Snow hydrology in a general circulation model

NASA Technical Reports Server (NTRS)

Marshall, Susan; Roads, John O.; Glatzmaier, Gary

1994-01-01

A snow hydrology has been implemented in an atmospheric general circulation model (GCM). The snow hydrology consists of parameterizations of snowfall and snow cover fraction, a prognostic calculation of snow temperature, and a model of the snow mass and hydrologic budgets. Previously, only snow albedo had been included by a specified snow line. A 3-year GCM simulation with this now more complete surface hydrology is compared to a previous GCM control run with the specified snow line, as well as with observations. In particular, the authors discuss comparisons of the atmospheric and surface hydrologic budgets and the surface energy budget for U.S. and Canadian areas. The new snow hydrology changes the annual cycle of the surface moisture and energy budgets in the model. There is a noticeable shift in the runoff maximum from winter in the control run to spring in the snow hydrology run. A substantial amount of GCM winter precipitation is now stored in the seasonal snowpack. Snow cover also acts as an important insulating layer between the atmosphere and the ground. Wintertime soil temperatures are much higher in the snow hydrology experiment than in the control experiment. Seasonal snow cover is important for dampening large fluctuations in GCM continental skin temperature during the Northern Hemisphere winter. Snow depths and snow extent show good agreement with observations over North America. The geographic distribution of maximum depths is not as well simulated by the model due, in part, to the coarse resolution of the model. The patterns of runoff are qualitatively and quantitatively similar to observed patterns of streamflow averaged over the continental United States. The seasonal cycles of precipitation and evaporation are also reasonably well simulated by the model, although their magnitudes are larger than is observed. This is due, in part, to a cold bias in this model, which results in a dry model atmosphere and enhances the hydrologic cycle everywhere.

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.

Meteorological and snow distribution data in the Izas Experimental Catchment (Spanish Pyrenees) from 2011 to 2017

NASA Astrophysics Data System (ADS)

Revuelto, Jesús; Azorin-Molina, Cesar; Alonso-González, Esteban; Sanmiguel-Vallelado, Alba; Navarro-Serrano, Francisco; Rico, Ibai; López-Moreno, Juan Ignacio

2017-12-01

This work describes the snow and meteorological data set available for the Izas Experimental Catchment in the Central Spanish Pyrenees, from the 2011 to 2017 snow seasons. The experimental site is located on the southern side of the Pyrenees between 2000 and 2300 m above sea level, covering an area of 55 ha. The site is a good example of a subalpine environment in which the evolution of snow accumulation and melt are of major importance in many mountain processes. The climatic data set consists of (i) continuous meteorological variables acquired from an automatic weather station (AWS), (ii) detailed information on snow depth distribution collected with a terrestrial laser scanner (TLS, lidar technology) for certain dates across the snow season (between three and six TLS surveys per snow season) and (iii) time-lapse images showing the evolution of the snow-covered area (SCA). The meteorological variables acquired at the AWS are precipitation, air temperature, incoming and reflected solar radiation, infrared surface temperature, relative humidity, wind speed and direction, atmospheric air pressure, surface temperature (snow or soil surface), and soil temperature; all were taken at 10 min intervals. Snow depth distribution was measured during 23 field campaigns using a TLS, and daily information on the SCA was also retrieved from time-lapse photography. The data set (https://doi.org/10.5281/zenodo.848277) is valuable since it provides high-spatial-resolution information on the snow depth and snow cover, which is particularly useful when combined with meteorological variables to simulate snow energy and mass balance. This information has already been analyzed in various scientific studies on snow pack dynamics and its interaction with the local climatology or topographical characteristics. However, the database generated has great potential for understanding other environmental processes from a hydrometeorological or ecological perspective in which snow dynamics play a determinant role.

Evaluating the performance of coupled snow-soil models in SURFEXv8 to simulate the permafrost thermal regime at a high Arctic site

NASA Astrophysics Data System (ADS)

Barrere, Mathieu; Domine, Florent; Decharme, Bertrand; Morin, Samuel; Vionnet, Vincent; Lafaysse, Matthieu

2017-09-01

Climate change projections still suffer from a limited representation of the permafrost-carbon feedback. Predicting the response of permafrost temperature to climate change requires accurate simulations of Arctic snow and soil properties. This study assesses the capacity of the coupled land surface and snow models ISBA-Crocus and ISBA-ES to simulate snow and soil properties at Bylot Island, a high Arctic site. Field measurements complemented with ERA-Interim reanalyses were used to drive the models and to evaluate simulation outputs. Snow height, density, temperature, thermal conductivity and thermal insulance are examined to determine the critical variables involved in the soil and snow thermal regime. Simulated soil properties are compared to measurements of thermal conductivity, temperature and water content. The simulated snow density profiles are unrealistic, which is most likely caused by the lack of representation in snow models of the upward water vapor fluxes generated by the strong temperature gradients within the snowpack. The resulting vertical profiles of thermal conductivity are inverted compared to observations, with high simulated values at the bottom of the snowpack. Still, ISBA-Crocus manages to successfully simulate the soil temperature in winter. Results are satisfactory in summer, but the temperature of the top soil could be better reproduced by adequately representing surface organic layers, i.e., mosses and litter, and in particular their water retention capacity. Transition periods (soil freezing and thawing) are the least well reproduced because the high basal snow thermal conductivity induces an excessively rapid heat transfer between the soil and the snow in simulations. Hence, global climate models should carefully consider Arctic snow thermal properties, and especially the thermal conductivity of the basal snow layer, to perform accurate predictions of the permafrost evolution under climate change.

Estimate of temperature change due to ice and snow accretion in the boreal forest regions

NASA Astrophysics Data System (ADS)

Sugiura, K.; Nagai, S.; Suzuki, R.; Eicken, H.; Maximov, T. C.

2016-12-01

Previous research has demonstrated that there is a wide difference between the surface albedo in winter/spring in snow-covered forest regions in various global climate models. If the forest is covered with snow, the surface albedo would increase. In this study, we carried out field observations to monitor the frequency of ice and snow accretion in the boreal forest regions. The time-lapse digital camera was set up on each side of the observation towers at the site located to the north of Fairbanks (USA) and at the site located to the north of Yakutsk (Russia). It was confirmed that both forests were not necessarily covered with snow without a break from the start of continuous snow cover until the end. In addition, the boreal forest at the Yakutsk site is covered with snow in comparison with the boreal forest at the Fairbanks site for a long term such as for about five month. Using a one-dimensional mathematics model about the energy flow including atmospheric multiple scattering, we estimated temperature change due to ice and snow accretion in the boreal forest regions. The result show that the mean surface temperature rises approximately 0.5 [oC] when the boreal forest is not covered with snow. In this presentation, we discuss the snow albedo parameterization in the boreal forest regions and the one-dimensional mathematics model to provide a basis for a better understanding of the role of snow in the climate system.

Wind-driven snow conditions control the occurrence of contemporary marginal mountain permafrost in the Chic-Choc Mountains, south-eastern Canada: a case study from Mont Jacques-Cartier

NASA Astrophysics Data System (ADS)

Davesne, Gautier; Fortier, Daniel; Domine, Florent; Gray, James T.

2017-06-01

We present data on the distribution and thermophysical properties of snow collected sporadically over 4 decades along with recent data of ground surface temperature from Mont Jacques-Cartier (1268 m a.s.l.), the highest summit in the Appalachians of south-eastern Canada. We demonstrate that the occurrence of contemporary permafrost is necessarily associated with a very thin and wind-packed winter snow cover which brings local azonal topo-climatic conditions on the dome-shaped summit. The aims of this study were (i) to understand the snow distribution pattern and snow thermophysical properties on the Mont Jacques-Cartier summit and (ii) to investigate the impact of snow on the spatial distribution of the ground surface temperature (GST) using temperature sensors deployed over the summit. Results showed that above the local treeline, the summit is characterized by a snow cover typically less than 30 cm thick which is explained by the strong westerly winds interacting with the local surface roughness created by the physiography and surficial geomorphology of the site. The snowpack structure is fairly similar to that observed on windy Arctic tundra with a top dense wind slab (300 to 450 kg m-3) of high thermal conductivity, which facilitates heat transfer between the ground surface and the atmosphere. The mean annual ground surface temperature (MAGST) below this thin and wind-packed snow cover was about -1 °C in 2013 and 2014, for the higher, exposed, blockfield-covered sector of the summit characterized by a sporadic herbaceous cover. In contrast, for the gentle slopes covered with stunted spruce (krummholz), and for the steep leeward slope to the south-east of the summit, the MAGST was around 3 °C in 2013 and 2014. The study concludes that the permafrost on Mont Jacques-Cartier, most widely in the Chic-Choc Mountains and by extension in the southern highest summits of the Appalachians, is therefore likely limited to the barren wind-exposed surface of the summit where the low air temperature, the thin snowpack and the wind action bring local cold surface conditions favourable to permafrost development.

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 quantity compared to the snow gauges are well estimated in the high elevation.

Investigations into the climate of the South Pole

NASA Astrophysics Data System (ADS)

Town, Michael S.

Four investigations into the climate of the South Pole are presented. The general subjects of polar cloud cover, the surface energy balance in a stable boundary layer, subsurface energy transfer in snow, and modification of water stable isotopes in snow after deposition are investigated based on the historical data set from the South Pole. Clouds over the South Pole. A new, accurate cloud fraction time series is developed based on downwelling infrared radiation measurements taken at the South Pole. The results are compared to cloud fraction estimates from visual observations and satellite retrievals of cloud fraction. Visual observers are found to underestimate monthly mean cloud fraction by as much as 20% during the winter, and satellite retrievals of cloud fraction are not accurate for operational or climatic purposes. We find associations of monthly mean cloud fraction with other meteorological variables at the South Pole for use in testing models of polar weather and climate. Surface energy balance. A re-examination of the surface energy balance at the South Pole is motivated by large discrepancies in the literature. We are not able to find closure in the new surface energy balance, likely due to weaknesses in the turbulent heat flux parameterizations in extremely stable boundary layers. These results will be useful for constraining our understanding and parameterization of stable boundary layers. Subsurface energy transfer. A finite-volume model of the snow is used to simulate nine years of near-surface snow temperatures, heating rates, and vapor pressures at the South Pole. We generate statistics characterizing heat and vapor transfer in the snow on submonthly to interannual time scales. The variability of near-surface snow temperatures on submonthly time scales is large, and has potential implications for revising the interpretation of paleoclimate records of water stable isotopes in polar snow. Modification of water stable isotopes after deposition. The evolution of water stable isotopes in near-surface polar snow is simulated using a Rayleigh fractionation model including the processes of pore-space diffusion, forced ventilation, and intra-ice-grain diffusion. We find isotopic enrichment of winter snow during subsequent summers as enriched water vapor is forced into the snow and deposits as frost. This process depends on snow and atmospheric temperatures, surface wind speed, accumulation rate, and surface morphology. We further find that differential enrichment between the present day and the Last Glacial Maximum (LGM) may exaggerate the greenlandic glacial-interglacial temperature difference derived from water stable isotopes. In Antarctica, present-day post-depositional modification is likely equal to that of the LGM due to the compensating factors of lower temperatures and lower accumulation rate during the LGM.

Dynamics of Phase Transitions in a Snow Mass Containing Water-Soluble Salt Particles

NASA Astrophysics Data System (ADS)

Zelenko, V. L.; Heifets, L. I.; Orlov, Yu. N.; Voskresenskiy, N. M.

2018-07-01

A macrokinetic approach is used to describe the dynamics of phase transitions in a snow mass containing water-soluble salt particles. Equations are derived that describe the rate of salt granule dissolution and the change in the phase composition and temperature of a snow mass under the conditions of heat transfer with an isothermal surface. An experimental setup that models the change in the state of a snow mass placed on an isothermal surface is created to verify theoretical conclusions. Experimental observations of the change in temperature of the snow mass are compared to theoretical calculations. The mathematical model that is developed can be used to predict the state of a snow mass on roads treated with a deicing agent, or to analyze the state of snow masses containing water-soluble salt inclusions and resting on mountain slopes.

Arctic tundra shrub invasion and soot deposition: Consequences for spring snowmelt and near-surface air temperatures

NASA Astrophysics Data System (ADS)

Strack, John E.

Invasive shrubs and soot pollution both have the potential to alter the surface energy balance and timing of snow melt in the Arctic. Shrubs reduce the amount of snow lost to sublimation on the tundra during the winter leading to a deeper end-of-winter snowpack. The shrubs also enhance the absorption of energy by the snowpack during the melt season, by converting incoming solar radiation to longwave radiation and sensible heat. This results in a faster rate of snow melt, warmer near-surface air temperatures, and a deeper boundary layer. Soot deposition lowers the albedo of the snow allowing it to more effectively absorb incoming solar radiation and thus melt faster. This study uses the Colorado State University Regional Atmospheric Modeling System version 4.4 (CSU-RAMS 4.4), equipped with an enhanced snow model, to investigate the effects of shrub encroachment and soot deposition on the atmosphere and snowpack in the Kuparuk Basin of Alaska during the May-June melt period. The results of the simulations suggest that a complete invasion of the tundra by shrubs leads to a 1.5 degree C warming of 2-m air temperatures, 17 watts per meter square increase in surface sensible heat flux, and a 108 m increase in boundary layer depth during the melt period. The snow free-date also occurred 11 days earlier despite having a larger initial snowpack. The results also show that a decrease in the snow albedo of 0.1, due to soot pollution, caused the snow-free date to occur five days earlier. The soot pollution caused a 0.5 degree C warming of 2-m air temperatures and a 2 watts per meter square increase in surface sensible heat flux. In addition, the boundary layer averaged 25 m deeper in the polluted snow simulation.

Effects of Vegetation and of Heat and Vapor Fluxes from Soil on Snowpack Evolution and Radiobrightness

NASA Technical Reports Server (NTRS)

Chung, Y. C.; England, A. W.; DeRoo, R. D.; Weininger, Etai

2006-01-01

The radiobrightness of a snowpack is strongly linked to the snow moisture content profile, to the point that the only operational inversion algorithms require dry snow. Forward dynamic models do not include the effects of freezing and thawing of the soil beneath the snowpack and the effect of vegetation within the snow or above the snow. To get a more realistic description of the evolution of the snowpack, we reported an addition to the Snow-Soil-Vegetation-Atmosphere- Transfer (SSVAT) model, wherein we coupled soil processes of the Land Surface Process (LSP) model with the snow model SNTHERM. In the near future we will be adding a radiobrightness prediction based on the modeled moisture, temperature and snow grain size profiles. The initial investigations with this SSVAT for a late winter and early spring snow pack indicate that soil processes warm the snowpack and the soil. Vapor diffusion needs to be considered whenever the ground is thawed. In the early spring, heat flow from the ground into a snow and a strong temperature gradient across the snow lead to thermal convection. The buried vegetation can be ignored for a late winter snow pack. The warmer surface snow temperature will affect radiobrightness since it is most sensitive to snow surface characteristics. Comparison to data shows that SSVAT provides a more realistic representation of the temperature and moisture profiles in the snowpack and its underlying soil than SNTHERM. The radiobrightness module will be optimized for the prediction of brightness when the snow is moist. The liquid water content of snow causes considerable absorption compared to dry snow, and so longer wavelengths are likely to be most revealing as to the state of a moist snowpack. For volumetric moisture contents below about 7% (the pendular regime), the water forms rings around the contact points between snow grains. Electrostatic modeling of these pendular rings shows that the absorption of these rings is significantly higher than a sphere of the same volume. The first implementation of the radiobrightness module will therefore be a simple radiative transfer model without scattering.

The impact of changing the land surface scheme in ACCESS(v1.0/1.1) on the surface climatology

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

Kowalczyk, Eva A.; Stevens, Lauren E.; Law, Rachel M.

The Community Atmosphere Biosphere Land Exchange (CABLE) model has been coupled to the UK Met Office Unified Model (UM) within the existing framework of the Australian Community Climate and Earth System Simulator (ACCESS), replacing the Met Office Surface Exchange Scheme (MOSES). Here we investigate how features of the CABLE model impact on present-day surface climate using ACCESS atmosphere-only simulations. The main differences attributed to CABLE include a warmer winter and a cooler summer in the Northern Hemisphere (NH), earlier NH spring runoff from snowmelt, and smaller seasonal and diurnal temperature ranges. The cooler NH summer temperatures in canopy-covered regions aremore » more consistent with observations and are attributed to two factors. Firstly, CABLE accounts for aerodynamic and radiative interactions between the canopy and the ground below; this placement of the canopy above the ground eliminates the need for a separate bare ground tile in canopy-covered areas. Secondly, CABLE simulates larger evapotranspiration fluxes and a slightly larger daytime cloud cover fraction. Warmer NH winter temperatures result from the parameterization of cold climate processes in CABLE in snow-covered areas. In particular, prognostic snow density increases through the winter and lowers the diurnally resolved snow albedo; variable snow thermal conductivity prevents early winter heat loss but allows more heat to enter the ground as the snow season progresses; liquid precipitation freezing within the snowpack delays the building of the snowpack in autumn and accelerates snow melting in spring. Altogether we find that the ACCESS simulation of surface air temperature benefits from the specific representation of the turbulent transport within and just above the canopy in the roughness sublayer as well as the more complex snow scheme in CABLE relative to MOSES.« less

The impact of changing the land surface scheme in ACCESS(v1.0/1.1) on the surface climatology

DOE PAGES

Kowalczyk, Eva A.; Stevens, Lauren E.; Law, Rachel M.; ...

2016-08-23

The Community Atmosphere Biosphere Land Exchange (CABLE) model has been coupled to the UK Met Office Unified Model (UM) within the existing framework of the Australian Community Climate and Earth System Simulator (ACCESS), replacing the Met Office Surface Exchange Scheme (MOSES). Here we investigate how features of the CABLE model impact on present-day surface climate using ACCESS atmosphere-only simulations. The main differences attributed to CABLE include a warmer winter and a cooler summer in the Northern Hemisphere (NH), earlier NH spring runoff from snowmelt, and smaller seasonal and diurnal temperature ranges. The cooler NH summer temperatures in canopy-covered regions aremore » more consistent with observations and are attributed to two factors. Firstly, CABLE accounts for aerodynamic and radiative interactions between the canopy and the ground below; this placement of the canopy above the ground eliminates the need for a separate bare ground tile in canopy-covered areas. Secondly, CABLE simulates larger evapotranspiration fluxes and a slightly larger daytime cloud cover fraction. Warmer NH winter temperatures result from the parameterization of cold climate processes in CABLE in snow-covered areas. In particular, prognostic snow density increases through the winter and lowers the diurnally resolved snow albedo; variable snow thermal conductivity prevents early winter heat loss but allows more heat to enter the ground as the snow season progresses; liquid precipitation freezing within the snowpack delays the building of the snowpack in autumn and accelerates snow melting in spring. Altogether we find that the ACCESS simulation of surface air temperature benefits from the specific representation of the turbulent transport within and just above the canopy in the roughness sublayer as well as the more complex snow scheme in CABLE relative to MOSES.« less

Wind slab formation in snow: experimental setup and first results

NASA Astrophysics Data System (ADS)

Sommer, Christian; Lehning, Michael; Fierz, Charles

2016-04-01

The formation of wind-hardened surface layers, also known as wind slabs or wind crusts, is studied. Better knowledge about which processes and parameters are important will lead to an improved understanding of the mass balances in polar and alpine areas. It will also improve snow-cover models (i.e. SNOWPACK) as well as the forecast of avalanche danger. A ring-shaped wind tunnel has been built and instrumented. The facility is ring-shaped to simulate an infinitely long snow surface (infinite fetch). A SnowMicroPen (SMP) is used to measure the snow hardness. Other sensors measure environmental conditions such as wind velocity, air temperature, air humidity, the temperature of the snow and of the snow surface. A camera is used to detect drifting particles and to measure the Specific Surface Area (SSA) at the snow surface via near-infrared photography. First experiments indicate that mechanical fragmentation followed by sintering is the most efficient process to harden the surface. The hardness increased rapidly during drifting snow events, but only slowly or not at all when the wind speed was kept below the threshold for drifting snow. With drifting, the penetration resistance increased from the original 0.07 N to around 0.3 N in about an hour. Without drifting, a slow, further increase in resistance was observed. In about six hours, the hardness of the top 1-2 cm increased to 0.5 N. During this eight-hour experiment consisting of about two hours with intermittent drifting and six hours without drifting, the density at the surface increased from 66 kg/m3 to around 170 kg/m3. In the unaffected region close to the ground, the density increased from 100 kg/m3 to 110 kg/m3.

Observational Evidence of Changes in Soil Temperatures across Eurasian Continent

NASA Astrophysics Data System (ADS)

Zhang, T.

2015-12-01

Soil temperature is one of the key climate change indicators and plays an important role in plant growth, agriculture, carbon cycle and ecosystems as a whole. In this study, variability and changes in ground surface and soil temperatures up to 3.20 m were investigated based on data and information obtained from hydrometeorological stations across Eurasian continent since the early 1950s. Ground surface and soil temperatures were measured daily by using the same standard method and by the trained professionals across Eurasian continent, which makes the dataset unique and comparable over a large study region. Using the daily soil temperature profiles, soil seasonal freeze depth was also obtained through linear interpolation. Preliminary results show that soil temperatures at various depths have increased dramatically, almost twice as much as air temperature increase over the same period. Regionally, soil temperature increase was more dramatically in high northern latitudes than mid/lower latitude regions. Air temperature changes alone may not be able to fully explain the magnitude of changes in soil temperatures. Further study indicates that snow cover establishment started later in autumn and snow cover disappearance occurred earlier in spring, while winter snow depth became thicker with a decreasing trend of snow density. Changes in snow cover conditions may play an important role in changes of soil temperatures over the Eurasian continent.

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 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.

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 temperature and grain size supports the idea that rapid, destructive metamorphism occurs when snow temperatures are at the melting point.

Validation of snow characteristics and snow albedo feedback in the Canadian Regional Climate Model simulations over North America

NASA Astrophysics Data System (ADS)

Fang, B.; Sushama, L.; Diro, G. T.

2015-12-01

Snow characteristics and snow albedo feedback (SAF) over North America, as simulated by the fifth-generation Canadian Regional Climate Model (CRCM5), when driven by ERA-40/ERA-Interim, CanESM2 and MPI-ESM-LR at the lateral boundaries, are analyzed in this study. Validation of snow characteristics is performed by comparing simulations against available observations from MODIS, ISCCP and CMC. Results show that the model is able to represent the main spatial distribution of snow characteristics with some overestimation in snow mass and snow depth over the Canadian high Arctic. Some overestimation in surface albedo is also noted for the boreal region which is believed to be related to the snow unloading parameterization, as well as the overestimation of snow albedo. SAF is assessed both in seasonal and climate change contexts when possible. The strength of SAF is quantified as the amount of additional net shortwave radiation at the top of the atmosphere as surface albedo decreases in association with a 1°C increase in surface temperature. Following Qu and Hall (2007), this is expressed as the product of the variation in planetary albedo with surface albedo and the change in surface albedo for 1°C change in surface air temperature during the season, which in turn is determined by the strength of the snow cover and snowpack metamorphosis feedback loops. Analysis of the latter term in the seasonal cycle suggests that for CRCM5 simulations, the snow cover feedback loop is more dominant compared to the snowpack metamorphosis feedback loop, whereas for MODIS, the two feedback loops have more or less similar strength. Moreover, the SAF strength in the climate change context appears to be weaker than in the seasonal cycle and is sensitive to the driving GCM and the RCP scenario.

A continuum model for meltwater flow through compacting snow

NASA Astrophysics Data System (ADS)

Meyer, Colin R.; Hewitt, Ian J.

2017-12-01

Meltwater is produced on the surface of glaciers and ice sheets when the seasonal energy forcing warms the snow to its melting temperature. This meltwater percolates into the snow and subsequently runs off laterally in streams, is stored as liquid water, or refreezes, thus warming the subsurface through the release of latent heat. We present a continuum model for the percolation process that includes heat conduction, meltwater percolation and refreezing, as well as mechanical compaction. The model is forced by surface mass and energy balances, and the percolation process is described using Darcy's law, allowing for both partially and fully saturated pore space. Water is allowed to run off from the surface if the snow is fully saturated. The model outputs include the temperature, density, and water-content profiles and the surface runoff and water storage. We compare the propagation of freezing fronts that occur in the model to observations from the Greenland Ice Sheet. We show that the model applies to both accumulation and ablation areas and allows for a transition between the two as the surface energy forcing varies. The largest average firn temperatures occur at intermediate values of the surface forcing when perennial water storage is predicted.

The Infrared Sensor Suite for SnowEx 2017

NASA Technical Reports Server (NTRS)

Hall, D. K.; Chickadel, C. C.; Crawford, C. J.; DeMarco, E. L.; Jennings, D. E.; Jhabvala, M. D.; Kim, E. J.; Lundquist, J. D.; Lunsford, A. W.

2017-01-01

SnowEx is a winter airborne and field campaign designed to measure snow-water equivalent in forested landscapes. A major focus of Year 1 (2016-17) of NASA's SnowEx campaign will be an extensive field program involving dozens of participants from U.S. government agencies and from many universities and institutions, both domestic and foreign. Along with other instruments, two infrared (IR) sensors will be flown on a Naval Research Laboratory P-3 aircraft. Surface temperature is a critical input to hydrologic models and will be measured during the SnowEx mission. A Quantum Well Infrared Photodetector (QWIP) IR imaging camera system will be flown along with a KT-15 remote thermometer to aid in the calibration of the IR image data. Together, these instruments will measure surface temperature of snow and ice targets to an expected accuracy of less than 1C.

Observed contrast changes in snow cover phenology in northern middle and high latitudes from 2001–2014

PubMed Central

Chen, Xiaona; Liang, Shunlin; Cao, Yunfeng; He, Tao; Wang, Dongdong

2015-01-01

Quantifying and attributing the phenological changes in snow cover are essential for meteorological, hydrological, ecological, and societal implications. However, snow cover phenology changes have not been well documented. Evidence from multiple satellite and reanalysis data from 2001 to 2014 points out that the snow end date (De) advanced by 5.11 (±2.20) days in northern high latitudes (52–75°N) and was delayed by 3.28 (±2.59) days in northern mid-latitudes (32–52°N) at the 90% confidence level. Dominated by changes in De, snow duration days (Dd) was shorter in duration by 5.57 (±2.55) days in high latitudes and longer by 9.74 (±2.58) days in mid-latitudes. Changes in De during the spring season were consistent with the spatiotemporal pattern of land surface albedo change. Decreased land surface temperature combined with increased precipitation in mid-latitudes and significantly increased land surface temperature in high latitudes, impacted by recent Pacific surface cooling, Arctic amplification and strengthening westerlies, result in contrasting changes in the Northern Hemisphere snow cover phenology. Changes in the snow cover phenology led to contrasting anomalies of snow radiative forcing, which is dominated by De and accounts for 51% of the total shortwave flux anomalies at the top of the atmosphere. PMID:26581632

Interannual changes in snow cover and its impact on ground surface temperatures in Livingston Island (Antarctica)

NASA Astrophysics Data System (ADS)

Nieuwendam, Alexandre; Ramos, Miguel; Vieira, Gonçalo

2015-04-01

In permafrost areas the seasonal snow cover is an important factor on the ground thermal regime. Snow depth and timing are important in ground insulation from the atmosphere, creating different snow patterns and resulting in spatially variable ground temperatures. The aim of this work is to characterize the interactions between ground thermal regimes and snow cover and the influence on permafrost spatial distribution. The study area is the ice-free terrains of northwestern Hurd Peninsula in the vicinity of the Spanish Antarctic Station "Juan Carlos I" and Bulgarian Antarctic Station "St. Kliment Ohridski". Air and ground temperatures and snow thickness data where analysed from 4 sites along an altitudinal transect in Hurd Peninsula from 2007 to 2012: Nuevo Incinerador (25 m asl), Collado Ramos (110 m), Ohridski (140 m) and Reina Sofia Peak (275 m). The data covers 6 cold seasons showing different conditions: i) very cold with thin snow cover; ii) cold with a gradual increase of snow cover; iii) warm with thick snow cover. The data shows three types of periods regarding the ground surface thermal regime and the thickness of snow cover: a) thin snow cover and short-term fluctuation of ground temperatures; b) thick snow cover and stable ground temperatures; c) very thick snow cover and ground temperatures nearly constant at 0°C. a) Thin snow cover periods: Collado Ramos and Ohridski sites show frequent temperature variations, alternating between short-term fluctuations and stable ground temperatures. Nuevo Incinerador displays during most of the winter stable ground temperatures; b) Cold winters with a gradual increase of the snow cover: Nuevo Incinerador, Collado Ramos and Ohridski sites show similar behavior, with a long period of stable ground temperatures; c) Thick snow cover periods: Collado Ramos and Ohridski show long periods of stable ground, while Nuevo Incinerador shows temperatures close to 0°C since the beginning of the winter, due to early snow cover, which prevents cooling. Reina Sofia shows a very different behavior from the other sites, with a frequent stabilization of ground temperatures during all the winters, and last until late-fall. This situation could be related to the structure, and physical and thermal properties of snow cover. The analysis of the Freezing Degree Days (FDDs) and freezing n-factor reveals significant interannual variations. Ohridski shows the highest FDDs values followed by Reina Sofia. Nuevo Incinerador showed the lowest FDDs values. The freezing n-factor shows highest values at Ohridski, followed by Collado Ramos and Reina Sofia with very similar values. Nuevo Incinerador shows the lowest n-factor values. Snow cover doesn't insulate the ground from freezing, but depending on its thickness, density and the amount of heat in the ground, it decreases ground temperatures amplitudes and increases delays relative to air temperature changes. Even where snow cover remains several centimeters thick for several months, slow decrease of bottom temperature is possible, reaching a minimum value at the end of the winter. The results demonstrate that Reina Sofia and Ohridski sites, because of the seasonal behavior, FDDs and freezing n-factor, demonstrate higher winter ground cooling. This research was funded by PERMANTAR-3 (PTDC/AAG-GLO/3908/2012) project (Fundação para a Ciência e a Tecnologia of Portugal)

Snow multivariable data assimilation for hydrological predictions in mountain areas

NASA Astrophysics Data System (ADS)

Piazzi, Gaia; Campo, Lorenzo; Gabellani, Simone; Rudari, Roberto; Castelli, Fabio; Cremonese, Edoardo; Morra di Cella, Umberto; Stevenin, Hervé; Ratto, Sara Maria

2016-04-01

The seasonal presence of snow on alpine catchments strongly impacts both surface energy balance and water resource. Thus, the knowledge of the snowpack dynamics is of critical importance for several applications, such as water resource management, floods prediction and hydroelectric power production. Several independent data sources provide information about snowpack state: ground-based measurements, satellite data and physical models. Although all these data types are reliable, each of them is affected by specific flaws and errors (respectively dependency on local conditions, sensor biases and limitations, initialization and poor quality forcing data). Moreover, 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 observational and modeled information to obtain the most likely estimate of snowpack state. Indeed, by combining all the available sources of information, the implementation of DA schemes can quantify and reduce the uncertainties of the estimations. This study presents SMASH (Snow Multidata Assimilation System for Hydrology), a multi-layer snow dynamic model, strengthened by a robust multivariable data assimilation algorithm. 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, relative air humidity, precipitation and incident solar radiation) to provide a complete estimate of snowpack state. The implementation of an Ensemble Kalman Filter (EnKF) scheme enables to assimilate simultaneously ground-based and remotely sensed data of different snow-related variables (snow albedo and surface temperature, Snow Water Equivalent from passive microwave sensors and Snow Cover Area). SMASH performance was evaluated in the period June 2012 - December 2013 at the meteorological station of Torgnon (Tellinod, 2 160 msl), located in Aosta Valley, a mountain region in northwestern Italy. The EnKF algorithm was firstly tested by assimilating several ground-based measurements: snow depth, land surface temperature, snow density and albedo. The assimilation of snow observed data revealed an overall considerable enhancement of model predictions with respect to the open loop experiments. A first attempt to integrate also remote sensed information was performed by assimilating the Land Surface Temperature (LST) from METEOSAT Second Generation (MSG), leading to good results. The analysis allowed identifying the snow depth and the snowpack surface temperature as the most impacting variables in the assimilation process. In order to pinpoint an optimal number of ensemble instances, SMASH performances were also quantitatively evaluated by varying the instances amount. Furthermore, the impact of the data assimilation frequency was analyzed by varying the assimilation time step (3h, 6h, 12h, 24h).

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.

Modeling of multi-phase interactions of reactive nitrogen between snow and air in Antarctica

NASA Astrophysics Data System (ADS)

McCrystall, M.; Chan, H. G. V.; Frey, M. M.; King, M. D.

2016-12-01

In polar and snow-covered regions, the snowpack is an important link between atmospheric, terrestrial and oceanic systems. Trace gases, including nitrogen oxides, produced via photochemical reactions in snow are partially released to the lower atmosphere with considerable impact on its composition. However, the post-depositional processes that change the chemical composition and physical properties of the snowpack are still poorly understood. Most current snow chemistry models oversimplify as they assume air-liquid interactions and aqueous phase chemistry taking place at the interface between the snow grain and air. Here, we develop a novel temperature dependent multi-phase (gas-liquid-ice) physical exchange model for reactive nitrogen. The model is validated with existing year-round observations of nitrate in the top 0.5-2 cm of snow and the overlying atmosphere at two very different Antarctic locations: Dome C on the East Antarctic Plateau with very low annual mean temperature (-54ºC) and accumulation rate (<30 kg m-2 yr-1); and Halley, a coastal site with at times at or above freezing temperatures during summer, high accumulation rate and high background level of sea salt aerosol. We find that below the eutectic temperature of the H2O/dominant ion mixture the surface snow nitrate is controlled by kinetic adsorption onto the surface of snow grains followed by grain diffusion. Above the eutectic temperature, in addition to the former two processes, thermodynamic equilibrium of HNO3 between interstitial air and liquid water pockets, possibly present at triple junctions or grooves at grain boundaries, greatly enhances the nitrate uptake by snow in agreement with the concentration peak observed in summer.

