, we analysed the contribution of the different terms of the surface energy balance to snow ablation for a pile covered with a 40 cm thick sawdust layer and a pile without insulation. Short-wave radiation was the dominant source of energy for both scenarios, but the moist sawdust caused strong cooling by long-wave emission and negative sensible and latent heat fluxes. This cooling effect reduces the energy available for melt by up to a factor of 12. As a result only 9 % of the net short-wave energy remained available for melt. Finally, sensitivity studies of the parameters thickness of the sawdust layer, air temperature, precipitation and wind speed were performed. We show that sawdust thickness has a tremendous effect on snow loss. Higher air temperatures and wind speeds increase snow ablation but less significantly. No significant effect of additional precipitation could be found as the sawdust remained wet during the entire summer with the measured quantity of rain. Setting precipitation amounts to zero, however, strongly increased melt. Overall, the 40 cm sawdust provides sufficient

An Evaluation of Arctic Ocean Precipitation from Reanalyses for use in Snow Accumulation and Melt Models over Sea Ice

NASA Astrophysics Data System (ADS)

Barrett, A. P.; Stroeve, J.; Liston, G. E.; Tschudi, M. A.; Stewart, S.

2017-12-01

Retrievals of sea ice thickness from satellite- and air-borne sensors require knowledge of snow depth and density. Early retrievals used climatologies of snow depth and density - "The Warren Climatology" - based on observations from 31 Soviet drifting stations between 1957 and 1991. This climatology was the best available Arctic-wide data set at the time. However, it does not account for year-to-year variations in spatial and temporal patterns of snow depth, nor does it account for changes in snow depth over longer time periods. Recent efforts to retrieve ice thickness have used output from global and regional atmospheric reanalyses directly or as input to snow accumulation, density evolution, and melt models to estimate snow depth. While such efforts represent the state-of-the-art in terms of Arctic-wide snow depth fields, there can be large differences between precipitation (and other variables) from reanalyses. Knowledge about these differences and about biases in precipitation magnitude are important for getting the best-possible retrievals of ice thickness. Here, we evaluate fields of total precipitation and snow fall from the NASA MERRA and MERRA2, NOAA CFSR and CFSR version 2, ECMWF ERA-Interim, and Arctic System (ASR) reanalyses with a view to understanding differences in the magnitude, and temporal and spatial patterns of precipitation. Where possible we use observations to understand biases in the reanalysis output. Time series of annual total precipitation for the central Arctic correlate well with all reanalyses showing similar year-to-year variability. Time series for MERRA, MERRA2 and CFSR show no evidence of long-term trends. By contrast ERA-Interim appears to be wetter in the most recent decade. The ASR records only spans 2000 to 2012 but is similar to ERA-Interim. CFSR and MERRA2 are wetter than the other five reanalyses, especially over the eastern Arctic and North Atlantic.

Experimental manipulations of snow-depth: Effects on nutrient content of caribou forage

USGS Publications Warehouse

Walsh, Noreen E.; McCabe, Thomas R.; Welker, J.M.; Parsons, A.N.

1997-01-01

We investigated the potential effects of global climate change on arctic tundra vegetation used as caribou forage. A total of 96 experimental plots was established at six sites on the coastal plain of the Arctic National Wildlife Refuge, Alaska, in 1993 and 1994. We erected snow-fences to increase the amount of snow deposition, and therefore delay the date of the snowmelt on 48 plots (referred to as increased snow/late melting plots). We used black mesh netting on the surface of the snow to increase the rate of melting on 24 plots; the remaining 24 plots served as controls. In July 1994, we collected green leaves from Eriophorum vaginatum, Salix planifolia, and Betula nana and analysed these samples for total carbon and total nitrogen content. Ratios of carbon to nitrogen differed among treatments for all three species. Generally, C:N ratios for B. nana and E. vaginatum on increased snow/late melting plots were lower than on control plots. C:N ratios for S. planifolia on increased snow/late melting plots did not differ from controls, but were lower than on plots which started to melt early. These results may be due to the timing of nitrogen translocation from leaf and stem tissue into storage organs, or due to an increase in available nitrogen input to the system. Further sampling is needed to adequately determine the mechanism responsible for increased nitrogen content of caribou forage in areas with increased amount of snow and delayed snowmelt. ?? 1997 Blackwell Science Ltd.

Early snow melts and biomass burning over Eastern Eurasia and their impacts on the air quality in Northern Japan

NASA Astrophysics Data System (ADS)

Yasunari, T. J.; daSilva, A.; Akiyama, M.; Hayasaki, M.; Murao, N.; Kim, K. M.

2016-12-01

We investigated monthly characteristics including a couple of large biomass burnings (BB) in Eastern Eurasia during 2003 and 2014, and the smoke impacts on Northern Japan. The new re-analyses data including the aerosol data assimilation, called MERRA-2, which was produced by the NASA's Global Modeling and Assimilation Office (GMAO), the monthly mean MODIS snow cover fraction (SCF) data (MOD10CM; further re-gridded), and the observations on PM2.5, elemental carbon (EC), and organic carbon (OC) in Sapporo city (Hokkaido, Japan), were used in our analyses. For the MERRA-2 and MODIS SCF data, we calculated 12-year climatology for each month and these anomalies from the climatology on the focused variables. Three-month means of the anomalies for the last three months until the BB months were calculated except for the SCF. For the SCF, the three-month mean anomalies until the one month before the BB months were also calculated. Here we start especially focusing on the identified fire months with the MERRA-2 data (May 2003, April 2008, and July 2014) in terms of these smoke impacts on the air qualities in Northern Japan (i.e., Hokkaido). We identified two types of biomass burning patterns within these three months. For the BBs in May 2003 and April 2008, the main BB areas were seen in the eastern part of the Lake Baikal. In July 2014, the main BB area was in the Sakha Republic and close to the Arctic region. Then, the MERRA-2 data overestimated the observations (EC, OC, and PM2.5) in Sapporo (Hokkaido, Japan) during the smoke transports, but the elevated timings were well reproduced. For all the three BB cases, abnormally reduced SCF were seen by the one month before the Eurasian BB generations (i.e., earlier than the BB generations). The positive and negative anomalies of 2-m temperature and surface soil wetness, covering the three-month until the BB months, were identified. These suggest that early snow-melting anomalies for these three years could make the following BB

On the formation of glide-snow avalanches

NASA Astrophysics Data System (ADS)

Mitterer, C.; Schweizer, J.

2012-12-01

On steep slopes the full snowpack can glide on the ground; tension cracks may open and eventually the slope may fail as a glide-snow avalanche. Due to their large mass they have considerable destructive potential. Glide-snow avalanches typically occur when the snow-soil interface is moist or wet so that basal friction is reduced. The occurrence, however, of glide cracks and their evolution to glide avalanches are still poorly understood. Consequently, glides are difficult to predict as (i) not all cracks develop into an avalanche, and (ii) for those that do, the time between crack opening and avalanche event might vary from hours to weeks - or on the other hand be so short that there is no warning at all by crack opening. To improve our understanding we monitored several slopes and related glide snow activity to meteorological data. In addition, we explored conditions that favor the formation of a thin wet basal snowpack layer with a physical-based model representing water and heat flux at the snow-soil interface. The statistical analyses revealed that glide-snow avalanche activity might be associated to an early season and a spring condition. While early season conditions tend to have warm and dry autumns followed by heavy snowfalls, spring conditions showed good agreement with increasing air temperature. The model indicates that energy (summer heat) stored in the ground might be sufficient to melt snow at the bottom of the snowpack. Due to capillary forces, water will rise for a few centimeters into the snowpack and thereby reduce friction at the interface. Alternatively, we demonstrate that also in the absence of melt water production at the bottom of the snowpack water may accumulate in the bottom layer due to an upward flux into the snowpack if a dry snowpack overlies a wet soil. The particular conditions that are obviously required at the snow-soil interface explain the strong winter-to-winter variations in snow gliding.

Widespread albedo decreasing and induced melting of Himalayan snow and ice in the early 21st century.

PubMed

Ming, Jing; Wang, Yaqiang; Du, Zhencai; Zhang, Tong; Guo, Wanqin; Xiao, Cunde; Xu, Xiaobin; Ding, Minghu; Zhang, Dongqi; Yang, Wen

2015-01-01

The widely distributed glaciers in the greater Himalayan region have generally experienced rapid shrinkage since the 1850s. As invaluable sources of water and because of their scarcity, these glaciers are extremely important. Beginning in the twenty-first century, new methods have been applied to measure the mass budget of these glaciers. Investigations have shown that the albedo is an important parameter that affects the melting of Himalayan glaciers. The surface albedo based on the Moderate Resolution Imaging Spectroradiometer (MODIS) data over the Hindu Kush, Karakoram and Himalaya (HKH) glaciers is surveyed in this study for the period 2000-2011. The general albedo trend shows that the glaciers have been darkening since 2000. The most rapid decrease in the surface albedo has occurred in the glacial area above 6000 m, which implies that melting will likely extend to snow accumulation areas. The mass-loss equivalent (MLE) of the HKH glacial area caused by surface shortwave radiation absorption is estimated to be 10.4 Gt yr-1, which may contribute to 1.2% of the global sea level rise on annual average (2003-2009). This work probably presents a first scene depicting the albedo variations over the whole HKH glacial area during the period 2000-2011. Most rapidly decreasing in albedo has been detected in the highest area, which deserves to be especially concerned.

Monitoring Snow on ice as Critical Habitat for Ringed Seals

NASA Astrophysics Data System (ADS)

Kelly, B. P.; Moran, J.; Douglas, D. C.; Nghiem, S. V.

2007-12-01

Ringed seals are the primary prey of polar bears, and they are found in all seasonally ice covered seas of the northern hemisphere as well as in several freshwater lakes. The presence of snow covered sea ice is essential for successful ringed seal reproduction. Ringed seals abrade holes in the ice allowing them to surface and breathe under the snow cover. Where snow accumulates to sufficient depths, ringed seals excavate subnivean lairs above breathing holes. They rest, give birth, and nurse their young in those lairs. Temperatures within the lairs remain within a few degrees of freezing, well within the zone of thermal neutrality for newborn ringed seals, even at ambient temperatures of -30° C. High rates of seal mortality have been recorded when early snow melt caused lairs to collapse exposing newborn seals to predators and to subsequent extreme cold events. As melt onset dates come earlier in the Arctic Ocean, ringed seal populations (and the polar bears that depend upon them) will be increasingly challenged. We determined dates of lair abandonment by ringed seals fitted with radio transmitters in the Beaufort Sea (n = 60). We compared abandonment dates to melt onset dates measured in the field, as well as estimated dates derived from active (Ku-band backscatter) and passive (SSM/I) microwave satellite imagery. Date of snow melt significantly improved models of environmental influences on the timing of lair abandonment. We used an algorithm based on multi-channel means and variances of passive microwave data to detect melt onset dates. Those melt onset dates predicted the date of lair abandonment ± 3 days (r 2 = 0.982, p = 0.001). The predictive power of passive microwave proxies combined with their historical record suggest they could serve to monitor critical changes to ringed seal habitat.

Assessment of the timing of daily peak streamflow during melt season in a snow dominated watershed

USDA-ARS?s Scientific Manuscript database

Previous studies have shown that gauge-observed daily streamflow peak times (DPT) during spring snowmelt can exhibit distinct temporal shifts through the season. These shifts have been attributed to three processes that affect the timing of snowmelt arrival: 1) melt flux translation through the snow...

Snow wetness measurements for melt forecasting

NASA Technical Reports Server (NTRS)

Linlor, W. I.; Clapp, F. D.; Meier, M. F.; Smith, J. L.

1975-01-01

A microwave technique for directly measuring snow pack wetness in remote installations is described. The technique, which uses satellite telemetry for data gathering, is based on the attenuation of a microwave beam in transmission through snow.

Phenological adjustment in arctic bird species: relative importance of snow melt and ecological factors

USGS Publications Warehouse

Liebezeit, Joseph R.; Gurney, K. E. B.; Budde, Michael E.; Zack, Steve; Ward, David H.

2014-01-01

Previous studies have documented advancement in clutch initiation dates (CIDs) in response to climate change, most notably for temperate-breeding passerines. Despite accelerated climate change in the Arctic, few studies have examined nest phenology shifts in arctic breeding species. We investigated whether CIDs have advanced for the most abundant breeding shorebird and passerine species at a long-term monitoring site in arctic Alaska. We pooled data from three additional nearby sites to determine the explanatory power of snow melt and ecological variables (predator abundance, green-up) on changes in breeding phenology. As predicted, all species (semipalmated sandpiper, Calidris pusilla, pectoral sandpiper, Calidris melanotos, red-necked phalarope, Phalaropus lobatus, red phalarope, Phalaropus fulicarius, Lapland longspur, Calcarius lapponicus) exhibited advanced CIDs ranging from 0.40 to 0.80 days/year over 9 years. Timing of snow melt was the most important variable in explaining clutch initiation advancement (“climate/snow hypothesis”) for four of the five species, while green-up was a much less important explanatory factor. We found no evidence that high predator abundances led to earlier laying dates (“predator/re-nest hypothesis”). Our results support previous arctic studies in that climate change in the cryosphere will have a strong impact on nesting phenology although factors explaining changes in nest phenology are not necessarily uniform across the entire Arctic. Our results suggest some arctic-breeding shorebird and passerine species are altering their breeding phenology to initiate nesting earlier enabling them to, at least temporarily, avoid the negative consequences of a trophic mismatch.

Widespread Albedo Decreasing and Induced Melting of Himalayan Snow and Ice in the Early 21st Century

PubMed Central

Ming, Jing; Wang, Yaqiang; Du, Zhencai; Zhang, Tong; Guo, Wanqin; Xiao, Cunde; Xu, Xiaobin; Ding, Minghu; Zhang, Dongqi; Yang, Wen

2015-01-01

Background The widely distributed glaciers in the greater Himalayan region have generally experienced rapid shrinkage since the 1850s. As invaluable sources of water and because of their scarcity, these glaciers are extremely important. Beginning in the twenty-first century, new methods have been applied to measure the mass budget of these glaciers. Investigations have shown that the albedo is an important parameter that affects the melting of Himalayan glaciers. Methodology/Principal Findings The surface albedo based on the Moderate Resolution Imaging Spectroradiometer (MODIS) data over the Hindu Kush, Karakoram and Himalaya (HKH) glaciers is surveyed in this study for the period 2000–2011. The general albedo trend shows that the glaciers have been darkening since 2000. The most rapid decrease in the surface albedo has occurred in the glacial area above 6000 m, which implies that melting will likely extend to snow accumulation areas. The mass-loss equivalent (MLE) of the HKH glacial area caused by surface shortwave radiation absorption is estimated to be 10.4 Gt yr-1, which may contribute to 1.2% of the global sea level rise on annual average (2003–2009). Conclusions/Significance This work probably presents a first scene depicting the albedo variations over the whole HKH glacial area during the period 2000–2011. Most rapidly decreasing in albedo has been detected in the highest area, which deserves to be especially concerned. PMID:26039088

Measuring the expressed abundance of the three phases of water with an imaging spectrometer over melting snow

NASA Astrophysics Data System (ADS)

Green, Robert O.; Painter, Thomas H.; Roberts, Dar A.; Dozier, Jeff

2006-10-01

From imaging spectrometer data, we simultaneously estimate the abundance of the three phases of water in an environment that includes melting snow, basing the analysis on the spectral shift in the absorption coefficient between water vapor, liquid water, and ice at 940, 980, and 1030 nm respectively. We apply a spectral fitting algorithm that measures the expressed abundance of the three phases of water to a data set acquired by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) over Mount Rainier, Washington, on 14 June 1996. Precipitable water vapor varies from 1 mm over the summit of Mount Rainier to 10 mm over the lower valleys to the northwest. Equivalent path absorption of liquid water varies from 0 to 13 mm, with the zero values over rocky areas and high-elevation snow and the high values associated with liquid water held in vegetation canopies and in melting snow. Ice abundance varies from 0 to 30 mm equivalent path absorption in the snow- and glacier-covered portions of Mount Rainier. The water and ice abundances are related to the amount of liquid water and the sizes of the ice grains in the near-surface layer. Precision of the estimates, calculated over locally homogeneous areas, indicates an uncertainty of better than 1.5% for all three phases, except for liquid water in vegetation, where an optimally homogeneous site was not found. The analysis supports new strategies for hydrological research and applications as imaging spectrometers become more available.

Snow Pattern Delineation, Scaling, Fidelity, and Landscape Factors

NASA Astrophysics Data System (ADS)

Hiemstra, C. A.; Wagner, A. M.; Deeb, E. J.; Morriss, B. F.; Sturm, M.

2014-12-01

In many snow-covered landscapes, snow tends to be shallow or deep in the same locations year after year. As snowmelt progresses in spring, areas of shallow snow become snow-free earlier than areas with deep snow. This pattern (Sturm and Wagner 2010) could likely be used to inform or improve modeled snow depth estimates where ground measurements are not collected; however, we must be certain of their utility before ingesting them into model calculations. Do patterns, as we detect them, have a relationship with earlier measured snow distributions? Second, are certain areas on the landscape likely to yield patterns that are influenced too highly by melting to be useful? Our Imnavait Creek Study Area (11 by 19 km) is on Alaska's North Slope, where we have examined a vast library of spring satellite imagery (ranging from mostly snow-covered to mostly snow-free). Landsat TM Imagery has been collected from the early 1980s-present, and the temporal and spatial resolution is roughly two weeks and 30 m, respectively. High resolution satellite imagery (WorldView 1, WorldView 2, IKONOS) has been obtained from 2010-2013 for the same area with almost daily- to monthly-temporal and at 2.5 m spatial resolutions, respectively. We found that there is a striking similarity among patterns from year to year across the span of decades and resolutions. However, the relationship of pattern with observed snow depths was strong in some areas and less clear in others. Overall, we suspect spatial scaling, spatial mismatch, sampling errors, and melt patterns explain most of the areas of pattern and depth disparity.

Interannual variability of dust-mass loading and composition of dust deposited on snow cover in the San Juan Mountains, CO, USA: Insights into effects on snow melt

NASA Astrophysics Data System (ADS)

Goldstein, H. L.; Reynolds, R. L.; Derry, J.; Kokaly, R. F.; Moskowitz, B. M.

2017-12-01

Dust deposited on snow cover (DOS) in the American West can enhance snow-melt rates and advance the timing of melting, which together can result in earlier-than-normal runoff and overall smaller late-season water supplies. Understanding DOS properties and how they affect the absorption of solar radiation can lead to improved snow-melt models by accounting for important dust components. Here, we report on the interannual variability of DOS-mass loading, particle size, organic matter, and iron mineralogy, and their correspondences to laboratory-measured reflectance of samples from the Swamp Angel Study Plot in the San Juan Mountains, Colorado, USA. Samples were collected near the end of spring in water year 2009 (WY09) and from WY11-WY16, when dust layers deposited throughout the year had merged into one layer at the snow surface. Dust-mass loading on snow ranged 2-64 g/m2, mostly as particles with median sizes of 13-33 micrometers. Average reflectance values of DOS varied little across total (0.4 to 2.50 µm) and visible (0.4 to 0.7 µm) wavelengths at 0.30-0.45 and 0.19-0.27, respectively. Reflectance values lacked correspondence to particle-size. Total reflectance values inversely corresponded to concentrations of (1) organic matter content (4-20 weight %; r2 = 0.71) that included forms of black carbon and locally derived material such as pollen, and (2) magnetite (0.05 to 0.13 weight %; r2 = 0.44). Magnetite may be a surrogate for related dark, light-absorbing minerals. Concentrations of crystalline ferric oxide minerals (hematite+goethite) based on magnetic properties at room-temperature did not show inverse association to visible reflectance values. These ferric oxide measures, however, did not account for the amounts of nano-sized ferric oxides known to exist in these samples. Quantification of such nano-sized particles is required to evaluate their possible effects on visible reflectance. Nonetheless, our results emphasize that reflectance values of year

Albedo Drop on the Greenland Ice Sheet: Relative Impacts of Wet and Dry Snow Processes

NASA Astrophysics Data System (ADS)

Chen, J.; Polashenski, C.

2014-12-01

The energy balance of the Greenland Ice Sheet (GIS) is strongly impacted by changes in snow albedo. MODIS (Moderate Resolution Imaging Spectroradiometer) observations indicate that the GIS albedo has dropped since the early part of this century. We analyze data from the MODIS products MOD10A1 for broadband snow albedo and MOD09A1 for surface spectral reflectance since 2001 to better explain the physical mechanisms driving these changes. The MODIS products are filtered, and the data is masked using microwave-derived surface melt maps to isolate albedo changes due to dry snow processes from those driven by melt impacts. Results show that the majority of recent changes in the GIS albedo - even at high elevations - are driven by snow wetting rather than dry snow processes such as grain metamorphosis and aerosol impurity deposition. The spectral signature of the smaller changes occurring within dry snow areas suggests that grain metamorphosis dominates the albedo decline in these regions.

Spatio-temporal variability of snow water equivalent in the extra-tropical Andes Cordillera from distributed energy balance modeling and remotely sensed snow cover

NASA Astrophysics Data System (ADS)

Cornwell, E.; Molotch, N. P.; McPhee, J.

2016-01-01

Seasonal snow cover is the primary water source for human use and ecosystems along the extratropical Andes Cordillera. Despite its importance, relatively little research has been devoted to understanding the properties, distribution and variability of this natural resource. This research provides high-resolution (500 m), daily distributed estimates of end-of-winter and spring snow water equivalent over a 152 000 km2 domain that includes the mountainous reaches of central Chile and Argentina. Remotely sensed fractional snow-covered area and other relevant forcings are combined with extrapolated data from meteorological stations and a simplified physically based energy balance model in order to obtain melt-season melt fluxes that are then aggregated to estimate the end-of-winter (or peak) snow water equivalent (SWE). Peak SWE estimates show an overall coefficient of determination R2 of 0.68 and RMSE of 274 mm compared to observations at 12 automatic snow water equivalent sensors distributed across the model domain, with R2 values between 0.32 and 0.88. Regional estimates of peak SWE accumulation show differential patterns strongly modulated by elevation, latitude and position relative to the continental divide. The spatial distribution of peak SWE shows that the 4000-5000 m a.s.l. elevation band is significant for snow accumulation, despite having a smaller surface area than the 3000-4000 m a.s.l. band. On average, maximum snow accumulation is observed in early September in the western Andes, and in early October on the eastern side of the continental divide. The results presented here have the potential of informing applications such as seasonal forecast model assessment and improvement, regional climate model validation, as well as evaluation of observational networks and water resource infrastructure development.

Early results from NASA's SnowEx campaign

NASA Astrophysics Data System (ADS)

Kim, Edward; Gatebe, Charles; Hall, Dorothy; Misakonis, Amy; Elder, Kelly; Marshall, Hans Peter; Hiemstra, Chris; Brucker, Ludovic; Crawford, Chris; Kang, Do Hyuk; De Marco, Eugenia; Beckley, Matt; Entin, Jared

2017-04-01

SnowEx is a multi-year airborne snow campaign with the primary goal of addressing the question: How much water is stored in Earth's terrestrial snow-covered regions? Year 1 (2016-17) focuses on the distribution of snow-water equivalent (SWE) and the snow energy balance in a forested environment. The year 1 primary site is Grand Mesa and the secondary site is the Senator Beck Basin, both in western, Colorado, USA. Ten core sensors on four core aircraft will make observations using a broad suite of airborne sensors including active and passive microwave, and active and passive optical/infrared sensing techniques to determine the sensitivity and accuracy of these potential satellite remote sensing techniques, along with models, to measure snow under a range of forest conditions. SnowEx also includes an extensive range of ground truth measurements—in-situ samples, snow pits, ground based remote sensing measurements, and sophisticated new techniques. A detailed description of the data collected will be given and some early results will be presented. Seasonal snow cover is the largest single component of the cryosphere in areal extent (covering an average of 46M km2 of Earth's surface (31 % of land areas) each year). This seasonal snow has major societal impacts in the areas of water resources, natural hazards (floods and droughts), water security, and weather and climate. The only practical way to estimate the quantity of snow on a consistent global basis is through satellites. Yet, current space-based techniques underestimate storage of snow water equivalent (SWE) by as much as 50%, and model-based estimates can differ greatly vs. estimates based on remotely-sensed observations. At peak coverage, as much as half of snow-covered terrestrial areas involve forested areas, so quantifying the challenge represented by forests is important to plan any future snow mission. Single-sensor approaches may work for certain snow types and certain conditions, but not for others

Measured Black Carbon Deposition on the Sierra Nevada Snow Pack and Implication for Snow Pack Retreat

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hadley, O.L.; Corrigan, C.E.; Kirchstetter, T.W.

2010-01-12

Modeling studies show that the darkening of snow and ice by black carbon deposition is a major factor for the rapid disappearance of arctic sea ice, mountain glaciers and snow packs. This study provides one of the first direct measurements for the efficient removal of black carbon from the atmosphere by snow and its subsequent deposition to the snow packs of California. The early melting of the snow packs in the Sierras is one of the contributing factors to the severe water problems in California. BC concentrations in falling snow were measured at two mountain locations and in rain atmore » a coastal site. All three stations reveal large BC concentrations in precipitation, ranging from 1.7 ng/g to 12.9 ng/g. The BC concentrations in the air after the snow fall were negligible suggesting an extremely efficient removal of BC by snow. The data suggest that below cloud scavenging, rather than ice nuclei, was the dominant source of BC in the snow. A five-year comparison of BC, dust, and total fine aerosol mass concentrations at multiple sites reveals that the measurements made at the sampling sites were representative of large scale deposition in the Sierra Nevada. The relative concentration of iron and calcium in the mountain aerosol indicates that one-quarter to one-third of the BC may have been transported from Asia.« less

Resilience to Changing Snow Depth in a Shrubland Ecosystem.

NASA Astrophysics Data System (ADS)

Loik, M. E.

2008-12-01

Snowfall is the dominant hydrologic input for high elevations and latitudes of the arid- and semi-arid western United States. Sierra Nevada snowpack provides numerous important services for California, but is vulnerable to anthropogenic forcing of the coupled ocean-atmosphere system. GCM and RCM scenarios envision reduced snowpack and earlier melt under a warmer climate, but how will these changes affect soil and plant water relations and ecosystem processes? And, how resilient will this ecosystem be to short- and long-term forcing of snow depth and melt timing? To address these questions, our experiments utilize large- scale, long-term roadside snow fences to manipulate snow depth and melt timing in eastern California, USA. Interannual snow depth averages 1344 mm with a CV of 48% (April 1, 1928-2008). Snow fences altered snow melt timing by up to 18 days in high-snowfall years, and affected short-term soil moisture pulses less in low- than medium- or high-snowfall years. Sublimation in this arid location accounted for about 2 mol m- 2 of water loss from the snowpack in 2005. Plant water potential increased after the ENSO winter of 2005 and stayed relatively constant for the following three years, even after the low snowfall of winter 2007. Over the long-term, changes in snow depth and melt timing have impacted cover or biomass of Achnatherum thurberianum, Elymus elemoides, and Purshia tridentata. Growth of adult conifers (Pinus jeffreyi and Pi. contorta) was not equally sensitive to snow depth. Thus, complex interactions between snow depth, soil water inputs, physiological processes, and population patterns help drive the resilience of this ecosystem to changes in snow depth and melt timing.

Assessment of snow-glacier melt and rainfall contribution to stream runoff in Baspa Basin, Indian Himalaya.

PubMed

Gaddam, Vinay Kumar; Kulkarni, Anil V; Gupta, Anil Kumar

2018-02-20

Hydrological regimes of most of the Himalayan river catchments are poorly studied due to sparse hydro-meteorological data. Hence, stream runoff assessment becomes difficult for various socio-industrial activities in the Himalaya. Therefore, an attempt is made in this study to assess the stream runoff of Baspa River in Himachal Pradesh, India, by evaluating the contribution from snow-ice melt and rainfall runoff. The total volume of flow was computed for a period of 15 years, from 2000 to 2014, and validated with the long-term field discharge measurements, obtained from Jaipee Hydropower station (31° 32' 35.53″ N, 78° 00' 54.80″ E), at Kuppa barrage in the basin. The observations suggest (1) a good correlation (r 2  > 0.80) between the modeled runoff and field discharge measurements, and (2) out of the total runoff, 81.2% are produced by snowmelt, 11.4% by rainfall, and 7.4% from ice melt. The catchment receives ~75% of its total runoff in the ablation period (i.e., from May to September). In addition, an early snowmelt is observed in accumulation season during study period, indicating the significant influence of natural and anthropogenic factors on high-altitude areas.

What do We Know the Snow Darkening Effect Over Himalayan Glaciers?

NASA Technical Reports Server (NTRS)

Yasunari, T. J.; Lau, K.-U.; Koster, R. D.; Suarez, M.; Mahanama, S. P.; Gautam, R.; Kim, K. M.; Dasilva, A. M.; Colarco, P. R.

2011-01-01

The atmospheric absorbing aerosols such as dust, black carbon (BC), organic carbon (OC) are now well known warming factors in the atmosphere. However, when these aerosols deposit onto the snow surface, it causes darkening of snow and thereby absorbing more energy at the snow surface leading to the accelerated melting of snow. If this happens over Himalayan glacier surface, the glacier meltings are expected and may contribute the mass balance changes though the mass balance itself is more complicated issue. Glacier has mainly two parts: ablation and accumulation zones. Those are separated by the Equilibrium Line Altitude (ELA). Above and below ELA, snow accumulation and melting are dominant, respectively. The change of ELA will influence the glacier disappearance in future. In the Himalayan region, many glacier are debris covered glacier at the terminus (i.e., in the ablation zone). Debris is pieces of rock from local land and the debris covered parts are probably not affected by any deposition of the absorbing aerosols because the snow surface is already covered by debris (the debris covered parts have different mechanism of melting). Hence, the contribution of the snow darkening effect is considered to be most important "over non debris covered part" of the Himalayan glacier (i.e., over the snow or ice surface area). To discuss the whole glacier retreat, mass balance of each glacier is most important including the discussion on glacier flow, vertical compaction of glacier, melting amount, etc. The contribution of the snow darkening is mostly associated with "the snow/ice surface melting". Note that the surface melting itself is not always directly related to glacier retreats because sometimes melt water refreezes inside of the glacier. We should discuss glacier retreats in terms of not only the snow darkening but also other contributions to the mass balance.

Comparison of glacial and non-glacial-fed streams to evaluate the loading of persistent organic pollutants through seasonal snow/ice melt.

PubMed

Bizzotto, E C; Villa, S; Vaj, C; Vighi, M

2009-02-01

The release of persistent organic pollutants (PCBs, HCB, HCHs and DDTs) accumulated in Alpine glaciers, was studied during spring-summer 2006 on the Frodolfo glacial-fed stream (Italian Alps). Samples were also taken on a non-glacial stream in the same valley, to compare POP contribution from different water sources (glacier ice, recent snow and spring). In late spring and early summer (May, June) recent snow melting is the most important process. POP contamination is more affected by local emissions and transport, and comparable levels have been measured in both streams for all studied compounds. In late summer and autumn (July-October), the contribution of ice melting strongly increases. In the glacial-fed stream the concentration of chlorinated pesticides (HCHs and DDTs) is about one order of magnitude higher than in the non-glacial-fed. A different behaviour was observed for PCBs, characterised by a peak in June showing, in both streams, concentrations three orders of magnitude higher than the background levels measured in May and in October. This result should be attributed to local emissions rather than long range atmospheric transport (LRAT). This hypothesis is supported by the PCB congener profile in June strictly comparable to the most commonly used Aroclor technical mixtures. The different seasonal behaviour observed for the different groups of chemicals indicates the POP loading in glacial streams is a combined role of long range atmospheric transport and local emission.

Changes in the relation between snow station observations and basin scale snow water resources

NASA Astrophysics Data System (ADS)

Sexstone, G. A.; Penn, C. A.; Clow, D. W.; Moeser, D.; Liston, G. E.

2017-12-01

Snow monitoring stations that measure snow water equivalent or snow depth provide fundamental observations used for predicting water availability and flood risk in mountainous regions. In the western United States, snow station observations provided by the Natural Resources Conservation Service Snow Telemetry (SNOTEL) network are relied upon for forecasting spring and summer streamflow volume. Streamflow forecast accuracy has declined for many regions over the last several decades. Changes in snow accumulation and melt related to climate, land use, and forest cover are not accounted for in current forecasts, and are likely sources of error. Therefore, understanding and updating relations between snow station observations and basin scale snow water resources is crucial to improve accuracy of streamflow prediction. In this study, we investigated the representativeness of snow station observations when compared to simulated basin-wide snow water resources within the Rio Grande headwaters of Colorado. We used the combination of a process-based snow model (SnowModel), field-based measurements, and remote sensing observations to compare the spatiotemporal variability of simulated basin-wide snow accumulation and melt with that of SNOTEL station observations. Results indicated that observations are comparable to simulated basin-average winter precipitation but overestimate both the simulated basin-average snow water equivalent and snowmelt rate. Changes in the representation of snow station observations over time in the Rio Grande headwaters were also investigated and compared to observed streamflow and streamflow forecasting errors. Results from this study provide important insight in the context of non-stationarity for future water availability assessments and streamflow predictions.

Retention and radiative forcing of black carbon in Eastern Sierra Nevada snow

NASA Astrophysics Data System (ADS)

Sterle, K. M.; McConnell, J. R.; Dozier, J.; Edwards, R.; Flanner, M. G.

2012-06-01

Snow and glacier melt water contribute water resources to a fifth of Earth's population. Snow melt processes are sensitive not only to temperature changes, but also changes in albedo caused by deposition of particles such as refractory black carbon (rBC) and continental dust. The concentrations, sources, and fate of rBC particles in seasonal snow and its surface layers are uncertain, and thus an understanding of rBC's effect on snow albedo, melt processes, and radiation balance is critical for water management in a changing climate. Measurements of rBC in a sequence of snow pits and surface snow samples in the Eastern Sierra Nevada of California during the snow accumulation and melt seasons of 2009 show that concentrations of rBC were enhanced seven fold in surface snow (~25 ng g-1) compared to bulk values in the snow pack (~3 ng g-1). Unlike major ions which are preferentially released during initial melt, rBC and continental dust are retained in the snow, enhancing concentrations late into spring, until a final flush well into the melt period. We estimate a combined rBC and continental dust surface radiative forcing of 20 to 40 W m-2 during April and May, with dust likely contributing a greater share of the forcing than rBC.

Monitoring global snow cover

NASA Technical Reports Server (NTRS)

Armstrong, Richard; Hardman, Molly

1991-01-01

A snow model that supports the daily, operational analysis of global snow depth and age has been developed. It provides improved spatial interpolation of surface reports by incorporating digital elevation data, and by the application of regionalized variables (kriging) through the use of a global snow depth climatology. Where surface observations are inadequate, the model applies satellite remote sensing. Techniques for extrapolation into data-void mountain areas and a procedure to compute snow melt are also contained in the model.

A Distributed Snow Evolution Modeling System (SnowModel)

NASA Astrophysics Data System (ADS)

Liston, G. E.; Elder, K.

2004-12-01

A spatially distributed snow-evolution modeling system (SnowModel) has been specifically designed to be applicable over a wide range of snow landscapes, climates, and conditions. To reach this goal, SnowModel is composed of four sub-models: MicroMet defines the meteorological forcing conditions, EnBal calculates surface energy exchanges, SnowMass simulates snow depth and water-equivalent evolution, and SnowTran-3D accounts for snow redistribution by wind. While other distributed snow models exist, SnowModel is unique in that it includes a well-tested blowing-snow sub-model (SnowTran-3D) for application in windy arctic, alpine, and prairie environments where snowdrifts are common. These environments comprise 68% of the seasonally snow-covered Northern Hemisphere land surface. SnowModel also accounts for snow processes occurring in forested environments (e.g., canopy interception related processes). SnowModel is designed to simulate snow-related physical processes occurring at spatial scales of 5-m and greater, and temporal scales of 1-hour and greater. These include: accumulation from precipitation; wind redistribution and sublimation; loading, unloading, and sublimation within forest canopies; snow-density evolution; and snowpack ripening and melt. To enhance its wide applicability, SnowModel includes the physical calculations required to simulate snow evolution within each of the global snow classes defined by Sturm et al. (1995), e.g., tundra, taiga, alpine, prairie, maritime, and ephemeral snow covers. The three, 25-km by 25-km, Cold Land Processes Experiment (CLPX) mesoscale study areas (MSAs: Fraser, North Park, and Rabbit Ears) are used as SnowModel simulation examples to highlight model strengths, weaknesses, and features in forested, semi-forested, alpine, and shrubland environments.

An Integrated Modeling System for Estimating Glacier and Snow Melt Driven Streamflow from Remote Sensing and Earth System Data Products in the Himalayas

NASA Technical Reports Server (NTRS)

Brown, M. E.; Racoviteanu, A. E.; Tarboton, D. G.; Sen Gupta, A.; Nigro, J.; Policelli, F.; Habib, S.; Tokay, M.; Shrestha, M. S.; Bajracharya, S.

2014-01-01

Quantification of the contribution of the hydrologic components (snow, ice and rain) to river discharge in the Hindu Kush Himalayan (HKH) region is important for decision-making in water sensitive sectors, and for water resources management and flood risk reduction. In this area, access to and monitoring of the glaciers and their melt outflow is challenging due to difficult access, thus modeling based on remote sensing offers the potential for providing information to improve water resources management and decision making. This paper describes an integrated modeling system developed using downscaled NASA satellite based and earth system data products coupled with in-situ hydrologic data to assess the contribution of snow and glaciers to the flows of the rivers in the HKH region. Snow and glacier melt was estimated using the Utah Energy Balance (UEB) model, further enhanced to accommodate glacier ice melt over clean and debris-covered tongues, then meltwater was input into the USGS Geospatial Stream Flow Model (Geo- SFM). The two model components were integrated into Better Assessment Science Integrating point and Nonpoint Sources modeling framework (BASINS) as a user-friendly open source system and was made available to countries in high Asia. Here we present a case study from the Langtang Khola watershed in the monsoon-influenced Nepal Himalaya, used to validate our energy balance approach and to test the applicability of our modeling system. The snow and glacier melt model predicts that for the eight years used for model evaluation (October 2003-September 2010), the total surface water input over the basin was 9.43 m, originating as 62% from glacier melt, 30% from snowmelt and 8% from rainfall. Measured streamflow for those years were 5.02 m, reflecting a runoff coefficient of 0.53. GeoSFM simulated streamflow was 5.31 m indicating reasonable correspondence between measured and model confirming the capability of the integrated system to provide a quantification

Air temperature thresholds to evaluate snow melting at the surface of Alpine glaciers by T-index models: the case study of Forni Glacier (Italy)

NASA Astrophysics Data System (ADS)

Senese, A.; Maugeri, M.; Vuillermoz, E.; Smiraglia, C.; Diolaiuti, G.

2014-03-01

The glacier melt conditions (i.e.: null surface temperature and positive energy budget) can be assessed by analyzing meteorological and energy data acquired by a supraglacial Automatic Weather Station (AWS). In the case this latter is not present the assessment of actual melting conditions and the evaluation of the melt amount is difficult and simple methods based on T-index (or degree days) models are generally applied. These models require the choice of a correct temperature threshold. In fact, melt does not necessarily occur at daily air temperatures higher than 273.15 K. In this paper, to detect the most indicative threshold witnessing melt conditions in the April-June period, we have analyzed air temperature data recorded from 2006 to 2012 by a supraglacial AWS set up at 2631 m a.s.l. on the ablation tongue of the Forni Glacier (Italian Alps), and by a weather station located outside the studied glacier (at Bormio, a village at 1225 m a.s.l.). Moreover we have evaluated the glacier energy budget and the Snow Water Equivalent (SWE) values during this time-frame. Then the snow ablation amount was estimated both from the surface energy balance (from supraglacial AWS data) and from T-index method (from Bormio data, applying the mean tropospheric lapse rate and varying the air temperature threshold) and the results were compared. We found that the mean tropospheric lapse rate permits a good and reliable reconstruction of glacier air temperatures and the major uncertainty in the computation of snow melt is driven by the choice of an appropriate temperature threshold. From our study using a 5.0 K lower threshold value (with respect to the largely applied 273.15 K) permits the most reliable reconstruction of glacier melt.

Melting in Martian Snowbanks

NASA Technical Reports Server (NTRS)

Zent, A. P.; Sutter, B.

2005-01-01

Precipitation as snow is an emerging paradigm for understanding water flow on Mars, which gracefully resolves many outstanding uncertainties in climatic and geomorphic interpretation. Snowfall does not require a powerful global greenhouse to effect global precipitation. It has long been assumed that global average temperatures greater than 273K are required to sustain liquid water at the surface via rainfall and runoff. Unfortunately, the best greenhouse models to date predict global mean surface temperatures early in Mars' history that differ little from today's, unless exceptional conditions are invoked. Snowfall however, can occur at temperatures less than 273K; all that is required is saturation of the atmosphere. At global temperatures lower than 273K, H2O would have been injected into the atmosphere by impacts and volcanic eruptions during the Noachian, and by obliquity-driven climate oscillations more recently. Snow cover can accumulate for a considerable period, and be available for melting during local spring and summer, unless sublimation rates are sufficient to remove the entire snowpack. We decided to explore the physics that controls the melting of snow in the high-latitude regions of Mars to understand the frequency and drainage of snowmelt in the high martian latitudes.

Energy balance-based distributed modeling of snow and glacier melt runoff for the Hunza river basin in the Pakistan Karakoram Himalayan region

NASA Astrophysics Data System (ADS)

Shrestha, M.; Wang, L.; Koike, T.; Xue, Y.; Hirabayashi, Y.; Ahmad, S.

2012-12-01

A spatially distributed biosphere hydrological model with energy balance-based multilayer snow physics and multilayer glacier model, including debris free and debris covered surface (enhanced WEB-DHM-S) has been developed and applied to the Hunza river basin in the Pakistan Karakoram Himalayan region, where about 34% of the basin area is covered by glaciers. The spatial distribution of seasonal snow and glacier cover, snow and glacier melt runoff along with rainfall-contributed runoff, and glacier mass balances are simulated. The simulations are carried out at hourly time steps and at 1-km spatial resolution for the two hydrological years (2002-2003) with the use of APHRODITE precipitation dataset, observed temperature, and other atmospheric forcing variables from the Global Land Data Assimilation System (GLDAS). The pixel-to-pixel comparisons for the snow-free and snow-covered grids over the region reveal that the simulation agrees well with the Moderate Resolution Imaging Spectroradiometer (MODIS) eight-day maximum snow-cover extent data (MOD10A2) with an accuracy of 83% and a positive bias of 2.8 %. The quantitative evaluation also shows that the model is able to reproduce the river discharge satisfactorily with Nash efficiency of 0.92. It is found that the contribution of rainfall to total streamflow is small (about 10-12%) while the contribution of snow and glacier is considerably large (35-40% for snowmelt and 50-53% for glaciermelt, respectively). The model simulates the state of snow and glaciers at each model grid prognostically and thus can estimate the net annual mass balance. The net mass balance varies from -2 m to +2 m water equivalent. Additionally, the hypsography analysis for the equilibrium line altitude (ELA) suggests that the average ELA in this region is about 5700 m with substantial variation from glacier to glacier and region to region. This study is the first to adopt a distributed biosphere hydrological model with the energy balance- based

Analyzing the importance of wind-blown snow accumulations on Mount

NASA Astrophysics Data System (ADS)

Nestler, Alexander; Huss, Matthias; Ambartsumian, Rouben; Hambarian, Artak; Mohr, Sandra; Santi, Flavio

2013-04-01

Armenia's climate has a predominantly continental character with high amounts of precipitation and low temperatures during wintertime and a lack of precipitation together with high temperatures during summer. On the volcano Mount Aragatz, snow is relocated by strong winds into massive accumulations between 2500 and 4100 m a.s.l. during the winter season. These snow accumulations appear every winter in regular patterns as cornices on the lee side of sharp edges, such as those of ridges and canyons, which are arranged in a radial manner around the central crater. The biggest cornices almost outlast the hot period and provide considerable amounts of melt water until they disappear completely by the end of August. Snow melt water is known to have a high economic importance for agriculture on the slopes of Mount Aragatz and in the surroundings of Armenia's captial Yerewan. The aim of this study is to estimate the quantity of water naturally stored as snow on Mount Aragatz, and to what degree the use of geotextiles can prolong the lives of these snow accumulations. The characteristics and the spatial distribution of snow cornices on Mount Aragatz were determined using classical glaciological methods in June/July 2011 and 2012, involving snow depth soundings, water equivalent measurements and snow melt monitoring using ablation stakes, together with GPS mappings and classifications obtained from satellite images of the snow cornices. The combination of these data with ASTER DEMs and local weather data allows the modelling of the formation of wind-driven snow accumulations. Statistical relationships between the measured extent and volume of the snow cornices and surface parameters such as slope, aspect and curvature are established. In order to analyze the meltdown of the snow accumulations and the consequent impacts on runoff generation and the hydrological regime, a glacio-hydrological model integrating topographic parameters and meteorological data is applied. The

Finland Validation of the New Blended Snow Product

NASA Technical Reports Server (NTRS)

Kim, E. J.; Casey, K. A.; Hallikainen, M. T.; Foster, J. L.; Hall, D. K.; Riggs, G. A.

2008-01-01

As part of an ongoing effort to validate satellite remote sensing snow products for the recentlydeveloped U.S. Air Force Weather Agency (AFWA) - NASA blended snow product, Satellite and in-situ data for snow extent and snow water equivalent (SWE) are evaluated in Finland for the 2006-2007 snow season Finnish Meteorological Institute (FMI) daily weather station data and Finnish Environment Institute (SYKE) bi-monthly snow course data are used as ground truth. Initial comparison results display positive agreement between the AFWA NASA Snow Algorithm (ANSA) snow extent and SWE maps and in situ data, with discrepancies in accordance with known AMSR-E and MODIS snow mapping limitations. Future ANSA product improvement plans include additional validation and inclusion of fractional snow cover in the ANSA data product. Furthermore, the AMSR-E 19 GHz (horizontal channel) with the difference between ascending and descending satellite passes (Diurnal Amplitude Variations, DAV) will be used to detect the onset of melt, and QuikSCAT scatterometer data (14 GHz) will be used to map areas of actively melting snow.

Sublimation From Snow in Northern Environments

NASA Astrophysics Data System (ADS)

Pomeroy, J. W.

2002-12-01

Sublimation from snow is an often neglected component of water and energy balances. Research under the Mackenzie GEWEX Study has attempted to understand the snow and atmospheric processes controlling sublimation and to estimate the magnitude of sublimation in high latitude catchments. Eddy correlation units were used to measure vertical water vapour fluxes from a high latitude boreal forest, snow-covered tundra and shrub-covered tundra in Wolf Creek Research Basin, near Whitehorse Yukon, Territory Canada. Over Jan-Apr. water vapour fluxes from the forest canopy amounted to 18.3 mm, a significant loss from winter snowfall of 54 mm. Most of this loss occurred when the canopy was snow-covered. The weight of snow measured on a suspended, weighed tree indicates that this flux is dominated by sublimation of intercepted snow. In the melt period (April), water vapour fluxes were uniformly small ranging from 0.21 mm/day on the tundra slope, 0.23 mm/day for the forest and 0.27 mm/day for the shrub-tundra. During the melt period the forest and shrub canopies was snow-free and roots were frozen, so the primary source of water vapour from all sites was the surface snow.

The Airborne Snow Observatory: fusion of scanning lidar, imaging spectrometer, and physically-based modeling for mapping snow water equivalent and snow albedo

USDA-ARS?s Scientific Manuscript database

Snow cover and its melt dominate regional climate and water resources in many of the world’s mountainous regions. Snowmelt timing and magnitude in mountains tend to be controlled by absorption of solar radiation and snow water equivalent, respectively, and yet both of these are very poorly known ev...

Spring snow conditions on Arctic sea ice north of Svalbard, during the Norwegian Young Sea ICE (N-ICE2015) expedition

NASA Astrophysics Data System (ADS)

Gallet, Jean-Charles; Merkouriadi, Ioanna; Liston, Glen E.; Polashenski, Chris; Hudson, Stephen; Rösel, Anja; Gerland, Sebastian

2017-10-01

Snow is crucial over sea ice due to its conflicting role in reflecting the incoming solar energy and reducing the heat transfer so that its temporal and spatial variability are important to estimate. During the Norwegian Young Sea ICE (N-ICE2015) campaign, snow physical properties and variability were examined, and results from April until mid-June 2015 are presented here. Overall, the snow thickness was about 20 cm higher than the climatology for second-year ice, with an average of 55 ± 27 cm and 32 ± 20 cm on first-year ice. The average density was 350-400 kg m-3 in spring, with higher values in June due to melting. Due to flooding in March, larger variability in snow water equivalent was observed. However, the snow structure was quite homogeneous in spring due to warmer weather and lower amount of storms passing over the field camp. The snow was mostly consisted of wind slab, faceted, and depth hoar type crystals with occasional fresh snow. These observations highlight the more dynamic character of evolution of snow properties over sea ice compared to previous observations, due to more variable sea ice and weather conditions in this area. The snowpack was isothermal as early as 10 June with the first onset of melt clearly identified in early June. Based on our observations, we estimate than snow could be accurately represented by a three to four layers modeling approach, in order to better consider the high variability of snow thickness and density together with the rapid metamorphose of the snow in springtime.

Snow effects on alpine vegetation in the Qinghai-Tibetan Plateau

USGS Publications Warehouse

Wang, Kun; Zhang, Li; Qiu, Yubao; Ji, Lei; Tian, Feng; Wang, Cuizhen; Wang, Zhiyong

2013-01-01

Understanding the relationships between snow and vegetation is important for interpretation of the responses of alpine ecosystems to climate changes. The Qinghai-Tibetan Plateau is regarded as an ideal area due to its undisturbed features with low population and relatively high snow cover. We used 500 m Moderate Resolution Imaging Spectroradiometer (MODIS) datasets during 2001–2010 to examine the snow–vegetation relationships, specifically, (1) the influence of snow melting date on vegetation green-up date and (2) the effects of snow cover duration on vegetation greenness. The results showed that the alpine vegetation responded strongly to snow phenology (i.e., snow melting date and snow cover duration) over large areas of the Qinghai-Tibetan Plateau. Snow melting date and vegetation green-up date were significantly correlated (p < 0.1) in 39.9% of meadow areas (accounting for 26.2% of vegetated areas) and 36.7% of steppe areas (28.1% of vegetated areas). Vegetation growth was influenced by different seasonal snow cover durations (SCDs) in different regions. Generally, the December–February and March–May SCDs played a significantly role in vegetation growth, both positively and negatively, depending on different water source regions. Snow's positive impact on vegetation was larger than the negative impact.

Effects of BC, Icelandic volcanic sand and glaciogenic silt on the spectral reflectance and melt of seasonal Arctic snow (SoS-2013 experiment)

NASA Astrophysics Data System (ADS)

Meinander, O.; Virkkula, A.; Svensson, J.; Kivekäs, N.; Aarva, A.; Dagsson Waldhauserová, P.; Arnalds; Hannula, H.; Anttila, K.; Peltoniemi, J.; Gritsevich, M.; Hakala, T.; Lahtinen, P.; Järvinen, O.; Kaartinen, H.; Lihavainen, H.; Kontu, A.; Neitola, K.; Raaterova, A.; Bichell, R.; De Leeuw, G.

2013-12-01

The Soot on the Snow (SoS-2013) experiment was carried out in Sodankylä (67°22'N, 26°39'E, 179 m a.s.l.), north of the Arctic Circle, to study the effects of deposition of Black Carbon (BC), Icelandic volcanic sand and glaciogenic silt on the surface albedo and melt of seasonal snow. The BC was soot originating from chimneys above residential wood-burning fireplaces in Helsinki, except on one experimental spot the soot was from a chimney of an oil burner, and on one from the a peat-burning power plant. The volcanic sand was near black mixture of the volcanic ash of glaciofluvial nature, originating from under the Myrdalsjokull glacier, which may be mixed with the ash of the Eyjafjallajokull eruption in 2010 and the Grimsvotn eruption in 2011. The glaciogenic silt was lighter in colour, from light-brown to slightly yellowish, consisting mainly of silt and some coarse clay sized particles, capable of being transported and deposited on the local glaciers as well as several hundreds of kilometres towards the Europe. The SoS-2013 experiment was undertaken at the Sodankylä airport with a large, flat, open space and untouched snow. Thirteen spots of different concentrations of soot, volcanic sand, and silt were generated by blowing the impurities on natural snow. We also had an untouched reference measurement spot. The impurities were deposited only once to each spot, and thereafter the spots were monitored until the snow was melted. The sites were left to develop naturally, introducing as little disturbance as possible. Continuous broadband albedo was measured using pyranometers installed on seven spots. Snow samples were collected for their elemental carbon (EC) and organic (OC) concentration analysis with the Thermal/Optical Carbon Aerosol Analyzer (OC/EC), following the NIOSH 5040 protocol. The spectral reflectance of the melting snow was measured using two ASD spectrometers, one measuring in the UV-B spectral range (325-1075 nm), and the other from UV-A up to IR

Evaluation of distributed hydrologic impacts of temperature-index and energy-based snow models

USDA-ARS?s Scientific Manuscript database

Proper characterizations of snow melt and accumulation processes in the snow-dominated mountain environment are needed to understand and predict spatiotemporal distribution of water cycle components. Two commonly used strategies in modeling of snow accumulation and melt are the full energy based and...

Idiosyncratic Responses of High Arctic Plants to Changing Snow Regimes

PubMed Central

Rumpf, Sabine B.; Semenchuk, Philipp R.; Dullinger, Stefan; Cooper, Elisabeth J.

2014-01-01

The Arctic is one of the ecosystems most affected by climate change; in particular, winter temperatures and precipitation are predicted to increase with consequent changes to snow cover depth and duration. Whether the snow-free period will be shortened or prolonged depends on the extent and temporal patterns of the temperature and precipitation rise; resulting changes will likely affect plant growth with cascading effects throughout the ecosystem. We experimentally manipulated snow regimes using snow fences and shoveling and assessed aboveground size of eight common high arctic plant species weekly throughout the summer. We demonstrated that plant growth responded to snow regime, and that air temperature sum during the snow free period was the best predictor for plant size. The majority of our studied species showed periodic growth; increases in plant size stopped after certain cumulative temperatures were obtained. Plants in early snow-free treatments without additional spring warming were smaller than controls. Response to deeper snow with later melt-out varied between species and categorizing responses by growth forms or habitat associations did not reveal generic trends. We therefore stress the importance of examining responses at the species level, since generalized predictions of aboveground growth responses to changing snow regimes cannot be made. PMID:24523859

Idiosyncratic responses of high Arctic plants to changing snow regimes.

PubMed

Rumpf, Sabine B; Semenchuk, Philipp R; Dullinger, Stefan; Cooper, Elisabeth J

2014-01-01

The Arctic is one of the ecosystems most affected by climate change; in particular, winter temperatures and precipitation are predicted to increase with consequent changes to snow cover depth and duration. Whether the snow-free period will be shortened or prolonged depends on the extent and temporal patterns of the temperature and precipitation rise; resulting changes will likely affect plant growth with cascading effects throughout the ecosystem. We experimentally manipulated snow regimes using snow fences and shoveling and assessed aboveground size of eight common high arctic plant species weekly throughout the summer. We demonstrated that plant growth responded to snow regime, and that air temperature sum during the snow free period was the best predictor for plant size. The majority of our studied species showed periodic growth; increases in plant size stopped after certain cumulative temperatures were obtained. Plants in early snow-free treatments without additional spring warming were smaller than controls. Response to deeper snow with later melt-out varied between species and categorizing responses by growth forms or habitat associations did not reveal generic trends. We therefore stress the importance of examining responses at the species level, since generalized predictions of aboveground growth responses to changing snow regimes cannot be made.

Influence of snowpack and melt energy heterogeneity on snow cover depletion and snowmelt runoff simulation in a cold mountain environment

NASA Astrophysics Data System (ADS)

DeBeer, Chris M.; Pomeroy, John W.