Recent increase in snow-melt area in the Greenland Ice sheet as an indicator of the effect of reduced surface albedo by snow impurities

NASA Astrophysics Data System (ADS)

Rikiishi, K.

2008-12-01

Recent rapid decline of cryosphere including mountain glaciers, sea ice, and seasonal snow cover tends to be associated with global warming. However, positive feedback is likely to operate between the cryosphere and air temperature, and then it may not be so simple to decide the cause-and-effect relation between them. The theory of heat budget for snow surface tells us that sensible heat transfer from the air to the snow by atmospheric warming by 1°C is about 10 W/m2, which is comparable with heat supply introduced by reduction of the snow surface albedo by only 0.02. Since snow impurities such as black carbon and soil- origin dusts have been accumulated every year on the snow surface in snow-melting season, it is very important to examine whether the snow-melting on the ice sheets, mountain glaciers, and sea ice is caused by global warming or by accumulated snow impurities originated from atmospheric pollutants. In this paper we analyze the dataset of snow-melt area in the Greenland ice sheet for the years 1979 - 2007 (available from the National Snow and Ice Data Center), which is reduced empirically from the satellite micro-wave observations by SMMR and SMM/I. It has been found that, seasonally, the snow-melt area extends most significantly from the second half of June to the first half of July when the sun is highest and sunshine duration is longest, while it doesn't extend any more from the second half of July to the first half of August when the air temperature is highest. This fact may imply that sensible heat required for snow-melting comes from the solar radiation rather than from the atmosphere. As for the interannual variation of snow-melt area, on the other hand, we have found that the growth rate of snow-melt area gradually increases from July, to August, and to the first half of September as the impurities come out to and accumulated at the snow surface. However, the growth rate is almost zero in June and the second half of September when fresh snow of high albedo covers the surface. This fact may imply that the combined operation of solar radiation and snow impurities is responsible for the recent global decline of cryosphere. Discussion about other research works will be given in the presentation in order to support the above idea.

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 and greater heat gain during spring. The net effect is to reduce annual mean soil temperatures by up to 3°C in snow-affected regions.

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 and greater heat gain during spring. The net effect is to reduce annual mean soil temperatures by up to 3°C in snow-affected regions.

Open System Tribology and Influence of Weather Condition.

PubMed

Lyu, Yezhe; Bergseth, Ellen; Olofsson, Ulf

2016-08-30

The tribology of an open system at temperatures ranging between 3 °C and -35 °C, with and without snow, was investigated using a pin-on-disc tribometer mounted in a temperature-controlled environmental chamber. The relationship between the microstructure and ductility of the materials and the tribology at the contacting surfaces was investigated. The study shows that during continuous sliding, pressure causes snow particles to melt into a liquid-like layer, encouraging the generation of oxide flakes on the contact path. The friction coefficient and wear rate are dramatically reduced through an oxidative friction and wear mechanism. In the absence of snow, the tribological process is controlled by the low temperature brittleness of steel in the temperature range from 3 °C to -15 °C. At these temperatures, cracks are prone to form and extend on the worn surfaces, resulting in the spalling of bulk scraps, which are crushed into debris that increases the friction coefficient and wear rate due to strong abrasion. When the temperature falls to -25 °C, an ice layer condenses on the metal surfaces and relaxes the tribological process in the same way as the added snow particles, which significantly decreases the friction and wear.

Open System Tribology and Influence of Weather Condition

PubMed Central

Lyu, Yezhe; Bergseth, Ellen; Olofsson, Ulf

2016-01-01

The tribology of an open system at temperatures ranging between 3 °C and −35 °C, with and without snow, was investigated using a pin-on-disc tribometer mounted in a temperature-controlled environmental chamber. The relationship between the microstructure and ductility of the materials and the tribology at the contacting surfaces was investigated. The study shows that during continuous sliding, pressure causes snow particles to melt into a liquid-like layer, encouraging the generation of oxide flakes on the contact path. The friction coefficient and wear rate are dramatically reduced through an oxidative friction and wear mechanism. In the absence of snow, the tribological process is controlled by the low temperature brittleness of steel in the temperature range from 3 °C to −15 °C. At these temperatures, cracks are prone to form and extend on the worn surfaces, resulting in the spalling of bulk scraps, which are crushed into debris that increases the friction coefficient and wear rate due to strong abrasion. When the temperature falls to −25 °C, an ice layer condenses on the metal surfaces and relaxes the tribological process in the same way as the added snow particles, which significantly decreases the friction and wear. PMID:27573973

Snow depth retrieval from L-band satellite measurements on Arctic and Antarctic sea ice

NASA Astrophysics Data System (ADS)

Maaß, N.; Kaleschke, L.; Wever, N.; Lehning, M.; Nicolaus, M.; Rossmann, H. L.

2017-12-01

The passive microwave mission SMOS provides daily coverage of the polar regions and measures at a low frequency of 1.4 GHz (L-band). SMOS observations have been used to operationally retrieve sea ice thickness up to 1 m and to estimate snow depth in the Arctic for thicker ice. Here, we present how SMOS-retrieved snow depths compare with airborne measurements from NASA's Operation IceBridge mission (OIB) and with AMSR-2 satellite retrievals at higher frequencies, and we show first applications to Antarctic sea ice. In previous studies, SMOS and OIB snow depths showed good agreement on spatial scales from 50 to 1000 km for some days and disagreement for other days. Here, we present a more comprehensive comparison of OIB and SMOS snow depths in the Arctic for 2011 to 2015. We find that the SMOS retrieval works best for cold conditions and depends on auxiliary information on ice surface temperature, here provided by MODIS thermal imagery satellite data. However, comparing SMOS and OIB snow depths is difficult because of the different spatial resolutions (SMOS: 40 km, OIB: 40 m). Spatial variability within the SMOS footprint can lead to different snow conditions as seen from SMOS and OIB. Ideally the comparison is made for uniform conditions: Low lead and open water fraction, low spatial and temporal variability of ice surface temperature, no mixture of multi- and first-year ice. Under these conditions and cold temperatures (surface temperatures below -25°C), correlation coefficients between SMOS and OIB snow depths increase from 0.3 to 0.6. A finding from the comparison with AMSR-2 snow depths is that the SMOS-based maps depend less on the age of the sea ice than the maps derived from higher frequencies. Additionally, we show first results of SMOS snow depths for Antarctic sea ice. SMOS observations are compared to measurements of autonomous snow buoys drifting in the Weddell Sea since 2014. For a better comparability of these point measurements with SMOS data, we use model simulations along these trajectories made with a sea ice version of SNOWPACK, a 1D multi-layer thermodynamic snow model driven by reanalysis data. These simulations are especially helpful for indicating the occurrence of snow-ice-transformation, which cannot be identified in the buoy data and contributes to the measured snow height.

Intraseasonal Characteristics Of North Atlantic Oscillation

NASA Astrophysics Data System (ADS)

Bojariu, R.; Gimeno, L..; de La Torre, L.; Nieto, R.

There is evidence of a temporal structure of regional response to the NAO variability in the cold season (e.g. NAO-related climate fluctuations reveal their strongest signal in January). To document the details of NAO intraseasonal characteristics we anal- ysed surface and upper air variables (air surface temperature, sea-ice concentration, sea surface temperature, and sea level pressure and geopotential heights at 700 hPa level) in individual months, from November to April. The data consist of 40 years of monthly reanalyses (1961-2000) extracted from the NCAR-NCEP data set. In ad- dition, snow cover data are used (monthly snow cover frequencies from the Climate Prediction Centre and number of days with snow cover from the Former Soviet Union Hydrological Snow Surveys available at the National Snow and Ice Data Centre). A NAO-related signal with predictive potential has been identified in November air surface temperature over Europe and SLP and geopotential heights over Eurasia. Neg- ative thermal anomalies over the Central Europe and positive geopotential anomalies at 700 hPa over a latitudinal belt from Arabic Peninsula to Pacific Ocean are associated with a high NAO index in the following winter. The November thermal anomalies that seem to be related to the NAO interannual persistence are also linked with the fluctu- ations of snow cover over Europe. Both tropical and high latitude influences may play a role in the onset of the November signal and in further NAO development.

Properties of the surface snow in Princess Elizabeth Land, East Antarctica - climate and non-climate dependent variability of the surface mass balance and stable water isotopic composition

NASA Astrophysics Data System (ADS)

Vladimirova, D.; Ekaykin, A.; Lipenkov, V.; Popov, S. V.; Petit, J. R.; Masson-Delmotte, V.

2017-12-01

Glaciological and meteorological observations conducted during the past four decades in Princess Elizabeth Land, East Antarctica, are compiled. The database is used to investigate spatial patterns of surface snow isotopic composition and surface mass balance, including detailed information near subglacial lake Vostok. We show diverse relationships between snow isotopic composition and surface temperature. In the most inland part (elevation 3200-3400 m a.s.l.), surface snow isotopic composition varies independently from surface temperature, and is closely related to the distance to the open water source (with a slope of 0.98±0.17 ‰ per 100 km). Surface mass balance values are higher along the ice sheet slope, and relatively evenly distributed inland. The minimum values of snow isotopic composition and surface mass balance are identified in an area XX km southwestward from Vostok station. The spatial distribution of deuterium excess delineates regions influenced by the Indian Ocean and Pacific Ocean air masses, with Vostok area being situated close to their boundary. Anomalously high deuterium excess values are observed near Dome A, suggesting high kinetic fractionation for its moisture source, or specifically high post-deposition artifacts. The dataset is available for further studies such as the assessment of skills of general circulation or regional atmospheric models, and the search for the oldest ice.

Monitoring Mountain Meteorology without Much Money (Invited)

NASA Astrophysics Data System (ADS)

Lundquist, J. D.

2009-12-01

Mountains are the water towers of the world, storing winter precipitation in the form of snow until summer, when it can be used for agriculture and cities. However, mountain weather is highly variable, and measurements are sparsely distributed. In order adequately sample snow and climate variables in complex terrain, we need as many measurements as possible. This means that instruments must be inexpensive and relatively simple to deploy. Here, we demonstrate how dime-sized temperature sensors developed for the refrigeration industry can be used to monitor air temperature (using evergreen trees as radiation shields) and snow cover duration (using the diurnal cycle in near-surface soil temperature). Together, these measurements can be used to recreate accumulated snow water equivalent over the prior year. We also demonstrate how buckets of water may be placed under networked acoustic snow depth sensors to provide an index of daily evaporation rates at SNOTEL stations. (a) Temperature sensor sealed for deployment in the soil. (b) Launching a temperature sensor into a tree. (c) Pulley system to keep sensor above the snow. (a) Photo of bucket underneath acoustic snow depth sensor. (b) Water depth in the bucket as calculated by the snow depth sensor and by a pressure sensor inside the bucket.

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 understanding the impacts of future climate change on snow albedo in the Northeastern US.

Future Change of Snow Water Equivalent over Japan

NASA Astrophysics Data System (ADS)

Hara, M.; Kawase, H.; Kimura, F.; Fujita, M.; Ma, X.

2012-12-01

Western side of Honshu Island and Hokkaido Island in Japan are ones of the heaviest snowfall areas in the world. Although a heavy snowfall often brings disaster, snow is one of the major sources for agriculture, industrial, and house-use in Japan. Even during the winter, the monthly mean of the surface air temperature often exceeds 0 C in large parts of the heavy snow areas along the Sea of Japan. Thus, snow cover may be seriously reduced in these areas as a result of the global warming, which is caused by an increase in greenhouse gases. The change in seasonal march of snow water equivalent, e.g., snowmelt season and amount will strongly influence to social-economic activities. We performed a series of numerical experiments including present and future climate simulations and much-snow and less-snow cases using a regional climate model. Pseudo-Global-Warming (PGW) method (Kimura and Kitoh, 2008) is applied for the future climate simulations. MIROC 3.2 medres 2070s output under IPCC SRES A2 scenario and 1990s output under 20c3m scenario used for PGW method. The precipitation, snow depth, and surface air temperature of the hindcast simulations show good agreement with the AMeDAS station data. In much-snow cases, The decreasing rate of maximum total snow water equivalent over Japan due to climate change was 49%. Main cause of the decrease of the total snow water equivalent is the air temperature rise due to global climate change. The difference in the precipitation amount between the present and the future simulations is small.

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 melt dynamics in forested land surfaces. The turbulent transport dynamics, including counter-gradient fluxes, and radiation features including land surface albedo, are discussed in the context of the snow energy balance.

Assimilation and High Resolution Forecasts of Surface and Near Surface Conditions for the 2010 Vancouver Winter Olympic and Paralympic Games

NASA Astrophysics Data System (ADS)

Bernier, Natacha B.; Bélair, Stéphane; Bilodeau, Bernard; Tong, Linying

2014-01-01

A dynamical model was experimentally implemented to provide high resolution forecasts at points of interests in the 2010 Vancouver Olympics and Paralympics Region. In a first experiment, GEM-Surf, the near surface and land surface modeling system, is driven by operational atmospheric forecasts and used to refine the surface forecasts according to local surface conditions such as elevation and vegetation type. In this simple form, temperature and snow depth forecasts are improved mainly as a result of the better representation of real elevation. In a second experiment, screen level observations and operational atmospheric forecasts are blended to drive a continuous cycle of near surface and land surface hindcasts. Hindcasts of the previous day conditions are then regarded as today's optimized initial conditions. Hence, in this experiment, given observations are available, observation driven hindcasts continuously ensure that daily forecasts are issued from improved initial conditions. GEM-Surf forecasts obtained from improved short-range hindcasts produced using these better conditions result in improved snow depth forecasts. In a third experiment, assimilation of snow depth data is applied to further optimize GEM-Surf's initial conditions, in addition to the use of blended observations and forecasts for forcing. Results show that snow depth and summer temperature forecasts are further improved by the addition of snow depth data assimilation.

Influence of snow cover changes on surface radiation and heat balance based on the WRF model

NASA Astrophysics Data System (ADS)

Yu, Lingxue; Liu, Tingxiang; Bu, Kun; Yang, Jiuchun; Chang, Liping; Zhang, Shuwen

2017-10-01

The snow cover extent in mid-high latitude areas of the Northern Hemisphere has significantly declined corresponding to the global warming, especially since the 1970s. Snow-climate feedbacks play a critical role in regulating the global radiation balance and influencing surface heat flux exchange. However, the degree to which snow cover changes affect the radiation budget and energy balance on a regional scale and the difference between snow-climate and land use/cover change (LUCC)-climate feedbacks have been rarely studied. In this paper, we selected Heilongjiang Basin, where the snow cover has changed obviously, as our study area and used the WRF model to simulate the influences of snow cover changes on the surface radiation budget and heat balance. In the scenario simulation, the localized surface parameter data improved the accuracy by 10 % compared with the control group. The spatial and temporal analysis of the surface variables showed that the net surface radiation, sensible heat flux, Bowen ratio, temperature and percentage of snow cover were negatively correlated and that the ground heat flux and latent heat flux were positively correlated with the percentage of snow cover. The spatial analysis also showed that a significant relationship existed between the surface variables and land cover types, which was not obviously as that for snow cover changes. Finally, six typical study areas were selected to quantitatively analyse the influence of land cover types beneath the snow cover on heat absorption and transfer, which showed that when the land was snow covered, the conversion of forest to farmland can dramatically influence the net radiation and other surface variables, whereas the snow-free land showed significantly reduced influence. Furthermore, compared with typical land cover changes, e.g., the conversion of forest into farmland, the influence of snow cover changes on net radiation and sensible heat flux were 60 % higher than that of land cover changes, indicating the importance of snow cover changes in the surface-atmospheric feedback system.

Experimental and ecosystem model approach to assessing the sensitivity of High arctic deep permafrost to changes in surface temperature and precipitation

NASA Astrophysics Data System (ADS)

Rasmussen, L. H.; Zhang, W.; Elberling, B.; Cable, S.

2016-12-01

Permafrost affected areas in Greenland are expected to experience large temperature increases within the 21st century. Most previous studies on permafrost consider near-surface soil, where changes will happen first. However, how sensitive the deep permafrost temperature is to near-surface conditions through changes in soil thermal properties, snow depth and soil moisture, is not known. In this study, we measured the sensitivity of thermal conductivity (TC) to gravimetric water content (GWC) in frozen and thawed deep permafrost sediments from deltaic, alluvial and fluvial depositional environments in the Zackenberg valley, NE Greenland. We also calibrated a coupled heat and water transfer model, the "CoupModel", for the two closely situated deltaic sites, one with average snow depth and the other with topographic snow accumulation. With the calibrated model, we simulated deep permafrost thermal dynamics in four scenarios with changes in surface forcing: a. 3 °C warming and 20 % increase in precipitation; b. 3 °C warming and 100 % increase in precipitation; c. 6 °C warming and 20 % increase in precipitation; d. 6 °C warming and 100 % increase in precipitation.Our results indicated that frozen sediments had higher TC than thawed sediments. All sediments showed a positive linear relation between TC and soil moisture when frozen, and a logarithmic one when thawed. Fluvial sediments had high sensitivity, but never reached above 12 % GWC, indicating a field effect of water retention capacity. Alluvial sediments were less sensitive to soil moisture than deltaic and fluvial sediments, indicating the importance of unfrozen water in frozen sediment. The deltaic site with snow accumulation had 1 °C higher annual mean ground temperature than the average snow site. The soil temperature at the depth of 18 m increased with 1.5 °C and 3.5 °C in the scenarios with 3 °C and 6 °C warming, respectively. Precipitation had no significant additional effect to warming. We conclude that below-ground sediment properties affect the sensitivity of TC to GWC, that surface temperature changes can significantly affect the deep permafrost within a short period, and that differences in snow depth affect surface temperatures. Geology, pedology and precipitation should thus be considered if estimating future High arctic deep permafrost sensitivity.

Impacts of peatland forestation on regional climate conditions in Finland

NASA Astrophysics Data System (ADS)

Gao, Yao; Markkanen, Tiina; Backman, Leif; Henttonen, Helena M.; Pietikäinen, Joni-Pekka; Laaksonen, Ari

2014-05-01

Climate response to anthropogenic land cover change happens more locally and occurs on a shorter time scale than the global warming due to increased GHGs. Over the second half of last Century, peatlands were vastly drained in Finland to stimulate forest growth for timber production. In this study, we investigate the biophysical effects of peatland forestation on near-surface climate conditions in Finland. For this, the regional climate model REMO, developed in Max Plank Institute (currently in Climate Service Center, Germany), provides an effective way. Two sets of 15-year climate simulations were done by REMO, using the historic (1920s; The 1st Finnish National Forest Inventory) and present-day (2000s; the 10th Finnish National Forest Inventory) land cover maps, respectively. The simulated surface air temperature and precipitation were then analyzed. In the most intensive peatland forestation area in Finland, the differences in monthly averaged daily mean surface air temperature show a warming effect around 0.2 to 0.3 K in February and March and reach to 0.5 K in April, whereas a slight cooling effect, less than 0.2 K, is found from May till October. Consequently, the selected snow clearance dates in model gridboxes over that area are advanced 0.5 to 4 days in the mean of 15 years. The monthly averaged precipitation only shows small differences, less than 10 mm/month, in a varied pattern in Finland from April to September. Furthermore, a more detailed analysis was conducted on the peatland forestation area with a 23% decrease in peatland and a 15% increase in forest types. 11 day running means of simulated temperature and energy balance terms, as well as snow depth were averaged over 15 years. Results show a positive feedback induced by peatland forestation between the surface air temperature and snow depth in snow melting period. This is because the warmer temperature caused by lower surface albedo due to more forest in snow cover period leads to a quicker and earlier snow melting. Meanwhile, surface albedo is reduced and consequently surface air temperature is increased. Additionally, the maximum difference from individual gridboxes in this area over 15 years of 11 day running means of daily mean surface air temperature reaches 2 K, which is four times as much as the maximum difference of 15-year regional average of that. This illustrates that the spring warming effect from peatland forestation in Finland is highly heterogeneous spatially and temporally.

Estimating the Longwave Radiation Underneath the Forest Canopy in Snow-dominated Setting

NASA Astrophysics Data System (ADS)

Zhou, Y.; Kumar, M.; Link, T. E.

2017-12-01

Forest canopies alter incoming longwave radiation at the land surface, thus influencing snow cover energetics. The snow surface receives longwave radiation from the sky as well as from surrounding vegetation. The longwave radiation from trees is determined by its skin temperature, which shows significant heterogeneity depending on its position and morphometric attributes. Here our goal is to derive an effective tree temperature that can be used to estimate the longwave radiation received by the land surface pixel. To this end, we implement these three steps: 1) derive a relation between tree trunk surface temperature and the incident longwave radiation, shortwave radiation, and air temperature; 2) develop an inverse model to calculate the effective temperature by establishing a relationship between the effective temperature and the actual tree temperature; and 3) estimate the effective temperature using widely measured variables, such as solar radiation and forest density. Data used to derive aforementioned relations were obtained at the University of Idaho Experimental Forest, in northern Idaho. Tree skin temperature, incoming longwave radiation, solar radiation received by the tree surface, and air temperature were measured at an isolated tree and a tree within a homogeneous forest stand. Longwave radiation received by the land surface and the sky view factors were also measured at the same two locations. The calculated effective temperature was then compared with the measured tree trunk surface temperature. Additional longwave radiation measurements with pyrgeometer arrays were conducted under forests with different densities to evaluate the relationship between effective temperature and forest density. Our preliminary results show that when exposed to direct shortwave radiation, the tree surface temperature shows a significant difference from the air temperature. Under cloudy or shaded conditions, the tree surface temperature closely follows the air temperature. The effective tree temperature follows the air temperature in a dense forest stand, although it is significantly larger than the air temperature near the isolated tree. This discrepancy motivates us to explore ways to represent the effective tree temperature for stands with different densities.

Simulating Snow in Canadian Boreal Environments with CLASS for ESM-SnowMIP

NASA Astrophysics Data System (ADS)

Wang, L.; Bartlett, P. A.; Derksen, C.; Ireson, A. M.; Essery, R.

2017-12-01

The ability of land surface schemes to provide realistic simulations of snow cover is necessary for accurate representation of energy and water balances in climate models. Historically, this has been particularly challenging in boreal forests, where poor treatment of both snow masking by forests and vegetation-snow interaction has resulted in biases in simulated albedo and snowpack properties, with subsequent effects on both regional temperatures and the snow albedo feedback in coupled simulations. The SnowMIP (Snow Model Intercomparison Project) series of experiments or `MIPs' was initiated in order to provide assessments of the performance of various snow- and land-surface-models at selected locations, in order to understand the primary factors affecting model performance. Here we present preliminary results of simulations conducted for the third such MIP, ESM-SnowMIP (Earth System Model - Snow Model Intercomparison Project), using the Canadian Land Surface Scheme (CLASS) at boreal forest sites in central Saskatchewan. We assess the ability of our latest model version (CLASS 3.6.2) to simulate observed snowpack properties (snow water equivalent, density and depth) and above-canopy albedo over 13 winters. We also examine the sensitivity of these simulations to climate forcing at local and regional scales.

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.

Soil Moisture and Snow Cover: Active or Passive Elements of Climate

NASA Technical Reports Server (NTRS)

Oglesby, Robert J.; Marshall, Susan; Erickson, David J., III; Robertson, Franklin R.; Roads, John O.; Arnold, James E. (Technical Monitor)

2002-01-01

A key question is the extent to which surface effects such as soil moisture and snow cover are simply passive elements or whether they can affect the evolution of climate on seasonal and longer time scales. We have constructed ensembles of predictability studies using the NCAR CCM3 in which we compared the relative roles of initial surface and atmospheric conditions over the central and western U.S. in determining the subsequent evolution of soil moisture and of snow cover. Results from simulations with realistic soil moisture anomalies indicate that internal climate variability may be the strongest factor, with some indication that the initial atmospheric state is also important. Model runs with exaggerated soil moisture reductions (near-desert conditions) showed a much larger effect, with warmer surface temperatures, reduced precipitation, and lower surface pressures; the latter indicating a response of the atmospheric circulation. These results suggest the possibility of a threshold effect in soil moisture, whereby an anomaly must be of a sufficient size before it can have a significant impact on the atmospheric circulation and climate. Results from simulations with realistic snow cover anomalies indicate that the time of year can be crucial. When introduced in late winter, these anomalies strongly affected the subsequent evolution of snow cover. When introduced in early winter, however, little or no effect is seen on the subsequent snow cover. Runs with greatly exaggerated initial snow cover indicate that the high reflectivity of snow is the most important process by which snow cover can impact climate, through lower surface temperatures and increased surface pressures. The results to date were obtained for model runs with present-day conditions. We are currently analyzing runs made with projected forcings for the 21st century to see if these results are modified in any way under likely scenarios of future climate change. An intriguing new statistical technique involving 'clustering' is developed to assist in this analysis.

Impacts of Satellite-Based Snow Albedo Assimilation on Offline and Coupled Land Surface Model Simulations.

PubMed

Wang, Tao; Peng, Shushi; Krinner, Gerhard; Ryder, James; Li, Yue; Dantec-Nédélec, Sarah; Ottlé, Catherine

2015-01-01

Seasonal snow cover in the Northern Hemisphere is the largest component of the terrestrial cryosphere and plays a major role in the climate system through strong positive feedbacks related to albedo. The snow-albedo feedback is invoked as an important cause for the polar amplification of ongoing and projected climate change, and its parameterization across models is an important source of uncertainty in climate simulations. Here, instead of developing a physical snow albedo scheme, we use a direct insertion approach to assimilate satellite-based surface albedo during the snow season (hereafter as snow albedo assimilation) into the land surface model ORCHIDEE (ORganizing Carbon and Hydrology In Dynamic EcosystEms) and assess the influences of such assimilation on offline and coupled simulations. Our results have shown that snow albedo assimilation in both ORCHIDEE and ORCHIDEE-LMDZ (a general circulation model of Laboratoire de Météorologie Dynamique) improve the simulation accuracy of mean seasonal (October throughout May) snow water equivalent over the region north of 40 degrees. The sensitivity of snow water equivalent to snow albedo assimilation is more pronounced in the coupled simulation than the offline simulation since the feedback of albedo on air temperature is allowed in ORCHIDEE-LMDZ. We have also shown that simulations of air temperature at 2 meters in ORCHIDEE-LMDZ due to snow albedo assimilation are significantly improved during the spring in particular over the eastern Siberia region. This is a result of the fact that high amounts of shortwave radiation during the spring can maximize its snow albedo feedback, which is also supported by the finding that the spatial sensitivity of temperature change to albedo change is much larger during the spring than during the autumn and winter. In addition, the radiative forcing at the top of the atmosphere induced by snow albedo assimilation during the spring is estimated to be -2.50 W m-2, the magnitude of which is almost comparable to that due to CO2 (2.83 W m-2) increases since 1750. Our results thus highlight the necessity of realistic representation of snow albedo in the model and demonstrate the use of satellite-based snow albedo to improve model behaviors, which opens new avenues for constraining snow albedo feedback in earth system models.

Impacts of Satellite-Based Snow Albedo Assimilation on Offline and Coupled Land Surface Model Simulations

PubMed Central

Wang, Tao; Peng, Shushi; Krinner, Gerhard; Ryder, James; Li, Yue; Dantec-Nédélec, Sarah; Ottlé, Catherine

2015-01-01

Seasonal snow cover in the Northern Hemisphere is the largest component of the terrestrial cryosphere and plays a major role in the climate system through strong positive feedbacks related to albedo. The snow-albedo feedback is invoked as an important cause for the polar amplification of ongoing and projected climate change, and its parameterization across models is an important source of uncertainty in climate simulations. Here, instead of developing a physical snow albedo scheme, we use a direct insertion approach to assimilate satellite-based surface albedo during the snow season (hereafter as snow albedo assimilation) into the land surface model ORCHIDEE (ORganizing Carbon and Hydrology In Dynamic EcosystEms) and assess the influences of such assimilation on offline and coupled simulations. Our results have shown that snow albedo assimilation in both ORCHIDEE and ORCHIDEE-LMDZ (a general circulation model of Laboratoire de Météorologie Dynamique) improve the simulation accuracy of mean seasonal (October throughout May) snow water equivalent over the region north of 40 degrees. The sensitivity of snow water equivalent to snow albedo assimilation is more pronounced in the coupled simulation than the offline simulation since the feedback of albedo on air temperature is allowed in ORCHIDEE-LMDZ. We have also shown that simulations of air temperature at 2 meters in ORCHIDEE-LMDZ due to snow albedo assimilation are significantly improved during the spring in particular over the eastern Siberia region. This is a result of the fact that high amounts of shortwave radiation during the spring can maximize its snow albedo feedback, which is also supported by the finding that the spatial sensitivity of temperature change to albedo change is much larger during the spring than during the autumn and winter. In addition, the radiative forcing at the top of the atmosphere induced by snow albedo assimilation during the spring is estimated to be -2.50 W m-2, the magnitude of which is almost comparable to that due to CO2 (2.83 W m-2) increases since 1750. Our results thus highlight the necessity of realistic representation of snow albedo in the model and demonstrate the use of satellite-based snow albedo to improve model behaviors, which opens new avenues for constraining snow albedo feedback in earth system models. PMID:26366564

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 in the ancient cratered terrain of Mars. ?? 1987.

Concentration of Nitrate near the Surface of Frozen Salt Solutions

NASA Astrophysics Data System (ADS)

Michelsen, R. R. H.; Marrocco, H. A.

2017-12-01

The photolysis of nitrate near the surface of snow and ice in Earth's environment results in the emission of nitrogen oxides (NO, NO2 and, in acidic snow, HONO) and OH radicals. As a result, nitrate photolysis affects the composition and oxidative capacity of the overlying atmosphere. Photolysis yields depend in part on how much nitrate is close enough to the surface to be photolyzed. These concentrations are assumed to be higher than the concentrations of nitrate that are measured in melted snow and ice samples. However, near-surface concentrations of nitrate have not been directly measured. In this work, laboratory studies of the concentration of nitrate in frozen aqueous solutions are described. Individual aqueous solutions of nitric acid, sodium nitrate, and magnesium nitrate were mixed. Attenuated total reflection infrared spectroscopy was utilized to measure the nitrate and liquid water signals within 200 - 400 nm of the lower surface of frozen samples. Temperature was varied from -18°C to -2°C. In addition to the amount of nitrate observed, changes to the frozen samples' morphology with annealing are discussed. Nitrate concentrations near the lower surface of these frozen solutions are high: close to 1 M at warmer temperatures and almost 4 M at the coldest temperature. Known freezing point depression data describe the observed concentrations better than ideal solution thermodynamics, which overestimate concentration significantly at colder temperatures. The implications for modeling the chemistry of snow are discussed. Extending and relating this work to the interaction of gas-phase nitric acid with the surfaces of vapor-deposited ice will also be explored.

GPM Pre-Launch Algorithm Development for Physically-Based Falling Snow Retrievals

NASA Technical Reports Server (NTRS)

Jackson, Gail Skofronick; Tokay, Ali; Kramer, Anne W.; Hudak, David

2008-01-01

In this work we compare and correlate the long time series (Nov.-March) neasurements of precipitation rate from the Parsivels and 2DVD to the passive (89, 150, 183+/-1, +/-3, +/-7 GHz) observations of NOAA's AMSU-B radiometer. There are approximately 5-8 AMSU-B overpass views of the CARE site a day. We separate the comparisons into categories of no precipitation, liquid rain and falling snow precipitation. Scatterplots between the Parsivel snowfall rates and AMSU-B brightness temperatures (TBs) did not show an exploitable relationship for retrievals. We further compared and contrasted brightness temperatures to other surface measurements such as temperature and relative humidity with equally unsatisfying results. We found that there are similar TBs (especially at 89 and 150 GHz) for cases with falling snow and for non-precipitating cases. The comparisons indicate that surface emissivity contributions to the satellite observed TB over land can add uncertainty in detecting and estimating falling snow. The newest results show that the cloud icc scattering signal in the AMSU-B data call be detected by computing clear air TBs based on CARE radiosonde data and a rough estimate of surface emissivity. That is the differences in computed TI3 and AMSU-B TB for precipitating and nonprecipitating cases are unique such that the precipitating versus lon-precipitating cases can be identified. These results require that the radiosonde releases are within an hour of the AMSU-B data and allow for three surface types: no snow on the ground, less than 5 cm snow on the ground, and greater than 5 cm on the ground (as given by ground station data). Forest fraction and measured emissivities were combined to calculate the surface emissivities. The above work and future work to incorporate knowledge about falling snow retrievals into the framework of the expected GPM Bayesian retrievals will be described during this presentation.

Surface formation, preservation, and history of low-porosity crusts at the WAIS Divide site, West Antarctica

NASA Astrophysics Data System (ADS)

Fegyveresi, John M.; Alley, Richard B.; Muto, Atsuhiro; Orsi, Anaïs J.; Spencer, Matthew K.

2018-01-01

Observations at the West Antarctic Ice Sheet (WAIS) Divide site show that near-surface snow is strongly altered by weather-related processes such as strong winds and temperature fluctuations, producing features that are recognizable in the deep ice core. Prominent glazed surface crusts develop frequently at the site during summer seasons. Surface, snow pit, and ice core observations made in this study during summer field seasons from 2008-2009 to 2012-2013, supplemented by automated weather station (AWS) data with short- and longwave radiation sensors, revealed that such crusts formed during relatively low-wind, low-humidity, clear-sky periods with intense daytime sunshine. After formation, such glazed surfaces typically developed cracks in a polygonal pattern likely from thermal contraction at night. Cracking was commonest when several clear days occurred in succession and was generally followed by surface hoar growth; vapor escaping through the cracks during sunny days may have contributed to the high humidity that favored nighttime formation of surface hoar. Temperature and radiation observations show that daytime solar heating often warmed the near-surface snow above the air temperature, contributing to upward mass transfer, favoring crust formation from below, and then surface hoar formation. A simple surface energy calculation supports this observation. Subsequent examination of the WDC06A deep ice core revealed that crusts are preserved through the bubbly ice, and some occur in snow accumulated during winters, although not as commonly as in summertime deposits. Although no one has been on site to observe crust formation during winter, it may be favored by greater wintertime wind packing from stronger peak winds, high temperatures and steep temperature gradients from rapid midwinter warmings reaching as high as -15 °C, and perhaps longer intervals of surface stability. Time variations in crust occurrence in the core may provide paleoclimatic information, although additional studies are required. Discontinuity and cracking of crusts likely explain why crusts do not produce significant anomalies in other paleoclimatic records.

Surface studies of water isotopes in Antarctica for quantitative interpretation of deep ice core data

NASA Astrophysics Data System (ADS)

Landais, Amaelle; Casado, Mathieu; Prié, Frédéric; Magand, Olivier; Arnaud, Laurent; Ekaykin, Alexey; Petit, Jean-Robert; Picard, Ghislain; Fily, Michel; Minster, Bénédicte; Touzeau, Alexandra; Goursaud, Sentia; Masson-Delmotte, Valérie; Jouzel, Jean; Orsi, Anaïs

2017-07-01

Polar ice cores are unique climate archives. Indeed, most of them have a continuous stratigraphy and present high temporal resolution of many climate variables in a single archive. While water isotopic records (δD or δ18O) in ice cores are often taken as references for past atmospheric temperature variations, their relationship to temperature is associated with a large uncertainty. Several reasons are invoked to explain the limitation of such an approach; in particular, post-deposition effects are important in East Antarctica because of the low accumulation rates. The strong influence of post-deposition processes highlights the need for surface polar research programs in addition to deep drilling programs. We present here new results on water isotopes from several recent surface programs, mostly over East Antarctica. Together with previously published data, the new data presented in this study have several implications for the climatic reconstructions based on ice core isotopic data: (1) The spatial relationship between surface mean temperature and mean snow isotopic composition over the first meters in depth can be explained quite straightforwardly using simple isotopic models tuned to d-excess vs. δ18O evolution in transects on the East Antarctic sector. The observed spatial slopes are significantly higher (∼ 0.7-0.8‰·°C-1 for δ18O vs. temperature) than seasonal slopes inferred from precipitation data at Vostok and Dome C (0.35 to 0.46‰·°C-1). We explain these differences by changes in condensation versus surface temperature between summer and winter in the central East Antarctic plateau, where the inversion layer vanishes in summer. (2) Post-deposition effects linked to exchanges between the snow surface and the atmospheric water vapor lead to an evolution of δ18O in the surface snow, even in the absence of any precipitation event. This evolution preserves the positive correlation between the δ18O of snow and surface temperature, but is associated with a much slower δ18O-vs-temperature slope than the slope observed in the seasonal precipitation. (3) Post-deposition effects clearly limit the archiving of high-resolution (seasonal) climatic variability in the polar snow, but we suggest that sites with an accumulation rate of the order of 40 kg.m-2.yr-1 may record a seasonal cycle at shallow depths.

In Situ Observations of Snow Metamorphosis Acceleration Induced by Dust and Black Carbon

NASA Astrophysics Data System (ADS)

Schneider, A. M.; Flanner, M.

2017-12-01

Previous studies demonstrate the dependence of shortwave infrared (SWIR) reflectance on snow specific surface area (SSA) and others examine the direct darkening effect dust and black carbon (BC) deposition has on snow and ice-covered surfaces. The extent to which these light absorbing aerosols (LAAs) accelerate snow metamorphosis, however, is challenging to assess in situ as measurement techniques easily disturb snowpack. Here, we use two Near-Infrared Emitting Reflectance Domes (NERDs) to measure 1300 and 1550nm bidirectional reflectance factors (BRFs) of natural snow and experimental plots with added dust and BC. We obtain NERD measurements and subsequently collect and transport snow samples to the nearby U.S. Army Corps of Engineers' Cold Regions Research and Engineering Lab for micro computed tomography (micro-CT) analysis. Snow 1300 (1550) nm BRFs evolve from 0.6 (0.15) in fresh snow to 0.2 (0.03) after metamorphosis. Hourly-scale time evolving snow surface BRFs and SSA estimates from micro-CT reveal more rapid SWIR darkening and snow metamorphosis in contaminated versus natural plots. Cloudiness and high wind speeds can completely obscure these results if LAAs mobilize before absorbing enough radiant energy. These findings verify experimentally that dust and BC deposition can accelerate snow metamorphosis and enhance snow albedo feedback in sunny, calm weather conditions. Although quantifying the enhancement of snow albedo feedback induced by LAAs requires further surface temperature, solar irradiance, and impurity concentration measurements, this study provides experimental verification of positive feedback occurring where dust and BC accelerate snow metamorphosis.

Climate Sensitivity to Realistic Solar Heating of Snow and Ice

NASA Astrophysics Data System (ADS)

Flanner, M.; Zender, C. S.

2004-12-01

Snow and ice-covered surfaces are highly reflective and play an integral role in the planetary radiation budget. However, GCMs typically prescribe snow reflection and absorption based on minimal knowledge of snow physical characteristics. We performed climate sensitivity simulations with the NCAR CCSM including a new physically-based multi-layer snow radiative transfer model. The model predicts the effects of vertically resolved heating, absorbing aerosol, and snowpack transparency on snowpack evolution and climate. These processes significantly reduce the model's near-infrared albedo bias over deep snowpacks. While the current CCSM implementation prescribes all solar radiative absorption to occur in the top 2 cm of snow, we estimate that about 65% occurs beneath this level. Accounting for the vertical distribution of snowpack heating and more realistic reflectance significantly alters snowpack depth, surface albedo, and surface air temperature over Northern Hemisphere regions. Implications for the strength of the ice-albedo feedback will be discussed.

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.

Changing Seasonality of Tundra Vegetation and Associated Climatic Variables

NASA Astrophysics Data System (ADS)

Bhatt, U. S.; Walker, D. A.; Raynolds, M. K.; Bieniek, P.; Epstein, H. E.; Comiso, J. C.; Pinzon, J.; Tucker, C. J.; Steele, M.; Ermold, W. S.; Zhang, J.

2014-12-01

This study documents changes in the seasonality of tundra vegetation productivity and its associated climate variables using long-term data sets. An overall increase of Pan-Arctic tundra greenness potential corresponds to increased land surface temperatures and declining sea ice concentrations. While sea ice has continued to decline, summer land surface temperature and vegetation productivity increases have stalled during the last decade in parts of the Arctic. To understand the processes behind these features we investigate additional climate parameters. This study employs remotely sensed weekly 25-km sea ice concentration, weekly surface temperature, and bi-weekly NDVI from 1982 to 2013. Maximum NDVI (MaxNDVI, Maximum Normalized Difference Vegetation Index), Time Integrated NDVI (TI-NDVI), Summer Warmth Index (SWI, sum of degree months above freezing during May-August), ocean heat content (PIOMAS, model incorporating ocean data assimilation), and snow water equivalent (GlobSnow, assimilated snow data set) are explored. We analyzed the data for the full period (1982-2013) and for two sub-periods (1982-1998 and 1999-2013), which were chosen based on the declining Pan-Arctic SWI since 1998. MaxNDVI has increased from 1982-2013 over most of the Arctic but has declined from 1999 to 2013 over western Eurasia, northern Canada, and southwest Alaska. TI-NDVI has trends that are similar to those for MaxNDVI for the full period but displays widespread declines over the 1999-2013 period. Therefore, as the MaxNDVI has continued to increase overall for the Arctic, TI-NDVI has been declining since 1999. SWI has large relative increases over the 1982-2013 period in eastern Canada and Greenland and strong declines in western Eurasia and southern Canadian tundra. Weekly Pan-Arctic tundra land surface temperatures warmed throughout the summer during the 1982-1998 period but display midsummer declines from 1999-2013. Weekly snow water equivalent over Arctic tundra has declined over most seasons but shows slight increases in spring in North America and during fall over Eurasia. Later spring or earlier fall snow cover can both lead to reductions in TI-NDVI. The time-varying spatial patterns of NDVI trends can be largely explained using either snow cover or land surface temperature trends.

Soil thermal dynamics, snow cover, and frozen depth under five temperature treatments in an ombrotrophic bog: Constrained forecast with data assimilation: Forecast With Data Assimilation

DOE PAGES

Huang, Yuanyuan; Jiang, Jiang; Ma, Shuang; ...

2017-08-18

We report that accurate simulation of soil thermal dynamics is essential for realistic prediction of soil biogeochemical responses to climate change. To facilitate ecological forecasting at the Spruce and Peatland Responses Under Climatic and Environmental change site, we incorporated a soil temperature module into a Terrestrial ECOsystem (TECO) model by accounting for surface energy budget, snow dynamics, and heat transfer among soil layers and during freeze-thaw events. We conditioned TECO with detailed soil temperature and snow depth observations through data assimilation before the model was used for forecasting. The constrained model reproduced variations in observed temperature from different soil layers,more » the magnitude of snow depth, the timing of snowfall and snowmelt, and the range of frozen depth. The conditioned TECO forecasted probabilistic distributions of soil temperature dynamics in six soil layers, snow, and frozen depths under temperature treatments of +0.0, +2.25, +4.5, +6.75, and +9.0°C. Air warming caused stronger elevation in soil temperature during summer than winter due to winter snow and ice. And soil temperature increased more in shallow soil layers in summer in response to air warming. Whole ecosystem warming (peat + air warmings) generally reduced snow and frozen depths. The accuracy of forecasted snow and frozen depths relied on the precision of weather forcing. Uncertainty is smaller for forecasting soil temperature but large for snow and frozen depths. Lastly, timely and effective soil thermal forecast, constrained through data assimilation that combines process-based understanding and detailed observations, provides boundary conditions for better predictions of future biogeochemical cycles.« less

Soil thermal dynamics, snow cover, and frozen depth under five temperature treatments in an ombrotrophic bog: Constrained forecast with data assimilation: Forecast With Data Assimilation

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

Huang, Yuanyuan; Jiang, Jiang; Ma, Shuang

We report that accurate simulation of soil thermal dynamics is essential for realistic prediction of soil biogeochemical responses to climate change. To facilitate ecological forecasting at the Spruce and Peatland Responses Under Climatic and Environmental change site, we incorporated a soil temperature module into a Terrestrial ECOsystem (TECO) model by accounting for surface energy budget, snow dynamics, and heat transfer among soil layers and during freeze-thaw events. We conditioned TECO with detailed soil temperature and snow depth observations through data assimilation before the model was used for forecasting. The constrained model reproduced variations in observed temperature from different soil layers,more » the magnitude of snow depth, the timing of snowfall and snowmelt, and the range of frozen depth. The conditioned TECO forecasted probabilistic distributions of soil temperature dynamics in six soil layers, snow, and frozen depths under temperature treatments of +0.0, +2.25, +4.5, +6.75, and +9.0°C. Air warming caused stronger elevation in soil temperature during summer than winter due to winter snow and ice. And soil temperature increased more in shallow soil layers in summer in response to air warming. Whole ecosystem warming (peat + air warmings) generally reduced snow and frozen depths. The accuracy of forecasted snow and frozen depths relied on the precision of weather forcing. Uncertainty is smaller for forecasting soil temperature but large for snow and frozen depths. Lastly, timely and effective soil thermal forecast, constrained through data assimilation that combines process-based understanding and detailed observations, provides boundary conditions for better predictions of future biogeochemical cycles.« less

Inventory of File nam.t00z.awip2000.tm00.grib2

Science.gov Websites

analysis Pressure Reduced to MSL [Pa] 002 1 hybrid level RIME analysis Rime Factor [non-dim] 003 surface Temperature [K] 014 surface WEASD analysis Water Equivalent of Accumulated Snow Depth [kg/m^2] 015 2 m above ^2] 021 surface WEASD 0-0 day acc f Water Equivalent of Accumulated Snow Depth [kg/m^2] 022 surface

Modelling the physical multiphase interactions of HNO3 between snow and air on the Antarctic Plateau (Dome C) and coast (Halley)

NASA Astrophysics Data System (ADS)

Chan, Hoi Ga; Frey, Markus M.; King, Martin D.

2018-02-01

Emissions of nitrogen oxide (NOx = NO + NO2) from the photolysis of nitrate (NO3-) in snow affect the oxidising capacity of the lower troposphere especially in remote regions of high latitudes with little pollution. Current air-snow exchange models are limited by poor understanding of processes and often require unphysical tuning parameters. Here, two multiphase models were developed from physically based parameterisations to describe the interaction of nitrate between the surface layer of the snowpack and the overlying atmosphere. The first model is similar to previous approaches and assumes that below a threshold temperature, To, the air-snow grain interface is pure ice and above To a disordered interface (DI) emerges covering the entire grain surface. The second model assumes that air-ice interactions dominate over all temperatures below melting of ice and that any liquid present above the eutectic temperature is concentrated in micropockets. The models are used to predict the nitrate in surface snow constrained by year-round observations of mixing ratios of nitric acid in air at a cold site on the Antarctic Plateau (Dome C; 75°06' S, 123°33' E; 3233 m a.s.l.) and at a relatively warm site on the Antarctic coast (Halley; 75°35' S, 26°39' E; 35 m a.s.l). The first model agrees reasonably well with observations at Dome C (Cv(RMSE) = 1.34) but performs poorly at Halley (Cv(RMSE) = 89.28) while the second model reproduces with good agreement observations at both sites (Cv(RMSE) = 0.84 at both sites). It is therefore suggested that in winter air-snow interactions of nitrate are determined by non-equilibrium surface adsorption and co-condensation on ice coupled with solid-state diffusion inside the grain, similar to Bock et al. (2016). In summer, however, the air-snow exchange of nitrate is mainly driven by solvation into liquid micropockets following Henry's law with contributions to total surface snow NO3- concentrations of 75 and 80 % at Dome C and Halley, respectively. It is also found that the liquid volume of the snow grain and air-micropocket partitioning of HNO3 are sensitive to both the total solute concentration of mineral ions within the snow and pH of the snow. The second model provides an alternative method to predict nitrate concentration in the surface snow layer which is applicable over the entire range of environmental conditions typical for Antarctica and forms a basis for a future full 1-D snowpack model as well as parameterisations in regional or global atmospheric chemistry models.

Objective Characterization of Snow Microstructure for Microwave Emission Modeling

NASA Technical Reports Server (NTRS)

Durand, Michael; Kim, Edward J.; Molotch, Noah P.; Margulis, Steven A.; Courville, Zoe; Malzler, Christian

2012-01-01

Passive microwave (PM) measurements are sensitive to the presence and quantity of snow, a fact that has long been used to monitor snowcover from space. In order to estimate total snow water equivalent (SWE) within PM footprints (on the order of approx 100 sq km), it is prerequisite to understand snow microwave emission at the point scale and how microwave radiation integrates spatially; the former is the topic of this paper. Snow microstructure is one of the fundamental controls on the propagation of microwave radiation through snow. Our goal in this study is to evaluate the prospects for driving the Microwave Emission Model of Layered Snowpacks with objective measurements of snow specific surface area to reproduce measured brightness temperatures when forced with objective measurements of snow specific surface area (S). This eliminates the need to treat the grain size as a free-fit parameter.

[Measurement and estimation methods and research progress of snow evaporation in forests].

PubMed

Li, Hui-Dong; Guan, De-Xin; Jin, Chang-Jie; Wang, An-Zhi; Yuan, Feng-Hui; Wu, Jia-Bing

2013-12-01

Accurate measurement and estimation of snow evaporation (sublimation) in forests is one of the important issues to the understanding of snow surface energy and water balance, and it is also an essential part of regional hydrological and climate models. This paper summarized the measurement and estimation methods of snow evaporation in forests, and made a comprehensive applicability evaluation, including mass-balance methods (snow water equivalent method, comparative measurements of snowfall and through-snowfall, snow evaporation pan, lysimeter, weighing of cut tree, weighing interception on crown, and gamma-ray attenuation technique) and micrometeorological methods (Bowen-ratio energy-balance method, Penman combination equation, aerodynamics method, surface temperature technique and eddy covariance method). Also this paper reviewed the progress of snow evaporation in different forests and its influencal factors. At last, combining the deficiency of past research, an outlook for snow evaporation rearch in forests was presented, hoping to provide a reference for related research in the future.

Effect of Photodesorption on the Snow Lines at the Surface of Optically Thick Circumstellar Disks around Herbig Ae/Be Stars

NASA Astrophysics Data System (ADS)

Oka, Akinori; Inoue, Akio K.; Nakamoto, Taishi; Honda, Mitsuhiko

2012-03-01

We investigate the effect of photodesorption on the snow line position at the surface of a protoplanetary disk around a Herbig Ae/Be star, motivated by the detection of water ice particles at the surface of the disk around HD142527 by Honda et al. For this aim, we obtain the density and temperature structure in the disk with a 1+1D radiative transfer and determine the distribution of water ice particles in the disk by the balance between condensation, sublimation, and photodesorption. We find that photodesorption induced by far-ultraviolet radiation from the central star depresses the ice-condensation front toward the mid-plane and pushes the surface snow line significantly outward when the stellar effective temperature exceeds a certain critical value. This critical effective temperature depends on the stellar luminosity and mass, the water abundance in the disk, and the yield of photodesorption. We present an approximate analytic formula for the critical temperature. We separate Herbig Ae/Be stars into two groups on the HR diagram according to the critical temperature: one is the disks where photodesorption is effective and from which we may not find ice particles at the surface, and the other is the disks where photodesorption is not effective. We estimate the snow line position at the surface of the disk around HD142527 to be 100-300 AU, which is consistent with the water ice detection at >140 AU in the disk. All the results depend on the dust grain size in a complex way, and this point requires more work in the future.

Soil Moisture and Snow Cover: Active or Passive Elements of Climate?

NASA Technical Reports Server (NTRS)

Oglesby, Robert J.; Marshall, Susan; Erickson, David J., III; Robertson, Franklin R.; Roads, John O.; Arnold, James E. (Technical Monitor)

2002-01-01

A key question in the study of the hydrologic cycle is the extent to which surface effects such as soil moisture and snow cover are simply passive elements or whether they can affect the evolution of climate on seasonal and longer time scales. We have constructed ensembles of predictability studies using the NCAR CCM3 in which we compared the relative roles of initial surface and atmospheric conditions over the central and western U.S. in determining the subsequent evolution of soil moisture and of snow cover. We have also made sensitivity studies with exaggerated soil moisture and snow cover anomalies in order to determine the physical processes that may be important. Results from simulations with realistic soil moisture anomalies indicate that internal climate variability may be the strongest factor, with some indication that the initial atmospheric state is also important. The initial state of soil moisture does not appear important, a result that held whether simulations were started in late winter or late spring. Model runs with exaggerated soil moisture reductions (near-desert conditions) showed a much larger effect, with warmer surface temperatures, reduced precipitation, and lower surface pressures; the latter indicating a response of the atmospheric circulation. These results suggest the possibility of a threshold effect in soil moisture, whereby an anomaly must be of a sufficient size before it can have a significant impact on the atmospheric circulation and hence climate. Results from simulations with realistic snow cover anomalies indicate that the time of year can be crucial. When introduced in late winter, these anomalies strongly affected the subsequent evolution of snow cover. When introduced in early winter, however, little or no effect is seen on the subsequent snow cover. Runs with greatly exaggerated initial snow cover indicate that the high reflectively of snow is the most important process by which snow cover cart impact climate, through lower surface temperatures and increased surface pressures. In early winter, the amount of solar radiation is very small and so this albedo effect is inconsequential while in late winter, with the sun higher in the sky and period of daylight longer, the effect is much stronger.

Geographical Distribution of Thundersnow and their Properties from GPM Ku-band Radar

NASA Astrophysics Data System (ADS)

Adhikari, A.; Liu, C.

2017-12-01

Lightning in snow and freezing rain are relatively uncommon, compared to the warm season thunderstorm. These events can be identified by lightning with the surface temperature colder than 0oC, or named as "cold lightning", A six-years of "cold lightning" characteristics and climatology, including seasonal, diurnal, and surface temperature distribution, are generated after collocating WWLLN and NLDN lightning with ERA-Interim 2 meter temperature. The thundersnow cases are further identified with all vertical temperature profile below 0oC, and the freezing rain cases have temperature warmer than 4oC somewhere in the column above the freezing surface. The statistics of thundersnow events from WWLLN and NLDN are compared over the United States (US). Though with different detection efficiency, WWLLN and NLDN demonstrate almost identical geographical distribution of thundersnow over the US. Taking the full advantage of the Global Precipitation Measuring Mission (GPM) Ku band radar, Thunder Snow Features (TSFs) are defined with contiguous area of non-zero near surface snow precipitation derived from Ku radar along with the collocated WWLLN lightning strikes. Though only a small number of TSFs are identified with three year GPM data, all TSFs have maximum radar reflectivity above 30 dBZ at temperature colder than -10oC, which indicates the importance of non-inductive charging in these events.

Satellite-derived, melt-season surface temperature of the Greenland Ice Sheet (2000-2005) and its relationship to mass balance

USGS Publications Warehouse

Hall, D.K.; Williams, R.S.; Casey, K.A.; DiGirolamo, N.E.; Wan, Z.

2006-01-01

Mean, clear-sky surface temperature of the Greenland Ice Sheet was measured for each melt season from 2000 to 2005 using Moderate-Resolution Imaging Spectroradiometer (MODIS)–derived land-surface temperature (LST) data-product maps. During the period of most-active melt, the mean, clear-sky surface temperature of the ice sheet was highest in 2002 (−8.29 ± 5.29°C) and 2005 (−8.29 ± 5.43°C), compared to a 6-year mean of −9.04 ± 5.59°C, in agreement with recent work by other investigators showing unusually extensive melt in 2002 and 2005. Surface-temperature variability shows a correspondence with the dry-snow facies of the ice sheet; a reduction in area of the dry-snow facies would indicate a more-negative mass balance. Surface-temperature variability generally increased during the study period and is most pronounced in the 2005 melt season; this is consistent with surface instability caused by air-temperature fluctuations.

Snow Cover Mapping at the Continental to Global Scale Using Combined Visible and Passive Microwave Satellite Data

NASA Astrophysics Data System (ADS)

Armstrong, R. L.; Brodzik, M.; Savoie, M. H.

2007-12-01

Over the past several decades both visible and passive microwave satellite data have been utilized for snow mapping at the continental to global scale. Snow mapping using visible data has been based primarily on the magnitude of the surface reflectance, and in more recent cases on specific spectral signatures, while microwave data can be used to identify snow cover because the microwave energy emitted by the underlying soil is scattered by the snow grains resulting in a sharp decrease in brightness temperature and a characteristic negative spectral gradient. Both passive microwave and visible data sets indicate 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. We describe the respective problems as well as the advantages and disadvantages of these two types of satellite data for snow cover mapping and demonstrate how a multi-sensor approach is optimal. For the period 1978 to present we combine data from the NOAA weekly snow charts with snow cover derived from the SMMR and SSM/I brightness temperature data. For the period since 2002 we blend NASA EOS MODIS and AMSR-E data sets. Our current product incorporates MODIS data from the Climate Modelers Grid (CMG) at approximately 5 km (0.05 deg.) with microwave-derived snow water equivalent (SWE) at 25 km, resulting in a blended product that includes percent snow cover in the larger grid cell whenever the microwave SWE signal is absent. Validation of AMSR-E at the brightness temperature level is provided through the comparison with data from the well-calibrated heritage SSM/I sensor over large homogeneous snow-covered surfaces (e.g. Dome C region, Antarctica). We also describe how the application of the higher frequency microwave channels (85 and 89 GHz)enhances accurate mapping of shallow and intermittent snow cover.

MODIS Snow and Ice Production

NASA Technical Reports Server (NTRS)

Hall, Dorthoy K.; Hoser, Paul (Technical Monitor)

2002-01-01

Daily, global snow cover maps, and sea ice cover and sea ice surface temperature (IST) maps are derived from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS), are available at no cost through the National Snow and Ice Data Center (NSIDC). Included on this CD-ROM are samples of the MODIS snow and ice products. In addition, an animation, done by the Scientific Visualization studio at Goddard Space Flight Center, is also included.

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.

A Physical Model to Determine Snowfall over Land by Microwave Radiometry

NASA Technical Reports Server (NTRS)

Skofronick-Jackson, G.; Kim, M.-J.; Weinman, J. A.; Chang, D.-E.

2003-01-01

Because microwave brightness temperatures emitted by snow covered surfaces are highly variable, snowfall above such surfaces is difficult to observe using window channels that occur at low frequencies (v less than 100 GHz). Furthermore, at frequencies v less than or equal to 37 GHz, sensitivity to liquid hydrometeors is dominant. These problems are mitigated at high frequencies (v greater than 100 GHz) where water vapor screens the surface emission and sensitivity to frozen hydrometeors is significant. However the scattering effect of snowfall in the atmosphere at those higher frequencies is also impacted by water vapor in the upper atmosphere. This work describes the methodology and results of physically-based retrievals of snow falling over land surfaces. The theory of scattering by randomly oriented dry snow particles at high microwave frequencies appears to be better described by regarding snow as a concatenation of equivalent ice spheres rather than as a sphere with the effective dielectric constant of an air-ice mixture. An equivalent sphere snow scattering model was validated against high frequency attenuation measurements. Satellite-based high frequency observations from an Advanced Microwave Sounding Unit (AMSU-B) instrument during the March 5-6, 2001 New England blizzard were used to retrieve snowfall over land. Vertical distributions of snow, temperature and relative humidity profiles were derived from the Pennsylvania State University-National Center for Atmospheric Research (PSU-NCAR) fifth-generation Mesoscale Model (MM5). Those data were applied and modified in a radiative transfer model that derived brightness temperatures consistent with the AMSU-B observations. The retrieved snowfall distribution was validated with radar reflectivity measurements obtained from the National Oceanic and Atmospheric Administration (NOAA) National Weather Service (NWS) ground-based radar network.

Seasonal variations of the backscattering coefficient measured by radar altimeters over the Antarctic Ice Sheet

NASA Astrophysics Data System (ADS)

Ibrahime Adodo, Fifi; Remy, Frédérique; Picard, Ghislain

2018-05-01

Spaceborne radar altimeters are a valuable tool for observing the Antarctic Ice Sheet. The radar wave interaction with the snow provides information on both the surface and the subsurface of the snowpack due to its dependence on the snow properties. However, the penetration of the radar wave within the snowpack also induces a negative bias on the estimated surface elevation. Empirical corrections of this space- and time-varying bias are usually based on the backscattering coefficient variability. We investigate the spatial and seasonal variations of the backscattering coefficient at the S (3.2 GHz ˜ 9.4 cm), Ku (13.6 GHz ˜ 2.3 cm) and Ka (37 GHz ˜ 0.8 cm) bands. We identified that the backscattering coefficient at Ku band reaches a maximum in winter in part of the continent (Region 1) and in the summer in the remaining (Region 2), while the evolution at other frequencies is relatively uniform over the whole continent. To explain this contrasting behavior between frequencies and between regions, we studied the sensitivity of the backscattering coefficient at three frequencies to several parameters (surface snow density, snow temperature and snow grain size) using an electromagnetic model. The results show that the seasonal cycle of the backscattering coefficient at Ka frequency is dominated by the volume echo and is mainly driven by snow temperature evolution everywhere. In contrast, at S band, the cycle is dominated by the surface echo. At Ku band, the seasonal cycle is dominated by the volume echo in Region 1 and by the surface echo in Region 2. This investigation provides new information on the seasonal dynamics of the Antarctic Ice Sheet surface and provides new clues to build more accurate corrections of the radar altimeter surface elevation signal in the future.

Monitoring the Impacts of Forest Management on Snowpack Duration

NASA Astrophysics Data System (ADS)

O'Halloran, T.; Tyler, S.; Gaffney, R.; Pai, H.

2017-12-01

Seasonal snowpack constitutes a significant portion of the hydrologic budget in mountain watersheds and influences dynamic (e.g., runoff magnitude and timing, soil moisture availability) and energetic processes (e.g., surface-atmosphere energy fluxes, ground temperature). Altered forest structure can affect snow accumulation and ablation. As part of a long-term monitoring project, this work examines the impact of forest management practices on snow cover in Lassen National Forest, California. We deployed a fiber optic distributed temperature sensing (DTS) cable and multiple meteorological stations in thinned, clear-cut, and untreated areas of forest. The DTS data was collected at 1 meter spatial intervals every 4 hours from February to May 2017. To determine snow cover, daily temperature variations were examined along locations of the DTS cable associated with our areas of interest. Between the various treatments, snow duration was greater in both clear-cut and untreated forest compared to the thinned area. However, snow duration varied by only six days. We also investigated other meteorological forcings, such as average winter temperature and precipitation, which coupled with forest modifications could explain snow duration in our study.

Studies of snowpack properties by passive microwave radiometry

NASA Technical Reports Server (NTRS)

Chang, A. T. C.; Hall, D. K.; Foster, J. L.; Rango, A.; Schmugge, T. J.

1978-01-01

Research involving the microwave characteristics of snow was undertaken in order to expand the information content currently available from remote sensing, namely the measurement of snowcovered area. Microwave radiation emitted from beneath the snow surface can be sensed and thus permits information on internal snowpack properties to be inferred. The intensity of radiation received is a function of the average temperature and emissivity of the snow layers and is commonly referred to as the brightness temperature (T sub b). The T sub b varies with snow grain and crystal sizes, liquid water content and snowpack temperature. The T sub b of the 0.8 cm wavelength channel was found to decrease moreso with increasing snow depth than the 1.4 cm channel. More scattering of the shorter wavelength radiation occurs thus resulting in a lower T sub b for shorter wavelengths in a dry snowpack. The longer 21.0 cm wavelength was used to assess the condition of the underlying ground. Ultimately it may be possible to estimate snow volume over large areas using calibrated brightness temperatures and consequently improve snowmelt runoff predictions.

Snow control on active layer and permafrost in steep alpine rock walls (Aiguille du Midi, 3842 m a.s.l, Mont Blanc massif)

NASA Astrophysics Data System (ADS)

Magnin, Florence; Westermann, Sebastian; Pogliotti, Paolo; Ravanel, Ludovic; Deline, Philip

2016-04-01

Permafrost degradation through the thickening of the active layer and the rising temperature at depth is a crucial process of rock wall stability. The ongoing increase in rock falls observed during hot periods in mid-latitude mountain ranges is regarded as a result of permafrost degradation. However, the short-term thermal dynamics of alpine rock walls are misunderstood since they result of complex processes related to the interaction of local climate variables, heterogeneous snow cover and heat transfers. As a consequence steady-state and long-term changes that can be approached with simpler process mainly related to air temperature, solar radiations and heat conduction were the most common dynamics to be studied so far. The effect of snow on the bedrock surface temperature is increasingly investigated and has already been demonstrated to be an essential factor of permafrost distribution. Nevertheless, its effect on the year-to-year changes of the active layer thickness and of the permafrost temperature in steep alpine bedrock has not been investigated yet, partly due to the lack of appropriate data. We explore the role of snow accumulations on the active layer and permafrost thermal regime of steep rock walls of a high-elevated site, the Aiguille du Midi (AdM, 3842 m a.s.l, Mont Blanc massif, Western European Alps) by mean of a multi-methods approach. We first analyse six years of temperature records in three 10-m-deep boreholes. Then we describe the snow accumulation patterns on two rock faces by means of automatically processed camera records. Finally, sensitivity analyses of the active layer thickness and permafrost temperature towards timing and magnitude of snow accumulations are performed using the numerical permafrost model CryoGrid 3. The energy balance module is forced with local meteorological measurements on the AdM S face and validated with surface temperature measurements at the weather station location. The heat conduction scheme is calibrated with the temperature measurements in the S-exposed borehole. Results show that the snow may be responsible for permafrost presence while it is absent in the surrounding snow free bedrock. The long lasting of the snow at high elevation, where it can remain until the mid-summer has a delaying effect on the seasonal thaw, which contributes to the lowering of the active layer thickness.

MELIFT - A new device for accurate measurements in a snow rich environment

NASA Astrophysics Data System (ADS)

Dorninger, M.