2017-10-01

The spatial heterogeneity of mountain snow cover and ablation is important in controlling patterns of snow cover depletion (SCD), meltwater production, and runoff, yet is not well-represented in most large-scale hydrological models and land surface schemes. Analyses were conducted in this study to examine the influence of various representations of snow cover and melt energy heterogeneity on both simulated SCD and stream discharge from a small alpine basin in the Canadian Rocky Mountains. Simulations were performed using the Cold Regions Hydrological Model (CRHM), where point-scale snowmelt computations were made using a snowpack energy balance formulation and applied to spatial frequency distributions of snow water equivalent (SWE) on individual slope-, aspect-, and landcover-based hydrological response units (HRUs) in the basin. Hydrological routines were added to represent the vertical and lateral transfers of water through the basin and channel system. From previous studies it is understood that the heterogeneity of late winter SWE is a primary control on patterns of SCD. The analyses here showed that spatial variation in applied melt energy, mainly due to differences in net radiation, has an important influence on SCD at multiple scales and basin discharge, and cannot be neglected without serious error in the prediction of these variables. A single basin SWE distribution using the basin-wide mean SWE (SWE ‾) and coefficient of variation (CV; standard deviation/mean) was found to represent the fine-scale spatial heterogeneity of SWE sufficiently well. Simulations that accounted for differences in (SWE ‾) among HRUs but neglected the sub-HRU heterogeneity of SWE were found to yield similar discharge results as simulations that included this heterogeneity, while SCD was poorly represented, even at the basin level. Finally, applying point-scale snowmelt computations based on a single SWE depth for each HRU (thereby neglecting spatial differences in internal

Comparison of Passive Microwave-Derived Early Melt Onset Records on Arctic Sea Ice

NASA Technical Reports Server (NTRS)

Bliss, Angela C.; Miller, Jeffrey A.; Meier, Walter N.

2017-01-01

Two long records of melt onset (MO) on Arctic sea ice from passive microwave brightness temperatures (Tbs) obtained by a series of satellite-borne instruments are compared. The Passive Microwave (PMW) method and Advanced Horizontal Range Algorithm (AHRA) detect the increase in emissivity that occurs when liquid water develops around snow grains at the onset of early melting on sea ice. The timing of MO on Arctic sea ice influences the amount of solar radiation absorbed by the ice-ocean system throughout the melt season by reducing surface albedos in the early spring. This work presents a thorough comparison of these two methods for the time series of MO dates from 1979through 2012. The methods are first compared using the published data as a baseline comparison of the publically available data products. A second comparison is performed on adjusted MO dates we produced to remove known differences in inter-sensor calibration of Tbs and masking techniques used to develop the original MO date products. These adjustments result in a more consistent set of input Tbs for the algorithms. Tests of significance indicate that the trends in the time series of annual mean MO dates for the PMW and AHRA are statistically different for the majority of the Arctic Ocean including the Laptev, E. Siberian, Chukchi, Beaufort, and central Arctic regions with mean differences as large as 38.3 days in the Barents Sea. Trend agreement improves for our more consistent MO dates for nearly all regions. Mean differences remain large, primarily due to differing sensitivity of in-algorithm thresholds and larger uncertainties in thin-ice regions.

Remote Sensing of Snow Cover. Section; Snow Extent

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Frei, Allan; Drey, Stephen J.

2012-01-01

Snow was easily identified in the first image obtained from the Television Infrared Operational Satellite-1 (TIROS-1) weather satellite in 1960 because the high albedo of snow presents a good contrast with most other natural surfaces. Subsequently, the National Oceanic and Atmospheric Administration (NOAA) began to map snow using satellite-borne instruments in 1966. Snow plays an important role in the Earth s energy balance, causing more solar radiation to be reflected back into space as compared to most snow-free surfaces. Seasonal snow cover also provides a critical water resource through meltwater emanating from rivers that originate from high-mountain areas such as the Tibetan Plateau. Meltwater from mountain snow packs flows to some of the world s most densely-populated areas such as Southeast Asia, benefiting over 1 billion people (Immerzeel et al., 2010). In this section, we provide a brief overview of the remote sensing of snow cover using visible and near-infrared (VNIR) and passive-microwave (PM) data. Snow can be mapped using the microwave part of the electromagnetic spectrum, even in darkness and through cloud cover, but at a coarser spatial resolution than when using VNIR data. Fusing VNIR and PM algorithms to produce a blended product offers synergistic benefits. Snow-water equivalent (SWE), snow extent, and melt onset are important parameters for climate models and for the initialization of atmospheric forecasts at daily and seasonal time scales. Snowmelt data are also needed as input to hydrological models to improve flood control and irrigation management.

Water-soluble elements in snow and ice on Mt. Yulong.

PubMed

Niu, Hewen; Kang, Shichang; Shi, Xiaofei; He, Yuanqing; Lu, Xixi; Shi, Xiaoyi; Paudyal, Rukumesh; Du, Jiankuo; Wang, Shijin; Du, Jun; Chen, Jizu

2017-01-01

Melting of high-elevation glaciers can be accelerated by the deposition of light-absorbing aerosols (e.g., organic carbon, mineral dust), resulting in significant reductions of the surface albedo on glaciers. Organic carbon deposited in glaciers is of great significance to global carbon cycles, snow photochemistry, and air-snow exchange processes. In this work, various snow and ice samples were collected at high elevation sites (4300-4850masl) from Mt. Yulong on the southeastern Tibetan Plateau in 2015. These samples were analyzed for water-soluble organic carbon (DOC), total nitrogen (TN), and water-soluble inorganic ions (WSIs) to elucidate the chemical species and compositions of the glaciers in the Mt. Yulong region. Generally, glacial meltwater had the lowest DOC content (0.39mgL -1 ), while fresh snow had the highest (2.03mgL -1 ) among various types of snow and ice samples. There were obvious spatial and temporal trends of DOC and WSIs in glaciers. The DOC and TN concentrations decreased in the order of fresh snow, snow meltwater, snowpit, and surface snow, resulting from the photolysis of DOC and snow's quick-melt effects. The surface snow had low DOC and TN depletion ratios in the melt season; specifically, the ratios were -0.79 and -0.19mgL -1 d -1 , respectively. In the winter season, the ratios of DOC and TN were remarkably higher, with values of -0.20mgL -1 d -1 and -0.08mgL -1 d -1 , respectively. A reduction of the DOC and TN content in glaciers was due to snow's quick melt and sublimation. Deposition of these light-absorbing impurities (LAPs) in glaciers might accelerate snowmelt and even glacial retreat. Copyright © 2016 Elsevier B.V. All rights reserved.

Response of snow-dependent hydrologic extremes to continued global warming

DOE Office of Scientific and Technical Information (OSTI.GOV)

Diffenbaugh, Noah; Scherer, Martin; Ashfaq, Moetasim

2012-01-01

Snow accumulation is critical for water availability in the Northern Hemisphere1,2, raising concern that global warming could have important impacts on natural and human systems in snow-dependent regions1,3. Although regional hydrologic changes have been observed (for example, refs 1,3 5), the time of emergence of extreme changes in snow accumulation and melt remains a key unknown for assessing climate- change impacts3,6,7. We find that the CMIP5 global climate model ensemble exhibits an imminent shift towards low snow years in the Northern Hemisphere, with areas of western North America, northeastern Europe and the Greater Himalaya showing the strongest emergence during themore » near- termdecadesandat2 Cglobalwarming.Theoccurrenceof extremely low snow years becomes widespread by the late twenty-first century, as do the occurrences of extremely high early-season snowmelt and runoff (implying increasing flood risk), and extremely low late-season snowmelt and runoff (implying increasing water stress). Our results suggest that many snow-dependent regions of the Northern Hemisphere are likely to experience increasing stress from low snow years within the next three decades, and from extreme changes in snow-dominated water resources if global warming exceeds 2 C above the pre-industrial baseline.« less

Extracting fields snow coverage information with HJ-1A/B satellites data

NASA Astrophysics Data System (ADS)

Dong, Wenquan; Meng, Jihua

2015-10-01

The distribution and change of snow coverage are sensitive factors of climate change. In northeast part of China, farmlands are still covered with snow in spring. Since sowing activity can only be done when the snow melted, fields snow coverage monitoring provides reference for the determination of sowing date. Because of the restriction of the sensors and application requirements, current researches on remote sensing of snow focus more on the study of musicale and large scale, rather than the study of small scale, and especially research on snow melting period is rarely reported.HJ-1A/B satellites are parts of little satellite constellation, focusing on environment and disaster monitoring and meteorological forecast. Compared to other data sources, HJ-1A/B satellites both have comparatively higher temporal and spatial resolution and are more conducive to monitor the variations of melting snow coverage at small watershed. This paper was based on HJ-1A/1B data, taking Hongxing farm of Bei'an, Heilongjiang Province, China as the study area. In this paper, we exploited the methods for extraction of snow cover information on farmland in two cases, both HJ-1A/1B CCD with HJ-1B IRS data and just HJ-1A/1B CCD data. The reason we chose the two cases is that, the two optical satellites HJ-1A/B are capable of providing a whole territory coverage period in visible light spectrum in two days, infrared spectrum in four days. So sometimes we can only obtain CCD image. In this case, the method of normalized snow index cannot be used to extract snow coverage information. Using HJ-1A/1B CCD with HJ-1B IRS data, combined with the theory of snow remote sensing monitoring, this paper analyzed spectral response characteristics of HJ-1A/1B satellites data, then the widely used Normalized Difference Snow Index(NDSI) and S3 Index were quoted to the HJ-1A/1B satellites data. The NDSI uses reflectance values of Red and SWIR spectral bands of HJ-1B, and S3 index uses reflectance values of

Gullies on Mars: Origin by Snow and Ice Melting and Potential for Life Based on Possible Analogs from Devon Island, High Arctic

NASA Technical Reports Server (NTRS)

Lee, Pascal; Cockell, Charles S.; McKay, Christopher P.

2004-01-01

Gullies on Devon Island, High Arctic, which form by melting of transient surface ice and snow covers and offer morphologic and contextual analogs for gullies reported on Mars are reported to display enhancements in biological activity in contrast to surrounding polar desert terrain.

Soot on snow in Iceland: First results on black carbon and organic carbon in Iceland 2016 snow and ice samples, including the glacier Solheimajökull

NASA Astrophysics Data System (ADS)

Meinander, Outi; Dagsson-Waldhauserova, Pavla; Gritsevich, Maria; Aurela, Minna; Arnalds, Olafur; Dragosics, Monika; Virkkula, Aki; Svensson, Jonas; Peltoniemi, Jouni; Kontu, Anna; Kivekäs, Niku; Leppäranta, Matti; de Leeuw, Gerrit; Laaksonen, Ari; Lihavainen, Heikki; Arslan, Ali N.; Paatero, Jussi

2017-04-01

New results on black carbon (BC) and organic carbon (OC) on snow and ice in Iceland in 2016 will be presented in connection to our earlier results on BC and OC on Arctic seasonal snow surface, and in connection to our 2013 and 2016 experiments on effects of light absorbing impurities, including Icelandic dust, on snow albedo, melt and density. Our sampling included the glacier Solheimajökull in Iceland. The mass balance of this glacier is negative and it has been shrinking during the last 20 years by 900 meters from its southwestern corner. Icelandic snow and ice samples were not expected to contain high concentrations of BC, as power generation with domestic renewable water and geothermal power energy sources cover 80 % of the total energy consumption in Iceland. Our BC results on filters analyzed with a Thermal/Optical Carbon Aerosol Analyzer (OC/EC) confirm this assumption. Other potential soot sources in Iceland include agricultural burning, industry (aluminum and ferroalloy production and fishing industry), open burning, residential heating and transport (shipping, road traffic, aviation). On the contrary to low BC, we have found high concentrations of organic carbon in our Iceland 2016 samples. Some of the possible reasons for those will be discussed in this presentation. Earlier, we have measured and reported unexpectedly low snow albedo values of Arctic seasonally melting snow in Sodankylä, north of Arctic Circle. Our low albedo results of melting snow have been confirmed by three independent data sets. We have explained these low values to be due to: (i) large snow grain sizes up to 3 mm in diameter (seasonally melting snow); (ii) meltwater surrounding the grains and increasing the effective grain size; (iii) absorption caused by impurities in the snow, with concentration of elemental carbon (black carbon) in snow of 87 ppb, and organic carbon 2894 ppb. The high concentrations of carbon were due to air masses originating from the Kola Peninsula, Russia

Measuring snow cover using satellite imagery during 1973 and 1974 melt season: North Santiam, Boise, and Upper Snake Basins, phase 1. [LANDSAT satellites, imaging techniques

NASA Technical Reports Server (NTRS)

Wiegman, E. J.; Evans, W. E.; Hadfield, R.

1975-01-01

Measurements are examined of snow coverage during the snow-melt season in 1973 and 1974 from LANDSAT imagery for the three Columbia River Subbasins. Satellite derived snow cover inventories for the three test basins were obtained as an alternative to inventories performed with the current operational practice of using small aircraft flights over selected snow fields. The accuracy and precision versus cost for several different interactive image analysis procedures was investigated using a display device, the Electronic Satellite Image Analysis Console. Single-band radiance thresholding was the principal technique employed in the snow detection, although this technique was supplemented by an editing procedure involving reference to hand-generated elevation contours. For each data and view measured, a binary thematic map or "mask" depicting the snow cover was generated by a combination of objective and subjective procedures. Photographs of data analysis equipment (displays) are shown.

Sentinels for snow science

NASA Astrophysics Data System (ADS)

Gascoin, S.; Grizonnet, M.; Baba, W. M.; Hagolle, O.; Fayad, A.; Mermoz, S.; Kinnard, C.; Fatima, K.; Jarlan, L.; Hanich, L.

2017-12-01

Current spaceborne sensors do not allow retrieving the snow water equivalent in mountain regions, "the most important unsolved problem in snow hydrology" (Dozier, 2016). While the NASA is operating an airborne mission to survey the SWE in the western USA, elsewhere, however, snow scientists and water managers do not have access to routine SWE measurements at the scale of a mountain range. In this presentation we suggest that the advent of the Copernicus Earth Observation programme opens new perspectives to address this issue in mountain regions worldwide. The Sentinel-2 mission will provide global-scale multispectral observations at 20 m resolution every 5-days (cloud permitting). The Sentinel-1 mission is already imaging the global land surface with a C-band radar at 10 m resolution every 6 days. These observations are unprecedented in terms of spatial and temporal resolution. However, the nature of the observation (radiometry, wavelength) is in the continuity of previous and ongoing missions. As a result, it is relatively straightforward to re-use algorithms that were developed by the remote sensing community over the last decades. For instance, Sentinel-2 data can be used to derive maps of the snow cover extent from the normalized difference snow index, which was initially proposed for Landsat. In addition, the 5-days repeat cycle allows the application of gap-filling algorithms, which were developed for MODIS based on the temporal dimension. The Sentinel-1 data can be used to detect the wet snow cover and track melting areas as proposed for ERS in the early 1990's. Eventually, we show an example where Sentinel-2-like data improved the simulation of the SWE in the data-scarce region of the High Atlas in Morocco through assimilation in a distributed snowpack model. We encourage snow scientists to embrace Sentinel-1 and Sentinel-2 data to enhance our knowledge on the snow cover dynamics in mountain regions.

Generation of liquid water on Mars through the melting of a dusty snowpack

USGS Publications Warehouse

Clow, G.D.

1987-01-01

The possibility that snowmelt could have provided liquid water for valley network formation early in the history of Mars is investigated using an optical-thermal model developed for dusty snowpacks at temperate latitudes. The heating of the postulated snow is assumed to be driven primarily by the absorption of solar radiation during clear sky conditions. Radiative heating rates are predicted as a function of depth and shown to be sensitive to the dust concentration and the size of the ice grains while the thermal conductivity is controlled by temperature, atmospheric pressure, and bulk density. Rates of metamorphism indicate that fresh fine-grained snow on Mars would evolve into moderately coarse snow during a single summer season. Results from global climate models are used to constrain the mean-annual surface temperatures for snow and the atmospheric exchange terms in the surface energy balance. Mean-annual temperatures within Martian snowpacks fail to reach the melting point for all atmospheric pressures below 1000 mbar despite a predicted temperature enhancement beneath the surface of the snowpacks. When seasonal and diurnal variations in the incident solar flux are included in the model, melting occurs at midday during the summer for a wide range of snow types and atmospheric pressures if the dust levels in the snow exceed 100 ppmw (parts per million by weight). The optimum dust concentration appears to be about 1000 ppmw. With this dust load, melting can occur in the upper few centimeters of a dense coarse-grained snow at atmospheric pressures as low as 7 mbar. Snowpack thickness and the thermal conductivity of the underlying substrate determine whether the generated snow-melt can penetrate to the snowpack base, survive basal ice formation, and subsequently become available for runoff. Under favorable conditions, liquid water becomes available for runoff at atmospheric pressures as low as 30 to 100 mbar if the substrate is composed of regolith, as is expected

Evaluation of the most suitable threshold value for modelling snow glacier melt through T- index approach: the case study of Forni Glacier (Italian Alps)

NASA Astrophysics Data System (ADS)

Senese, Antonella; Maugeri, Maurizio; Vuillermoz, Elisa; Smiraglia, Claudio; Diolaiuti, Guglielmina

2014-05-01

Glacier melt occurs whenever the surface temperature is null (273.15 K) and the net energy budget is positive. These conditions can be assessed by analyzing meteorological and energy data acquired by a supraglacial Automatic Weather Station (AWS). In the case this latter is not present at the glacier surface the assessment of actual melting conditions and the evaluation of melt amount is difficult and degree-day (also named T-index) models are applied. These approaches require the choice of a correct temperature threshold. In fact, melt does not necessarily occur at daily air temperatures higher than 273.15 K, since it is determined by the energy budget which in turn is only indirectly affected by air temperature. This is the case of the late spring period when ablation processes start at the glacier surface thus progressively reducing snow thickness. In this study, to detect the most indicative air temperature threshold witnessing melt conditions in the April-June period, we analyzed air temperature data recorded from 2006 to 2012 by a supraglacial AWS (at 2631 m a.s.l.) on the ablation tongue of the Forni Glacier (Italy), and by a weather station located nearby the studied glacier (at Bormio, 1225 m a.s.l.). Moreover we evaluated the glacier energy budget (which gives the actual melt, Senese et al., 2012) and the snow water equivalent values during this time-frame. Then the ablation amount was estimated both from the surface energy balance (MEB from supraglacial AWS data) and from degree-day method (MT-INDEX, in this latter case applying the mean tropospheric lapse rate to temperature data acquired at Bormio changing the air temperature threshold) and the results were compared. We found that the mean tropospheric lapse rate permits a good and reliable reconstruction of daily glacier air temperature conditions and the major uncertainty in the computation of snow melt from degree-day models is driven by the choice of an appropriate air temperature threshold. Then

The Impact of Detailed Snow Physics on the Simulation of Snow Cover and Subsurface Thermodynamics at Continental Scales

NASA Technical Reports Server (NTRS)

Stieglitz, Marc; Ducharne, Agnes; Koster, Randy; Suarez, Max; Busalacchi, Antonio J. (Technical Monitor)

2000-01-01

The three-layer snow model is coupled to the global catchment-based Land Surface Model (LSM) of the NASA Seasonal to Interannual Prediction Project (NSIPP) project, and the combined models are used to simulate the growth and ablation of snow cover over the North American continent for the period 1987-1988. The various snow processes included in the three-layer model, such as snow melting and re-freezing, dynamic changes in snow density, and snow insulating properties, are shown (through a comparison with the corresponding simulation using a much simpler snow model) to lead to an improved simulation of ground thermodynamics on the continental scale.

Remotely Sensed Spatio-Temporal Variability of Snow Cover in Himalayan Region with Perspective of Climate Change

NASA Astrophysics Data System (ADS)

Dhakal, S.; Ojha, S.

2017-12-01

Climate change and its impact of water resource have gained tremendous attention among scientific committee, governments and other stakeholders since last couple of decades, especially in Himalayan region. In this study, we purpose remotely sensed measurements to monitor snow cover, both spatially and temporal, and assess climate change impact on water resource. The snow cover data from MODIS satellite (2000-2010) have been used to analyze some climate change indicators. In particular, the variability in the maximum snow extent with elevations, its temporal variability (8-day, monthly, seasonal and annual), its variation trend and its relation with temperature have been analyzed. The snow products used in this study are the maximum snow extent and fractional snow covers, which come in 8-day temporal and 500m and 0.05 degree spatial resolutions, respectively. The results showed a tremendous potential of the MODIS snow product for studying the spatial and temporal variability of snow as well as the study of climate change impact in large and inaccessible regions like the Himalayas. The snow area extent (SAE) (%) time series exhibits similar patterns during seven hydrological years, even though there are some deviations in the accumulation and melt periods. The analysis showed relatively well inverse relation between the daily mean temperature and SAE during the melting period. Some important trends of snow fall are also observed. In particular, the decreasing trend in January and increasing trend in late winter and early spring may be interpreted as a signal of a possible seasonal shift. However, it requires more years of data to verify this conclusion.

Impact melting early in lunar history

NASA Technical Reports Server (NTRS)

Lange, M. A.; Ahrens, T. J.

1979-01-01

The total amount of impact melt produced during early lunar history is examined in light of theoretically and experimentally determined relations between crater diameter (D) and impact melt volume. The time dependence of the melt production is given by the time dependent impact rate as derived from cratering statistics for two different crater-size classes. Results show that small scale cratering (D less than or equal to 30 km) leads to melt volumes which fit selected observations specifying the amount of impact melt contained in the lunar regolith and in craters with diameters less than 10 km. Larger craters (D greater than 30 km) are capable of forming the abundant impact melt breccias found on the lunar surface. The group of large craters (D greater than 30 km) produces nearly 10 times as much impact melt as all the smaller craters, and thus, the large impacts dominate the modification of the lunar surface. A contradiction between the distribution of radiometric rock ages and a model of exponentially decreasing cratering rate going back to 4.5 b.y. is reflected in uncertainty in the distribution of impact melt as a function of time on the moon.

Lava-snow interactions at Tolbachik 2012-13 eruption: comparison to recent field observations and experiments

NASA Astrophysics Data System (ADS)

Edwards, B. R.; Belousov, A.; Belousova, M.; Izbekov, P. E.; Bindeman, I. N.; Gardeev, E.; Muravyev, Y. D.; Melnikov, D.

2013-12-01

More than a dozen volcanic eruptions in the past twenty years have produced lava interaction with snow or ice, some of which have produced damaging floods/lahars. However, the factors controlling melting during lava-snow/ice interactions is not well understood. Recent observations from the presently ongoing eruption at Tolbachik, Kamchatka confirm some general observations from large-scale experiments, and recent eruptions (2010 Fimmvorduhals; Edwards et al, 2012), but also show new types of behavior not before described. The new observations provide further constraints on heat transfer between ice/snow and three different lava morphologies: ';a'a, pahoehoe, and toothpaste. ';A'a flows at Tolbachik commonly were able to travel over seasonal snow cover (up to 4 m thick), especially where the snow was covered by tephra within 1.5 km of the vent area. Locally, heated meltwater discharge events issued from beneath the front of advancing lava, even though snow observation pits dug in front of advancing ';a'a flows also showed that in some areas melting was not as extensive. Once, an ';a'a flow was seen to collapse through snow, generating short-lived phreatomagmatic/phreatic activity. Closer to the vent, pahoehoe flow lobes and sheet flows occasionally spilled over onto snow and were able to rapidly transit snow with few obvious signs of melting/steam generation. Most of these flows did melt through basal snow layers within 24 hours however. We were also able to closely observe ';toothpaste' lava flows ';intruding' into snow in several locations, including snow-pits, and to watch it pushing up through snow forming temporary snow domes. Toothpaste lava caused the most rapid melting and most significant volumes of steam, as the meltwater drained down into the intruding lava. Behaviour seen at Tolbachik is similar to historic (e.g., Hekla 1947; Einarrson, 1949) and recent observations (e.g. Fimmvorduhals), as well as large-scale experiments (Edwards et al., 2013). While

Impacts of Snow Darkening by Absorbing Aerosols on Eurasian Climate

NASA Technical Reports Server (NTRS)

Kim, Kyu-Myong; Lau, William K M.; Yasunari, Teppei J.; Kim, Maeng-Ki; Koster, Randal D.

2016-01-01

The deposition of absorbing aerosols on snow surfaces reduces snow-albedo and allows snowpack to absorb more sunlight. This so-called snow darkening effect (SDE) accelerates snow melting and leads to surface warming in spring. To examine the impact of SDE on weather and climate during late spring and early summer, two sets of NASA GEOS-5 model simulations with and without SDE are conducted. Results show that SDE-induced surface heating is particularly pronounced in Eurasian regions where significant depositions of dust transported from the North African deserts, and black carbon from biomass burning from Asia and Europe occur. In these regions, the surface heating due to SDE increases surface skin temperature by 3-6 degrees Kelvin near the snowline in spring. Surface energy budget analysis indicates that SDE-induced excess heating is associated with a large increase in surface evaporation, subsequently leading to a significant reduction in soil moisture, and increased risks of drought and heat waves in late spring to early summer. Overall, we find that rainfall deficit combined with SDE-induced dry soil in spring provide favorable condition for summertime heat waves over large regions of Eurasia. Increased frequency of summer heat waves with SDE and the region of maximum increase in heat-wave frequency are found along the snow line, providing evidence that early snowmelt by SDE may increase the risks of extreme summer heat wave. Our results suggest that climate models that do not include SDE may significantly underestimate the effect of global warming over extra-tropical continental regions.

Measuring snow liquid water content with low-cost GPS receivers.

PubMed

Koch, Franziska; Prasch, Monika; Schmid, Lino; Schweizer, Jürg; Mauser, Wolfram

2014-11-06

The amount of liquid water in snow characterizes the wetness of a snowpack. Its temporal evolution plays an important role for wet-snow avalanche prediction, as well as the onset of meltwater release and water availability estimations within a river basin. However, it is still a challenge and a not yet satisfyingly solved issue to measure the liquid water content (LWC) in snow with conventional in situ and remote sensing techniques. We propose a new approach based on the attenuation of microwave radiation in the L-band emitted by the satellites of the Global Positioning System (GPS). For this purpose, we performed a continuous low-cost GPS measurement experiment at the Weissfluhjoch test site in Switzerland, during the snow melt period in 2013. As a measure of signal strength, we analyzed the carrier-to-noise power density ratio (C/N0) and developed a procedure to normalize these data. The bulk volumetric LWC was determined based on assumptions for attenuation, reflection and refraction of radiation in wet snow. The onset of melt, as well as daily melt-freeze cycles were clearly detected. The temporal evolution of the LWC was closely related to the meteorological and snow-hydrological data. Due to its non-destructive setup, its cost-efficiency and global availability, this approach has the potential to be implemented in distributed sensor networks for avalanche prediction or basin-wide melt onset measurements.

Impact of spatial variation in snow water equivalent and snow ablation on spring snowcover depletion over an alpine ridge

NASA Astrophysics Data System (ADS)

Schirmer, Michael; Harder, Phillip; Pomeroy, John

2016-04-01

The spatial and temporal dynamics of mountain snowmelt are controlled by the spatial distribution of snow accumulation and redistribution and the pattern of melt energy applied to this snowcover. In order to better quantify the spatial variations of accumulation and ablation, Structure-from-Motion techniques were applied to sequential aerial photographs of an alpine ridge in the Canadian Rocky Mountains taken from an Unmanned Aerial Vehicle (UAV). Seven spatial maps of snow depth and changes to depth during late melt (May-July) were generated at very high resolutions covering an area of 800 x 600 m. The accuracy was assessed with over 100 GPS measurements and RMSE were found to be less than 10 cm. Low resolution manual measurements of density permitted calculation of snow water equivalent (SWE) and change in SWE (ablation rate). The results indicate a highly variable initial SWE distribution, which was five times more variable than the spatial variation in ablation rate. Spatial variation in ablation rate was still substantial, with a factor of two difference between north and south aspects and small scale variations due to local dust deposition. However, the impact of spatial variations in ablation rate on the snowcover depletion curve could not be discerned. The reason for this is that only a weak spatial correlation developed between SWE and ablation rate. These findings suggest that despite substantial variations in ablation rate, snowcover depletion curve calculations should emphasize the spatial variation of initial SWE rather than the variation in ablation rate. While there is scientific evidence from other field studies that support this, there are also studies that suggest that spatial variations in ablation rate can influence snowcover depletion curves in complex terrain, particularly in early melt. The development of UAV photogrammetry has provided an opportunity for further detailed measurement of ablation rates, SWE and snowcover depletion over complex

Microwave Signatures of Melting/Refreezing Snow: Observations and Modeling Using Dense Medium Radiative Transfer Theory

NASA Technical Reports Server (NTRS)

Tedesco, Marco; Kim, Edward J.; England, Anthony; deRoo, Roger; Hardy, Janet

2005-01-01

Microwave brightness temperatures of snow covered terrains can be modeled by means of the Dense Radiative Transfer Medium Theory (DMRT). In a dense medium, such as snow, the assumption of independent scattering is no longer valid and the scattering of correlated scatterers must be considered. In the DMRT, this is done considering a pair distribution function of the particles position. In the electromagnetic model, the snowpack is simulated as a homogeneous layer having effective permittivity and albedo calculated through the DMRT. In order to account for clustering of snow crystals, a model of cohesive particles can be applied, where the cohesion between the particles is described by means of a dimensionless parameters called stickiness (z), representing a measure of the inversion of the attraction of the particles. The lower the z the higher the stickiness. In this study, microwave signatures of melting and refreezing cycles of seasonal snowpacks at high altitudes are studied by means of both experimental and modeling tools. Radiometric data were collected 24 hours per day by the University of Michigan Tower Mounted Radiometer System (TMRS). The brightness temperatures collected by means of the TMRS are simulated by means of a multi-layer electromagnetic model based on the dense medium theory with the inputs to the model derived from the data collected at the snow pits and from the meteorological station. The paper is structured as follows: in the first Section the temperature profiles recorded by the meteorological station and the snow pit data are presented and analyzed; in the second Section, the characteristics of the radiometric system used to collect the brightness temperatures are reported together with the temporal behavior of the recorded brightness temperatures; in the successive Section the multi-layer DMRT-based electromagnetic model is described; in the fourth Section the comparison between modeled and measured brightness temperatures is discussed. We

Satellite Snow-Cover Mapping: A Brief Review

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.

1995-01-01

Satellite snow mapping has been accomplished since 1966, initially using data from the reflective part of the electromagnetic spectrum, and now also employing data from the microwave part of the spectrum. Visible and near-infrared sensors can provide excellent spatial resolution from space enabling detailed snow mapping. When digital elevation models are also used, snow mapping can provide realistic measurements of snow extent even in mountainous areas. Passive-microwave satellite data permit global snow cover to be mapped on a near-daily basis and estimates of snow depth to be made, but with relatively poor spatial resolution (approximately 25 km). Dense forest cover limits both techniques and optical remote sensing is limited further by cloudcover conditions. Satellite remote sensing of snow cover with imaging radars is still in the early stages of research, but shows promise at least for mapping wet or melting snow using C-band (5.3 GHz) synthetic aperture radar (SAR) data. Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) data beginning with the launch of the first EOS platform in 1998. Digital maps will be produced that will provide daily, and maximum weekly global snow, sea ice and lake ice cover at 1-km spatial resolution. Statistics will be generated on the extent and persistence of snow or ice cover in each pixel for each weekly map, cloudcover permitting. It will also be possible to generate snow- and ice-cover maps using MODIS data at 250- and 500-m resolution, and to study and map snow and ice characteristics such as albedo. been under development. Passive-microwave data offer the potential for determining not only snow cover, but snow water equivalent, depth and wetness under all sky conditions. A number of algorithms have been developed to utilize passive-microwave brightness temperatures to provide information on snow cover and water equivalent. The variability of vegetative Algorithms are being developed to map global snow

Routine Mapping of the Snow Depth Distribution on Sea Ice

NASA Astrophysics Data System (ADS)

Farrell, S. L.; Newman, T.; Richter-Menge, J.; Dattler, M.; Paden, J. D.; Yan, S.; Li, J.; Leuschen, C.

2016-12-01

The annual growth and retreat of the polar sea ice cover is influenced by the seasonal accumulation, redistribution and melt of snow on sea ice. Due to its high albedo and low thermal conductivity, snow is also a controlling parameter in the mass and energy budgets of the polar climate system. Under a changing climate scenario it is critical to obtain reliable and routine measurements of snow depth, across basin scales, and long time periods, so as to understand regional, seasonal and inter-annual variability, and the subsequent impacts on the sea ice cover itself. Moreover the snow depth distribution remains a significant source of uncertainty in the derivation of sea ice thickness from remote sensing measurements, as well as in numerical model predictions of future climate state. Radar altimeter systems flown onboard NASA's Operation IceBridge (OIB) mission now provide annual measurements of snow across both the Arctic and Southern Ocean ice packs. We describe recent advances in the processing techniques used to interpret airborne radar waveforms and produce accurate and robust snow depth results. As a consequence of instrument effects and data quality issues associated with the initial release of the OIB airborne radar data, the entire data set was reprocessed to remove coherent noise and sidelobes in the radar echograms. These reprocessed data were released to the community in early 2016, and are available for improved derivation of snow depth. Here, using the reprocessed data, we present the results of seven years of radar measurements collected over Arctic sea ice at the end of winter, just prior to melt. Our analysis provides the snow depth distribution on both seasonal and multi-year sea ice. We present the inter-annual variability in snow depth for both the Central Arctic and the Beaufort/Chukchi Seas. We validate our results via comparison with temporally and spatially coincident in situ measurements gathered during many of the OIB surveys. The results

Changes in DOM Character and Composition during Spring Snow Melt in the Jemez River Basin Critical Zone Observatory.

NASA Astrophysics Data System (ADS)

Thompson, M.; Olshansky, Y.; Chorover, J.

2017-12-01

Dynamics of dissolved organic matter (DOM) in stream waters are important indicators of internal processes in the critical zone, such as decomposition and mobilization of soil organic matter, hydrologic flow paths, potential for metal mobilization and nutrient redistribution. Previous studies indicate that DOM concentration was highest during peak snow melt in the La Jara catchment located in the Jemez River Basin Critical Zone Observatory (Perdrial et al., 2014). We postulate that the molecular composition and character of DOM changes with the advance of spring snow melt. Water samples were collected from two flumes located at the outlets of the La Jara Creek and from a zero order basin within this catchment through the spring snowmelt from March 1 to May 15 2017. DOM concentration increased with stream discharge. Quantification of molecular changes was conducted using Fourier transform infrared spectroscopy (FTIR), which showed the variation in carboxyl abundance (wavenumbers 1680, 1600 and 1410 cm-1) correlated with dissolved organic carbon concentration, indicating that this component is relatively a constant fraction of the organic carbon exported through the stream during spring snowmelt. In contrast, amide vibrations (3550, 1640 and 670 cm-1) were shown to decrease with the advance of spring snowmelt. This trend further corresponded to a decrease in the ratio of carboxylic acid (above) to aromatic (1622, 1490, 955 cm-1) moieties, suggesting either a flush of compounds accumulated prior to spring snow melt, or increased decomposition of plant derived material in the soil that was then transported to the stream. Aliphatic components (2965, 2925 and 2865 cm-1) decreased from the beginning to the middle of sampling period, then showed an increase toward the end of snowmelt. O-Alkyl peak (1150 and 1073 cm-1) varied without a clear trend during the spring snowmelt. These changes in O-Alkyl and aliphatic compounds may be related to microbial derived compounds and

Rainfall and snow-melt triggered glacial lake outbursts: a systematic analysis of the Kedarnath (Uttarakhand, India), June 2013 disaster

NASA Astrophysics Data System (ADS)

Allen, Simon; Rastner, Philipp; Arora, Manohar; Huggel, Christian; Stoffel, Markus

2015-04-01

Heavy rainfall in early June 2013 triggered flash flooding and landslides throughout the Indian Himalayan state of Uttarakhand, killing more than 6000 people. The destruction of roads and trekking routes left around 100,000 pilgrims and tourists stranded. Most fatalities and damages resulted directly from a lake outburst and debris flow disaster originating from above the village of Kedarnath on June 16 and 17. Here we provide a first systematic analysis of the contributing factors leading to the Kedarnath disaster, both in terms of hydro-meteorological triggering (rainfall, snowmelt, and temperature) and topographic predisposition. Specifically, the topographic characteristics of the Charobari lake watershed above Kedarnath are compared with other glacial lakes across the northwestern Indian Himalayan states of Uttarakhand and Himachal Pradesh, and implications for glacier lake outburst hazard assessment in a changing climate are discussed. Our analysis suggests that the early onset of heavy monsoon rainfall (390 mm, June 10 - 17) immediately following a prolonged four week period of unusually rapid snow cover depletion and elevated streamflow is the crucial hydro-meteorological factor, resulting in slope saturation and significant runoff into the small seasonal glacial lake. Over a four week period the MODIS-derived snow covered area above Kedarnath decreased nearly 50%, from above average coverage in mid-May to well below average coverage by the second week of June. Such a rapid decrease has not been observed in the previous 13-year record, where the average decrease in snow covered area over the same four week window is only 15%. The unusual situation of the lake being dammed in a steep, unstable paraglacial environment, but fed entirely from snow-melt and rainfall within a fluvial dominated watershed is important in the context of this disaster. A simple scheme enabling large-scale recognition of such an unfavorable topographic setting is presented, and on the

Measuring Snow Liquid Water Content with Low-Cost GPS Receivers

PubMed Central

Koch, Franziska; Prasch, Monika; Schmid, Lino; Schweizer, Jürg; Mauser, Wolfram

2014-01-01

The amount of liquid water in snow characterizes the wetness of a snowpack. Its temporal evolution plays an important role for wet-snow avalanche prediction, as well as the onset of meltwater release and water availability estimations within a river basin. However, it is still a challenge and a not yet satisfyingly solved issue to measure the liquid water content (LWC) in snow with conventional in situ and remote sensing techniques. We propose a new approach based on the attenuation of microwave radiation in the L-band emitted by the satellites of the Global Positioning System (GPS). For this purpose, we performed a continuous low-cost GPS measurement experiment at the Weissfluhjoch test site in Switzerland, during the snow melt period in 2013. As a measure of signal strength, we analyzed the carrier-to-noise power density ratio (C/N0) and developed a procedure to normalize these data. The bulk volumetric LWC was determined based on assumptions for attenuation, reflection and refraction of radiation in wet snow. The onset of melt, as well as daily melt-freeze cycles were clearly detected. The temporal evolution of the LWC was closely related to the meteorological and snow-hydrological data. Due to its non-destructive setup, its cost-efficiency and global availability, this approach has the potential to be implemented in distributed sensor networks for avalanche prediction or basin-wide melt onset measurements. PMID:25384007

Kindergarten Explorations with Snow, Ice, and Water

ERIC Educational Resources Information Center

Carroll, Martha A.

1978-01-01

Using winter snow, kindergarten students can explore the properties of water. Students demonstrate melting, freezing, expansion, and evaporation through a number of activities involving a paper cup and a scoop of snow. Procedures and student reactions are described in detail by the teacher-author. (MA)

Synergy of Earth Observation and In-Situ Monitoring Data for Flood Hazard Early Warning System

NASA Astrophysics Data System (ADS)

Brodsky, Lukas; Kodesova, Radka; Spazierova, Katerina

2010-12-01

In this study, we demonstrate synergy of EO and in-situ monitoring data for early warning flood hazard system in the Czech Republic developed within ESA PECS project FLOREO. The development of the demonstration system is oriented to support existing monitoring activities, especially snow melt and surface water runoff contributing to flooding events. The system consists of two main parts accordingly, the first is snow cover and snow melt monitoring driven mainly by EO data and the other is surface water runoff modeling and monitoring driven by synergy of in-situ and EO data.

Validating SWE reconstruction using Airborne Snow Observatory measurements in the Sierra Nevada

NASA Astrophysics Data System (ADS)

Bair, N.; Rittger, K.; Davis, R. E.; Dozier, J.

2015-12-01

The Airborne Snow Observatory (ASO) program offers high resolution estimates of snow water equivalent (SWE) in several small basins across California during the melt season. Primarily, water managers use this information to model snowmelt runoff into reservoirs. Another, and potentially more impactful, use of ASO SWE measurements is in validating and improving satellite-based SWE estimates which can be used in austere regions with no ground-based snow or water measurements, such as Afghanistan's Hindu Kush. Using the entire ASO dataset to date (2013-2015) which is mostly from the Upper Tuolumne basin, but also includes measurements from 2015 in the Kings, Rush Creek, Merced, and Mammoth Lakes basins, we compare ASO measurements to those from a SWE reconstruction method. Briefly, SWE reconstruction involves downscaling energy balance forcings to compute potential melt energy, then using satellite-derived estimates of fractional snow covered area (fSCA) to estimate snow melt from potential melt. The snowpack can then be built in reverse, given a remotely-sensed date of snow disappearance (fSCA=0). Our model has improvements over previous iterations in that it: uses the full energy balance (compared to a modified degree-day) approach, models bulk and surface snow temperatures, accounts for ephemeral snow, and uses a remotely-sensed snow albedo adjusted for impurities. To check that ASO provides accurate snow measurements, we compare fSCA derived from ASO snow depth at 3 m resolution with fSCA from a spectral unmixing algorithm for LandSAT at 30 m, and from binary SCA estimates from Geoeye at 0.5 m from supervised classification. To conclude, we document how our reconstruction model has evolved over the years and provide specific examples where improvements have been made using ASO and other verification sources.

Soot climate forcing via snow and ice albedos.

PubMed

Hansen, James; Nazarenko, Larissa

2004-01-13

Plausible estimates for the effect of soot on snow and ice albedos (1.5% in the Arctic and 3% in Northern Hemisphere land areas) yield a climate forcing of +0.3 W/m(2) in the Northern Hemisphere. The "efficacy" of this forcing is approximately 2, i.e., for a given forcing it is twice as effective as CO(2) in altering global surface air temperature. This indirect soot forcing may have contributed to global warming of the past century, including the trend toward early springs in the Northern Hemisphere, thinning Arctic sea ice, and melting land ice and permafrost. If, as we suggest, melting ice and sea level rise define the level of dangerous anthropogenic interference with the climate system, then reducing soot emissions, thus restoring snow albedos to pristine high values, would have the double benefit of reducing global warming and raising the global temperature level at which dangerous anthropogenic interference occurs. However, soot contributions to climate change do not alter the conclusion that anthropogenic greenhouse gases have been the main cause of recent global warming and will be the predominant climate forcing in the future.

Integration of MODIS Snow, Cloud and Land Area Coverage Data with SNOTEL to Generate Inter-Annual and Within-Season Snow Depletion Curves and Maps

NASA Astrophysics Data System (ADS)

Qualls, R. J.; Woodruff, C.

2017-12-01

The behavior of inter-annual trends in mountain snow cover would represent extremely useful information for drought and climate change assessment; however, individual data sources exhibit specific limitations for characterizing this behavior. For example, SNOTEL data provide time series point values of Snow Water Equivalent (SWE), but lack spatial content apart from that contained in a sparse network of point values. Satellite observations in the visible spectrum can provide snow covered area, but not SWE at present, and are limited by cloud cover which often obscures visibility of the ground, especially during the winter and spring in mountainous areas. Cloud cover, therefore, often limits both temporal and spatial coverage of satellite remote sensing of snow. Among the platforms providing the best combination of temporal and spatial coverage to overcome the cloud obscuration problem by providing frequent overflights, the Aqua and Terra satellites carrying the MODIS instrument package provide 500 m, daily resolution observations of snow cover. These were only launched in 1999 and the early 2000's, thus limiting the historical period over which these data are available. A hybrid method incorporating SNOTEL and MODIS data has been developed which accomplishes cloud removal, and enables determination of the time series of watershed spatial snow cover when either SNOTEL or MODIS data are available. This allows one to generate spatial snow cover information for watersheds with SNOTEL stations for periods both before and after the launch of the Aqua and Terra satellites, extending the spatial information about snow cover over the period of record of the SNOTEL stations present in a watershed. This method is used to quantify the spatial time series of snow over the 9000 km2 Upper Snake River watershed and to evaluate inter-annual trends in the timing, rate, and duration of melt over the nearly 40 year period from the early 1980's to the present, and shows promise for

High Arctic flowering phenology and plant-pollinator interactions in response to delayed snow melt and simulated warming

NASA Astrophysics Data System (ADS)

Gillespie, Mark A. K.; Baggesen, Nanna; Cooper, Elisabeth J.

2016-11-01

The projected alterations to climate in the High Arctic are likely to result in changes to the short growing season, particularly with varying predicted effects on winter snowfall, the timing of summer snowmelt and air temperatures. These changes are likely to affect the phenology of interacting species in a variety of ways, but few studies have investigated the effects of combined climate drivers on plant-pollinator interactions in the High Arctic. In this study, we alter the timing of flowering phenology using a field manipulation experiment in which snow depth is increased using snow fences and temperatures are enhanced by open-top chambers (OTCs). We used this experiment to quantify the combined effects of treatments on the flowering phenology of six dominant plant species (Dryas octopetala, Cassiope tetragona, Bistorta vivipara, Saxifraga oppositifolia, Stellaria crassipes and Pedicularis hirsuita), and to simulate differing responses to climate between plants and pollinators in a subset of plots. Flowers were counted regularly throughout the growing season of 2015, and insect visitors were caught on flowers during standardised observation sessions. As expected, deep snow plots had delayed snow melt timing and this in turn delayed the first and peak flowering dates of the plants and shortened the prefloration period overall. The OTCs counteracted the delay in first and peak flowering to some extent. There was no effect of treatment on length of flowering season, although for all variables there were species-specific responses. The insect flower-visitor community was species poor, and although evidence of disruption to phenological overlaps was not found, the results do highlight the vulnerability of the plant-pollinator network in this system with differing phenological shifts between insects and plants and reduced visitation rates to flowers in plots with deep snow.

Contribution of rainfall, snow and ice melt to the hydrological regime of the Arve upper catchment and to severe flood events

NASA Astrophysics Data System (ADS)

Lecourt, Grégoire; Revuelto, Jesús; Morin, Samuel; Zin, Isabella; Lafaysse, Matthieu; Condom, Thomas; Six, Delphine; Vionnet, Vincent; Charrois, Luc; Dumont, Marie; Gottardi, Frédéric; Laarman, Olivier; Coulaud, Catherine; Esteves, Michel; Lebel, Thierry; Vincent, Christian

2016-04-01

In Alpine catchments, the hydrological response to meteorological events is highly influenced by the precipitation phase (liquid or solid) and by snow and ice melt. It is thus necessary to simulate accurately the snowpack evolution and its spatial distribution to perform relevant hydrological simulations. This work is focused on the upper Arve Valley (Western Alps). This 205 km2 catchment has large glaciated areas (roughly 32% of the study area) and covers a large range of elevations (1000-4500 m a.s.l.). Snow presence is significant year-round. The area is also characterized by steep terrain and strong vegetation heterogeneity. Modelling hydrological processes in such a complex catchment is therefore challenging. The detailed ISBA land surface model (including the Crocus snowpack scheme) has been applied to the study area using a topography based discretization (classifying terrain by aspect, elevation, slope and presence of glacier). The meteorological forcing used to run the simulations is the reanalysis issued from the SAFRAN model which assimilates meteorological observations from the Meteo-France networks. Conceptual reservoirs with calibrated values of emptying parameters are used to represent the underground water storage. This approach has been tested to simulate the discharge on the Arve catchment and three sub-catchments over 1990-2015. The simulations were evaluated with respect to observed water discharges for several headwaters with varying glaciated areas. They allow to quantify the relative contribution of rainfall, snow and ice melt to the hydrological regime of the basin. Additionally, we present a detailed analysis of several particular flood events. For these events, the ability of the model to correctly represent the catchment behaviour is investigated, looking particularly to the relevance of the simulated snowpack. Particularly, its spatial distribution is evaluated using MODIS snow cover maps, punctual snowpack observations and summer

Hydrologic response across a snow persistence gradient on the west and east slopes of the Rocky Mountains in Colorado

NASA Astrophysics Data System (ADS)

Richard, G. A.; Hammond, J. C.; Kampf, S. K.; Moore, C. D.; Eurich, A.

2017-12-01

Snowpack trend analyses and modeling studies suggest that lower elevation snowpacks in mountain regions are most sensitive to drought and warming temperatures, however, in Colorado, most snow monitoring occurs in the high elevations where snow lasts throughout the winter and most streamflow monitoring occurs at lower elevations. The lack of combined snow and streamflow monitoring in watersheds along the transition from intermittent to persistent snow creates a gap in our understanding of snowmelt and runoff within the intermittent-persistent snow transition. Expanded hydrologic monitoring that spans the gradient of snow conditions in Colorado can help improve streamflow prediction and inform land and water managers. This study established hydrologic monitoring watersheds in intermittent, transitional, and persistent snow zones on the east slope and west slope of the Rocky Mountains in Colorado, and uses this monitoring network to improve understanding of how snow accumulation and melt affect soil moisture and streamflow generation under different snow conditions. We monitored six small watersheds (three west slope, three east slope) (0.8 to 3.9 km2) that drain intermittent, transitional, and persistent snow zones. At each site, we measured: streamflow, snow depth, soil moisture, precipitation, air temperature, and snow water equivalent (SWE). In our first season of monitoring, the west slope persistent and transitional sites had more mid-winter melt and infiltration, shorter snowpack duration, and lower peak SWE than the east slope sites. Snow cover remained at the east slope persistent site into June, whereas much of the snow at the persistent site on the west slope had already melted by early June. The difference in soil water input likely has consequences for streamflow response that we will continue to examine in future years. At the west slope intermittent site, the stream did not flow during the entire first year of monitoring, while at the east slope

Geologic Tests for Snowmelt Runoff on Early Mars

NASA Astrophysics Data System (ADS)

Kite, E. S.; Sneed, J.; Mayer, D. P.

2017-12-01

Data from the Curiosity rover have sharpened the question: was Early Mars climate warm enough for rainfall, or was the climate cold? The hypothesis of a cold (snow-and-ice melt) climate on Early Mars can be tested using runoff production. Runoff production cannot exceed snowmelt rate in a cold climate. Therefore, high runoff production would rule out cold conditions, and would suggest rain (or catastrophic melting of snow). How can runoff production be reliably measured? To constrain runoff production, the lead author is measuring paleochannel widths and meander wavelengths for Early Mars watersheds with well-defined drainage area. The measurement method is the same as in Kite et al., EPSL, 2015. >250 channel-width measurements and 89 meander wavelength measurements are included, representing 158 drainage areas. The catalog emphasizes better-preserved (post-Noachian) paleochannels, but includes a re-survey of previously-reported paleochannel width and wavelength measurement sites. Channel widths and wavelengths are a proxy for paleodischarge. Discharge (m3/s) can be divided by drainage area (m2) to obtain a lower bound on runoff-production (mm/hr). If runoff production >(1-3) mm/hr, then a seasonal melting snow-and-ice climate is strongly disfavored. However, high runoff production would be consistent with rainfall. Initial results will be reported at the conference. The figure shows the locations of measurement sites for Early Mars channel width (black) and meander wavelength (red).

Spectral reflectance characteristics of different snow and snow-covered land surface objects and mixed spectrum fitting

USGS Publications Warehouse

Zhang, J.-H.; Zhou, Z.-M.; Wang, P.-J.; Yao, F.-M.; Yang, L.

2011-01-01

The field spectroradiometer was used to measure spectra of different snow and snow-covered land surface objects in Beijing area. The result showed that for a pure snow spectrum, the snow reflectance peaks appeared from visible to 800 nm band locations; there was an obvious absorption valley of snow spectrum near 1030 nm wavelength. Compared with fresh snow, the reflection peaks of the old snow and melting snow showed different degrees of decline in the ranges of 300~1300, 1700~1800 and 2200~2300 nm, the lowest was from the compacted snow and frozen ice. For the vegetation and snow mixed spectral characteristics, it was indicated that the spectral reflectance increased for the snow-covered land types(including pine leaf with snow and pine leaf on snow background), due to the influence of snow background in the range of 350~1300 nm. However, the spectrum reflectance of mixed pixel remained a vegetation spectral characteristic. In the end, based on the spectrum analysis of snow, vegetation, and mixed snow/vegetation pixels, the mixed spectral fitting equations were established, and the results showed that there was good correlation between spectral curves by simulation fitting and observed ones(correlation coefficient R2=0.9509).

Siting, design and operational controls for snow disposal sites.

PubMed

Wheaton, S R; Rice, W J

2003-01-01

The Municipality of Anchorage (MOA), at 61 degrees north latitude, ploughs and hauls snow from urban streets throughout the winter, incorporating grit and chloride applied to street surfaces for traffic safety. Hauled snow is stored at snow disposal facilities, where it melts at ambient spring temperatures. MOA studies performed from 1998 through 2001 show that disposal site melt processes can be manipulated, through site design and operation practices, to control chloride and turbidity in meltwater. An experimental passive "V-swale" pad configuration tested by MOA investigators reduced site meltwater turbidity by an order of magnitude (to about 50 NTU from the 500 NTU typical of more conventional planar pad geometry). The MOA has developed new siting, design and operational criteria for snow disposal facilities to conform to the tested V-swale pad configuration.

Deriving Snow-Cover Depletion Curves for Different Spatial Scales from Remote Sensing and Snow Telemetry Data

NASA Technical Reports Server (NTRS)

Fassnacht, Steven R.; Sexstone, Graham A.; Kashipazha, Amir H.; Lopez-Moreno, Juan Ignacio; Jasinski, Michael F.; Kampf, Stephanie K.; Von Thaden, Benjamin C.

2015-01-01

During the melting of a snowpack, snow water equivalent (SWE) can be correlated to snow-covered area (SCA) once snow-free areas appear, which is when SCA begins to decrease below 100%. This amount of SWE is called the threshold SWE. Daily SWE data from snow telemetry stations were related to SCA derived from moderate-resolution imaging spectro radiometer images to produce snow-cover depletion curves. The snow depletion curves were created for an 80,000 sq km domain across southern Wyoming and northern Colorado encompassing 54 snow telemetry stations. Eight yearly snow depletion curves were compared, and it is shown that the slope of each is a function of the amount of snow received. Snow-cover depletion curves were also derived for all the individual stations, for which the threshold SWE could be estimated from peak SWE and the topography around each station. A stations peak SWE was much more important than the main topographic variables that included location, elevation, slope, and modelled clear sky solar radiation. The threshold SWE mostly illustrated inter-annual consistency.

Further observations of snow and frost in the Adirondacks

Treesearch

Howard W. Lull; Francis M. Rushmore

1961-01-01

Snow-depth and water-content measurements were made in March and April 1960 in the vicinity of Paul Smiths, New York, to check on procedures developed the previous year for predicting snow accumulation and melt.

Combining low-cost GPS receivers with upGPR to derive continuously liquid water content, snow height and snow water equivalent in Alpine snow covers

NASA Astrophysics Data System (ADS)

Koch, Franziska; Schmid, Lino; Prasch, Monika; Heilig, Achim; Eisen, Olaf; Schweizer, Jürg; Mauser, Wolfram

2015-04-01

The temporal evolution of Alpine snowpacks is important for assessing water supply, hydropower generation, flood predictions and avalanche forecasts. Especially in high mountain regions with an extremely varying topography, it is until now often difficult to derive continuous and non-destructive information on snow parameters. Since autumn 2012, we are running a new low-cost GPS (Global Positioning System) snow measurement experiment at the high alpine study site Weissfluhjoch (2450 m a.s.l.) in Switzerland. The globally and freely broadcasted GPS L1-band (1.57542 GHz) was continuously recorded with GPS antennas, which are installed at the ground surface underneath the snowpack. GPS raw data, containing carrier-to-noise power density ratio (C/N0) as well as elevation and azimuth angle information for each time step of 1 s, was stored and analyzed for all 32 GPS satellites. Since the dielectric permittivity of an overlying wet snowpack influences microwave radiation, the bulk volumetric liquid water content as well as daily melt-freeze cycles can be derived non-destructively from GPS signal strength losses and external snow height information. This liquid water content information is qualitatively in good accordance with meteorological and snow-hydrological data and quantitatively highly agrees with continuous data derived from an upward-looking ground-penetrating radar (upGPR) working in a similar frequency range. As a promising novelty, we combined the GPS signal strength data with upGPR travel-time information of active impulse radar rays to the snow surface and back from underneath the snow cover. This combination allows determining liquid water content, snow height and snow water equivalent from beneath the snow cover without using any other external information. The snow parameters derived by combining upGPR and GPS data are in good agreement with conventional sensors as e.g. laser distance gauges or snow pillows. As the GPS sensors are cheap, they can easily

Drivers and environmental responses to the changing annual snow cycle of northern Alaska

USGS Publications Warehouse

Cox, Christopher J.; Stone, Robert S.; Douglas, David C.; Stanitski, Diane; Divoky, George J.; Dutton, Geoff S.; Sweeney, Colm; George, J. Craig; Longenecker, David U.