2012-04-01

A deep snow pack, remote locations, no external power supply and very low temperatures are often the main ingredients when it comes to the deployment of meteorological stations in mountainous terrain. The accurate position of the sensor related to the snow surface is normally not known. A new device called METLIFT overcomes the problems. WMO recommends a height between 1.2 m and 2 m above ground level for the measurement of air temperature and humidity. The height above ground level is specified to take care of the possible strong vertical temperature and humidity gradients at the lowest layers in the atmosphere. Especially in snow rich and remote locations it may be hardly possible to follow this advice. Therefore most of the meteorological stations in mountainous terrain are situated at mountain tops where strong winds will blow off the snow or in valleys where a daily inspection of the sensors is possible. In other unpopulated mountainous areas, e.g. basins, plateaus, the distance of the sensor to the snow surface is not known or the sensor will be snow-covered. A new device was developed to guarantee the sensor height above surface within the WMO limits in harsh and remote environments. An ultrasonic snow height sensor measures the distance to the snow surface. If it exceeds certain limits due to snow accumulation or snow melt the lift adapts its height accordingly. The prototype of METLIFT has been installed in Lower Austria at an altitude of 1000m. The lift is 6 m high and can pull out for another 4 m. Sensor arms are mounted every meter to allow the connection of additional sensors or to measure a profile of a certain parameter of the lowest 5 m above surface. Sensors can be added easily since cable wiring is provided to each sensor arm. Horizontal winds are measured at 7 m height above surface. METLIFT is independent of external power supply. Three lead gel accumulators recharged by three solar panels provide the energy necessary for the sensors, the data loggers, the data transmission components and for the electromotor to lift the system. METLIFT is energy optimised to keep the energy consumption at low levels. The components of the lift device consist of a 12V electromotor with a worm gear with a transmission rate of 2856:1. This means that the lift moves extremely slow. The data logger can be programmed via the GSM connection from remote locations, the data flow is also conducted via this connection. First results of the winter campaign 2011/2012 will be presented at the conference.

Microwave remote sensing of snowpacks

NASA Technical Reports Server (NTRS)

Stiles, W. H.; Ulaby, F. T.

1980-01-01

The interaction mechanisms responsible for the microwave backscattering and emission behavior of snow were investigated, and models were developed relating the backscattering coefficient (sigma) and apparent temperature (T) to the physical parameters of the snowpack. The microwave responses to snow wetness, snow water equivalent, snow surface roughness, and to diurnal variations were investigated. Snow wetness was shown to have an increasing effect with increasing frequency and angle of incidence for both active and passive cases. Increasing snow wetness was observed to decrease the magnitude sigma and increase T. Snow water equivalent was also observed to exhibit a significant influence sigma and T. Snow surface configuration (roughness) was observed to be significant only for wet snow surface conditions. Diurnal variations were as large as 15 dB for sigma at 35 GHz and 120 K for T at 37 GHz. Simple models for sigma and T of a snowpack scene were developed in terms of the most significant ground-truth parameters. The coefficients for these models were then evaluated; the fits to the sigma and T measurements were generally good. Finally, areas of needed additional observations were outlined and experiments were specified to further the understanding of the microwave-snowpack interaction mechanisms.

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.

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.

A new MRI land surface model HAL

NASA Astrophysics Data System (ADS)

Hosaka, M.

2011-12-01

A land surface model HAL is newly developed for MRI-ESM1. It is used for the CMIP simulations. HAL consists of three submodels: SiByl (vegetation), SNOWA (snow) and SOILA (soil) in the current version. It also contains a land coupler LCUP which connects some submodels and an atmospheric model. The vegetation submodel SiByl has surface vegetation processes similar to JMA/SiB (Sato et al. 1987, Hirai et al. 2007). SiByl has 2 vegetation layers (canopy and grass) and calculates heat, moisture, and momentum fluxes between the land surface and the atmosphere. The snow submodel SNOWA can have any number of snow layers and the maximum value is set to 8 for the CMIP5 experiments. Temperature, SWE, density, grain size and the aerosol deposition contents of each layer are predicted. The snow properties including the grain size are predicted due to snow metamorphism processes (Niwano et al., 2011), and the snow albedo is diagnosed from the aerosol mixing ratio, the snow properties and the temperature (Aoki et al., 2011). The soil submodel SOILA can also have any number of soil layers, and is composed of 14 soil layers in the CMIP5 experiments. The temperature of each layer is predicted by solving heat conduction equations. The soil moisture is predicted by solving the Darcy equation, in which hydraulic conductivity depends on the soil moisture. The land coupler LCUP is designed to enable the complicated constructions of the submidels. HAL can include some competing submodels (precise and detailed ones, and simpler ones), and they can run at the same simulations. LCUP enables a 2-step model validation, in which we compare the results of the detailed submodels with the in-situ observation directly at the 1st step, and follows the comparison between them and those of the simpler ones at the 2nd step. When the performances of the detailed ones are good, we can improve the simpler ones by using the detailed ones as reference models.

The layered evolution of fabric and microstructure of snow at Point Barnola, Central East Antarctica

NASA Astrophysics Data System (ADS)

Calonne, Neige; Montagnat, Maurine; Matzl, Margret; Schneebeli, Martin

2017-02-01

Snow fabric, defined as the distribution of the c-axis orientations of the ice crystals in snow, is poorly known. So far, only one study exits that measured snow fabric based on a statistically representative technique. This recent study has revealed the impact of temperature gradient metamorphism on the evolution of fabric in natural snow, based on cold laboratory experiments. On polar ice sheets, snow properties are currently investigated regarding their strong variability in time and space, notably because of their potential influence on firn processes and consequently on ice core analysis. Here, we present measurements of fabric and microstructure of snow from Point Barnola, East Antarctica (close to Dome C). We analyzed a snow profile from 0 to 3 m depth, where temperature gradients occur. The main contributions of the paper are (1) a detailed characterization of snow in the upper meters of the ice sheet, especially by providing data on snow fabric, and (2) the study of a fundamental snow process, never observed up to now in a natural snowpack, namely the role of temperature gradient metamorphism on the evolution of the snow fabric. Snow samples were scanned by micro-tomography to measure continuous profiles of microstructural properties (density, specific surface area and pore thickness). Fabric analysis was performed using an automatic ice texture analyzer on 77 representative thin sections cut out from the samples. Different types of snow fabric could be identified and persist at depth. Snow fabric is significantly correlated with snow microstructure, pointing to the simultaneous influence of temperature gradient metamorphism on both properties. We propose a mechanism based on preferential grain growth to explain the fabric evolution under temperature gradients. Our work opens the question of how such a layered profile of fabric and microstructure evolves at depth and further influences the physical and mechanical properties of snow and firn. More generally, it opens the way to further studies on the influence of the snow fabric in snow processes related to anisotropic properties of ice such as grain growth, mechanical response, electromagnetic behavior.

A model of the planetary boundary layer over a snow surface

NASA Technical Reports Server (NTRS)

Halberstam, I.; Melendez, R.

1979-01-01

A model of the planetary boundary layer over a snow surface has been developed. It contains the vertical heat exchange processes due to radiation, conduction, and atmospheric turbulence. Parametrization of the boundary layer is based on similarity functions developed by Hoffert and Sud (1976), which involve a dimensionless variable, dependent on boundary-layer height and a localized Monin-Obukhov length. The model also contains the atmospheric surface layer and the snowpack itself, where snowmelt and snow evaporation are calculated. The results indicate a strong dependence of surface temperatures, especially at night, on the bursts of turbulence which result from the frictional damping of surface-layer winds during periods of high stability, as described by Businger (1973). The model also shows the cooling and drying effect of the snow on the atmosphere, which may be the mechanism for air mass transformation in sub-Arctic regions.

Investigating Satellite Microwave observations of Precipitation in Different Climate Regimes

NASA Astrophysics Data System (ADS)

Wang, N.; Ferraro, R. R.

2013-12-01

Microwave satellite remote sensing of precipitation over land is a challenging problem due to the highly variable land surface emissivity, which, if not properly accounted for, can be much greater than the precipitation signal itself, especially in light rain/snow conditions. Additionally, surfaces such as arid land, deserts and snow cover have brightness temperature characteristics similar to precipitation Ongoing work by GPM microwave radiometer team is constructing databases through a variety of means, however, there is much uncertainty as to what is the optimal information needed for the wide array of sensors in the GPM constellation, including examination of regional conditions. The original data sets will focus on stratification by emissivity class, surface temperature and total perceptible water. We'll perform sensitivity studies to determine the potential role of ancillary data (e.g., land surface temperature, snow cover/water equivalent, etc.) to improve precipitation estimation over land in different climate regimes, including rain and snow. In other words, what information outside of the radiances can help describe the background and subsequent departures from it that are active precipitating regions? It is likely that this information will be a function of the various precipitation regimes. Statistical methods such as Principal Component Analysis (PCA) will be utilized in this task. Databases from a variety of sources are being constructed. They include existing satellite microwave measurements of precipitating and non-precipitating conditions, ground radar precipitation rate estimates, surface emissivity climatology from satellites, surface temperature and TPW from NWP reanalysis. Results from the analysis of these databases with respect to the microwave precipitation sensitivity to the variety of environmental conditions in different climate regimes will be discussed.

Incorporation of surface albedo-temperature feedback in a one-dimensional radiative-connective climate model

NASA Technical Reports Server (NTRS)

Wang, W. C.; Stone, P. H.

1979-01-01

The feedback between ice snow albedo and temperature is included in a one dimensional radiative convective climate model. The effect of this feedback on sensitivity to changes in solar constant is studied for the current values of the solar constant and cloud characteristics. The ice snow albedo feedback amplifies global climate sensitivity by 33% and 50%, respectively, for assumptions of constant cloud altitude and constant cloud temperature.

Coupling of snow and permafrost processes using the Basic Modeling Interface (BMI)

NASA Astrophysics Data System (ADS)

Wang, K.; Overeem, I.; Jafarov, E. E.; Piper, M.; Stewart, S.; Clow, G. D.; Schaefer, K. M.

2017-12-01

We developed a permafrost modeling tool based by implementing the Kudryavtsev empirical permafrost active layer depth model (the so-called "Ku" component). The model is specifically set up to have a basic model interface (BMI), which enhances the potential coupling to other earth surface processes model components. This model is accessible through the Web Modeling Tool in Community Surface Dynamics Modeling System (CSDMS). The Kudryavtsev model has been applied for entire Alaska to model permafrost distribution at high spatial resolution and model predictions have been verified by Circumpolar Active Layer Monitoring (CALM) in-situ observations. The Ku component uses monthly meteorological forcing, including air temperature, snow depth, and snow density, and predicts active layer thickness (ALT) and temperature on the top of permafrost (TTOP), which are important factors in snow-hydrological processes. BMI provides an easy approach to couple the models with each other. Here, we provide a case of coupling the Ku component to snow process components, including the Snow-Degree-Day (SDD) method and Snow-Energy-Balance (SEB) method, which are existing components in the hydrological model TOPOFLOW. The work flow is (1) get variables from meteorology component, set the values to snow process component, and advance the snow process component, (2) get variables from meteorology and snow component, provide these to the Ku component and advance, (3) get variables from snow process component, set the values to meteorology component, and advance the meteorology component. The next phase is to couple the permafrost component with fully BMI-compliant TOPOFLOW hydrological model, which could provide a useful tool to investigate the permafrost hydrological effect.

Altitude-dependent influence of snow cover on alpine land surface phenology

NASA Astrophysics Data System (ADS)

Xie, Jing; Kneubühler, Mathias; Garonna, Irene; Notarnicola, Claudia; De Gregorio, Ludovica; De Jong, Rogier; Chimani, Barbara; Schaepman, Michael E.

2017-05-01

Snow cover impacts alpine land surface phenology in various ways, but our knowledge about the effect of snow cover on alpine land surface phenology is still limited. We studied this relationship in the European Alps using satellite-derived metrics of snow cover phenology (SCP), namely, first snow fall, last snow day, and snow cover duration (SCD), in combination with land surface phenology (LSP), namely, start of season (SOS), end of season, and length of season (LOS) for the period of 2003-2014. We tested the dependency of interannual differences (Δ) of SCP and LSP metrics with altitude (up to 3000 m above sea level) for seven natural vegetation types, four main climatic subregions, and four terrain expositions. We found that 25.3% of all pixels showed significant (p < 0.05) correlation between ΔSCD and ΔSOS and 15.3% between ΔSCD and ΔLOS across the entire study area. Correlations between ΔSCD and ΔSOS as well as ΔSCD and ΔLOS are more pronounced in the northern subregions of the Alps, at high altitudes, and on north and west facing terrain—or more generally, in regions with longer SCD. We conclude that snow cover has a greater effect on alpine phenology at higher than at lower altitudes, which may be attributed to the coupled influence of snow cover with underground conditions and air temperature. Alpine ecosystems may therefore be particularly sensitive to future change of snow cover at high altitudes under climate warming scenarios.

Improvement of Mars Surface Snow Albedo Modeling in LMD Mars GCM With SNICAR

NASA Astrophysics Data System (ADS)

Singh, D.; Flanner, M. G.; Millour, E.

2018-03-01

The current version of Laboratoire de Météorologie Dynamique (LMD) Mars GCM (original-MGCM) uses annually repeating (prescribed) CO2 snow albedo values based on the Thermal Emission Spectrometer observations. We integrate the Snow, Ice, and Aerosol Radiation (SNICAR) model with MGCM (SNICAR-MGCM) to prognostically determine H2O and CO2 snow albedos interactively in the model. Using the new diagnostic capabilities of this model, we find that cryospheric surfaces (with dust) increase the global surface albedo of Mars by 0.022. Over snow-covered regions, SNICAR-MGCM simulates mean albedo that is higher by about 0.034 than prescribed values in the original-MGCM. Globally, shortwave flux into the surface decreases by 1.26 W/m2, and net CO2 snow deposition increases by about 4% with SNICAR-MGCM over one Martian annual cycle as compared to the original-MGCM simulations. SNICAR integration reduces the mean global surface temperature and the surface pressure of Mars by about 0.87% and 2.5%, respectively. Changes in albedo also show a similar distribution to dust deposition over the globe. The SNICAR-MGCM model generates albedos with higher sensitivity to surface dust content as compared to original-MGCM. For snow-covered regions, we improve the correlation between albedo and optical depth of dust from -0.91 to -0.97 with SNICAR-MGCM as compared to the original-MGCM. Dust substantially darkens Mars's cryosphere, thereby reducing its impact on the global shortwave energy budget by more than half, relative to the impact of pure snow.

Snow micro-structure at Kongsvegen glacier, Svalbard

NASA Astrophysics Data System (ADS)

Bilgeri, F.; Karner, F.; Steinkogler, W.; Fromm, R.; Obleitner, F.; Kohler, J.

2012-04-01

Measurements of physical snow properties have been performed at several sites at Kongsvegen glacier, which is a key Arctic glacier in western Spitzbergen (79N, 13E). The data were collected at six locations along the flow line of the glacier at different elevations (161 to 741m asl.) and describe snow that was deposited during winter 2010/11. We basically consider the vertical profiles of snow temperature, density, hardness, grain size and crystal shapes derived from standard stratigraphic methods (snow pits)and measurements using advanced instruments like Snow Micropen® and NIR imagery. Some parameters were measured repeatedly and with different instruments which proves a high quality as well as long-term and spatial representativeness of the data. The general snow conditions at the end of winter are characterized by a linear increase of snow depth and water equivalent with elevation. Snow hardness also increases with elevation while density remains remarkably constant. At most sites the snow temperature, density, hardness and grain size increase from the surface towards the snow-ice interface. The surface and the bottom layers stand out by specific changes in snow signature (crystal types) and delineate the bulk of the snow pack which itself features a rather complex layering. Comparison of the high-resolution profiles measured at different elevations at the glacier suggests some principal correlations of the signatures of hardness, grain size and crystal type. Thus, some major features (e.g. particularly hard layers) can be traced along the glacier, but the high-resolution layering can not straightforwardly be related from one site to the other. This basically reflects a locally different history of the snow pack in terms of precipitation events and post-depositional snow metamorphism. The issue is investigated more quantitatively by enhanced statistical processing of the observed signatures and simulation of the history of individual layers. These studies are supported by meteorological measurements at the snow observation sites.

Impacts of absorbing aerosol deposition on snowpack and hydrologic cycle in the Rocky Mountain region using variable-resolution CESM (VR-CESM)

NASA Astrophysics Data System (ADS)

Wu, C.; Liu, X.; Lin, Z.; Rahimi-Esfarjani, S. R.; Lu, Z.

2017-12-01

Deposition of light-absorbing aerosols (LAAs) including black carbon (BC) and dust onto snow surface has been suggested to reduce the snow albedo, and modulate the snowpack and consequent hydrologic cycle. In this study we use the variable-resolution Community Earth System Model (VR-CESM) to quantify the impacts of LAAs deposition onto snow in the Rocky Mountain region (RMR) during the period of 1981-2005. We first evaluate the model simulation of LAA concentrations both in the atmosphere and in snow, and then investigate the snowpack and runoff changes induced by LAAs-in-snow. The model simulates similar magnitudes of surface atmospheric dust concentrations as observations, but underestimates surface atmospheric BC concentrations by about a factor of two. Despite of this, the magnitude of BC-in-snow concentrations is overall comparable to observations. Regional mean surface radiative effect (SRE) due to LAAs-in-snow reaches up to 0.6-1.7 W m-2 in spring, and dust contributes to about 21-43% of total SRE. Maximum surface air temperature increase due to the LLA's SRE is around 0.9-1.1oC. Snow water equivalent and snow cover fraction reduce by around 2-50 mm and 0.05-0.2, respectively in the two regions around the mountains (Eastern Snake River Plain and Southwestern Wyoming) due to positive snow-albedo feedbacks. During the snow melting period, LAAs accelerate the hydrologic cycle with runoff increased by 7%-42% in April-May and reduced by 2-23% in June-July in the mountainous regions. Under the influence of LAAs-in-snow, Southern Rockies experience the most significant reduction of runoff by about 15% in the later stage of snow melt (i.e., June-July). Our results highlight the potentially important role of LAAs-in-snow in the historical and future changes of snowpack in the RMR.

A Comparison of Sea Ice Type, Sea Ice Temperature, and Snow Thickness Distributions in the Arctic Seasonal Ice Zones with the DMSP SSM/I

NASA Technical Reports Server (NTRS)

St.Germain, Karen; Cavalieri, Donald J.; Markus, Thorsten

1997-01-01

Global climate studies have shown that sea ice is a critical component in the global climate system through its effect on the ocean and atmosphere, and on the earth's radiation balance. Polar energy studies have further shown that the distribution of thin ice and open water largely controls the distribution of surface heat exchange between the ocean and atmosphere within the winter Arctic ice pack. The thickness of the ice, the depth of snow on the ice, and the temperature profile of the snow/ice composite are all important parameters in calculating surface heat fluxes. In recent years, researchers have used various combinations of DMSP SSMI channels to independently estimate the thin ice type (which is related to ice thickness), the thin ice temperature, and the depth of snow on the ice. In each case validation efforts provided encouraging results, but taken individually each algorithm gives only one piece of the information necessary to compute the energy fluxes through the ice and snow. In this paper we present a comparison of the results from each of these algorithms to provide a more comprehensive picture of the seasonal ice zone using passive microwave observations.

Clear-Sky Narrowband Albedo Variations Derived from VIRS and MODIS Data

NASA Technical Reports Server (NTRS)

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

2004-01-01

A critical parameter for detecting clouds and aerosols and for retrieving their microphysical properties is the clear-sky radiance. The Clouds and the Earth's Radiant Energy System (CERES) Project uses the visible (VIS; 0.63 m) and near-infrared (NIR; 1.6 or 2.13 m) channels available on same satellites as the CERES scanners. Another channel often used for cloud and aerosol, and vegetation cover retrievals is the vegetation (VEG; 0.86- m) channel that has been available on the Advanced Very High Resolution Radiometer (AVHRR) for many years. Generally, clear-sky albedo for a given surface type is determined for conditions when the vegetation is either thriving or dormant and free of snow. Snow albedo is typically estimated without considering the underlying surface type. The albedo for a surface blanketed by snow, however, should vary with surface type because the vegetation often emerges from the snow to varying degrees depending on the vertical dimensions of the vegetation. For example, a snowcovered prairie will probably be brighter than a snowcovered forest because the snow typically falls off the trees exposing the darker surfaces while the snow on a grassland at the same temperatures will likely be continuous and, therefore, more reflective. Accounting for the vegetation-induced differences should improve the capabilities for distinguishing snow and clouds over different surface types and facilitate improvements in the accuracy of radiative transfer calculations between the snow-covered surface and the atmosphere, eventually leading to improvements in models of the energy budgets over land. This paper presents a more complete analysis of the CERES spectral clear-sky reflectances to determine the variations in clear-sky top-of-atmosphere (TOA) albedos for both snow-free and snow-covered surfaces for four spectral channels using data from Terra and Aqua.. The results should be valuable for improved cloud retrievals and for modeling radiation fields.

Warming effects on the urban hydrology in cold climate regions.

PubMed

Järvi, L; Grimmond, C S B; McFadden, J P; Christen, A; Strachan, I B; Taka, M; Warsta, L; Heimann, M

2017-07-19

While approximately 338 million people in the Northern hemisphere live in regions that are regularly snow covered in winter, there is little hydro-climatologic knowledge in the cities impacted by snow. Using observations and modelling we have evaluated the energy and water exchanges of four cities that are exposed to wintertime snow. We show that the presence of snow critically changes the impact that city design has on the local-scale hydrology and climate. After snow melt, the cities return to being strongly controlled by the proportion of built and vegetated surfaces. However in winter, the presence of snow masks the influence of the built and vegetated fractions. We show how inter-year variability of wintertime temperature can modify this effect of snow. With increasing temperatures, these cities could be pushed towards very different partitioning between runoff and evapotranspiration. We derive the dependency of wintertime runoff on this warming effect in combination with the effect of urban densification.

Arctic tundra shrub invasion and soot deposition: Consequences for spring snowmelt and near-surface air temperatures

NASA Astrophysics Data System (ADS)

Strack, John E.; Pielke, Roger A.; Liston, Glen E.

2007-12-01

Invasive shrubs and soot pollution both have the potential to alter the surface energy balance and timing of snow melt in the Arctic. Shrubs reduce the amount of snow lost to sublimation on the tundra during the winter leading to a deeper end-of-winter snowpack. The shrubs also enhance the absorption of energy by the snowpack during the melt season by converting incoming solar radiation to longwave radiation and sensible heat. Soot deposition lowers the albedo of the snow, allowing it to more effectively absorb incoming solar radiation and thus melt faster. This study uses the Colorado State University Regional Atmospheric Modeling System version 4.4 (CSU-RAMS 4.4), equipped with an enhanced snow model, to investigate the effects of shrub encroachment and soot deposition on the atmosphere and snowpack in the Kuparuk Basin of Alaska during the May-June melt period. The results of the simulations suggest that a complete invasion of the tundra by shrubs leads to a 2.2°C warming of 3 m air temperatures and a 108 m increase in boundary layer depth during the melt period. The snow-free date also occurred 11 d earlier despite having a larger initial snowpack. The results also show that a decrease in the snow albedo of 0.1, owing to soot pollution, caused the snow-free date to occur 5 d earlier. The soot pollution caused a 1.0°C warming of 3 m air temperatures and a 25 m average deepening of the boundary layer.

MODIS Snow and Sea Ice Products

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Riggs, George A.; Salomonson, Vincent V.

2004-01-01

In this chapter, we describe the suite of Earth Observing System (EOS) Moderate-Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua snow and sea ice products. Global, daily products, developed at Goddard Space Flight Center, are archived and distributed through the National Snow and Ice Data Center at various resolutions and on different grids useful for different communities Snow products include binary snow cover, snow albedo, and in the near future, fraction of snow in a 5OO-m pixel. Sea ice products include ice extent determined with two different algorithms, and sea ice surface temperature. The algorithms used to develop these products are described. Both the snow and sea ice products, available since February 24,2000, are useful for modelers. Validation of the products is also discussed.

Modelling high Arctic deep permafrost temperature sensitivity in Northeast Greenland based on experimental and field observations

NASA Astrophysics Data System (ADS)

Rasmussen, Laura Helene; Zhang, Wenxin; Hollesen, Jørgen; Cable, Stefanie; Hvidtfeldt Christiansen, Hanne; Jansson, Per-Erik; Elberling, Bo

2017-04-01

Permafrost affected areas in Greenland are expected to experience a marked temperature increase within decades. Most studies have considered near-surface permafrost sensitivity, whereas permafrost temperatures below the depths of zero annual amplitude is less studied despite being closely related to changes in near-surface conditions, such as changes in active layer thermal properties, soil moisture and snow depth. In this study, we measured the sensitivity of thermal conductivity (TC) to gravimetric water content (GWC) in frozen and thawed permafrost sediments from fine-sandy and gravelly deltaic and fine-sandy alluvial deposits in the Zackenberg valley, NE Greenland. We further calibrated a coupled heat and water transfer model, the "CoupModel", for one central delta sediment site with average snow depth and further forced it with meteorology from a nearby delta sediment site with a topographic snow accumulation. With the calibrated model, we simulated deep permafrost thermal dynamics in four 20-year scenarios with changes in surface temperature and active layer (AL) soil moisture: a) 3 °C warming and AL water table at 0.5 m depth; b) 3 °C warming and AL water table at 0.1 m depth; c) 6 °C warming and AL water table at 0.5 m depth and d) 6 °C warming and AL water table at 0.1 m depth. Our results indicate that frozen sediments have higher TC than thawed sediments. All sediments show a positive linear relation between TC and soil moisture when frozen, and a logarithmic one when thawed. Gravelly delta sediments were highly sensitive, but never reached above 12 % GWC, indicating a field effect of water retention capacity. Alluvial sediments are less sensitive to soil moisture than deltaic (fine and coarse) sediments, indicating the importance of unfrozen water in frozen sediment. The deltaic site with snow accumulation had 1 °C higher mean annual ground temperature than the average snow depth site. Permafrost temperature at the depth of 18 m increased with 1.5 °C and 3.5 °C in the scenarios with 3 °C and 6 °C warming, respectively. Increasing the soil moisture had no important additional effect to warming, although an increase in thermal offset was indicated. We conclude that below-ground sediment properties affect the sensitivity of TC to GWC, that surface temperature changes can influence the deep permafrost within a short time scale, and that differences in snow depth affect surface temperatures. Sediment type and the type of precipitation should thus be considered when estimating future High Arctic deep permafrost sensitivity.

Precipitation phase partitioning variability across the Northern Hemisphere

NASA Astrophysics Data System (ADS)

Jennings, K. S.; Winchell, T. S.; Livneh, B.; Molotch, N. P.

2017-12-01

Precipitation phase drives myriad hydrologic, climatic, and biogeochemical processes. Despite its importance, many of the land surface models used to simulate such processes and their sensitivity to climate warming rely on simple, spatially uniform air temperature thresholds to partition rainfall and snowfall. Our analysis of a 29-year dataset with 18.7 million observations of precipitation phase from 12,143 stations across the Northern Hemisphere land surface showed marked spatial variability in the near-surface air temperature at which precipitation is equally likely to fall as rain and snow, the 50% rain-snow threshold. This value averaged 1.0°C and ranged from -0.4°C to 2.4°C for 95% of the stations analyzed. High-elevation continental areas such as the Rocky Mountains of the western U.S. and the Tibetan Plateau of central Asia generally exhibited the warmest thresholds, in some cases exceeding 3.0°C. Conversely, the coldest thresholds were observed on the Pacific Coast of North America, the southeast U.S., and parts of Eurasia, with values dropping below -0.5°C. Analysis of the meteorological conditions during storm events showed relative humidity exerted the strongest control on phase partitioning, with surface pressure playing a secondary role. Lower relative humidity and surface pressure were both associated with warmer 50% rain-snow thresholds. Additionally, we trained a binary logistic regression model on the observations to classify rain and snow events and found including relative humidity as a predictor variable significantly increased model performance between 0.6°C and 3.8°C when phase partitioning is most uncertain. We then used the optimized model and a spatially continuous reanalysis product to map the 50% rain-snow threshold across the Northern Hemisphere. The map reproduced patterns in the observed thresholds with a mean bias of 0.5°C relative to the station data. The above results suggest land surface models could be improved by incorporating relative humidity into their precipitation phase prediction schemes or by using a spatially variable, optimized rain-snow temperature threshold. This is particularly important for climate warming simulations where misdiagnosing a shift from snow to rain or inaccurately quantifying snowfall fraction would likely lead to biased results.

Studies of snowpack properties by passive microwave radiometry

NASA Technical Reports Server (NTRS)

Chang, A. T. C.; Hall, D. K.; Foster, J. L.; Rango, A.; Schmugge, T. J.

1979-01-01

Research involving the microwave characteristics of snow was undertaken in order to expand the information content currently available from remote sensing, namely the measurement of snowcovered area. Microwave radiation emitted from beneath the snow surface can be sensed and thus permits information on internal snowpack properties to be inferred. The intensity of radiation received is a function of the average temperature and emissivity of the snow layers and is commonly referred to as the brightness temperature (T sub B). The T sub B varies with snow grain and crystal sizes, liquid water content, and snowpack temperature. The T sub B of the 0.8 cm wavelength channel was found to decrease more so with increasing snow depth than the 1.4 cm channel. More scattering of the shorter wavelength radiation occurs thus resulting in a lower T sub B for shorter wavelengths in a dry snowpack. The longer 21.0 cm wavelength was used to assess the condition of the underlying ground.

Measurement of the spectral absorption of liquid water in melting snow with an imaging spectrometer

NASA Technical Reports Server (NTRS)

Green, Robert O.; Dozier, Jeff

1995-01-01

Melting of the snowpack is a critical parameter that drives aspects of the hydrology in regions of the earth where snow accumulates seasonally. New techniques for measurement of snow melt over regional scales offer the potential to improve monitoring and modeling of snow-driven hydrological processes. We present the results of measuring the spectral absorption of liquid water in a melting snowpack with the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). AVIRIS data were acquired over Mammoth Mountain, in east central California on 21 May 1994 at 18:35 UTC. The air temperature at 2926 m on Mammoth Mountain at site A was measured at 15-minute intervals during the day preceding the AVIRIS data acquisition. At this elevation, the air temperature did not drop below freezing the night of May 20 and had risen to 6 degrees Celsius by the time of the overflight on May 21. These temperature conditions support the presence of melting snow at the surface as the AVIRIS data were acquired.

An electrostatic charge measurement of blowing snow particles focusing on collision frequency to the snow surface

NASA Astrophysics Data System (ADS)

Omiya, S.; Sato, A.

2010-12-01

Blowing snow particles are known to have an electrostatic charge. This charge may be a contributing factor in the formation of snow drifts and snow cornices and changing of the trajectory of blowing snow particles. These formations and phenomena can cause natural disaster such as an avalanche and a visibility deterioration, and obstruct transportation during winter season. Therefore, charging phenomenon of the blowing snow particles is an important issue in terms of not only precise understanding of the particle motion but disaster prevention. The primary factor of charge accumulation to the blowing snow particles is thought to be due to “saltation” of them. The “saltation” is one of movement forms of blowing snow: when the snow particles are transported by the wind, they repeat frictional collisions with the snow surface. In previous studies, charge-to-mass ratios measured in the field were approximately -50 to -10 μC/kg, and in the wind tunnel were approximately -0.8 to -0.1 μC/kg. While there were qualitatively consistent in sign, negative, there were huge gaps quantitatively between them. One reason of those gaps is speculated to be due to differences in fetch. In other words, the difference of the collision frequency of snow particles to the snow surface has caused the gaps. But it is merely a suggestion and that has not been confirmed. The purpose of this experiment is to measure the charge of blowing snow particles focusing on the collision frequency and clarify the relationship between them. Experiments were carried out in the cryogenic wind tunnel of Snow and Ice Research Center (NIED, JAPAN). A Faraday cage and an electrometer were used to measure the charge of snow particles. These experiments were conducted over the hard snow surface condition to prevent the erosion of the snow surface and the generation of new snow particles from the surface. The collision frequency of particle was controlled by changing the wind velocity (4.5 to 7 m/s) under the fixed fetch (12m). The number of collisions of particle was converted from the wind velocity using an equation obtained by Kosugi et al. (2004). Blowing snow particles tend to accumulate negative charges gradually with increase of the number of collisions to the snow surface. As a result, it is demonstrated that the gaps between the field values and the wind tunnel ones were due to difference of the collision frequency of snow particles. Assuming a logarithmic relationship as first approximation between the measured charges and the number of collisions, the charge-to-mass ratios will reach roughly the same value which was obtained in the field with several hundreds collisions. For instance, fetch is needed roughly 200m for blowing snow particles to gain -30 μC/kg under the following conditions: air temperature -20 degrees Celsius, wind velocity 7m/s and hard snow surface. REFERENCE: Kosugi et al., (2004): Dependence of drifting snow saltation length on snow surface hardness. Cold Reg. Sci. Technol., 39, 133-139.

Siberia snow depth climatology derived from SSM/I data using a combined dynamic and static algorithm

USGS Publications Warehouse

Grippa, M.; Mognard, N.; Le, Toan T.; Josberger, E.G.

2004-01-01

One of the major challenges in determining snow depth (SD) from passive microwave measurements is to take into account the spatiotemporal variations of the snow grain size. Static algorithms based on a constant snow grain size cannot provide accurate estimates of snow pack thickness, particularly over large regions where the snow pack is subjected to big spatial temperature variations. A recent dynamic algorithm that accounts for the dependence of the microwave scattering on the snow grain size has been developed to estimate snow depth from the Special Sensor Microwave/Imager (SSM/I) over the Northern Great Plains (NGP) in the US. In this paper, we develop a combined dynamic and static algorithm to estimate snow depth from 13 years of SSM/I observations over Central Siberia. This region is characterised by extremely cold surface air temperatures and by the presence of permafrost that significantly affects the ground temperature. The dynamic algorithm is implemented to take into account these effects and it yields accurate snow depths early in the winter, when thin snowpacks combine with cold air temperatures to generate rapid crystal growth. However, it is not applicable later in the winter when the grain size growth slows. Combining the dynamic algorithm to a static algorithm, with a temporally constant but spatially varying coefficient, we obtain reasonable snow depth estimates throughout the entire snow season. Validation is carried out by comparing the satellite snow depth monthly averages to monthly climatological data. We show that the location of the snow depth maxima and minima is improved when applying the combined algorithm, since its dynamic portion explicitly incorporate the thermal gradient through the snowpack. The results obtained are presented and evaluated for five different vegetation zones of Central Siberia. Comparison with in situ measurements is also shown and discussed. ?? 2004 Elsevier Inc. All rights reserved.

Forward-looking Assimilation of MODIS-derived Snow Covered Area into a Land Surface Model

NASA Technical Reports Server (NTRS)

Zaitchik, Benjamin F.; Rodell, Matthew

2008-01-01

Snow cover over land has a significant impact on the surface radiation budget, turbulent energy fluxes to the atmosphere, and local hydrological fluxes. For this reason, inaccuracies in the representation of snow covered area (SCA) within a land surface model (LSM) can lead to substantial errors in both offline and coupled simulations. Data assimilation algorithms have the potential to address this problem. However, the assimilation of SCA observations is complicated by an information deficit in the observation SCA indicates only the presence or absence of snow, and not snow volume and by the fact that assimilated SCA observations can introduce inconsistencies with atmospheric forcing data, leading to non-physical artifacts in the local water balance. In this paper we present a novel assimilation algorithm that introduces MODIS SCA observations to the Noah LSM in global, uncoupled simulations. The algorithm utilizes observations from up to 72 hours ahead of the model simulation in order to correct against emerging errors in the simulation of snow cover while preserving the local hydrologic balance. This is accomplished by using future snow observations to adjust air temperature and, when necessary, precipitation within the LSM. In global, offline integrations, this new assimilation algorithm provided improved simulation of SCA and snow water equivalent relative to open loop integrations and integrations that used an earlier SCA assimilation algorithm. These improvements, in turn, influenced the simulation of surface water and energy fluxes both during the snow season and, in some regions, on into the following spring.

The Studies on Aerosol Transport, Its Deposition, and Its Impact on Climate - the Study on the Surface Material Circulation can Connect from the Past to the Future

NASA Technical Reports Server (NTRS)

Yasunari, Teppei

2012-01-01

Recently the issue on glacier retreats comes up and many factors should be relevant to the issue. The absorbing aerosols such as dust and black carbon (BC) are considered to be one of the factors. After they deposited onto the snow surface, it will reduce snow albedo (called snow darkening effect) and probably contribute to further melting of glacier. The Goddard Earth Observing System version 5 (GEOS-5) has developed at NASAlGSFC. However, the original snowpack model used in the land surface model in the GEOS-5 did not consider the snow darkening effect. Here we developed the new snow albedo scheme which can consider the snow darkening effect. In addition, another scheme on calculating mass concentrations on the absorbing aerosols in snowpack was also developed, in which the direct aerosol depositions from the chemical transport model in the GEOS-5 were used. The scheme has been validated with the observed data obtained at backyard of the Institute of Low Temperature Science, Hokkaido University, by Dr. Teruo Aoki (Meteorological Research Institute) et al. including me. The observed data was obtained when I was Ph.D. candidate. The original GEOS-5 during 2007-2009 over the Himalayas and Tibetan Plateau region showed more reductions of snow than that of the new GEOS-5 because the original one used lower albedo settings. On snow cover fraction, the new GEOS-5 simulated more realistic snow-covered area comparing to the MODIS snow cover fraction. The reductions on snow albedo, snow cover fraction, and snow water equivalent were seen with statistically significance if we consider the snow darkening effect comparing to the results without the snow darkening effect. In the real world, debris-cover, inside refreezing process, surface flow of lacier, etc. affect glacier mass balance and the simu.latedresults immediately do not affect whole glacier retreating. However, our results indicate that some surface melting over non debris-covered parts of the glacier would be explained by the snow darkening effect. Further discussion and observations are necessary to assess the glacier issue.

CRYOLINK: Monitoring of permafrost and seasonal frost in southern Norway

NASA Astrophysics Data System (ADS)

Farbrot, Herman; Hipp, Tobias; Etzelmüller, Bernd; Humlum, Ole; Isaksen, Ketil; Strand Ødegârd, Rune

2010-05-01

The modern southern boundary for Scandinavian permafrost is located in the mountains of Southern Norway. Permafrost and seasonal frost are considered key components of the cryosphere, and the climate-permafrost relation has acquired added importance with the increasing awareness and concern of rising air temperatures. The three-year research project CRYOLINK ("Permafrost and seasonal frost in southern Norway") aims at improving knowledge on past and present ground temperatures, seasonal frost, and distribution of mountain permafrost in Southern Norway by addressing the fundamental problem of heat transfer between the atmosphere and the ground surface. Hence, several shallow boreholes have been drilled in August 2008 in three areas (Juvvass, Jetta and Tron) situated along a west-east transect. On most borehole sites air and ground temperatures are measured. Further, vertical arrays of Miniature Temperature Dataloggers (MTDs; Thermochron iBottons®) at fixed heights above the ground surface have been installed to roughly determine the snow depths at the sites, which is also indicated by digital cameras providing daily pictures of snow and weather conditions. In addition individual MTDs have been placed out to measure ground surface temperature at different aspects and snow settings. This presentation will focus on the field set up and give examples of data obtained from the sites.

Sensitivity of Support Vector Machine Predictions of Passive Microwave Brightness Temperature Over Snow-covered Terrain in High Mountain Asia

NASA Astrophysics Data System (ADS)

Ahmad, J. A.; Forman, B. A.

2017-12-01

High Mountain Asia (HMA) serves as a water supply source for over 1.3 billion people, primarily in south-east Asia. Most of this water originates as snow (or ice) that melts during the summer months and contributes to the run-off downstream. In spite of its critical role, there is still considerable uncertainty regarding the total amount of snow in HMA and its spatial and temporal variation. In this study, the NASA Land Information Systems (LIS) is used to model the hydrologic cycle over the Indus basin. In addition, the ability of support vector machines (SVM), a machine learning technique, to predict passive microwave brightness temperatures at a specific frequency and polarization as a function of LIS-derived land surface model output is explored in a sensitivity analysis. Multi-frequency, multi-polarization passive microwave brightness temperatures as measured by the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) over the Indus basin are used as training targets during the SVM training process. Normalized sensitivity coefficients (NSC) are then computed to assess the sensitivity of a well-trained SVM to each LIS-derived state variable. Preliminary results conform with the known first-order physics. For example, input states directly linked to physical temperature like snow temperature, air temperature, and vegetation temperature have positive NSC's whereas input states that increase volume scattering such as snow water equivalent or snow density yield negative NSC's. Air temperature exhibits the largest sensitivity coefficients due to its inherent, high-frequency variability. Adherence of this machine learning algorithm to the first-order physics bodes well for its potential use in LIS as the observation operator within a radiance data assimilation system aimed at improving regional- and continental-scale snow estimates.

Terra Data Confirm Warm, Dry U.S. Winter

NASA Technical Reports Server (NTRS)

2002-01-01

New maps of land surface temperature and snow cover produced by NASA's Terra satellite show this year's winter was warmer than last year's, and the snow line stayed farther north than normal. The observations confirm earlier National Oceanic and Atmospheric Administration reports that the United States was unusually warm and dry this past winter. (Click to read the NASA press release and to access higher-resolution images.) For the last two years, a new sensor aboard Terra has been collecting the most detailed global measurements ever made of our world's land surface temperatures and snow cover. The Moderate-resolution Imaging Spectroradiometer (MODIS) is already giving scientists new insights into our changing planet. Average temperatures during December 2001 through February 2002 for the contiguous United States appear to have been unseasonably warm from the Rockies eastward. In the top image the coldest temperatures appear black, while dark green, blue, red, yellow, and white indicate progressively warmer temperatures. MODIS observes both land surface temperature and emissivity, which indicates how efficiently a surface absorbs and emits thermal radiation. Compared to the winter of 2000-01, temperatures throughout much of the U.S. were warmer in 2001-02. The bottom image depicts the differences on a scale from dark blue (colder this year than last) to red (warmer this year than last). A large region of warm temperatures dominated the northern Great Plains, while the area around the Great Salt Lake was a cold spot. Images courtesy Robert Simmon, NASA GSFC, based upon data courtesy Zhengming Wan, MODIS Land Science Team member at the University of California, Santa Barbara's Institute for Computational Earth System Science

Temporal Changes in the Observed Relationship between Cloud Cover and Surface Air Temperature.

NASA Astrophysics Data System (ADS)

Sun, Bomin; Groisman, Pavel Ya.; Bradley, Raymond S.; Keimig, Frank T.

2000-12-01

The relationship between cloud cover and near-surface air temperature and its decadal changes are examined using the hourly synoptic data for the past four to six decades from five regions of the Northern Hemisphere: Canada, the United States, the former Soviet Union, China, and tropical islands of the western Pacific. The authors define the normalized cloud cover-surface air temperature relationship, NOCET or dT/dCL, as a temperature anomaly with a unit (one-tenth) deviation of total cloud cover from its average value. Then mean monthly NOCET time series (night- and daytime, separately) are area-averaged and parameterized as functions of surface air humidity and snow cover. The day- and nighttime NOCET variations are strongly anticorrelated with changes in surface humidity. Furthermore, the daytime NOCET changes are positively correlated to changes in snow cover extent. The regionally averaged nighttime NOCET varies from 0.05 K tenth1 in the wet Tropics to 1.0 K tenth1 at midlatitudes in winter. The daytime regional NOCET ranges from 0.4 K tenth1 in the Tropics to 0.7 K tenth1 at midlatitudes in winter.The authors found a general strengthening of a daytime surface cooling during the post-World War II period associated with cloud cover over the United States and China, but a minor reduction of this cooling in higher latitudes. Furthermore, since the 1970s, a prominent increase in atmospheric humidity has significantly weakened the effectiveness of the surface warming (best seen at nighttime) associated with cloud cover.The authors apportion the spatiotemporal field of interactions between total cloud cover and surface air temperature into a bivariate relationship (described by two equations, one for daytime and one for nighttime) with surface air humidity and snow cover and two constant factors. These factors are invariant in space and time domains. It is speculated that they may represent empirical estimates of the overall cloud cover effect on the surface air temperature.

Photovoltaic cell electrical heating system for removing snow on panel including verification.

PubMed

Weiss, Agnes; Weiss, Helmut

2017-11-16

Small photovoltaic plants in private ownership are typically rated at 5 kW (peak). The panels are mounted on roofs at a decline angle of 20° to 45°. In winter time, a dense layer of snow at a width of e.g., 10 cm keeps off solar radiation from the photovoltaic cells for weeks under continental climate conditions. Practically, no energy is produced over the time of snow coverage. Only until outside air temperature has risen high enough for a rather long-time interval to allow partial melting of snow; the snow layer rushes down in an avalanche. Following this proposal, snow removal can be arranged electrically at an extremely positive energy balance in a fast way. A photovoltaic cell is a large junction area diode inside with a threshold voltage of about 0.6 to 0.7 V (depending on temperature). This forward voltage drop created by an externally driven current through the modules can be efficiently used to provide well-distributed heat dissipation at the cell and further on at the glass surface of the whole panel. The adhesion of snow on glass is widely reduced through this heating in case a thin water film can be produced by this external short time heating. Laboratory experiments provided a temperature increase through rated panel current of more than 10 °C within about 10 min. This heating can initiate the avalanche for snow removal on intention as described before provided the clamping effect on snow at the edge of the panel frame is overcome by an additional heating foil. Basics of internal cell heat production, heating thermal effects in time course, thermographic measurements on temperature distribution, power circuit opportunities including battery storage elements and snow-removal under practical conditions are described.

Relationships between nocturnal winter road slipperiness, cloud cover and surface temperature

NASA Astrophysics Data System (ADS)

Grimbacher, T.; Schmid, W.

2003-04-01

Ice and Snow are important risks for road traffic. In this study we show several events of slipperiness in Switzerland, mainly caused by rain or snow falling on a frozen surface. Other reasons for slippery conditions are frost or freezing dew in clear nights and nocturnal clearing after precipitation, which goes along with radiative cooling. The main parameters of road weather forecasts are precipitation, cloudiness and surface temperature. Precipitation is well predictable with weather radars and radar nowcasting algorithms. Temperatures are often taken from numerical weather prediction models, but because of changes in cloud cover these model values are inaccurate in terms of predicting the onset of freezing. Cloudiness, especially the advection, formation and dissipation of clouds and their interaction with surface temperatures, is one of the major unsolved problems of road weather forecasts. Cloud cover and the temperature difference between air and surface temperature are important parameters of the radiation balance. In this contribution, we show the relationship between them, proved at several stations all over Switzerland. We found a quadratic correlation coefficient of typically 60% and improved it considering other meteorological parameters like wind speed and surface water. The acquired relationship may vary from one station to another, but we conclude that temperature difference is a signature for nocturnal cloudiness. We investigated nocturnal cloudiness for two cases from winters 2002 and 2003 in the canton of Lucerne in central Switzerland. There, an ultra-dense combination of two networks with together 55 stations within 50x50 km^2 is operated, measuring air and surface temperature, wind and other road weather parameters. With the aid of our equations, temperature differences detected from this network were converted into cloud maps. A comparison between precipitation seen by radar, cloud maps and surface temperatures shows that there are similar structures in all data. Depending on the situation, we also identified additional effects influencing the temperature differences, for instance the advection of could air or the influence of melting heat at or after a snow event. All these findings help to further understand the phenomena, and hence will contribute to a better predictability of winter road slipperiness.

Snow stratigraphic heterogeneity within ground-based passive microwave radiometer footprints: implications for emission modelling

NASA Astrophysics Data System (ADS)

Sandells, M.; Rutter, N.; Derksen, C.; Langlois, A.; Lemmetyinen, J.; Montpetit, B.; Pulliainen, J. T.; Royer, A.; Toose, P.

2012-12-01

Remote sensing of snow mass remains a challenging area of research. Scattering of electromagnetic radiation is sensitive to snow mass, but is also affected by contrasts in the dielectric properties of the snow. Although the argument that errors from simple algorithms average out at large scales has been used to justify current retrieval methods, it is not obvious why this should be the case. This hypothesis needs to be tested more rigorously. A ground-based field experiment was carried out to assess the impact of sub-footprint snow heterogeneity on microwave brightness temperature, in Churchill, Canada in winter in early 2010. Passive microwave measurements of snow were made using sled-mounted radiometers at 75cm intervals over a 5m transect. Measurements were made at horizontal and vertical polarizations at frequencies of 19 and 37 GHz. Snow beneath the radiometer footprints was subsequently excavated, creating a snow trench wall along the centrepoints of adjacent footprints. The trench wall was carefully smoothed and photographed with a near-infrared camera in order to determine the positions of stratigraphic snow layer boundaries. Three one-dimensional vertical profiles of snowpack properties (density and snow specific surface area) were taken at 75cm, 185cm and 355cm from the left hand side of the trench. These profile measurements were used to derive snow density and grain size for each of the layers identified from the NIR image. Microwave brightness temperatures for the 2-dimensional map of snow properties was simulated with the Helsinki University of Technology (HUT) model at 1cm intervals horizontally across the trench. Where each of five ice lenses was identified in the snow stratigraphy, a decrease in brightness temperature was simulated. However, the median brightness temperature simulated across the trench was substantially higher than the observations, of the order of tens of Kelvin, dependent on frequency and polarization. In order to understand and quantify possible sources of error in the simulations, a number of experiments were carried out to investigate the sensitivity of the brightness temperature to: 1) uncertainties in field observations, 2) representation of ice lenses, 3) model layering structure, and 4) near-infrared derived grain size representing snow grain size at microwave wavelengths. Field measurement error made little difference to the simulated brightness temperature, nor did the representation of ice lenses as crusts of high density snow. As the number of layers in the snow was reduced to 3, 2, or 1, the simulated brightness temperature increased slightly. However, scaling of snow grain size had a dramatic effect on the simulated brightness temperatures, reducing the median bias of the simulations to within measurement error for the statistically different brightness temperature distributions. This indicated that further investigation is required to define what is meant by the microwave grain size, and how this relates to the grain size that is used in the microwave emission model.

Soil Moisture and Snow Cover: Active or Passive Elements of Climate?

NASA Technical Reports Server (NTRS)

Oglesby, Robert J.; Marshall, Susan; Robertson, Franklin R.; Roads, John O.; Arnold, James E. (Technical Monitor)

2001-01-01

A key question in the study of the hydrologic cycle is the extent to which surface effects such as soil moisture and snow cover are simply passive elements or whether they can affect the evolution of climate on seasonal and longer time scales. We have constructed ensembles of predictability studies using the NCAR CCM3 in which we compared the relative roles of initial surface and atmospheric conditions over the central and western U.S. GAPP region in determining the subsequent evolution of soil moisture and of snow cover. We have also made sensitivity studies with exaggerated soil moisture and snow cover anomalies in order to determine the physical processes that may be important. Results from simulations with realistic soil moisture anomalies indicate that internal climate variability may be the strongest factor, with some indication that the initial atmospheric state is also important. The initial state of soil moisture does not appear important, a result that held whether simulations were started in late winter or late spring. Model runs with exaggerated soil moisture reductions (near-desert conditions) showed a much larger effect, with warmer surface temperatures, reduced precipitation, and lower surface pressures; the latter indicating a response of the atmospheric circulation. These results suggest the possibility of a threshold effect in soil moisture, whereby an anomaly must be of a sufficient size before it can have a significant impact on the atmospheric circulation and hence climate. Results from simulations with realistic snow cover anomalies indicate that the time of year can be crucial. When introduced in late winter, these anomalies strongly affected the subsequent evolution of snow cover. When introduced in early winter, however, little or no effect is seen on the subsequent snow cover. Runs with greatly exaggerated initial snow cover indicate that the high reflectivity of snow is the most important process by which snow cover can impact climate, through lower surface temperatures and increased surface pressures. In early winter, the amount of solar radiation is very small and so this albedo, effect is inconsequential while in late winter, with the sun higher in the sky and period of daylight longer, the effect is much stronger. The results to date were obtained for model runs with present-day conditions. We are currently analyzing runs made with projected forcings for the 21st century to see if these results are modified in any way under likely scenarios of future climate change.

Climate Effects and Efficacy of Dust and Soot in Snow

NASA Astrophysics Data System (ADS)

Zender, C. S.; Flanner, M. G.; Randerson, J. T.; Mahowald, N. M.; Rasch, P. J.; Yoshioka, M.; Painter, T.

2006-12-01

Dust and industrial and biomass burning emissions from low and mid-latitudes dominate the absorbing impurities trapped in snow at mid- and high-latitudes. We study the effects of dust and smoke on global and regional climate using a general circulation model driven by observed and predicted aerosol emissions determined from satellite and in situ observations. The model has sophisticated treatments of aerosol and snowpack radiative and thermodynamic processes that compare well with observations of snow albedo evolution and impurity concentration. This presentation focuses on the individual and combined contributions of present day dust and soot to snow-albedo forcing and on the global temperature and snowpack responses. Results are emphasized near India and East Asia, where the anthropogenic aerosol forcing of surface albedo and hydrology is greatest. We find that dust and black carbon (BC) aerosols have climate change efficacies (surface temperature change per unit forcing) about 3--4 times greater than CO2, making them the most efficacious forcing agents known. We estimate present day dust and soot snowpack-forcing of ~ 0.050 W m-2 warms global climate by ~ 0.16 °K. Anthropogenic soot from fossil fuel sources causes more than 50% of this warming, and biomass burning can account for up to 30% in strong tropical or boreal burn years. The greatest forcings occur in the Tarim/Mongol region (due to dust), northeastern China (due to soot), and the Tibetan Plateau (both). Dirty springtime snow in these regions can darken albedo by more than 0.1 and increase surface absorption by more than 20 W m-2. These results have implications for the strength of the Asian Monsoon, which is negatively correlated with antecedent snow cover in non-ENSO years. Dust and soot have such strong efficacies because they increase spring melt rates thus reduce summer snow cover. In some regions and seasons, dirty snow reduces snowpack depth and cover by 50%, triggering strong snow and sea-ice albedo feedbacks.

Improving the Representation of Snow Crystal Properties within a Single-Moment Microphysics Scheme

NASA Technical Reports Server (NTRS)

Molthan, Andrew L.; Petersen, Walter A.; Case, Jonathan L.; Dembek, Scott R.

2010-01-01

The assumptions of a single-moment microphysics scheme (NASA Goddard) were evaluated using a variety of surface, aircraft and radar data sets. Fixed distribution intercepts and snow bulk densities fail to represent the vertical variability and diversity of crystal populations for this event. Temperature-based equations have merit, but they can be adversely affected by complex temperature profiles that are inverted or isothermal. Column-based approaches can mitigate complex profiles of temperature but are restricted by the ability of the model to represent cloud depth. Spheres are insufficient for use in CloudSat reflectivity comparisons due to Mie resonance, but reasonable for Rayleigh scattering applications. Microphysics schemes will benefit from a greater range of snow crystal characteristics to accommodate naturally occurring diversity.

Grey Tienshan Urumqi Glacier No.1 and light-absorbing impurities.

PubMed

Ming, Jing; Xiao, Cunde; Wang, Feiteng; Li, Zhongqin; Li, Yamin

2016-05-01

The Tienshan Urumqi Glacier No.1 (TUG1) usually shows "grey" surfaces in summers. Besides known regional warming, what should be responsible for largely reducing its surface albedo and making it look "grey"? A field campaign was conducted on the TUG1 on a selected cloud-free day of 2013 after a snow fall at night. Fresh and aged snow samples were collected in the field, and snow densities, grain sizes, and spectral reflectances were measured. Light-absorbing impurities (LAIs) including black carbon (BC) and dust, and number concentrations and sizes of the insoluble particles (IPs) in the samples were measured in the laboratory. High temperatures in summer probably enhanced the snow ageing. During the snow ageing process, the snow density varied from 243 to 458 kg m(-3), associated with the snow grain size varying from 290 to 2500 μm. The concentrations of LAIs in aged snow were significantly higher than those in fresh snow. Dust and BC varied from 16 ppm and 25 ppb in fresh snow to 1507 ppm and 1738 ppb in aged snow, respectively. Large albedo difference between the fresh and aged snow suggests a consequent forcing of 180 W m(-2). Simulations under scenarios show that snow ageing, BC, and dust were responsible for 44, 25, and 7 % of the albedo reduction in the accumulation zone, respectively.

Spatial variability of shortwave radiative fluxes in the context of snowmelt

NASA Astrophysics Data System (ADS)

Pinker, Rachel T.; Ma, Yingtao; Hinkelman, Laura; Lundquist, Jessica

2014-05-01

Snow-covered mountain ranges are a major source of water supply for run-off and groundwater recharge. Snowmelt supplies as much as 75% of surface water in basins of the western United States. Factors that affect the rate of snow melt include incoming shortwave and longwave radiation, surface albedo, snow emissivity, snow surface temperature, sensible and latent heat fluxes, ground heat flux, and energy transferred to the snowpack from deposited snow or rain. The net radiation generally makes up about 80% of the energy balance and is dominated by the shortwave radiation. Complex terrain poses a great challenge for obtaining the needed information on radiative fluxes from satellites due to elevation issues, spatially-variable cloud cover, rapidly changing surface conditions during snow fall and snow melt, lack of high quality ground truth for evaluation of the satellite based estimates, as well as scale issues between the ground observations and the satellite footprint. In this study we utilize observations of high spatial resolution (5-km) as available from the Moderate Resolution Imaging Spectro-radiometer (MODIS) to derive surface shortwave radiative fluxes in complex terrain, with attention to the impact of slopes on the amount of radiation received. The methodology developed has been applied to several water years (January to July during 2003, 2004, 2005 and 2009) over the western part of the United States, and the available information was used to derive metrics on spatial and temporal variability in the shortwave fluxes. It is planned to apply the findings from this study for testing improvements in Snow Water Equivalent (SWE) estimates.

Detection Thresholds of Falling Snow from Satellite-Borne Active and Passive Sensors

NASA Technical Reports Server (NTRS)

Skofronick-Jackson, Gail; Johnson, Benjamin T.; Munchak, S. Joseph

2012-01-01

Precipitation, including rain and snow, is a critical part of the Earth's energy and hydrology cycles. Precipitation impacts latent heating profiles locally while global circulation patterns distribute precipitation and energy from the equator to the poles. For the hydrological cycle, falling snow is a primary contributor in northern latitudes during the winter seasons. Falling snow is the source of snow pack accumulations that provide fresh water resources for many communities in the world. Furthermore, falling snow impacts society by causing transportation disruptions during severe snow events. In order to collect information on the complete global precipitation cycle, both liquid and frozen precipitation must be collected. The challenges of estimating falling snow from space still exist though progress is being made. These challenges include weak falling snow signatures with respect to background (surface, water vapor) signatures for passive sensors over land surfaces, unknowns about the spherical and non-spherical shapes of the snowflakes, their particle size distributions (PSDs) and how the assumptions about the unknowns impact observed brightness temperatures or radar reflectivities, differences in near surface snowfall and total column snow amounts, and limited ground truth to validate against. While these challenges remain, knowledge of their impact on expected retrieval results is an important key for understanding falling snow retrieval estimations. Since falling snow from space is the next precipitation measurement challenge from space, information must be determined in order to guide retrieval algorithm development for these current and future missions. This information includes thresholds of detection for various sensor channel configurations, snow event system characteristics, snowflake particle assumptions, and surface types. For example, can a lake effect snow system with low (approx 2.5 km) cloud tops having an ice water content (IWC) at the surface of 0.25 g / cubic m and dendrite snowflakes be detected? If this information is known, we can focus retrieval efforts on detectable storms and concentrate advances on achievable results. Here, the focus is to determine thresholds of detection for falling snow for various snow conditions over land and lake surfaces. The results rely on simulated Weather Research Forecasting (WRF) simulations of falling snow cases since simulations provide all the information to determine the measurements from space and the ground truth. Sensitivity analyses were performed to better ascertain the relationships between multifrequency microwave and millimeter-wave sensor observations and the falling snow/underlying field of view. In addition, thresholds of detection for various sensor channel configurations, snow event system characteristics, snowflake particle assumptions, and surface types were studied. Results will be presented for active radar at Ku, Ka, and W-band and for passive radiometer channels from 10 to 183 GHz.

Incorporation of the Mass Concentration and the New Snow Albedo Schemes into the Global Forecasting Model, GEOS-5 and the Impact of the New Schemes over Himalayan Glaciers

NASA Technical Reports Server (NTRS)

Yasunari, Teppei

2012-01-01

Recently the issue on glacier retreats comes up and many factors should be relevant to the issue. The absorbing aerosols such as dust and black carbon (BC) are considered to be one of the factors. After they deposited onto the snow surface, it will reduce snow albedo (called snow darkening effect) and probably contribute to further melting of glacier. The Goddard Earth Observing System version 5 (GEOS-5) has developed at NASA/GSFC. However, the original snowpack model used in the land surface model in the GEOS-5 did not consider the snow darkening effect. Here we developed the new snow albedo scheme which can consider the snow darkening effect. In addition, another scheme on calculating mass concentrations on the absorbing aerosols in snowpack was also developed, in which the direct aerosol depositions from the chemical transport model in the GEOS-5 were used. The scheme has been validated with the observed data obtained at backyard of the Institute of Low Temperature Science, Hokkaido University, by Dr. Teruo Aoki (Meteorological Research Institute) et aL including me. The observed data was obtained when I was Ph.D. candidate. The original GEOS-5during 2007-2009 over the Himalayas and Tibetan Plateau region showed more reductions of snow than that of the new GEOS-5 because the original one used lower albedo settings. On snow cover fraction, the new GEOS-5 simulated more realistic snow-covered area comparing to the MODIS snow cover fraction. The reductions on snow albedo, snow cover fraction, and snow water equivalent were seen with statistically significance if we consider the snow darkening effect comparing to the results without the snow darkening effect. In the real world, debris cover, inside refreezing process, surface flow of glacier, etc. affect glacier mass balance and the simulated results immediately do not affect whole glacier retreating. However, our results indicate that some surface melting over non debris covered parts of the glacier would be explained by the snow darkening effect. Further discussion and observations are necessary to assess the glacier issue.

Examination of snowmelt over Western Himalayas using remote sensing data

NASA Astrophysics Data System (ADS)

Tiwari, Sarita; Kar, Sarat C.; Bhatla, R.

2016-07-01

Snowmelt variability in the Western Himalayas has been examined using remotely sensed snow water equivalent (SWE) and snow-covered area (SCA) datasets. It is seen that climatological snowfall and snowmelt amount varies in the Himalayan region from west to east and from month to month. Maximum snowmelt occurs at the elevation zone between 4500 and 5000 m. As the spring and summer approach and snowmelt begins, a large amount of snow melts in May. Strength and weaknesses of temperature-based snowmelt models have been analyzed for this region by computing the snowmelt factor or the degree-day factor (DDF). It is seen that average DDF in the Himalayas is more in April and less in July. During spring and summer months, melting rate is higher in the areas that have height above 2500 m. The region that lies between 4500 and 5000 m elevation zones contributes toward more snowmelt with higher melting rate. Snowmelt models have been developed to estimate interannual variations of monthly snowmelt amount using the DDF, observed SWE, and surface air temperature from reanalysis datasets. In order to further improve the estimate snowmelt, regression between observed and modeled snowmelt has been carried out and revised DDF values have been computed. It is found that both the models do not capture the interannual variability of snowmelt in April. The skill of the model is moderate in May and June, but the skill is relatively better in July. In order to explain this skill, interannual variability (IAV) of surface air temperature has been examined. Compared to July, in April, the IAV of temperature is large indicating that a climatological value of DDF is not sufficient to explain the snowmelt rate in April. Snow area and snow amount depletion curves over Himalayas indicate that in a small area at high altitude, snow is still observed with large SWE whereas over most of the region, all the snow has melted.

Analysis of passive microwave signatures over snow-covered mountainous area

NASA Astrophysics Data System (ADS)

Kim, R. S.; Durand, M. T.

2015-12-01

Accurate knowledge of snow distribution over mountainous area is critical for climate studies and the passive microwave(PM) measurements have been widely used and invested in order to obtain information about snowpack properties. Understanding and analyzing the signatures for the explicit inversion of the remote sensing data from land surfaces is required for successful using of passive microwave sensors but this task is often ambiguous due to the large variability of physical conditions and object types. In this paper, we discuss the pattern of measured brightness temperatures and emissivities at vertical and horizontal polarization over the frequency range of 10.7 to 89 GHz of land surfaces under various snow and vegetation conditions. The Multiband polarimetric Scanning Radiometer(PSR) imagery is used over NASA Cold Land Processes Field Experiment(CLPX) study area with ground-based measurements of snow depth and snow properties. Classification of snow under various conditions in mountainous area is implemented based on different patterns of microwave signatures.

Sulfur dioxide reactions on ice surfaces: Implications for dry deposition to snow

Treesearch

Martha H. Conklin; Richard A. Sommerfeld; S. Kay Laird; John E. Villinski

1993-01-01

Controlled exposure of ice to a reactive gas, SO2, demonstrated the importance of the chemical composition of the ice surface on the accumulation of acidity in snow. In a series of bench-scale continuous-flow column experiments run at four temperatures (-1, -8, -30 and -60°C), SO2 was shown to dissolve and to react with other species in the ice-air interfacial region...

Putting the Capital 'A' in CoCoRAHS: A Pilot Program to Measure Albedo using the Community Collaborative Rain, Hail, and Snow (CoCoRaHS) Network

NASA Astrophysics Data System (ADS)

Burakowski, E. A.; Stampone, M. D.; Wake, C. P.; Dibb, J. E.

2012-12-01

The Community Collaborative Rain, Hail, and Snow (CoCoRaHS) Network, started in 1998 as a community-based network of volunteer weather observer in Colorado, is the single largest provider of daily precipitation observations in the United States. We embrace the CoCoRaHS mission to use low-cost measurement tools, provide training and education, and utilize an interactive website to collect high quality albedo data for research and education applications. We trained a select sub-set of CoCoRaHS's eighteen most enthusiastic, self-proclaimed 'weather nuts' in the state of New Hampshire to collect surface albedo, snow depth, and snow density measurements between 23-Nov-2011 and 15-Mar-2012. At less than 700 per observer, the low-cost albedo data falls within ±0.05 of albedo values collected from a First Class Kipp and Zonen Albedometer (CMA6) at local solar noon. CoCoRaHS albedo values range from 0.99 for fresh snow to 0.34 for shallow, aged snow. Snow-free albedo ranges from 0.09 to 0.39, depending on ground cover. Albedo is found to increase logarithmically with snow depth and decrease linearly with snow density. The latter relationship with snow density is inferred to be a proxy for increasing snow grain size as snowpack ages and compacts, supported by spectral albedo measurements collected with an ASD FieldSpec4 spectrometer. The newly established albedo network also serves as a development test bed for interactive online mapping and graphing applications for CoCoRaHS observers to investigate spatial and temporal patterns in albedo, snow depth, and snow density (www.cocorahs-albedo.org). The 2012-2013 field season will include low-cost infrared temperature guns (<40 each) to investigate the relationship between surface albedo and skin temperature. We have also recruited middle- and high-schools as volunteer observers and are working with the teachers to develop curriculum and lesson plans that utilize the low-cost measurement tools provided by CoCoRAHS. CoCoRAHS data will provide critical spatially distributed measurements of surface data that will be used to validate and improve land surface modeling of New Hampshire climate under different land cover scenarios. Building on the success of the first season, the newly established albedo network shows promise to put the capital 'A' in CoCoRAHS.Figure 1. (a) Map of Community Collaborative Rain, Hail, and Snow (CoCoRAHS) volunteers participating in the pilot albedo project, and (b) CoCoRAHS snow measurement kit.