2017-01-01

On the North Slope of Alaska, earlier spring snowmelt and later onset of autumn snow accumulation are tied to atmospheric dynamics and sea ice conditions, and result in environmental responses.Linkages between atmospheric, ecological and biogeochemical variables in the changing Arctic are analyzed using long-term measurements near Utqiaġvik (formerly Barrow), Alaska. Two key variables are the date when snow disappears in spring, as determined primarily by atmospheric dynamics, precipitation, air temperature, winter snow accumulation and cloud cover, as well as the date of onset of snowpack in autumn that is additionally influenced by ocean temperature and sea ice extent. In 2015 and 2016 the snow melted early at Utqiaġvik due mainly to anomalous warmth during May of both years attributed to atmospheric circulation patterns, with 2016 having the record earliest snowmelt. These years are discussed in the context of a 115-year snowmelt record at Utqiaġvik with a trend toward earlier melting since the mid- 1970s (-2.86 days/decade, 1975-2016). At nearby Cooper Island, where a colony of seabirds, Black Guillemots, have been monitored since 1975, timing of egg laying is correlated with Utqiaġvik snowmelt with 2015 and 2016 being the earliest years in the 42-year record. Ice-out at a nearby freshwater lagoon is also correlated with Utqiaġvik snowmelt. The date when snow begins to accumulate in autumn at Utqiaġvik shows a trend towards later dates (+4.6 days/decade, 1975-2016), with 2016 the latest on record. The relationships between the lengthening snow-free season and regional phenology, soil temperatures, fluxes of gases from the tundra, and to regional sea ice conditions are discussed. Better understanding of these interactions is needed to predict the annual snow cycles in the region at seasonal to decadal scales, and to anticipate coupled environmental responses.

Evaluation of the SMAP model calculated snow albedo at the SIGMA-A site, northwest Greenland, during the 2012 record surface melt event

NASA Astrophysics Data System (ADS)

Niwano, M.; Aoki, T.; Matoba, S.; Yamaguchi, S.; Tanikawa, T.; Kuchiki, K.; Motoyama, H.

2015-12-01

The snow and ice on the Greenland ice sheet (GrIS) experienced the extreme surface melt around 12 July, 2012. In order to understand the snow-atmosphere interaction during the period, we applied a physical snowpack model SMAP to the GrIS snowpack. In the SMAP model, the snow albedo is calculated by the PBSAM component explicitly considering effects of snow grain size and light-absorbing snow impurities such as black carbon and dust. Temporal evolution of snow grain size is calculated internally in the SMAP model, whereas mass concentrations of snow impurities are externally given from observations. In the PBSAM, the (shortwave) snow albedo is calculated from a weighted summation of visible albedo (primarily affected by snow impurities) and near-infrared albedo (mainly controlled by snow grain size). The weights for these albedos are the visible and near-infrared fractions of the downward shortwave radiant flux. The SMAP model forced by meteorological data obtained from an automated weather station at SIGMA-A site, northwest GrIS during 30 June to 14 July, 2012　(IOP) was evaluated in terms of surface (optically equivalent) snow grain size and snow albedo. Snow grain size simulated by the model was compared against that retrieved from in-situ spectral albedo measurements. Although the RMSE and ME were reasonable (0.21 mm and 0.17 mm, respectively), the small snow grain size associated with the surface hoar could not be simulated by the SMAP model. As for snow albedo, simulation results agreed well with observations throughout the IOP (RMSE was 0.022 and ME was 0.008). Under cloudy-sky conditions, the SMAP model reproduced observed rapid increase in the snow albedo. When cloud cover is present the near-infrared fraction of the downward shortwave radiant flux is decreased, while it is increased under clear-sky conditions. Therefore, the above mentioned performance of the SMAP model can be attributed to the PBSAM component driven by the observed near-infrared and

Snow and ice perturbation during historical volcanic eruptions and the formation of lahars and floods

USGS Publications Warehouse

Major, Jon J.; Newhall, Christopher G.

1989-01-01

Historical eruptions have produced lahars and floods by perturbing snow and ice at more than 40 volcanoes worldwide. Most of these volcanoes are located at latitudes higher than 35°; those at lower latitudes reach altitudes generally above 4000 m. Volcanic events can perturb mantles of snow and ice in at least five ways: (1) scouring and melting by flowing pyroclastic debris or blasts of hot gases and pyroclastic debris, (2) surficial melting by lava flows, (3) basal melting of glacial ice or snow by subglacial eruptions or geothermal activity, (4) ejection of water by eruptions through a crater lake, and (5) deposition of tephra fall. Historical records of volcanic eruptions at snow-clad volcanoes show the following: (1) Flowing pyroclastic debris (pyroclastic flows and surges) and blasts of hot gases and pyroclastic debris are the most common volcanic events that generate lahars and floods; (2) Surficial lava flows generally cannot melt snow and ice rapidly enough to form large lahars or floods; (3) Heating the base of a glacier or snowpack by subglacial eruptions or by geothermal activity can induce basal melting that may result in ponding of water and lead to sudden outpourings of water or sediment-rich debris flows; (4) Tephra falls usually alter ablation rates of snow and ice but generally produce little meltwater that results in the formation of lahars and floods; (5) Lahars and floods generated by flowing pyroclastic debris, blasts of hot gases and pyroclastic debris, or basal melting of snow and ice commonly have volumes that exceed 105 m3.The glowing lava (pyroclastic flow) which flowed with force over ravines and ridges...gathered in the basin quickly and then forced downwards. As a result, tremendously wide and deep pathways in the ice and snow were made and produced great streams of water (Wolf 1878).

Snow and ice perturbation during historical volcanic eruptions and the formation of lahars and floods

NASA Astrophysics Data System (ADS)

Major, Jon J.; Newhall, Christopher G.

1989-10-01

Historical eruptions have produced lahars and floods by perturbing snow and ice at more than 40 volcanoes worldwide. Most of these volcanoes are located at latitudes higher than 35°; those at lower latitudes reach altitudes generally above 4000 m. Volcanic events can perturb mantles of snow and ice in at least five ways: (1) scouring and melting by flowing pyroclastic debris or blasts of hot gases and pyroclastic debris, (2) surficial melting by lava flows, (3) basal melting of glacial ice or snow by subglacial eruptions or geothermal activity, (4) ejection of water by eruptions through a crater lake, and (5) deposition of tephra fall. Historical records of volcanic eruptions at snow-clad volcanoes show the following: (1) Flowing pyroclastic debris (pyroclastic flows and surges) and blasts of hot gases and pyroclastic debris are the most common volcanic events that generate lahars and floods; (2) Surficial lava flows generally cannot melt snow and ice rapidly enough to form large lahars or floods; (3) Heating the base of a glacier or snowpack by subglacial eruptions or by geothermal activity can induce basal melting that may result in ponding of water and lead to sudden outpourings of water or sediment-rich debris flows; (4) Tephra falls usually alter ablation rates of snow and ice but generally produce little meltwater that results in the formation of lahars and floods; (5) Lahars and floods generated by flowing pyroclastic debris, blasts of hot gases and pyroclastic debris, or basal melting of snow and ice commonly have volumes that exceed 105 m3. The glowing lava (pyroclastic flow) which flowed with force over ravines and ridges...gathered in the basin quickly and then forced downwards. As a result, tremendously wide and deep pathways in the ice and snow were made and produced great streams of water (Wolf 1878).

Light-absorbing impurities accelerate glacier melt in the Central Tibetan Plateau.

PubMed

Li, Xiaofei; Kang, Shichang; He, Xiaobo; Qu, Bin; Tripathee, Lekhendra; Jing, Zhefan; Paudyal, Rukumesh; Li, Yang; Zhang, Yulan; Yan, Fangping; Li, Gang; Li, Chaoliu

2017-06-01

Light-absorbing impurities (LAIs), such as organic carbon (OC), black carbon (BC), and mineral dust (MD) deposited on the glacier surface can reduce albedo, thus accelerating the glacier melt. Surface fresh snow, aged snow, granular ice, and snowpits samples were collected between August 2014 and October 2015 on the Xiao Dongkemadi (XDKMD) glacier (33°04'N, 92°04'E) in the central Tibetan Plateau (TP). The spatiotemporal variations of LAIs concentrations in the surface snow/ice were observed to be consistent, differing mainly in magnitudes. LAIs concentrations were found to be in the order: granular ice>snowpit>aged snow>fresh snow, which must be because of post-depositional effects and enrichment. In addition, more intense melting led to higher LAIs concentrations exposed to the surface at a lower elevation, suggesting a strong negative relationship between LAIs concentrations and elevation. The scavenging efficiencies of OC and BC were same (0.07±0.02 for OC, 0.07±0.01 for BC), and the highest enrichments was observed in late September and August for surface snow and granular ice, respectively. Meanwhile, as revealed by the changes in the OC/BC ratios, intense glacier melt mainly occurred between August and October. Based on the SNow ICe Aerosol Radiative (SNICAR) model simulations, BC and MD in the surface snow/ice were responsible for about 52%±19% and 25%±14% of the albedo reduction, while the radiative forcing (RF) were estimated to be 42.74±40.96Wm -2 and 21.23±22.08Wm -2 , respectively. Meanwhile, the highest RF was observed in the granular ice, suggesting that the exposed glaciers melt and retreat more easily than the snow distributed glaciers. Furthermore, our results suggest that BC was the main forcing factor compared with MD in accelerating glacier melt during the melt season in the Central TP. Copyright © 2017 Elsevier B.V. All rights reserved.

Export of Algal Communities from Land Fast Arctic Sea Ice Influenced by Overlying Snow Depth and Episodic Rain Events

NASA Astrophysics Data System (ADS)

Neuer, S.; Juhl, A. R.; Aumack, C.; McHugh, C.; Wolverton, M. A.; Kinzler, K.

2016-02-01

Sea ice algal communities dominate primary production of the coastal Arctic Ocean in spring. As the sea ice bloom terminates, algae are released from the ice into the underlying, nutrient-rich waters, potentially seeding blooms and feeding higher trophic levels in the water column and benthos. We studied the sea ice community including export events over four consecutive field seasons (2011-2014) during the spring ice algae bloom in land-fast ice near Barrow, Alaska, allowing us to investigate both seasonal and interannual differences. Within each year, we observed a delay in algal export from ice in areas covered by thicker snow compared to areas with thinner snow coverage. Variability in snow cover therefore resulted in a prolonged supply of organic matter to the underlying water column. Earlier export in 2012 was followed by a shift in the diatom community within the ice from pennates to centrics. During an unusual warm period in early May 2014, precipitation falling as rain substantially decreased the snow cover thickness (from snow depth > 20 cm down to 0-2 cm). After the early snowmelt, algae were rapidly lost from the sea ice, and a subsequent bloom of taxonomically-distinct, under-ice phytoplankton developed a few days later. The typical immured sea ice diatoms never recovered in terms of biomass, though pennate diatoms (predominantly Nitzschia frigida) did regrow to some extent near the ice bottom. Sinking rates of the under-ice phytoplankton were much more variable than those of ice algae particles, which would potentially impact residence time in the water column, and fluxes to the benthos. Thus, the early melt episode, triggered by rain, transitioned directly into the seasonal melt and the release of biomass from the ice, shifting production from sea ice to the water column, with as-of-yet unknown consequences for the springtime Arctic food web.

Permeability measurements on new and equitemperature snow

Treesearch

R. A. Sommerfeld; J. R. Rocchio

1993-01-01

During the month of February, between 46 and 53% of the land area of the northern hemisphere is snow covered. Continental snowpacks act as chemical reservoirs; pollutants can accumulate in the pack over the entire winter and are released during a relatively short spring melt period. Interactions between the snow and the atmosphere can change the quantities of different...

Snow and glaciers in the tropics: the importance of snowfall level and snow line altitude in the Peruvian Cordilleras

NASA Astrophysics Data System (ADS)

Schauwecker, Simone; Rohrer, Mario; Huggel, Christian; Salzmann, Nadine; Montoya, Nilton; Endries, Jason; Perry, Baker

2016-04-01

The snow line altitude, defined as the line separating snow from ice or firn surfaces, is among the most important parameters in the glacier mass and energy balance of tropical glaciers, since it determines net shortwave radiation via surface albedo. Therefore, hydroglaciological models require estimations of the melting layer during precipitation events, as well as parameterisations of the transient snow line. Typically, the height of the melting layer is implemented by simple air temperature extrapolation techniques, using data from nearby meteorological stations and constant lapse rates. Nonetheless, in the Peruvian mountain ranges, stations at the height of glacier tongues (>5000 m asl.) are scarce and the extrapolation techniques must use data from distant and much lower elevated stations, which need prior careful validation. Thus, reliable snowfall level and snow line altitude estimates from multiple data sets are necessary. Here, we assemble and analyse data from multiple sources (remote sensing, in-situ station data, reanalysis data) in order to assess their applicability in estimating both, the melting layer and snow line altitude. We especially focus on the potential of radar bright band data from TRMM and CloudSat satellite data for its use as a proxy for the snow/rain transition height. As expected for tropical regions, the seasonal and regional variability in the snow line altitude is comparatively low. During the course of the dry season, Landsat satellite as well as webcam images show that the transient snow line is generally increasing, interrupted by light snowfall or graupel events with low precipitation amounts and fast decay rates. We show limitations and possibilities of different data sources as well as their applicability to validate temperature extrapolation methods. Further on, we analyse the implications of the relatively low variability in seasonal snow line altitude on local glacier mass balance gradients. We show that the snow line

Increasing the efficiency of the process of snow mass utilization from the urban infrastructure and reducing the negative impact on the environment through the introduction of an installation for the utilization of snow mass

NASA Astrophysics Data System (ADS)

Dovbysh, V. O.; Burakova, L. N.; Burakova, A. D.

2018-01-01

The article raises the problem of the maintenance of the urban area in winter, namely, the problem of disposal of snow masses from the urban area. The article describes the main disadvantages of the existing snow-melting systems for the utilization of city snow mass and are encouraged to develop an installation for melting of snow, functioning at the expense of power consumption. The developed installation allows to reduce the noise level during its operation, to exclude the influence of exhaust gases on the environment, therefore, to improve the environmental safety of the urban infrastructure.

Geomatics contributions to key indicators for estimation and monitoring of snow cover input to hydrogeological resources

NASA Astrophysics Data System (ADS)

Somma, J.; Drapeau, L.; Abou Chakra, C.; El-Ali, T.

2014-12-01

Climate change is a subject of concern for the inhabitants of the semi-arid zones because water needs are greatly increasing with population growth. For the Middle East region, the karstic geology of Lebanon with its high and steep mountains makes it a real water tower and promotes an essential snow cover. Studies carried out on snow water equivalent reserve [1] remain still insufficient for the development of continuous monitoring. Modeling the lebanese high plateau made of sinkholes and undulations eases the computations of land capacity for snow retention. It is therefore an interesting testing ground for snow volumes calculations [2]. To improve previous attempts, a research project focuses on snow melting processes. It uses the cessation date of snow melt water infiltration which is crucial in the precocity or the delay of low water level [3]; and geomatics to determinate the major factor for the evaluation of storaged water (spatial or vertical extension of snow cover). The project studies the sensitivity of temporal snow melting variabilities to quantities of snow precipitations and climatic conditions. Field measurements were collected at very high topographic precision [4] in a specific sinkhole and were used to create volumes models for measuring indicators such as: snow water equivalent; melting speed in relation to climatic data; forecast of completed meting date; correlations with springs discharges. Other methodological procedures take into account snow depressions (sinkholes and ripples) capacity retention; daily webcam images to monitor the accumulation and melt rate and remotely sensed Pleiades stereoscopic images to create snow cover elevation model at the time of acquisition. [1]Corbane et al., 2004 ; 2005 ; Corbane, 2002 ; Bernier et al., 2001, 2003 ; Shaban et al., 2004; Aouad et al., 2004, Aouad-Rizk et al., 2005 ; Gédéon el al., 2004 [2] Somma et al ; 2014 [3] Drapeau et al ; 2013 [4] Drapeau et al, 2013; Somma et Drapeau, 2011 ; Somma et

A Blended Global Snow Product using Visible, Passive Microwave and Scatterometer Satellite Data

NASA Technical Reports Server (NTRS)

Foster, James L.; Hall, Dorothy K.; Eylander, John B.; Riggs, George A.; Nghiem, Son V.; Tedesco, Marco; Kim, Edward; Montesano, Paul M.; Kelly, Richard E. J.; Casey, Kimberly A.;

Snow as Field-Teaching Medium for Earth Science.

ERIC Educational Resources Information Center

Custer, Stephan Gregory

1991-01-01

Snow is a widely available earth-science teaching medium which can be used to explore scientific concepts in the field, either directly or by analogy. Snow can be considered a mineral, sediment, sedimentary rock, or metamorphic rock. Natural processes such as crystal growth, melting, sedimentation, and metamorphism can be studied in practical time…

Mapping the spatial distribution and time evolution of snow water equivalent with passive microwave measurements

USGS Publications Warehouse

Guo, J.; Tsang, L.; Josberger, E.G.; Wood, A.W.; Hwang, J.-N.; Lettenmaier, D.P.

2003-01-01

This paper presents an algorithm that estimates the spatial distribution and temporal evolution of snow water equivalent and snow depth based on passive remote sensing measurements. It combines the inversion of passive microwave remote sensing measurements via dense media radiative transfer modeling results with snow accumulation and melt model predictions to yield improved estimates of snow depth and snow water equivalent, at a pixel resolution of 5 arc-min. In the inversion, snow grain size evolution is constrained based on pattern matching by using the local snow temperature history. This algorithm is applied to produce spatial snow maps of Upper Rio Grande River basin in Colorado. The simulation results are compared with that of the snow accumulation and melt model and a linear regression method. The quantitative comparison with the ground truth measurements from four Snowpack Telemetry (SNOTEL) sites in the basin shows that this algorithm is able to improve the estimation of snow parameters.

Assessing the controls of the snow energy balance and water available for runoff in a rain-an-snow environment

Treesearch

Adam B. Mazurkiewicz; David G. Callery; Jeffrey J. McDonnell

2008-01-01

Rain-on-snow (ROS) melt production and its contribution to water available for runoff is poorly understood. In the Pacific Northwest (PNW) of the USA, ROS drives many runoff events with turbulent energy exchanges dominating the snow energy balance (EB). While previous experimental work in the PNW (most notably the H.J. Andrews Experimental Forest (HJA» has quantified...

Comparing different snow products to assess spatio-temporal snow cover patterns in the Central Taurus Mountains, Turkey

NASA Astrophysics Data System (ADS)

Sturm, K.; Helmschrot, J.

2013-12-01

differs notably during snow accumulation and ablation periods, the highest deviations occurring in December, April, and May. The highest SCA inconsistencies are observed in the low and mid altitudes, whereas the higher elevations are snow-covered very early in the snow season as modeled by J2000. During these periods, J2000 simulates a significantly larger SCA than MODIS. The analysis of individual time steps suggests that the J2000 daily model does capture individual snow events, whereas the MODIS products fail to do so due to their temporal resolution. Furthermore, acquisition time and inner-daily melt and re-freezing effects may affect SCA estimates from MODIS data. In other cases, differences can clearly be associated to insufficient model input data, primarily due to limited spatial precipitation and temperature data. Our study indicates that individual products might provide inconsistent information on temporal and spatial snow cover. We recommend considering a combined analysis of different snow products in order to provide reliable information on snow cover dynamics, in particular in eastern Mediterranean high-altitude environments.

Retention and radiative forcing of black carbon in eastern Sierra Nevada snow

NASA Astrophysics Data System (ADS)

Sterle, K. M.; McConnell, J. R.; Dozier, J.; Edwards, R.; Flanner, M. G.

2013-02-01

When contaminated by absorbing particles, such as refractory black carbon (rBC) and continental dust, snow's albedo decreases and thus its absorption of solar radiation increases, thereby hastening snowmelt. For this reason, an understanding of rBC's affect on snow albedo, melt processes, and radiation balance is critical for water management, especially in a changing climate. Measurements of rBC in a sequence of snow pits and surface snow samples in the eastern Sierra Nevada of California during the snow accumulation and ablation seasons of 2009 show that concentrations of rBC were enhanced sevenfold in surface snow (~25 ng g-1) compared to bulk values in the snowpack (~3 ng g-1). Unlike major ions, which were preferentially released during the initial melt, rBC and continental dust were retained in the snow, enhancing concentrations well into late spring, until a final flush occurred during the ablation period. We estimate a combined rBC and continental dust surface radiative forcing of 20 to 40 W m-2 during April and May, with dust likely contributing a greater share of the forcing.

A new parameterization of the post-fire snow albedo effect

NASA Astrophysics Data System (ADS)

Gleason, K. E.; Nolin, A. W.

2013-12-01

Mountain snowpack serves as an important natural reservoir of water: recharging aquifers, sustaining streams, and providing important ecosystem services. Reduced snowpacks and earlier snowmelt have been shown to affect fire size, frequency, and severity in the western United States. In turn, wildfire disturbance affects patterns of snow accumulation and ablation by reducing canopy interception, increasing turbulent fluxes, and modifying the surface radiation balance. Recent work shows that after a high severity forest fire, approximately 60% more solar radiation reaches the snow surface due to the reduction in canopy density. Also, significant amounts of pyrogenic carbon particles and larger burned woody debris (BWD) are shed from standing charred trees, which concentrate on the snowpack, darken its surface, and reduce snow albedo by 50% during ablation. Although the post-fire forest environment drives a substantial increase in net shortwave radiation at the snowpack surface, driving earlier and more rapid melt, hydrologic models do not explicitly incorporate forest fire disturbance effects to snowpack dynamics. The objective of this study was to parameterize the post-fire snow albedo effect due to BWD deposition on snow to better represent forest fire disturbance in modeling of snow-dominated hydrologic regimes. Based on empirical results from winter experiments, in-situ snow monitoring, and remote sensing data from a recent forest fire in the Oregon High Cascades, we characterized the post-fire snow albedo effect, and developed a simple parameterization of snowpack albedo decay in the post-fire forest environment. We modified the recession coefficient in the algorithm: α = α0 + K exp (-nr) where α = snowpack albedo, α0 = minimum snowpack albedo (≈0.4), K = constant (≈ 0.44), -n = number of days since last major snowfall, r = recession coefficient [Rohrer and Braun, 1994]. Our parameterization quantified BWD deposition and snow albedo decay rates and

THE INFLUENCE OF THE SPATIAL DISTRIBUTION OF SNOW ON BASIN-AVERAGED SNOWMELT. (R824784)

EPA Science Inventory

Spatial variability in snow accumulation and melt owing to topographic effects on solar radiation, snow drifting, air temperature and precipitation is important in determining the timing of snowmelt releases. Precipitation and temperature effects related to topography affect snow...

Seasonal Change in Bacterial Flora and Biomass in Mountain Snow from the Tateyama Mountains, Japan, Analyzed by 16S rRNA Gene Sequencing and Real-Time PCR

PubMed Central

Segawa, Takahiro; Miyamoto, Koji; Ushida, Kazunari; Agata, Kiyokazu; Okada, Norihiro; Kohshima, Shiro

2005-01-01

The bacterial flora and biomass in mountain snow from the Tateyama Mountains, Toyama Prefecture, Japan, one of the heaviest snowfall regions in the world, were analyzed by amplified ribosomal DNA restriction analysis followed by 16S rRNA gene sequencing and DNA quantification by real-time PCR. Samples of surface snow collected in various months during the melting season contained a psychrophilic bacterium, Cryobacterium psychrophilum, and two psychrotrophic bacteria, Variovorax paradoxus and Janthinobacterium lividum. Bacterial colonies that developed in an in situ meltwater medium at 4°C were revealed to be V. paradoxus. The biomasses of C. psychrophilum, J. lividum, and V. paradoxus, as estimated by real-time PCR, showed large increases during the melting season from March to October (2.0 × 105-fold, 1.5 × 105-fold, and 1.0 × 104-fold increases, respectively), suggesting their rapid growth in the surface snow. The biomasses of C. psychrophilum and J. lividum increased significantly from March to April, reached a maximum in August, and dropped at the end of the melting season. In contrast, the biomass of V. paradoxus did not increase as rapidly during the early melting season but continued to increase from June until October. The differences in development observed among these bacterial species suggest that their growth was promoted by different nutrients and/or environmental conditions in the snow. Since these three types of bacteria have also been reported to be present in a glacier in Antarctica and a Greenland ice core, they seem to be specialized members of the snow biota that are distributed in snow and ice environments in various parts of the world. PMID:15640179

Seasonal change in bacterial flora and biomass in mountain snow from the Tateyama Mountains, Japan, analyzed by 16S rRNA gene sequencing and real-time PCR.

PubMed

Segawa, Takahiro; Miyamoto, Koji; Ushida, Kazunari; Agata, Kiyokazu; Okada, Norihiro; Kohshima, Shiro

2005-01-01

The bacterial flora and biomass in mountain snow from the Tateyama Mountains, Toyama Prefecture, Japan, one of the heaviest snowfall regions in the world, were analyzed by amplified ribosomal DNA restriction analysis followed by 16S rRNA gene sequencing and DNA quantification by real-time PCR. Samples of surface snow collected in various months during the melting season contained a psychrophilic bacterium, Cryobacterium psychrophilum, and two psychrotrophic bacteria, Variovorax paradoxus and Janthinobacterium lividum. Bacterial colonies that developed in an in situ meltwater medium at 4 degrees C were revealed to be V. paradoxus. The biomasses of C. psychrophilum, J. lividum, and V. paradoxus, as estimated by real-time PCR, showed large increases during the melting season from March to October (2.0 x 10(5)-fold, 1.5 x 10(5)-fold, and 1.0 x 10(4)-fold increases, respectively), suggesting their rapid growth in the surface snow. The biomasses of C. psychrophilum and J. lividum increased significantly from March to April, reached a maximum in August, and dropped at the end of the melting season. In contrast, the biomass of V. paradoxus did not increase as rapidly during the early melting season but continued to increase from June until October. The differences in development observed among these bacterial species suggest that their growth was promoted by different nutrients and/or environmental conditions in the snow. Since these three types of bacteria have also been reported to be present in a glacier in Antarctica and a Greenland ice core, they seem to be specialized members of the snow biota that are distributed in snow and ice environments in various parts of the world.

Coupling of a Simple 3-Layer Snow Model to GISS GCM

NASA Astrophysics Data System (ADS)

Aleinov, I.

2001-12-01

Appropriate simulation of the snow cover dynamics is an important issue for the General Circulation Models (GCMs). The presence of snow has a significant impact on ground albedo and on heat and moisture balance. A 3-layer snow model similar to the one proposed by Lynch-Stieglitz was developed with the purpose of using it inside the GCM developed in the NASA Goddard Institute for Space Studies (GISS). The water transport between the layers is modeled explicitly while the heat balance is computed implicitly between the snow layers and semi-implicitly on the surface. The processes of melting and refreezing and compactification of layers under the gravitational force are modeled appropriately. It was noticed that implicit computation of the heat transport can cause a significant under- or over-estimation of the incoming heat flux when the temperature of the upper snow layer is equal to 0 C. This may lead in particular to delayed snow melting in spring. To remedy this problem a special flux-control algorithm was added to the model, which checks computed flux for possible errors and if such are detected the heat transport is recomputed again with the appropriate corrections. The model was tested off-line with Sleepers River forcing data and exhibited a good agreement between simulated and observed quantities for snow depth, snow density and snow temperature. The model was then incorporated into the GISS GCM. Inside the GCM the model is driven completely by the data simulated by other parts of the GCM. The screening effect of the vegetation is introduced by means of masking depth. For a thin snowpack a fractional cover is implemented so that the total thickness of the the snow is never less then 10 cm (rather, the areal fraction of the snow cover decreases when it melts). The model was tested with 6 year long GCM speed-up runs. It proved to be stable and produced reasonable results for the global snow cover. In comparison to the old GISS GCM snow model (which was

A new fractional snow-covered area parameterization for the Community Land Model and its effect on the surface energy balance

NASA Astrophysics Data System (ADS)

Swenson, S. C.; Lawrence, D. M.

2011-11-01

One function of the Community Land Model (CLM4) is the determination of surface albedo in the Community Earth System Model (CESM1). Because the typical spatial scales of CESM1 simulations are large compared to the scales of variability of surface properties such as snow cover and vegetation, unresolved surface heterogeneity is parameterized. Fractional snow-covered area, or snow-covered fraction (SCF), within a CLM4 grid cell is parameterized as a function of grid cell mean snow depth and snow density. This parameterization is based on an analysis of monthly averaged SCF and snow depth that showed a seasonal shift in the snow depth-SCF relationship. In this paper, we show that this shift is an artifact of the monthly sampling and that the current parameterization does not reflect the relationship observed between snow depth and SCF at the daily time scale. We demonstrate that the snow depth analysis used in the original study exhibits a bias toward early melt when compared to satellite-observed SCF. This bias results in a tendency to overestimate SCF as a function of snow depth. Using a more consistent, higher spatial and temporal resolution snow depth analysis reveals a clear hysteresis between snow accumulation and melt seasons. Here, a new SCF parameterization based on snow water equivalent is developed to capture the observed seasonal snow depth-SCF evolution. The effects of the new SCF parameterization on the surface energy budget are described. In CLM4, surface energy fluxes are calculated assuming a uniform snow cover. To more realistically simulate environments having patchy snow cover, we modify the model by computing the surface fluxes separately for snow-free and snow-covered fractions of a grid cell. In this configuration, the form of the parameterized snow depth-SCF relationship is shown to greatly affect the surface energy budget. The direct exposure of the snow-free surfaces to the atmosphere leads to greater heat loss from the ground during autumn

A new fractional snow-covered area parameterization for the Community Land Model and its effect on the surface energy balance

NASA Astrophysics Data System (ADS)

Swenson, S. C.; Lawrence, D. M.

2012-11-01

One function of the Community Land Model (CLM4) is the determination of surface albedo in the Community Earth System Model (CESM1). Because the typical spatial scales of CESM1 simulations are large compared to the scales of variability of surface properties such as snow cover and vegetation, unresolved surface heterogeneity is parameterized. Fractional snow-covered area, or snow-covered fraction (SCF), within a CLM4 grid cell is parameterized as a function of grid cell mean snow depth and snow density. This parameterization is based on an analysis of monthly averaged SCF and snow depth that showed a seasonal shift in the snow depth-SCF relationship. In this paper, we show that this shift is an artifact of the monthly sampling and that the current parameterization does not reflect the relationship observed between snow depth and SCF at the daily time scale. We demonstrate that the snow depth analysis used in the original study exhibits a bias toward early melt when compared to satellite-observed SCF. This bias results in a tendency to overestimate SCF as a function of snow depth. Using a more consistent, higher spatial and temporal resolution snow depth analysis reveals a clear hysteresis between snow accumulation and melt seasons. Here, a new SCF parameterization based on snow water equivalent is developed to capture the observed seasonal snow depth-SCF evolution. The effects of the new SCF parameterization on the surface energy budget are described. In CLM4, surface energy fluxes are calculated assuming a uniform snow cover. To more realistically simulate environments having patchy snow cover, we modify the model by computing the surface fluxes separately for snow-free and snow-covered fractions of a grid cell. In this configuration, the form of the parameterized snow depth-SCF relationship is shown to greatly affect the surface energy budget. The direct exposure of the snow-free surfaces to the atmosphere leads to greater heat loss from the ground during autumn

Snow deposition and melt under different vegetative covers in central New York

Treesearch

A. R. Eschner; D. R. Satterlund

1963-01-01

Two-thirds of the annual runoff from watersheds in the Allegheny Plateau of central New York comes from the snow-or snow and rain that falls in December through April. Although the amounts of precipitation in this period are fairly uniform from year to year, the proportion that falls as snow varies; so does the amount that accumulates on the ground, and its duration...

Optimizing placements of ground-based snow sensors for areal snow cover estimation using a machine-learning algorithm and melt-season snow-LiDAR data

NASA Astrophysics Data System (ADS)

Oroza, C.; Zheng, Z.; Glaser, S. D.; Bales, R. C.; Conklin, M. H.

2016-12-01

We present a structured, analytical approach to optimize ground-sensor placements based on time-series remotely sensed (LiDAR) data and machine-learning algorithms. We focused on catchments within the Merced and Tuolumne river basins, covered by the JPL Airborne Snow Observatory LiDAR program. First, we used a Gaussian mixture model to identify representative sensor locations in the space of independent variables for each catchment. Multiple independent variables that govern the distribution of snow depth were used, including elevation, slope, and aspect. Second, we used a Gaussian process to estimate the areal distribution of snow depth from the initial set of measurements. This is a covariance-based model that also estimates the areal distribution of model uncertainty based on the independent variable weights and autocorrelation. The uncertainty raster was used to strategically add sensors to minimize model uncertainty. We assessed the temporal accuracy of the method using LiDAR-derived snow-depth rasters collected in water-year 2014. In each area, optimal sensor placements were determined using the first available snow raster for the year. The accuracy in the remaining LiDAR surveys was compared to 100 configurations of sensors selected at random. We found the accuracy of the model from the proposed placements to be higher and more consistent in each remaining survey than the average random configuration. We found that a relatively small number of sensors can be used to accurately reproduce the spatial patterns of snow depth across the basins, when placed using spatial snow data. Our approach also simplifies sensor placement. At present, field surveys are required to identify representative locations for such networks, a process that is labor intensive and provides limited guarantees on the networks' representation of catchment independent variables.

Modeling Snow Regime in Cores of Small Planetary Bodies

NASA Astrophysics Data System (ADS)

Boukaré, C. E.; Ricard, Y. R.; Parmentier, E.; Parman, S. W.

2017-12-01

Observations of present day magnetic field on small planetary bodies such as Ganymede or Mercury challenge our understanding of planetary dynamo. Several mechanisms have been proposed to explain the origin of magnetic fields. Among the proposed scenarios, one family of models relies on snow regime. Snow regime is supported by experimental studies showing that melting curves can first intersect adiabats in regions where the solidifying phase is not gravitationaly stable. First solids should thus remelt during their ascent or descent. The effect of the snow zone on magnetic field generation remains an open question. Could magnetic field be generated in the snow zone? If not, what is the depth extent of the snow zone? How remelting in the snow zone drive compositional convection in the liquid layer? Several authors have tackled this question with 1D-spherical models. Zhang and Schubert, 2012 model sinking of the dense phase as internally heated convection. However, to our knowledge, there is no study on the convection structure associated with sedimentation and phase change at planetary scale. We extend the numerical model developped in [Boukare et al., 2017] to model snow dynamics in 2D Cartesian geometry. We build a general approach for modeling double diffusive convection coupled with solid-liquid phase change and phase separation. We identify several aspects that may govern the convection structure of the solidifying system: viscosity contrast between the snow zone and the liquid layer, crystal size, rate of melting/solidification and partitioning of light components during phase change.

The effects of dust on Colorado mountain snow cover albedo and compositional links to dust-source areas

NASA Astrophysics Data System (ADS)

Goldstein, H. L.; Reynolds, R. L.; Landry, C.; Derry, J. E.; Kokaly, R. F.; Breit, G. N.

2016-12-01

Dust deposited on mountain snow cover (DOS) changes snow albedo, enhances absorption of solar radiation, and effectively increases rates of snow melt, leading to earlier-than-normal runoff and overall smaller late-season water supplies for tens of millions of people and industries in the American West. Visible-spectrum reflectance of DOS samples is on the order of 0.2 (80% absorption), in stark contrast to the high reflectivity of pure snow which approaches 1.0. Samples of DOS were collected from 12 high-elevation Colorado mountain sites near the end of spring from 2013 through 2016 prior to complete snow melt, when most dust layers had merged into one layer. These samples were analyzed to measure dust properties that affect snow albedo and to link DOS to dust-source areas. Dust mass loadings to snow during water year 2014 varied from 5 to 30 g/m2. Median particle sizes centered around 20 micrometers with more than 80% of the dust <63 micrometers. Dark minerals, carbonaceous matter, and iron oxides, including nano-sized hematite and goethite, together diminished reflectance according to their variable concentrations. Documenting variations in dust-particle masses, sizes, and compositions helps determine their influences on snow-melt and may be useful for modeling snow-melt effects from future dust. Furthermore, variations in dust components and particle sizes lead to new ways to recognize sources of dust by comparison with properties of fine-grained sediments in dust-source areas. Much of the DOS in the San Juan Mountains, Colorado can be linked to southern Colorado Plateau source areas by compositional similarities and satellite imagery. Understanding dust properties that affect snow albedo and recognizing the sources of dust deposited on snow cover may guide mitigation of dust emission that affects water resources of the Colorado River basin.

Winter Ice and Snow as Models of Igneous Rock Formation.

ERIC Educational Resources Information Center

Romey, William D.

1983-01-01

Examines some features of ice and snow that offer teachers and researchers help in understanding many aspects of igneous processes and configurations. Careful observation of such processes as melting, decay, evolution, and snow accumulation provide important clues to understanding processes by which many kinds of rocks form. (Author/JN)

Radar backscattering from snow facies of the Greenland ice sheet: Results from the AIRSAR 1991 campaign

NASA Technical Reports Server (NTRS)

Rignot, Eric; Jezek, K.; Vanzyl, J. J.; Drinkwater, Mark R.; Lou, Y. L.

1993-01-01

In June 1991, the NASA/JPL airborne SAR (AIRSAR) acquired C- (lambda = 5.6cm), L- (lambda = 24cm), and P- (lambda = 68m) band polarimetric SAR data over the Greenland ice sheet. These data are processed using version 3.55 of the AIRSAR processor which provides radiometrically and polarimetrically calibrated images. The internal calibration of the AIRSAR data is cross-checked using the radar response from corner reflectors deployed prior to flight in one of the scenes. In addition, a quantitative assessment of the noise power level at various frequencies and polarizations is made in all the scenes. Synoptic SAR data corresponding to a swath width of about 12 by 50 km in length (compared to the standard 12 x 12 km size of high-resolution scenes) are also processed and calibrated to study transitions in radar backscatter as a function of snow facies at selected frequencies and polarizations. The snow facies on the Greenland ice sheet are traditionally categorized based on differences in melting regime during the summer months. The interior of Greenland corresponds to the dry snow zone where terrain elevation is the highest and no snow melt occurs. The lowest elevation boundary of the dry snow zone is known traditionally as the dry snow line. Beneath it is the percolation zone where melting occurs in the summer and water percolates through the snow freezing at depth to form massive ice lenses and ice pipes. At the downslope margin of this zone is the wet snow line. Below it, the wet snow zone corresponds to the lowest elevations where snow remains at the end of the summer. Ablation produces enough meltwater to create areas of snow saturated with water, together with ponds and lakes. The lowest altitude zone of ablation sees enough summer melt to remove all traces of seasonal snow accumulation, such that the surface comprises bare glacier ice.

Mountain hydrology, snow color, and the fourth paradigm

NASA Astrophysics Data System (ADS)

Dozier, Jeff

2011-10-01

The world's mountain ranges accumulate substantial snow, whose melt produces the bulk of runoff and often combines with rain to cause floods. Worldwide, inadequate understanding and a reliance on sparsely distributed observations limit our ability to predict seasonal and paroxysmal runoff as climate changes, ecosystems adapt, populations grow, land use evolves, and societies make choices. To improve assessments of snow accumulation, melt, and runoff, scientists and community planners can take advantage of two emerging trends: (1) an ability to remotely sense snow properties from satellites at a spatial scale appropriate for mountain regions (10- to 100-meter resolution, coverage of the order of 100,000 square kilometers) and a daily temporal scale appropriate for the dynamic nature of snow and (2) The Fourth Paradigm [Hey et al., 2009], which posits a new scientific approach in which insight is discovered through the manipulation of large data sets as the evolutionary step in scientific thinking beyond the first three paradigms: empiricism, analyses, and simulation. The inspiration for the book's title comes from pioneering computer scientist Jim Gray, based on a lecture he gave at the National Academy of Sciences 3 weeks before he disappeared at sea.

Snow Coverage Analysis Using ASTER over the Sierra Nevada Mountain Range

NASA Astrophysics Data System (ADS)

Ross, B.

2017-12-01

Snow has strong impacts on human behavior, state and local activities, and the economy. The Sierra Nevada snowpack is California's most important natural reservoir of water. Such snow is melting sooner and faster. A recent California drought study showed that there was a deficit of 1.5 million acre-feet of water in 2014 due to the fast melting rates. Scientists have been using the Moderate Resolution Imaging Spectrometer (MODIS) which is available at the spatial resolution of 500-meter, to analyze the changes in snow coverage. While such analysis provides us with the valuable information, it would be more beneficial to employ the imageries at a higher spatial resolution for snow studies. Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER), which acquires the high-resolution imageries ranging from 15-meter to 90-meter, has recently become freely available to the public. Our study utilized two scenes obtained from ASTER to investigate the changes in snow extent over the Sierra Nevada's mountain area for an 8-year period. These two scenes were collected on April 11, 2007 and April 16, 2015 covering the same geographic region. Normalized Difference Snow Index (NDSI) was adopted to delineate the snow coverage in each scene. Our study shows a substantial decrease of snow coverage in the studied geographic region by pixel count.

Global mountain snow and ice loss driven by dust and black carbon radiative forcing

NASA Astrophysics Data System (ADS)

Painter, T. H.

2014-12-01

Changes in mountain snow and glaciers have been our strongest indicators of the effects of changing climate. Earlier melt of snow and losses of glacier mass have perturbed regional water cycling, regional climate, and ecosystem dynamics, and contributed strongly to sea level rise. Recent studies however have revealed that in some regions, the reduction of albedo by light absorbing impurities in snow and ice such as dust and black carbon can be distinctly more powerful than regional warming at melting snow and ice. In the Rocky Mountains, dust deposition has increased 5 to 7 fold in the last 150 years, leading to ~3 weeks earlier loss of snow cover from forced melt. In absolute terms, in some years dust radiative forcing there can shorten snow cover duration by nearly two months. Remote sensing retrievals are beginning to reveal powerful dust and black carbon radiative forcing in the Hindu Kush through Himalaya. In light of recent ice cores that show pronounced increases in loading of dust and BC during the Anthropocene, these forcings may have contributed far more to glacier retreat than previously thought. For example, we have shown that the paradoxical end of the Little Ice Age in the European Alps beginning around 1850 (when glaciers began to retreat but temperatures continued to decline and precipitation was unchanged) very likely was driven by the massive increases in deposition to snow and ice of black carbon from industrialization in surrounding nations. A more robust understanding of changes in mountain snow and ice during the Anthropocene requires that we move past simplistic treatments (e.g. temperature-index modeling) to energy balance approaches that assess changes in the individual forcings such as the most powerful component for melt - net solar radiation. Remote sensing retrievals from imaging spectrometers and multispectral sensors are giving us more powerful insights into the time-space variation of snow and ice albedo.

Sensitivity of Alpine Snow and Streamflow Regimes to Climate Changes

NASA Astrophysics Data System (ADS)

Rasouli, K.; Pomeroy, J. W.; Marks, D. G.; Bernhardt, M.

2014-12-01

Understanding the sensitivity of hydrological processes to climate change in alpine areas with snow dominated regimes is of paramount importance as alpine basins show both high runoff efficiency associated with the melt of the seasonal snowpack and great sensitivity of snow processes to temperature change. In this study, meteorological data measured in a selection of alpine headwaters basins including Reynolds Mountain East, Idaho, USA, Wolf Creek, Yukon in Canada, and Zugspitze Mountain, Germany with climates ranging from arctic to continental temperate were used to study the snow and streamflow sensitivity to climate change. All research sites have detailed multi-decadal meteorological and snow measurements. The Cold Regions Hydrological Modelling platform (CRHM) was used to create a model representing a typical alpine headwater basin discretized into hydrological response units with physically based representations of snow redistribution by wind, complex terrain snowmelt energetics and runoff processes in alpine tundra. The sensitivity of snow hydrology to climate change was investigated by changing air temperature and precipitation using weather generating methods based on the change factors obtained from different climate model projections for future and current periods. The basin mean and spatial variability of peak snow water equivalent, sublimation loss, duration of snow season, snowmelt rates, streamflow peak, and basin discharge were assessed under varying climate scenarios and the most sensitive hydrological mechanisms to the changes in the different alpine climates were detected. The results show that snow hydrology in colder alpine climates is more resilient to warming than that in warmer climates, but that compensatory factors to warming such as reduced blowing snow sublimation loss and reduced melt rate should also be assessed when considering climate change impacts on alpine hydrology.

Utilizing Multiple Datasets for Snow Cover Mapping

NASA Technical Reports Server (NTRS)

Tait, Andrew B.; Hall, Dorothy K.; Foster, James L.; Armstrong, Richard L.

1999-01-01

Snow-cover maps generated from surface data are based on direct measurements, however they are prone to interpolation errors where climate stations are sparsely distributed. Snow cover is clearly discernable using satellite-attained optical data because of the high albedo of snow, yet the surface is often obscured by cloud cover. Passive microwave (PM) data is unaffected by clouds, however, the snow-cover signature is significantly affected by melting snow and the microwaves may be transparent to thin snow (less than 3cm). Both optical and microwave sensors have problems discerning snow beneath forest canopies. This paper describes a method that combines ground and satellite data to produce a Multiple-Dataset Snow-Cover Product (MDSCP). Comparisons with current snow-cover products show that the MDSCP draws together the advantages of each of its component products while minimizing their potential errors. Improved estimates of the snow-covered area are derived through the addition of two snow-cover classes ("thin or patchy" and "high elevation" snow cover) and from the analysis of the climate station data within each class. The compatibility of this method for use with Moderate Resolution Imaging Spectroradiometer (MODIS) data, which will be available in 2000, is also discussed. With the assimilation of these data, the resolution of the MDSCP would be improved both spatially and temporally and the analysis would become completely automated.

Dust on Snow Processes and Impacts in the Upper Colorado River Basin

NASA Astrophysics Data System (ADS)

Skiles, M.; Painter, T. H.; Okin, G. S.

2015-12-01

In the Upper Colorado River Basin episodic deposition of mineral dust onto mountain snow cover frequently occurs in the spring when wind speeds and dust emission peaks on the nearby Colorado Plateau, and deposition rates have increased since the intensive settlement in the western USA in the mid 1880s. Dust deposition darkens the snow surface, and accelerates snowmelt through reduction of albedo and further indirect reduction of albedo by accelerating the growth of snow grain size. Observation and modeling of dust-on-snow processes began in 2005 at Senator Beck Basin Study Area (SBBSA) in the San Juan Mountains, CO, work which has shown that dust advances melt, shifts runoff timing and intensity, and reduces total water yield. The consistency of deposition and magnitude of impacts highlighted the need for more detailed understanding of the radiative impacts of dust-on-snow in this region. Here I will present results from a novel, high resolution, daily snow property dataset, collected at SBBSA over the 2013 ablation season, to facilitate physically based radiative transfer and snowmelt modeling. Measurements included snow albedo and vertical profiles of snow density, optical snow grain size, and dust/black carbon concentrations. This dataset was used to assess the relationship between episodic dust events, snow grain growth, and albedo over time, and observe the relation between deposited dust and melt water. Additionally, modeling results include the determination of the regionally specific dust-on-snow complex refractive index and radiative forcing partitioning between dust and black carbon, and dust and snow grain growth.

Subgrid parameterization of snow distribution at a Mediterranean site using terrestrial photography

NASA Astrophysics Data System (ADS)

Pimentel, Rafael; Herrero, Javier; José Polo, María

2017-02-01

Subgrid variability introduces non-negligible scale effects on the grid-based representation of snow. This heterogeneity is even more evident in semiarid regions, where the high variability of the climate produces various accumulation melting cycles throughout the year and a large spatial heterogeneity of the snow cover. This variability in a watershed can often be represented by snow accumulation-depletion curves (ADCs). In this study, terrestrial photography (TP) of a cell-sized area (30 × 30 m) was used to define local snow ADCs at a Mediterranean site. Snow-cover fraction (SCF) and snow-depth (h) values obtained with this technique constituted the two datasets used to define ADCs. A flexible sigmoid function was selected to parameterize snow behaviour on this subgrid scale. It was then fitted to meet five different snow patterns in the control area: one for the accumulation phase and four for the melting phase in a cycle within the snow season. Each pattern was successfully associated with the snow conditions and previous evolution. The resulting ADCs were associated to certain physical features of the snow, which were used to incorporate them in the point snow model formulated by Herrero et al. (2009) by means of a decision tree. The final performance of this model was tested against field observations recorded over four hydrological years (2009-2013). The calibration and validation of this ADC snow model was found to have a high level of accuracy, with global RMSE values of 105.8 mm for the average snow depth and 0.21 m2 m-2 for the snow-cover fraction in the control area. The use of ADCs on the cell scale proposed in this research provided a sound basis for the extension of point snow models to larger areas by means of a gridded distributed calculation.

Use of distributed snow cover information to update snow storages of a lumped rainfall-runoff model operationally

NASA Astrophysics Data System (ADS)

Lisniak, D.; Meissner, D.; Klein, B.; Pinzinger, R.

2013-12-01

The German Federal Institute of Hydrology (BfG) offers navigational water-level forecasting services on the Federal Waterways, like the rivers Rhine and Danube. In cooperation with the Federal States this mandate also includes the forecasting of flood events. For the River Rhine, the most frequented inland waterway in Central Europe, the BfG employs a hydrological model (HBV) coupled to a hydraulic model (SOBEK) by the FEWS-framework to perform daily forecasts of water-levels operationally. Sensitivity studies have shown that the state of soil water storage in the hydrological model is a major factor of uncertainty when performing short- to medium-range forecasts some days ahead. Taking into account the various additional sources of uncertainty associated with hydrological modeling, including measurement uncertainties, it is essential to estimate an optimal initial state of the soil water storage before propagating it in time, forced by meteorological forecasts, and transforming it into discharge. We show, that using the Ensemble Kalman Filter these initial states can be updated straightforward under certain hydrologic conditions. However, this approach is not sufficient if the runoff is mainly generated by snow melt. Since the snow cover evolution is modeled rather poorly by the HBV-model in our operational setting, flood events caused by snow melt are consistently underestimated by the HBV-model, which has long term effects in basins characterized by a nival runoff regime. Thus, it appears beneficial to update the snow storage of the HBV-model with information derived from regionalized snow cover observations. We present a method to incorporate spatially distributed snow cover observations into the lumped HBV-model. We show the plausibility of this approach and asses the benefits of a coupled snow cover and soil water storage updating, which combine a direct insertion with an Ensemble Kalman Filter. The Ensemble Kalman Filter used here takes into account the

Role of snow and glacier melt in controlling river hydrology in Liddar watershed (western Himalaya) under current and future climate

NASA Astrophysics Data System (ADS)

Jeelani, G.; Feddema, Johannes J.; van der Veen, Cornelis J.; Stearns, Leigh

2012-12-01

Snowmelt and icemelt are believed to be important regulators of seasonal discharge of Himalayan rivers. To analyze the long term contribution of snowmelt and glacier/icemelt to river hydrology we apply a water budget model to simulate hydrology of the Liddar watershed in the western Himalaya, India for the 20th century (1901-2010) and future IPCC A1B climate change scenario. Long term (1901-2010) temperature and precipitation data in this region show a warming trend (0.08°C yr-1) and an increase in precipitation (0.28 mm yr-1), with a significant variability in seasonal trends. In particular, winter months have undergone the most warming, along with a decrease in precipitation rates; precipitation has increased throughout the spring. These trends have accelerated the melting and rapid disappearance of snow, causing a seasonal redistribution in the availability of water. Our model results show that about 60% of the annual runoff of the Liddar watershed is contributed from the snowmelt, while only 2% is contributed from glacier ice. The climate trend observed from the 1901 to 2010 time period and its impact on the availability of water will become significantly worse under the IPCC climate change scenarios. Our results suggest that there is a significant shift in the timing and quantity of water runoff in this region of the Himalayas due to snow distribution and melt. With greatly increased spring runoff and its reductions in summer potentially leading to reduced water availability for irrigation agriculture in summer.

Snow cover data records from satellite and conventional measurements

NASA Astrophysics Data System (ADS)

Derksen, C.; Brown, R.; Wang, L.

2008-12-01

A major goal of snow-related research in the Climate Research Division of Environment Canada is the development of consistent snow cover information from satellite and in situ data sources for climate monitoring and model evaluation. This work involves new satellite algorithm development for reliable mapping of snow water equivalent (SWE), snow cover extent (SCE) and snow cover onset and melt dates, evaluation of existing snow cover products such as the NOAA weekly data set with in situ and satellite data, and the reconstruction and reanalysis of snow cover information from the application of physical snow models, geostatistics and data assimilation methods. In the context of the International Polar Year, a major effort is being made to develop and evaluate snow cover information over the Arctic region with a particular focus on the dynamic spring melt period where positive feedbacks to the climate system are more pronounced. Assessment of the NOAA daily and weekly SCE products with MODIS and QuikSCAT derived datasets identified a systematic late bias of 2-3 weeks in snow-off dates over northern Canada. This bias was not observed over northern Eurasia which suggests that regional differences in variables such as lake fraction and cloud cover are systematically influencing the accuracy of the NOAA product over northern Canada. Considerable progress has been made in deriving passive microwave derived SWE information over sub- Arctic regions of North America where pre-existing algorithms were unable to account for the influence of forest cover and lake ice. Previous uncertainties in retrieving SWE across the boreal forest have been resolved with the combination of 18.7 and 10.7 GHz measurements from the Advanced Microwave Scanning Radiometer (AMSR-E; 2002-present). Full time series development (1978-onwards) remains problematic, however, because 10.7 GHz measurements are not available from the Special Sensor Microwave/Imager (1987-present). Satellite measurements

Bioavailability of mineral-bound iron to a snow algae-bacteria co-culture and implications for albedo-altering snow algae blooms.

PubMed

Harrold, Z R; Hausrath, E M; Garcia, A H; Murray, A E; Tschauner, O; Raymond, J; Huang, S

2018-01-26

Snow algae can form large-scale blooms across the snowpack surface and near-surface environments. These pigmented blooms can decrease snow albedo, increase local melt rates, and may impact the global heat budget and water cycle. Yet, underlying causes for the geospatial occurrence of these blooms remain unconstrained. One possible factor contributing to snow algae blooms is the presence of mineral dust as a micronutrient source. We investigated the bioavailability of iron (Fe) -bearing minerals, including forsterite (Fo 90 , Mg 1.8 Fe 0.2 SiO 4 ), goethite, smectite and pyrite as Fe sources for a Chloromonas brevispina - bacteria co-culture through laboratory-based experimentation. Fo 90 was capable of stimulating snow algal growth and increased the algal growth rate in otherwise Fe-depleted co-cultures. Fo 90 -bearing systems also exhibited a decrease in bacteria:algae ratios compared to Fe-depleted conditions, suggesting a shift in microbial community structure. The C. brevispina co-culture also increased the rate of Fo 90 dissolution relative to an abiotic control. Analysis of 16S rRNA genes in the co-culture identified Gammaproteobacteria , Betaprotoeobacteria and Sphingobacteria , all of which are commonly found in snow and ice environments. Archaea were not detected. Collimonas and Pseudomonas , which are known to enhance mineral weathering rates, comprised two of the top eight (> 1 %) OTUs. These data provide unequivocal evidence that mineral dust can support elevated snow algae growth under otherwise Fe-depleted growth conditions, and that snow algae can enhance mineral dissolution under these conditions. IMPORTANCE Fe, a key micronutrient for photosynthetic growth, is necessary to support the formation of high-density snow algae blooms. The laboratory experiments described herein allow for a systematic investigation of snow algae-bacteria-mineral interactions and their ability to mobilize and uptake mineral-bound Fe. Results provide unequivocal and

Impacts of Early Summer Eurasian Snow Cover Change on Atmospheric Circulation in Northern Mid-Latitudes

NASA Astrophysics Data System (ADS)

Nozawa, T.

2016-12-01

Recently, Japan Aerospace Exploration Agency (JAXA) has developed a new long-term snow cover extent (SCE) product using Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) data spanning from 1980's to date. This new product (JAXA/SCE) has higher spatial resolution and smaller commission error compared with traditional SCE dataset of National Oceanic and Atmospheric Administration (NOAA/SCE). Continuity of the algorithm is another strong point in JAXA/SCE. According to the new JAXA/SCE dataset, the Eurasian SCE has been significantly retreating since 1980's, especially in late spring and early summer. Here, we investigate impacts of early summer Eurasian snow cover change on atmospheric circulation in Northern mid-latitudes, especially over the East Asia, using the new JAXA/SCE dataset and a few reanalysis data. We will present analyzed results on relationships between early summer SCE anomaly over the Eurasia and changes in atmospheric circulations such as upper level zonal jets (changes in strength, positions, etc.) over the East Asia.