Linkages between Snow Cover Seasonality, Terrain, and Land Surface Phenology in the Highland Pastures of Kyrgyzstan

NASA Astrophysics Data System (ADS)

Henebry, Geoffrey; Tomaszewska, Monika; Kelgenbaeva, Kamilya

2017-04-01

In the highlands of Kyrgyzstan, vertical transhumance is the foundation of montane agropastoralism. Terrain attributes, such as elevation, slope, and aspect, affect snow cover seasonality, which is a key influence on the timing of plant growth and forage availability. Our study areas include the highland pastures in Central Tien Shan mountains, specifically in the rayons of Naryn and At-Bashy in Naryn oblast, and Alay and Chong-Alay rayons in Osh oblast. To explore the linkages between snow cover seasonality and land surface phenology as modulated by terrain and variations in thermal time, we use 16 years (2001-2016) of Landsat surface reflectance data at 30 m resolution with MODIS land surface temperature and snow cover products at 1 km and 500 m resolution, respectively, and two digital elevation models, SRTM and ASTER GDEM. We model snow cover seasonality using frost degree-days and land surface phenology using growing degree-days as quadratic functions of thermal time: a convex quadratic (CxQ) model for land surface phenology and a concave quadratic (CvQ) model for snow cover seasonality. From the fitted parameter coefficients, we calculated phenometrics, including "peak height" and "thermal time to peak" for the CxQ models and "trough depth" and "thermal time to trough" for the CvQ models. We explore how these phenometrics change as a function of elevation and slope-aspect interactions and due to interannual variability. Further, we examine how snow cover duration and timing affects the subsequent peak height and thermal time to peak in wetter, drier, and normal years.

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.

Diagnosing land management and climate change impacts on snowmelt in semi-arid agricultural cold regions with an improved snowmelt model

NASA Astrophysics Data System (ADS)

Harder, P.; Pomeroy, J. W.; Helgason, W.

2017-12-01

Spring snowmelt is the most important hydrological event in semi-arid agricultural cold regions, recharging soil moisture and generating the majority of annual runoff. Adoption of no-till agricultural practices means vast areas of the Canadian Prairies, and other analogous regions, are characterized by standing crop stubble. The emergence of stubble during snowmelt will have important implications for the snowpack energy balance. In addition, spatiotemporally dynamic snowcover heterogeneity leads to enhancement of turbulent flux contributions to melt by advection of energy from warm moist bare ground to snow. Stubble emergence and advection are generally unaccounted for in snow models. To address these challenges a stubble-snow-atmosphere surface energy balance model is developed that relates stubble parameters to the snow surface energy balance. Existing fractal understandings of snowcover geometry are applied to a conceptualized boundary layer integration model to estimate a sensible and latent heat advection efficiency. The small-scale nature of stubble-snow-atmosphere interactions makes direct validation of the energy balance terms challenging. However, the energy balance estimates are assessed by comparing to measured snow and stubble surface temperatures, snow surface incoming shortwave radiation and areal average turbulent fluxes. Advection estimates are validated from a two-dimensional air temperature, water vapor and windspeed profiles. Snowcover geometry relationships are validated/updated with unmanned air vehicle observations. Observations for model assessment occurred in 2015 and 2016 on wheat and canola stubble fields in north-central Saskatchewan, Canada. The model is not calibrated to melt rates, yet compares well with available observations, providing confidence in the model structure and parameterization. Sensitivity analysis using the model revealed compensatory relationships in energy balance terms resulting in limited reduction of energy available for snowmelt as stubble height increases. The proposed model is used to diagnose the influence of stubble management and climate change on melt processes to reveal the potential implications on runoff generation, infiltration and land-atmosphere interactions.

Terrestrial Observations from NOAA Operational Satellites.

PubMed

Yates, H; Strong, A; McGinnis, D; Tarpley, D

1986-01-31

Important applications to oceanography, hydrology, and agriculture have been developed from operational satellites of the National Oceanic and Atmospheric Administration and are currently expanding rapidly. Areas of interest involving the oceans include sea surface temperature, ocean currents, and ocean color. Satellites can monitor various hydrological phenomena, including regional and global snow cover, river and sea ice extent, and areas of global inundation. Agriculturally important quantities derived from operational satellite observations include precipitation, daily temperature extremes, canopy temperatures, insolation, and snow cover. This overview describes the current status of each area.

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.

Vertical structure of recent Arctic warming.

PubMed

Graversen, Rune G; Mauritsen, Thorsten; Tjernström, Michael; Källén, Erland; Svensson, Gunilla

2008-01-03

Near-surface warming in the Arctic has been almost twice as large as the global average over recent decades-a phenomenon that is known as the 'Arctic amplification'. The underlying causes of this temperature amplification remain uncertain. The reduction in snow and ice cover that has occurred over recent decades may have played a role. Climate model experiments indicate that when global temperature rises, Arctic snow and ice cover retreats, causing excessive polar warming. Reduction of the snow and ice cover causes albedo changes, and increased refreezing of sea ice during the cold season and decreases in sea-ice thickness both increase heat flux from the ocean to the atmosphere. Changes in oceanic and atmospheric circulation, as well as cloud cover, have also been proposed to cause Arctic temperature amplification. Here we examine the vertical structure of temperature change in the Arctic during the late twentieth century using reanalysis data. We find evidence for temperature amplification well above the surface. Snow and ice feedbacks cannot be the main cause of the warming aloft during the greater part of the year, because these feedbacks are expected to primarily affect temperatures in the lowermost part of the atmosphere, resulting in a pattern of warming that we only observe in spring. A significant proportion of the observed temperature amplification must therefore be explained by mechanisms that induce warming above the lowermost part of the atmosphere. We regress the Arctic temperature field on the atmospheric energy transport into the Arctic and find that, in the summer half-year, a significant proportion of the vertical structure of warming can be explained by changes in this variable. We conclude that changes in atmospheric heat transport may be an important cause of the recent Arctic temperature amplification.

Simulated cold bias being improved by using MODIS time-varying albedo in the Tibetan Plateau in WRF model

NASA Astrophysics Data System (ADS)

Meng, X.; Lyu, S.; Zhang, T.; Zhao, L.; Li, Z.; Han, B.; Li, S.; Ma, D.; Chen, H.; Ao, Y.; Luo, S.; Shen, Y.; Guo, J.; Wen, L.

2018-04-01

Systematic cold biases exist in the simulation for 2 m air temperature in the Tibetan Plateau (TP) when using regional climate models and global atmospheric general circulation models. We updated the albedo in the Weather Research and Forecasting (WRF) Model lower boundary condition using the Global LAnd Surface Satellite Moderate-Resolution Imaging Spectroradiometer albedo products and demonstrated evident improvement for cold temperature biases in the TP. It is the large overestimation of albedo in winter and spring in the WRF model that resulted in the large cold temperature biases. The overestimated albedo was caused by the simulated precipitation biases and over-parameterization of snow albedo. Furthermore, light-absorbing aerosols can result in a large reduction of albedo in snow and ice cover. The results suggest the necessity of developing snow albedo parameterization using observations in the TP, where snow cover and melting are very different from other low-elevation regions, and the influence of aerosols should be considered as well. In addition to defining snow albedo, our results show an urgent call for improving precipitation simulation in the TP.

Measurement of the Spectral Absorption of Liquid Water in Melting Snow With an Imaging Spectrometer

NASA Technical Reports Server (NTRS)

Green, Robert O.; Dozier, Jeff

1995-01-01

Melting of the snowpack is a critical parameter that drives aspects of the hydrology in regions of the Earth where snow accumulates seasonally. New techniques for measurement of snow melt over regional scales offer the potential to improve monitoring and modeling of snow-driven hydrological processes. In this paper we present the results of measuring the spectral absorption of liquid water in a melting snowpack with the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). AVIRIS data were acquired over Mammoth Mountain, in east central California on 21 May 1994 at 18:35 UTC. The air temperature at 2926 m on Mammoth Mountain at site A was measured at 15-minute intervals during the day preceding the AVIRIS data acquisition. At this elevation. the air temperature did not drop below freezing the night of the May 20 and had risen to 6 degrees Celsius by the time of the overflight on May 21. These temperature conditions support the presence of melting snow at the surface as the AVIRIS data were acquired.

The Various Influences due to Aerosol Depositions

NASA Technical Reports Server (NTRS)

Yasunari, Teppei

2011-01-01

Recently the issue on glacier retreats comes up and many factors should be relevant to the issue. The absorbing aerosols such as dust and black carbon (BC) are considered to be one of the factors. After they deposited onto the snow surface, it will reduce snow albedo (called snow darkening effect) and probably contribute to further melting of glacier. The Goddard Earth Observing System version 5 (GEOS-5) has developed at NASA/GSFC. However, the original snowpack model used in the land surface model in the GEOS-5 did not consider the snow darkening effect. Here we developed the new snow albedo scheme which can consider the snow darkening effect. In addition, another scheme on calculating mass concentrations on the absorbing aerosols in snowpack was also developed, in which the direct aerosol depositions from the chemical transport model in the GEOS-5 were used. The scheme has been validated with the observed data obtained at backyard of the Institute of Low Temperature Science, Hokkaido University, by Dr. Teruo Aoki (Meteorological Research Institute) et al. including me. The observed data was obtained when I was Ph.D.caftdidate. The original GEOS-5 during 2007-2009 over the Himalayas and Tibetan Plateau region showed more reductions of snow than that of the new GEOS-5 because the original one used lower albedo settings. On snow cover fraction, the new GEOS-5 simulated more realistic snow-covered area comparing to the MODIS snow cover fraction. The reductions on snow albedo, snow cover fraction, and snow water equivalent were seen with statistically significance if we consider the snow darkening effect comparing to the results without the snow darkening effect. In the real world, debris cover, inside refreezing process, surface flow of glacier, etc. affect glacier mass balance and the simulated results immediately do not affect whole glacier retreating. However, our results indicate that some surface melting over non debris covered parts of the glacier would be explained by the snow darkening effect. Further discussion and observations are necessary to assess the glacier issue.

Climatic controls on the snowmelt hydrology of the northern Rocky Mountains

USGS Publications Warehouse

Pederson, G.T.; Gray, S.T.; Ault, T.; Marsh, W.; Fagre, D.B.; Bunn, A.G.; Woodhouse, C.A.; Graumlich, L.J.

2011-01-01

The northern Rocky Mountains (NRMs) are a critical headwaters region with the majority of water resources originating from mountain snowpack. Observations showing declines in western U.S. snowpack have implications for water resources and biophysical processes in high-mountain environments. This study investigates oceanic and atmospheric controls underlying changes in timing, variability, and trends documented across the entire hydroclimatic-monitoring system within critical NRM watersheds. Analyses were conducted using records from 25 snow telemetry (SNOTEL) stations, 148 1 April snow course records, stream gauge records from 14 relatively unimpaired rivers, and 37 valley meteorological stations. Over the past four decades, midelevation SNOTEL records show a tendency toward decreased snowpack with peak snow water equivalent (SWE) arriving and melting out earlier. Temperature records show significant seasonal and annual decreases in the number of frost days (days ???0??C) and changes in spring minimum temperatures that correspond with atmospheric circulation changes and surface-albedo feedbacks in March and April. Warmer spring temperatures coupled with increases in mean and variance of spring precipitation correspond strongly to earlier snowmeltout, an increased number of snow-free days, and observed changes in streamflow timing and discharge. The majority of the variability in peak and total annual snowpack and streamflow, however, is explained by season-dependent interannual-to-interdecadal changes in atmospheric circulation associated with Pacific Ocean sea surface temperatures. Over recent decades, increased spring precipitation appears to be buffering NRM total annual streamflow from what would otherwise be greater snow-related declines in hydrologic yield. Results have important implications for ecosystems, water resources, and long-lead-forecasting capabilities. ?? 2011 American Meteorological Society.

An intercomparison of GCM and RCM dynamical downscaling for characterizing the hydroclimatology of California and Nevada

NASA Astrophysics Data System (ADS)

Xu, Z.; Rhoades, A.; Johansen, H.; Ullrich, P. A.; Collins, W. D.

2017-12-01

Dynamical downscaling is widely used to properly characterize regional surface heterogeneities that shape the local hydroclimatology. However, the factors in dynamical downscaling, including the refinement of model horizontal resolution, large-scale forcing datasets and dynamical cores, have not been fully evaluated. Two cutting-edge global-to-regional downscaling methods are used to assess these, specifically the variable-resolution Community Earth System Model (VR-CESM) and the Weather Research & Forecasting (WRF) regional climate model, under different horizontal resolutions (28, 14, and 7 km). Two groups of WRF simulations are driven by either the NCEP reanalysis dataset (WRF_NCEP) or VR-CESM outputs (WRF_VRCESM) to evaluate the effects of the large-scale forcing datasets. The impacts of dynamical core are assessed by comparing the VR-CESM simulations to the coupled WRF_VRCESM simulations with the same physical parameterizations and similar grid domains. The simulated hydroclimatology (i.e., total precipitation, snow cover, snow water equivalent and surface temperature) are compared with the reference datasets. The large-scale forcing datasets are critical to the WRF simulations in more accurately simulating total precipitation, SWE and snow cover, but not surface temperature. Both the WRF and VR-CESM results highlight that no significant benefit is found in the simulated hydroclimatology by just increasing horizontal resolution refinement from 28 to 7 km. Simulated surface temperature is sensitive to the choice of dynamical core. WRF generally simulates higher temperatures than VR-CESM, alleviates the systematic cold bias of DJF temperatures over the California mountain region, but overestimates the JJA temperature in California's Central Valley.

Towards the Consideration of Surface and Environment variables for a Microwave Precipitation Algorithm Over Land

NASA Astrophysics Data System (ADS)

Wang, N. Y.; You, Y.; Ferraro, R. R.; Guch, I.

2014-12-01

Microwave satellite remote sensing of precipitation over land is a challenging problem due to the highly variable land surface emissivity, which, if not properly accounted for, can be much greater than the precipitation signal itself, especially in light rain/snow conditions. Additionally, surfaces such as arid land, deserts and snow cover have brightness temperatures characteristics similar to precipitation Ongoing work by NASA's GPM microwave radiometer team is constructing databases for the GPROF algorithm through a variety of means, however, there is much uncertainty as to what is the optimal information needed for the wide array of sensors in the GPM constellation, including examination of regional conditions. The at-launch database focuses on stratification by emissivity class, surface temperature and total precipitable water (TPW). We'll perform sensitivity studies to determine the potential role of environmental factors such as land surface temperature, surface elevation, and relative humidity and storm morphology such as storm vertical structure, height, and ice thickness to improve precipitation estimation over land, including rain and snow. In other words, what information outside of the satellite radiances can help describe the background and subsequent departures from it that are active precipitating regions? It is likely that this information will be a function of the various precipitation regimes. Statistical methods such as Principal Component Analysis (PCA) will be utilized in this task. Databases from a variety of sources are being constructed. They include existing satellite microwave measurements of precipitating and non-precipitating conditions, ground radar precipitation rate estimates, surface emissivity climatology from satellites, surface temperature and TPW from NWP reanalysis. Results from the analysis of these databases with respect to the microwave precipitation sensitivity to the variety of environmental conditions in different climate regimes will be discussed.

Contemporary sand wedge development in seasonally frozen ground and paleoenvironmental implications

NASA Astrophysics Data System (ADS)

Wolfe, Stephen A.; Morse, Peter D.; Neudorf, Christina M.; Kokelj, Steven V.; Lian, Olav B.; O'Neill, H. Brendan

2018-05-01

Contemporary sand wedges and sand veins are active in seasonally frozen ground within the extensive discontinuous permafrost zone in Northwest Territories, Canada. The region has a subarctic continental climate with 291 mm a-1 precipitation, -4.1 °C mean annual air temperature, warm summers (July mean 17.0 °C), and cold winters (January mean -26.6 °C). Five years of continuous observations indicate that interannual variation of the ground thermal regime is dominantly controlled by winter air temperature and snow cover conditions. At sandy sites, thin snow cover and high thermal conductivity promote rapid freezing, high rates of ground cooling, and low near-surface ground temperatures (-15 to -25 °C), resulting in thermal contraction cracking to depths of 1.2 m. Cracking potentials are high in sandy soils when air temperatures are <-30 °C on successive days, mean freezing season air temperatures are ≤-17 °C, and snow cover is <0.15 m thick. In contrast, surface conditions in peatlands maintain permafrost, but thermal contraction cracking does not occur because thicker snow cover and the thermal properties of peat prolong freezeback and maintain higher winter ground temperatures. A combination of radiocarbon dating, optical dating, and stratigraphic observations were used to differentiate sand wedge types and formation histories. Thermal contraction cracks that develop in the sandy terrain are filled by surface (allochthonous) and/or host (autochthonous) material during the thaw season. Epigenetic sand wedges infilled with allochthonous sand develop within former beach sediments beneath an active eolian sand sheet. Narrower and deeper syngenetic wedges developed within aggrading eolian sand sheets, whereas wider and shallower antisyngenetic wedges developed in areas of active erosion. Thermal contraction cracking beneath vegetation-stabilized surfaces leads to crack infilling by autochthonous host and overlying organic material, with resultant downturning and subsidence of adjacent strata. Sand wedge development in seasonally frozen ground with limited surface sediment supply can result in stratigraphy similar to ice-wedge and composite-wedge pseudomorphs. Therefore, caution must be exercised when interpreting this suite of forms and inferring paleoenvironments.

Evolution of the snow area index of the subarctic snowpack in central Alaska over a whole season. consequences for the air to snow transfer of pollutants.

PubMed

Taillandier, A S; Domine, F; Simpson, W R; Sturm, M; Douglas, T A; Severin, K

2006-12-15

The detailed physical characteristics of the subarctic snowpack must be known to quantify the exchange of adsorbed pollutants between the atmosphere and the snow cover. For the first time, the combined evolutions of specific surface area (SSA), snow stratigraphy, temperature, and density were monitored throughout winter in central Alaska. We define the snow area index (SAI) as the vertically integrated surface area of snow crystals, and this variable is used to quantify pollutants' adsorption. Intense metamorphism generated by strong temperature gradients formed a thick depth hoar layer with low SSA (90 cm(2) g-1) and density (200 kg m(-3)), resulting in a low SAI. After snowpack buildup in autumn, the winter SAI remained around 1000 m(2)/m(2) of ground, much lower than the SAI of the Arctic snowpack, 2500 m(2) m-(2). With the example of PCBs 28 and 180, we calculate that the subarctic snowpack is a smaller reservoir of adsorbed pollutants than the Arctic snowpack and less efficiently transfers adsorbed pollutants from the atmosphere to ecosystems. The difference is greater for the more volatile PCB 28. With climate change, snowpack structure will be modified, and the snowpack's ability to transfer adsorbed pollutants from the atmosphere to ecosystems may be reduced, especially for the more volatile pollutants.

Estimation of snow emissivity via assimilation of multi-frequency passive microwave data into an ensemble-based data assimilation system

NASA Astrophysics Data System (ADS)

Farhadi, L.; Bateni, S. M.; Auligne, T.; Navari, M.

2017-12-01

Snow emissivity is a key parameter for the estimation of snow surface temperature, which is needed as an initial value in climate models and determination of the outgoing long-wave radiation. Moreover, snow emissivity is required for retrieval of atmospheric parameters (e.g., temperature and humidity profiles) from satellite measurements and satellite data assimilations in numerical weather prediction systems. Microwave emission models and remote sensing data cannot accurately estimate snow emissivity due to limitations attributed to each of them. Existing microwave emission models introduce significant uncertainties in their snow emissivity estimates. This is mainly due to shortcomings of the dense media theory for snow medium at high frequencies, and erroneous forcing variables. The well-known limitations of passive microwave data such as coarse spatial resolution, saturation in deep snowpack, and signal loss in wet snow are the major drawbacks of passive microwave retrieval algorithms for estimation of snow emissivity. A full exploitation of the information contained in the remote sensing data can be achieved by merging them with snow emission models within a data assimilation framework. Such an optimal merging can overcome the specific limitations of models and remote sensing data. An Ensemble Batch Smoother (EnBS) data assimilation framework was developed in this study to combine the synthetically generated passive microwave brightness temperatures at 1.4-, 18.7-, 36.5-, and 89-GHz frequencies with the MEMLS microwave emission model to reduce the uncertainty of the snow emissivity estimates. We have used the EnBS algorithm in the context of observing system simulation experiment (or synthetic experiment) at the local scale observation site (LSOS) of the NASA CLPX field campaign. Our findings showed that the developed methodology significantly improves the estimates of the snow emissivity. The simultaneous assimilation of passive microwave brightness temperatures at all frequencies (i.e., 1.4-, 18.7-, 36.5-, and 89-GHz) reduce the root-mean-square-error (RMSE) of snow emissivity at 1.4-, 18.7-, 36.5-, and 89-GHz (H-pol.) by 80%, 42%, 52%, 40%, respectively compared to the corresponding snow emissivity estimates from the open-loop model.

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 altitude - ranging within only few hundreds of meters within one year - determines the observed high mass balance gradients. An increase in air temperature by for example 1°C during precipitation events may have even stronger impacts on glacier mass balances of tropical glacier than it would have on those of mid-latitude glaciers. This is an important reason for the high sensitivity of tropical glaciers on past and current climatic changes.

Multi-year record of atmospheric and snow surface nitrate in the central Antarctic plateau.

PubMed

Traversi, R; Becagli, S; Brogioni, M; Caiazzo, L; Ciardini, V; Giardi, F; Legrand, M; Macelloni, G; Petkov, B; Preunkert, S; Scarchilli, C; Severi, M; Vitale, V; Udisti, R

2017-04-01

Continuous all year-round samplings of atmospheric aerosol and surface snow at high (daily to 4-day) resolution were carried out at Dome C since 2004-05 to 2013 and nitrate records are here presented. Basing on a larger statistical data set than previous studies, results confirm that nitrate seasonal pattern is characterized by maxima during austral summer for both aerosol and surface snow, occurring in-phase with solar UV irradiance. This temporal pattern is likely due to a combination of nitrate sources and post-depositional processes whose intensity usually enhances during the summer. Moreover, it should be noted that a case study of the synoptic conditions, which took place during a major nitrate event, showed the occurrence of a stratosphere-troposphere exchange. The sampling of both matrices at the same time with high resolution allowed the detection of a an about one-month long recurring lag of summer maxima in snow with respect to aerosol. This result can be explained by deposition and post-deposition processes occurring at the atmosphere-snow interface, such as a net uptake of gaseous nitric acid and a replenishment of the uppermost surface layers driven by a larger temperature gradient in summer. This hypothesis was preliminarily tested by a comparison with surface layers temperature data in the 2012-13 period. The analysis of the relationship between the nitrate concentration in the gas phase and total nitrate obtained at Dome C (2012-13) showed the major role of gaseous HNO 3 to the total nitrate budget suggesting the need to further investigate the gas-to-particle conversion processes. Copyright © 2017 Elsevier Ltd. All rights reserved.

NHM-SMAP: spatially and temporally high-resolution nonhydrostatic atmospheric model coupled with detailed snow process model for Greenland Ice Sheet

NASA Astrophysics Data System (ADS)

Niwano, Masashi; Aoki, Teruo; Hashimoto, Akihiro; Matoba, Sumito; Yamaguchi, Satoru; Tanikawa, Tomonori; Fujita, Koji; Tsushima, Akane; Iizuka, Yoshinori; Shimada, Rigen; Hori, Masahiro

2018-02-01

To improve surface mass balance (SMB) estimates for the Greenland Ice Sheet (GrIS), we developed a 5 km resolution regional climate model combining the Japan Meteorological Agency Non-Hydrostatic atmospheric Model and the Snow Metamorphism and Albedo Process model (NHM-SMAP) with an output interval of 1 h, forced by the Japanese 55-year reanalysis (JRA-55). We used in situ data to evaluate NHM-SMAP in the GrIS during the 2011-2014 mass balance years. We investigated two options for the lower boundary conditions of the atmosphere: an offline configuration using snow, firn, and ice albedo, surface temperature data from JRA-55, and an online configuration using values from SMAP. The online configuration improved model performance in simulating 2 m air temperature, suggesting that the surface analysis provided by JRA-55 is inadequate for the GrIS and that SMAP results can better simulate physical conditions of snow/firn/ice. It also reproduced the measured features of the GrIS climate, diurnal variations, and even a strong mesoscale wind event. In particular, it successfully reproduced the temporal evolution of the GrIS surface melt area extent as well as the record melt event around 12 July 2012, at which time the simulated melt area extent reached 92.4 %. Sensitivity tests showed that the choice of calculation schemes for vertical water movement in snow and firn has an effect as great as 200 Gt year-1 in the GrIS-wide accumulated SMB estimates; a scheme based on the Richards equation provided the best performance.

CREST-SAFE: Snow LST validation, wetness profiler creation, and depth/SWE product development

NASA Astrophysics Data System (ADS)

Perez Diaz, C. L.; Lakhankar, T.; Romanov, P.; Khanbilvardi, R.; Munoz Barreto, J.; Yu, Y.

2017-12-01

CREST-SAFE: Snow LST validation, wetness profiler creation, and depth/SWE product development The Field Snow Research Station (also referred to as Snow Analysis and Field Experiment, SAFE) is operated by the NOAA Center for Earth System Sciences and Remote Sensing Technologies (CREST) in the City University of New York (CUNY). The field station is located within the premises of the Caribou Municipal Airport (46°52'59'' N, 68°01'07'' W) and in close proximity to the National Weather Service (NWS) Regional Forecast Office. The station was established in 2010 to support studies in snow physics and snow remote sensing. The Visible Infrared Imager Radiometer Suite (VIIRS) Land Surface Temperature (LST) Environmental Data Record (EDR) and Moderate Resolution Imaging Spectroradiometer (MODIS) LST product (provided by the Terra and Aqua Earth Observing System satellites) were validated using in situ LST (T-skin) and near-surface air temperature (T-air) observations recorded at CREST-SAFE for the winters of 2013 and 2014. Results indicate that T-air correlates better than T-skin with VIIRS LST data and that the accuracy of nighttime LST retrievals is considerably better than that of daytime. Several trends in the MODIS LST data were observed, including the underestimation of daytime values and night-time values. Results indicate that, although all the data sets showed high correlation with ground measurements, day values yielded slightly higher accuracy ( 1°C). Additionally, we created a liquid water content (LWC)-profiling instrument using time-domain reflectometry (TDR) at CREST-SAFE and tested it during the snow melt period (February-April) immediately after installation in 2014. 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. Lastly, to improve on global snow cover mapping, a snow product capable of estimating snow depth and snow water equivalent (SWE) using microwave remote sensing and the CREST Snow Depth Regression Tree Model (SDRTM) was developed. Data from AMSR2 onboard the JAXA GCOM-W1 satellite is used to produce daily global snow depth and SWE maps in automated fashion at a 10-km resolution.

Ice-atmosphere interactions in the Canadian High Arctic: Implications for the thermo-mechanical evolution of terrestrial ice masses

NASA Astrophysics Data System (ADS)

Wohlleben, Trudy M. H.

Canadian High Arctic terrestrial ice masses and the polar atmosphere evolve codependently, and interactions between the two systems can lead to feedbacks, positive and negative. The two primary positive cryosphere-atmosphere feedbacks are: (1) The snow/ice-albedo feedback (where area changes in snow and/or ice cause changes in surface albedo and surface air temperatures, leading to further area changes in snow/ice); and (2) The elevation - mass balance feedback (where thickness changes in terrestrial ice masses cause changes to atmospheric circulation and precipitation patterns, leading to further ice thickness changes). In this thesis, numerical experiments are performed to: (1) quantify the magnitudes of the two feedbacks for chosen Canadian High Arctic terrestrial ice masses; and (2) to examine the direct and indirect consequences of surface air temperature changes upon englacial temperatures with implications for ice flow, mass flux divergence, and topographic evolution. Model results show that: (a) for John Evans Glacier, Ellesmere Island, the magnitude of the terrestrial snow/ice-albedo feedback can locally exceed that of sea ice on less than decadal timescales, with implications for glacier response times to climate perturbations; (b) although historical air temperature changes might be the direct cause of measured englacial temperature anomalies in various glacier and ice cap accumulation zones, they can also be the indirect cause of their enhanced diffusive loss; (c) while the direct result of past air temperature changes has been to cool the interior of John Evans Glacier, and its bed, the indirect result has been to create and maintain warm (pressure melting point) basal temperatures in the ablation zone; and (d) for Devon Ice Cap, observed mass gains in the northwest sector of the ice cap would be smaller without orographic precipitation and the mass balance---elevation feedback, supporting the hypothesis that this feedback is playing a role in the evolution of the ice cap.

Improvement and further development of SSM/I overland parameter algorithms using the WetNet workstation

NASA Technical Reports Server (NTRS)

Neale, Christopher M. U.; Mcdonnell, Jeffrey J.; Ramsey, Douglas; Hipps, Lawrence; Tarboton, David

1993-01-01

Since the launch of the DMSP Special Sensor Microwave/Imager (SSM/I), several algorithms have been developed to retrieve overland parameters. These include the present operational algorithms resulting from the Navy calibration/validation effort such as land surface type (Neale et al. 1990), land surface temperature (McFarland et al. 1990), surface moisture (McFarland and Neale, 1991) and snow parameters (McFarland and Neale, 1991). In addition, other work has been done including the classification of snow cover and precipitation using the SSM/I (Grody, 1991). Due to the empirical nature of most of the above mentioned algorithms, further research is warranted and improvements can probably be obtained through a combination of radiative transfer modelling to study the physical processes governing the microwave emissions at the SSM/I frequencies, and the incorporation of additional ground truth data and special cases into the regression data sets. We have proposed specifically to improve the retrieval of surface moisture and snow parameters using the WetNet SSM/I data sets along with ground truth information namely climatic variables from the NOAA cooperative network of weather stations as well as imagery from other satellite sensors such as the AVHRR and Thematic Mapper. In the case of surface moisture retrievals the characterization of vegetation density is of primary concern. The higher spatial resolution satellite imagery collected at concurrent periods will be used to characterize vegetation types and amounts which, along with radiative transfer modelling should lead to more physically based retrievals. Snow parameter retrieval algorithm improvement will initially concentrate on the classification of snowpacks (dry snow, wet snow, refrozen snow) and later on specific products such as snow water equivalent. Significant accomplishments in the past year are presented.

Effects of multilayer snow scheme on the simulation of snow: Offline Noah and coupled with NCEP CFSv2

NASA Astrophysics Data System (ADS)

Saha, Subodh Kumar; Sujith, K.; Pokhrel, Samir; Chaudhari, Hemantkumar S.; Hazra, Anupam

2017-03-01

The Noah version 2.7.1 is a moderately complex land surface model (LSM), with a single layer snowpack, combined with vegetation and underlying soil layer. Many previous studies have pointed out biases in the simulation of snow, which may hinder the skill of a forecasting system coupled with the Noah. In order to improve the simulation of snow by the Noah, a multilayer snow scheme (up to a maximum of six layers) is introduced. As Noah is the land surface component of the Climate Forecast System version 2 (CFSv2) of the National Centers for Environmental Prediction (NCEP), the modified Noah is also coupled with the CFSv2. The offline LSM shows large improvements in the simulation of snow depth, snow water equivalent (SWE), and snow cover area during snow season (October to June). CFSv2 with the modified Noah reveals a dramatic improvements in the simulation of snow depth and 2 m air temperature and moderate improvements in SWE. As suggested in the previous diagnostic and sensitivity study, improvements in the simulation of snow by CFSv2 have lead to the reduction in dry bias over the Indian subcontinent (by a maximum of 2 mm d-1). The multilayer snow scheme shows promising results in the simulation of snow as well as Indian summer monsoon rainfall and hence this development may be the part of the future version of the CFS.

Dominance of grain size impacts on seasonal snow albedo at open sites in New Hampshire

NASA Astrophysics Data System (ADS)

Adolph, Alden C.; Albert, Mary R.; Lazarcik, James; Dibb, Jack E.; Amante, Jacqueline M.; Price, Andrea

2017-01-01

Snow cover serves as a major control on the surface energy budget in temperate regions due to its high reflectivity compared to underlying surfaces. Winter in the northeastern United States has changed over the last several decades, resulting in shallower snowpacks, fewer days of snow cover, and increasing precipitation falling as rain in the winter. As these climatic changes occur, it is imperative that we understand current controls on the evolution of seasonal snow albedo in the region. Over three winter seasons between 2013 and 2015, snow characterization measurements were made at three open sites across New Hampshire. These near-daily measurements include spectral albedo, snow optical grain size determined through contact spectroscopy, snow depth, snow density, black carbon content, local meteorological parameters, and analysis of storm trajectories using the Hybrid Single-Particle Lagrangian Integrated Trajectory model. Using analysis of variance, we determine that land-based winter storms result in marginally higher albedo than coastal storms or storms from the Atlantic Ocean. Through multiple regression analysis, we determine that snow grain size is significantly more important in albedo reduction than black carbon content or snow density. And finally, we present a parameterization of albedo based on days since snowfall and temperature that accounts for 52% of variance in albedo over all three sites and years. Our improved understanding of current controls on snow albedo in the region will allow for better assessment of potential response of seasonal snow albedo and snow cover to changing climate.

Temperature signal in suspended sediment export from an Alpine catchment

NASA Astrophysics Data System (ADS)

Costa, Anna; Molnar, Peter; Stutenbecker, Laura; Bakker, Maarten; Silva, Tiago A.; Schlunegger, Fritz; Lane, Stuart N.; Loizeau, Jean-Luc; Girardclos, Stéphanie

2018-01-01

Suspended sediment export from large Alpine catchments ( > 1000 km2) over decadal timescales is sensitive to a number of factors, including long-term variations in climate, the activation-deactivation of different sediment sources (proglacial areas, hillslopes, etc.), transport through the fluvial system, and potential anthropogenic impacts on the sediment flux (e.g. through impoundments and flow regulation). Here, we report on a marked increase in suspended sediment concentrations observed near the outlet of the upper Rhône River Basin in the mid-1980s. This increase coincides with a statistically significant step-like increase in basin-wide mean air temperature. We explore the possible explanations of the suspended sediment rise in terms of changes in water discharge (transport capacity), and the activation of different potential sources of fine sediment (sediment supply) in the catchment by hydroclimatic forcing. Time series of precipitation and temperature-driven snowmelt, snow cover, and ice melt simulated with a spatially distributed degree-day model, together with erosive rainfall on snow-free surfaces, are tested to explore possible reasons for the rise in suspended sediment concentration. We show that the abrupt change in air temperature reduced snow cover and the contribution of snowmelt, and enhanced ice melt. The results of statistical tests show that the onset of increased ice melt was likely to play a dominant role in the suspended sediment concentration rise in the mid-1980s. Temperature-driven enhanced melting of glaciers, which cover about 10 % of the catchment surface, can increase suspended sediment yields through an increased contribution of sediment-rich glacial meltwater, increased sediment availability due to glacier recession, and increased runoff from sediment-rich proglacial areas. The reduced extent and duration of snow cover in the catchment are also potential contributors to the rise in suspended sediment concentration through hillslope erosion by rainfall on snow-free surfaces, and increased meltwater production on snow-free glacier surfaces. Despite the rise in air temperature, changes in mean discharge in the mid-1980s were not statistically significant, and their interpretation is complicated by hydropower reservoir management and the flushing operations at intakes. Overall, the results show that to explain changes in suspended sediment transport from large Alpine catchments it is necessary to include an understanding of the multitude of sediment sources involved together with the hydroclimatic conditioning of their activation (e.g. changes in precipitation, runoff, air temperature). In addition, this study points out that climate signals in suspended sediment dynamics may be visible even in highly regulated and human-impacted systems. This is particularly relevant for quantifying climate change and hydropower impacts on streamflow and sediment budgets in Alpine catchments.

Summer snowmelt patterns in the South Shetlands using TerraSAR-X imagery

NASA Astrophysics Data System (ADS)

Mora, C.; Jimenez, J. J.; Catalao Fernades, J.; Ferreira, A.; David, A.; Ramos, M.; Vieira, G.

2014-12-01

Snow plays an important role in controlling ground thermal regime and thus influencing permafrost distribution in the lower areas of the South Shetlands archipelago, where late lying snowpatches protect the soil from summer warming. However, summer snow distribution is complex in the mountainous environments of the Maritime Antarctica and it is very difficult to obtain accurate mapping products of snow cover extent and also to monitor snowmelt. Field observations of snow cover in the region are currently based on: i) thickness data from a very scarce network of meteorological stations, ii) temperature poles allowing to estimate snow thickness, iii) and time-lapse cameras allowing for assessing snow distribution over relatively small areas. The high cloudiness of the Maritime Antarctic environment limits good mapping results from the analysis of optical remote sensing imagery such as Landsat, QuickBird or GeoEye. Therefore, microwave sensors provide the best imagery, since they are not influenced by cloudiness and are sensitive to wet-snow, typical of the melting season. We have acquired TerraSAR-X scenes for Deception and Livingston Islands for January-March 2014 in spotlight (HH, VV and HH/VV) and stripmap modes (HH) and analyse the radar backscattering for determining the differences between wet-snow, dry-snow and bare soil aiming at developing snow melt pattern maps. For ground truthing, snowpits were dug in order to characterize snow stratigraphy, grain size, grain type and snow density and to evaluate its effects on radar backscattering. Time-lapse cameras allow to identify snow patch boundaries in the field and ground surface temperatures obtained with minloggers, together with air temperatures, allow to identify the presence of snow cover in the ground. The current research is conducted in the framework of the project PERMANTAR-3 (Permafrost monitoring and modelling in Antarctic Peninsula - PTDC/AAG-GLO/3908/2012 of the FCT and PROPOLAR).

Comparison between AVHRR surface temperature data and in-situ weather station temperatures over the Greenland Ice Sheet

NASA Astrophysics Data System (ADS)

Rezvanbehbahani, S.; Csatho, B. M.; Comiso, J. C.; Babonis, G. S.

2011-12-01

Advanced Very-High Resolution Radiometer (AVHRR) images have been exhaustively used to measure surface temperature time series of the Greenland Ice sheet. The purpose of this study is to assess the accuracy of monthly average ice sheet surface temperatures, derived from thermal infrared AVHRR satellite imagery on a 6.25 km grid. In-situ temperature data sets are from the Greenland Collection Network (GC-Net). GC-Net stations comprise sensors monitoring air temperature at 1 and 2 meter above the snow surface, gathered at every 60 seconds and monthly averaged to match the AVHRR temporal resolution. Our preliminary results confirm the good agreement between satellite and in-situ temperature measurements reported by previous studies. However, some large discrepancies still exist. While AVHRR provides ice surface temperature, in-situ stations measure air temperatures at different elevations above the snow surface. Since most in-situ data on ice sheets are collected by Automatic Weather Station (AWS) instruments, it is important to characterize the difference between surface and air temperatures. Therefore, we compared and analyzed average monthly AVHRR ice surface temperatures using data collected in 2002. Differences between these temperatures correlate with in-situ temperatures and GC-Net station elevations, with increasing differences at lower elevations and higher temperatures. The Summit Station (3199 m above sea level) and the Swiss Camp (1176 m above sea level) results were compared as high altitude and low altitude stations for 2002, respectively. Our results show that AVHRR derived temperatures were 0.5°K warmer than AWS temperature at the Summit Station, while this difference was 2.8°K in the opposite direction for the Swiss Camp with surface temperatures being lower than air temperatures. The positive bias of 0.5°K at the high altitude Summit Station (surface warmer than air) is within the retrieval error of AVHRR temperatures and might be in part due to atmospheric inversion. The large negative bias of 2.8°K at the low altitude Swiss Camp (surface colder than the air) could be caused by a combination of different factors including local effects such as more windy circumstances above the snow surface and biases introduced by the cloud-masking applied on the AVHRR images. Usually only satellite images acquired in clear-sky conditions are used for deriving monthly AVHRR average temperatures. Since cloud-free days are usually warmer, satellite derived temperatures tend to underestimate the real average temperatures, especially regions with frequent cloud cover, such as Swiss Camp. Therefore, cautions must be exercised while using ice surface temperatures derived from satellite imagery for glaciological applications. Eliminating the cloudy day's' temperature from the in-situ data prior to the comparison with AVHRR derived temperatures will provide a better assessment of AVHRR surface temperature measurement accuracy.

Snow crystal imaging using scanning electron microscopy: III. Glacier ice, snow and biota

USGS Publications Warehouse

Rango, A.; Wergin, W.P.; Erbe, E.F.; Josberger, E.G.

2000-01-01

Low-temperature scanning electron microscopy (SEM) was used to observe metamorphosed snow, glacial firn, and glacial ice obtained from South Cascade Glacier in Washington State, USA. Biotic samples consisting of algae (Chlamydomonas nivalis) and ice worms (a species of oligochaetes) were also collected and imaged. In the field, the snow and biological samples were mounted on copper plates, cooled in liquid nitrogen, and stored in dry shipping containers which maintain a temperature of -196??C. The firn and glacier ice samples were obtained by extracting horizontal ice cores, 8 mm in diameter, at different levels from larger standard glaciological (vertical) ice cores 7.5 cm in diameter. These samples were cooled in liquid nitrogen and placed in cryotubes, were stored in the same dry shipping container, and sent to the SEM facility. In the laboratory, the samples were sputter coated with platinum and imaged by a low-temperature SEM. To image the firn and glacier ice samples, the cores were fractured in liquid nitrogen, attached to a specimen holder, and then imaged. While light microscope images of snow and ice are difficult to interpret because of internal reflection and refraction, the SEM images provide a clear and unique view of the surface of the samples because they are generated from electrons emitted or reflected only from the surface of the sample. In addition, the SEM has a great depth of field with a wide range of magnifying capabilities. The resulting images clearly show the individual grains of the seasonal snowpack and the bonding between the snow grains. Images of firn show individual ice crystals, the bonding between the crystals, and connected air spaces. Images of glacier ice show a crystal structure on a scale of 1-2 mm which is considerably smaller than the expected crystal size. Microscopic air bubbles, less than 15 ??m in diameter, clearly marked the boundaries between these crystal-like features. The life forms associated with the glacier were easily imaged and studied. The low-temperature SEM sample collecting and handling methods proved to be operable in the field; the SEM analysis is applicable to glaciological studies and reveals details unattainable by conventional light microscopic methods.Low temperature scanning electron microscopy (SEM) was used to observe metamorphosed snow, glacial firn, and glacial ice obtained from South Cascade Glacier in Washington State, USA. Biotic samples consisting of algae and ice worms were also collected and imaged. The SEM images provide a clear and unique view of the surface of the samples because they are generated from electrons emitted or reflected only from the surface of the sample. The SEM has a great depth of field with a wide range of magnifying capabilities.

Freeze/thaw conditions at periglacial landforms in Kapp Linné, Svalbard, investigated using field observations, in situ, and radar satellite monitoring

NASA Astrophysics Data System (ADS)

Eckerstorfer, M.; Malnes, E.; Christiansen, H. H.

2017-09-01

In periglacial landscapes, snow dynamics and microtopography have profound implications of freeze-thaw conditions and thermal regime of the ground. We mapped periglacial landforms at Kapp Linné, central Svalbard, where we chose six widespread landforms (solifluction sheet, nivation hollow, palsa and peat in beach ridge depressions, raised marine beach ridge, and exposed bedrock ridge) as study sites. At these six landforms, we studied ground thermal conditions, freeze-thaw cycles, and snow dynamics using a combination of in situ monitoring and C-band radar satellite data in the period 2005-2012. Based on these physical parameters, the six studied landforms can be classified into raised, dry landforms with minor ground ice content and a thin, discontinuous snow cover and into wet landforms with high ice content located in the topographical depressions in-between with medium to thick snow cover. This results in a differential snow-melting period inferred from the C-band radar satellite data, causing the interseasonal and interlandform variability in the onset of ground surface thawing once the ground becomes snow free. Therefore, variability also exists in the period of thawed ground surface conditions. However, the length of the season with thawed ground surface conditions does not determine the mean annual ground surface temperature, it only correlates well with the active layer depths. From the C-band radar satellite data series, measured relative backscatter trends hint toward a decrease in snow cover through time and a more frequent presence of ice layers from mid-winter rain on snow events at Kapp Linné, Svalbard.

L-Band Brightness Temperature Variations at Dome C and Snow Metamorphism at the Surface

NASA Technical Reports Server (NTRS)

Brucker, Ludovic; Dinnat, Emmanuel; Picard, Ghislain; Champollion, Nicolas

2014-01-01

The Antarctic Plateau is a promising site to monitor microwave radiometers' drift, and to inter-calibrate microwave radiometers, especially 1.4 GigaHertz (L-band) radiometers on board the Soil Moisture and Ocean Salinity (SMOS), and AquariusSAC-D missions. The Plateau is a thick ice cover, thermally stable in depth, with large dimensions, and relatively low heterogeneities. In addition, its high latitude location in the Southern Hemisphere enables frequent observations by polar-orbiting satellites, and no contaminations by radio frequency interference. At Dome C (75S, 123E), on the Antarctic Plateau, the substantial amount of in-situ snow measurements available allows us to interpret variations in space-borne microwave brightness temperature (TB) (e.g. Macelloni et al., 2007, 2013, Brucker et al., 2011, Champollion et al., 2013). However, to analyze the observations from the Aquarius radiometers, whose sensitivity is 0.15 K, the stability of the snow layers near the surface that are most susceptible to rapidly change needs to be precisely assessed. This study focuses on the spatial and temporal variations of the Aquarius TB over the Antarctic Plateau, and at Dome C in particular, to highlight the impact of snow surface metamorphism on the TB observations at L-band.

Aquarius Brightness Temperature Variations at Dome C and Snow Metamorphism at the Surface. [29

NASA Technical Reports Server (NTRS)

Brucker, Ludovic; Dinnat, Emmanuel Phillippe; Picard, Ghislain; Champollion, Nicolas

2014-01-01

The Antarctic Plateau is a promising site to monitor microwave radiometers' drift, and to inter-calibrate microwave radiometers, especially 1.4 GHz (L-band) radiometers on board the Soil Moisture and Ocean Salinity (SMOS), and AquariusSAC-D missions. The Plateau is a thick ice cover, thermally stable in depth, with large dimensions, and relatively low heterogeneities. In addition, its high latitude location in the Southern Hemisphere enables frequent observations by polar-orbiting satellites, and no contaminations by radio frequency interference. At Dome C (75S, 123E), on the Antarctic Plateau, the substantial amount of in-situ snow measurements available allows us to interpret variations in space-borne microwave brightness temperature (TB) (e.g. Macelloni et al., 2007, 2013, Brucker et al., 2011, Champollion et al., 2013). However, to analyze the observations from the Aquarius radiometers, whose sensitivity is 0.15 K, the stability of the snow layers near the surface that are most susceptible to rapidly change needs to be precisely assessed. This study focuses on the spatial and temporal variations of the Aquarius TB over the Antarctic Plateau, and at Dome C in particular, to highlight the impact of snow surface metamorphism on the TB observations at L-band.

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.

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.

Electric field measurements during the blowing snow in a cryogenic wind tunnel by a non-contact voltmeter

NASA Astrophysics Data System (ADS)

Sato, A.; Omiya, S.

2011-12-01

It is known that the average atmospheric electric field is +100V/m in fair weather (positive electric field vector points downward). An increase of atmospheric electric field is reported when the blowing snow occurred. This phenomenon is mainly explained by the fact that the blowing snow particles have negative charge in average. It is suggested that an electrostatic force, given by the product of the electric field and the charge of the particle, may influence the particle trajectory and change those movements, saltation and suspension. The purpose of this experiment is to clarify the characteristics of the electric field during blowing snow event. Experiments were carried out in the cryogenic wind tunnel of Snow and Ice Research Center, NIED. A non-contact voltmeter was used to measure the electric field. An artificial blowing snow was generated by a snow particle supply machine. The rolling brushes of the machine scratch the snow surface and supply snow particles into the airflow. This machine made it possible to supply the snow particles at an arbitrary rate. This experiment was conducted in the following experimental conditions; wind speed of 5 to 7 m/s (3 patterns), supply snow quantity of 8.7 to 34.9 g/m/s (4 patterns), air temperature of -10 degree Celsius, fetch of 10 m and hard snow surface. Measured electric field was all negative, which is opposite direction to the previous measurements. This means that the blowing snow particles had positive charges. The negative electric field tended to increase with increase of the wind speed and the mass flux. These results can be explained from the previous experiment by Omiya and Sato (2010). The snow particles gain positive charges by the friction with the rolling brush which is made from polypropylene, however the particles accumulate negative charges gradually with increase of the collisions to the snow surface. Probably, the positive charges might have remained on the snow particles that had passed over the measurement point. Moreover, it is thought that because the saltation length is longer when the wind speed is higher, fewer collision frequencies left the particles more positive charges. REFERENCE:Omiya and Sato(2010): Measurement of electrostatic charge of blowing snow particles in a wind tunnel focusing on collision frequency to the snow surface. Hokkaido University Collection of Scholarly and Academic Papers

Snow model design for operational purposes

NASA Astrophysics Data System (ADS)

Kolberg, Sjur

2017-04-01

A parsimonious distributed energy balance snow model intended for operational use is evaluated using discharge, snow covered area and grain size; the latter two as observed from the MODIS sensor. The snow model is an improvement of the existing GamSnow model, which is a part of the Enki modelling framework. Core requirements for the new version have been: 1. Reduction of calibration freedom, motivated by previous experience of non-identifiable parameters in the existing version 2. Improvement of process representation based on recent advances in physically based snow modelling 3. Limiting the sensitivity to forcing data which are poorly known over the spatial domain of interest (often in mountainous areas) 4. Preference for observable states, and the ability to improve from updates. The albedo calculation is completely revised, now based on grain size through an emulation of the SNICAR model (Flanner and Zender, 2006; Gardener and Sharp, 2010). The number of calibration parameters in the albedo model is reduced from 6 to 2. The wind function governing turbulent energy fluxes has been reduced from 2 to 1 parameter. Following Raleigh et al (2011), snow surface radiant temperature is split from the top layer thermodynamic temperature, using bias-corrected wet-bulb temperature to model the former. Analyses are ongoing, and the poster will bring evaluation results from 16 years of MODIS observations and more than 25 catchments in southern Norway.

Spatial and Temporal Variabilities of Solar and Longwave Radiation Fluxes below a Coniferous Forest in the French Alps

NASA Astrophysics Data System (ADS)

Sicart, J. E.; Ramseyer, V.; Lejeune, Y.; Essery, R.; Webster, C.; Rutter, N.

2017-12-01

At high altitudes and latitudes, snow has a large influence on hydrological processes. Large fractions of these regions are covered by forests, which have a strong influence on snow accumulation and melting processes. Trees absorb a large part of the incoming shortwave radiation and this heat load is mostly dissipated as longwave radiation. Trees shelter the snow surface from wind, so sub-canopy snowmelt depends mainly on the radiative fluxes: vegetation attenuates the transmission of shortwave radiation but enhances longwave irradiance to the surface. An array of 13 pyranometers and 11 pyrgeometers was deployed on the snow surface below a coniferous forest at the CEN-MeteoFrance Col de Porte station in the French Alps (1325 m asl) during the 2017 winter in order to investigate spatial and temporal variabilities of solar and infrared irradiances in different meteorological conditions. Sky view factors measured with hemispherical photographs at each radiometer location were in a narrow range from 0.2 to 0.3. The temperature of the vegetation was measured with IR thermocouples and an IR camera. In clear sky conditions, the attenuation of solar radiation by the canopy reached 96% and its spatial variability exceeded 100 W m-2. Longwave irradiance varied by 30 W m-2 from dense canopy to gap areas. In overcast conditions, the spatial variabilities of solar and infrared irradiances were reduced and remained closely related to the sky view factor. A simple radiative model taking into account the penetration through the canopy of the direct and diffuse solar radiation, and isotropic infrared emission of the vegetation as a blackbody emitter, accurately reproduced the dynamics of the radiation fluxes at the snow surface. Model results show that solar transmissivity of the canopy in overcast conditions is an excellent proxy of the sky view factor and the emitting temperature of the vegetation remained close to the air temperature in this typically dense Alpine forest.

Vehicle-Snow Interaction: Modeling, Testing and Validation

DTIC Science & Technology

2009-10-12

Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for reviewing instructions...information if it does not display a currently valid OMB control number. 1 . REPORT DATE 12 OCT 2009 2. REPORT TYPE N/A 3. DATES COVERED - 4...surface – Snow temperature ~-6 C – Stored in a freezer ~-25 C • Microtribometer – – Temperature ~-10C – Pin sizes ( 1 /8”, 1 /4”, 3/8”, 1 /2”) – Force or

Investigation of models for large-scale meteorological prediction experiments

NASA Technical Reports Server (NTRS)

Spar, J.

1973-01-01

Studies are reported of the long term responses of the model atmosphere to anomalies in snow cover and sea surface temperature. An abstract of a previously issued report on the computed response to surface anomalies in a global atmospheric model is presented, and the experiments on the effects of transient sea surface temperature on the Mintz-Arakawa atmospheric model are reported.

Effects of short-term variability of meteorological variables on soil temperature in permafrost regions

NASA Astrophysics Data System (ADS)

Beer, Christian; Porada, Philipp; Ekici, Altug; Brakebusch, Matthias

2018-03-01

Effects of the short-term temporal variability of meteorological variables on soil temperature in northern high-latitude regions have been investigated. For this, a process-oriented land surface model has been driven using an artificially manipulated climate dataset. Short-term climate variability mainly impacts snow depth, and the thermal diffusivity of lichens and bryophytes. These impacts of climate variability on insulating surface layers together substantially alter the heat exchange between atmosphere and soil. As a result, soil temperature is 0.1 to 0.8 °C higher when climate variability is reduced. Earth system models project warming of the Arctic region but also increasing variability of meteorological variables and more often extreme meteorological events. Therefore, our results show that projected future increases in permafrost temperature and active-layer thickness in response to climate change will be lower (i) when taking into account future changes in short-term variability of meteorological variables and (ii) when representing dynamic snow and lichen and bryophyte functions in land surface models.

Application of Snowfall and Wind Statistics to Snow Transport Modeling for Snowdrift Control in Minnesota.

NASA Astrophysics Data System (ADS)

Shulski, Martha D.; Seeley, Mark W.

2004-11-01

Models were utilized to determine the snow accumulation season (SAS) and to quantify windblown snow for the purpose of snowdrift control for locations in Minnesota. The models require mean monthly temperature, snowfall, density of snow, and wind frequency distribution statistics. Temperature and precipitation data were obtained from local cooperative observing sites, and wind data came from Automated Surface Observing System (ASOS)/Automated Weather Observing System (AWOS) sites in the region. The temperature-based algorithm used to define the SAS reveals a geographic variability in the starting and ending dates of the season, which is determined by latitude and elevation. Mean seasonal snowfall shows a geographic distribution that is affected by topography and proximity to Lake Superior. Mean snowfall density also exhibits variability, with lower-density snow events displaced to higher-latitude positions. Seasonal wind frequencies show a strong bimodal distribution with peaks from the northwest and southeast vector direction, with an exception for locations in close proximity to the Lake Superior shoreline. In addition, for western and south-central Minnesota there is a considerably higher frequency of wind speeds above the mean snow transport threshold of 7 m s-1. As such, this area is more conducive to higher potential snow transport totals. Snow relocation coefficients in this area are in the range of 0.4 0.9, and, according to the empirical models used in this analysis, this range implies that actual snow transport is 40% 90% of the total potential in south-central and western areas of the state.

The Costs of Climate Change: Impact of Future Snow Cover Projections on Valuation of Albedo in Forest Management

NASA Astrophysics Data System (ADS)

Burakowski, E. A.; Lutz, D. A.

2014-12-01

Surface albedo provides an important climate regulating ecosystem service, particularly in the mid-latitudes where seasonal snow cover influences surface radiation budgets. In the case of substantial seasonal snow cover, the influence of albedo can equal or surpass the climatic benefits of carbon sequestration from forest growth. Climate mitigation platforms should therefore consider albedo in their framework in order to integrate these two climatic services in an economic context for the effective design and implementation of forest management projects. Over the next century, the influence of surface albedo is projected to diminish under higher emissions scenarios due to an overall decrease in snow depth and duration of snow cover in the mid-latitudes. In this study, we focus on the change in economic value of winter albedo in the northeastern United States projected through 2100 using the Special Report on Emissions Scenarios (SRES) a1 and b1 scenarios. Statistically downscaled temperature and precipitation are used as input to the Variable Infiltration Capacity (VIC) model to provide future daily snow depth fields through 2100. Using VIC projections of future snow depth, projected winter albedo fields over deforested lands were generated using an empirical logarithmic relationship between snow depth and albedo derived from a volunteer network of snow observers in New Hampshire over the period Nov 2011 through 2014. Our results show that greater reductions in snow depth and the number of winter days with snow cover in the a1 compared to the b1 scenario reduce wintertime albedo when forested lands are harvested. This result has implications on future trade-offs among albedo, carbon storage, and timber value that should be investigated in greater detail. The impacts of forest harvest on radiative forcing associated with energy redistribution (e.g., latent heat and surface roughness length) should also be considered in future work.

Surface and Atmospheric Contributions to Passive Microwave Brightness Temperatures for Falling Snow Events

NASA Technical Reports Server (NTRS)

Skofronick-Jackson, Gail; Johnson, Benjamin T.

2011-01-01

Physically based passive microwave precipitation retrieval algorithms require a set of relationships between satellite -observed brightness temperatures (TBs) and the physical state of the underlying atmosphere and surface. These relationships are nonlinear, such that inversions are ill ]posed especially over variable land surfaces. In order to elucidate these relationships, this work presents a theoretical analysis using TB weighting functions to quantify the percentage influence of the TB resulting from absorption, emission, and/or reflection from the surface, as well as from frozen hydrometeors in clouds, from atmospheric water vapor, and from other contributors. The percentage analysis was also compared to Jacobians. The results are presented for frequencies from 10 to 874 GHz, for individual snow profiles, and for averages over three cloud-resolving model simulations of falling snow. The bulk structure (e.g., ice water path and cloud depth) of the underlying cloud scene was found to affect the resultant TB and percentages, producing different values for blizzard, lake effect, and synoptic snow events. The slant path at a 53 viewing angle increases the hydrometeor contributions relative to nadir viewing channels. Jacobians provide the magnitude and direction of change in the TB values due to a change in the underlying scene; however, the percentage analysis provides detailed information on how that change affected contributions to the TB from the surface, hydrometeors, and water vapor. The TB percentage information presented in this paper provides information about the relative contributions to the TB and supplies key pieces of information required to develop and improve precipitation retrievals over land surfaces.

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.

Snow Physics and Meltwater Hydrology of the SSiB Model Employed for Climate Simulation Studies with GEOS 2 GCM

NASA Technical Reports Server (NTRS)

Mocko, David M.; Sud, Y. C.; Einaudi, Franco (Technical Monitor)

2000-01-01

Present-day climate models produce large climate drifts that interfere with the climate signals simulated in modelling studies. The simplifying assumptions of the physical parameterization of snow and ice processes lead to large biases in the annual cycles of surface temperature, evapotranspiration, and the water budget, which in turn causes erroneous land-atmosphere interactions. Since land processes are vital for climate prediction, and snow and snowmelt processes have been shown to affect Indian monsoons and North American rainfall and hydrology, special attention is now being given to cold land processes and their influence on the simulated annual cycle in GCMs. The snow model of the SSiB land-surface model being used at Goddard has evolved from a unified single snow-soil layer interacting with a deep soil layer through a force-restore procedure to a two-layer snow model atop a ground layer separated by a snow-ground interface. When the snow cover is deep, force-restore occurs within the snow layers. However, several other simplifying assumptions such as homogeneous snow cover, an empirical depth related surface albedo, snowmelt and melt-freeze in the diurnal cycles, and neglect of latent heat of soil freezing and thawing still remain as nagging problems. Several important influences of these assumptions will be discussed with the goal of improving them to better simulate the snowmelt and meltwater hydrology. Nevertheless, the current snow model (Mocko and Sud, 2000, submitted) better simulates cold land processes as compared to the original SSiB. This was confirmed against observations of soil moisture, runoff, and snow cover in global GSWP (Sud and Mocko, 1999) and point-scale Valdai simulations over seasonal snow regions. New results from the current snow model SSiB from the 10-year PILPS 2e intercomparison in northern Scandinavia will be presented.

Multi-Sensor Approach to Mapping Snow Cover Using Data From NASA's EOS Aqua and Terra Spacecraft

NASA Astrophysics Data System (ADS)

Armstrong, R. L.; Brodzik, M. J.

2003-12-01

Snow cover is an important variable for climate and hydrologic models due to its effects on energy and moisture budgets. Over the past several decades both optical and passive microwave satellite data have been utilized for snow mapping at the regional to global scale. For the period 1978 to 2002, we have shown earlier that both passive microwave and visible data sets indicate a similar pattern of inter-annual variability, although the maximum snow extents derived from the microwave data are, depending on season, less than those provided by the visible satellite data and the visible data typically show higher monthly variability. Snow mapping using optical data is based on the magnitude of the surface reflectance while microwave data can be used to identify snow cover because the microwave energy emitted by the underlying soil is scattered by the snow grains resulting in a sharp decrease in brightness temperature and a characteristic negative spectral gradient. Our previous work has defined the respective advantages and disadvantages of these two types of satellite data for snow cover mapping and it is clear that a blended product is optimal. We present a multi-sensor approach to snow mapping based both on historical data as well as data from current NASA EOS sensors. For the period 1978 to 2002 we combine data from the NOAA weekly snow charts with passive microwave data from the SMMR and SSM/I brightness temperature record. For the current and future time period we blend MODIS and AMSR-E data sets. An example of validation at the brightness temperature level is provided through the comparison of AMSR-E with data from the well-calibrated heritage SSM/I sensor over a large homogeneous snow-covered surface (Dome C, Antarctica). Prototype snow cover maps from AMSR-E compare well with maps derived from SSM/I. Our current blended product is being developed in the 25 km EASE-Grid while the MODIS data being used are in the Climate Modelers Grid (CMG) at approximately 5 km (0.05 deg.) allowing the blended product to indicate percent snow cover over the larger grid cell. Relationships between the percent area covered by snow as indicated by the MODIS data and the threshold for the appearance of snow as indicated by the passive microwave data are presented. Both MODIS and AMSR-E data have enhanced spatial resolution compared to the earlier data sources and examples of how this increased spatial resolution results in more accurate snow cover maps are presented. A wide range of validation data sets are being employed in this study including the NASA Cold Lands Processes Field Experiment undertaken in Colorado during 2002 and 2003.

The impact of snow and glaciers on meteorological variables in the Khumbu Valley, Nepalese Himalaya.

NASA Astrophysics Data System (ADS)

Potter, E.; Orr, A.; Willis, I.

2017-12-01

Previous observational studies have suggested that snow and glaciers have a big impact on local meteorological variables in the Himalayas, in particular affecting near surface temperature and the localised wind system. Understanding the impact of changing surface conditions on these systems and is crucial in improving future predictions of glacier melt and precipitation in the Himalayas. However, the mechanisms that control the local meteorology remain poorly understood due to the lack of in-situ data and detailed modelling studies. To investigate these mechanisms, we run the Weather Research and Forecasting (WRF) model at kilometre scale resolution for one month during the monsoon over the Khumbu Valley, Nepalese Himalaya. The model is run with and without snow and glacier coverage at the surface. The impact of adding debris cover into the model is also investigated. In the control run with snow and ice, thermally-driven near-surface winds are found to travel up valley during the day except over the glacier slopes. When the snow and ice is removed from the model, the up valley winds extend over the entire slope. Removal of the snow and ice also results in changes to cloud cover and hydrometeors. A momentum budget approach is used to fully understand the mechanisms that maintain the localised wind system, e.g. to determine the contributions from local forcing or synoptic forcing.

Antarctic surface temperature and sea ice biases in coupled climate models linked with cloud and land surface properties

NASA Astrophysics Data System (ADS)

Skiles, M.; Painter, T. H.; Marks, D. G.; Hedrick, A. R.

2014-12-01

Since 2013 the Airborne Snow Observatory (ASO) has been measuring spatial and temporal distribution of both snow water equivalent and snow albedo, the two most critical properties for understanding snowmelt runoff and timing, across key basins in the Western US. It is generally understood that net solar radiation (as controlled by variations in snow albedo and irradiance) provides the energy available for melt in almost all snow-covered environments. Until now, sparse measurements have restricted the ability to utilize measured net solar radiation in energy balance models, and current process simulations and model prediction of albedo evolution rely on oversimplifications of the processes. Data from ASO offers the unprecedented opportunity to utilize weekly measurements of spatially extensive spectral snow albedo to constrain and update snow albedo in a distributed snowmelt model for the first time. Here, we first investigate the sensitivity of the snow energy balance model SNOBAL to prescribed changes in snow albedo at two instrumented alpine catchments: at the point scale across 10 years at Senator Beck Basin Study Area in the San Juan Mountains, southwestern Colorado, and at the distributed scale across 25 years at Reynolds Creek Experimental Watershed, Idaho. We then compare distributed energy balance and snowmelt results across the ASO measurement record in the Tuolumne Basin in the Sierra Nevada Mountains, California, for model runs with and without integrated snow albedo from ASO.

Time-Lapse Micro-Tomography Measurements and Determination of Effective Transport Properties of Snow Metamorphism Under Advective Conditions

NASA Astrophysics Data System (ADS)

Ebner, P. P.; Grimm, S.; Steen-Larsen, H. C.; Schneebeli, M.; Steinfeld, A.

2014-12-01

The metamorphism of snow under advective air flow, with and without temperature gradient, was never experimentally investigated. We developed a new sample holder where metamorphism under advective conditions can be observed and measured using time-lapse micro-tomography [1]. Long-term experiments were performed and direct pore-level simulation (DPLS) [2,3] was directly applied on the extracted 3D digital geometry of the snow to calculate the effective transport properties by solving the governing fluid flow equations. The results showed no effect of isothermal advection, compared to rates typical for isothermal metamorphism. Appling a temperature gradient, the results showed increased snow metamorphism compared to rates typical for temperature gradient metamorphism. However, for both cases a change in the isotopic composition in the air as well as in the snow sample could be observed. These measurements could be influential to better understand snow-air exchange processes relevant for atmospheric chemistry and isotopic composition. REFERENCES[1] Ebner P. P., Grimm S., Schneebeli M., and Steinfeld A.: An instrumented sample holder for time-lapse micro-tomography measurements of snow under advective airflow. Geoscientific Instrumentation, Methods and Data Systems 4(2014), 353-373. [2] Zermatten E., Haussener S., Schneebeli M., and Steinfeld A.: Tomography-based determination of permeability and Dupuit-Forchheimer coefficient of characteristic snow samples. Journal of Glaciology 57(2011), 811-816. [3] Zermatten E., Schneebeli M., Arakawa H., and Steinfeld A.: Tomography-based determination of porosity, specific area and permeability of snow and comparison with measurements. Cold Regions Science and Technology 97 (2014), 33-40. Fig. 1: 3-D surface rendering of a refrozen wet snow sample with fluid flow streamline.