Snow and glacier change in koshi Basin Himalaya and its response to global warming

NASA Astrophysics Data System (ADS)

Gao, Y.; Yang, X.; Yao, T.; Yufeng, D.

2010-12-01

Recently, the argument that Himalayan glaciers will completely melt is rather controversial and the U.N.'s leading panel on climate change has apologized for misleading data published in a 2007 report that warned Himalayan glaciers could melt by 2035. Why the gradual melting of Himalayan glaciers makes most of the major media headlines? This is because Himalayan glacier is the headstream of major rivers in South Asia and Southeast Asia and more than 1/6 people live there. If mass of the glaciers melt or even disappear, people who rely on those rivers will be at risk. After this dispute, we need to realize that:”Although the melting rate still need to further study, the Himalayan glaciers are indeed melting. And in these areas, there are more uncertainties to affect water resource, such as snow fall, precipitation, regional temperature changes and so on”. Koshi Basin Himalaya, located in the boundary between China and Nepal, consist of three rivers i.e. Sun Koshi, Arun river (the headwaters of arun river in China called Pengqu) and Tamur. All of them converge to India Ganga River. The total area of Koshi Basin is about ~57,870 km2 and elevation ranges from 21 m (plain) to 8825m (Mountain glacier). This basin has the typical vertical zonation of Himalaya, so we choose it as the study area. Based on the snow cover data observed by the Moderate Resolution Imaging Spectroradiometer (MODIS) on the NASA Terra spacecraft from 2000-2010, the spatial-temporal distribution and variation of snow cover over the koshi basin are statistical analyzed. Glacier changes are also detected from Landsat images in 2000, 2005 and 2010. It is found that snow cover areas are mainly concentrated in the Ridge of Himalaya Mountain. And there are more persistently snow covered areas and glaciers in the South Slope of Himalaya Mountain with aspect to the North Slope, although the mean elevation of the North Slope is higher than south slope. During the decade of 2000-2010, a slight decreasing

Early spring post-fire snow albedo dynamics in high latitude boreal forests using Landsat-8 OLI data

PubMed Central

Wang, Zhuosen; Erb, Angela M.; Schaaf, Crystal B.; Sun, Qingsong; Liu, Yan; Yang, Yun; Shuai, Yanmin; Casey, Kimberly A.; Román, Miguel O.

2018-01-01

Taking advantage of the improved radiometric resolution of Landsat-8 OLI which, unlike previous Landsat sensors, does not saturate over snow, the progress of fire recovery progress at the landscape scale (< 100m) is examined. High quality Landsat-8 albedo retrievals can now capture the true reflective and layered character of snow cover over a full range of land surface conditions and vegetation densities. This new capability particularly improves the assessment of post-fire vegetation dynamics across low- to high- burn severity gradients in Arctic and boreal regions in the early spring, when the albedos during recovery show the greatest variation. We use 30 m resolution Landsat-8 surface reflectances with concurrent coarser resolution (500m) MODIS high quality full inversion surface Bidirectional Reflectance Distribution Functions (BRDF) products to produce higher resolution values of surface albedo. The high resolution full expression shortwave blue sky albedo product performs well with an overall RMSE of 0.0267 between tower and satellite measures under both snow-free and snow-covered conditions. While the importance of post-fire albedo recovery can be discerned from the MODIS albedo product at regional and global scales, our study addresses the particular importance of early spring post-fire albedo recovery at the landscape scale by considering the significant spatial heterogeneity of burn severity, and the impact of snow on the early spring albedo of various vegetation recovery types. We found that variations in early spring albedo within a single MODIS gridded pixel can be larger than 0.6. Since the frequency and severity of wildfires in Arctic and boreal systems is expected to increase in the coming decades, the dynamics of albedo in response to these rapid surface changes will increasingly impact the energy balance and contribute to other climate processes and physical feedback mechanisms. Surface radiation products derived from Landsat-8 data will thus

Early Spring Post-Fire Snow Albedo Dynamics in High Latitude Boreal Forests Using Landsat-8 OLI Data

NASA Technical Reports Server (NTRS)

Wang, Zhuosen; Erb, Angela M.; Schaaf, Crystal B.; Sun, Qingsong; Liu, Yan; Yang, Yun; Shuai, Yanmin; Casey, Kimberly A.; Roman, Miguel O.

2016-01-01

Taking advantage of the improved radiometric resolution of Landsat-8 OLI which, unlike previous Landsat sensors, does not saturate over snow, the progress of fire recovery progress at the landscape scale (less than 100 m) is examined. High quality Landsat-8 albedo retrievals can now capture the true reflective and layered character of snow cover over a full range of land surface conditions and vegetation densities. This new capability particularly improves the assessment of post-fire vegetation dynamics across low- to high-burn severity gradients in Arctic and boreal regions in the early spring, when the albedos during recovery show the greatest variation. We use 30 m resolution Landsat-8 surface reflectances with concurrent coarser resolution (500 m) MODIS high quality full inversion surface Bidirectional Reflectance Distribution Functions (BRDF) products to produce higher resolution values of surface albedo. The high resolution full expression shortwave blue sky albedo product performs well with an overall RMSE of 0.0267 between tower and satellite measures under both snow-free and snow-covered conditions. While the importance of post-fire albedo recovery can be discerned from the MODIS albedo product at regional and global scales, our study addresses the particular importance of early spring post-fire albedo recovery at the landscape scale by considering the significant spatial heterogeneity of burn severity, and the impact of snow on the early spring albedo of various vegetation recovery types. We found that variations in early spring albedo within a single MODIS gridded pixel can be larger than 0.6. Since the frequency and severity of wildfires in Arctic and boreal systems is expected to increase in the coming decades, the dynamics of albedo in response to these rapid surface changes will increasingly impact the energy balance and contribute to other climate processes and physical feedback mechanisms. Surface radiation products derived from Landsat-8 data will

Early spring post-fire snow albedo dynamics in high latitude boreal forests using Landsat-8 OLI data.

PubMed

Wang, Zhuosen; Erb, Angela M; Schaaf, Crystal B; Sun, Qingsong; Liu, Yan; Yang, Yun; Shuai, Yanmin; Casey, Kimberly A; Román, Miguel O

2016-11-01

Taking advantage of the improved radiometric resolution of Landsat-8 OLI which, unlike previous Landsat sensors, does not saturate over snow, the progress of fire recovery progress at the landscape scale (< 100m) is examined. High quality Landsat-8 albedo retrievals can now capture the true reflective and layered character of snow cover over a full range of land surface conditions and vegetation densities. This new capability particularly improves the assessment of post-fire vegetation dynamics across low- to high- burn severity gradients in Arctic and boreal regions in the early spring, when the albedos during recovery show the greatest variation. We use 30 m resolution Landsat-8 surface reflectances with concurrent coarser resolution (500m) MODIS high quality full inversion surface Bidirectional Reflectance Distribution Functions (BRDF) products to produce higher resolution values of surface albedo. The high resolution full expression shortwave blue sky albedo product performs well with an overall RMSE of 0.0267 between tower and satellite measures under both snow-free and snow-covered conditions. While the importance of post-fire albedo recovery can be discerned from the MODIS albedo product at regional and global scales, our study addresses the particular importance of early spring post-fire albedo recovery at the landscape scale by considering the significant spatial heterogeneity of burn severity, and the impact of snow on the early spring albedo of various vegetation recovery types. We found that variations in early spring albedo within a single MODIS gridded pixel can be larger than 0.6. Since the frequency and severity of wildfires in Arctic and boreal systems is expected to increase in the coming decades, the dynamics of albedo in response to these rapid surface changes will increasingly impact the energy balance and contribute to other climate processes and physical feedback mechanisms. Surface radiation products derived from Landsat-8 data will thus

Microbial cell retention in a melting High Arctic snowpack, Svalbard

NASA Astrophysics Data System (ADS)

Zarsky, Jakub; Björkman, Mats; Kühnel, Rafael; Hell, Katherina; Hodson, Andy; Sattler, Birgit; Psenner, Roland

2014-05-01

Introduction The melting snow pack represents a highly dynamic system not only for chemical compounds but also for bacterial cells. Microbial activity was found at subzero temperatures in ice veins when liquid water persists due to high concentration of ions on the surface of snow crystals and brine channels between large ice crystals in ice. Several observations also suggest microbial activity under subzero temperatures in seasonal snow. Even with regard to the spatial and temporal relevance of snow ecosystems, microbial activity in such an extreme habitat represents a relatively small proportion in the carbon flux of the global ecosystem and even of the glacial ecosystems specifically. On the other hand, it represents a remarkable piece of mosaic of the microbial activity in glacial ecosystems because the snow pack represents the first contact between the atmosphere and cryosphere. This topic also embodies vital crossovers to biogeochemistry and ecotoxicology, offering a quantitative view of utilization of various substrates relevant for downstream ecosystems. Here we present our study of the dynamics of both solvents and cells suspended in meltwater of the melting snowpack on a high arctic glacier to demonstrate the spatio-temporal constraint of interaction between solvent and bacterial cells in this environment. Method We used 6 lysimeters inserted into the bottom of the snowpack to collect replicated samples of melt water before it comes into contact with basal ice or slush layer at the base of the snow pack. The sampling site was chosen at Midre Lovénbreen (Svalbard, Kongsfjorden, MLB stake 6) where the snow pack showed melting on the surface but the basal ice was still dry. Sampling was conducted in June 2010 for a period of 10 days once per day and the snow profile was sampled according to distinguished layers in the profile at the beginning of the field mission and as bulk at its end. The height of snow above the lysimeters dropped from the initial 74 cm

Snow water equivalent mapping in Norway

NASA Astrophysics Data System (ADS)

Tveito, O. E.; Udnæs, H.-C.; Engeset, R.; Førland, E. J.; Isaksen, K.; Mengistu, Z.

2003-04-01

In high latitude area snow covers the ground large parts of the year. Information about the water volume as snow is of major importance in many respects. Flood forecasters at NVE need it in order to assess possible flood risks. Hydropower producers need it to plan the most efficient production of the water in their reservoirs, traders to estimate the potential energy available for the market. Meteorologists on their side use the information as boundary conditions in weather forecasting models. The Norwegian meteorological institute has provided snow accumulation maps for Norway for more than 50 years. These maps are now produced twice a month in the winter season. They show the accumulated precipitation in the winter season from the day the permanent snow cover is established. They do however not take melting into account, and do therefore not give a good description of the actual snow amounts during and after periods with snowmelt. Due to an increased need for a direct measure of water volumes as snow cover, met.no and NVE initialized a joint project in order to establish maps of the actual snow cover expressed in water equivalents. The project utilizes recent developments in the use of GIS in spatial modeling. Daily precipitation and temperature are distributed in space by using objective spatial interpolation methods. The interpolation considers topographical and other geographical parameters as well as weather type information. A degree-day model is used at each modeling point to calculate snow-accumulation and snowmelt. The maps represent a spatial scale of 1x1 km2. The modeled snow reservoir is validated by snow pillow values as well traditional snow depth observations. Preliminary results show that the new snow modeling approach reproduces the snow water equivalent well. The spatial approach also opens for a wide use in the terms of areal analysis.

The Contribution to High Asia Runoff from Ice and Snow (CHARIS): Understanding the source and trends of cryospheric contributions to the water balance

NASA Astrophysics Data System (ADS)

Rittger, K.; Armstrong, R. L.; Bair, N.; Racoviteanu, A.; Brodzik, M. J.; Hill, A. F.; Wilson, A. M.; Khan, A. L.; Ramage, J. M.; Khalsa, S. J. S.; Barrett, A. P.; Raup, B. H.; Painter, T. H.

2017-12-01

The Contribution to High Asia Runoff from Ice and Snow, or CHARIS, project is systematically assessing the role that glaciers and seasonal snow play in the freshwater resources of Central and South Asia. The study area encompasses roughly 3 million square kilometers of the Himalaya, Karakoram, Hindu Kush, Pamir and Tien Shan mountain ranges that drain to five major rivers: the Ganges, Brahmaputra, Indus, Amu Darya and Syr Darya. We estimate daily snow and glacier ice contributions to the water balance. Our automated partitioning method generates daily maps of 1) snow over ice (SOI), 2) exposed glacier ice (EGI), 3) debris covered glacier ice (DGI) and 4) snow over land (SOL) using fractional snow cover, snow grain size, and annual minimum ice and snow from the 500 m MODIS-derived MODSCAG and MODICE products. Maps of snow and ice cover are validated using high-resolution (30 m) maps of snow, ice, and debris cover from Landsat. The probability of detection is 0.91 and precision is 0.85 for MODICE. We examine trends in annual and monthly snow and ice maps and use daily maps as inputs to a calibrated temperature-index model and an uncalibrated energy balance model, ParBal. Melt model results and measurements of isotopes and specific ions used as an independent validation of melt modeling indicate a sharp geographic contrast in the role of snow and ice melt to downstream water supplies between the arid Tien Shan and Pamir ranges of Central Asia, where melt water dominates dry season flows, and the monsoon influenced central and eastern Himalaya where rain controls runoff. We also compare melt onset and duration from the melt models to the Calibrated, Enhanced Resolution Passive Microwave Brightness Temperature Earth Science Data Record. Trend analysis of annual and monthly area of permanent snow and ice (the union of SOI and EGI) for 2000 to 2016 shows statistically significant negative trends in the Ganges and Brahmaputra basins. There are no statistically significant

On the absorption of solar radiation in a layer of oil beneath a layer of snow

NASA Technical Reports Server (NTRS)

Larsen, J. C.; Barkstrom, B. R.

1976-01-01

Solar energy deposition in oil layers covered by snow is calculated for three model snow types using radiative transfer theory. It is suggested that excess absorbed energy is unlikely to escape, so that some melting is likely to occur for snow depths less than about 4 cm.

Microbial Community Analysis of Colored Snow from an Alpine Snowfield in Northern Japan Reveals the Prevalence of Betaproteobacteria with Snow Algae.

PubMed

Terashima, Mia; Umezawa, Kazuhiro; Mori, Shoichi; Kojima, Hisaya; Fukui, Manabu

2017-01-01

Psychrophilic algae blooms can be observed coloring the snow during the melt season in alpine snowfields. These algae are important primary producers on the snow surface environment, supporting the microbial community that coexists with algae, which includes heterotrophic bacteria and fungi. In this study, we analyzed the microbial community of green and red-colored snow containing algae from Mount Asahi, Japan. We found that Chloromonas spp. are the dominant algae in all samples analyzed, and Chlamydomonas is the second-most abundant genus in the red snow. For the bacterial community profile, species belonging to the subphylum Betaproteobacteria were frequently detected in both green and red snow, while members of the phylum Bacteroidetes were also prominent in red snow. Furthermore, multiple independently obtained strains of Chloromonas sp. from inoculates of red snow resulted in the growth of Betaproteobacteria with the alga and the presence of bacteria appears to support growth of the xenic algal cultures under laboratory conditions. The dominance of Betaproteobacteria in algae-containing snow in combination with the detection of Chloromonas sp. with Betaproteobacteria strains suggest that these bacteria can utilize the available carbon source in algae-rich environments and may in turn promote algal growth.

Impacts of snow darkening by absorbing aerosols on South Asian monsoon

NASA Astrophysics Data System (ADS)

Kim, K. M.; Lau, W. K. M.; Kim, M. K.; Sang, J.; Yasunari, T. J.; Koster, R. D.

2016-12-01

Seasonal heating over the Tibetan Plateau is a main driver of the onset of the South Asian Monsoon. Aerosols can play an important role in pre- and early monsoon seasonal heating process over the Tibetan Plateau by increasing atmospheric heating in the northern India, and by heating of the surface of the Tibetan Plateau and Himalayan slopes, via reduction of albedo of the snow surface through surface deposition - the so call snow-darkening effect (SDE). To examine the impact of SDE on weather and climate during late spring and early summer, two sets of NASA/GEOS-5 model simulations with and without SDE are conducted. Results show that SDE-induced surface heating accelerates snow melts and increases surface temperature over 4K in the entire Tibetan Plateau regions during boreal summer. Warmer Tibetan Plateau further accelerates seasonal warming in the upper troposphere and increases the north-south temperature gradient between the Tibetan Plateau and the equatorial Indian Ocean. This reversal of the north-south temperature gradient is a primary cause of the onset of the South Asian monsoon. SDE-induced increase of the meridional temperature gradient drives meridional circulation and enhanced upper tropospheric easterlies and lower tropospheric westerlies, and intensifies monsoon circulation and rainfall. This pattern enhances the EHP-like circulation anomalies induced by atmospheric heating of absorbing aerosols over the northern India. SDE-induced change in the India subcontinent differs that in Eurasia. SDE-induced land-atmospheric interactions in two regions will be also compared.

In-situ measurements of light-absorbing impurities in snow of glacier on Mt. Yulong and implications for radiative forcing estimates.

PubMed

Niu, Hewen; Kang, Shichang; Shi, Xiaofei; Paudyal, Rukumesh; He, Yuanqing; Li, Gang; Wang, Shijin; Pu, Tao; Shi, Xiaoyi

2017-03-01

The Tibetan Plateau (TP) or the third polar cryosphere borders geographical hotspots for discharges of black carbon (BC). BC and dust play important roles in climate system and Earth's energy budget, particularly after they are deposited on snow and glacial surfaces. BC and dust are two kinds of main light-absorbing impurities (LAIs) in snow and glaciers. Estimating concentrations and distribution of LAIs in snow and glacier ice in the TP is of great interest because this region is a global hotspot in geophysical research. Various snow samples, including surface aged-snow, superimposed ice and snow meltwater samples were collected from a typical temperate glacier on Mt. Yulong in the snow melt season in 2015. The samples were determined for BC, Organic Carbon (OC) concentrations using an improved thermal/optical reflectance (DRI Model 2001) method and gravimetric method for dust concentrations. Results indicated that the LAIs concentrations were highly elevation-dependent in the study area. Higher contents and probably greater deposition at relative lower elevations (generally <5000masl) of the glacier was observed. Temporal difference of LAIs contents demonstrated that LAIs in snow of glacier gradually increased as snow melting progressed. Evaluations of the relative absorption of BC and dust displayed that the impact of dust on snow albedo and radiative forcing (RF) is substantially larger than BC, particularly when dust contents are higher. This was verified by the absorption factor, which was <1.0. In addition, we found the BC-induced albedo reduction to be in the range of 2% to nearly 10% during the snow melting season, and the mean snow albedo reduction was 4.63%, hence for BC contents ranging from 281 to 894ngg -1 in snow of a typical temperate glacier on Mt. Yulong, the associated instantaneous RF will be 76.38-146.96Wm -2 . Further research is needed to partition LAIs induced glacial melt, modeling researches in combination with long-term in

PBSM3D: A finite volume, scalar-transport blowing snow model for use with variable resolution meshes

NASA Astrophysics Data System (ADS)

Marsh, C.; Wayand, N. E.; Pomeroy, J. W.; Wheater, H. S.; Spiteri, R. J.

2017-12-01

Blowing snow redistribution results in heterogeneous snowcovers that are ubiquitous in cold, windswept environments. Capturing this spatial and temporal variability is important for melt and runoff simulations. Point scale blowing snow transport models are difficult to apply in fully distributed hydrological models due to landscape heterogeneity and complex wind fields. Many existing distributed snow transport models have empirical wind flow and/or simplified wind direction algorithms that perform poorly in calculating snow redistribution where there are divergent wind flows, sharp topography, and over large spatial extents. Herein, a steady-state scalar transport model is discretized using the finite volume method (FVM), using parameterizations from the Prairie Blowing Snow Model (PBSM). PBSM has been applied in hydrological response units and grids to prairie, arctic, glacier, and alpine terrain and shows a good capability to represent snow redistribution over complex terrain. The FVM discretization takes advantage of the variable resolution mesh in the Canadian Hydrological Model (CHM) to ensure efficient calculations over small and large spatial extents. Variable resolution unstructured meshes preserve surface heterogeneity but result in fewer computational elements versus high-resolution structured (raster) grids. Snowpack, soil moisture, and streamflow observations were used to evaluate CHM-modelled outputs in a sub-arctic and an alpine basin. Newly developed remotely sensed snowcover indices allowed for validation over large basins. CHM simulations of snow hydrology were improved by inclusion of the blowing snow model. The results demonstrate the key role of snow transport processes in creating pre-melt snowcover heterogeneity and therefore governing post-melt soil moisture and runoff generation dynamics.

How Much Water is in That Snowpack? Improving Basin-wide Snow Water Equivalent Estimates from the Airborne Snow Observatory

NASA Astrophysics Data System (ADS)

Bormann, K.; Painter, T. H.; Marks, D. G.; Kirchner, P. B.; Winstral, A. H.; Ramirez, P.; Goodale, C. E.; Richardson, M.; Berisford, D. F.

2014-12-01

In the western US, snowmelt from the mountains contribute the vast majority of fresh water supply, in an otherwise dry region. With much of California currently experiencing extreme drought, it is critical for water managers to have accurate basin-wide estimations of snow water content during the spring melt season. At the forefront of basin-scale snow monitoring is the Jet Propulsion Laboratory's Airborne Snow Observatory (ASO). With combined LiDAR /spectrometer instruments and weekly flights over key basins throughout California, the ASO suite is capable of retrieving high-resolution basin-wide snow depth and albedo observations. To make best use of these high-resolution snow depths, spatially distributed snow density data are required to leverage snow water equivalent (SWE) from the measured depths. Snow density is a spatially and temporally variable property and is difficult to estimate at basin scales. Currently, ASO uses a physically based snow model (iSnobal) to resolve distributed snow density dynamics across the basin. However, there are issues with the density algorithms in iSnobal, particularly with snow depths below 0.50 m. This shortcoming limited the use of snow density fields from iSnobal during the poor snowfall year of 2014 in the Sierra Nevada, where snow depths were generally low. A deeper understanding of iSnobal model performance and uncertainty for snow density estimation is required. In this study, the model is compared to an existing climate-based statistical method for basin-wide snow density estimation in the Tuolumne basin in the Sierra Nevada and sparse field density measurements. The objective of this study is to improve the water resource information provided to water managers during ASO operation in the future by reducing the uncertainty introduced during the snow depth to SWE conversion.

Snow and Ice Crust Changes over Northern Eurasia since 1966

NASA Astrophysics Data System (ADS)

Bulygina, O.; Groisman, P. Y.; Razuvaev, V.; Radionov, V.

2009-12-01

When temperature of snow cover reaches zero Celsius first time since its establishment, snowmelt starts. In many parts of the world this process can be lengthy. The initial amount of heat that “arrives” to the snowpack might be insufficient for complete snowmelt, during the colder nights re-freeze of the melted snow may occur (thus creating the ice crust layers), and a new cold front (or the departure of the warm front that initiated melt) can decrease temperatures below the freezing point again and stop the snowmelt completely. It well can be that first such snowmelt occurs in winter (thaw day) and for several months thereafter snowpack stays on the ground. However, even the first such melt initiates a process of snow metamorphosis on its surface changing snow albedo and generating snow crust as well as on its bottom generating ice crust. Once emerged, the crusts will not disappear until the complete snowmelt. Furthermore, these crusts have numerous pathways of impact on the wild birds and animals in the Arctic environment as well as on domesticated reindeers. In extreme cases, the crusts may kill some wild species and prevent reindeers’ migration and feeding. Ongoing warming in high latitudes created situations when in the western half of Eurasian continent days with thaw became more frequent. Keeping in mind potential detrimental impacts of winter thaws and associated with them snow/ice crust development, it is worthwhile to study directly what are the major features of snow and ice crust over Eurasia and what is their dynamics. For the purpose of this study, we employed the national snow survey data set archived at the Russian Institute for Hydrometeorological Information. The dataset has routine snow surveys run throughout the cold season each decade (during the intense snowmelt, each 5 days) at all meteorological stations of the former USSR, thereafter, in Russia since 1966. Prior to 1966 snow surveys are also available but the methodology of

Snow multivariable data assimilation for hydrological predictions in Alpine sites

NASA Astrophysics Data System (ADS)

Piazzi, Gaia; Thirel, Guillaume; Campo, Lorenzo; Gabellani, Simone; Stevenin, Hervè

2017-04-01

Snowpack dynamics (snow accumulation and ablation) strongly impacts on hydrological processes in Alpine areas. During the winter season the presence of snow cover (snow accumulation) reduces the drainage in the basin with a resulting lower watershed time of concentration in case of possible rainfall events. Moreover, the release of the significant water volume stored in winter (snowmelt) considerably contributes to the total discharge during the melting period. Therefore when modeling hydrological processes in snow-dominated catchments the quality of predictions deeply depends on how the model succeeds in catching snowpack dynamics. The integration of a hydrological model with a snow module allows improving predictions of river discharges. Besides the well-known modeling limitations (uncertainty in parameterizations; possible errors affecting both meteorological forcing data and initial conditions; approximations in boundary conditions), there are physical factors that make an exhaustive reconstruction of snow dynamics complicated: snow intermittence in space and time, stratification and slow phenomena like metamorphism processes, uncertainty in snowfall evaluation, wind transportation, etc. Data Assimilation (DA) techniques provide an objective methodology to combine several independent snow-related data sources (model simulations, ground-based measurements and remote sensed observations) in order to obtain the most likely estimate of snowpack state. This study presents SMASH (Snow Multidata Assimilation System for Hydrology), a multi-layer snow dynamic model strengthened by a multivariable DA framework for hydrological purposes. The model is physically based on mass and energy balances and can be used to reproduce the main physical processes occurring within the snowpack: accumulation, density dynamics, melting, sublimation, radiative balance, heat and mass exchanges. The model is driven by observed forcing meteorological data (air temperature, wind velocity

Impacts of light-absorbing impurities on snow and their quantification with bidirectional reflectance measurements

NASA Astrophysics Data System (ADS)

Gritsevich, Maria; Peltoniemi, Jouni; Meinander, Outi; Dagsson-Waldhauserová, Pavla; Zubko, Nataliya; Hakala, Teemu; Virkkula, Aki; Svensson, Jonas; de Leeuw, Gerrit

2017-04-01

In order to quantify the effects of absorbing impurities on snow and define their contribution to the climate change, we have conducted a series of dedicated bidirectional reflectance measurements. Chimney soot, volcanic sand, and glaciogenic silt have been deposited on the snow in the controlled way. The bidirectional reflectance factors of these targets and untouched snow have been measured using the Finnish Geodetic Institute's field goniospectrometer FIGIFIGO, see, e.g., [1, 2] and references therein. It has been found that the contaminants darken the snow, and modify its appearance mostly as expected, with clear directional signal and modest spectral signal. A remarkable feature is the fact that any absorbing contaminant on snow enhances the metamorphosis under strong sunlight [3, 4]. Immediately after deposition, the contaminated snow surface appears darker than the pure snow in all viewing directions, but the heated soot particles start sinking down deeply into the snow in minutes. The nadir measurement remains darkest, but at larger zenith angles the surface of the soot-contaminated snow changes back to almost as white as clean snow. Thus, for on ground observer the darkening by impurities can be completely invisible, overestimating the albedo, but a nadir looking satellite sees the darkest points, now underestimating the albedo. After more time, also the nadir view brightens, and the remaining impurities may be biased towards more shadowed locations or less absorbing orientations by natural selection. This suggests that at noon the albedo should be lower than in the morning or afternoon. When sunlight stimulates more sinking than melting, albedo should be higher in the afternoon than in the morning, and vice versa when melting is dominating. Thus to estimate the effects caused by black carbon (BC) deposited on snow on climate changes may one need to take into account possible rapid diffusion of the BC inside the snow from its surface. When the snow melt

The application of depletion curves for parameterization of subgrid variability of snow

Treesearch

C. H. Luce; D. G. Tarboton

2004-01-01

Parameterization of subgrid-scale variability in snow accumulation and melt is important for improvements in distributed snowmelt modelling. We have taken the approach of using depletion curves that relate fractional snowcovered area to element-average snow water equivalent to parameterize the effect of snowpack heterogeneity within a physically based mass and energy...

Remote Sensing of Terrestrial Snow and Ice for Global Change Studies

NASA Technical Reports Server (NTRS)

Kelly, Richard; Hall, Dorothy K.

2007-01-01

Snow and ice play a significant role in the Earth's water cycle and are sensitive and informative indicators climate change. Significant changes in terrestrial snow and ice water storage are forecast, and while evidence of large-scale changes is emerging, in situ measurements alone are insufficient to help us understand and explain these changes. Imaging remote sensing systems are capable of successfully observing snow and ice in the cryosphere. This chapter examines how those remote sensing sensors, that now have more than 35 years of observation records, are capable of providing information about snow cover, snow water equivalent, snow melt, ice sheet temperature and ice sheet albedo. While significant progress has been made, especially in the last five years, a better understanding is required of the records of satellite observations of these cryospheric variables.

Snow cover surveys in Alaska from ERTS-1 data

NASA Technical Reports Server (NTRS)

Benson, C. S.

1973-01-01

September and October ERTS scenes have been analyzed to delineate snow cover patterns in northern Alaska's Brooks Range and on Mt. Wrangell, and active volcano in South Central Alaska. ERTS images demonstrate that the snow on the northern foothills of the Brooks Range are significantly more affected by katabatic wind action than are the southern foothills. Aufeis deposits along arctic rivers also can be identified in late summer. A survey of such aufeis deposits could identify additional summertime sources of fresh water supplies. Images of Mt. Wrangell permit monitoring of the interaction between volcanic heat and the mass balance of glaciers that exist on active volcanoes. Temporal changes in the areas of bare rock on the rim of the caldera on the summit reveal significant melting of new snow from an extensive storm on August 18. Digital analysis of data from subsequent passes over the summit on September 7, 23 and 24 revealed considerable bare rock exposed by melting, which is virtually impossible from solar heating at this altitude and date.

Near-Record Early Snowmelt and Signs of Environmental Change in Barrow, Alaska

NASA Astrophysics Data System (ADS)

Stanitski, D.; Cox, C.; Sweeney, C.; Divoky, G.; George, C.; Stone, R.

2015-12-01

The 2015 spring transition in Barrow, AK, was notable with the second earliest date of snow melt on record (JD148, May 28) and earliest ice free conditions on a local lagoon (JD178, June 27). The 73-year time series from the NOAA Global Monitoring Division's Barrow Observatory (BRW) has shown a trend toward earlier spring snowmelt, reinforced in 2015. Anomalous early snowmelt was also observed at nearby Cooper Island where a colony of sea birds, the Black Guillemot, nests each year once snow disappears. The appearance of "first egg" is well correlated with the date of snowmelt at BRW (Fig. 1), as is the ice-out date at the Isaktoak Lagoon (ISK). In 2015, the first egg was observed on JD159 (June 8), the earliest in the 40-year record (source: Friends of Cooper Island, http://cooperisland.org/). Each day of advance in the melt date at BRW results in an annual net radiation increase at the surface of about 1%. The documented changes can influence biogeochemical cycles, permafrost temperatures, and potentially the release of stored carbon. By mid July 2015, a 1°C increase in soil temperature at 0.5-m depth was measured compared to prior years; therefore, the active layer is expected to be unusually deep by autumn. The anomalous warmth that prevailed during spring 2015 can be attributed, in part, to atmospheric circulation, influenced by two typhoons in the North Pacific and the onset of El Niño. Warming was likely amplified locally as the early melting of snow increased absorption of solar radiation. Key factors influencing the trend toward earlier spring snowmelt will be presented as well as those contributing to the anomalous 2015 spring at BRW (e.g., winter snowfall, cloud cover, advection, local sea ice extent), and the impact early melt had on the 2015 summer surface radiation budget. Analysis of interactions underlying this anomaly will aid in developing strategies for improving predictability of interannual variability of the melt season and long-term change.

Winter in Antarctica: dark, cold, windy, and .... wet?? Measurements and modeling of extensive wintertime surface melt

NASA Astrophysics Data System (ADS)

Kuipers Munneke, P.; Luckman, A. J.; Bevan, S. L.; Gilbert, E.; Smeets, P.; van den Broeke, M. R.; Wang, W.; Zender, C. S.; Ashmore, D. W.; Hubbard, B. P.; Orr, A.; King, J.

2017-12-01

We know that increased surface melt, driven by atmospheric warming, contributed to the collapse of ice shelves as observed in the Antarctic Peninsula. This has induced grounded-ice acceleration and increased ice discharge. You may associate this surface melt with the austral summer season, with plenty of solar radiation driving the melt. In contrast, winter in Antarctica evokes images of darkness, snow, and cold. However, we will make you rethink this picture by presenting observations of frequent snow surface melt in winter, from a weather station located in a previously unsurveyed area of the Larsen C Ice Shelf. Peak intensities of this wintertime melt even exceed summertime values, and thermal satellite images show that large ponds of meltwater are formed at the surface in the pitch-dark Antarctic winter. Obviously, we wanted to find out what could drive these strong melt events if it's not the sun. It turns out that these multi-day melt events occur when warm and dry föhn winds descend from the Antarctic Peninsula mountains. Simulations with a high-resolution weather model confirm that these winds generate turbulent fluxes of sensible heat, leading to melt fluxes in excess of 200 W m-2. In 2015 and 2016, about 23% of the annual melt was produced in winter. We use satellite radar to show that winter melt occurs on many more places in the Antarctic Peninsula. It happens every year, although in some years the melting is much more widespread than in others. We think that wintertime melt matters as its refreezing warms the snow and increases snow density. In this way, winter melt preconditions the ice shelf for more extensive surface drainage, potentially leading to meltwater-driven instability.

A Review of Global Satellite-Derived Snow Products

NASA Technical Reports Server (NTRS)

Frei, Allan; Tedesco, Marco; Lee, Shihyan; Foster, James; Hall, Dorothy K.; Kelly, Richard; Robinson, David A.

2011-01-01

Snow cover over the Northern Hemisphere plays a crucial role in the Earth s hydrology and surface energy balance, and modulates feedbacks that control variations of global climate. While many of these variations are associated with exchanges of energy and mass between the land surface and the atmosphere, other expected changes are likely to propagate downstream and affect oceanic processes in coastal zones. For example, a large component of the freshwater flux into the Arctic Ocean comes from snow melt. The timing and magnitude of this flux affects biological and thermodynamic processes in the Arctic Ocean, and potentially across the globe through their impact on North Atlantic Deep Water formation. Several recent global remotely sensed products provide information at unprecedented temporal, spatial, and spectral resolutions. In this article we review the theoretical underpinnings and characteristics of three key products. We also demonstrate the seasonal and spatial patterns of agreement and disagreement amongst them, and discuss current and future directions in their application and development. Though there is general agreement amongst these products, there can be disagreement over certain geographic regions and under conditions of ephemeral, patchy and melting snow

A Review of Global Satellite-Derived Snow Products

NASA Technical Reports Server (NTRS)

Frei, Allan; Tedesco, Marco; Lee, Shihyan; Foster, James; Hall, Dorothy K.; Kelly, Richard; Robinson, David A.

2011-01-01

Snow cover over the Northern Hemisphere plays a crucial role in the Earth's hydrology and surface energy balance, and modulates feedbacks that control variations of global climate. While many of these variations are associated with exchanges of energy and mass between the land surface and the atmosphere, other expected changes are likely to propagate downstream and affect oceanic processes in coastal zones. For example, a large component of the freshwater flux into the Arctic Ocean comes from snow melt. The timing and magnitude of this flux affects biological and thermodynamic processes in the Arctic Ocean, and potentially across the globe through their impact on North Atlantic Deep Water formation. Several recent global remotely sensed products provide information at unprecedented temporal, spatial, and spectral resolutions. In this article we review the theoretical underpinnings and characteristics of three key products. We also demonstrate the seasonal and spatial patterns of agreement and disagreement amongst them, and discuss current and future directions in their application and development. Though there is general agreement amongst these products, there can be disagreement over certain geographic regions and under conditions of ephemeral, patchy and melting snow.

A Review of Global Satellite-derived Snow Products

NASA Technical Reports Server (NTRS)

Frei, Allan; Tedesco, Marco; Lee, Shihyan; Foster, James; Hall, Dorothy K.; Kelly, Richard; Robinson, David A.

2012-01-01

Snow cover over the Northern Hemisphere plays a crucial role in the Earth's hydrology and surface energy balance, and modulates feedbacks that control variations of global climate. While many of these variations are associated with exchanges of energy and mass between the land surface and the atmosphere, other expected changes are likely to propagate downstream and affect oceanic processes in coastal zones. For example, a large component of the freshwater flux into the Arctic Ocean comes from snow melt. The timing and magnitude of this flux affects biological and thermodynamic processes in the Arctic Ocean, and potentially across the globe through their impact on North Atlantic Deep Water formation. Several recent global remotely sensed products provide information at unprecedented temporal, spatial, and spectral resolutions. In this article we review the theoretical underpinnings and characteristics of three key products. We also demonstrate the seasonal and spatial patterns of agreement and disagreement amongst them, and discuss current and future directions in their application and development. Though there is general agreement amongst these products, there can be disagreement over certain geographic regions and under conditions of ephemeral, patchy and melting snow.

Early formation of preferential flow in a homogeneous snowpack observed by micro-CT

NASA Astrophysics Data System (ADS)

Avanzi, Francesco; Petrucci, Giacomo; Matzl, Margret; Schneebeli, Martin; De Michele, Carlo

2017-05-01

We performed X-ray microtomographic observations of wet-snow metamorphism during controlled continuous melting and melt-freeze events in the laboratory. Three blocks of snow were sieved into boxes and subjected to cyclic, superficial heating or heating-cooling to reproduce vertical water infiltration patterns in snow similarly to natural conditions. Periodically, samples were taken at different heights and scanned. Results suggest that wet-snow metamorphism dynamics are highly heterogeneous even in an initially homogeneous snowpack. Consistent with previous work, we observed an increase with time in the thickness of the ice structure, which is a measure of grain size. However, this was coupled with large temporal scatter between consecutive measurements of the specific surface area and of the statistical moments of grain thickness distributions. Because of marked differences in the right tail, grain thickness distributions did not show shape invariance with time, contrary to previous analyses. In our experiments, wet-snow metamorphism showed two strikingly different patterns: homogeneous coarsening superimposed by faster heterogeneous coarsening in areas that were affected by preferential percolation of water. Liquid water movement in snow and fast structural evolution may be thus intrinsically coupled by early formation of preferential flow at local scale. These observations suggest that further experiments are highly needed to fully understand wet-snow metamorphism and infiltration patterns in a natural snowpack.

Mesoscale Structure and Climatology of Rain-Snow Lines over North Carolina

DTIC Science & Technology

1988-01-01

that a feA hundred meters are required for snow to melt in temperatures up to 3"C. Findeisen (1940) first showed that the process of melting commonly...instability in rotating viscous fluids. J. Atmos. Sci., 36, 2425-2449. Findeisen , W., 1940: The formation of the 0*C isothermal layer and fractocumulus

Analysis of Light Absorbing Aerosols in Northern Pakistan: Concentration on Snow/Ice, their Source Regions and Impacts on Snow Albedo

NASA Astrophysics Data System (ADS)

Gul, C.; Praveen, P. S.; Shichang, K.; Adhikary, B.; Zhang, Y.; Ali, S.

2016-12-01

Elemental carbon (EC) and light absorbing organic carbon (OC) are important particulate impurities in snow and ice which significantly reduce the albedo of glaciers and accelerate their melting. Snow and ice samples were collected from Karakorum-Himalayan region of North Pakistan during the summer campaign (May-Jun) 2015 and only snow samples were collected during winter (Dec 2015- Jan 2016). Total 41 surface snow/ice samples were collected during summer campaign along different elevation ranges (2569 to 3895 a.m.s.l) from six glaciers: Sachin, Henarche, Barpu, Mear, Gulkin and Passu. Similarly 18 snow samples were collected from Sust, Hoper, Tawas, Astore, Shangla, and Kalam regions during the winter campaign. Quartz filters were used for filtering of melted snow and ice samples which were then analyzed by thermal optical reflectance (TOR) method to determine the concentration of EC and OC. The average concentration of EC (ng/g), OC (ng/g) and dust (ppm) were found as follows: Passu (249.5, 536.8, 475), Barpu (1190, 397.6, 1288), Gulkin (412, 793, 761), Sachin (911, 2130, 358), Mear (678, 2067, 83) and Henarche (755, 1868, 241) respectively during summer campaign. Similarly, average concentration of EC (ng/g), OC (ng/g) and dust (ppm) was found in the samples of Sust (2506, 1039, 131), Hoper (646, 1153, 76), Tawas (650, 1320, 16), Astore (1305, 2161, 97), Shangla (739, 2079, 31) and Kalam (107, 347, 5) respectively during winter campaign. Two methods were adopted to identify the source regions: one coupled emissions inventory with back trajectories, second with a simple region tagged chemical transport modeling analysis. In addition, CALIPSO subtype aerosol composition indicated that frequency of smoke in the atmosphere over the region was highest followed by dust and then polluted dust. SNICAR model was used to estimate the snow albedo reduction from our in-situ measurements. Snow albedo reduction was observed to be 0.3% to 27.6%. The derived results were used

Mapping Snow Grain Size over Greenland from MODIS

NASA Technical Reports Server (NTRS)

Lyapustin, Alexei; Tedesco, Marco; Wang, Yujie; Kokhanovsky, Alexander

2008-01-01

This paper presents a new automatic algorithm to derive optical snow grain size (SGS) at 1 km resolution using Moderate Resolution Imaging Spectroradiometer (MODIS) measurements. Differently from previous approaches, snow grains are not assumed to be spherical but a fractal approach is used to account for their irregular shape. The retrieval is conceptually based on an analytical asymptotic radiative transfer model which predicts spectral bidirectional snow reflectance as a function of the grain size and ice absorption. The analytical form of solution leads to an explicit and fast retrieval algorithm. The time series analysis of derived SGS shows a good sensitivity to snow metamorphism, including melting and snow precipitation events. Preprocessing is performed by a Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm, which includes gridding MODIS data to 1 km resolution, water vapor retrieval, cloud masking and an atmospheric correction. MAIAC cloud mask (CM) is a new algorithm based on a time series of gridded MODIS measurements and an image-based rather than pixel-based processing. Extensive processing of MODIS TERRA data over Greenland shows a robust performance of CM algorithm in discrimination of clouds over bright snow and ice. As part of the validation analysis, SGS derived from MODIS over selected sites in 2004 was compared to the microwave brightness temperature measurements of SSM\\I radiometer, which is sensitive to the amount of liquid water in the snowpack. The comparison showed a good qualitative agreement, with both datasets detecting two main periods of snowmelt. Additionally, MODIS SGS was compared with predictions of the snow model CROCUS driven by measurements of the automatic whether stations of the Greenland Climate Network. We found that CROCUS grain size is on average a factor of two larger than MODIS-derived SGS. Overall, the agreement between CROCUS and MODIS results was satisfactory, in particular before and during the

Analyzing dynamics of snow distribution and melt runoff in a meso-scaled watershed using the AgroEcoSystem-Watershed (AgES-W) model

NASA Astrophysics Data System (ADS)

Kunz, A.; Helmschrot, J.; Green, T. R.

2013-12-01

The seasonal snow cover in the western mountain regions of the United States functions as the primary supply and storage of water. Water management in these areas is often based on empirical relationships between point measurements of snow water equivalent (SWE) at selected sites and associated stream discharge. With a climate shifting towards more rain and less snow, due to the global warming, the patterns of snow deposition, and consequently the timing of melt, soil water content and the flow in streams and rivers will most likely alter. As a consequence, the established relationships between measured SWE and runoff will become unstable and unreliable, and consequently impacting the water resource management in this area. To better assess and understand the spatial and temporal dimension of altered snow cover on runoff generation in the intermountain region of the western United States, we set up the distributed hydrological AgroEcoSystem-Watershed (AgES-W) model for the Reynolds Creek Experimental Watershed (239 km2) in the Owyhee Mountains of Idaho. The study area with elevations ranging from 1101 to 2241 m is dominated by granitic and volcanic rocks and lake sediments. Deep moist soils allowing for mountain big sagebrush aspen and subalpine fir are found at higher elevations, whereas shallow, arid soils supporting sagebrush-grassland communities are common at lower elevations. Precipitation in the region varies from 230 mm at the lower elevations in the north up to 1100 mm in the higher regions at the southern margin south. The mean annual streamflow at the outlet is 0.56 m3/s. Since the Reynolds Creek Experimental Watershed (RCEW) was selected as a test basin in 1959, a comprehensive hydro-climatological network provides long-term records of daily snow, precipitation, temperature and streamflow measurements. Thus, we used a 30-year data record to calibrate and validate the AgES-W model to three nested sub-basins within the test site. First results show

Meteorological factors controlling year-to-year variations in the spring onset of snow melt over the Arctic sea ice

NASA Astrophysics Data System (ADS)

Maksimovich, E.

2010-09-01

The spring onset of snow melt on the Arctic sea ice shows large inter-annual variability. Surface melt triggers positive feedback mechanisms between the albedo, snow properties and thickness, as well as sea ice thickness. Hence, it is important to quantify the factors contributing to inter-annual variability of the melt onset (MO) in various parts of the Arctic Ocean. Meteorological factors controlling surface heat budget and surface melting/freezing are the shortwave and longwave radiative fluxes and the turbulent fluxes of sensible and latent heat. These fluxes depend on the weather conditions, including the radiative impact of clouds, heat advection and wind speed. We make use of SSM/I-based MO time series (Markus, Miller and Stroeve) and the ECMWF ERA Interim reanalysis on the meteorological conditions and surface fluxes, both data sets spanning the period 1989-2008 and covering recent years with a rapid sea ice decline. The advantage is that SSM/I-based MO time series are independent of the ERA-Interim data. Our objective is to investigate if there exists a physically consistent and statistically significant relationship between MO timing and corresponding meteorological conditions. Results based on the regression analysis between the MO timing and seasonal anomalies of surface longwave radiative fluxes reveal strong relationships. Synoptic scale (3-14 days) anomalies in downward longwave radiation are essential in the Western Arctic. Regarding the longer history (20-60 days) the distinct contribution from the downward longwave radiative fluxes is captured within the whole study region. Positive anomalies in the downward longwave radiation dominate over the simultaneous negative anomalies in the downward shortwave radiation. The anomalies in downward radiative fluxes are consistent with the total column water vapor, sea level pressure and 10-m wind direction. Sensible and latent heat fluxes affect surface melt timing in the Beaufort Sea and in the Atlantic

Polarimetric C-/X-band Synthetic Aperture Radar Observations of Melting Sea Ice in the Canadian Arctic Archipelago

NASA Astrophysics Data System (ADS)

Casey, J. A.; Beckers, J. F.; Brossier, E.; Haas, C.

2013-12-01

Operational ice information services rely heavily on space-borne synthetic aperture radar (SAR) data for the production of ice charts to meet their mandate of providing timely and accurate sea ice information to support safe and efficient marine operations. During the summer melt period, the usefulness of SAR data for sea ice monitoring is limited by the presence of wet snow and melt ponds on the ice surface, which can mask the signature of the underlying ice. This is a critical concern for ice services whose clients (e.g. commercial shipping, cruise tourism, resource exploration and extraction) are most active at this time of year when sea ice is at its minimum extent, concentration and thickness. As a result, there is a need to further quantify the loss of ice information in SAR data during the melt season and to identify what information can still be retrieved about ice surface conditions and melt pond evolution at this time of year. To date the majority of studies have been limited to analysis of single-polarization C-band SAR data. This study will investigate the potential complimentary and unique sea ice information that polarimetric C- and X-band SAR data can provide to supplement the information available from traditional single co-polarized C-band SAR data. A time-series of polarimetric C- and X-band SAR data was acquired over Jones Sound in the Canadian Arctic Archipelago, in the vicinity of the Grise Fiord, Nunavut. Five RADARSAT-2 Wide Fine Quad-pol images and 11 TerraSAR-X StripMap dual-pol (HH/VV) images were acquired. The time-series begins at the onset of melt in early June and extends through advanced melt conditions in late July. Over this period several ponding and drainage events and two snowfall events occurred. Field observations of sea ice properties were collected using an Ice Mass Balance (IMB) buoy, hourly photos from a time-lapse camera deployed on a coastal cliff, and manual in situ measurements of snow thickness and melt pond depth

Shifting mountain snow patterns in a changing climate from remote sensing retrieval.

PubMed

Dedieu, J P; Lessard-Fontaine, A; Ravazzani, G; Cremonese, E; Shalpykova, G; Beniston, M

2014-09-15

Observed climate change has already led to a wide range of impacts on environmental systems and society. In this context, many mountain regions seem to be particularly sensitive to a changing climate, through increases in temperature coupled with changes in precipitation regimes that are often larger than the global average (EEA, 2012). In mid-latitude mountains, these driving factors strongly influence the variability of the mountain snow-pack, through a decrease in seasonal reserves and earlier melting of the snow pack. These in turn impact on hydrological systems in different watersheds and, ultimately, have consequences for water management. Snow monitoring from remote sensing provides a unique opportunity to address the question of snow cover regime changes at the regional scale. This study outlines the results retrieved from the MODIS satellite images over a time period of 10 hydrological years (2000-2010) and applied to two case studies of the EU FP7 ACQWA project, namely the upper Rhone and Po in Europe and the headwaters of the Syr Darya in Kyrgyzstan (Central Asia). The satellite data were provided by the MODIS Terra MOD-09 reflectance images (NASA) and MOD-10 snow products (NSIDC). Daily snow maps were retrieved over that decade and the results presented here focus on the temporal and spatial changes in snow cover. This paper highlights the statistical bias observed in some specific regions, expressed by the standard deviation values (STD) of annual snow duration. This bias is linked to the response of snow cover to changes in elevation and can be used as a signal of strong instability in regions sensitive to climate change: with alternations of heavy snowfalls and rapid snow melting processes. The interest of the study is to compare the methodology between the medium scales (Europe) and the large scales (Central Asia) in order to overcome the limits of the applied methodologies and to improve their performances. Results show that the yearly snow cover

Snow Peak, OR: Miocene and Pliocene Tholeiitic Volcanism in the Cascadia Forearc

NASA Astrophysics Data System (ADS)

Hatfield, A. K.; Kent, A. J.; Nielsen, R. L.; Rowe, M. C.; Duncan, R. A.

2007-12-01

Snow Peak is a voluminous (>150 km3), glacially dissected shield volcano located approximately 50 km southeast of Salem, OR, with a summit height of 1,310 m above sea level. Snow Peak lies approximately 60 km west of the current High Cascade arc axis. Lavas from the southeast face of Snow Peak have been previously dated using K-Ar at ~3 Ma. New Ar-Ar dating indicates that lavas from the northwest face are ~5.4 Ma, and the summit plug is ~6 Ma. Snow Peak volcanics unconformably overlie western Cascade volcanics aged from middle to late Miocene (~10- 17 Ma). The age of Snow Peak is broadly contemporaneous with the initiation of modern High Cascade volcanism. Snow Peak's location provides a rare opportunity to study magmas produced within the modern High Cascades forearc region. The goal of this investigation is to characterize the composition and timing of volcanism at Snow Peak and the role of volatiles in magma genesis. Hypotheses for the formation of Snow Peak include flux melting associated with the Cascadia subduction zone and/or decompression melting associated with extensional faulting. Preliminary geochemical data on the basalts from Snow Peak indicate that they are low-to-medium-K tholeiites (SiO2 47.9-51.7 wt.%, MgO 5.5- 8.3 wt.%, K2O, 0.36-0.55 wt.%) and that they range from primitive to moderately evolved (Mg# 0.51-0.61). Common phenocryst phases are plagioclase, olivine, and clinopyroxene. Textures are typically hypocrystalline, and fine-grained to porphyritic. Mantle-normalized multi-element plots indicate Snow Peak lavas are generally HFSE depleted and LILE enriched. These data are consistent with a preliminary interpretation of a subduction zone signature, yet the major element composition most closely resembles high alumina olivine tholeiite (HAOT), more indicative of extensional environments. The degree of LILE enrichment is significantly lower than in calc alkaline lavas from the High Cascades and western Cascades. Determining the petrogenesis of

Assessing the hydropower potential of ungauged watersheds in Iceland using hydrological modeling and satellite retrieved snow cover images

NASA Astrophysics Data System (ADS)

Finger, David

2015-04-01

About 80% of the domestic energy production in Iceland comes from renewable energies. Hydropower accounts for about 20% this production, representing about 75% of the total electricity production in Iceland. In 2008 total electricity production from hydropower was about 12.5 TWh a-1, making Iceland a worldwide leader in hydropower production per capita. Furthermore, the total potential of hydroelectricity in Iceland is estimated to amount up to 220 TWh a-1. In this regard, hydrological modelling is an essential tool to adapt a sustainable management of water resources and estimate the potential of possible new sites for hydropower production. We used the conceptual lumped Hydrologiska Byråns Vattenbalansavdelning model (HBV) to estimate the potential of hydropower production in two remote areas in north-eastern Iceland (Leirdalshraun, a 274 km2 area above 595 m asl and Hafralónsá, a 946 km2 area above 235 m asl). The model parameters were determined by calibrating the model with discharge data from gauged sub catchments. Satellite snow cover images were used to constrain melt parameters of the model and assure adequate modelling of snow melt in the ungauged areas. This was particularly valuable to adequately estimate the contribution of snow melt, rainfall runoff and groundwater intrusion from glaciers outside the topographic boundaries of the selected watersheds. Runoff from the entire area potentially used for hydropower exploitation was estimated using the parameter sets of the gauged sub-catchments. Additionally, snow melt from the ungauged areas was validated with satellite based snow cover images, revealing a robust simulation of snow melt in the entire area. Based on the hydrological modelling the total amount of snow melt and rainfall runoff available in Leirdalshraun and Hafralónsá amounts up to 700 M m3 a-1 and 1000 M m3 a-1, respectively. These results reveal that the total hydropower potential of the two sites amounts up to 1.2 TWh a-1

Flow Pathways of Snow and Ground Ice Melt Water During Initial Seasonal Thawing of the Active Layer on Continuous Permafrost

NASA Astrophysics Data System (ADS)

Sjoberg, Y.; Johansson, E.; Rydberg, J.

2017-12-01

In most arctic environments, the snowmelt is the main hydrologic event of the year as a large fraction of annual precipitation rapidly moves through the catchment. Flow can occur on top of the frozen ground surface or through the developing active layer, and flow pathways are critical determinants for biogeochemical transport. We study the linkages between micro topography, active layer thaw, and water partitioning on a hillslope in Greenland during late snowmelt season to explore how seasonal subsurface flow pathways develop. During snowmelt, a parallel surface drainage pattern appears across the slope, consisting of small streams, and water also collects in puddles across the slope. Thaw rates in the active layer were significantly higher (T-test p<0.01) on wet parts of the slope (0.8 cm/day), compared to drier parts of the slope (0.6 cm/day). Analyses of stable water isotopic composition show that snow had the lightest isotopic signatures, but with a large spread of values, while seasonally frozen ground and standing surface water (puddles) were heavier. The stream water became heavier over the two-week sampling period, suggesting an increasing fraction of melted soil water input over time. In contrast, standing surface water (puddles) isotopic composition did not change over time. In boreal catchments, seasonal frost has previously been found to not significantly influence flow pathways during most snowmelt events, and pre-event groundwater make out most of the stream water during snowmelt. Our results from a continuous permafrost environment show that both surface (overland) and subsurface flow pathways in the active layer are active, and that a large fraction of the water moving on the hillslope comes from melted ground ice rather than snow in the late snowmelt season. This suggests a possibility that flow pathways during snowmelt could shift to deeper subsurface flow following degradation of continuous permafrost.

Remote sensing: Snow monitoring tool for today and tomorrow

NASA Technical Reports Server (NTRS)

Rango, A.

1977-01-01

Various types of remote sensing are now available or will be in the future for snowpack monitoring. Aircraft reconnaissance is now used in a conventional manner by various water resources agencies to obtain information on snowlines, depth, and melting of the snowpack for forecasting purposes. The use of earth resources satellites for mapping snowcovered area, snowlines, and changes in snowcover during the spring has increased during the last five years. Gamma ray aircraft flights, although confined to an extremely low altitude, provide a means for obtaining valuable information on snow water equivalent. The most recently developed remote sensing technology for snow, namely, microwave monitoring, has provided initial results that may eventually allow us to infer snow water equivalent or depth, snow wetness, and the hydrologic condition of the underlying soil.

Snow as a habitat for microorganisms

NASA Technical Reports Server (NTRS)

Hoham, Ronald W.

1989-01-01

There are three major habitats involving ice and snow, and the microorganisms studied from these habitats are most eukaryotic. Sea ice is inhabited by algae called diatoms, glacial ice has sparse populations of green algai cal desmids, and the temporary and permanent snows in mountainous regions and high latitudes are inhabited mostly by green algal flagellates. The life cycle of green algal flagellates is summarized by discussing the effects of light, temperature, nutrients, and snow melts. Specific examples of optimal conditions and environmental effects for various snow algae are given. It is not likely that the eukaryotic snow algae presented are candidated for life on the planet Mars. Evolutionally, eukaryotic cells as know on Earth may not have had the opportunity to develop on Mars (if life evolved at all on Mars) since eukaryotes did not appear on Earth until almost two billion years after the first prokaryotic organisms. However, the snow/ice ecosystems on Earth present themselves as extreme habitats were there is evidence of prokaryotic life (eubacteria and cyanbacteria) of which literally nothing is known. Any future surveillances of extant and/or extinct life on Mars should include probes (if not landing sites) to investigate sites of concentrations of ice water. The possibility of signs of life in Martian polar regions should not be overlooked.

Snow: A New Model Diagnostic and Seasonal Forecast Influences

NASA Astrophysics Data System (ADS)

Slater, A. G.; Lawrence, D. M.; Koven, C.

2015-12-01

Snow is the most variable of terrestrial surface condition on the planet with the seasonal extent of snow cover varying by about 48% of land area in the Northern Hemisphere. Physical properties of snow such as high albedo, high insulation along with its ability to store moisture make it an integral component of mid- and high-latitude climates and it is therefore important that models capture these properties and associated processes. In this work we explore two items associated with snow and their role in the climate system. Firstly, a diagnostic measure of snow insulation that is rooted in the physics of heat transfer is introduced. Insulation of the ground during cold Arctic winters heavily influences the rate and depth of ground freezing (or thawing), which can then influence hydrologic and biogeochemical fluxes. The ability of models to simulate snow insulation varies widely. Secondly, the role of snow upon seasonal forecasts is demonstrated within a currently operational modeling system. Due to model system biases, mass and longevity of snow can vary with forecasts. In turn, a longer lasting and greater moisture store can have impacts upon the surface temperature. These impacts can linger for over two months after all snow has melted. The cause of the biases is identified and a solution posed.

Assessing spatial and temporal snowpack evolution and melt with time-lapse photography

NASA Astrophysics Data System (ADS)

Bush, C. E.; Ewers, B. E.; Beverly, D.; Speckman, H. N.; Hyde, K.; Ohara, N.

2015-12-01

Snowpack supplies and stores water for many ecosystems of the greater Rocky Mountain region. In Wyoming the snowpack supplies water to 18 states east and west of the Continental Divide. The spatial variability in physical and biological processes creates a heterogeneous pattern of snow evolution. Understanding these processes within individual plots and throughout the entire watershed increases the predictive power of snow distribution, melt rates and contribution to streamflow. However, on site sampling of snow can be an expensive and arduous process. The objective of this experiment was to quantify spatial and temporal patterns of snowpack evolution and melt rates while minimizing perturbations to snowpack through the use of time-lapse photography via trail cameras. Field cameras were assessed as a method to quantify snow depths throughout the 120 ha No Name watershed at approximately 3000 m elevation in central Wyoming. RGB trail cameras were installed at three systematically chosen sites within the watershed to correlate physical and biological drivers of snow distribution. Five stakes were placed in each site in heterogeneous spots that remained in the frame of the camera. Stakes were divided into five centimeter increments, alternating black and white bars, with red bars denoting each half meter. Images were then taken at two-hour intervals over a period of three-months and analyzed with the ImageJ program. Snowpack distributions, as well as melt rates, were variable at both the plot and watershed scales. Meteorological and physical drivers, primarily topography and radiation, accounted for the greatest variability when comparing among plot across the watershed; however, LAI and soil and air temperature were the most significant drivers within plots. Snow-melt rate increased as soils and course woody debris became exposed increasing ground and soil temperature. These data will improve process model predictions of streamflow from the watershed.

EARLY IMPACT MELTING AND SPACE EXPOSURE HISTORY OF THE PAT91501 LCHONDRITE

NASA Technical Reports Server (NTRS)

Bogard, Donald D.; Garrison, D. H.; Herzog, G. F.; Xue, S.; Klein, J.; Middleton, R.

2004-01-01

Collisions probably occurred frequently in the early history of the asteroid belt. Their effects, which should be recorded in meteorites, must have included heating and melting along with shock alteration of mineral textures. Some non-chondritic meteorite types e.g., eucrites and IIE and IAB irons - do indeed give evidence of extensive impact heating more than 3.4 Gyr ago. The ordinary chondrites, in contrast, show little evidence of early impact heating. The Ar-Ar and Rb-Sr ages of ordinary chondrites that experienced intense shock are for the most part relatively young, many less than 1.5 Gyr. The numerous L-chondrites with Ar- Ar ages clustering near 0.5 Gy are a well-known example. One of them, the 105-kg Chico Lchondrite, shows the effects of unusually intense heating. It is approximately 60% impact melt and likely formed as a dyke beneath a large crater when the L-chondrite parent body underwent a very large impact approximately 0.5 Gyr ago. In rare instances, older shock dates are indicated for ordinary chondrites. Dixon et al show early impact resetting of Ar-Ar ages of a few LL-chondrites including MIL 99301 at 4.23 0.03 Gyr, but in none of these stones did shock lead to extensive melting. As of 2003, searches for chondritic melts attributable to early shock had turned up only the Shaw L-chondrite, which has an Ar-Ar age of approximately 4.42 Gyr. PAT91501 is an 8.55-kg L-chondrite containing vesicles and metal-troilite nodules. It is a unique, near-total impact melt, unshocked, depleted in siderophile and chalcophile elements, and contains only approximately 10% relic chondritic material. The authors conclude that PAT91501 crystallized rapidly and from a much more homogeneous melt than did Shaw. They suggest that PAT resembles Chico and likely formed as an impact melt vein within an impact crater. To define the history of PAT, we have determined its Ar-39-Ar-40 age and measured several radioactive and stable nuclides produced during its space exposure to

Evaluation of an assimilation scheme to estimate snow water equivalent in the High Atlas of Morocco.

NASA Astrophysics Data System (ADS)

Baba, W. M.; Baldo, E.; Gascoin, S.; Margulis, S. A.; Cortés, G.; Hanich, L.

2017-12-01

The snow melt from the Atlas mountains represents a crucial water resource for crop irrigation in Morocco. Due to the paucity of in situ measurements, and the high spatial variability of the snow cover in this semi-arid region, assimilation of snow cover area (SCA) from high resolution optical remote sensing into a snowpack energy-balance model is considered as a promising method to estimate the snow water equivalent (SWE) and snow melt at catchment scales. Here we present a preliminary evaluation of an uncalibrated particle batch smoother data assimilation scheme (Margulis et al., 2015, J. Hydrometeor., 16, 1752-1772) in the High-Atlas Rheraya pilot catchment (225 km2) over a snow season. This approach does not require in situ data since it is based on MERRA-2 reanalyses data and satellite fractional snow cover area data. We compared the output of this prior/posterior ensemble data assimilation system to output from the distributed snowpack evolution model SnowModel (Liston and Elder, 2006, J. Hydrometeor. 7, 1259-1276). SnowModel was forced with in situ meteorological data from five automatic weather stations (AWS) and some key parameters (precipitation correction factor and rain-snow phase transition parameters) were calibrated using a time series of 8-m resolution SCA maps from Formosat-2. The SnowModel simulation was validated using a continuous snow height record at one high elevation AWS. The results indicate that the open loop simulation was reasonably accurate (compared to SnowModel results) in spite of the coarse resolution of the MERRA-2 forcing. The assimilation of Formosat-2 SCA further improved the simulation in terms of the peak SWE and SWE evolution over the melt season. During the accumulation season, the differences between the modeled and estimated (posterior) SWE were more substantial. The differences appear to be due to some observed precipitation events not being captured in MERRA-2. Further investigation will determine whether additional

Combining Passive Microwave and Optical Data to Estimate Snow Water Equivalent in Afghanistan's Hindu Kush

NASA Astrophysics Data System (ADS)

Dozier, J.; Bair, N.; Calfa, A. A.; Skalka, C.; Tolle, K.; Bongard, J.

2015-12-01

The task is to estimate spatiotemporally distributed estimates of snow water equivalent (SWE) in snow-dominated mountain environments, including those that lack on-the-ground measurements such as the Hindu Kush range in Afghanistan. During the snow season, we can use two measurements: (1) passive microwave estimates of SWE, which generally underestimate in the mountains; (2) fractional snow-covered area from MODIS. Once the snow has melted, we can reconstruct the accumulated SWE back to the last significant snowfall by calculating the energy used in melt. The reconstructed SWE values provide a training set for predictions from the passive microwave SWE and snow-covered area. We examine several machine learning methods—regression-boosted decision trees, bagged trees, neural networks, and genetic programming—to estimate SWE. All methods work reasonably well, with R2 values greater than 0.8. Predictors built with multiple years of data reduce the bias that usually appears if we predict one year from just one other year's training set. Genetic programming tends to produce results that additionally provide physical insight. Adding precipitation estimates from the Global Precipitation Measurements mission is in progress.

Developing the snow component of a distributed hydrological model: a step-wise approach based on multi-objective analysis

NASA Astrophysics Data System (ADS)

Dunn, S. M.; Colohan, R. J. E.

1999-09-01

A snow component has been developed for the distributed hydrological model, DIY, using an approach that sequentially evaluates the behaviour of different functions as they are implemented in the model. The evaluation is performed using multi-objective functions to ensure that the internal structure of the model is correct. The development of the model, using a sub-catchment in the Cairngorm Mountains in Scotland, demonstrated that the degree-day model can be enhanced for hydroclimatic conditions typical of those found in Scotland, without increasing meteorological data requirements. An important element of the snow model is a function to account for wind re-distribution. This causes large accumulations of snow in small pockets, which are shown to be important in sustaining baseflows in the rivers during the late spring and early summer, long after the snowpack has melted from the bulk of the catchment. The importance of the wind function would not have been identified using a single objective function of total streamflow to evaluate the model behaviour.

Snow drought in western U.S. mountains: proximate causes, regional differences, and implications for streamflow and forests

NASA Astrophysics Data System (ADS)

Harpold, A. A.; Dettinger, M. D.; Rajagopal, S.

2017-12-01

Although drought is a recurring problem, recent extreme snow droughts have refocused attention on the interaction of meteorological extremes and snow accumulation in mountains. Only recently have two distinct types of snow drought been defined that help to differentiate a variety of water management implications. Dry snow drought is caused by deficits of winter precipitation and resulting low snow accumulation. Warm snow drought is characterized by temperature extremes causing faster and earlier snowmelt and/or shifts from snow to rain. Here we use 462 Snow Telemetry (SNOTEL) sites in the western U.S. to quantify snow drought as 75% of the long-term average snow water equivalent (SWE). We further subdivide dry snow droughts using SWE to winter precipitation (SWE/P) ratios that were near normal from warm snow droughts where SWE/P ratios were below normal and experienced SWE losses (warm-melt) or received unusual amounts of winter rain (warm-rain snow drought). Using this method we show clear regional patterns in the type and frequency of snow drought. Warm snow droughts on April 1st were most common in all but the highest elevations of the Rocky Mountains. The middle Rocky Mountains sites also experienced less frequent snow drought than the maritime and southern mountains. Warm-melt snow droughts were the primary cause in the Cascade Mountains and the southwestern sites, with only the Sierra Nevada and Wasatch mountains showing consistent warm-rain snow drought. These regional differences limited the predictability of snow drought with simple models of temperature and precipitation. We will discuss the effects of snow drought type and magnitude on streamflow forecasting skill using empirical relationships developed by water management agencies. We expect these types of snow drought to differentially affect streamflow regime and its predictability, as well as forest growth and mortality during and following drought.

Using mid-altitude regions as observatories of change in snow areas: the Natural Park of Cazorla, Segura y las Villas (South Spain) as study case for early snow regression.

NASA Astrophysics Data System (ADS)

Montilla, Soledad; Pimentel, Rafael; José Pérez-Palazón, María; Aguillar, Cristina; José Polo, María

2017-04-01

Snow plays a key role at the hydrological cycle in semiarid mountainous areas, modifying the energy and water balances that govern the regime of stored water in the snowpack, a key resource for the spring and summer river flow. The Natural and National Park of Sierra Nevada (SNNP), a coastal mountain range up to 3450 m a.s.l. in southern Spain, is a representative example of snow areas in Mediterranean-climate regions; its high altitudinal gradient results in a wide variety of eco-climatic environments, and it is part of the global monitoring network to study climate change. Both monitoring and modelling efforts have been performed to assess this variability and its significant scales; whereas increasing temperature trends have been found, no significant trends are observed so far regarding the precipitation regime both on a seasonal and annual basis, with a highly variable impact on the snow regime in this area, especially in the mid-altitude range. In this context, the study of the snow cover in the neighbouring Natural Park of Cazorla, Segura and Las Villas (CSLVNP), with similar climatic conditions but lower altitudes (up to 2107 m a.s.l.) is proposed as a parallel monitoring site for early warning of impacts of climate change on the snow regime. The CSLVNP is the most extensive protected area in Spain and it is located to the north of SNPN, with less influence of the Mediterranean Sea. This study carried out a first quantification of the snow importance in this area, which exhibits a large transitional zone with a dominant alpine environment, and its relationship with the observed local precipitation-temperature trends. For this, the snow cover fraction on a 30x30 m gridded resolution has been studied during a 5-yr period combining on-site meteorological observations and remote-sensing data analysis, and snow modelling by the distributed and physically based approach for Mediterranean regions proposed by Herrero et al. (2009; 2010). The analysis of the

Limitations of using a thermal imager for snow pit temperatures

NASA Astrophysics Data System (ADS)

Schirmer, M.; Jamieson, B.

2014-03-01

Driven by temperature gradients, kinetic snow metamorphism plays an import role in avalanche formation. When gradients based on temperatures measured 10 cm apart appear to be insufficient for kinetic metamorphism, faceting close to a crust can be observed. Recent studies that visualised small-scale (< 10 cm) thermal structures in a profile of snow layers with an infrared (IR) camera produced interesting results. The studies found melt-freeze crusts to be warmer or cooler than the surrounding snow depending on the large-scale gradient direction. However, an important assumption within these studies was that a thermal photo of a freshly exposed snow pit was similar enough to the internal temperature of the snow. In this study, we tested this assumption by recording thermal videos during the exposure of the snow pit wall. In the first minute, the results showed increasing gradients with time, both at melt-freeze crusts and artificial surface structures such as shovel scours. Cutting through a crust with a cutting blade or shovel produced small concavities (holes) even when the objective was to cut a planar surface. Our findings suggest there is a surface structure dependency of the thermal image, which was only observed at times during a strong cooling/warming of the exposed pit wall. We were able to reproduce the hot-crust/cold-crust phenomenon and relate it entirely to surface structure in a temperature-controlled cold laboratory. Concave areas cooled or warmed more slowly compared with convex areas (bumps) when applying temperature differences between snow and air. This can be explained by increased radiative and/or turbulent energy transfer at convex areas. Thermal videos suggest that such processes influence the snow temperature within seconds. Our findings show the limitations of using a thermal camera for measuring pit-wall temperatures, particularly during windy conditions, clear skies and large temperature differences between air and snow. At crusts or other

A Case Study of Using a Multilayered Thermodynamical Snow Model for Radiance Assimilation

NASA Technical Reports Server (NTRS)

Toure, Ally M.; Goita, Kalifa; Royer, Alain; Kim, Edward J.; Durand, Michael; Margulis, Steven A.; Lu, Huizhong

2011-01-01

A microwave radiance assimilation (RA) scheme for the retrieval of snow physical state variables requires a snowpack physical model (SM) coupled to a radiative transfer model. In order to assimilate microwave brightness temperatures (Tbs) at horizontal polarization (h-pol), an SM capable of resolving melt-refreeze crusts is required. To date, it has not been shown whether an RA scheme is tractable with the large number of state variables present in such an SM or whether melt-refreeze crust densities can be estimated. In this paper, an RA scheme is presented using the CROCUS SM which is capable of resolving melt-refreeze crusts. We assimilated both vertical (v) and horizontal (h) Tbs at 18.7 and 36.5 GHz. We found that assimilating Tb at both h-pol and vertical polarization (v-pol) into CROCUS dramatically improved snow depth estimates, with a bias of 1.4 cm compared to-7.3 cm reported by previous studies. Assimilation of both h-pol and v-pol led to more accurate results than assimilation of v-pol alone. The snow water equivalent (SWE) bias of the RA scheme was 0.4 cm, while the bias of the SWE estimated by an empirical retrieval algorithm was -2.9 cm. Characterization of melt-refreeze crusts via an RA scheme is demonstrated here for the first time; the RA scheme correctly identified the location of melt-refreeze crusts observed in situ.

Predicting Clear-Sky Reflectance Over Snow/Ice in Polar Regions

NASA Technical Reports Server (NTRS)

Chen, Yan; Sun-Mack, Sunny; Arduini, Robert F.; Hong, Gang; Minnis, Patrick

2015-01-01

Satellite remote sensing of clouds requires an accurate estimate of the clear-sky radiances for a given scene to detect clouds and aerosols and to retrieve their microphysical properties. Knowing the spatial and angular variability of clear-sky albedo is essential for predicting clear-sky radiance at solar wavelengths. The Clouds and the Earth's Radiant Energy System (CERES) Project uses the nearinfrared (NIR; 1.24, 1.6 or 2.13 micrometers), visible (VIS; 0.63 micrometers) and vegetation (VEG; 0.86 micrometers) channels available on the Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) to help identify clouds and retrieve their properties in both snow-free and snow-covered conditions. Thus, it is critical to have reliable distributions of clear-sky albedo for all of these channels. In CERES Edition 4 (Ed4), the 1.24-micrometer channel is used to retrieve cloud optical depth over snow/ice-covered surfaces. Thus, it is especially critical to accurately predict the 1.24-micrometer clear-sky albedo alpha and reflectance rho for a given location and time. Snow albedo and reflectance patterns are very complex due to surface texture, particle shapes and sizes, melt water, and vegetation protrusions from the snow surface. To minimize those effects, this study focuses on the permanent snow cover of Antarctica where vegetation is absent and melt water is minimal. Clear-sky albedos are determined as a function of solar zenith angle (SZA) from observations over all scenes determined to be cloud-free to produce a normalized directional albedo model (DRM). The DRM is used to develop alpha(SZA=0 degrees) on 10 foot grid for each season. These values provide the basis for predicting r at any location and set of viewing & illumination conditions. This paper examines the accuracy of this approach for two theoretical snow surface reflectance models.

Snow geese

USGS Publications Warehouse

Hupp, Jerry W.; Robertson, Donna G.; Brackney, Alan W.; Douglas, David C.; Reynolds, Patricia E.; Rhode, E.B.

2002-01-01

Part of the coastal plain of the Arctic National Wildlife Refuge, Alaska, is used as an autumn staging area by lesser snow geese (Chen caerulescens caerulescens) from the Western Canadian Arctic population (hereafter called the Western Arctic population). There were approximately 200,000 breeding adults in the Western Arctic population through the mid-1980s (Johnson and Herter 1989), but the population has recently increased to about 500,000 breeding adults (Kerbes et al. 1999).Early in their autumn migration, adult and juvenile snow geese from the Western Arctic population feed intensively while staging on the Beaufort Sea coastal plain in Canada and Alaska to build fat reserves needed for migration. Aerial censuses from 1973 to 1985 indicated that up to 600,000 adult and juvenile snow geese used the coastal plain for 2-4 weeks in late August until mid-September (Oates et al. 1987).We studied annual variation in numbers and spatial distribution of snow geese that staged on the coastal plain of the Arctic Refuge.

Limitations of using a thermal imager for snow pit temperatures

NASA Astrophysics Data System (ADS)

Schirmer, M.; Jamieson, B.

2013-10-01

Driven by temperature gradients, kinetic snow metamorphism is important for avalanche formation. Even when gradients appear to be insufficient for kinetic metamorphism, based on temperatures measured 10 cm apart, faceting close to a~crust can still be observed. Recent studies that visualized small scale (< 10 cm) thermal structures in a profile of snow layers with an infrared (IR) camera produced interesting results. The studies found melt-freeze crusts to be warmer or cooler than the surrounding snow depending on the large scale gradient direction. However, an important assumption within the studies was that a thermal photo of a freshly exposed snow pit was similar enough to the internal temperature of the snow. In this study, we tested this assumption by recording thermal videos during the exposure of the snow pit wall. In the first minute, the results showed increasing gradients with time, both at melt-freeze crusts and at artificial surface structures such as shovel scours. Cutting through a crust with a cutting blade or a shovel produced small concavities (holes) even when the objective was to cut a planar surface. Our findings suggest there is a surface structure dependency of the thermal image, which is only observed at times with large temperature differences between air and snow. We were able to reproduce the hot-crust/cold-crust phenomenon and relate it entirely to surface structure in a temperature-controlled cold laboratory. Concave areas cooled or warmed slower compared with convex areas (bumps) when applying temperature differences between snow and air. This can be explained by increased radiative transfer or convection by air at convex areas. Thermal videos suggest that such processes influence the snow temperature within seconds. Our findings show the limitations of the use of a thermal camera for measuring pit-wall temperatures, particularly in scenarios where large gradients exist between air and snow and the interaction of snow pit and

Lasting effects of snow accumulation on summer performance of large herbivores in alpine ecosystems may not last.

PubMed

Mysterud, Atle; Austrheim, Gunnar

2014-05-01

One of the clearest predictions from the IPCC is that we can expect much less snow cover due to global warming in the 21st century, especially in the lower alpine areas. In alpine ecosystems, snow accumulation in depressions gives rise to distinct snow-bed vegetation types, assumed to play a key role in ecosystem function. A delayed plant phenology yields high-quality forage in late summer for wild and domestic herbivores. Yet, the mechanistic pathways for how declining snow may affect future performance of large herbivores beyond the effect of phenology remain poorly documented. Here, we link unique individual-based data on diet choice, habitat selection and performance of domestic sheep over a 10-year period to manually GPS-recorded spatial positions of snow cover in early summer (0.57% to 43.3% in snow beds on 1st of July) in an alpine ecosystem. Snowy winters gave a higher proportion of easily digestible herbs in the diet and a more variable use of snow-bed and meadow vegetation types resulting in faster growing lambs. These patterns were consistent between two density treatment levels although slightly more marked for diet at low density, suggesting that effects of simple mitigation efforts such as managing population numbers will be meagre. Our study thus yields novel insight into the strong impact of melting snow on ecosystem function in alpine habitats, which are likely to affect productivity of both domestic and wild ungulate populations. © 2013 The Authors. Journal of Animal Ecology © 2013 British Ecological Society.

Relating C-band Microwave and Optical Satellite Observations as A Function of Snow Thickness on First-Year Sea Ice during the Winter to Summer Transition

NASA Astrophysics Data System (ADS)

Zheng, J.; Yackel, J.

2015-12-01

The Arctic sea ice and its snow cover have a direct impact on both the Arctic and global climate system through their ability to moderate heat exchange across the ocean-sea ice-atmosphere (OSA) interface. Snow cover plays a key role in the OSA interface radiation and energy exchange, as it controls the growth and decay of first-year sea ice (FYI). However, meteoric accumulation and redistribution of snow on FYI is highly stochastic over space and time, which makes it poorly understood. Previous studies have estimated local-scale snow thickness distributions using in-situ technique and modelling but it is spatially limited and challenging due to logistic difficulties. Moreover, snow albedo is also critical for determining the surface energy balance of the OSA during the critical summer ablation season. Even then, due to persistent and widespread cloud cover in the Arctic at various spatio-temporal scales, it is difficult and unreliable to remotely measure albedo of snow cover on FYI in the optical spectrum. Previous studies demonstrate that only large-scale sea ice albedo was successfully estimated using optical-satellite sensors. However, space-borne microwave sensors, with their capability of all-weather and 24-hour imaging, can provide enhanced information about snow cover on FYI. Daily spaceborne C-band scatterometer data (ASCAT) and MODIS data are used to investigate the the seasonal co-evolution of the microwave backscatter coefficient and optical albedo as a function of snow thickness on smooth FYI. The research focuses on snow-covered FYI near Cambridge Bay, Nunavut (Fig.1) during the winter to advanced-melt period (April-June, 2014). The ACSAT time series (Fig.2) show distinct increase in scattering at melt onset indicating the first occurrence of melt water in the snow cover. The corresponding albedo exhibits no decrease at this stage. We show how the standard deviation of ASCAT backscatter on FYI during winter can be used as a proxy for surface roughness

Metagenomic and satellite analyses of red snow in the Russian Arctic.

PubMed

Hisakawa, Nao; Quistad, Steven D; Hester, Eric R; Martynova, Daria; Maughan, Heather; Sala, Enric; Gavrilo, Maria V; Rohwer, Forest

2015-01-01

Cryophilic algae thrive in liquid water within snow and ice in alpine and polar regions worldwide. Blooms of these algae lower albedo (reflection of sunlight), thereby altering melting patterns (Kohshima, Seko & Yoshimura, 1993; Lutz et al., 2014; Thomas & Duval, 1995). Here metagenomic DNA analysis and satellite imaging were used to investigate red snow in Franz Josef Land in the Russian Arctic. Franz Josef Land red snow metagenomes confirmed that the communities are composed of the autotroph Chlamydomonas nivalis that is supporting a complex viral and heterotrophic bacterial community. Comparisons with white snow communities from other sites suggest that white snow and ice are initially colonized by fungal-dominated communities and then succeeded by the more complex C. nivalis-heterotroph red snow. Satellite image analysis showed that red snow covers up to 80% of the surface of snow and ice fields in Franz Josef Land and globally. Together these results show that C. nivalis supports a local food web that is on the rise as temperatures warm, with potential widespread impacts on alpine and polar environments worldwide.

Improving snow water equivalent simulations in an alpine basin using blended gage precipitation and snow pillow measurements

NASA Astrophysics Data System (ADS)

Sohrabi, M.; Safeeq, M.; Conklin, M. H.

2017-12-01

peak SWE was 810 mm for WTH and 380 mm for WTH+SP, which led to underestimation of snow season length and melt rate by up to 30 days and 12 mm/day, respectively, in WTH scenario. These results indicate that point scale snow observations at higher elevation can be used to improve precipitation input to hydrologic modeling in mountainous basins.

Daily gridded datasets of snow depth and snow water equivalent for the Iberian Peninsula from 1980 to 2014

NASA Astrophysics Data System (ADS)

Alonso-González, Esteban; López-Moreno, J. Ignacio; Gascoin, Simon; García-Valdecasas Ojeda, Matilde; Sanmiguel-Vallelado, Alba; Navarro-Serrano, Francisco; Revuelto, Jesús; Ceballos, Antonio; Jesús Esteban-Parra, María; Essery, Richard

2018-02-01

We present snow observations and a validated daily gridded snowpack dataset that was simulated from downscaled reanalysis of data for the Iberian Peninsula. The Iberian Peninsula has long-lasting seasonal snowpacks in its different mountain ranges, and winter snowfall occurs in most of its area. However, there are only limited direct observations of snow depth (SD) and snow water equivalent (SWE), making it difficult to analyze snow dynamics and the spatiotemporal patterns of snowfall. We used meteorological data from downscaled reanalyses as input of a physically based snow energy balance model to simulate SWE and SD over the Iberian Peninsula from 1980 to 2014. More specifically, the ERA-Interim reanalysis was downscaled to 10 km × 10 km resolution using the Weather Research and Forecasting (WRF) model. The WRF outputs were used directly, or as input to other submodels, to obtain data needed to drive the Factorial Snow Model (FSM). We used lapse rate coefficients and hygrobarometric adjustments to simulate snow series at 100 m elevations bands for each 10 km × 10 km grid cell in the Iberian Peninsula. The snow series were validated using data from MODIS satellite sensor and ground observations. The overall simulated snow series accurately reproduced the interannual variability of snowpack and the spatial variability of snow accumulation and melting, even in very complex topographic terrains. Thus, the presented dataset may be useful for many applications, including land management, hydrometeorological studies, phenology of flora and fauna, winter tourism, and risk management. The data presented here are freely available for download from Zenodo (https://doi.org/10.5281/zenodo.854618). This paper fully describes the work flow, data validation, uncertainty assessment, and possible applications and limitations of the database.

A conceptual snow model with an analytic resolution of the heat and phase change equations

NASA Astrophysics Data System (ADS)

Riboust, Philippe; Le Moine, Nicolas; Thirel, Guillaume; Ribstein, Pierre

2017-04-01

Compared to degree-day snow models, physically-based snow models resolve more processes in an attempt to achieve a better representation of reality. Often these physically-based models resolve the heat transport equations in snow using a vertical discretization of the snowpack. The snowpack is decomposed into several layers in which the mechanical and thermal states of the snow are calculated. A higher number of layers in the snowpack allow for better accuracy but it also tends to increase the computational costs. In order to develop a snow model that estimates the temperature profile of snow with a lower computational cost, we used an analytical decomposition of the vertical profile using eigenfunctions (i.e. trigonometric functions adapted to the specific boundary conditions). The mass transfer of snow melt has also been estimated using an analytical conceptualization of runoff fingering and matrix flow. As external meteorological forcing, the model uses solar and atmospheric radiation, air temperature, atmospheric humidity and precipitations. It has been tested and calibrated at point scale at two different stations in the Alps: Col de Porte (France, 1325 m) and Weissfluhjoch (Switzerland, 2540 m). A sensitivity analysis of model parameters and model inputs will be presented together with a comparison with measured snow surface temperature, SWE, snow depth, temperature profile and snow melt data. The snow model is created in order to be ultimately coupled with hydrological models for rainfall-runoff modeling in mountainous areas. We hope to create a model faster than physically-based models but capable to estimate more physical processes than degree-day snow models. This should help to build a more reliable snow model capable of being easily calibrated by remote sensing and in situ observation or to assimilate these data for forecasting purposes.

Long-term analyses of snow dynamics within the french Alps on the 1900-2100 period. Analyses of historical snow water equivalent observations, modelisations and projections of a hundred of snow courses.

NASA Astrophysics Data System (ADS)

Mathevet, T.; Joel, G.; Gottardi, F.; Nemoz, B.

2017-12-01

The aim of this communication is to present analyses of climate variability and change on snow water equivalent (SWE) observations, reconstructions (1900-2016) and scenarii (2020-2100) of a hundred of snow courses dissiminated within the french Alps. This issue became particularly important since a decade, in regions where snow variability had a large impact on water resources availability, poor snow conditions in ski resorts and artificial snow production. As a water resources manager in french mountainuous regions, EDF (french hydropower company) has developed and managed a hydrometeorological network since 1950. A recent data rescue research allowed to digitize long term SWE manual measurments of a hundred of snow courses within the french Alps. EDF have been operating an automatic SWE sensors network, complementary to the snow course network. Based on numerous SWE observations time-series and snow accumulation and melt model (Garavaglia et al., 2017), continuous daily historical SWE time-series have been reconstructed within the 1950-2016 period. These reconstructions have been extented to 1900 using 20 CR reanalyses (ANATEM method, Kuentz et al., 2015) and up to 2100 using GIEC Climate Change scenarii. Considering various mountainous areas within the french Alps, this communication focuses on : (1) long term (1900-2016) analyses of variability and trend of total precipitation, air temperature, snow water equivalent, snow line altitude, snow season length , (2) long term variability of hydrological regime of snow dominated watersheds and (3) future trends (2020 -2100) using GIEC Climate Change scenarii. Comparing historical period (1950-1984) to recent period (1984-2016), quantitative results within a region in the north Alps (Maurienne) shows an increase of air temperature by 1.2 °C, an increase of snow line height by 200m, a reduction of SWE by 200 mm/year and a reduction of snow season length by 15 days. These analyses will be extended from north to south

An ice core record of net snow accumulation and seasonal snow chemistry at Mt. Waddington, southwest British Columbia, Canada

NASA Astrophysics Data System (ADS)

Neff, P. D.; Steig, E. J.; Clark, D. H.; McConnell, J. R.; Pettit, E. C.; Menounos, B.

2011-12-01

We recovered a 141 m ice core from Combatant Col (51.39°N, 125.22°W, 3000 m asl) on the flank of Mt. Waddington, southern Coast Mountains, British Columbia, Canada. Aerosols and other impurities in the ice show unambiguous seasonal variations, allowing for annual dating of the core. Clustered melt layers, originating from summer surface heating, also aid in the dating of the core. Seasonality in water stable isotopes is preserved throughout the record, showing little evidence of diffusion at depth, and serves as an independent verification of the timescale. The annual signal of deuterium excess is especially well preserved. The record of lead deposition in the core agrees with those of ice cores from Mt. Logan and from Greenland, with a sharp drop-off in concentration in the 1970s and early 1980s, further validating the timescales. Despite significant summertime melt at this mid-latitude site, these data collectively reveal a continuous and annually resolved 36-year record of snow accumulation. We derived an accumulation time series from the Mt. Waddington ice core, after correcting for ice flow. Years of anomalously high or low snow accumulation in the core correspond with extremes in precipitation data and geopotential height anomalies from reanalysis data that make physical sense. Specifically, anomalously high accumulation years at Mt. Waddington correlate with years where "Pineapple Express" atmospheric river events bring large amounts of moisture from the tropical Pacific to western North America. The Mt. Waddington accumulation record thus reflects regional-scale climate. These results demonstrate the potential of ice core records from temperate glaciers to provide meaningful paleoclimate information. A longer core to bedrock (250-300 m) at the Mt. Waddington site could yield ice with an age of several hundred to 1000 years.

MODIS Snow-Cover Products

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Riggs, George A.; Salomonson, Vincent V.; DiGirolamo, Nicole E.; Bayr, Klaus J.; Houser, Paul R. (Technical Monitor)

2002-01-01

On December 18, 1999, the Terra satellite was launched with a complement of five instruments including the Moderate Resolution Imaging Spectroradiometer (MODIS). Many geophysical products are derived from MODIS data including global snow-cover products. MODIS snow and ice products have been available through the National Snow and Ice Data Center (NSIDC) Distributed Active Archive Center (DAAC) since September 13, 2000. MODIS snow-cover products represent potential improvement to or enhancement of the currently-available operational products mainly because the MODIS products are global and 500-m resolution, and have the capability to separate most snow and clouds. Also the snow-mapping algorithms are automated which means that a consistent data set may be generated for long-term climate studies that require snow-cover information. Extensive quality assurance (QA) information is stored with the products. The MODIS snow product suite begins with a 500-m resolution, 2330-km swath snow-cover map which is then gridded to an integerized sinusoidal grid to produce daily and 8-day composite tile products. The sequence proceeds to a climate-modeling grid (CMG) product at about 5.6-km spatial resolution, with both daily and 8-day composite products. Each pixel of the CMG contains fraction of snow cover from 40 - 100%. Measured errors of commission in the CMG are low, for example, on the continent of Australia in the spring, they vary from 0.02 - 0.10%. Near-term enhancements include daily snow albedo and fractional snow cover. A case study from March 6, 2000, involving MODIS data and field and aircraft measurements, is presented to show some early validation work.

Monitoring Antarctic ice sheet surface melting with TIMESAT algorithm

NASA Astrophysics Data System (ADS)

Ye, Y.; Cheng, X.; Li, X.; Liang, L.

2011-12-01

Antarctic ice sheet contributes significantly to the global heat budget by controlling the exchange of heat, moisture, and momentum at the surface-atmosphere interface, which directly influence the global atmospheric circulation and climate change. Ice sheet melting will cause snow humidity increase, which will accelerate the disintegration and movement of ice sheet. As a result, detecting Antarctic ice sheet melting is essential for global climate change research. In the past decades, various methods have been proposed for extracting snowmelt information from multi-channel satellite passive microwave data. Some methods are based on brightness temperature values or a composite index of them, and others are based on edge detection. TIMESAT (Time-series of Satellite sensor data) is an algorithm for extracting seasonality information from time-series of satellite sensor data. With TIMESAT long-time series brightness temperature (SSM/I 19H) is simulated by Double Logistic function. Snow is classified to wet and dry snow with generalized Gaussian model. The results were compared with those from a wavelet algorithm. On this basis, Antarctic automatic weather station data were used for ground verification. It shows that this algorithm is effective in ice sheet melting detection. The spatial distribution of melting areas(Fig.1) shows that, the majority of melting areas are located on the edge of Antarctic ice shelf region. It is affected by land cover type, surface elevation and geographic location (latitude). In addition, the Antarctic ice sheet melting varies with seasons. It is particularly acute in summer, peaking at December and January, staying low in March. In summary, from 1988 to 2008, Ross Ice Shelf and Ronnie Ice Shelf have the greatest interannual variability in amount of melting, which largely determines the overall interannual variability in Antarctica. Other regions, especially Larsen Ice Shelf and Wilkins Ice Shelf, which is in the Antarctic Peninsula

How do the radiative effects of springtime clouds and water vapor modulate the melt onset of Arctic sea ice?

NASA Astrophysics Data System (ADS)

Huang, Y.; Dong, X.; Xi, B.; Deng, Y.

2017-12-01

Earlier studies show that there is a strong positive correlation between the mean onset date of snow melt north of 70°N and the minimum Arctic sea ice extent (SIE) in September. Based on satellite records from 1980 to 2016, the September Arctic SIE minimum is most sensitive to the early melt onset over the Siberian Sea (73°-84°N, 90°-155°), which is defined as the area of focus (AOF) in this analysis. The day with melt onset exceeding 10% area of the AOF is marked as the initial melt date for a given year. With this definition, a strong positive correlation (r=0.59 at 99% confidence level) is found between the initial melt date over the AOF and the September SIE minimum over the Arctic. Daily anomalies of cloud and radiation properties are compared between six years with earliest initial melt dates (1990, 2012, 2007, 2003, 1991, 2016) and six years with latest initial melt dates (1996, 1984, 1983, 1982, 1987, 1992) using the NASA MERRA-2 reanalysis. Our results suggest that higher cloud water path (CWP) and precipitable water vapor (PWV) are clearly associated with early melt onset years through the period of mid-March to August. Major contrasts in CWP are found between the early and late onset years in a period of approximately 30 days prior to the onset to 30 days after the onset. As a result, the early melt onset years exhibit positive anomalies for downward longwave flux at the surface and negative anomalies for downward shortwave flux, shortwave cloud radiative effect (CRE) as well as net CRE. The negative net CRE is over-compensated by the positive longwave flux anomaly associated with elevated PWV, contributing to early melt onsets. The temporal evolution of CRE and PWV radiative effect during the entire melting season will be documented together with an analysis tracing the dynamical, mid-latitude origins of increased CWP and PWV prior to initial melt onsets.

High-Elevation Sierra Nevada Conifers Reveal Increasing Reliance on Snow Water with Changing Climate

NASA Astrophysics Data System (ADS)

Lepley, K. S.; Meko, D. M.; Touchan, R.; Shamir, E.; Graham, R.

2017-12-01

Snowpack in the Sierra Nevada Mountains accounts for around one third of California's water supply. Melting snow can provide water into dry summer months characteristic of the region's Mediterranean climate. As climate changes, understanding patterns of snowpack, snowmelt, and biological response are critical in this region of agricultural, recreational, and ecological value. Tree rings can act as proxy records to inform scientists and resource managers of past climate variability where instrumental data is unavailable. Here we investigate relationships between tree rings of high-elevation, snow-adapted conifer trees (Tsuga mertensiana, Abies magnifica) and April 1st snow-water equivalent (SWE) in the northern Sierra Nevada Mountains. The 1st principal component of 29 highly correlated regional SWE time series was modeled using multiple linear regression of four tree-ring chronologies including two lagged chronologies. Split-period verification analysis of this model revealed poor predictive skill in the early half (1929 - 1966) of the calibration period (1929 - 2003). Further analysis revealed a significant (p < 0.01) change in correlation between the Tsuga mertensiana chronology and SWE during early (1929 - 1970) and late (1971 - 2013) periods. Running 31-year correlations between this chronology and SWE rose from r = 0.10 in 1950 to r = 0.77 in 1996. This strengthening relationship is coincident with a positive trend in temperature, a negative trend in SWE, and increased variability in precipitation through time. Snow water is becoming a more limiting resource to tree growth as average temperatures rise and the hydrologic regime shifts. These results highlight the need for resource managers and policy makers to consider that biological response to climate is not static.

Estimation of Melt Ponds over Arctic Sea Ice using MODIS Surface Reflectance Data

NASA Astrophysics Data System (ADS)

Ding, Y.; Cheng, X.; Liu, J.

2017-12-01

Melt ponds over Arctic sea ice is one of the main factors affecting variability of surface albedo, increasing absorption of solar radiation and further melting of snow and ice. In recent years, a large number of melt ponds have been observed during the melt season in Arctic. Moreover, some studies have suggested that late spring to mid summer melt ponds information promises to improve the prediction skill of seasonal Arctic sea ice minimum. In the study, we extract the melt pond fraction over Arctic sea ice since 2000 using three bands MODIS weekly surface reflectance data by considering the difference of spectral reflectance in ponds, ice and open water. The preliminary comparison shows our derived Arctic-wide melt ponds are in good agreement with that derived by the University of Hamburg, especially at the pond distribution. We analyze seasonal evolution, interannual variability and trend of the melt ponds, as well as the changes of onset and re-freezing. The melt pond fraction shows an asymmetrical growth and decay pattern. The observed melt ponds fraction is almost within 25% in early May and increases rapidly in June and July with a high fraction of more than 40% in the east of Greenland and Beaufort Sea. A significant increasing trend in the melt pond fraction is observed for the period of 2000-2017. The relationship between melt pond fraction and sea ice extent will be also discussed. Key Words: melt ponds, sea ice, Arctic

Effects of seasonal snow and climatic controls on spring and autumn phenology in Alpine forest regions

NASA Astrophysics Data System (ADS)

Xie, J.; Kneubühler, M.; Garonna, I.; Jong, R. D.; Schaepman, M. E.

2017-12-01

Seasonal accumulation and melt of snow in mountainous regions varies with meteorological factors and affects forest phenology in various ways. However, our knowledge about the relationship between seasonal snow and forest phenology - and particularly its topographical variation - is still limited and needs further investigation. We tested the relationship between a number of snow, meteorological and land surface phenology metrics (satellite-derived and gridded) in the forested regions of the Swiss Alps for the period of 2003-2014. Satellite-derived start of season and end of season metrics (SOS and EOS, respectively), in combination with snow accumulation (SA), snow cover melt date (SCMD), monthly maximum, mean and minimum temperature, monthly mean relative sunshine duration and precipitation were considered in our analysis. We calculated Spearman's rank correlation of interannual differences (Δ) of SOS and EOS with snow and meteorological metrics and examined the variation of these correlations with elevation (from 200 up to 2400 meter above sea level (m a.s.l.)). We found SOS to have a significant (p < 0.05) positive correlation with both SCMD (mean R=0.71, over 34.2% of all pixels) and SA (mean R=0.62, over 19.0% of all pixels). On the other hand, SOS showed a significant negative correlation with spring temperature and relative sunshine duration. EOS showed significant positive correlation with autumn temperature (mean R=0.70, over 30.4% of all pixels). Moreover, we found the forest phenology of the northern and eastern Swiss Alps to be more sensitive to seasonal snow but less sensitive to meteorological factors than in the southern and western Swiss Alps. The areas which are sensitive to seasonal snow and meteorological factors are more pronounced at higher elevations. We conclude that the effect of snow melt on spring phenology is of equal magnitude as spring temperature and relative sunshine duration. Autumn forest phenology is mainly influenced by autumn

Distributed snow modeling suitable for use with operational data for the American River watershed.

NASA Astrophysics Data System (ADS)

Shamir, E.; Georgakakos, K. P.

2004-12-01

The mountainous terrain of the American River watershed (~4300 km2) at the Western slope of the Northern Sierra Nevada is subject to significant variability in the atmospheric forcing that controls the snow accumulation and ablations processes (i.e., precipitation, surface temperature, and radiation). For a hydrologic model that attempts to predict both short- and long-term streamflow discharges, a plausible description of the seasonal and intermittent winter snow pack accumulation and ablation is crucial. At present the NWS-CNRFC operational snow model is implemented in a semi distributed manner (modeling unit of about 100-1000 km2) and therefore lump distinct spatial variability of snow processes. In this study we attempt to account for the precipitation, temperature, and radiation spatial variability by constructing a distributed snow accumulation and melting model suitable for use with commonly available sparse data. An adaptation of the NWS-Snow17 energy and mass balance that is used operationally at the NWS River Forecast Centers is implemented at 1 km2 grid cells with distributed input and model parameters. The input to the model (i.e., precipitation and surface temperature) is interpolated from observed point data. The surface temperature was interpolated over the basin based on adiabatic lapse rates using topographic information whereas the precipitation was interpolated based on maps of climatic mean annual rainfall distribution acquired from PRISM. The model parameters that control the melting rate due to radiation were interpolated based on aspect. The study was conducted for the entire American basin for the snow seasons of 1999-2000. Validation of the Snow Water Equivalent (SWE) prediction is done by comparing to observation from 12 snow Sensors. The Snow Cover Area (SCA) prediction was evaluated by comparing to remotely sensed 500m daily snow cover derived from MODIS. The results that the distribution of snow over the area is well captured and the

Conceptualisation of Snowpack Isotope Dynamics in Spatially Distributed Tracer-Aided Runoff Models in Snow Influenced Northern Cathments

NASA Astrophysics Data System (ADS)

Ala-aho, P. O. A.; Tetzlaff, D.; Laudon, H.; McNamara, J. P.; Soulsby, C.

2016-12-01

We use the Spatially distributed Tracer-Aided Rainfall-Runoff (STARR) modelling framework to explore non-stationary flow and isotope response in three northern headwater catchments. The model simulates dynamic, spatially variable tracer concentration in different water stores and fluxes within a catchment, which can constrain internal catchment mixing processes, flow paths and associated water ages. To date, a major limitation in using such models in snow-dominated catchments has been the difficulties in paramaterising the isotopic transformations in snowpack accumulation and melt. We use high quality long term datasets for hydrometrics and stable water isotopes collected in three northern study catchments for model calibration and testing. The three catchments exhibit different hydroclimatic conditions, soil and vegetation types, and topographic relief, which brings about variable degree of snow dominance across the catchments. To account for the snow influence we develop novel formulations to estimate the isotope evolution in the snowpack and melt. Algorithms for the isotopic evolution parameterize an isotopic offset between snow evaporation and melt fluxes and the remaining snow storage. The model for each catchment is calibrated to match both streamflow and tracer concentration at the stream outlet to ensure internal consistency of the system behaviour. The model is able to reproduce the streamflow along with the spatio-temporal differences in tracer concentrations across the three studies catchments reasonably well. Incorporating the spatially distributed snowmelt processes and associated isotope transformations proved essential in capturing the stream tracer reponse for strongly snow-influenced cathments. This provides a transferrable tool which can be used to understand spatio-temporal variability of mixing and water ages for different storages and flow paths in other snow influenced, environments.

A statistical estimation of Snow Water Equivalent coupling ground data and MODIS images

NASA Astrophysics Data System (ADS)

Bavera, D.; Bocchiola, D.; de Michele, C.

2007-12-01

The Snow Water Equivalent (SWE) is an important component of the hydrologic balance of mountain basins and snow fed areas in general. The total cumulated snow water equivalent at the end of the accumulation season represents the water availability at melt. Here, a statistical methodology to estimate the Snow Water Equivalent, at April 1st, is developed coupling ground data (snow depth and snow density measurements) and MODIS images. The methodology is applied to the Mallero river basin (about 320 km²) located in the Central Alps, northern Italy, where are available 11 snow gauges and a lot of sparse snow density measurements. The application covers 7 years from 2001 to 2007. The analysis has identified some problems in the MODIS information due to the cloud cover and misclassification for orographic shadow. The study is performed in the framework of AWARE (A tool for monitoring and forecasting Available WAter REsource in mountain environment) EU-project, a STREP Project in the VI F.P., GMES Initiative.

A new spatial snow distribution in hydrological models parameterized from observed spatial variability of precipitation.

NASA Astrophysics Data System (ADS)

Skaugen, Thomas; Weltzien, Ingunn

2016-04-01

The traditional catchment hydrological model with its many free calibration parameters is not a well suited tool for prediction under conditions for which is has not been calibrated. Important tasks for hydrological modelling such as prediction in ungauged basins and assessing hydrological effects of climate change are hence not solved satisfactory. In order to reduce the number of calibration parameters in hydrological models we have introduced a new model which uses a dynamic gamma distribution as the spatial frequency distribution of snow water equivalent (SWE). The parameters are estimated from observed spatial variability of precipitation and the magnitude of accumulation and melting events and are hence not subject to calibration. The relationship between spatial mean and variance of precipitation is found to follow a pattern where decreasing temporal correlation with increasing accumulation or duration of the event leads to a levelling off or even a decrease of the spatial variance. The new model for snow distribution is implemented in the, already parameter parsimonious, DDD (Distance Distribution Dynamics) hydrological model and was tested for 71 Norwegian catchments. We compared the new snow distribution model with the current operational snow distribution model where a fixed, calibrated coefficient of variation parameterizes a log-normal model for snow distribution. Results show that the precision of runoff simulations is equal, but that the new snow distribution model better simulates snow covered area (SCA) when compared with MODIS satellite derived snow cover. In addition, SWE is simulated more realistically in that seasonal snow is melted out and the building up of "snow towers" is prevented and hence spurious trends in SWE.

Experimental Insights on Natural Lava-Ice/Snow Interactions and Their Implications for Glaciovolcanic and Submarine Eruptions

NASA Astrophysics Data System (ADS)

Edwards, B. R.; Karson, J.; Wysocki, R.; Lev, E.; Bindeman, I. N.; Kueppers, U.

2012-12-01

Lava-ice-snow interactions have recently gained global attention through the eruptions of ice-covered volcanoes, particularly from Eyjafjallajokull in south-central Iceland, with dramatic effects on local communities and global air travel. However, as with most submarine eruptions, direct observations of lava-ice/snow interactions are rare. Only a few hundred potentially active volcanoes are presently ice-covered, these volcanoes are generally in remote places, and their associated hazards make close observation and measurements dangerous. Here we report the results of the first large-scale experiments designed to provide new constraints on natural interactions between lava and ice/snow. The experiments comprised controlled effusion of tens of kilograms of melted basalt on top of ice/snow, and provide insights about observations from natural lava-ice-snow interactions including new constraints for: 1) rapid lava advance along the ice-lava interface; 2) rapid downwards melting of lava flows through ice; 3) lava flow exploitation of pre-existing discontinuities to travel laterally beneath and within ice; and 4) formation of abundant limu o Pele and non-explosive vapor transport from the base to the top of the lava flow with minor O isotope exchange. The experiments are consistent with observations from eruptions showing that lava is more efficient at melting ice when emplaced on top of the ice as opposed to beneath the ice, as well as the efficacy of tephra cover for slowing melting. The experimental extrusion rates are as within the range of those for submarine eruptions as well, and reproduce some features seen in submarine eruptions including voluminous production of gas rich cavities within initially anhydrous lavas and limu on lava surfaces. Our initial results raise questions about the possibility of secondary ingestion of water by submarine and glaciovolcanic lava flows, and the origins of apparent primary gas cavities in those flows. Basaltic melt moving down

Contribution of high resolution remote sensing data to the modeling of the snow cover the in Atlas Mountains

NASA Astrophysics Data System (ADS)

Baba, Wassim; Gascoin, Simon; Hanich, Lahoucine; Kinnard, Christophe

2017-04-01

Snow melt from the Atlas Mountains watersheds represent an important water resource for the semi-arid, cultivated, lowlands. Due to the high incoming solar radiation and low precipitation, the spatial-temporal variability of the snowpack is expected to be strongly influenced by the topography. We explore this hypothesis using a distributed energy balance snow model (SnowModel) in the experimental watershed of the Rheraya River in Morocco (225 km2). The digital elevation model (DEM) in SnowModel is used for the computation of the gridded meteorological forcing from the automatic weather stations data. We acquired three Pléiades stereo pairs in to produce an accurate, high resolution DEM of the Rheraya watershed at 4 m posting. Then, the DEM was resampled to different spatial resolutions (8 m, 30 m, 90 m, 250 m and 500 m) to simulate the snowpack evolution over 2008-2009 snow season. As validation data we used a time series of 15 maps of the snow cover area (SCA) from Formosat-2 imagery over the same snow season in the upper Rheraya watershed. These maps have a resolution of 8 m, which enables to capture small-scale variability in the snow cover. We found that the simulations at 90 m, 30 m and 8 m yield similar results at the catchment scale, with significant differences in areas of very steep topography only. From February to April, an overall good agreement was observed between the simulated SCA and the Formosat-2 SCA at 8 m and 90 m. Before the melting season, true positive (TP) column of confusion matrix is close to 1, but it drops to 0.6 during the melting season. Heidke Skill Score is higher than 0.7 for the most of the validation dates and averages 0.8. On the contrary, 500 m simulation underestimates the SCA throughout the snow season and the TP score is always inferior to the one obtained at 8 m and 90 m. We further analyzed the effect of topography by comparing the distribution of meteorological and snowpack variables along north-south and east

Early Melt on the Greenland Ice Sheet

NASA Image and Video Library

2017-12-08

On June 15, 2016, the Advanced Land Imager (ALI) on NASA’s Earth Observing-1 satellite acquired a natural-color image of an area just inland from the coast of southwestern Greenland (120 kilometers southeast of Ilulisat and 500 kilometers north-northeast of Nuuk). According to Marco Tedesco, a professor at Columbia University’s Lamont Doherty Earth Observatory, melting in this area began relatively early in April but was not sustained. It started up again in May and grew into the watery June scene pictured above. Surface melt can directly contribute to sea level rise via runoff. It can also force its way through crevasses to the base of a glacier, temporarily speeding up ice flow and indirectly contributing to sea level rise. Also, ponding of meltwater can “darken” the ice sheet’s surface and lead to further melting. Read more: earthobservatory.nasa.gov/IOTD/view.php?id=88288 Credit: NASA Earth Observatory image by Jesse Allen, using EO-1 ALI data provided courtesy of the NASA EO-1 team NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Effects of Absorbing Aerosols on Accelerated Melting of Snowpack in the Hindu-Kush-Himalayas-Tibetan Plateau Region

NASA Technical Reports Server (NTRS)

Lau, William K.; Kyu-Myong, Kim; Yasunari, Teppei; Gautam, Ritesh; Hsu, Christina

2011-01-01

The impacts of absorbing aerosol on melting of snowpack in the Hindu-Kush-Himalayas-Tibetan Plateau (HKHT) region are studied using in-situ, satellite observations, and GEOS-5 GCM. Based on atmospheric black carbon measurements from the Pyramid observation ( 5 km elevation) in Mt. Everest, we estimate that deposition of black carbon on snow surface will give rise to a reduction in snow surface albedo of 2- 5 %, and an increased annual runoff of 12-34% for a typical Tibetan glacier. Examination of satellite reflectivity and re-analysis data reveals signals of possible impacts of dust and black carbon in darkening the snow surface, and accelerating spring melting of snowpack in the HKHT, following a build-up of absorbing aerosols in the Indo-Gangetic Plain. Results from GCM experiments show that 8-10% increase in the rate of melting of snowpack over the western Himalayas and Tibetan Plateau can be attributed to the elevated-heat-pump (EHP) feedback effect, initiated from the absorption of solar radiation by dust and black carbon accumulated to great height ( 5 km) over the Indo-Gangetic Plain and Himalayas foothills in the pre-monsoon season (April-May). The accelerated melting of the snowpack is enabled by an EHP-induced atmosphere-land-snowpack positive feedback involving a) orographic forcing of the monsoon flow by the complex terrain, and thermal forcing of the HKHT region, leading to increased moisture, cloudiness and rainfall over the Himalayas foothills and northern India, b) warming of the upper troposphere over the Tibetan Plateau, and c) an snow albedo-temperature feedback initiated by a transfer of latent and sensible heat from a warmer atmosphere over the HKHT to the underlying snow surface. Results from ongoing modeling work to assess the relative roles of EHP vs. snow-darkening effects on accelerated melting of snowpack in HKHT region will also be discussed.

Observational evidence of EHP effects on the early melting of snowpack over the Tibetan Plateau and Indian summer monsoon

NASA Astrophysics Data System (ADS)

Sang, Jeong; Kim, Maeng-Ki; Lau, William K. M.; Kim, Kyu-Myong; Lee, Woo-Seop

2013-04-01

In this study, observational evidences are presented showing that the Indo-Gangetic Plain (IGP) regions, bounded by the high altitude Himalayan mountains, are subject to heavy loading of absorbing aerosols, i.e., black carbon and dust, which can lead to widespread enhancement warming over the Tibetan Plateau and accelerated snowmelt in the western Tibetan Plateau (WTP) and Himalayas. The two pre-monsoon seasons of high aerosol and low aerosol cases were strikingly contrasting in terms of the aerosol loading over IGP. The warming of the TP in high aerosol cases relative to low aerosol cases was widespread, covering most of the WTP and Himalayas. This warming is closely linked to patterns of the snow melt. Consistent with the Elevated Heat Pump hypothesis, we find that increased loading of absorbing aerosols over IGP in the pre-monsoon season is associated with increased heating of the upper troposphere by dynamical feedback induced by aerosol heating, and enhances the rate of snowmelt over Himalayas and the WTP in April-May, indicating that the heating of the troposphere by elevated dust and black carbon aerosols in the boreal spring can lead to widespread enhanced land-atmosphere warming, accelerated snow melt in the Himalayas and Tibetan Plateau, and enhanced precipitation in May-June over the northern India.

Spatiotemporal variability in surface energy balance across tundra, snow and ice in Greenland.

PubMed

Lund, Magnus; Stiegler, Christian; Abermann, Jakob; Citterio, Michele; Hansen, Birger U; van As, Dirk

2017-02-01

The surface energy balance (SEB) is essential for understanding the coupled cryosphere-atmosphere system in the Arctic. In this study, we investigate the spatiotemporal variability in SEB across tundra, snow and ice. During the snow-free period, the main energy sink for ice sites is surface melt. For tundra, energy is used for sensible and latent heat flux and soil heat flux leading to permafrost thaw. Longer snow-free period increases melting of the Greenland Ice Sheet and glaciers and may promote tundra permafrost thaw. During winter, clouds have a warming effect across surface types whereas during summer clouds have a cooling effect over tundra and a warming effect over ice, reflecting the spatial variation in albedo. The complex interactions between factors affecting SEB across surface types remain a challenge for understanding current and future conditions. Extended monitoring activities coupled with modelling efforts are essential for assessing the impact of warming in the Arctic.

Physical and Chemical Properties of Seasonal Snow and the Impacts on Albedo in New Hampshire, USA

NASA Astrophysics Data System (ADS)

Adolph, A. C.; Albert, M. R.; Amante, J.; Dibb, J. E.

2014-12-01

Snow albedo is critical to surface energy budgets and thus to the timing of mid-winter and vernal melt events in seasonal snow packs. Timing of these melt events is important in predicting flooding, understanding plant and animal phenology, and the availability of winter recreational activity. The state of New Hampshire experiences large spatial and temporal variability in snow albedo as a result of differences in meteorological conditions, physical snow structure, and chemical impurities in the snow, particularly highly absorptive black carbon (BC) and dust particles. This work focuses on the winters of 2012-2013 and 2013-2014, comparing three intensive study sites. Data collected at these sites include sub-hourly meteorological data, near daily measurements of snow depth, snow density, surface IR temperature, specific surface area (SSA) from contact spectroscopy, and spectrally resolved snow albedo using an ASD FieldSpec4 throughout the winter season. Additionally, snow samples were analyzed for black carbon content and other chemical impurities including Cl-, NO3-, NH4 , K , Na , Mg2+ , Ca2+ and SO42-. For each storm event at the three intensive sites, moisture sources and paths were determined using HYPLIT back trajectory modeling to determine potential sources of black carbon and other impurities in the snow. Storms with terrestrial-based paths across the US Midwest and Canada resulted in higher BC content than storms with ocean-based paths and sources. In addition to the variable storm path between sites and between years, the second year of study was on average 2.5°C colder than the first year, impacting duration of snow cover at each site and the SSA of surface snow which is sensitive to frequency of snow events and relies on cold temperatures to reduce grain metamorphism. Combining an understanding of storm frequency and path with physical and chemical attributes of the snow allows us to investigate snow albedo sensitivities with implications for

Endolithic microbial life in extreme cold climate: snow is required, but perhaps less is more.

PubMed

Sun, Henry J

2013-04-03

Cyanobacteria and lichens living under sandstone surfaces in the McMurdo Dry Valleys require snow for moisture. Snow accumulated beyond a thin layer, however, is counterproductive, interfering with rock insolation, snow melting, and photosynthetic access to light. With this in mind, the facts that rock slope and direction control colonization, and that climate change results in regional extinctions, can be explained. Vertical cliffs, which lack snow cover and are perpetually dry, are devoid of organisms. Boulder tops and edges can trap snow, but gravity and wind prevent excessive buildup. There, the organisms flourish. In places where snow-thinning cannot occur and snow drifts collect, rocks may contain living or dead communities. In light of these observations, the possibility of finding extraterrestrial endolithic communities on Mars cannot be eliminated.

Endolithic Microbial Life in Extreme Cold Climate: Snow Is Required, but Perhaps Less Is More

PubMed Central

Sun, Henry J.

2013-01-01

Cyanobacteria and lichens living under sandstone surfaces in the McMurdo Dry Valleys require snow for moisture. Snow accumulated beyond a thin layer, however, is counterproductive, interfering with rock insolation, snow melting, and photosynthetic access to light. With this in mind, the facts that rock slope and direction control colonization, and that climate change results in regional extinctions, can be explained. Vertical cliffs, which lack snow cover and are perpetually dry, are devoid of organisms. Boulder tops and edges can trap snow, but gravity and wind prevent excessive buildup. There, the organisms flourish. In places where snow-thinning cannot occur and snow drifts collect, rocks may contain living or dead communities. In light of these observations, the possibility of finding extraterrestrial endolithic communities on Mars cannot be eliminated. PMID:24832803

Improving Surface Mass Balance Over Ice Sheets and Snow Depth on Sea Ice

NASA Technical Reports Server (NTRS)

Koenig, Lora Suzanne; Box, Jason; Kurtz, Nathan

2013-01-01

Surface mass balance (SMB) over ice sheets and snow on sea ice (SOSI) are important components of the cryosphere. Large knowledge gaps remain in scientists' abilities to monitor SMB and SOSI, including insufficient measurements and difficulties with satellite retrievals. On ice sheets, snow accumulation is the sole mass gain to SMB, and meltwater runoff can be the dominant single loss factor in extremely warm years such as 2012. SOSI affects the growth and melt cycle of the Earth's polar sea ice cover. The summer of 2012 saw the largest satellite-recorded melt area over the Greenland ice sheet and the smallest satellite-recorded Arctic sea ice extent, making this meeting both timely and relevant.

Using Gridded Snow Covered Area and Snow-Water Equivalence Spatial Data Sets to Improve Snow-Pack Depletion Simulation in a Continental Scale Hydrologic Model

NASA Astrophysics Data System (ADS)

Risley, J. C.; Tracey, J. A.; Markstrom, S. L.; Hay, L.

2014-12-01

Snow cover areal depletion curves were used in a continuous daily hydrologic model to simulate seasonal spring snowmelt during the period between maximum snowpack accumulation and total melt. The curves are defined as the ratio of snow-water equivalence (SWE) divided by the seasonal maximum snow-water equivalence (Ai) (Y axis) versus the percent snow cover area (SCA) (X axis). The slope of the curve can vary depending on local watershed conditions. Windy sparsely vegetated high elevation watersheds, for example, can have a steeper slope than lower elevation forested watersheds. To improve the accuracy of simulated runoff at ungaged watersheds, individual snow cover areal depletion curves were created for over 100,000 hydrologic response units (HRU) in the continental scale U.S. Geological Survey (USGS) National Hydrologic Model (NHM). NHM includes the same components of the USGS Precipitation-Runoff-Modeling System (PRMS), except it uses consistent land surface characterization and model parameterization across the U.S. continent. Weighted-mean daily time series of 1-kilometer gridded SWE, from Snow Data Assimilation System (SNODAS), and 500-meter gridded SCA, from Moderate Resolution Imaging Spectroradiometer (MODIS), for 2003-2014 were computed for each HRU using the USGS Geo Data Portal. Using a screening process, pairs of SWE/Ai and SCA from the snowmelt period of each year were selected. SCA values derived from imagery that did not have any cloud cover and were >0 and <100 percent were selected. Unrealistically low and high SCA values that were paired with high and low SWE/Ai ratios, respectively, were removed. Second order polynomial equations were then fit to the remaining pairs of SWE/Ai and SCA to create a unique curve for each HRU. Simulations comparing these new curves with an existing single default curve in NHM will be made to determine if there are significant improvements in runoff.

Effects of Absorbing Aerosols on Accelerated Melting of Snowpack in the Tibetan-Himalayas Region

NASA Technical Reports Server (NTRS)

Lau, William K. M.

2011-01-01

The impacts of absorbing aerosol on melting of snowpack in the Hindu-Kush-Tibetan-Himalayas (HKTH) region are studied using NASA satellite and GEOS-5 GCM. Results from GCM experiments shows that a 8-10% in the rate of melting of snowpack over the western Himalayas and Tibetan Plateau can be attributed to the aerosol elevated-heat-pump (EHP) feedback effect (Lau et al. 2008), initiated by the absorption of solar radiation by absorbing aerosols accumulated over the Indo-Gangetic Plain and Himalayas foothills. On the other hand, deposition of black carbon on snow surface was estimated to give rise to a reduction in snow surface albedo of 2 - 5%, and an increased annual runoff of 9-24%. From case studies using satellite observations and re-analysis data, we find consistent signals of possible impacts of dust and black carbon aerosol in blackening snow surface, in accelerating spring melting of snowpack in the HKHT, and consequentially in influencing shifts in long-term Asian summer monsoon rainfall pattern.

Application of snow models to snow removal operations on the Going-to-the-Sun Road, Glacier National Park

USGS Publications Warehouse

Fagre, Daniel B.; Klasner, Frederick L.

2000-01-01

Snow removal, and the attendant avalanche risk for road crews, is a major issue on mountain highways worldwide. The Going-to-the-Sun Road is the only road that crosses Glacier National Park, Montana. This 80-km highway ascends over 1200m along the wall of a glaciated basin and crosses the continental divide. The annual opening of the road is critical to the regional economy and there is public pressure to open the road as early as possible. Despite the 67-year history of snow removal activities, few stat on snow conditions at upper elevations were available to guide annual planning for the raod opening. We examined statistical relationships between the opening date and nearby SNOTEL data on snow water equivalence (WE) for 30 years. Early spring SWE (first Monday in April) accounted for only 33% of the variance in road opening dates. Because avalanche spotters, used to warn heavy equipment operators of danger, are ineffective during spring storms or low-visibility conditions, we incorporated the percentage of days with precipitation during plowing as a proxy for visibility. This improved the model's predictive power to 69%/ A mountain snow simulator (MTSNOW) was used to calculate the depth and density of snow at various points along the road and field data were collected for comparison. MTSNOW underestimated the observed snow conditions, in part because it does not yet account for wind redistribution of snow. The severe topography of the upper reaches of the road are subjected to extensive wind redistribution of snow as evidence by the formation of "The Big Drift" on the lee side of Logan Pass.

The Airborne Snow Observatory: fusion of imaging spectrometer and scanning lidar for studies of mountain snow cover (Invited)

NASA Astrophysics Data System (ADS)

Painter, T. H.; Andreadis, K.; Berisford, D. F.; Goodale, C. E.; Hart, A. F.; Heneghan, C.; Deems, J. S.; Gehrke, F.; Marks, D. G.; Mattmann, C. A.; McGurk, B. J.; Ramirez, P.; Seidel, F. C.; Skiles, M.; Trangsrud, A.; Winstral, A. H.; Kirchner, P.; Zimdars, P. A.; Yaghoobi, R.; Boustani, M.; Khudikyan, S.; Richardson, M.; Atwater, R.; Horn, J.; Goods, D.; Verma, R.; Boardman, J. W.

2013-12-01

Snow cover and its melt dominate regional climate and water resources in many of the world's mountainous regions. However, we face significant water resource challenges due to the intersection of increasing demand from population growth and changes in runoff total and timing due to climate change. Moreover, increasing temperatures in desert systems will increase dust loading to mountain snow cover, thus reducing the snow cover albedo and accelerating snowmelt runoff. The two most critical properties for understanding snowmelt runoff and timing are the spatial and temporal distributions of snow water equivalent (SWE) and snow albedo. Despite their importance in controlling volume and timing of runoff, snowpack albedo and SWE are still poorly quantified in the US and not at all in most of the globe, leaving runoff models poorly constrained. Recognizing this need, JPL developed the Airborne Snow Observatory (ASO), an imaging spectrometer and imaging LiDAR system, to quantify snow water equivalent and snow albedo, provide unprecedented knowledge of snow properties, and provide complete, robust inputs to snowmelt runoff models, water management models, and systems of the future. Critical in the design of the ASO system is the availability of snow water equivalent and albedo products within 24 hours of acquisition for timely constraint of snowmelt runoff forecast models. In spring 2013, ASO was deployed for its first year of a multi-year Demonstration Mission of weekly acquisitions in the Tuolumne River Basin (Sierra Nevada) and monthly acquisitions in the Uncompahgre River Basin (Colorado). The ASO data were used to constrain spatially distributed models of varying complexities and integrated into the operations of the O'Shaughnessy Dam on the Hetch Hetchy reservoir on the Tuolumne River. Here we present the first results from the ASO Demonstration Mission 1 along with modeling results with and without the constraint by the ASO's high spatial resolution and spatially

The Microwave Properties of Simulated Melting Precipitation Particles: Sensitivity to Initial Melting

NASA Technical Reports Server (NTRS)

Johnson, B. T.; Olson, W. S.; Skofronick-Jackson, G.

2016-01-01

A simplified approach is presented for assessing the microwave response to the initial melting of realistically shaped ice particles. This paper is divided into two parts: (1) a description of the Single Particle Melting Model (SPMM), a heuristic melting simulation for ice-phase precipitation particles of any shape or size (SPMM is applied to two simulated aggregate snow particles, simulating melting up to 0.15 melt fraction by mass), and (2) the computation of the single-particle microwave scattering and extinction properties of these hydrometeors, using the discrete dipole approximation (via DDSCAT), at the following selected frequencies: 13.4, 35.6, and 94.0GHz for radar applications and 89, 165.0, and 183.31GHz for radiometer applications. These selected frequencies are consistent with current microwave remote-sensing platforms, such as CloudSat and the Global Precipitation Measurement (GPM) mission. Comparisons with calculations using variable-density spheres indicate significant deviations in scattering and extinction properties throughout the initial range of melting (liquid volume fractions less than 0.15). Integration of the single-particle properties over an exponential particle size distribution provides additional insight into idealized radar reflectivity and passive microwave brightness temperature sensitivity to variations in size/mass, shape, melt fraction, and particle orientation.

[Effects of snow cover on water soluble and organic solvent soluble components during foliar litter decomposition in an alpine forest].

PubMed

Xu, Li-Ya; Yang, Wan-Qin; Li, Han; Ni, Xiang-Yin; He, Jie; Wu, Fu-Zhong

2014-11-01

Seasonal snow cover may change the characteristics of freezing, leaching and freeze-thaw cycles in the scenario of climate change, and then play important roles in the dynamics of water soluble and organic solvent soluble components during foliar litter decomposition in the alpine forest. Therefore, a field litterbag experiment was conducted in an alpine forest in western Sichuan, China. The foliar litterbags of typical tree species (birch, cypress, larch and fir) and shrub species (willow and azalea) were placed on the forest floor under different snow cover thickness (deep snow, medium snow, thin snow and no snow). The litterbags were sampled at snow formation stage, snow cover stage and snow melting stage in winter. The results showed that the content of water soluble components from six foliar litters decreased at snow formation stage and snow melting stage, but increased at snow cover stage as litter decomposition proceeded in the winter. Besides the content of organic solvent soluble components from azalea foliar litter increased at snow cover stage, the content of organic solvent soluble components from the other five foliar litters kept a continue decreasing tendency in the winter. Compared with the content of organic solvent soluble components, the content of water soluble components was affected more strongly by snow cover thickness, especially at snow formation stage and snow cover stage. Compared with the thicker snow covers, the thin snow cover promoted the decrease of water soluble component contents from willow and azalea foliar litter and restrain the decrease of water soluble component content from cypress foliar litter. Few changes in the content of water soluble components from birch, fir and larch foliar litter were observed under the different thicknesses of snow cover. The results suggested that the effects of snow cover on the contents of water soluble and organic solvent soluble components during litter decomposition would be controlled by

Chemical composition of snow in the northern Sierra Nevada and other areas

USGS Publications Warehouse

Feth, John Henry Frederick; Rogers, S.M.; Roberson, Charles Elmer

1964-01-01

Melting snow provides a large part of the water used throughout the western conterminous United States for agriculture, industry, and domestic supply. It is an active agent in chemical weathering, supplies moisture for forest growth, and sustains fish and wildlife. Despite its importance, virtually nothing has been known of the chemical character of snow in the western mountains until the present study.Analysis of more than 100 samples, most from the northern Sierra Nevada, but some from Utah, Denver, Colo., and scattered points, shows that melted snow is a dilute solution containing measurable amounts of some or all of the inorganic constituents commonly found in natural water. There are significant regional differences in chemical composition; the progressive increase in calcium content with increasing distance eastward from the west slope of the Sierra Nevada is the most pronounced. The chemical character of individual snowfalls is variable. Some show predominant influence of oceanic salt; others show strong effects of mineralization from continental sources, probably largely dust. Silica and boron were found in about half the samples analyzed for these constituents; precipitation is seldom analyzed for these substances.Results of the chemical analyses for major constituents in snow samples are summarized in the following table. The median and mean values for individual constituents are derived from 41-78 samples of Sierra Nevada snow, 6-18 samples of Utah snow, and 6-17 samples of Denver, Colo., snow.The sodium, chloride, and perhaps boron found in snow are probably incorporated in moisture-laden air masses as they move over the Pacific Ocean. Silica, although abundant in the silicate-mineral nuclei found in some snowflakes, may be derived in soluble form largely from dust. Calcium, magnesium, and some bicarbonate are probably added by dust of continental origin. The sources of the other constituents remain unknown.When snowmelt comes in contact with the

The dynamic bacterial communities of a melting High Arctic glacier snowpack

PubMed Central

Hell, Katherina; Edwards, Arwyn; Zarsky, Jakub; Podmirseg, Sabine M; Girdwood, Susan; Pachebat, Justin A; Insam, Heribert; Sattler, Birgit

2013-01-01

Snow environments can occupy over a third of land surface area, but little is known about the dynamics of snowpack bacteria. The effect of snow melt on bacterial community structure and diversity of surface environments of a Svalbard glacier was examined using analyses of 16S rRNA genes via T-RFLP, qPCR and 454 pyrosequencing. Distinct community structures were found in different habitat types, with changes over 1 week apparent, in particular for the dominant bacterial class present, Betaproteobacteria. The differences observed were consistent with influences from depositional mode (snowfall vs aeolian dusts), contrasting snow with dust-rich snow layers and near-surface ice. Contrary to that, slush as the decompositional product of snow harboured distinct lineages of bacteria, further implying post-depositional changes in community structure. Taxa affiliated to the betaproteobacterial genus Polaromonas were particularly dynamic, and evidence for the presence of betaproteobacterial ammonia-oxidizing bacteria was uncovered, inviting the prospect that the dynamic bacterial communities associated with snowpacks may be active in supraglacial nitrogen cycling and capable of rapid responses to changes induced by snowmelt. Furthermore the potential of supraglacial snowpack ecosystems to respond to transient yet spatially extensive melting episodes such as that observed across most of Greenland's ice sheet in 2012 merits further investigation. PMID:23552623

The dynamic bacterial communities of a melting High Arctic glacier snowpack.

PubMed

Hell, Katherina; Edwards, Arwyn; Zarsky, Jakub; Podmirseg, Sabine M; Girdwood, Susan; Pachebat, Justin A; Insam, Heribert; Sattler, Birgit

2013-09-01

Snow environments can occupy over a third of land surface area, but little is known about the dynamics of snowpack bacteria. The effect of snow melt on bacterial community structure and diversity of surface environments of a Svalbard glacier was examined using analyses of 16S rRNA genes via T-RFLP, qPCR and 454 pyrosequencing. Distinct community structures were found in different habitat types, with changes over 1 week apparent, in particular for the dominant bacterial class present, Betaproteobacteria. The differences observed were consistent with influences from depositional mode (snowfall vs aeolian dusts), contrasting snow with dust-rich snow layers and near-surface ice. Contrary to that, slush as the decompositional product of snow harboured distinct lineages of bacteria, further implying post-depositional changes in community structure. Taxa affiliated to the betaproteobacterial genus Polaromonas were particularly dynamic, and evidence for the presence of betaproteobacterial ammonia-oxidizing bacteria was uncovered, inviting the prospect that the dynamic bacterial communities associated with snowpacks may be active in supraglacial nitrogen cycling and capable of rapid responses to changes induced by snowmelt. Furthermore the potential of supraglacial snowpack ecosystems to respond to transient yet spatially extensive melting episodes such as that observed across most of Greenland's ice sheet in 2012 merits further investigation.

Snow hydrology in Mediterranean mountain regions: A review

NASA Astrophysics Data System (ADS)

Fayad, Abbas; Gascoin, Simon; Faour, Ghaleb; López-Moreno, Juan Ignacio; Drapeau, Laurent; Page, Michel Le; Escadafal, Richard

2017-08-01

Water resources in Mediterranean regions are under increasing pressure due to climate change, economic development, and population growth. Many Mediterranean rivers have their headwaters in mountainous regions where hydrological processes are driven by snowpack dynamics and the specific variability of the Mediterranean climate. A good knowledge of the snow processes in the Mediterranean mountains is therefore a key element of water management strategies in such regions. The objective of this paper is to review the literature on snow hydrology in Mediterranean mountains to identify the existing knowledge, key research questions, and promising technologies. We collected 620 peer-reviewed papers, published between 1913 and 2016, that deal with the Mediterranean-like mountain regions in the western United States, the central Chilean Andes, and the Mediterranean basin. A large amount of studies in the western United States form a strong scientific basis for other Mediterranean mountain regions. We found that: (1) the persistence of snow cover is highly variable in space and time but mainly controlled by elevation and precipitation; (2) the snowmelt is driven by radiative fluxes, but the contribution of heat fluxes is stronger at the end of the snow season and during heat waves and rain-on-snow events; (3) the snow densification rates are higher in these regions when compared to other climate regions; and (4) the snow sublimation is an important component of snow ablation, especially in high-elevation regions. Among the pressing issues is the lack of continuous ground observation in high-elevation regions. However, a few years of snow depth (HS) and snow water equivalent (SWE) data can provide realistic information on snowpack variability. A better spatial characterization of snow cover can be achieved by combining ground observations with remotely sensed snow data. SWE reconstruction using satellite snow cover area and a melt model provides reasonable information that

Pollution from the 2014-15 Bárðarbunga eruption monitored by snow cores from the Vatnajökull glacier, Iceland

NASA Astrophysics Data System (ADS)

Galeczka, Iwona; Eiriksdottir, Eydis Salome; Pálsson, Finnur; Oelkers, Eric; Lutz, Stefanie; Benning, Liane G.; Stefánsson, Andri; Kjartansdóttir, Ríkey; Gunnarsson-Robin, Jóhann; Ono, Shuhei; Ólafsdóttir, Rósa; Jónasdóttir, Elín Björk; Gislason, Sigurdur R.

2017-11-01

The chemical composition of Icelandic rain and snow is dominated by marine aerosols, however human and volcanic activity can also affect these compositions. The six month long 2014-15 Bárðarbunga volcanic eruption was the largest in Iceland for more than 200 years and it released into the atmosphere an average of 60 kt/day SO2, 30 kt/day CO2, 500 t/day HCl and 280 t/day HF. To study the effect of this eruption on the winter precipitation, snow cores were collected from the Vatnajökull glacier and the highlands northeast of the glacier. In addition to 29 bulk snow cores from that precipitated from September 2014 until March 2015, two cores were sampled in 21 and 44 increments to quantify the spatial and time evolution of the chemical composition of the snow. The pH and chemical compositions of melted snow samples indicate that snow has been affected by the volcanic gases emitted during the Bárðarbunga eruption. The pH of the melted bulk snow cores ranged from 4.41 to 5.64 with an average value of 5.01. This is four times greater H+ activity than pure water saturated with the atmospheric CO2. The highest concentrations of volatiles in the snow cores were found close to the eruption site as predicted from CALPUFF SO2 gas dispersion quality model. The anion concentrations (SO4, Cl, and F) were higher and the pH was lower compared to equivalent snow samples collected during 1997-2006 from the unpolluted Icelandic Langjökull glacier. Higher SO4 and Cl concentrations in the snow compared with the unpolluted rainwater of marine origin confirm the addition of a non-seawater SO4 and Cl. The δ34S isotopic composition confirms that the sulphur addition is of volcanic aerosol origin. The chemical evolution of the snow with depth reflects changes in the lava effusion and gas emission rates. Those rates were the highest at the early stage of the eruption. Snow that fell during that time, represented by samples from the deepest part of the snow cores, had the lowest pH and

Refinements to SSiB with an Emphasis on Snow-Physics: Evaluation and Validation Using GSWP and Valdai Data

NASA Technical Reports Server (NTRS)

Mocko, David M.; Sud, Y. C.

2000-01-01

Refinements to the snow-physics scheme of SSiB (Simplified Simple Biosphere Model) are described and evaluated. The upgrades include a partial redesign of the conceptual architecture to better simulate the diurnal temperature of the snow surface. For a deep snowpack, there are two separate prognostic temperature snow layers - the top layer responds to diurnal fluctuations in the surface forcing, while the deep layer exhibits a slowly varying response. In addition, the use of a very deep soil temperature and a treatment of snow aging with its influence on snow density is parameterized and evaluated. The upgraded snow scheme produces better timing of snow melt in GSWP-style simulations using ISLSCP Initiative I data for 1987-1988 in the Russian Wheat Belt region. To simulate more realistic runoff in regions with high orographic variability, additional improvements are made to SSiB's soil hydrology. These improvements include an orography-based surface runoff scheme as well as interaction with a water table below SSiB's three soil layers. The addition of these parameterizations further help to simulate more realistic runoff and accompanying prognostic soil moisture fields in the GSWP-style simulations. In intercomparisons of the performance of the new snow-physics SSiB with its earlier versions using an 18-year single-site dataset from Valdai Russia, the version of SSiB described in this paper again produces the earliest onset of snow melt. Soil moisture and deep soil temperatures also compare favorably with observations.

Snow survey and vegetation growth in high mountains (Swiss Alps)

NASA Technical Reports Server (NTRS)

Haefner, H. (Principal Investigator)

1973-01-01

The author has identified the following significant results. A method for mapping snow over large areas was developed combining the possibilities of a Quantimet (QTM 72) to evaluate the exact density level of the snow cover for each individual image (or a selected section of the photo) with the higher resolution of photographic techniques. The density level established on the monitor by visual control is used as reference for the exposure time of a lithographic film, producing a clear tonal separation of all snow- and ice-covered areas from uncovered land in black and white. The data is projected onto special maps 1:500,000 or 1:100,000 showing the contour lines and the hydrographic features only. The areal extent of the snow cover may be calculated directly with the QTM 720 or on the map. Bands 4 and 5 provide the most accurate results for mapping snow. Using all four bands a separation of an old melting snow cover from a new one is possible. Regional meteorological studies combining ERTS-1 imagery and conventional sources describe synoptical evolution of meteorological systems over the Alps.

Using Snow Fences to Augument Fresh Water Supplies in Shallow Arctic Lakes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stuefer, Svetlana

2013-03-31

This project was funded by the U.S. Department of Energy, National Energy Technology Laboratory (NETL) to address environmental research questions specifically related to Alaska's oil and gas natural resources development. The focus of this project was on the environmental issues associated with allocation of water resources for construction of ice roads and ice pads. Earlier NETL projects showed that oil and gas exploration activities in the U.S. Arctic require large amounts of water for ice road and ice pad construction. Traditionally, lakes have been the source of freshwater for this purpose. The distinctive hydrological regime of northern lakes, caused bymore » the presence of ice cover and permafrost, exerts influence on lake water availability in winter. Lakes are covered with ice from October to June, and there is often no water recharge of lakes until snowmelt in early June. After snowmelt, water volumes in the lakes decrease throughout the summer, when water loss due to evaporation is considerably greater than water gained from rainfall. This balance switches in August, when air temperature drops, evaporation decreases, and rain (or snow) is more likely to occur. Some of the summer surface storage deficit in the active layer and surface water bodies (lakes, ponds, wetlands) is recharged during this time. However, if the surface storage deficit is not replenished (for example, precipitation in the fall is low and near‐surface soils are dry), lake recharge is directly affected, and water availability for the following winter is reduced. In this study, we used snow fences to augment fresh water supplies in shallow arctic lakes despite unfavorable natural conditions. We implemented snow‐control practices to enhance snowdrift accumulation (greater snow water equivalent), which led to increased meltwater production and an extended melting season that resulted in lake recharge despite low precipitation during the years of the experiment. For three years

Twenty-four year record of Northern Hemisphere snow cover derived from passive microwave remote sensing

NASA Astrophysics Data System (ADS)

Armstrong, Richard L.; Brodzik, Mary Jo

2003-04-01

Snow cover is an important variable for climate and hydrologic models due to its effects on energy and moisture budgets. Seasonal snow can cover more than 50% of the Northern Hemisphere land surface during the winter resulting in snow cover being the land surface characteristic responsible for the largest annual and interannual differences in albedo. Passive microwave satellite remote sensing can augment measurements based on visible satellite data alone because of the ability to acquire data through most clouds or during darkness as well as to provide a measure of snow depth or water equivalent. It is now possible to monitor the global fluctuation of snow cover over a 24 year period using passive microwave data (Scanning Multichannel Microwave Radiometer (SMMR) 1978-1987 and Special Sensor Microwave/Imager (SSM/I), 1987-present). Evaluation of snow extent derived from passive microwave algorithms is presented through comparison with the NOAA Northern Hemisphere snow extent data. For the period 1978 to 2002, both passive microwave and visible data sets show a smiliar pattern of inter-annual variability, although the maximum snow extents derived from the microwave data are consistently less than those provided by the visible statellite data and the visible data typically show higher monthly variability. During shallow snow conditions of the early winter season microwave data consistently indicate less snow-covered area than the visible data. This underestimate of snow extent results from the fact that shallow snow cover (less than about 5.0 cm) does not provide a scattering signal of sufficient strength to be detected by the algorithms. As the snow cover continues to build during the months of January through March, as well as on into the melt season, agreement between the two data types continually improves. This occurs because as the snow becomes deeper and the layered structure more complex, the negative spectral gradient driving the passive microwave algorithm

Modification of Soil Temperature and Moisture Budgets by Snow Processes

NASA Astrophysics Data System (ADS)

Feng, X.; Houser, P.

2006-12-01

Snow cover significantly influences the land surface energy and surface moisture budgets. Snow thermally insulates the soil column from large and rapid temperature fluctuations, and snow melting provides an important source for surface runoff and soil moisture. Therefore, it is important to accurately understand and predict the energy and moisture exchange between surface and subsurface associated with snow accumulation and ablation. The objective of this study is to understand the impact of land surface model soil layering treatment on the realistic simulation of soil temperature and soil moisture. We seek to understand how many soil layers are required to fully take into account soil thermodynamic properties and hydrological process while also honoring efficient calculation and inexpensive computation? This work attempts to address this question using field measurements from the Cold Land Processes Field Experiment (CLPX). In addition, to gain a better understanding of surface heat and surface moisture transfer process between land surface and deep soil involved in snow processes, numerical simulations were performed at several Meso-Cell Study Areas (MSAs) of CLPX using the Center for Ocean-Land-Atmosphere (COLA) Simplified Version of the Simple Biosphere Model (SSiB). Measurements of soil temperature and soil moisture were analyzed at several CLPX sites with different vegetation and soil features. The monthly mean vertical profile of soil temperature during October 2002 to July 2003 at North Park Illinois River exhibits a large near surface variation (<5 cm), reveals a significant transition zone from 5 cm to 25 cm, and becomes uniform beyond 25cm. This result shows us that three soil layers are reasonable in solving the vertical variation of soil temperature at these study sites. With 6 soil layers, SSiB also captures the vertical variation of soil temperature during entire winter season, featuring with six soil layers, but the bare soil temperature is

Machine Learning on Images: Combining Passive Microwave and Optical Data to Estimate Snow Water Equivalent

NASA Astrophysics Data System (ADS)

Dozier, J.; Tolle, K.; Bair, N.

2014-12-01

We have a problem that may be a specific example of a generic one. The task is to estimate spatiotemporally distributed estimates of snow water equivalent (SWE) in snow-dominated mountain environments, including those that lack on-the-ground measurements. Several independent methods exist, but all are problematic. The remotely sensed date of disappearance of snow from each pixel can be combined with a calculation of melt to reconstruct the accumulated SWE for each day back to the last significant snowfall. Comparison with streamflow measurements in mountain ranges where such data are available shows this method to be accurate, but the big disadvantage is that SWE can only be calculated retroactively after snow disappears, and even then only for areas with little accumulation during the melt season. Passive microwave sensors offer real-time global SWE estimates but suffer from several issues, notably signal loss in wet snow or in forests, saturation in deep snow, subpixel variability in the mountains owing to the large (~25 km) pixel size, and SWE overestimation in the presence of large grains such as depth and surface hoar. Throughout the winter and spring, snow-covered area can be measured at sub-km spatial resolution with optical sensors, with accuracy and timeliness improved by interpolating and smoothing across multiple days. So the question is, how can we establish the relationship between Reconstruction—available only after the snow goes away—and passive microwave and optical data to accurately estimate SWE during the snow season, when the information can help forecast spring runoff? Linear regression provides one answer, but can modern machine learning techniques (used to persuade people to click on web advertisements) adapt to improve forecasts of floods and droughts in areas where more than one billion people depend on snowmelt for their water resources?

Climate change and forest fires synergistically drive widespread melt events of the Greenland Ice Sheet.

PubMed

Keegan, Kaitlin M; Albert, Mary R; McConnell, Joseph R; Baker, Ian

2014-06-03

In July 2012, over 97% of the Greenland Ice Sheet experienced surface melt, the first widespread melt during the era of satellite remote sensing. Analysis of six Greenland shallow firn cores from the dry snow region confirms that the most recent prior widespread melt occurred in 1889. A firn core from the center of the ice sheet demonstrated that exceptionally warm temperatures combined with black carbon sediments from Northern Hemisphere forest fires reduced albedo below a critical threshold in the dry snow region, and caused the melting events in both 1889 and 2012. We use these data to project the frequency of widespread melt into the year 2100. Since Arctic temperatures and the frequency of forest fires are both expected to rise with climate change, our results suggest that widespread melt events on the Greenland Ice Sheet may begin to occur almost annually by the end of century. These events are likely to alter the surface mass balance of the ice sheet, leaving the surface susceptible to further melting.

A comparison study of two snow models using data from different Alpine sites

NASA Astrophysics Data System (ADS)

Piazzi, Gaia; Riboust, Philippe; Campo, Lorenzo; Cremonese, Edoardo; Gabellani, Simone; Le Moine, Nicolas; Morra di Cella, Umberto; Ribstein, Pierre; Thirel, Guillaume

2017-04-01

The hydrological balance of an Alpine catchment is strongly affected by snowpack dynamics. Melt-water supplies a significant component of the annual water budget, both in terms of soil moisture and runoff, which play a critical role in floods generation and impact water resource management in snow-dominated basins. Several snow models have been developed with variable degrees of complexity, mainly depending on their target application and the availability of computational resources and data. According to the level of detail, snow models range from statistical snowmelt-runoff and degree-day methods using composite snow-soil or explicit snow layer(s), to physically-based and energy balance snow models, consisting of detailed internal snow-process schemes. Intermediate-complexity approaches have been widely developed resulting in simplified versions of the physical parameterization schemes with a reduced snowpack layering. Nevertheless, an increasing model complexity does not necessarily entail improved model simulations. This study presents a comparison analysis between two snow models designed for hydrological purposes. The snow module developed at UPMC and IRSTEA is a mono-layer energy balance model analytically resolving heat and phase change equations into the snowpack. Vertical mass exchange into the snowpack is also analytically resolved. The model is intended to be used for hydrological studies but also to give a realistic estimation of the snowpack state at watershed scale (SWE and snow depth). The structure of the model allows it to be easily calibrated using snow observation. This model is further presented in EGU2017-7492. The snow module of SMASH (Snow Multidata Assimilation System for Hydrology) consists in a multi-layer snow dynamic scheme. It is physically based on mass and energy balances and it reproduces the main physical processes occurring within the snowpack: accumulation, density dynamics, melting, sublimation, radiative balance, heat and mass

Spaceborne Radar Observations of High Mountain Asia Snow and Ice

NASA Astrophysics Data System (ADS)

Lund, J.

2016-12-01

The glaciers of High Mountain Asia show a negative trend in mass balance. Within its sub regions, however, a complex pattern of climate regions and glacial forcings arise. This complexity, coupled with the challenges of field study in the region, illicit notable uncertainties both in observation and prediction of glacial mass balance. Beyond being valuable indicators of climate variability, the glaciers of High Mountain Asia are important water resources for densely populated downstream regions, and also contribute to global sea level rise. Scatterometry, regularly used in polar regions to detect melt in snow and ice, has seen little use in lower latitude glaciers. In High Mountain Asia, focus has been placed on spatial and temporal trends in scatterometer signals for melt onset and freeze-up. In polar regions, scatterometry and synthetic aperture radar (SAR) data have been used to estimate snow accumulation, along with interferometric SAR (InSAR) to measure glacier velocity, better constraining glacial mass balance estimates. For this poster, multiple radar sensors will be compared with both in situ as well as reanalysis precipitation data in varying climate regions in High Mountain Asia to explore correlations between snow accumulation and radar signals. Snowmelt timing influences on InSAR coherence may also be explored.

The changing impact of snow conditions and refreezing on the mass balance of an idealized Svalbard glacier

NASA Astrophysics Data System (ADS)

Van Pelt, Ward; Pohjola, Veijo; Reijmer, Carleen

2016-11-01

Glacier surface melt and runoff depend strongly on seasonal and perennial snow (firn) conditions. Not only does the presence of snow and firn directly affect melt rates by reflecting solar radiation, it may also act as a buffer against mass loss by storing melt water in refrozen or liquid form. In Svalbard, ongoing and projected amplified climate change with respect to the global mean change has severe implications for the state of snow and firn and its impact on glacier mass loss. Model experiments with a coupled surface energy balance - firn model were done to investigate the surface mass balance and the changing role of snow and firn conditions for an idealized Svalbard glacier. A climate forcing for the past, present and future (1984-2104) is constructed, based on observational data from Svalbard Airport and a seasonally dependent projection scenario. Results illustrate ongoing and future firn degradation in response to an elevational retreat of the equilibrium line altitude (ELA) of 31 m decade-1. The temperate firn zone is found to retreat and expand, while cold ice in the ablation zone warms considerably. In response to pronounced winter warming and an associated increase in winter rainfall, the current prevalence of refreezing during the melt season gradually shifts to the winter season in a future climate. Sensitivity tests reveal that in a present and future climate the density and thermodynamic structure of Svalbard glaciers are heavily influenced by refreezing. Refreezing acts as a net buffer against mass loss. However, the net mass balance change after refreezing is substantially smaller than the amount of refreezing itself, which can be ascribed to melt-enhancing effects after refreezing, which partly offset the primary mass-retaining effect of refreezing.

Lower forest density enhances snow retention in regions with warmer winters: A global framework developed from plot-scale observations and modeling

NASA Astrophysics Data System (ADS)

Lundquist, Jessica D.; Dickerson-Lange, Susan E.; Lutz, James A.; Cristea, Nicoleta C.

2013-10-01

Many regions of the world are dependent on snow cover for frost protection and summer water supplies. These same regions are predominantly forested, with forests highly vulnerable to change. Here we combine a meta-analysis of observational studies across the globe with modeling to show that in regions with average December-January-February (DJF) temperatures greater than -1°C, forest cover reduces snow duration by 1-2 weeks compared to adjacent open areas. This occurs because the dominant effect of forest cover shifts from slowing snowmelt by shading the snow and blocking the wind to accelerating snowmelt from increasing longwave radiation. In many locations, midwinter melt removes forest snow before solar radiation is great enough for forest shading to matter, and with warming temperatures, midwinter melt is likely to become more widespread. This temperature-effect in forest-snow-climate interactions must be considered in representations of the combined ecohydrological system and can be used advantageously in forest management strategies.

The growth of shrubs on high Arctic tundra at Bylot Island: impact on snow physical properties and permafrost thermal regime

NASA Astrophysics Data System (ADS)

Domine, Florent; Barrere, Mathieu; Morin, Samuel

2016-12-01

With climate warming, shrubs have been observed to grow on Arctic tundra. Their presence is known to increase snow height and is expected to increase the thermal insulating effect of the snowpack. An important consequence would be the warming of the ground, which will accelerate permafrost thaw, providing an important positive feedback to warming. At Bylot Island (73° N, 80° W) in the Canadian high Arctic where bushes of willows (Salix richardsonii Hook) are growing, we have observed the snow stratigraphy and measured the vertical profiles of snow density, thermal conductivity and specific surface area (SSA) in over 20 sites of high Arctic tundra and in willow bushes 20 to 40 cm high. We find that shrubs increase snow height, but only up to their own height. In shrubs, snow density, thermal conductivity and SSA are all significantly lower than on herb tundra. In shrubs, depth hoar which has a low thermal conductivity was observed to grow up to shrub height, while on herb tundra, depth hoar only developed to 5 to 10 cm high. The thermal resistance of the snowpack was in general higher in shrubs than on herb tundra. More signs of melting were observed in shrubs, presumably because stems absorb radiation and provide hotspots that initiate melting. When melting was extensive, thermal conductivity was increased and thermal resistance was reduced, counteracting the observed effect of shrubs in the absence of melting. Simulations of the effect of shrubs on snow properties and on the ground thermal regime were made with the Crocus snow physics model and the ISBA (Interactions between Soil-Biosphere-Atmosphere) land surface scheme, driven by in situ and reanalysis meteorological data. These simulations did not take into account the summer impact of shrubs. They predict that the ground at 5 cm depth at Bylot Island during the 2014-2015 winter would be up to 13 °C warmer in the presence of shrubs. Such warming may however be mitigated by summer effects.

Inorganic carbon addition stimulates snow algae primary productivity

NASA Astrophysics Data System (ADS)

Hamilton, T. L.; Havig, J. R.

2017-12-01

Earth has experienced glacial/interglacial oscillations throughout its history. Today over 15 million square kilometers (5.8 million square miles) of Earth's land surface is covered in ice including glaciers, ice caps, and the ice sheets of Greenland and Antarctica, most of which are retreating as a consequence of increased atmospheric CO2. Glaciers are teeming with life and supraglacial snow and ice surfaces are often red due to blooms of photoautotrophic algae. Recent evidence suggests the red pigmentation, secondary carotenoids produced in part to thrive under high irradiation, lowers albedo and accelerates melt. However, there are relatively few studies that report the productivity of snow algae communities and the parameters that constrain their growth on snow and ice surfaces. Here, we demonstrate that snow algae primary productivity can be stimulated by the addition of inorganic carbon. We found an increase in light-dependent carbon assimilation in snow algae microcosms amended with increasing amounts of inorganic carbon. Our snow algae communities were dominated by typical cosmopolitan snow algae species recovered from Alpine and Arctic environments. The climate feedbacks necessary to enter and exit glacial/interglacial oscillations are poorly understood. Evidence and models agree that global Snowball events are accompanied by changes in atmospheric CO2 with increasing CO2 necessary for entering periods of interglacial time. Our results demonstrate a positive feedback between increased CO2 and snow algal productivity and presumably growth. With the recent call for bio-albedo effects to be considered in climate models, our results underscore the need for robust climate models to include feedbacks between supraglacial primary productivity, albedo, and atmospheric CO2.

Snow cover distribution over elevation zones in a mountainous catchment

NASA Astrophysics Data System (ADS)

Panagoulia, D.; Panagopoulos, Y.

2009-04-01

A good understanding of the elevetional distribution of snow cover is necessary to predict the timing and volume of runoff. In a complex mountainous terrain the snow cover distribution within a watershed is highly variable in time and space and is dependent on elevation, slope, aspect, vegetation type, surface roughness, radiation load, and energy exchange at the snow-air interface. Decreases in snowpack due to climate change could disrupt the downstream urban and agricultural water supplies, while increases could lead to seasonal flooding. Solar and longwave radiation are dominant energy inputs driving the ablation process. Turbulent energy exchange at the snow cover surface is important during the snow season. The evaporation of blowing and drifting snow is strongly dependent upon wind speed. Much of the spatial heterogeneity of snow cover is the result of snow redistribution by wind. Elevation is important in determining temperature and precipitation gradients along hillslopes, while the temperature gradients determine where precipitation falls as rain and snow and contribute to variable melt rates within the hillslope. Under these premises, the snow accumulation and ablation (SAA) model of the US National Weather Service (US NWS) was applied to implement the snow cover extent over elevation zones of a mountainous catchment (the Mesochora catchment in Western-Central Greece), taking also into account the indirectly included processes of sublimation, interception, and snow redistribution. The catchment hydrology is controlled by snowfall and snowmelt and the simulated discharge was computed from the soil moisture accounting (SMA) model of the US NWS and compared to the measured discharge. The elevationally distributed snow cover extent presented different patterns with different time of maximization, extinction and return during the year, producing different timing of discharge that is a crucial factor for the control and management of water resources systems.

Empirical Retrieval of Surface Melt Magnitude from Coupled MODIS Optical and Thermal Measurements over the Greenland Ice Sheet during the 2001 Ablation Season.

PubMed

Lampkin, Derrick; Peng, Rui

2008-08-22

Accelerated ice flow near the equilibrium line of west-central Greenland Ice Sheet (GIS) has been attributed to an increase in infiltrated surface melt water as a response to climate warming. The assessment of surface melting events must be more than the detection of melt onset or extent. Retrieval of surface melt magnitude is necessary to improve understanding of ice sheet flow and surface melt coupling. In this paper, we report on a new technique to quantify the magnitude of surface melt. Cloud-free dates of June 10, July 5, 7, 9, and 11, 2001 Moderate Resolution Imaging Spectroradiometer (MODIS) daily reflectance Band 5 (1.230-1.250μm) and surface temperature images rescaled to 1km over western Greenland were used in the retrieval algorithm. An optical-thermal feature space partitioned as a function of melt magnitude was derived using a one-dimensional thermal snowmelt model (SNTHERM89). SNTHERM89 was forced by hourly meteorological data from the Greenland Climate Network (GC-Net) at reference sites spanning dry snow, percolation, and wet snow zones in the Jakobshavn drainage basin in western GIS. Melt magnitude or effective melt (E-melt) was derived for satellite composite periods covering May, June, and July displaying low fractions (0-1%) at elevations greater than 2500m and fractions at or greater than 15% at elevations lower than 1000m assessed for only the upper 5 cm of the snow surface. Validation of E-melt involved comparison of intensity to dry and wet zones determined from QSCAT backscatter. Higher intensities (> 8%) were distributed in wet snow zones, while lower intensities were grouped in dry zones at a first order accuracy of ~ ±2%.

Building a Snow Data System on the Apache OODT Open Technology Stack

NASA Astrophysics Data System (ADS)

Goodale, C. E.; Painter, T. H.; Mattmann, C. A.; Hart, A. F.; Ramirez, P.; Zimdars, P.; Bryant, A. C.; Snow Data System Team

2011-12-01

Snow cover and its melt dominate regional climate and hydrology in many of the world's mountainous regions. One-sixth of Earth's population depends on snow- or glacier-melt for water resources. Operationally, seasonal forecasts of snowmelt-generated streamflow are leveraged through empirical relations based on past snowmelt periods. These historical data show that climate is changing, but the changes reduce the reliability of the empirical relations. Therefore optimal future management of snowmelt derived water resources will require explicit physical models driven by remotely sensed snow property data. Toward this goal, the Snow Optics Laboratory at the Jet Propulsion Laboratory has initiated a near real-time processing pipeline to generate and publish post-processed snow data products within a few hours of satellite acquisition. To solve this challenge, a Scientific Data Management and Processing System was required and the JPL Team leveraged an open-source project called Object Oriented Data Technology (OODT). OODT was developed within NASA's Jet Propulsion Laboratory across the last 10 years. OODT has supported various scientific data management and processing projects, providing solutions in the Earth, Planetary, and Medical science fields. It became apparent that the project needed to be opened to a larger audience to foster and promote growth and adoption. OODT was open-sourced at the Apache Software Foundation in November 2010 and has a growing community of users and committers that are constantly improving the software. Leveraging OODT, the JPL Snow Data System (SnowDS) Team was able to install and configure a core Data Management System (DMS) that would download MODIS raw data files and archive the products in a local repository for post processing. The team has since built an online data portal, and an algorithm-processing pipeline using the Apache OODT software as the foundation. We will present the working SnowDS system with its core remote sensing

Spatiotemporal changes of snow cover over the Tibetan plateau based on cloud-removed moderate resolution imaging spectroradiometer fractional snow cover product from 2001 to 2011

NASA Astrophysics Data System (ADS)

Tang, Zhiguang; Wang, Jian; Li, Hongyi; Yan, Lili

2013-01-01

Snow cover changes over the Tibetan plateau (TP) are examined using moderate resolution imaging spectroradiometer (MODIS) daily fractional snow cover (FSC) data from 2001 to 2011 as well as in situ temperature data. First, the accuracy of the MODIS FSC data under clear sky conditions is evaluated by comparing with Landsat 30-m observations. Then we describe a cloud-gap-filled (CGF) method using cubic spline interpolation algorithm to fill in data gaps caused by clouds. Finally, the spatial and temporal changes of snow cover are analyzed on the basis of the MODIS-derived snow-covered area and snow-covered days (SCD) data. Results show that the mean absolute error of MODIS FSC data under clear sky condition is about 0.098 over the TP. The CGF method is efficient in cloud reduction (overall mean absolute error of the retrieved FSC data is 0.092). There is a very high inter-annual and intra-seasonal variability of snow cover in the 11 years. The higher snow cover corresponds well with the huge mountains. The accumulation and melt periods of snow cover vary in different elevation zones. About 34.14% (5.56% with a significant decline) and 24.75% (3.9% with a significant increase) of the study area presents declining and increasing trend in SCD, respectively. The inter-annual fluctuation of snow cover can be explained by the high negative correlations observed between the snow cover and the in situ temperature, especially in some elevations of February, April, May, August, and September.

Terrestrial photography as a complementary measurement in weather stations for snow monitoring

NASA Astrophysics Data System (ADS)

Pimentel, Rafael; José Pérez-Palazón, María; Herrero, Javier; José Polo, María

2015-04-01

Snow monitoring constitutes a basic key to know snow behaviour and evolution, which have particular features in semiarid regions (i.e. highly strong spatiotemporal variability, and the occurrence of several accumulation-melting cycles throughout the year). On one hand, traditional snow observation, such as snow surveys and snow pillows have the inconvenience of a limited accessibility during snow season and the impossibility to cover a vast extension. On the other hand, satellite remote sensing techniques, largely employed in medium to large scale regional studies, has the disadvantage of a fixed spatial and temporal resolutions which in some cases are not able to reproduce snow processes at small scale. An economic alternative is the use of terrestrial photography which scales are adapted to the study problem. At the microscale resolution permits the continuous monitoring of snow, adapting the resolution of the observation to the scales of the processes. Besides its use as raw observation datasets to calibrate and validate models' results, terrestrial photography constitutes valuable information to complement weather stations observations. It allows the discriminating possible mistakes in meteorological observations (i.e. overestimation on rain measurements) and a better understanding of snow behaviour against certain weather agents (i.e. blowing snow). Thus, terrestrial photography is a feasible and convenient technique to be included in weather monitoring stations in mountainous areas in semiarid regions.

The electrical self-potential method is a non-intrusive snow-hydrological sensor

NASA Astrophysics Data System (ADS)

Thompson, S. S.; Kulessa, B.; Essery, R. L. H.; Lüthi, M. P.

2015-08-01

Our ability to measure, quantify and assimilate hydrological properties and processes of snow in operational models is disproportionally poor compared to the significance of seasonal snowmelt as a global water resource and major risk factor in flood and avalanche forecasting. Encouraged by recent theoretical, modelling and laboratory work, we show here that the diurnal evolution of aerially-distributed self-potential magnitudes closely track those of bulk meltwater fluxes in melting in-situ snowpacks at Rhone and Jungfraujoch glaciers, Switzerland. Numerical modelling infers temporally-evolving liquid water contents in the snowpacks on successive days in close agreement with snow-pit measurements. Muting previous concerns, the governing physical and chemical properties of snow and meltwater became temporally invariant for modelling purposes. Because measurement procedure is straightforward and readily automated for continuous monitoring over significant spatial scales, we conclude that the self-potential geophysical method is a highly-promising non-intrusive snow-hydrological sensor for measurement practice, modelling and operational snow forecasting.

Separating snow, clean and debris covered ice in the Upper Indus Basin, Hindukush-Karakoram-Himalayas, using Landsat images between 1998 and 2002

NASA Astrophysics Data System (ADS)

Khan, Asif; Naz, Bibi S.; Bowling, Laura C.

2015-02-01

The Hindukush Karakoram Himalayan mountains contain some of the largest glaciers of the world, and supply melt water from perennial snow and glaciers to the Upper Indus Basin (UIB) upstream of Tarbela dam, which constitutes greater than 80% of the annual flows, and caters to the needs of millions of people in the Indus Basin. It is therefore important to study the response of perennial snow and glaciers in the UIB under changing climatic conditions, using improved hydrological modeling, glacier mass balance, and observations of glacier responses. However, the available glacier inventories and datasets only provide total perennial-snow and glacier cover areas, despite the fact that snow, clean ice and debris covered ice have different melt rates and densities. This distinction is vital for improved hydrological modeling and mass balance studies. This study, therefore, presents a separated perennial snow and glacier inventory (perennial snow-cover on steep slopes, perennial snow-covered ice, clean and debris covered ice) based on a semi-automated method that combines Landsat images and surface slope information in a supervised maximum likelihood classification to map distinct glacier zones, followed by manual post processing. The accuracy of the presented inventory falls well within the accuracy limits of available snow and glacier inventory products. For the entire UIB, estimates of perennial and/or seasonal snow on steep slopes, snow-covered ice, clean and debris covered ice zones are 7238 ± 724, 5226 ± 522, 4695 ± 469 and 2126 ± 212 km2 respectively. Thus total snow and glacier cover is 19,285 ± 1928 km2, out of which 12,075 ± 1207 km2 is glacier cover (excluding steep slope snow-cover). Equilibrium Line Altitude (ELA) estimates based on the Snow Line Elevation (SLE) in various watersheds range between 4800 and 5500 m, while the Accumulation Area Ratio (AAR) ranges between 7% and 80%. 0 °C isotherms during peak ablation months (July and August) range

Towards Improved Snow Water Equivalent Estimation via GRACE Assimilation

NASA Technical Reports Server (NTRS)

Forman, Bart; Reichle, Rofl; Rodell, Matt

2011-01-01

Passive microwave (e.g. AMSR-E) and visible spectrum (e.g. MODIS) measurements of snow states have been used in conjunction with land surface models to better characterize snow pack states, most notably snow water equivalent (SWE). However, both types of measurements have limitations. AMSR-E, for example, suffers a loss of information in deep/wet snow packs. Similarly, MODIS suffers a loss of temporal correlation information beyond the initial accumulation and final ablation phases of the snow season. Gravimetric measurements, on the other hand, do not suffer from these limitations. In this study, gravimetric measurements from the Gravity Recovery and Climate Experiment (GRACE) mission are used in a land surface model data assimilation (DA) framework to better characterize SWE in the Mackenzie River basin located in northern Canada. Comparisons are made against independent, ground-based SWE observations, state-of-the-art modeled SWE estimates, and independent, ground-based river discharge observations. Preliminary results suggest improved SWE estimates, including improved timing of the subsequent ablation and runoff of the snow pack. Additionally, use of the DA procedure can add vertical and horizontal resolution to the coarse-scale GRACE measurements as well as effectively downscale the measurements in time. Such findings offer the potential for better understanding of the hydrologic cycle in snow-dominated basins located in remote regions of the globe where ground-based observation collection if difficult, if not impossible. This information could ultimately lead to improved freshwater resource management in communities dependent on snow melt as well as a reduction in the uncertainty of river discharge into the Arctic Ocean.

Satellite Remote Sensing of Snow/Ice Albedo over the Himalayas

NASA Technical Reports Server (NTRS)

Hsu, N. Christina; Gautam, Ritesh

2012-01-01

The Himalayan glaciers and snowpacks play an important role in the hydrological cycle over Asia. The seasonal snow melt from the Himalayan glaciers and snowpacks is one of the key elements to the livelihood of the downstream densely populated regions of South Asia. During the pre-monsoon season (April-May-June), South Asia not only experiences the reversal of the regional meridional tropospheric temperature gradient (i.e., the onset of the summer monsoon), but also is being bombarded by dry westerly airmass that transports mineral dust from various Southwest Asian desert and arid regions into the Indo-Gangetic Plains in northern India. Mixed with heavy anthropogenic pollution, mineral dust constitutes the bulk of regional aerosol loading and forms an extensive and vertically extended brown haze lapping against the southern slopes of the Himalayas. Episodic dust plumes are advected over the Himalayas, and are discernible in satellite imagery, resulting in dust-capped snow surface. Motivated by the potential implications of accelerated snowmelt, we examine the changes in radiative energetics induced by aerosol transport over the Himalayan snow cover by utilizing space borne observations. Our objective lies in the investigation of potential impacts of aerosol solar absorption on the Top-of-Atmosphere (TOA) spectral reflectivity and the broadband albedo, and hence the accelerated snowmelt, particularly in the western Himalayas. Lambertian Equivalent Reflectivity (LER) in the visible and near-infrared wavelengths, derived from Moderate Resolution Imaging Spectroradiometer radiances, is used to generate statistics for determining perturbation caused due to dust layer over snow surface in over ten years of continuous observations. Case studies indicate significant reduction of LER ranging from 5 to 8% in the 412-860nm spectra. Broadband flux observations, from the Clouds and the Earth's Radiant Energy System, are also used to investigate changes in shortwave TOA flux over

High fidelity remote sensing of snow properties from MODIS and the Airborne Snow Observatory: Snowflakes to Terabytes

NASA Astrophysics Data System (ADS)

Painter, T.; Mattmann, C. A.; Brodzik, M.; Bryant, A. C.; Goodale, C. E.; Hart, A. F.; Ramirez, P.; Rittger, K. E.; Seidel, F. C.; Zimdars, P. A.

2012-12-01

The response of the cryosphere to climate forcings largely determines Earth's climate sensitivity. However, our understanding of the strength of the simulated snow albedo feedback varies by a factor of three in the GCMs used in the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, mainly caused by uncertainties in snow extent and the albedo of snow-covered areas from imprecise remote sensing retrievals. Additionally, the Western US and other regions of the globe depend predominantly on snowmelt for their water supply to agriculture, industry and cities, hydroelectric power, and recreation, against rising demand from increasing population. In the mountains of the Upper Colorado River Basin, dust radiative forcing in snow shortens snow cover duration by 3-7 weeks. Extended to the entire upper basin, the 5-fold increase in dust load since the late-1800s results in a 3-week earlier peak runoff and a 5% annual loss of total runoff. The remotely sensed dynamics of snow cover duration and melt however have not been factored into hydrological modeling, operational forecasting, and policymaking. To address these deficiencies in our understanding of snow properties, we have developed and validated a suite of MODIS snow products that provide accurate fractional snow covered area and radiative forcing of dust and carbonaceous aerosols in snow. The MODIS Snow Covered Area and Grain size (MODSCAG) and MODIS Dust Radiative Forcing in Snow (MODDRFS) algorithms, developed and transferred from imaging spectroscopy techniques, leverage the complete MODIS surface reflectance spectrum. The two most critical properties for understanding snowmelt runoff and timing are the spatial and temporal distributions of snow water equivalent (SWE) and snow albedo. We have created the Airborne Snow Observatory (ASO), an imaging spectrometer and scanning LiDAR system, to quantify SWE and snow albedo, generate unprecedented knowledge of snow properties, and provide complete

Snow cover and extreme winter warming events control flower abundance of some, but not all species in high arctic Svalbard

PubMed Central

Semenchuk, Philipp R; Elberling, Bo; Cooper, Elisabeth J

2013-01-01

Abstract The High Arctic winter is expected to be altered through ongoing and future climate change. Winter precipitation and snow depth are projected to increase and melt out dates change accordingly. Also, snow cover and depth will play an important role in protecting plant canopy from increasingly more frequent extreme winter warming events. Flower production of many Arctic plants is dependent on melt out timing, since season length determines resource availability for flower preformation. We erected snow fences to increase snow depth and shorten growing season, and counted flowers of six species over 5 years, during which we experienced two extreme winter warming events. Most species were resistant to snow cover increase, but two species reduced flower abundance due to shortened growing seasons. Cassiope tetragona responded strongly with fewer flowers in deep snow regimes during years without extreme events, while Stellaria crassipes responded partly. Snow pack thickness determined whether winter warming events had an effect on flower abundance of some species. Warming events clearly reduced flower abundance in shallow but not in deep snow regimes of Cassiope tetragona, but only marginally for Dryas octopetala. However, the affected species were resilient and individuals did not experience any long term effects. In the case of short or cold summers, a subset of species suffered reduced reproductive success, which may affect future plant composition through possible cascading competition effects. Extreme winter warming events were shown to expose the canopy to cold winter air. The following summer most of the overwintering flower buds could not produce flowers. Thus reproductive success is reduced if this occurs in subsequent years. We conclude that snow depth influences flower abundance by altering season length and by protecting or exposing flower buds to cold winter air, but most species studied are resistant to changes. Winter warming events, often

Large-area surveys for black carbon and other light-absorbing impurities in snow: Arctic, Antarctic, North America, China (Invited)

NASA Astrophysics Data System (ADS)

Warren, S. G.; Doherty, S. J.; Hegg, D.; Dang, C.; Zhang, R.; Grenfell, T. C.; Brandt, R. E.; Clarke, A. D.; Zatko, M.

2013-12-01

Absorption of radiation by ice is extremely weak at visible and near-UV wavelengths, so small amounts of light-absorbing impurities (LAI) in snow can dominate the absorption of sunlight at these wavelengths, reducing the albedo relative to that of pure snow and leading to earlier snowmelt. Snow samples were collected in Alaska, Canada, Greenland, Svalbard, Norway, Russia, and the Arctic Ocean, on tundra, glaciers, ice caps, sea ice, and frozen lakes, and in boreal forests. Snow was collected mostly in spring, when the entire winter snowpack was accessible for sampling. Snow was also collected at 67 sites in western North America. Expeditions from Lanzhou University obtained black carbon (BC) amounts at 84 sites in northeast and northwest China. BC was measured at 3 locations on the Antarctic Plateau, and at 5 sites on East Antarctic sea ice. The snow is melted and filtered; the filters are analyzed in a spectrophotometer. Median BC mixing ratios in snow range over 4 orders of magnitude from 0.2 ng/g in Antarctica to 1000 ng/g in northeast China. Chemical analyses, input to a receptor model, indicate that the major source of BC in most of the Arctic is biomass burning, but industrial sources dominate in Svalbard and the central Arctic Ocean. Non-BC impurities, principally brown (organic) carbon, are typically responsible for ~40% of the visible and ultraviolet absorption. In northeast China BC is the dominant LAI, but in Inner Mongolia soil dominates. When the snow surface layer melts, much of the BC is left at the top of the snowpack rather than carried away in meltwater, thus causing a positive feedback on snowmelt. This process was quantified through field studies in Greenland, Alaska, and Norway, where we found that only 10-30% of the BC is removed with meltwater. The BC content of the Arctic atmosphere has declined markedly since 1989, according to the continuous measurements of near-surface air in Canada, Alaska, and Svalbard. Correspondingly, our recent BC

Spatial Relationships Between Snow Contaminant Content, Grain Size, and Surface Temperature in Multi-spectral Remote Sensing Data of Mt. Rainier, WA

NASA Astrophysics Data System (ADS)

Kay, J. E.; Hansen, G.; Gillespie, A.; Pettit, E.

2002-12-01

Relating cryosphere change to climate change requires estimation of radiative fluxes on snow-covered surfaces. The distribution of, and relationship between, snow-pack properties that affect radiative balance can be estimated with high-resolution remote-sensing data. MODIS/ASTER airborne simulator (MASTER) data were collected at Mt. Rainier to reveal spatial patterns of, and correlations between, snow contaminant content, grain size, and temperature. The visible and near-infrared (VNIR: 11 bands, 0.4-1.0 μm) and the short-wave infrared (SWIR: 14 bands, 1.6-2.4 μm) data are processed to bi-directional reflectance (BDR) and albedo, by removing atmospheric effects and by normalizing to Solar irradiance and incidence angle. VNIR BDR and albedo are used as a proxy for snow contaminant content. Physical and optical grain size are estimated by comparing SWIR BDR and albedo to modeled and measured spectra, and ground-truth measurements. The thermal infrared data (TIR: 10 bands, 8-13 μm) are processed to temperature by removing emissivity and atmospheric effects. In combination, the VNIR, SWIR, and TIR data reveal a distinct pattern of contaminants, grain size, and temperature related to a recent snowfall and the end-of-the-summer melting season. At lower elevations, the surface accumulation of dirty lag deposits resulted in snow with very low visible albedo (20-30 %), large physical and optical grain radii (500-1500 μm, 200 μm), and temperatures near the melting point. At higher elevations, the recent snowfall left snow with low contaminant content, and a higher visible albedo (60-90 %). However, a region near the summit with smaller physical and optical grain radii (400 μm, 100 μm), and temperatures below the melting point, is distinguished from a middle elevation region with grain sizes and temperatures similar to the lower region. Contaminants reduce VNIR albedo and significantly enhance absorption of incoming solar radiation. The spatial correlation between

Glacier Melt Detection in Complex Terrain Using New AMSR-E Calibrated Enhanced Daily EASE-Grid 2.0 Brightness Temperature (CETB) Earth System Data Record

NASA Astrophysics Data System (ADS)

Ramage, J. M.; Brodzik, M. J.; Hardman, M.

2016-12-01

Passive microwave (PM) 18 GHz and 36 GHz horizontally- and vertically-polarized brightness temperatures (Tb) channels from the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) have been important sources of information about snow melt status in glacial environments, particularly at high latitudes. PM data are sensitive to the changes in near-surface liquid water that accompany melt onset, melt intensification, and refreezing. Overpasses are frequent enough that in most areas multiple (2-8) observations per day are possible, yielding the potential for determining the dynamic state of the snow pack during transition seasons. AMSR-E Tb data have been used effectively to determine melt onset and melt intensification using daily Tb and diurnal amplitude variation (DAV) thresholds. Due to mixed pixels in historically coarse spatial resolution Tb data, melt analysis has been impractical in ice-marginal zones where pixels may be only fractionally snow/ice covered, and in areas where the glacier is near large bodies of water: even small regions of open water in a pixel severely impact the microwave signal. We use the new enhanced-resolution Calibrated Passive Microwave Daily EASE-Grid 2.0 Brightness Temperature (CETB) Earth System Data Record product's twice daily obserations to test and update existing snow melt algorithms by determining appropriate melt thresholds for both Tb and DAV for the CETB 18 and 36 GHz channels. We use the enhanced resolution data to evaluate melt characteristics along glacier margins and melt transition zones during the melt seasons in locations spanning a wide range of melt scenarios, including the Patagonian Andes, the Alaskan Coast Range, and the Russian High Arctic icecaps. We quantify how improvement of spatial resolution from the original 12.5 - 25 km-scale pixels to the enhanced resolution of 3.125 - 6.25 km improves the ability to evaluate melt timing across boundaries and transition zones in diverse glacial environments.

Impacts of Synoptic Weather Patterns on Snow Albedo at Sites in New England

NASA Astrophysics Data System (ADS)

Adolph, A. C.; Albert, M. R.; Lazarcik, J.; Dibb, J. E.; Amante, J.; Price, A. N.

2015-12-01

Winter snow in the northeastern United States has changed over the last several decades, resulting in shallower snow packs, fewer days of snow cover and increasing precipitation falling as rain in the winter. In addition to these changes which cause reductions in surface albedo, increasing winter temperatures also lead to more rapid snow grain growth, resulting in decreased snow reflectivity. We present in-situ measurements and analyses to test the sensitivity of seasonal snow albedo to varying weather conditions at sites in New England. In particular, we investigate the impact of temperature on snow albedo through melt and grain growth, the impact of precipitation event frequency on albedo through snow "freshening," and the impact of storm path on snow structure and snow albedo. Over three winter seasons between 2013 and 2015, in-situ snow characterization measurements were made at three non-forested sites across New Hampshire. These near-daily measurements include spectrally resolved albedo, snow optical grain size determined through contact spectroscopy, snow depth, snow density and local meteorological parameters. Combining this information with storm tracks derived from HYSPLIT modeling, we quantify the current sensitivity of northeastern US snow albedo to temperature as well as precipitation type, frequency and path. Our analysis shows that southerly winter storms result in snow with a significantly lower albedo than storms which come from across the continental US or the Atlantic Ocean. Interannual variability in temperature and statewide spatial variability in snowfall rates at our sites show the relative importance of snowfall amount and temperatures in albedo evolution over the course of the winter.

Validation of A One-Dimensional Snow-Land Surface Model at the Sleepers River Watershed

NASA Astrophysics Data System (ADS)

Sun, Wen-Yih; Chern, Jiun-Dar

A one-dimensional land surface model, based on conservations of heat and water substance inside the soil and snow, is presented. To validate the model, a stand-alone experiment is carried out with five years of meteorological and hydrological observations collected from the NOAA-ARS Cooperative Snow Research Project (1966-1974) at the Sleepers River watershed in Danville, Vermont, U.S.A. The numerical results show that the model is capable of reproducing the observed soil temperature at different depths during the winter as well as a rapid increase of soil temperature after snow melts in the spring. The model also simulates the density, temperature, thickness, and equivalent water depth of snow reasonably well. The numerical results are sensitive to the fresh snow density and the soil properties used in the model, which affect the heat exchange between the snowpack and the soil.

Effects of soot-induced snow albedo change on snowpack and hydrological cycle in western U.S. based on WRF chemistry and regional climate simulations

NASA Astrophysics Data System (ADS)

Qian, Y.; Gustafson, W. I.; Leung, R.; Ghan, S. J.

2008-12-01

Radiative forcing induced by soot on snow is an important anthropogenic forcing affecting the global climate. In this study we simulated the deposition of soot aerosol on snow and the resulting impact on snowpack and the hydrological cycle in the western United States. A yearlong simulation was performed using the chemistry version of the Weather Research and Forecasting model (WRF-Chem) to determine the soot deposition, followed by three simulations using WRF in meteorology-only mode, with and without the soot-induced snow albedo perturbations. The chemistry simulation shows large spatial variability in soot deposition that reflects the localized emissions and the influence of the complex terrain. The soot-induced snow albedo perturbations increase the surface net solar radiation flux during late winter to early spring, increase the surface air temperature, and reduce the snow accumulation and spring snowmelt. These effects are stronger over the central Rockies and southern Alberta, where soot deposition and snowpack overlap the most. The indirect forcing of soot accelerates snowmelt and alters stream flows, including a trend toward earlier melt dates in the western United States. The soot-induced albedo reduction initiates a positive feedback process whereby dirty snow absorbs more solar radiation, heating the surface and warming the air. This warming causes reduced snow depth and fraction, which further reduces the regional surface albedo for the snow covered regions. For a doubled snow albedo perturbation, the change to surface energy and temperature is around 50-80%, however, snowpack reduction is nonlinearly accelerated.

[Effects of seasonal snow cover on soil nitrogen transformation in alpine ecosystem: a review].

PubMed

Liu, Lin; Wu, Yan; He, Yi-xin; Wu, Ning; Sun, Geng; Zhang, Lin; Xu, Jun-jun

2011-08-01

Seasonal snow cover has pronounced effects on the soil nitrogen concentration and transformation in alpine ecosystem. Snowfall is an important form of nitrogen deposition, which directly affects the content of soil available nitrogen. Different depths and different duration of snow cover caused by snowfall may lead the heterogeneity of abiotic factors (soil temperature and moisture) and biotic factors (soil microbes, alpine plants, and alpine animals), and further, produce complicated effects on the mineralization and immobilization of soil nitrogen. This paper introduced in emphasis the inherent mechanisms of soil nitrogen mineralization and leaching under the effects of frequent freeze-thaw events during the durative melting of snow cover, and summarized the main research results of field in situ experiments about the effects of seasonal snow cover on soil nitrogen in alpine ecosystem based on the possible changes in snow cover in the future. Some suggestions with regard to the effects of seasonal snow cover on soil nitrogen were put forward.

Seasonal variations of snow chemistry and mineral dust in the snow pit at GV7, Antarctica

NASA Astrophysics Data System (ADS)

Kang, Jung-Ho; Hwang, Heejin; Han, Yongchoul; Hong, Sang Bum; Lee, Khanghyun; Do Hur, Soon; Frezzotti, Massimo; Narcisi, Biancamaria

2015-04-01

We conducted the scientific ice coring project led by PNRA and KOPRI during the 2013/2014 Italian-Korean Antarctic Expedition in the framework of International Partnerships in Ice Core Science (IPICS) to understand the climatic variability in the last 2000 years. In the part of project, we collected a 3.0 m-depth snow pit at the site of GV7 (S 70° 41'17.1", E 158° 51'48.9", 1950 m a.s.l.), Antarctica. Here, we present the results obtained from the analysis of the water isotope compositions, the major ion concentrations, and the mineral dust concentrations from the snow pit. Snow densities and temperatures also measured in the field. At KOPRI, the samples were melted, then the stable water isotopes, major ions, and particle size distribution were analyzed with the cavity ring-down spectrometers (L1102-i, Piccaro), ion chromatography (ICS-2100, Thermo), and coulter counter (Multisizer 3, Beckman Coulter), respectively. The δ18O varies between -38.3 and -24.1o with a mean value of -31.0o. The δD ranges between -331 and -186o with a mean value of -243o. Among the ion concentrations (Na+, Ca2+, Mg2+, Cl-, SO42-, CH3SO3-(MSA)) from the snow pit, MSA concentrations show a clear seasonal variation. The mineral dust in the pit characterized with the differences of the concentration and the particle size distribution by the seasonality. These data allow us to assume about 4.5 years of snow deposition covered from 2009 to 2013 by these oscillations of the isotopes and geochemical characteristics.

Why on the snow? Winter emergence strategies of snow-active Chironomidae (Diptera) in Poland.

PubMed

Soszyńska-Maj, Agnieszka; Paasivirta, Lauri; Giłka, Wojciech

2016-10-01

A long-term study of adult non-biting midges (Chironomidae) active in winter on the snow in mountain areas and lowlands in Poland yielded 35 species. The lowland and mountain communities differed significantly in their specific composition. The mountain assemblage was found to be more diverse and abundant, with a substantial contribution from the subfamily Diamesinae, whereas Orthocladiinae predominated in the lowlands. Orthocladius wetterensis Brundin was the most characteristic and superdominant species in the winter-active chironomid communities in both areas. Only a few specimens and species of snow-active chironomids were recorded in late autumn and early winter. The abundance of chironomids peaked in late February in the mountain and lowland areas with an additional peak in the mountain areas in early April. However, this second peak of activity consisted mainly of Orthocladiinae, as Diamesinae emerged earliest in the season. Most snow-active species emerged in mid- and late winter, but their seasonal patterns differed between the 2 regions as a result of the different species composition and the duration of snow cover in these regions. Spearman's rank correlation coefficient tests yielded positive results between each season and the number of chironomid individuals recorded in the mountain area. A positive correlation between air temperature, rising to +3.5 °C, and the number of specimens recorded on the snow in the mountain community was statistically significant. The winter emergence and mate-searching strategies of chironomids are discussed in the light of global warming, and a brief compilation of most important published data on the phenomena studied is provided. © 2015 Institute of Zoology, Chinese Academy of Sciences.

Empirical Retrieval of Surface Melt Magnitude from Coupled MODIS Optical and Thermal Measurements over the Greenland Ice Sheet during the 2001 Ablation Season

PubMed Central

Lampkin, Derrick; Peng, Rui

2008-01-01

Accelerated ice flow near the equilibrium line of west-central Greenland Ice Sheet (GIS) has been attributed to an increase in infiltrated surface melt water as a response to climate warming. The assessment of surface melting events must be more than the detection of melt onset or extent. Retrieval of surface melt magnitude is necessary to improve understanding of ice sheet flow and surface melt coupling. In this paper, we report on a new technique to quantify the magnitude of surface melt. Cloud-free dates of June 10, July 5, 7, 9, and 11, 2001 Moderate Resolution Imaging Spectroradiometer (MODIS) daily reflectance Band 5 (1.230-1.250μm) and surface temperature images rescaled to 1km over western Greenland were used in the retrieval algorithm. An optical-thermal feature space partitioned as a function of melt magnitude was derived using a one-dimensional thermal snowmelt model (SNTHERM89). SNTHERM89 was forced by hourly meteorological data from the Greenland Climate Network (GC-Net) at reference sites spanning dry snow, percolation, and wet snow zones in the Jakobshavn drainage basin in western GIS. Melt magnitude or effective melt (E-melt) was derived for satellite composite periods covering May, June, and July displaying low fractions (0-1%) at elevations greater than 2500m and fractions at or greater than 15% at elevations lower than 1000m assessed for only the upper 5 cm of the snow surface. Validation of E-melt involved comparison of intensity to dry and wet zones determined from QSCAT backscatter. Higher intensities (> 8%) were distributed in wet snow zones, while lower intensities were grouped in dry zones at a first order accuracy of ∼ ±2%. PMID:27873793

The Electrical Self-Potential Method as a Non-Intrusive Snow-Hydrological Sensor

NASA Astrophysics Data System (ADS)

Kulessa, B.; Thompson, S. S.; Luethi, M. P.; Essery, R.

2015-12-01

Building on growing momentum in the application of geophysical techniques to snow problems and, specifically, on new theory and an electrical geophysical snow hydrological model published recently; we demonstrate for the first time that the electrical self-potential geophysical technique can sense in-situ bulk meltwater fluxes. This has broad and immediate implications for snow measurement practice, modelling and operational snow forecasting. Our ability to measure, quantify and assimilate hydrological properties and processes of snow in operational models is disproportionally poor compared to the significance of seasonal snowmelt as a global water resource and major risk factor in flood and avalanche forecasting. Encouraged by recent theoretical, modelling and laboratory work, we show here that the diurnal evolution of aerially-distributed self-potential magnitudes closely track those of bulk meltwater fluxes in melting in-situ snowpacks at Rhone and Jungfraujoch glaciers, Switzerland. Numerical modelling infers temporally-evolving liquid water contents in the snowpacks on successive days in close agreement with snow-pit measurements. Muting previous concerns, the governing physical and chemical properties of snow and meltwater became temporally invariant for modelling purposes. Because measurement procedure is straightforward and readily automated for continuous monitoring over significant spatial scales, we conclude that the self-potential geophysical method is a highly-promising non-intrusive snow-hydrological sensor for measurement practice, modelling and operational snow forecasting.

The Spatial and Temporal Variability of Meltwater Flow Paths: Insights From a Grid of Over 100 Snow Lysimeters

NASA Astrophysics Data System (ADS)

Webb, R. W.; Williams, M. W.; Erickson, T. A.

2018-02-01

Snowmelt is an important part of the hydrologic cycle and ecosystem dynamics for headwater systems. However, the physical process of water flow through snow is a poorly understood aspect of snow hydrology as meltwater flow paths tend to be highly complex. Meltwater flow paths diverge and converge as percolating meltwater reaches stratigraphic layer interfaces creating high spatial variability. Additionally, a snowpack is temporally heterogeneous due to rapid localized metamorphism that occurs during melt. This study uses a snowmelt lysimeter array at tree line in the Niwot Ridge study area of northern Colorado. The array is designed to address the issue of spatial and temporal variability of basal discharge at 105 locations over an area of 1,300 m2. Observed coefficients of variation ranged from 0 to almost 10 indicating more variability than previously observed, though this variability decreased throughout each melt season. Snowmelt basal discharge also significantly increases as snow depth decreases displaying a cluster pattern that peaks during weeks 3-5 of the snowmelt season. These results are explained by the flow of meltwater along snow layer interfaces. As the snowpack becomes less stratified through the melt season, the pattern transforms from preferential flow paths to uniform matrix flow. Correlation ranges of the observed basal discharge correspond to a mean representative elementary area of 100 m2, or a characteristic length of 10 m. Snowmelt models representing processes at scales less than this will need to explicitly incorporate the spatial variability of snowmelt discharge and meltwater flow paths through snow between model pixels.

Monitoring snow cover and its effect on runoff regime in the Jizera Mountains

NASA Astrophysics Data System (ADS)

Kulasova, Alena

2015-04-01

The Jizera Mountains in the northern Bohemia are known by its rich snow cover. Winter precipitation represents usually a half of the precipitation in the hydrological year. Gradual snow accumulation and melt depends on the course of the particular winter period, the topography of the catchments and the type of vegetation. During winter the snow depth, and especially the snow water equivalent, are affected by the changing character of the falling precipitation, air and soil temperatures and the wind. More rapid snowmelt occurs more on the slopes without forest oriented to the South, while a gradual snowmelt occurs on the locations turned to the North and in forest. Melting snow recharges groundwater and affects water quality in an important way. In case of extreme situation the snowmelt monitoring is important from the point of view of flood protection of communities and property. Therefore the immediate information on the amount of water in snow is necessary. The way to get this information is the continuous monitoring of the snow depth and snow water equivalent. In the Jizera Mountains a regular monitoring of snow cover has been going on since the end of the 19th century. In the 80s of the last century the Jizera Mountains were affected by the increased fallout of pollutants in the air. There followed a gradual dieback of the forest cover and cutting down the upper part of the ridges. In order to get data for the quantification of runoff regime changes in the changing natural environment, the Czech Hydrometeorological Institute (CHMI) founded in the upper part of the Mountains several experimental catchments. One of the activities of the employees of the experimental basis is the regular measurement of snow cover at selected sites from 1982 up to now. At the same time snow cover is being observed using snow pillows, where its mass is monitored with the help of pressure sensors. In order to improve the reliability of the continuous measurement of the snow water

Responses of Plant Community Composition to Long-term Changes in Snow Depth at the Great Basin Desert - Sierra Nevada ecotone.

NASA Astrophysics Data System (ADS)

Loik, M. E.

2015-12-01

Snowfall is the dominant hydrologic input for many high-elevation ecosystems of the western United States. Many climate models envision changes in California's Sierra Nevada snow pack characteristics, which would severely impact the storage and release of water for one of the world's largest economies. Given the importance of snowfall for future carbon cycling in high elevation ecosystems, how will these changes affect seedling recruitment, plant mortality, and community composition? To address this question, experiments utilize snow fences to manipulate snow depth and melt timing at a desert-montane ecotone in eastern California, USA. Long-term April 1 snow pack depth averages 1344 mm (1928-2015) but is highly variable from year to year. Snow fences increased equilibrium drift snow depth by 100%. Long-term changes in snow depth and melt timing are associated with s shift from shurbs to graminoids where snow depth was increased for >50 years. Changes in snow have impacted growth for only three plant species. Moreover, annual growth ring increments of the conifers Pinus jeffreyi and Pi. contorta were not equally sensitive to snow depth. There were over 8000 seedlings of the shrubs Artemisia tridentata and Purshia tridentata found in 6300 m2 in summer 2009, following about 1400 mm of winter snow and spring rain. The frequency of seedlings of A. tridentata and P. tridentata were much lower on increased-depth plots compared to ambient-depth, and reduced-depth plots. Survival of the first year was lowest for A. tridentata. Survival of seedlings from the 2008 cohort was much higher for P. tridentata than A. tridentata during the 2011-2015 drought. Results indicate complex interactions between snow depth and plant community characteristics, and that responses of plants at this ecotone may not respond similarly to increases vs. decreases in snow depth. These changes portend altered carbon uptake in this region under future snowfall scenarios.

Observations of Precipitation Size and Fall Speed Characteristics within Coexisting Rain and Wet Snow

NASA Technical Reports Server (NTRS)

Yuter, Sandra E.; Kingsmill, David E.; Nance, Louisa B.; Loeffler-Mang, Martin

2006-01-01

Ground-based measurements of particle size and fall speed distributions using a Particle Size and Velocity (PARSIVEL) disdrometer are compa red among samples obtained in mixed precipitation (rain and wet snow) and rain in the Oregon Cascade Mountains and in dry snow in the Rock y Mountains of Colorado. Coexisting rain and snow particles are distinguished using a classification method based on their size and fall sp eed properties. The bimodal distribution of the particles' joint fall speed-size characteristics at air temperatures from 0.5 to 0 C suggests that wet-snow particles quickly make a transition to rain once mel ting has progressed sufficiently. As air temperatures increase to 1.5 C, the reduction in the number of very large aggregates with a diame ter > 10 mm coincides with the appearance of rain particles larger than 6 mm. In this setting. very large raindrops appear to be the result of aggregates melting with minimal breakup rather than formation by c oalescence. In contrast to dry snow and rain, the fall speed for wet snow has a much weaker correlation between increasing size and increasing fall speed. Wet snow has a larger standard deviation of fall spee d (120%-230% relative to dry snow) for a given particle size. The ave rage fall speed for observed wet-snow particles with a diameter great er than or equal to 2.4 mm is 2 m/s with a standard deviation of 0.8 m/s. The large standard deviation is likely related to the coexistence of particles of similar physical size with different percentages of melting. These results suggest that different particle sizes are not required for aggregation since wet-snow particles of the same size can have different fall speeds. Given the large standard deviation of fa ll speeds in wet snow, the collision efficiency for wet snow is likely larger than that of dry snow. For particle sizes between 1 and 10 mm in diameter within mixed precipitation, rain constituted I % of the particles by volume within the isothermal layer

Seasonal and Elevational Variations of Black Carbon and Dust in Snow and Ice in the Solu-Khumbu, Nepal and Estimated Radiative Forcings

NASA Astrophysics Data System (ADS)

Kaspari, S.; Painter, T. H.; Gysel, M.; Skiles, M.; Schwikowski, M.

2014-12-01

Black carbon (BC) and dust deposited on snow and glacier surfaces can reduce the surface albedo, accelerate melt, and trigger albedo feedback. Assessing BC and dust concentrations in snow and ice in the Himalaya is of interest because this region borders large BC and dust sources, and seasonal snow and glacier ice in this region are an important source of water resources. Snow and ice samples were collected from crevasse profiles and snowpits at elevations between 5400 and 6400 m asl from Mera glacier located in the Solu-Khumbu region of Nepal. The samples were measured for Fe concentrations (used as a dust proxy) via ICP-MS, total impurity content gravimetrically, and BC concentrations using a Single Particle Soot Photometer (SP2). BC and Fe concentrations are substantially higher at elevations < 6000 m due to post-depositional processes including melt and sublimation and greater loading in the lower troposphere. Because the largest areal extent of snow and ice resides at elevations < 6000 m, the higher BC and dust concentrations at these elevations can reduce the snow and glacier albedo over large areas, accelerating melt, affecting glacier mass-balance and water resources, and contributing to a positive climate forcing. Radiative transfer modeling constrained by measurements at 5400 m at Mera La indicates that BC concentrations in the winter-spring snow/ice horizons are sufficient to reduce albedo by 6-10% relative to clean snow, corresponding to localized instantaneous radiative forcings of 75-120 W m-2. The other bulk impurity concentrations, when treated separately as dust, reduce albedo by 40-42% relative to clean snow and give localized instantaneous radiative forcings of 488 to 525 W m-2. Adding the BC absorption to the other impurities results in additional radiative forcings of 3 W m-2. While these results suggest that the snow albedo and radiative forcing effect of dust is considerably greater than BC, there are several sources of uncertainty.

Early Earth Felsic Crust Formation: Insights from Numerical Modelling of High-MgO Archaean Basalt Partial Melting

NASA Astrophysics Data System (ADS)

Riel, N., Jr.

2015-12-01

The Tonalite-Trondhjemite-Granodiorite series (TTGs) represent the bulk of the felsic continental crust that formed between 4.4 and 2.5 Ga and is preserved in Archaean craton (3.8-2.5 Ga). It is now recognized that the petrogenesis of TTG series derives from an hydrous mafic system at high pressure. However, the source of the early TTGs (3.5-3.2 Ga) have not been preserved and its characteristics are still debated. In this study we use thermodynamical modelling coupled with two-phase flow to investigate the products of partial melting of high-MgO primary mafic crust. Our model setup is made of a 45-km thick hydrated mafic crust and is heated above the solidus from 50 to 200°C. To explore the effects of melt-rock interactions during melt transfer (via two-phase flow), the melt composition is modelled either in thermodynamic equilibrium with the rock or in thermodynamic disequilibrium. Our modelling results show that partial melting of hydrous high-MgO metabasalt crust can produce significant volumes of felsic melt. The average composition of these melts is SiO2-rich > 62%, Mg# = 40-50, Na2O ~6%, MgO = 0.5-1% which is consistent with the composition of TTGs. The residual rock after melt segregation is composed of olivine + garnet + pyroxene which is in agreement with Archaean eclogites found in mantle xenoliths of Archaean cratons. Moreover, the depleted residual rock is denser than the mantle and is likely to be recycled in the mantle. We show that the early felsic crust with a TTGs signature could have been formed by partial melting of high-MgO hydrated metabasaltic crust, and propose that plume-related activity and/or rapid burial due to high volcanic activity are likely geodynamic conditions to generate an early felsic crust.

Influence of spring snowpack melting on thunderstorm activity in the Catalan Pyrenees

NASA Astrophysics Data System (ADS)

Pascual, R.; Callado, A.; Terradelles, E.; Téllez, B.

2009-09-01

Catalan Pyrenees, the eastern half of the Pyrenees range, is a very popular area for tourism, hiking and climbing. This sector of the range is 200 km long and, on average, 80 km wide. Its highest peaks reach 3000 m ASL and there are many summits above 2500 m ASL. Two of the main climatic characteristics of the region are the very frequent summer convective storms and the late autumn, winter and spring snow-cover. Both characteristics have normally been studied from different points of view, and weather forecasts in late spring have not normally considered the plausible relationship between them. The snowpack melting from April to June, especially rapid in May, leads to important changes on the surface energy balance since the evolution from snow-covered ground to bare soil or canopy, significantly alters the surface albedo and the turbulent, latent and sensible, heat fluxes. These modifications have a noticeable influence in developing or inhibiting thermally-induced mesoscale circulations such as upslope winds, valley breezes or plane-mountain breezes, and could condition the triggering of convection, showers and storm activity. In order to gain insight into the relationship between the spring snowpack melting and the location of thunderstorm activity, a comparison between seasonal snow-cover and thunderstorm frequency evolution (using lightning network data) for a period of 5 years has been carried out, showing a progressive transition from a non-convective to a convective precipitation regime in areas where the snowpack has melted recently Furthermore, a meso-beta scale non-hydrostatic numerical weather prediction model at a 2.5-km horizontal resolution is used to study the sensitivity of snowpack extension on the thunderstorms development over the complex orography of the Catalan Pyrenees. A spring case with thunderstorm activity restricted to snow-free areas has been selected and accurately simulated. A number of sensitivity runs with different initial snow

Snow Water Equivalent estimation based on satellite observation

NASA Astrophysics Data System (ADS)

Macchiavello, G.; Pesce, F.; Boni, G.; Gabellani, S.

2009-09-01

The availability of remotely sensed images and them analysis is a powerful tool for monitoring the extension and typology of snow cover over territory where the in situ measurements are often difficult. Information on snow are fundamental for monitoring and forecasting the available water above all in regions at mid latitudes as Mediterranean where snowmelt may cause floods. The hydrological model requirements and the daily acquisitions of MODIS (Moderate Resolution Imaging Spectroradiometer), drove, in previous research activities, to the development of a method to automatically map the snow cover from multi-spectral images. But, the major hydrological parameter related to the snow pack is the Snow Water Equivalent (SWE). This represents a direct measure of stored water in the basin. Because of it, the work was focused to the daily estimation of SWE from MODIS images. But, the complexity of this aim, based only on optical data, doesn’t find any information in literature. Since, from the spectral range of MODIS data it is not possible to extract a direct relation between spectral information and the SWE. Then a new method, respectful of the physic of the snow, was defined and developed. Reminding that the snow water equivalent is the product of the three factors as snow density, snow depth and the snow covered areas, the proposed approach works separately on each of these physical behaviors. Referring to the physical characteristic of snow, the snow density is function of the snow age, then it was studied a new method to evaluate this. Where, a module for snow age simulation from albedo information was developed. It activates an age counter updated by new snow information set to estimate snow age from zero accumulation status to the end of melting season. The height of the snow pack, can be retrieved by adopting relation between vegetation and snow depth distributions. This computes snow height distribution by the relation between snow cover fraction and the

Use of MODIS Snow-Cover Maps for Detecting Snowmelt Trends in North America

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Foster, James L.; Riggs, George A.; Robinson, David A.; Hoon-Starr, Jody A.

2012-01-01

Research has shown that the snow season in the Northern Hemisphere has been getting shorter in recent decades, consistent with documented global temperature increases. Specifically, the snow is melting earlier in the spring allowing for a longer growing season and associated land-cover changes. Here we focus on North America. Using the Moderate-Resolution Imaging Radiometer (MODIS) cloud-gap-filled standard snow-cover data product we can detect a trend toward earlier spring snowmelt in the approx 12 years since the MODIS launch. However, not all areas in North America show earlier spring snowmelt over the study period. We show examples of springtime snowmelt over North America, beginning in March 2000 and extending through the winter of 2012 for all of North America, and for various specific areas such as the Wind River Range in Wyoming and in the Catskill Mountains in New York. We also compare our approx 12-year trends with trends derived from the Rutgers Global Snow Lab snow cover climate-data record.

Canadian snow and sea ice: historical trends and projections

NASA Astrophysics Data System (ADS)

Mudryk, Lawrence R.; Derksen, Chris; Howell, Stephen; Laliberté, Fred; Thackeray, Chad; Sospedra-Alfonso, Reinel; Vionnet, Vincent; Kushner, Paul J.; Brown, Ross

2018-04-01

The Canadian Sea Ice and Snow Evolution (CanSISE) Network is a climate research network focused on developing and applying state of the art observational data to advance dynamical prediction, projections, and understanding of seasonal snow cover and sea ice in Canada and the circumpolar Arctic. Here, we present an assessment from the CanSISE Network on trends in the historical record of snow cover (fraction, water equivalent) and sea ice (area, concentration, type, and thickness) across Canada. We also assess projected changes in snow cover and sea ice likely to occur by mid-century, as simulated by the Coupled Model Intercomparison Project Phase 5 (CMIP5) suite of Earth system models. The historical datasets show that the fraction of Canadian land and marine areas covered by snow and ice is decreasing over time, with seasonal and regional variability in the trends consistent with regional differences in surface temperature trends. In particular, summer sea ice cover has decreased significantly across nearly all Canadian marine regions, and the rate of multi-year ice loss in the Beaufort Sea and Canadian Arctic Archipelago has nearly doubled over the last 8 years. The multi-model consensus over the 2020-2050 period shows reductions in fall and spring snow cover fraction and sea ice concentration of 5-10 % per decade (or 15-30 % in total), with similar reductions in winter sea ice concentration in both Hudson Bay and eastern Canadian waters. Peak pre-melt terrestrial snow water equivalent reductions of up to 10 % per decade (30 % in total) are projected across southern Canada.

Do we need a dynamic snow depth threshold when comparing hydrological models with remote sensing products in mountain catchments?

NASA Astrophysics Data System (ADS)

Engel, Michael; Bertoldi, Giacomo; Notarnicola, Claudia; Comiti, Francesco

2017-04-01

To assess the performance of simulated snow cover of hydrological models, it is common practice to compare simulated data with observed ones derived from satellite images such as MODIS. However, technical and methodological limitations such as data availability of MODIS products, its spatial resolution or difficulties in finding appropriate parameterisations of the model need to be solved previously. Another important assumption usually made is the threshold of minimum simulated snow depth, generally set to 10 mm of snow depth, to respect the MODIS detection thresholds for snow cover. But is such a constant threshold appropriate for complex alpine terrain? How important is the impact of different snow depth thresholds on the spatial and temporal distribution of the pixel-based overall accuracy (OA)? To address this aspect, we compared the snow covered area (SCA) simulated by the GEOtop 2.0 snow model to the daily composite 250 m EURAC MODIS SCA in the upper Saldur basin (61 km2, Eastern Italian Alps) during the period October 2011 - October 2013. Initially, we calibrated the snow model against snow depths and snow water equivalents at point scale, taken from measurements at different meteorological stations. We applied different snow depth thresholds (0 mm, 10 mm, 50 mm, and 100 mm) to obtain the simulated snow cover and assessed the changes in OA both in time (during the entire evaluation period, accumulation and melting season) and space (entire catchment and specific areas of topographic characteristics such as elevation, slope, aspect, landcover, and roughness). Results show remarkable spatial and temporal differences in OA with respect to different snow depth thresholds. Inaccuracies of simulated and observed SCA during the accumulation season September to November 2012 were located in areas with north-west aspect, slopes of 30° or little elevation differences at sub-pixel scale (-0.25 to 0 m). We obtained best agreements with MODIS SCA for a snow depth

Spring Melt and the Redistribution of Organochlorine Pesticides in the Sea-Ice Environment: A Comparative Study between Arctic and Antarctic Regions.

PubMed

Bigot, Marie; Hawker, Darryl W; Cropp, Roger; Muir, Derek Cg; Jensen, Bjarne; Bossi, Rossana; Bengtson Nash, Susan M

2017-08-15

Complementary sampling of air, snow, sea-ice, and seawater for a range of organochlorine pesticides (OCPs) was undertaken through the early stages of respective spring sea-ice melting at coastal sites in northeast Greenland and eastern Antarctica to investigate OCP concentrations and redistribution during this time. Mean concentrations in seawater, sea-ice and snow were generally greater at the Arctic site. For example, α-HCH was found to have the largest concentrations of all analytes in Arctic seawater and sea-ice meltwater samples (224-253 and 34.7-48.2 pg·L -1 respectively compared to 1.0-1.3 and <0.63 pg·L -1 respectively for Antarctic samples). Differences in atmospheric samples were generally not as pronounced however. Findings suggest that sea-ice OCP burdens originate from both snow and seawater. The distribution profile between seawater and sea-ice showed a compound-dependency for Arctic samples not evident with those from the Antarctic, possibly due to full submersion of sea-ice at the former. Seasonal sea-ice melt processes may alter the exchange rates of selected OCPs between air and seawater, but are not expected to reverse their direction, which fugacity modeling indicates is volatilisation in the Arctic and net deposition in the Antarctic. These predictions are consistent with the limited current observations.

A simple algorithm for identifying periods of snow accumulation on a radiometer

NASA Astrophysics Data System (ADS)

Lapo, Karl E.; Hinkelman, Laura M.; Landry, Christopher C.; Massmann, Adam K.; Lundquist, Jessica D.

2015-09-01

Downwelling solar, Qsi, and longwave, Qli, irradiances at the earth's surface are the primary energy inputs for many hydrologic processes, and uncertainties in measurements of these two terms confound evaluations of estimated irradiances and negatively impact hydrologic modeling. Observations of Qsi and Qli in cold environments are subject to conditions that create additional uncertainties not encountered in other climates, specifically the accumulation of snow on uplooking radiometers. To address this issue, we present an automated method for estimating these periods of snow accumulation. Our method is based on forest interception of snow and uses common meteorological observations. In this algorithm, snow accumulation must exceed a threshold to obscure the sensor and is only removed through scouring by wind or melting. The algorithm is evaluated at two sites representing different mountain climates: (1) Snoqualmie Pass, Washington (maritime) and (2) the Senator Beck Basin Study Area, Colorado (continental). The algorithm agrees well with time-lapse camera observations at the Washington site and with multiple measurements at the Colorado site, with 70-80% of observed snow accumulation events correctly identified. We suggest using the method for quality controlling irradiance observations in snow-dominated climates where regular, daily maintenance is not possible.

No evidence of widespread decline of snow cover on the Tibetan Plateau over 2000-2015.

PubMed

Wang, Xiaoyue; Wu, Chaoyang; Wang, Huanjiong; Gonsamo, Alemu; Liu, Zhengjia

2017-11-07

Understanding the changes in snow cover is essential for biological and hydrological processes in the Tibetan Plateau (TP) and its surrounding areas. However, the changes in snow cover phenology over the TP have not been well documented. Using Moderate Resolution Imaging Spectroradiometer (MODIS) daily snow products and the Interactive Multi-sensor Snow and Ice Mapping System (IMS) data, we reported daily cloud-free snow cover product over the Tibetan Plateau (TP) for 2000-2015. Snow cover start (SCS), melt (SCM) and duration (SCD) dates were calculated for each hydrological year, and their spatial and temporal variations were analyzed with elevation variations. Our results show no widespread decline in snow cover over the past fifteen years and the trends of snow cover phenology over the TP has high spatial heterogeneity. Later SCS, earlier SCM, and thus decreased SCD mainly occurred in the areas with elevation below 3500 m a.s.l., while regions in central and southwestern edges of the TP showed advanced SCS, delayed SCM and consequently longer SCD. The roles of temperature and precipitation on snow cover penology varied in different elevation zones, and the impact of both temperature and precipitation strengthened as elevation increases.

Enhanced hemispheric-scale snow mapping through the blending of optical and microwave satellite data

NASA Astrophysics Data System (ADS)

Armstrong, R. L.; Brodzik, M. J.; Savoie, M.; Knowles, K.

2003-04-01

Snow cover is an important variable for climate and hydrologic models due to its effects on energy and moisture budgets. Seasonal snow can cover more than 50% of the Northern Hemisphere land surface during the winter resulting in snow cover being the land surface characteristic responsible for the largest annual and interannual differences in albedo. Passive microwave satellite remote sensing can augment measurements based on visible satellite data alone because of the ability to acquire data through most clouds or during darkness as well as to provide a measure of snow depth or water equivalent. Global snow cover fluctuation can now be monitored over a 24 year period using passive microwave data (Scanning Multichannel Microwave Radiometer (SMMR) 1978-1987 and Special Sensor Microwave/Imager (SSM/I), 1987-present). Evaluation of snow extent derived from passive microwave algorithms is presented through comparison with the NOAA Northern Hemisphere weekly snow extent data. For the period 1978 to 2002, both passive microwave and visible data sets show a similar pattern of inter-annual variability, although the maximum snow extents derived from the microwave data are consistently less than those provided by the visible satellite data and the visible data typically show higher monthly variability. Decadal trends and their significance are compared for the two data types. During shallow snow conditions of the early winter season microwave data consistently indicate less snow-covered area than the visible data. This underestimate of snow extent results from the fact that shallow snow cover (less than about 5.0 cm) does not provide a scattering signal of sufficient strength to be detected by the algorithms. As the snow cover continues to build during the months of January through March, as well as throughout the melt season, agreement between the two data types continually improves. This occurs because as the snow becomes deeper and the layered structure more complex, the

Core formation in the early solar system through percolation: 4-D in-situ visualization of melt migration

NASA Astrophysics Data System (ADS)

Bromiley, G.; Berg, M.; Le Godec, Y.; Mezouar, N.; Atwood, R. C.; Phillipe, J.

2015-12-01

Although core formation was a key stage in the evolution of terrestrial planets, the physical processes which resulted in segregation of iron and silicate remain poorly understood. Formation of a silicate magma oceans provides an obvious mechanism for segregation of core-forming liquids, although recent work has strengthened arguments for a complex, multi-stage model of core formation. Extreme pressure1 and the effects of deformation2 have both been shown to promote percolation of Fe-rich melts in a solid silicate matrix, providing mechanisms for early, low temperature core-formation. However, the efficiency of these processes remains untested and we lack meaningful experimental data on resulting melt segregation velocities. Arguments regarding the efficiency of core formation through percolation of Fe-rich melts in solid silicate are based on simple, empirical models. Here, we review textural evidence from recent experiments which supports early core formation driven by deformation-aided percolation of Fe-rich melts. We then present results of novel in-situ synchrotron studies designed to provide time-resolved 3-D microimaging of percolating melt in model systems under extreme conditions. Under low strain rates characteristic of deformation-aided core formation, segregation of metallic (core-forming) melts by percolation is driven by stress gradients. This is expected to ultimately result in channelization and efficient segregation of melts noted in high-strain, low pressure experiments3. In-situ visualization also demonstrates that percolation of viscous metallic melts is surprisingly rapid. A combination of melt channelization and hydraulic fracture results in rapid, episodic melt migration, even over the limited time scale of experiments. The efficiency of this process depends strongly on the geometry of the melt network and is scaled to grain size in the matrix. We use both in-situ visualization and high-resolution ex-situ analysis to provide accurate

Multi-scale assimilation of remotely sensed snow observations for hydrologic estimation

NASA Astrophysics Data System (ADS)

Andreadis, K.; Lettenmaier, D.

2008-12-01

Data assimilation provides a framework for optimally merging model predictions and remote sensing observations of snow properties (snow cover extent, water equivalent, grain size, melt state), ideally overcoming limitations of both. A synthetic twin experiment is used to evaluate a data assimilation system that would ingest remotely sensed observations from passive microwave and visible wavelength sensors (brightness temperature and snow cover extent derived products, respectively) with the objective of estimating snow water equivalent. Two data assimilation techniques are used, the Ensemble Kalman filter and the Ensemble Multiscale Kalman filter (EnMKF). One of the challenges inherent in such a data assimilation system is the discrepancy in spatial scales between the different types of snow-related observations. The EnMKF represents the sample model error covariance with a tree that relates the system state variables at different locations and scales through a set of parent-child relationships. This provides an attractive framework to efficiently assimilate observations at different spatial scales. This study provides a first assessment of the feasibility of a system that would assimilate observations from multiple sensors (MODIS snow cover and AMSR-E brightness temperatures) and at different spatial scales for snow water equivalent estimation. The relative value of the different types of observations is examined. Additionally, the error characteristics of both model and observations are discussed.

Role of Snow Deposition of Perfluoroalkylated Substances at Coastal Livingston Island (Maritime Antarctica).

PubMed

Casal, Paulo; Zhang, Yifeng; Martin, Jonathan W; Pizarro, Mariana; Jiménez, Begoña; Dachs, Jordi

2017-08-01

Perfluoroalkyl substances (PFAS) are ubiquitous in the environment, including remote polar regions. To evaluate the role of snow deposition as an input of PFAS to Maritime Antarctica, fresh snow deposition, surface snow, streams from melted snow, coastal seawater, and plankton samples were collected over a three-month period (December 2014-February 2015) at Livingston Island. Local sources of PFASs were significant for perfluoroalkyl sulfonates (PFSAs) and C7-14 perfluoroalkyl carboxylates (PFCAs) in snow but limited to the transited areas of the research station. The concentrations of 14 ionizable PFAS (∑PFAS) in freshly deposited snow (760-3600 pg L -1 ) were 1 order of magnitude higher than those in background surface snow (82-430 pg L -1 ). ∑PFAS ranged from 94 to 420 pg L -1 in seawater and from 3.1 to 16 ng g dw -1 in plankton. Ratios of individual PFAS concentrations in freshly deposited snow relative to surface snow (C SD /C Snow ), snowmelt (C SD /C SM ), and seawater (C SD /C SW ) were close to 1 (from 0.44 to 1.4) for all perfluorooctanesulfonate (PFOS) isomers, suggesting that snowfall does not contribute significantly to PFOS in seawater. Conversely, these ratios for PFCAs ranged from 1 to 33 and were positively correlated with the number of carbons in the PFCA alkylated chain. These trends suggest that snow deposition, scavenging sea-salt aerosol bound PFAS, plays a role as a significant input of PFCAs to the Maritime Antarctica.

A distributed snow-evolution modeling system (SnowModel)

Treesearch

Glen E. Liston; Kelly Elder

2006-01-01

SnowModel is a spatially distributed snow-evolution modeling system designed for application in landscapes, climates, and conditions where snow occurs. It is an aggregation of four submodels: MicroMet defines meteorological forcing conditions, EnBal calculates surface energy exchanges, SnowPack simulates snow depth and water-equivalent evolution, and SnowTran-3D...

Snow and Ice Mask for the MODIS Aerosol Products

NASA Technical Reports Server (NTRS)

Li, Rong-Rong; Remer, Lorraine; Kaufman, Yoram J.; Mattoo, Shana; Gao, Bo-Cai; Vermote, Eric

2005-01-01

The atmospheric products have been derived operationally from multichannel imaging data collected with the Moderate Resolution Imaging SpectroRadiometers (MODIS) on board the NASA Terra and Aqua spacecrafts. Preliminary validations of the products were previously reported. Through analysis of more extensive time-series of MODIS aerosol products (Collection 4), we have found that the aerosol products over land areas are slightly contaminated by snow and ice during the springtime snow-melting season. We have developed an empirical technique using MODIS near-IR channels centered near 0.86 and 1.24 pm and a thermal emission channel near 11 pm to mask out these snow-contaminated pixels over land. Improved aerosol retrievals over land have been obtained. Sample results from application of the technique to MODIS data acquired over North America, northern Europe, and northeastern Asia are presented. The technique has been implemented into the MODIS Collection 5 operational algorithm for retrieving aerosols over land from MODIS data.

A webgis supported snow information system with long time satellite data for Turkey

NASA Astrophysics Data System (ADS)

Surer, S.; Bolat, K.; Akyurek, Z.

2012-04-01

KARBILSIS is an online platform which is developed in order to provide end-users with daily remote sensing snow products for Turkey (www.karbilsis.com). The project has been started as a research activity after an award by Ministry of Science and Technology has been granted to our company. At the first stage of our project MODIS atmospherically corrected reflectance data has been downloaded covering the period of 2000-2011 which makes more than ten years of satellite imagery for Turkey. The archived MODIS data that have been obtained from National Snow and Ice Data Center (NSIDC) is mainly MOD09GA product that includes seven spectral bands. Only the tiles which are covering Turkey have been archived namely 19&20 horizontal and 4&5 vertical ones. In order to provide scientists with a website giving the availability of analysis of snow covered area for long terms based on their area of interests, a fractional snow extent (FSE) product has been generated. For FSE product a normalized difference snow index (NDSI) based algorithm has been developed using daily land surface reflectance values (MOD09GA). In addition to MODIS data, four different Landsat images belonging to different days of snowy period (January, March, and May) have been used during algorithm development taking into account a better representation of different reflectance values of snow which highly varies depending on the accumulation and melting periods. Landsat images were used as reference images. First the Landsat images were orthorectified and mapped to a cartographic projection. Then image segmentation was applied to obtain homogeneous tiles, where the homogeneity is defined as similarity in pixel values. The mean-shift segmentation approach, where each pixel was associated with a significant mode of the joint domain density located in its neighborhood, was applied. After segmentation, the image was classified into snow and no-snow classes with Maximum Likelihood Classification Method. FSE

Variations in Below Canopy Turbulent Flux From Snow in North American Mountain Environments

NASA Astrophysics Data System (ADS)

Essery, R.; Marks, D.; Pomeroy, J.; Grangere, R.; Reba, M.; Hedstrom, N.; Link, T.; Winstral, A.

2004-12-01

Sensible and latent heat and mass fluxes from the snow surface are modulated by site canopy density and structure. Forest and shrub canopies reduce wind speeds and alter the radiation and thermal environment which will alter the below canopy energetics that control the magnitude of turbulent fluxes between the snow surface and the atmosphere. In this study eddy covariance (EC) systems were located in three experimental catchments along a mountain transect through the North American Cordillera. Within each catchment, a variety of sites representing the local range of climate, weather, and canopy conditions were selected for measurement of sensible and latent heat and mass flux from the snow surface. EC measurements were made 1) below a uniform pine canopy (2745m) in the Fraser Experimental Forest in Colorado from February through June melt-out in 2003; 2) at an open, unforested site (2100m), and below an Aspen canopy (2055m) within a small headwater catchment in the Reynolds Creek Experimental Watershed, Owyhee Mts., Idaho from October, 2003, through June melt-out, 2004; and 3) at five sites, representing a range of conditions: a) below a dense spruce forest (750m); b) a north-facing shrub-tundra slope (1383m); c) a south-facing shrub-tundra slope; d) the valley bottom between b) and c) (1363m); and e) a tundra site (1402m) in the Wolf Creek Research Basin (WCRB) in the Yukon, Canada during the 2001 and 2002 snow seasons. Summary data from all sites are presented and compared including the relative significance of sublimation losses at each site, the importance of interception losses to the snowcover mass balance, and the occurrence of condensation events. Site and weather conditions that inhibit or enhance flux from the snow surface are discussed. This research will improve snow modeling by allowing better representation of turbulent fluxes from snow in forested regions, and improved simulation of the snowcover mass balance over low deposition, high latitude sites

Clay Mineralogy and Crystallinity as a Climatic Indicator: Evidence for Both Cold and Temperate Conditions on Early Mars

NASA Technical Reports Server (NTRS)

Horgan, B.; Rutledge, A.; Rampe, E. B.

2015-01-01

Surface weathering on Earth is driven by precipitation (rain/snow melt). Here we summarize the influence of climate on minerals produced during surface weathering, based on terrestrial literature and our new laboratory analyses of weathering products from glacial analog sites. By comparison to minerals identified in likely surface environments on Mars, we evaluate the implications for early martian climate.

Validation and application of MODIS-derived clean snow albedo and dust radiative forcing

NASA Astrophysics Data System (ADS)

Rittger, K. E.; Bryant, A. C.; Seidel, F. C.; Bair, E. H.; Skiles, M.; Goodale, C. E.; Ramirez, P.; Mattmann, C. A.; Dozier, J.; Painter, T.

2012-12-01

Snow albedo is an important control on snowmelt. Though albedo evolution of aging snow can be roughly modeled from grain growth, dust and other light absorbing impurities are extrinsic and therefore must be measured. Estimates of clean snow albedo and surface radiative forcing from impurities, which can be inferred from MODIS 500 m surface reflectance products, can provide this driving data for snowmelt models. Here we use MODSCAG (MODIS snow covered area and grain size) to estimate the clean snow albedo and MODDRFS (MODIS dust radiative forcing of snow) to estimate the additional absorbed solar radiation from dust and black carbon. With its finer spatial (20 m) and spectral (10 nm) resolutions, AVIRIS provides a way to estimate the accuracy of MODIS products and understand variability of snow albedo at a finer scale that we explore though a range of topography. The AVIRIS database includes images from late in the accumulation season through the melt season when we are most interested in changes in snow albedo. In addition to the spatial validation, we employ the best estimate of albedo from MODIS in an energy balance reconstruction model to estimate the maximum snow water equivalent. MODDRFS calculates radiative forcing only in pixels that are completely snow-covered, so we spatially interpolate the product to estimate the forcing in all pixels where MODSCAG has given us estimates of clean snow albedo. Comparisons with snow pillows and courses show better agreement when the radiative forcing from absorbing impurities is included in the energy balance reconstruction.

Leaf anatomy, BVOC emission and CO2 exchange of arctic plants following snow addition and summer warming

PubMed Central

Schollert, Michelle; Kivimäenpää, Minna; Michelsen, Anders; Blok, Daan; Rinnan, Riikka

2017-01-01

Background and Aims Climate change in the Arctic is projected to increase temperature, precipitation and snowfall. This may alter leaf anatomy and gas exchange either directly or indirectly. Our aim was to assess whether increased snow depth and warming modify leaf anatomy and affect biogenic volatile organic compound (BVOC) emissions and CO2 exchange of the widespread arctic shrubs Betula nana and Empetrum nigrum ssp. hermaphroditum. Methods Measurements were conducted in a full-factorial field experiment in Central West Greenland, with passive summer warming by open-top chambers and snow addition using snow fences. Leaf anatomy was assessed using light microscopy and scanning electron microscopy. BVOC emissions were measured using a dynamic enclosure system and collection of BVOCs into adsorbent cartridges analysed by gas chromatography–mass spectrometry. Carbon dioxide exchange was measured using an infrared gas analyser. Key Results Despite a later snowmelt and reduced photosynthesis for B. nana especially, no apparent delays in the BVOC emissions were observed in response to snow addition. Only a few effects of the treatments were seen for the BVOC emissions, with sesquiterpenes being the most responsive compound group. Snow addition affected leaf anatomy by increasing the glandular trichome density in B. nana and modifying the mesophyll of E. hermaphroditum. The open-top chambers thickened the epidermis of B. nana, while increasing the glandular trichome density and reducing the palisade:spongy mesophyll ratio in E. hermaphroditum. Conclusions Leaf anatomy was modified by both treatments already after the first winter and we suggest links between leaf anatomy, CO2 exchange and BVOC emissions. While warming is likely to reduce soil moisture, melt water from a deeper snow pack alleviates water stress in the early growing season. The study emphasizes the ecological importance of changes in winter precipitation in the Arctic, which can interact with climate

Improving Understanding of Glacier Melt Contribution to High Asian River Discharge through Collaboration and Capacity Building with High Asian CHARIS Partner Institutions

NASA Astrophysics Data System (ADS)

Armstrong, Richard; Brodzik, Mary Jo; Armstrong, Betsy; Barrett, Andrew; Fetterer, Florence; Hill, Alice; Jodha Khalsa, Siri; Racoviteanu, Adina; Raup, Bruce; Rittger, Karl; Williams, Mark; Wilson, Alana; Ye, Qinghua

2017-04-01

The Contribution to High Asia Runoff from Ice & Snow (CHARIS) project uses remote sensing data combined with modeling from 2000 to the present to improve proportional estimates of melt from glaciers and seasonal snow surfaces. Based at the National Snow and Ice Data Center (NSIDC), University of Colorado, Boulder, USA, the CHARIS project objectives are twofold: 1) capacity-building efforts with CHARIS partners from eight High Asian countries to better forecast future availability and vulnerability of water resources in the region, and 2) improving our ability to systematically assess the role of glaciers and seasonal snow in the freshwater resources of High Asia. Capacity-building efforts include working with CHARIS partners from Bhutan, Nepal, India, Pakistan, Afghanistan, Kazakhstan, Kyrgyzstan and Tajikistan. Our capacity-building activities include training, data sharing, supporting fieldwork, graduate student education and infrastructure development. Because of the scarcity of in situ data in this High Asian region, we are using the wealth of available remote sensing data to characterize digital elevation, daily maps of fractional snow-cover, annual maps of glacier and permanent snow cover area and downscaled reanalysis temperature data in snow melt models to estimate the relative proportions of river runoff from glacierized and seasonally snow-covered surfaces. Current collaboration with Qinghua Ye, visiting scientist at NSIDC from the Institute of Tibetan Plateau Research, CAS, focuses on remote sensing methods to detect changes in the mountain cryosphere. Collaboration with our Asian partners supports the systematic analysis of the annual cycle of seasonal snow and glacier ice melt across the High Mountain Asia region. With our Asian partners, we have derived reciprocal benefits, learning from their specialized local knowledge and obtaining access to their in situ data. We expect that the improved understanding of runoff from snow and glacier surfaces will

Snow in Time for the Solstice

NASA Technical Reports Server (NTRS)

2004-01-01

In mid-December, the weather in eastern North America cooperated with the calendar, and a wintry blast from the Arctic delivered freezing cold air, blustery winds, and snow just in time for the Winter Solstice on December 21' the Northern Hemisphere's longest night of the year and the official start of winter. This image was captured by the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) on December 20, 2004, the day after an Arctic storm dove down into the United States, bringing snow to New England (upper right of top image); the coastal mid-Atlantic, including Washington, D.C.; and the southern Appalachian Mountains in Tennessee and North Carolina. Over the Atlantic Ocean (image right), the fierce Arctic winds were raking the clouds into rows, like a gardener getting ready to plant the seeds of winter. The detailed close-up at the bottom of this image pair shows the cloud and snow patterns around Lake Ontario, illustrating the occurrence of 'lake-effect snow.' Areas in western upstate New York often get as much as fifteen feet or more of snow each year as cold air from Canada and the Arctic sweeps down over the relatively warm waters of Lakes Ontario and Erie. Cold air plus moisture from the lakes equals heavy snow. Since the wind generally blows from west to east, it is the 'downwind' cities like Buffalo and Rochester that receive the heaping helpings of snowfall, while cities on the upwind side of the lake, such as Toronto, receive much less. Unlike storms that begin with specific low-pressure systems in the Pacific Ocean and march eastward across the Pacific Northwest, the Rockies, the Great Plains, and sometimes the East, the lake-effect snows aren't tied to a specific atmospheric disturbance. They are more a function of geography, which means that the lakes can keep fueling snow storms for as long as they remain ice-free in early winter, as well as when they begin to thaw in late winter and early spring. Image courtesy the SeaWiFS Project, NASA

Estimating Temporal Redistribution of Surface Melt Water into Upper Stratigraphy of the Juneau Icefield, Alaska

NASA Astrophysics Data System (ADS)

Wilner, J.; Smith, B.; Moore, T.; Campbell, S. W.; Slavin, B. V.; Hollander, J.; Wolf, J.

2015-12-01

The redistribution of winter accumulation from surface melt into firn or deeper layers (i.e. internal accumulation) remains a poorly understood component of glacier mass balance. Winter accumulation is usually quantified prior to summer melt, however the time window between accumulation and the onset of melt is minimal so this is not always possible. Studies which are initiated following the onset of summer melt either neglect sources of internal accumulation or attempt to estimate melt (and therefore winter accumulation uncertainty) through a variety of modeling methods. Here, we used ground-penetrating radar (GPR) repeat common midpoint (CMP) surveys with supporting common offset surveys, mass balance snow pits, and probing to estimate temporal changes in water content within the winter accumulation and firn layers of the southern Juneau Icefield, Alaska. In temperate glaciers, radio-wave velocity is primarily dependent on water content and snow or firn density. We assume density changes are temporally slow relative to water flow through the snow and firn pack, and therefore infer that changing radio-wave velocities measured by successive CMP surveys result from flux in surface melt through deeper layers. Preliminary CMP data yield radio-wave velocities of 0.15 to 0.2 m/ns in snowpack densities averaging 0.56 g cm-3, indicating partially to fully saturated snowpack (4-9% water content). Further spatial-temporal analysis of CMP surveys is being conducted. We recommend that repeat CMP surveys be conducted over a longer time frame to estimate stratigraphic water redistribution between the end of winter accumulation and maximum melt season. This information could be incorporated into surface energy balance models to further understanding of the influence of internal accumulation on glacier mass balance.

The Snow Must Go On: Ground Ice Encasement, Snow Compaction and Absence of Snow Differently Cause Soil Hypoxia, CO2 Accumulation and Tree Seedling Damage in Boreal Forest

PubMed Central

Vuosku, Jaana; Ovaskainen, Anu; Stark, Sari; Rautio, Pasi

2016-01-01

At high latitudes, the climate has warmed at twice the rate of the global average with most changes observed in autumn, winter and spring. Increasing winter temperatures and wide temperature fluctuations are leading to more frequent rain-on-snow events and freeze-thaw cycles causing snow compaction and formation of ice layers in the snowpack, thus creating ice encasement (IE). By decreasing the snowpack insulation capacity and restricting soil-atmosphere gas exchange, modification of the snow properties may lead to colder soil but also to hypoxia and accumulation of trace gases in the subnivean environment. To test the effects of these overwintering conditions changes on plant winter survival and growth, we established a snow manipulation experiment in a coniferous forest in Northern Finland with Norway spruce and Scots pine seedlings. In addition to ambient conditions and prevention of IE, we applied three snow manipulation levels: IE created by artificial rain-on-snow events, snow compaction and complete snow removal. Snow removal led to deeper soil frost during winter, but no clear effect of IE or snow compaction done in early winter was observed on soil temperature. Hypoxia and accumulation of CO2 were highest in the IE plots but, more importantly, the duration of CO2 concentration above 5% was 17 days in IE plots compared to 0 days in ambient plots. IE was the most damaging winter condition for both species, decreasing the proportion of healthy seedlings by 47% for spruce and 76% for pine compared to ambient conditions. Seedlings in all three treatments tended to grow less than seedlings in ambient conditions but only IE had a significant effect on spruce growth. Our results demonstrate a negative impact of winter climate change on boreal forest regeneration and productivity. Changing snow conditions may thus partially mitigate the positive effect of increasing growing season temperatures on boreal forest productivity. PMID:27254100

The Snow Must Go On: Ground Ice Encasement, Snow Compaction and Absence of Snow Differently Cause Soil Hypoxia, CO2 Accumulation and Tree Seedling Damage in Boreal Forest.

PubMed

Martz, Françoise; Vuosku, Jaana; Ovaskainen, Anu; Stark, Sari; Rautio, Pasi

2016-01-01

At high latitudes, the climate has warmed at twice the rate of the global average with most changes observed in autumn, winter and spring. Increasing winter temperatures and wide temperature fluctuations are leading to more frequent rain-on-snow events and freeze-thaw cycles causing snow compaction and formation of ice layers in the snowpack, thus creating ice encasement (IE). By decreasing the snowpack insulation capacity and restricting soil-atmosphere gas exchange, modification of the snow properties may lead to colder soil but also to hypoxia and accumulation of trace gases in the subnivean environment. To test the effects of these overwintering conditions changes on plant winter survival and growth, we established a snow manipulation experiment in a coniferous forest in Northern Finland with Norway spruce and Scots pine seedlings. In addition to ambient conditions and prevention of IE, we applied three snow manipulation levels: IE created by artificial rain-on-snow events, snow compaction and complete snow removal. Snow removal led to deeper soil frost during winter, but no clear effect of IE or snow compaction done in early winter was observed on soil temperature. Hypoxia and accumulation of CO2 were highest in the IE plots but, more importantly, the duration of CO2 concentration above 5% was 17 days in IE plots compared to 0 days in ambient plots. IE was the most damaging winter condition for both species, decreasing the proportion of healthy seedlings by 47% for spruce and 76% for pine compared to ambient conditions. Seedlings in all three treatments tended to grow less than seedlings in ambient conditions but only IE had a significant effect on spruce growth. Our results demonstrate a negative impact of winter climate change on boreal forest regeneration and productivity. Changing snow conditions may thus partially mitigate the positive effect of increasing growing season temperatures on boreal forest productivity.

Automatic Calibration of a Distributed Rainfall-Runoff Model, Using the Degree-Day Formulation for Snow Melting, Within DMIP2 Project

NASA Astrophysics Data System (ADS)

Frances, F.; Orozco, I.

2010-12-01

This work presents the assessment of the TETIS distributed hydrological model in mountain basins of the American and Carson rivers in Sierra Nevada (USA) at hourly time discretization, as part of the DMIP2 Project. In TETIS each cell of the spatial grid conceptualizes the water cycle using six tanks connected among them. The relationship between tanks depends on the case, although at the end in most situations, simple linear reservoirs and flow thresholds schemes are used with exceptional results (Vélez et al., 1999; Francés et al., 2002). In particular, within the snow tank, snow melting is based in this work on the simple degree-day method with spatial constant parameters. The TETIS model includes an automatic calibration module, based on the SCE-UA algorithm (Duan et al., 1992; Duan et al., 1994) and the model effective parameters are organized following a split structure, as presented by Francés and Benito (1995) and Francés et al. (2007). In this way, the calibration involves in TETIS up to 9 correction factors (CFs), which correct globally the different parameter maps instead of each parameter cell value, thus reducing drastically the number of variables to be calibrated. This strategy allows for a fast and agile modification in different hydrological processes preserving the spatial structure of each parameter map. With the snowmelt submodel, automatic model calibration was carried out in three steps, separating the calibration of rainfall-runoff and snowmelt parameters. In the first step, the automatic calibration of the CFs during the period 05/20/1990 to 07/31/1990 in the American River (without snow influence), gave a Nash-Sutcliffe Efficiency (NSE) index of 0.92. The calibration of the three degree-day parameters was done using all the SNOTEL stations in the American and Carson rivers. Finally, using previous calibrations as initial values, the complete calibration done in the Carson River for the period 10/01/1992 to 07/31/1993 gave a NSE index of

Consequences of early snowmelt in Rocky Mountains

NASA Astrophysics Data System (ADS)

Balcerak, Ernie

2013-01-01

Snow melted significantly earlier in the Rocky Mountains in 2012 than in previous years, with serious consequences for plants and animals, scientists reported at the AGU Fall Meeting. David Inouye of the University of Maryland, College Park, and the Rocky Mountain Biological Laboratory said that "the timing of winter's end is changing." He has been observing snowmelt dates and flowering of plants at a site at 2900 meters altitude. This year's snowmelt occurred 23 April, whereas the previous year, snow melted 19 June, he reported.

Effects of soot-induced snow albedo change on snowpack and hydrological cycle in western United States based on Weather Research and Forecasting chemistry and regional climate simulations

NASA Astrophysics Data System (ADS)

Qian, Yun; Gustafson, William I.; Leung, L. Ruby; Ghan, Steven J.

2009-02-01

Radiative forcing induced by soot on snow is an important anthropogenic forcing affecting the global climate. In this study we simulated the deposition of soot aerosol on snow and the resulting impact on snowpack and the hydrological cycle in the western United States. A year-long simulation was performed using the chemistry version of the Weather Research and Forecasting model (WRF-Chem) to determine the soot deposition, followed by three simulations using WRF in meteorology-only mode, with and without the soot-induced snow albedo perturbations. The chemistry simulation shows large spatial variability in soot deposition that reflects the localized emissions and the influence of the complex terrain. The soot-induced snow albedo perturbations increase the surface net solar radiation flux during late winter to early spring, increase the surface air temperature, and reduce the snow accumulation and spring snowmelt. These effects are stronger over the central Rockies and southern Alberta, where soot deposition and snowpack overlap the most. The indirect forcing of soot accelerates snowmelt and alters stream flows, including a trend toward earlier melt dates in the western United States. The soot-induced albedo reduction initiates a positive feedback process whereby dirty snow absorbs more solar radiation, heating the surface and warming the air. This warming causes reduced snow depth and fraction, which further reduces the regional surface albedo for the snow-covered regions. For a doubled snow albedo perturbation, the change to surface energy and temperature is around 50-80%; however, snowpack reduction is nonlinearly accelerated.

Proof of Concept: Development of Snow Liquid Water Content Profiler Using CS650 Reflectometers at Caribou, ME, USA.

PubMed

Pérez Díaz, Carlos L; Muñoz, Jonathan; Lakhankar, Tarendra; Khanbilvardi, Reza; Romanov, Peter

2017-03-21

The quantity of liquid water in the snowpack defines its wetness. The temporal evolution of snow wetness's plays a significant role in wet-snow avalanche prediction, meltwater release, and water availability estimations and assessments within a river basin. However, it remains a difficult task and a demanding issue to measure the snowpack's liquid water content (LWC) and its temporal evolution with conventional in situ techniques. We propose an approach based on the use of time-domain reflectometry (TDR) and CS650 soil water content reflectometers to measure the snowpack's LWC and temperature profiles. For this purpose, we created an easily-applicable, low-cost, automated, and continuous LWC profiling instrument using reflectometers at the Cooperative Remote Sensing Science and Technology Center-Snow Analysis and Field Experiment (CREST-SAFE) in Caribou, ME, USA, and tested it during the snow melt period (February-April) immediately after installation in 2014. Snow Thermal Model (SNTHERM) LWC simulations forced with CREST-SAFE meteorological data were used to evaluate the accuracy of the instrument. Results showed overall good agreement, but clearly indicated inaccuracy under wet snow conditions. For this reason, we present two (for dry and wet snow) statistical relationships between snow LWC and dielectric permittivity similar to Topp's equation for the LWC of mineral soils. These equations were validated using CREST-SAFE in situ data from winter 2015. Results displayed high agreement when compared to LWC estimates obtained using empirical formulas developed in previous studies, and minor improvement over wet snow LWC estimates. Additionally, the equations seemed to be able to capture the snowpack state (i.e., onset of melt, medium, and maximum saturation). Lastly, field test results show advantages, such as: automated, continuous measurements, the temperature profiling of the snowpack, and the possible categorization of its state. However, future work should

Climate-driven changes in grassland vegetation, snow cover, and lake water of the Qinghai Lake basin

NASA Astrophysics Data System (ADS)

Wang, Xuelu; Liang, Tiangang; Xie, Hongjie; Huang, Xiaodong; Lin, Huilong

2016-07-01

Qinghai Lake basin and the lake have undergone significant changes in recent decades. We examine MODIS-derived grassland vegetation and snow cover of the Qinghai Lake basin and their relations with climate parameters during 2001 to 2010. Results show: (1) temperature and precipitation of the Qinghai Lake basin increased while evaporation decreased; (2) most of the grassland areas improved due to increased temperature and growing season precipitation; (3) weak relations between snow cover and precipitation/vegetation; (4) a significantly negative correlation between lake area and temperature (r=-0.9, p<0.05) and (5) a positive relation between lake level (lake-level difference) and temperature (precipitation). Compared with Namco Lake (located in the inner Tibetan Plateau) where the primary water source of lake level increases was the accelerated melt of glacier/perennial snow cover in the lake basin, for the Qinghai Lake, however, it was the increased precipitation. Increased precipitation explained the improvement of vegetation cover in the Qinghai Lake basin, while accelerated melt of glacier/perennial snow cover was responsible for the degradation of vegetation cover in Namco Lake basin. These results suggest different responses to the similar warming climate: improved (degraded) ecological condition and productive capacity of the Qinghai Lake basin (Namco Lake basin).

A preliminary study on isotopic evolution of ice by a melting experiment

NASA Astrophysics Data System (ADS)

Ham, J. Y.; Lee, J.; Lee, W. S.; Han, Y.; Hur, S. D.

2016-12-01

Evidences of melted snow at surface were found on some ice cores. Melted layers may generate a significant error when paleo-temperature was retrieved from ice cores using stable water isotopes. To resolve this problem, it is necessary to understand the isotopic changes of ice and its meltwater that is made during the ice and snow melting. Isotopic fractionations between liquid water and snow have been discussed by Taylor et al. (2002) and Lee et al. (2009). The goal of this work is to understand isotopic evolution of ice and its meltwater. Melting experiments in a cold room were designed and conducted with heat source (infrared lamp) to mimic solar radiation. Melting rates were calculated in terms of specific discharge (g/min). To control melting rates, distances between ice surface and heat source were adjusted in various conditions (1 cm, 10 cm and 20 cm). The experiments were conducted by three different melting rates, 1.6 g/min, 3.5 g/min and 5.8 g/min. We used cubic ice that has 3 cm in width, length and height in dimension with 1.5 kg or 2 kg of ice used totally. The total time spent melting the whole ice was 592, 783, and 1180 minutes, respectively. Cold room temperature was range of -1 to 1°C, which removes an effect of air temperature. Meltwater samples were collected and isotopic compositions of oxygen and hydrogen were determined by a cavity ring down spectrometer (Picarro L-1120) installed at the Korea Polar Research Institute. We also analyzed bulk water and bulk ice to make the ice used in the experiments (-8.20 ‰ and -58.73 ‰ for oxygen and hydrogen isotopes, respectively). The isotopic compositions of meltwater increased linearly or to a second degree polynomial. The isotopic variations were larger in the lower melting rates, compared to the higher melting rates (0.65 of lower melting rates vs. 0.35 higher melting rates for oxygen isotope). The slope of linear regression between oxygen and hydrogen ranged 6.2, 7.3 and 6.2, which is less than

Late Noachian and early Hesperian ridge systems in the south circumpolar Dorsa Argentea Formation, Mars: Evidence for two stages of melting of an extensive late Noachian ice sheet

NASA Astrophysics Data System (ADS)

Kress, Ailish M.; Head, James W.

2015-05-01

-based glaciation. The Late Noachian and Early Hesperian ages of the ridge systems closely correspond to the ages of valley network/open basin lake systems, representing runoff, drainage and storage of liquid water in non-polar regions of the surface of Mars. Potential causes of such wet-based conditions in the DAF include: 1) top-down melting due to atmospheric warming, 2) enhanced snow and ice accumulation and raising of the melting isotherm to the base of the ice sheet, or 3) basal melting associated with intrusive volcanism (volcano-ice interactions). The early phase of melting is closely correlated in time with valley network formation and thus may be due to global atmospheric warming, while the later phase of melting may be linked to Early Hesperian global volcanism and specific volcano-ice interactions (table mountains) in the DAF. Crater ages indicate that these wet-based conditions ceased by the Late Hesperian, and that further retreat of the DAF to its present configuration occurred largely through sublimation, not melting, thus preserving the extensive ridge systems. MARSIS radar data suggest that significant areas of layered, potentially ice-rich parts of the Dorsa Argentea Formation remain today.

MODSNOW-Tool: an operational tool for daily snow cover monitoring using MODIS data

NASA Astrophysics Data System (ADS)

Gafurov, Abror; Lüdtke, Stefan; Unger-Shayesteh, Katy; Vorogushyn, Sergiy; Schöne, Tilo; Schmidt, Sebastian; Kalashnikova, Olga; Merz, Bruno

2017-04-01

Spatially distributed snow cover information in mountain areas is extremely important for water storage estimations, seasonal water availability forecasting, or the assessment of snow-related hazards (e.g. enhanced snow-melt following intensive rains, or avalanche events). Moreover, spatially distributed snow cover information can be used to calibrate and/or validate hydrological models. We present the MODSNOW-Tool - an operational monitoring tool offers a user-friendly application which can be used for catchment-based operational snow cover monitoring. The application automatically downloads and processes freely available daily Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover data. The MODSNOW-Tool uses a step-wise approach for cloud removal and delivers cloud-free snow cover maps for the selected river basins including basin specific snow cover extent statistics. The accuracy of cloud-eliminated MODSNOW snow cover maps was validated for 84 almost cloud-free days in the Karadarya river basin in Central Asia, and an average accuracy of 94 % was achieved. The MODSNOW-Tool can be used in operational and non-operational mode. In the operational mode, the tool is set up as a scheduled task on a local computer allowing automatic execution without user interaction and delivers snow cover maps on a daily basis. In the non-operational mode, the tool can be used to process historical time series of snow cover maps. The MODSNOW-Tool is currently implemented and in use at the national hydrometeorological services of four Central Asian states - Kazakhstan, Kyrgyzstan, Uzbekistan and Turkmenistan and used for seasonal water availability forecast.

On Modeling Air/Space-Borne Radar Returns in the Melting Layer

NASA Technical Reports Server (NTRS)

Liao, Liang; Meneghini, Robert

2005-01-01

The bright band is the enhanced radar echo associated with the melting of hydrometeors in stratiform rain where the melting process usually occurs below 0 C isotherm over a distance of about 500m. To simulate this radar signature, a scattering model of melting snow is proposed in which the fractional water content is prescribed as a function of the radius of a spherical mixed- phase particle consisting of air, ice and water. The model is based on the observation that melting starts at the surface of the particle and then gradually develops towards the center. To compute the scattering parameters of a non-uniform melting particle, the particle is modeled as a sphere represented by a collection of 64(exp 3) cubic cells of identical size where the probability of water at any cell is prescribed as a function of the radius. The internal field of the particle, used for deriving the effective dielectric constant, is computed by the Conjugate Gradient and Fast Fourier Transform (CGFFT) numerical methods. To make computations of the scattering parameters more efficient, a multi-layer stratified-sphere scattering model is introduced after demonstrating that the scattering parameters of the non-uniformly melting particle can be accurately reproduced by the stratified sphere. In conjunction with a melting layer model that describes the melting fractions and fall velocities of hydrometeors as a function of the distance from the 0 C isotherm, the stratified-sphere model is used to simulate the radar bright band profiles. These simulated profiles are shown to compare well with measurements from the Precipitation Radar (PR) aboard the Tropical Rainfall Measuring Mission (TRMM) satellite and a dual-wavelength airborne radar. The results suggest that the proposed model of a melting snow particle may be useful in studying the characteristics of the bright-band in particular and mixed- phase hydrometeors in general.

Iron snow in the Martian Core?

NASA Astrophysics Data System (ADS)

Davies, C. J.; Pommier, A.

2017-12-01

The decline of Mars' global magnetic field some 3.8-4.1 billion years ago is thought to reflect the demise of the dynamo that operated in its liquid core. The termination of the dynamo is intimately tied to the thermochemical evolution of the core-mantle system and therefore to the present-day physical state of the Martian core. The standard model predicts that the Martian dynamo failed because thermal convection stopped and the core remained entirely liquid until the present. Here we consider an alternative hypothesis that the Martian core crystallized from the top down in the so-called iron snow regime. We derive energy-entropy equations describing the long-timescale thermal and magnetic evolution of the core that incorporate the self-consistent formation of a snow layer that freezes out pure iron and is assumed to be on the liquidus; the iron sinks and remelts in the deeper core, acting as a possible source for magnetic field generation. Compositions are in the FeS system, with a sulfur content up to 16 wt%. The values of the different parameters (core radius, density and CMB pressure) are varied within bounds set by recent internal structure models that satisfy existing geodetic constraints (planetary mass, moment of inertia and tidal Love number). The melting curve and adiabat, CMB heat flow and thermal conductivity were also varied, based on previous experimental and numerical works. We observe that the formation of snow zones occurs for a wide range of interior and thermal structure properties and depends critically on the initial sulfur concentration. Gravitational energy release and latent heat effects arising during growth of the snow zone do not generate sufficient entropy to restart the dynamo unless the snow zone occupies a significant fraction of the core. Our results suggest that snow zones can be 1.5-2 Gyrs old, though thermal stratification of the uppermost core, not included in our model, likely delays onset. Models that match the available

The Kühtai data set: 25 years of lysimetric, snow pillow, and meteorological measurements

PubMed Central

Kirnbauer, R.; Parajka, J.; Schöber, J.; Blöschl, G.

2017-01-01

Abstract Snow measurements at the Kühtai station in Tirol, Austria, (1920 m.a.s.l.) are described. The data set includes snow water equivalent from a 10 m2 snow pillow, snow melt outflow from a 10 m2 snow lysimeter placed at the same location as the pillow, meteorological data (precipitation, incoming shortwave radiation, reflected shortwave radiation, air temperature, relative air humidity, and wind speed), and other data (snow depths, snow temperatures at seven heights) from the period October 1990 to May 2015. All data have been quality checked, and gaps in the meteorological data have been filled in. The data set is unique in that all data are available at a temporal resolution of 15 min over a period of 25 years with minimal changes in the experimental setup. The data set can therefore be used to analyze snow pack processes over a long‐time period, including their extremes and long‐term changes, in an Alpine climate. Analyses may benefit from the combined measurement of snow water equivalent, lysimeter outflow, and precipitation at a wind‐sheltered alpine site. An example use of data shows the temporal variability of daily and 1 April snow water equivalent observed at the Kühtai site. The results indicate that the snow water equivalent maximum varies between 200 and more than 500 mm w.e., but there is no statistically significant temporal trend in the period 1990–2015. PMID:28931957

How much can Greenland melt? An upper bound on mass loss from the Greenland Ice Sheet through surface melting

NASA Astrophysics Data System (ADS)

Liu, X.; Bassis, J. N.

2015-12-01

With observations showing accelerated mass loss from the Greenland Ice Sheet due to surface melt, the Greenland Ice Sheet is becoming one of the most significant contributors to sea level rise. The contribution of the Greenland Ice Sheet o sea level rise is likely to accelerate in the coming decade and centuries as atmospheric temperatures continue to rise, potentially triggering ever larger surface melt rates. However, at present considerable uncertainty remains in projecting the contribution to sea level of the Greenland Ice Sheet both due to uncertainty in atmospheric forcing and the ice sheet response to climate forcing. Here we seek an upper bound on the contribution of surface melt from the Greenland to sea level rise in the coming century using a surface energy balance model coupled to an englacial model. We use IPCC Representative Concentration Pathways (RCP8.5, RCP6, RCP4.5, RCP2.6) climate scenarios from an ensemble of global climate models in our simulations to project the maximum rate of ice volume loss and related sea-level rise associated with surface melting. To estimate the upper bound, we assume the Greenland Ice Sheet is perpetually covered in thick clouds, which maximize longwave radiation to the ice sheet. We further assume that deposition of black carbon darkens the ice substantially turning it nearly black, substantially reducing its albedo. Although assuming that all melt water not stored in the snow/firn is instantaneously transported off the ice sheet increases mass loss in the short term, refreezing of retained water warms the ice and may lead to more melt in the long term. Hence we examine both assumptions and use the scenario that leads to the most surface melt by 2100. Preliminary models results suggest that under the most aggressive climate forcing, surface melt from the Greenland Ice Sheet contributes ~1 m to sea level by the year 2100. This is a significant contribution and ignores dynamic effects. We also examined a lower bound

Key characteristics of the Fe-snow regime in Ganymede's core

NASA Astrophysics Data System (ADS)

Rückriemen, Tina; Breuer, Doris; Spohn, Tilman

2014-05-01

Ganymede shows signs of an internally produced dipolar magnetic field (|Bdip|≡719 nT) [1]. For small planetary bodies such as Ganymede the Fe-snow regime, i.e. the top-down solidification of iron, has been suggested to play an important role in the core cooling history [2,3]. In that regime, iron crystals form first at the core-mantle boundary (CMB) due to shallow or negative slopes of the melting temperature [2,3]. The solid iron particles are heavier than the surrounding Fe-FeS fluid, i.e. a snow zone forms, settle to deeper core regions, where the core temperature is higher than the melting temperature, and remelt again. As a consequence, a stable chemical gradient in the Fe-FeS fluid arises within the snow zone. We speculate this style of convection via sedimentation to be small scale, therefore it lacks an important criterion necessary for dynamo action [4]. Below this zone, whose thickness increases with time, the process of remelting of iron creates a gravitationally unstable situation. We propose that this could be the driving mechanism for a potential dynamo. However, dynamo action would be restricted to the time period the snow zone needs to grow across the core. With a 1D thermo-chemical evolution model, we investigate key characteristics of the Fe-snow regime within Ganymede's core: the compositional density gradient of the fluid Fe-FeS within the snow zone and the time period necessary to grow the snow zone across the core. Additionally, we determine the dipolar magnetic field strength associated with a dynamo in Ganymede's deeper fluid core. We vary important input paramters such as the initial sulfur concentration (7-19 wt.%), the core heat flux (2-6 mW/m2) and the thermal conductivity (20-60 W/mK) with the nominal model being: xs=10 wt.%, qcmb=4 mW/m2, kc=32 W/mK. We find, that heat fluxes higher than 6 or 22 mW/m2 are required for double-diffusive or overturning convection to overcome the compositional density gradient within the snow zone

Simulation of Surface Energy Fluxes and Snow Interception Using a Higher Order Closure Multi-Layer Soil-Vegetation-Atmospheric Model: The Effect of Canopy Shape and Structure

NASA Astrophysics Data System (ADS)

McGowan, L. E.; Dahlke, H. E.; Paw U, K. T.

2015-12-01

Snow cover is a critical driver of the Earth's surface energy budget, climate change, and water resources. Variations in snow cover not only affect the energy budget of the land surface but also represent a major water supply source. In California, US estimates of snow depth, extent, and melt in the Sierra Nevada are critical to estimating the amount of water available for both California agriculture and urban users. However, accurate estimates of snow cover and snow melt processes in forested area still remain a challenge. Canopy structure influences the vertical and spatiotemporal distribution of snow, and therefore ultimately determines the degree and extent by which snow alters both the surface energy balance and water availability in forested regions. In this study we use the Advanced Canopy-Atmosphere-Soil algorithm (ACASA), a multi-layer soil-vegetation-atmosphere numerical model, to simulate the effect of different snow-covered canopy structures on the energy budget, and temperature and other scalar profiles within different forest types in the Sierra Nevada, California. ACASA incorporates a higher order turbulence closure scheme which allows the detailed simulation of turbulent fluxes of heat and water vapor as well as the CO2 exchange of several layers within the canopy. As such ACASA can capture the counter gradient fluxes within canopies that may occur frequently, but are typically unaccounted for, in most snow hydrology models. Six different canopy types were modeled ranging from coniferous forests (e.g. most biomass near the ground) to top-heavy (e.g. most biomass near the top of the crown) deciduous forests to multi-layered forest canopies (e.g. mixture of young and mature trees). Preliminary results indicate that the canopy shape and structure associated with different canopy types fundamentally influence the vertical scalar profiles (including those of temperature, moisture, and wind speed) in the canopy and thus alter the interception and snow

Causes of Glacier Melt Extremes in the Alps Since 1949

NASA Astrophysics Data System (ADS)

Thibert, E.; Dkengne Sielenou, P.; Vionnet, V.; Eckert, N.; Vincent, C.

2018-01-01

Recent record-breaking glacier melt values are attributable to peculiar extreme events and long-term warming trends that shift averages upward. Analyzing one of the world's longest mass balance series with extreme value statistics, we show that detrending melt anomalies makes it possible to disentangle these effects, leading to a fairer evaluation of the return period of melt extreme values such as 2003, and to characterize them by a more realistic bounded behavior. Using surface energy balance simulations, we show that three independent drivers control melt: global radiation, latent heat, and the amount of snow at the beginning of the melting season. Extremes are governed by large deviations in global radiation combined with sensible heat. Long-term trends are driven by the lengthening of melt duration due to earlier and longer-lasting melting of ice along with melt intensification caused by trends in long-wave irradiance and latent heat due to higher air moisture.

Toward Surface Mass Balance Modeling over Antarctic Peninsula with Improved Snow/Ice Physics within WRF

NASA Astrophysics Data System (ADS)

Villamil-Otero, G.; Zhang, J.; Yao, Y.

2017-12-01

The Antarctic Peninsula (AP) has long been the focus of climate change studies due to its rapid environmental changes such as significantly increased glacier melt and retreat, and ice-shelf break-up. Progress has been continuously made in the use of regional modeling to simulate surface mass changes over ice sheets. Most efforts, however, focus on the ice sheets of Greenland with considerable fewer studies in Antarctica. In this study the Weather Research and Forecasting (WRF) model, which has been applied to the Antarctic region for weather modeling, is adopted to capture the past and future surface mass balance changes over AP. In order to enhance the capabilities of WRF model simulating surface mass balance over the ice surface, we implement various ice and snow processes within the WRF and develop a new WRF suite (WRF-Ice). The WRF-Ice includes a thermodynamic ice sheet model that improves the representation of internal melting and refreezing processes and the thermodynamic effects over ice sheet. WRF-Ice also couples a thermodynamic sea ice model to improve the simulation of surface temperature and fluxes over sea ice. Lastly, complex snow processes are also taken into consideration including the implementation of a snowdrift model that takes into account the redistribution of blowing snow as well as the thermodynamic impact of drifting snow sublimation on the lower atmospheric boundary layer. Intensive testing of these ice and snow processes are performed to assess the capability of WRF-Ice in simulating the surface mass balance changes over AP.

Observation of melt onset on multiyear Arctic sea ice using the ERS 1 synthetic aperture radar

NASA Technical Reports Server (NTRS)

Winebrenner, D. P.; Nelson, E. D.; Colony, R.; West, R. D.

1994-01-01

We present nearly coincident observations of backscattering from the Earth Remote-Sensing Satellite (ERS) 1 synthetic aperture radar (SAR) and of near-surface temperature from six drifting buoys in the Beaufort Sea, showing that the onset of melting in snow on multiyear sea ice is clearly detectable in the SAR data. Melt onset is marked by a clean, steep decrease in the backscattering cross section of multiyear ice at 5.3 GHz and VV polarization. We investigate the scattering physics responsible for the signature change and find that the cross section decrease is due solely to the appearance of liquid water in the snow cover overlying the ice. A thin layer of moist snow is sufficient to cause the observed decrease. We present a prototype algorithm to estimate the date of melt onset using the ERS 1 SAR and apply the algorithm first to the SAR data for which we have corresponding buoy temperatures. The melt onset dates estimated by the SAR algorithm agree with those obtained independently from the temperature data to within 4 days or less, with the exception of one case in which temperatures oscillated about 0 C for several weeks. Lastly, we apply the algorithm to the entire ERS 1 SAR data record acquired by the Alaska SAR Facility for the Beaufort Sea north of 73 deg N during the spring of 1992, to produce a map of the dates of melt onset over an area roughly 1000 km on a side. The progression of melt onset is primarily poleward but shows a weak meridional dependence at latitudes of approximately 76 deg-77 deg N. Melting begins in the southern part of the study region on June 13 and by June 20 has progressed to the northermost part of the region.

Estimating snow depth of alpine snowpack via airborne multifrequency passive microwave radiance observations: Colorado, USA

NASA Astrophysics Data System (ADS)

Kim, R. S.; Durand, M. T.; Li, D.; Baldo, E.; Margulis, S. A.; Dumont, M.; Morin, S.

2017-12-01

This paper presents a newly-proposed snow depth retrieval approach for mountainous deep snow using airborne multifrequency passive microwave (PM) radiance observation. In contrast to previous snow depth estimations using satellite PM radiance assimilation, the newly-proposed method utilized single flight observation and deployed the snow hydrologic models. This method is promising since the satellite-based retrieval methods have difficulties to estimate snow depth due to their coarse resolution and computational effort. Indeed, this approach consists of particle filter using combinations of multiple PM frequencies and multi-layer snow physical model (i.e., Crocus) to resolve melt-refreeze crusts. The method was performed over NASA Cold Land Processes Experiment (CLPX) area in Colorado during 2002 and 2003. Results showed that there was a significant improvement over the prior snow depth estimates and the capability to reduce the prior snow depth biases. When applying our snow depth retrieval algorithm using a combination of four PM frequencies (10.7,18.7, 37.0 and 89.0 GHz), the RMSE values were reduced by 48 % at the snow depth transects sites where forest density was less than 5% despite deep snow conditions. This method displayed a sensitivity to different combinations of frequencies, model stratigraphy (i.e. different number of layering scheme for snow physical model) and estimation methods (particle filter and Kalman filter). The prior RMSE values at the forest-covered areas were reduced by 37 - 42 % even in the presence of forest cover.

Rain-on-snow Events in Southwestern British Columbia: A Long-term Analysis of Meteorological Conditions and Snowpack Response

NASA Astrophysics Data System (ADS)

Trubilowicz, J. W.; Moore, D.

2015-12-01

Snowpack dynamics and runoff generation in coastal mountain regions are complicated by rain-on-snow (ROS) events. During major ROS events associated with warm, moist air and strong winds, turbulent heat fluxes can produce substantial melt to supplement rainfall, but previous studies suggest this may not be true for smaller, more frequent events. The internal temperature and water content of the snowpack are also expected to influence runoff generation during ROS events: a cold snowpack with no liquid water content will have the ability to store significant amounts of rainfall, whereas a 'ripe' snowpack may begin to melt and generate outflow with little rain input. However, it is not well understood how antecedent snowpack conditions and energy fluxes differ between ROS events that cause large runoff events and those that do not, in large part because major flood-producing ROS events occur infrequently, and thus are often not sampled during short-term research projects. To generate greater understanding of runoff generation over the spectrum of ROS magnitudes and frequencies, we analyzed data from Automated Snow Pillow (ASP) sites, which record hourly air temperature, precipitation and snowpack water equivalent and offer up to several decades of data at each site. We supplemented the ASP data with output from the North American Regional Reanalysis (NARR) product to support point scale snow modeling for 335 ROS event records from six ASP sites in southwestern BC from 2003 to 2013. Our analysis reconstructed the weather conditions, surface energy exchanges, internal mass and energy states of the snowpack, and generation of snow melt and water available for runoff (WAR) for each ROS event. Results indicate that WAR generation during large events is largely independent of the snowpack conditions, but for smaller events, the antecedent snow conditions play a significant role in either damping or enhancing WAR generation.

Multi-resolution Changes in the Spatial Extent of Perennial Arctic Alpine Snow and Ice Fields with Potential Archaeological Significance in the Central Brooks Range, Alaska

NASA Astrophysics Data System (ADS)

Tedesche, M. E.; Freeburg, A. K.; Rasic, J. T.; Ciancibelli, C.; Fassnacht, S. R.

2015-12-01

Perennial snow and ice fields could be an important archaeological and paleoecological resource for Gates of the Arctic National Park and Preserve in the central Brooks Range mountains of Arctic Alaska. These features may have cultural significance, as prehistoric artifacts may be frozen within the snow and ice. Globally significant discoveries have been made recently as ancient artifacts and animal dung have been found in melting alpine snow and ice patches in the Southern Yukon and Northwest Territories in Canada, the Wrangell mountains in Alaska, as well as in other areas. These sites are melting rapidly, which results in quick decay of biological materials. The summer of 2015 saw historic lows in year round snow cover extent for most of Alaska. Twenty mid to high elevation sites, including eighteen perennial snow and ice fields, and two glaciers, were surveyed in July 2015 to quantify their areal extent. This survey was accomplished by using both low flying aircraft (helicopter), as well as with on the ground in-situ (by foot) measurements. By helicopter, visual surveys were conducted within tens of meters of the surface. Sites visited by foot were surveyed for extent of snow and ice coverage, melt water hydrologic parameters and chemistry, and initial estimates of depths and delineations between snow, firn, and ice. Imagery from both historic aerial photography and from 5m resolution IKONOS satellite information were correlated with the field data. Initial results indicate good agreement in permanent snow and ice cover between field surveyed data and the 1985 to 2011 Landsat imagery-based Northwest Alaska snow persistence map created by Macander et al. (2015). The most deviation between the Macander et al. model and the field surveyed results typically occurred as an overestimate of perennial extent on the steepest aspects. These differences are either a function of image classification or due to accelerated ablation rates in perennial snow and ice coverage

Improved Snow Mapping Accuracy with Revised MODIS Snow Algorithm

NASA Technical Reports Server (NTRS)

Riggs, George; Hall, Dorothy K.

2012-01-01

The MODIS snow cover products have been used in over 225 published studies. From those reports, and our ongoing analysis, we have learned about the accuracy and errors in the snow products. Revisions have been made in the algorithms to improve the accuracy of snow cover detection in Collection 6 (C6), the next processing/reprocessing of the MODIS data archive planned to start in September 2012. Our objective in the C6 revision of the MODIS snow-cover algorithms and products is to maximize the capability to detect snow cover while minimizing snow detection errors of commission and omission. While the basic snow detection algorithm will not change, new screens will be applied to alleviate snow detection commission and omission errors, and only the fractional snow cover (FSC) will be output (the binary snow cover area (SCA) map will no longer be included).

Temporal trend of the snow-related variables in Sierra Nevada in the last years: An analysis combining Earth Observation and hydrological modelling

NASA Astrophysics Data System (ADS)

Pérez-Luque, Antonio J.; Herrero, Javier; Bonet, Francisco J.; Pérez-Pérez, Ramón

2016-04-01

Climate change is causing declines in snow-cover extent and duration in European mountain ranges. This is especially important in Mediterranean mountain ranges where the observed trends towards precipitation and higher temperatures can provoke problems of water scarcity. In this work, we analyzed temporal trends (2000 to 2014) of snow-related variables obtained from satellite and modelling data in Sierra Nevada, a Mediterranean high-mountain range located in Southern Spain, at 37°N. Snow cover indicators (snow-cover duration, snow-cover onset dates and snow-cover melting dates) were obtained by processing images of MOD10A2 MODIS product using an automated workflow. Precipitation data were obtained using WiMMed, a complete and fully distributed hydrological model that is used to map the annual rainfall and snowfall with a resolution of 30x30 m over the whole study area. It uses expert algorithms to interpolate precipitation and temperature at an hourly scale, and simulates partition of precipitation into snowfall with several methods. For each snow-related indicator (snow-covers and snowfall), a trend analysis was applied at the MODIS pixel scale during the study period (2000-2014). We applied Mann-Kendall test and Theil-Sen slope estimation in each of the pixels comprising Sierra Nevada. The trend analysis assesses the intensity, magnitude and degree of statistical significance during the period analysed. The spatial pattern of these trends was explored according to elevation ranges. Finally, we explored the relationship between trends of snow-cover related indicators and precipitation trends. Our results show that snow-cover has undergone significant changes in the last 14 years. 80 % of the pixels covering Sierra Nevada showed a negative trend in the duration of snow-cover. We also observed a delay in the snow-cover onset date (68.03 % pixels showing a positive trend in the snow-cover onset date) and an advance in the melt date (80.72 % of pixels followed a

Development of a land surface model with coupled snow and frozen soil physics

NASA Astrophysics Data System (ADS)

Wang, Lei; Zhou, Jing; Qi, Jia; Sun, Litao; Yang, Kun; Tian, Lide; Lin, Yanluan; Liu, Wenbin; Shrestha, Maheswor; Xue, Yongkang; Koike, Toshio; Ma, Yaoming; Li, Xiuping; Chen, Yingying; Chen, Deliang; Piao, Shilong; Lu, Hui

2017-06-01

Snow and frozen soil are important factors that influence terrestrial water and energy balances through snowpack accumulation and melt and soil freeze-thaw. In this study, a new land surface model (LSM) with coupled snow and frozen soil physics was developed based on a hydrologically improved LSM (HydroSiB2). First, an energy-balance-based three-layer snow model was incorporated into HydroSiB2 (hereafter HydroSiB2-S) to provide an improved description of the internal processes of the snow pack. Second, a universal and simplified soil model was coupled with HydroSiB2-S to depict soil water freezing and thawing (hereafter HydroSiB2-SF). In order to avoid the instability caused by the uncertainty in estimating water phase changes, enthalpy was adopted as a prognostic variable instead of snow/soil temperature in the energy balance equation of the snow/frozen soil module. The newly developed models were then carefully evaluated at two typical sites of the Tibetan Plateau (TP) (one snow covered and the other snow free, both with underlying frozen soil). At the snow-covered site in northeastern TP (DY), HydroSiB2-SF demonstrated significant improvements over HydroSiB2-F (same as HydroSiB2-SF but using the original single-layer snow module of HydroSiB2), showing the importance of snow internal processes in three-layer snow parameterization. At the snow-free site in southwestern TP (Ngari), HydroSiB2-SF reasonably simulated soil water phase changes while HydroSiB2-S did not, indicating the crucial role of frozen soil parameterization in depicting the soil thermal and water dynamics. Finally, HydroSiB2-SF proved to be capable of simulating upward moisture fluxes toward the freezing front from the underlying soil layers in winter.

Are We Biologically Safe with Snow Precipitation? A Case Study in Beijing

PubMed Central

Shen, Fangxia; Yao, Maosheng

2013-01-01

In this study, the bacterial and fungal abundances, diversities, conductance levels as well as total organic carbon (TOC) were investigated in the snow samples collected from five different snow occurrences in Beijing between January and March, 2010. The collected snow samples were melted and cultured at three different temperatures (4, 26 and 37°C). The culturable bacterial concentrations were manually counted and the resulting colony forming units (CFUs) at 26°C were further studied using V3 region of 16 S rRNA gene-targeted polymerase chain reaction -denaturing gradient gel electrophoresis (PCR-DGGE). The clone library was constructed after the liquid culturing of snow samples at 26°C. And microscopic method was employed to investigate the fungal diversity in the samples. In addition, outdoor air samples were also collected using mixed cellulose ester (MCE) filters and compared with snow samples with respect to described characteristics. The results revealed that snow samples had bacterial concentrations as much as 16000 CFU/ml for those cultured at 26°C, and the conductance levels ranged from 5.6×10−6 to 2.4×10−5 S. PCR-DGGE, sequencing and microscopic analysis revealed remarkable bacterial and fungal diversity differences between the snow samples and the outdoor air samples. In addition, DGGE banding profiles for the snow samples collected were also shown distinctly different from one another. Absent from the outdoor air, certain human, plant, and insect fungal pathogens were found in the snow samples. By calculation, culturable bacteria accounted for an average of 3.38% (±1.96%) of TOC for the snow samples, and 0.01% for that of outdoor air samples. The results here suggest that snow precipitations are important sources of fungal pathogens and ice nucleators, thus could affect local climate, human health and agriculture security. PMID:23762327

Are we biologically safe with snow precipitation? A case study in beijing.

PubMed

Shen, Fangxia; Yao, Maosheng

2013-01-01

In this study, the bacterial and fungal abundances, diversities, conductance levels as well as total organic carbon (TOC) were investigated in the snow samples collected from five different snow occurrences in Beijing between January and March, 2010. The collected snow samples were melted and cultured at three different temperatures (4, 26 and 37°C). The culturable bacterial concentrations were manually counted and the resulting colony forming units (CFUs) at 26°C were further studied using V3 region of 16 S rRNA gene-targeted polymerase chain reaction -denaturing gradient gel electrophoresis (PCR-DGGE). The clone library was constructed after the liquid culturing of snow samples at 26°C. And microscopic method was employed to investigate the fungal diversity in the samples. In addition, outdoor air samples were also collected using mixed cellulose ester (MCE) filters and compared with snow samples with respect to described characteristics. The results revealed that snow samples had bacterial concentrations as much as 16000 CFU/ml for those cultured at 26°C, and the conductance levels ranged from 5.6×10(-6) to 2.4×10(-5) S. PCR-DGGE, sequencing and microscopic analysis revealed remarkable bacterial and fungal diversity differences between the snow samples and the outdoor air samples. In addition, DGGE banding profiles for the snow samples collected were also shown distinctly different from one another. Absent from the outdoor air, certain human, plant, and insect fungal pathogens were found in the snow samples. By calculation, culturable bacteria accounted for an average of 3.38% (±1.96%) of TOC for the snow samples, and 0.01% for that of outdoor air samples. The results here suggest that snow precipitations are important sources of fungal pathogens and ice nucleators, thus could affect local climate, human health and agriculture security.

Modeling and measuring snow for assessing climate change impacts in Glacier National Park, Montana

USGS Publications Warehouse

Fagre, Daniel B.; Selkowitz, David J.; Reardon, Blase; Holzer, Karen; Mckeon, Lisa L.

2002-01-01

A 12-year program of global change research at Glacier National Park by the U.S. Geological Survey and numerous collaborators has made progress in quantifying the role of snow as a driver of mountain ecosystem processes. Spatially extensive snow surveys during the annual accumulation/ablation cycle covered two mountain watersheds and approximately 1,000 km2 . Over 7,000 snow depth and snow water equivalent (SWE) measurements have been made through spring 2002. These augment two SNOTEL sites, 9 NRCS snow courses, and approximately 150 snow pit analyses. Snow data were used to establish spatially-explicit interannual variability in snowpack SWE. East of the Continental Divide, snowpack SWE was lower but also less variable than west of the Divide. Analysis of snowpacks suggest downward trends in SWE, a reduction in snow cover duration, and earlier melt-out dates during the past 52 years. Concurrently, high elevation forests and treelines have responded with increased growth. However, the 80 year record of snow from 3 NRCS snow courses reflects a strong influence from the Pacific Decadal Oscillation, resulting in 20-30 year phases of greater or lesser mean SWE. Coupled with the fine-resolution spatial snow data from the two watersheds, the ecological consequences of changes in snowpack can be empirically assessed at a habitat patch scale. This will be required because snow distribution models have had varied success in simulating snowpack accumulation/ablation dynamics in these mountain watersheds, ranging from R2=0.38 for individual south-facing forested snow survey routes to R2=0.95 when aggregated to the watershed scale. Key ecological responses to snowpack changes occur below the watershed scale, such as snow-mediated expansion of forest into subalpine meadows, making continued spatially-explicit snow surveys a necessity. 

Impact melting of frozen oceans on the early Earth: implications for the origin of life

NASA Technical Reports Server (NTRS)

Bada, J. L.; Bigham, C.; Miller, S. L.

1994-01-01

Without sufficient greenhouse gases in the atmosphere, the early Earth would have become a permanently frozen planet because the young Sun was less luminous than it is today. Several resolutions to this faint young Sun-frozen Earth paradox have been proposed, with an atmosphere rich in CO2 being the one generally favored. However, these models assume that there were no mechanisms for melting a once frozen ocean. Here we show that bolide impacts between about 3.6 and 4.0 billion years ago could have episodically melted an ice-covered early ocean. Thaw-freeze cycles associated with bolide impacts could have been important for the initiation of abiotic reactions that gave rise to the first living organisms.

Annual Greenland Accumulation Rates (2009-2012) from Airborne Snow Radar

NASA Technical Reports Server (NTRS)

Koenig, Lora S.; Ivanoff, Alvaro; Alexander, Patrick M.; MacGregor, Joseph A.; Fettweis, Xavier; Panzer, Ben; Paden, John D.; Forster, Richard R.; Das, Indrani; McConnell, Joseph R.;