Assessment of spatial variability of major-ion concentrations and del oxygen-18 values in surface snow, Upper Fremont Glacier, Wyoming, USA

USGS Publications Warehouse

Naftz, D.L.; Schuster, P.F.; Reddy, M.M.

1994-01-01

One hundred samples were collected from the surface of the Upper Fremont Glacier at equally spaced intervals defined by an 8100m2 snow grid to asesss the significance of lateral variability in major-ion concentrations and del oxygen-18 values. Comparison of the observed variability of each chemical constituent to the variability expected by measurement error indicated substantial lateral variability with the surface-snow layer. Results of the nested ANOVA indicate most of the variance for every constituent is in the values grouped at the two smaller geographic scales (between 506m2 and within 506m2 sections). The variance data from the snow grid were used to develop equations to evaluate the significance of both positive and negative concentration/value peaks of nitrate and del oxygen-18 with depth, in a 160m ice core. Values of del oxygen-18 in the section from 110-150m below the surface consistently vary outside the expected limits and possibly represents cooler temperatures during the Little Ice Age from about 1810 to 1725 A.D. -from Authors

A Comparison of the SNICAR Radiative Transfer Model to In Situ Snow Characterization Measurements at Sites in New England, USA

NASA Astrophysics Data System (ADS)

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

2016-12-01

As a highly reflective material, snow serves as an important control on surface energy balance. Given the current changes in climate and the sensitivity of snow cover to rising temperatures, it is critical that we understand the role of snow and its associated feedbacks in the climate system. Much of snow albedo research has focused on polar or high altitude snow packs, but rapid changes are also occurring in temperate regions; in the northeastern United States of America, changing climate has resulted in shallower snow packs and fewer days of snow cover. As these changes occur and we seek to understand the associated implications for snow albedo within climate dynamics, it is imperative that we are able to accurately represent snow in models. The SNow, ICe, and Aerosol Radiation model (SNICAR), developed by Flanner and Zender (2005) and used in the IPCC assessments, provides upward and downward radiative fluxes of one or many snow layers based on the following inputs: snow depth, density, grain size, and impurity content; solar zenith angle; lighting conditions; and albedo of the surface beneath the snowpack. To our knowledge, the SNICAR model has not been validated with data from a mid-latitude temperate region. Through a measurement campaign that occurred from winter 2013-2016, we have collected over 400 independent observations of a suite of snow characterization measurements and spectral snow albedo from three different sites in New Hampshire, USA. Comparison of our spectral albedo measurements to the SNICAR albedo derived from measured snow properties and illumination conditions will allow for validation of the model or recommendations for improvement based on the sensitivities found in the data.

Air-snow interaction of nitrogen species in the polar regions

NASA Astrophysics Data System (ADS)

Cutting Thakur, Roseline; Thamban, Meloth

2017-04-01

The previous studies in the polar regions have frequently compared ion concentration of nitrogen species in snow and aerosol, neglecting to discuss the fact that snow could also scavenge chemical compounds in the gas phase. Further, Peroxyacetyl nitrate (PAN(g)) which is a reactive nitrogen oxide and constitutes ˜90% of the total NOy in the higher altitudes has very scarce measurements in Antarctica and higher altitude areas. The present study reports the interaction of gaseous PAN(g) and HNO3(g)species with NO3- in aerosols and surface snow, in different meteorological conditions at both Antarctic and Arctic regions. Trace gases were sampled through the denuder tubes followed by a Teflon filter to collect the aerosol species and analyzed through the Ion Chromatography technique. Simultaneous snow measurements were also carried out near the air sampling site, close to the Polar Indian research stations. Samples were collected over a period of 15 days in January-February, 2014 in Larsemann Hills, East Antarctica, and 9 days during April, 2012 in Ny- Ålesund, Arctic. Obervations suggest that during high temperature, high radiation and high humidity conditions HNO3(g) concentration decrease with a simultaneous increase in aerosol NO3- [NO3- (A)] in both the regions. It implies that HNO3(g) converts to NO3-(A) probably through the reaction with sea-salt aerosols leading to the formation NO3- in aerosols. Further, the NO3- aerosol-snow interaction is also strong in these conditions. Such associations suggested that, dry deposition of nitrate aerosol could be a source of snow nitrate [NO3- (S)]. Further, a decrease of PAN(g)concentration with a simultaneous increase in NO3-(A) suggested that PAN(g) undergoes photolytic conversion to form NO2(g) and HNO3(g), which may further hydrolyze to form NO3-(A) due to high humidity conditions. However, this mechanism was not dominant during low temperature and low radiation conditions in both the regions, rather a direct gaseous exchange was found to influence the NO3-(S) concentration. Since, HNO3(g) is a highly water soluble and strong acid with a strong affinity to ice, the increasing humidity facilitates the adsorption of HNO3(g)on the snow surface, thereby, increasing the NO3-(S). In such conditions, PAN(g) concentration also decreased with a simultaneous increase in NO3- (S) indicating that direct PAN(g) adsorption on surface snow could be an additional source of NO3-(S). HNO3(g) being a more sticky gas than any other gaseous nitrogen species was scavenged more than PAN(g) on the snow surface. The precipitation events in the Antarctic and Arctic regions increases the concentration of NO3-(S) nearly 2-10 fold, with a simultaneous decrease of NO3-(A) and gaseous HNO3(g) and PAN(g) concentration. This strongly suggests that during precipitation events gaseous as well as particulate scavenging of nitrogen species could be significant. This study suggests that apart from the dry deposition of aerosol species on the snow surface and the outward fluxes of gaseous species from the snow surface, the direct gaseous adsorption of trace gases on the snow surface also needs to be critically evaluated, before computing the nitrogen budget in the polar regions.

Improving simulations of precipitation phase and snowpack at a site subject to cold air intrusions: Snoqualmie Pass, WA

NASA Astrophysics Data System (ADS)

Wayand, Nicholas E.; Stimberis, John; Zagrodnik, Joseph P.; Mass, Clifford F.; Lundquist, Jessica D.

2016-09-01

Low-level cold air from eastern Washington often flows westward through mountain passes in the Washington Cascades, creating localized inversions and locally reducing climatological temperatures. The persistence of this inversion during a frontal passage can result in complex patterns of snow and rain that are difficult to predict. Yet these predictions are critical to support highway avalanche control, ski resort operations, and modeling of headwater snowpack storage. In this study we used observations of precipitation phase from a disdrometer and snow depth sensors across Snoqualmie Pass, WA, to evaluate surface-air-temperature-based and mesoscale-model-based predictions of precipitation phase during the anomalously warm 2014-2015 winter. Correlations of phase between surface-based methods and observations were greatly improved (r2 from 0.45 to 0.66) and frozen precipitation biases reduced (+36% to -6% of accumulated snow water equivalent) by using air temperature from a nearby higher-elevation station, which was less impacted by low-level inversions. Alternatively, we found a hybrid method that combines surface-based predictions with output from the Weather Research and Forecasting mesoscale model to have improved skill (r2 = 0.61) over both parent models (r2 = 0.42 and 0.55). These results suggest that prediction of precipitation phase in mountain passes can be improved by incorporating observations or models from above the surface layer.

Suppression of the water ice and snow albedo feedback on planets orbiting red dwarf stars and the subsequent widening of the habitable zone.

PubMed

Joshi, Manoj M; Haberle, Robert M

2012-01-01

M stars comprise 80% of main sequence stars, so their planetary systems provide the best chance for finding habitable planets, that is, those with surface liquid water. We have modeled the broadband albedo or reflectivity of water ice and snow for simulated planetary surfaces orbiting two observed red dwarf stars (or M stars), using spectrally resolved data of Earth's cryosphere. The gradual reduction of the albedos of snow and ice at wavelengths greater than 1 μm, combined with M stars emitting a significant fraction of their radiation at these same longer wavelengths, means that the albedos of ice and snow on planets orbiting M stars are much lower than their values on Earth. Our results imply that the ice/snow albedo climate feedback is significantly weaker for planets orbiting M stars than for planets orbiting G-type stars such as the Sun. In addition, planets with significant ice and snow cover will have significantly higher surface temperatures for a given stellar flux if the spectral variation of cryospheric albedo is considered, which in turn implies that the outer edge of the habitable zone around M stars may be 10-30% farther away from the parent star than previously thought.

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 temperature. The effects of seasonal snow and climatic controls on spring and autumn phenology are more pronounced at higher than at lower elevations. We suggest that alpine forest ecosystems above 1500 m a.s.l. will therefore be particularly sensitive to future changes of seasonal snow and climate warming scenarios in the Swiss Alps.

Blowing Snow Sublimation and Transport over Antarctica from 11 Years of CALIPSO Observations

NASA Technical Reports Server (NTRS)

Palm, Stephen P.; Kayetha, Vinay; Yang, Yuekui; Pauly, Rebecca

2017-01-01

Blowing snow processes commonly occur over the earth's ice sheets when the 10 mile wind speed exceeds a threshold value. These processes play a key role in the sublimation and redistribution of snow thereby influencing the surface mass balance. Prior field studies and modeling results have shown the importance of blowing snow sublimation and transport on the surface mass budget and hydrological cycle of high-latitude regions. For the first time, we present continent-wide estimates of blowing snow sublimation and transport over Antarctica for the period 2006-2016 based on direct observation of blowing snow events. We use an improved version of the blowing snow detection algorithm developed for previous work that uses atmospheric backscatter measurements obtained from the CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) lidar aboard the CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) satellite. The blowing snow events identified by CALIPSO and meteorological fields from MERRA-2 are used to compute the blowing snow sublimation and transport rates. Our results show that maximum sublimation occurs along and slightly inland of the coastline. This is contrary to the observed maximum blowing snow frequency which occurs over the interior. The associated temperature and moisture reanalysis fields likely contribute to the spatial distribution of the maximum sublimation values. However, the spatial pattern of the sublimation rate over Antarctica is consistent with modeling studies and precipitation estimates. Overall, our results show that the 2006-2016 Antarctica average integrated blowing snow sublimation is about 393 +/- 196 Gt yr(exp -1), which is considerably larger than previous model-derived estimates. We find maximum blowing snow transport amount of 5 Mt km-1 yr(exp -1) over parts of East Antarctica and estimate that the average snow transport from continent to ocean is about 3.7 Gt yr(exp -1). These continent-wide estimates are the first of their kind and can be used to help model and constrain the surface mass budget over Antarctica.

Impact of absorbing aerosol deposition on snow albedo reduction over the southern Tibetan plateau based on satellite observations

NASA Astrophysics Data System (ADS)

Lee, Wei-Liang; Liou, K. N.; He, Cenlin; Liang, Hsin-Chien; Wang, Tai-Chi; Li, Qinbin; Liu, Zhenxin; Yue, Qing

2017-08-01

We investigate the snow albedo variation in spring over the southern Tibetan Plateau induced by the deposition of light-absorbing aerosols using remote sensing data from moderate resolution imaging spectroradiometer (MODIS) aboard Terra satellite during 2001-2012. We have selected pixels with 100 % snow cover for the entire period in March and April to avoid albedo contamination by other types of land surfaces. A model simulation using GEOS-Chem shows that aerosol optical depth (AOD) is a good indicator for black carbon and dust deposition on snow over the southern Tibetan Plateau. The monthly means of satellite-retrieved land surface temperature (LST) and AOD over 100 % snow-covered pixels during the 12 years are used in multiple linear regression analysis to derive the empirical relationship between snow albedo and these variables. Along with the LST effect, AOD is shown to be an important factor contributing to snow albedo reduction. We illustrate through statistical analysis that a 1-K increase in LST and a 0.1 increase in AOD indicate decreases in snow albedo by 0.75 and 2.1 % in the southern Tibetan Plateau, corresponding to local shortwave radiative forcing of 1.5 and 4.2 W m-2, respectively.

LS3MIP (v1.0) Contribution to CMIP6: The Land Surface, Snow and Soil Moisture Model Intercomparison Project Aims, Setup and Expected Outcome.

NASA Technical Reports Server (NTRS)

Van Den Hurk, Bart; Kim, Hyungjun; Krinner, Gerhard; Seneviratne, Sonia I.; Derksen, Chris; Oki, Taikan; Douville, Herve; Colin, Jeanne; Ducharne, Agnes; Cheruy, Frederique;

LS3MIP (v1.0) contribution to CMIP6: the Land Surface, Snow and Soilmoisture Model Intercomparison Project – aims, setup and expected outcome

DOE PAGES

van den Hurk, Bart; Kim, Hyungjun; Krinner, Gerhard; ...

2016-08-24

The Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP) is designed to provide a comprehensive assessment of land surface, snow and soil moisture feedbacks on climate variability and climate change, and to diagnose systematic biases in the land modules of current Earth system models (ESMs). Furthermore, the solid and liquid water stored at the land surface has a large influence on the regional climate, its variability and predictability, including effects on the energy, water and carbon cycles. Notably, snow and soil moisture affect surface radiation and flux partitioning properties, moisture storage and land surface memory. They both stronglymore » affect atmospheric conditions, in particular surface air temperature and precipitation, but also large-scale circulation patterns. But, models show divergent responses and representations of these feedbacks as well as systematic biases in the underlying processes. LS3MIP will provide the means to quantify the associated uncertainties and better constrain climate change projections, which is of particular interest for highly vulnerable regions (densely populated areas, agricultural regions, the Arctic, semi-arid and other sensitive terrestrial ecosystems). The experiments are subdivided in two components, the first addressing systematic land biases in offline mode (“LMIP”, building upon the 3rd phase of Global Soil Wetness Project; GSWP3) and the second addressing land feedbacks attributed to soil moisture and snow in an integrated framework (“LFMIP”, building upon the GLACE-CMIP blueprint).« less

LS3MIP (v1.0) contribution to CMIP6: the Land Surface, Snow and Soilmoisture Model Intercomparison Project – aims, setup and expected outcome

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

van den Hurk, Bart; Kim, Hyungjun; Krinner, Gerhard

The Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP) is designed to provide a comprehensive assessment of land surface, snow and soil moisture feedbacks on climate variability and climate change, and to diagnose systematic biases in the land modules of current Earth system models (ESMs). Furthermore, the solid and liquid water stored at the land surface has a large influence on the regional climate, its variability and predictability, including effects on the energy, water and carbon cycles. Notably, snow and soil moisture affect surface radiation and flux partitioning properties, moisture storage and land surface memory. They both stronglymore » affect atmospheric conditions, in particular surface air temperature and precipitation, but also large-scale circulation patterns. But, models show divergent responses and representations of these feedbacks as well as systematic biases in the underlying processes. LS3MIP will provide the means to quantify the associated uncertainties and better constrain climate change projections, which is of particular interest for highly vulnerable regions (densely populated areas, agricultural regions, the Arctic, semi-arid and other sensitive terrestrial ecosystems). The experiments are subdivided in two components, the first addressing systematic land biases in offline mode (“LMIP”, building upon the 3rd phase of Global Soil Wetness Project; GSWP3) and the second addressing land feedbacks attributed to soil moisture and snow in an integrated framework (“LFMIP”, building upon the GLACE-CMIP blueprint).« less

Improved Passive Microwave Algorithms for North America and Eurasia

NASA Technical Reports Server (NTRS)

Foster, James; Chang, Alfred; Hall, Dorothy

1997-01-01

Microwave algorithms simplify complex physical processes in order to estimate geophysical parameters such as snow cover and snow depth. The microwave radiances received at the satellite sensor and expressed as brightness temperatures are a composite of contributions from the Earth's surface, the Earth's atmosphere and from space. Owing to the coarse resolution inherent to passive microwave sensors, each pixel value represents a mixture of contributions from different surface types including deep snow, shallow snow, forests and open areas. Algorithms are generated in order to resolve these mixtures. The accuracy of the retrieved information is affected by uncertainties in the assumptions used in the radiative transfer equation (Steffen et al., 1992). One such uncertainty in the Chang et al., (1987) snow algorithm is that the snow grain radius is 0.3 mm for all layers of the snowpack and for all physiographic regions. However, this is not usually the case. The influence of larger grain sizes appears to be of more importance for deeper snowpacks in the interior of Eurasia. Based on this consideration and the effects of forests, a revised SMMR snow algorithm produces more realistic snow mass values. The purpose of this study is to present results of the revised algorithm (referred to for the remainder of this paper as the GSFC 94 snow algorithm) which incorporates differences in both fractional forest cover and snow grain size. Results from the GSFC 94 algorithm will be compared to the original Chang et al. (1987) algorithm and to climatological snow depth data as well.

Australian snowpack in the NARCliM ensemble: evaluation, bias correction and future projections

NASA Astrophysics Data System (ADS)

Luca, Alejandro Di; Evans, Jason P.; Ji, Fei

2017-10-01

In this study we evaluate the ability of an ensemble of high-resolution Regional Climate Model simulations to represent snow cover characteristics over the Australian Alps and go on to asses future projections of snowpack characteristics. Our results show that the ensemble presents a cold temperature bias and overestimates total precipitation leading to a general overestimation of the snow cover as compared with MODIS satellite data. We then produce a new set of snowpack characteristics by running a temperature based snow melt/accumulation model forced by bias corrected temperature and precipitation fields. While some positive snow cover biases remain, the bias corrected (BC) dataset show large improvements regarding the simulation of total amounts, seasonality and spatial distribution of the snow cover compared with MODIS products. Both the raw and BC datasets are then used to assess future changes in the snowpack characteristics. Both datasets show robust increases in near-surface temperatures and decreases in snowfall that lead to a substantial reduction of the snowpack over the Australian Alps. The snowpack decreases by about 15 and 60% by 2030 and 2070 respectively. While the BC data introduce large differences in the simulation of the present climate snowpack, in relative terms future changes appear to be similar to those obtained using the raw data. Future temperature projections show a clear dependence with elevation through the snow-albedo feedback effect that affects snowpack projections. Uncertainties in future projections of the snowpack are large in both datasets and are mainly dominated by the choice of the lateral boundary conditions.

Long-term record of atmospheric and snow surface nitrate from Dome C (Central Antarctica)

NASA Astrophysics Data System (ADS)

Traversi, Rita; Becagli, Silvia; Brogioni, Marco; Caiazzo, Laura; Ciardini, Virginia; Giardi, Fabio; Legrand, Michel; Macelloni, Giovanni; Petkov, Boyan; Preunkert, Suzanne; Scarchilli, Claudio; Severi, Mirko; Vitale, Vito; Udisti, Roberto

2017-04-01

Nitrate is the end product of the oxidation of atmospheric nitrogen oxides and one of the most abundant ions present in polar ice and snow, mainly as nitric acid in present-climate conditions. Nitrate stratigraphies from snow and ice layers have the potential to provide records of past changes in atmospheric composition, including atmospheric NOx cycling and oxidative capacity, as well as past solar activity or major variations in Earth's magnetic field. Nevertheless, in order to exploit such a potential, chemical concentrations in the air, snow, firn and ice core need to be correlated. Hence, the knowledge of the link between atmosphere and snow composition at the time of deposition is basic to reconstruct past climate and past atmospheric chemical composition. The extent of such knowledge depends on whether the species of interest are gaseous or in the condensed phase, and if they are reversible and/or irreversibly deposited to snow. In order to provide a contribution to their air-to-snow exchange in the Antarctic plateau, as well as to the understanding of dominant sources and sinks of nitrate, we present here nitrate records in atmospheric aerosol and surface snow sampled at high resolution, all year-round, at Dome C along 9 years (November 2004 - November 2013). This represents the longest and most highly resolved record from continental Antarctica, where continuous and long-term atmosphere and snow samplings are particularly difficult due to the extreme meteorological conditions and, at the same time, need of extra-care in avoiding contamination due to the low level of ion concentrations. Results confirm, on a larger statistical data set with respect to previous observations, nitrate seasonal pattern with summer maxima both for aerosol and surface snow, in-phase with UV solar irradiance. Such a temporal pattern is likely a combination of nitrate sources and post-depositional processes that enhance during summer. Moreover, a case study of synoptic analysis for a major nitrate event showed the occurrence of a stratosphere-troposphere exchange in the sampled days. The sampling of both matrices carried out at high resolution at the same time allowed detecting a recurring lag, about one-month long, of summer maxima in snow with respect to aerosol. Such a temporal shift can be explained only by taking into account deposition and post-deposition processes taking place at the atmosphere-snow interface, including likely both a net uptake of gaseous nitric acid and a replenishment of the uppermost surface layers driven by a larger temperature gradient in summer. Such a possibility was tested in a preliminary way by a comparison with measurements of surface layers temperature carried out in 2012-13 time period. A comparison with nitrate concentration in the gas phase and total nitrate obtained from Dome C (2012-13) showed the major role of gaseous HNO3 to total nitrate budget hinting to the need of further investigation of the gas-to-particle conversion processes.

Nitrogen and carbon soil dynamics in response to climate change in a high-elevation ecosystem in the Rocky Mountains, U.S.A.

USGS Publications Warehouse

Williams, M.W.; Brooks, P.D.; Seastedt, T.

1998-01-01

We have implemented a long-term snow-fence experiment at the Niwot Ridge Long-Term Ecological Research (NWT) site in the Colorado Front Range of the Rocky Mountains, U.S.A., to assess the effects of climate change on alpine ecology and biogeochemical cycles. The responses of carbon (C) and nitrogen (N) dynamics in high-elevation mountains to changes in climate are investigated by manipulating the length and duration of snow cover with the 2.6 x 60 m snow fence, providing a proxy for climate change. Results from the first year of operation in 1994 showed that the period of continuous snow cover was increased by 90 d. The deeper and earlier snowpack behind the fence insulated soils from winter air temperatures, resulting in a 9??C increase in annual minimum temperature at the soil surface. The extended period of snow cover resulted in subnivial microbial activity playing a major role in annual C and N cycling. The amount of C mineralized under the snow as measured by CO2 production was 22 g m-2 in 1993 and 35 g m-2 in 1994, accounting for 20% of annual net primary aboveground production before construction of the snow fence in 1993 and 31% after the snow fence was constructed in 1994. In a similar fashion, maximum subnivial N2O flux increased 3-fold behind the snow fence, from 75 ??g N m-2 d-1 in 1993 to 250 ??g N m-2 d-1 in 1994. The amount of N lost from denitrification was greater than the annual atmospheric input of N in snowfall. Surface litter decomposition studies show that there was a significant increase in the litter mass loss under deep and early snow, with no significant change under medium and little snow conditions. Changes in climate that result in differences in snow duration, depth, and extent may therefore produce large changes in the C and N soil dynamics of alpine ecosystems.

Impact of new land boundary conditions from Moderate Resolution Imaging Spectroradiometer (MODIS) data on the climatology of land surface variables

NASA Astrophysics Data System (ADS)

Tian, Y.; Dickinson, R. E.; Zhou, L.; Shaikh, M.

2004-10-01

This paper uses the Community Land Model (CLM2) to investigate the improvements of a new land surface data set, created from multiple high-quality collection 4 Moderate Resolution Imaging Spectroradiometer data of leaf area index (LAI), plant functional type, and vegetation continuous fields, for modeled land surface variables. The previous land surface data in CLM2 underestimate LAI and overestimate the percent cover of grass/crop over most of the global area. For snow-covered regions with abundant solar energy the increased LAI and percent cover of tree/shrub in the new data set decreases the percent cover of surface snow and increases net radiation and thus increases ground and surface (2-m) air temperature, which reduces most of the model cold bias. For snow-free regions the increased LAI and changes in the percent cover from grass/crop to tree or shrub decrease ground and surface air temperature by converting most of the increased net radiation to latent heat flux, which decreases the model warm bias. Furthermore, the new data set greatly decreases ground evaporation and increases canopy evapotranspiration over tropical forests, especially during the wet season, owing to the higher LAI and more trees in the new data set. It makes the simulated ground evaporation and canopy evapotranspiration closer to reality and also reduces the warm biases over tropical regions.

Improvement of Mars surface snow albedo modeling in LMD Mars GCM with SNICAR

NASA Astrophysics Data System (ADS)

Singh, D.; Flanner, M.; Millour, E.

2017-12-01

The current version of Laboratoire de Météorologie Dynamique (LMD) Mars GCM (original-MGCM) uses annually repeating (prescribed) albedo values from the Thermal Emission Spectrometer observations. We integrate the Snow, Ice, and Aerosol Radiation (SNICAR) model with MGCM (SNICAR-MGCM) to prognostically determine H2O and CO2 ice cap albedos interactively in the model. Over snow-covered regions mean SNICAR-MGCM albedo is higher by about 0.034 than original-MGCM. Changes in albedo and surface dust content also impact the shortwave energy flux at the surface. SNICAR-MGCM model simulates a change of -1.26 W/m2 shortwave flux on a global scale. Globally, net CO2 ice deposition increases by about 4% over one Martian annual cycle as compared to original-MGCM simulations. SNICAR integration reduces the net mean global surface temperature, and the global surface pressure of Mars by about 0.87% and 2.5% respectively. Changes in albedo also show a similar distribution as dust deposition over the globe. The SNICAR-MGCM model generates albedos with higher sensitivity to surface dust content as compared to original-MGCM. For snow-covered regions, we improve the correlation between albedo and optical depth of dust from -0.91 to -0.97 with SNICAR-MGCM as compared to original-MGCM. Using new diagnostic capabilities with this model, we find that cryospheric surfaces (with dust) increase the global surface albedo of Mars by 0.022. The cryospheric effect is severely muted by dust in snow, however, which acts to decrease the planet-mean surface albedo by 0.06.

Fluctuating snow line altitudes in the Hunza basin (Karakoram) using Landsat OLI imagery

NASA Astrophysics Data System (ADS)

Racoviteanu, Adina; Rittger, Karl; Brodzik, Mary J.; Painter, Thomas H.; Armstrong, Richard

2016-04-01

Snowline altitudes (SLAs) on glacier surfaces are needed for separating snow and ice as input for melt models. When measured at the end of the ablation season, SLAs are used for inferring stable-state glacier equilibrium line altitudes (ELAs). Direct measurements of snowlines are rarely possible particularly in remote, high altitude glacierized terrain, but remote sensing data can be used to separate these snow and ice surfaces. Snow lines are commonly visible on optical satellite images acquired at the end of the ablation season if the images are contrasted enough, and are manually digitized on screen using various satellite band combinations for visual interpretation, which is a time-consuming, subjective process. Here we use Landsat OLI imagery at 30 m resolution to estimate glacier SLAs for a subset of the Hunza basin in the Upper Indus in the Karakoram. Clean glacier ice surfaces are delineated using a standardized semi-automated band ratio algorithm with image segmentation. Within the glacier surface, snow and ice are separated using supervised classification schemes based on regions of interest, and glacier SLAs are extracted on the basis of these areas. SLAs are compared with estimates from a new automated method that relies on fractional snow covered area rather than on band ratio algorithms for delineating clean glacier ice surfaces, and on grain size (instead of supervised classification) for separating snow from glacier ice on the glacier surface. The two methods produce comparable snow/ice outputs. The fSCA-derived glacierized areas are slightly larger than the band ratio estimates. Some of the additional area is the result of better detection in shadows from spectral mixture analysis (true positive) while the rest is shallow water, which is spectrally similar to snow/ice (false positive). On the glacier surface, a thresholding the snow grain size image (grain size > 500μm) results in similar glacier ice areas derived from the supervised classification, but there is noise (snow) on edges of dirty ice/ moraines at the glacier termini and around rock outcrops on the glacier surface. Neither of the two methods distinguishes the debris-covered ice, so these were mapped separately using a combination of topographic indices (slope, terrain curvature), along with remote sensing surface temperature and texture data. Using average elevation of snow and ice areas, we calculate an ELA of 5260 m for 2013. We construct yearly time series of the ELAs around the centerlines of selected glaciers in the Hunza for the period 2000 - 2014 using Landsat imagery. We explore spatial trends in glacier ELAs within the region, as well as relationships between ELA and topographic characteristics extracted on a glacier-by-glacier basis from a digital elevation model.

Short-Term Retrospective Land Data Assimilation Schemes

NASA Technical Reports Server (NTRS)

Houser, P. R.; Cosgrove, B. A.; Entin, J. K.; Lettenmaier, D.; ODonnell, G.; Mitchell, K.; Marshall, C.; Lohmann, D.; Schaake, J. C.; Duan, Q.;

Towards Understanding the Timing and Frequency of Rain-on-Snow (ROS) Events in Alaska

NASA Astrophysics Data System (ADS)

Pan, C.; Kirchner, P. B.; Kimball, J. S.; Kim, Y.; Kamp, U.

2017-12-01

Rain-on-snow (ROS) events affect ecosystem processes at multiple spatial and temporal scales including hydrology, carbon cycling, wildlife movement and human transportation and result in marked changes to snowpack processes including enhanced snow melt, surface albedo and energy balance. Changes in the surface structure of the snowpack are visible through optical remote sensing and changes in the relative content and distribution of water, air and ice in the snowpack are detectable using passive microwave remote sensing. This project aims to develop ROS products to elucidate changes in frequency and distribution in ROS events using satellite data products derived from both optical and passive microwave satellite records. To detect ROS events, we use downscaled brightness temperature measurements derived from vertical and horizontal polarizations at 19 and 37 GHz from the Advanced Microwave Scanning Radiometer (AMSR-E/2) passive microwave satellites. Preliminary results indicate an overall classification accuracy of 77.6% relative to in situ weather observations including surface air temperature, precipitation, and snow depth. ROS events are spatially distributed largely to elevations below 500 m and occur most frequently on northern to western aspects in addition to southeastern. Regional ROS hot spots occur in southwest Alaska characterized by warmer climates and transient snowcover. The seasonal timing of ROS events indicates increasing frequency during the fall and spring months.

Virtual Sensors: Using Data Mining to Efficiently Estimate Spectra

NASA Technical Reports Server (NTRS)

Srivastava, Ashok; Oza, Nikunj; Stroeve, Julienne

2004-01-01

Detecting clouds within a satellite image is essential for retrieving surface geophysical parameters, such as albedo and temperature, from optical and thermal imagery because the retrieval methods tend to be valid for clear skies only. Thus, routine satellite data processing requires reliable automated cloud detection algorithms that are applicable to many surface types. Unfortunately, cloud detection over snow and ice is difficult due to the lack of spectral contrast between clouds and snow. Snow and clouds are both highly reflective in the visible wavelen,ats and often show little contrast in the thermal Infrared. However, at 1.6 microns, the spectral signatures of snow and clouds differ enough to allow improved snow/ice/cloud discrimination. The recent Terra and Aqua Moderate Resolution Imaging Spectro-Radiometer (MODIS) sensors have a channel (channel 6) at 1.6 microns. Presently the most comprehensive, long-term information on surface albedo and temperature over snow- and ice-covered surfaces comes from the Advanced Very High Resolution Radiometer ( AVHRR) sensor that has been providing imagery since July 1981. The earlier AVHRR sensors (e.g. AVHRR/2) did not however have a channel designed for discriminating clouds from snow, such as the 1.6 micron channel available on the more recent AVHRR/3 or the MODIS sensors. In the absence of the 1.6 micron channel, the AVHRR Polar Pathfinder (APP) product performs cloud detection using a combination of time-series analysis and multispectral threshold tests based on the satellite's measuring channels to produce a cloud mask. The method has been found to work reasonably well over sea ice, but not so well over the ice sheets. Thus, improving the cloud mask in the APP dataset would be extremely helpful toward increasing the accuracy of the albedo and temperature retrievals, as well as extending the time-series of albedo and temperature retrievals from the more recent sensors to the historical ones. In this work, we use data mining methods to construct a model of MODIS channel 6 as a function of other channels that are common to both MODIS and AVHRR. The idea is to use the model to generate the equivalent of MODIS channel 6 for AVHRR as a function of the AVHRR equivalents to MODIS channels. We call this a Virtual Sensor because it predicts unmeasured spectra. The goal is to use this virtual channel 6. to yield a cloud mask superior to what is currently used in APP . Our results show that several data mining methods such as multilayer perceptrons (MLPs), ensemble methods (e.g., bagging), and kernel methods (e.g., support vector machines) generate channel 6 for unseen MODIS images with high accuracy. Because the true channel 6 is not available for AVHRR images, we qualitatively assess the virtual channel 6 for several AVHRR images.

Reproduction of influence of autumn snow cover anomalies on the following winter atmospheric dynamics in INMCM4.0 and INMCM5.0 data

NASA Astrophysics Data System (ADS)

Martynova, Yuliya

2015-04-01

There are different studies of the influence of autumn snow cover anomalies on atmospheric dynamics in the following winter (e.g. Allen R.J. and Zender C.S., 2011; Martynova Yu.V. and Krupchatnikov V.N., 2010). The mechanism of this effect is complex and largely affects stratospheric processes (Cohen J. et al., 2007). The snow cover rapidly increases exceeding normal values. Emerged diabatic cooling results in pressure increase over and temperature decrease under the normal value. Thus, in troposphere upward energy flux increases, and then it is absorbed in stratosphere. Strong convergence of wave activity flux causes geopotential heights increase, polar vortex slowdown and stratospheric temperature increase. Emerged geopotential and wind anomalies extend from stratosphere to troposphere up to surface. As a result, strong negative AO mode appears near the surface as surface air temperature increase. Siberia plays important role in this mechanism. Firstly, the most extensive snow cover is formed there. Secondly, according to NOAA satellite observations this cover is generally formed in October (Gong G. Et al., 2003). As a result, Siberia is very interesting for investigations of the autumn snow cover anomalies influence on the atmospheric dynamics in the following winter. This study is devoted to detection and estimation of described mechanism in INMCM4.0 and INMCM5.0 data. INMCM5.0 model represents further development of INMCM4.0 model (Volodin E.M. et al., 2010; Volodin E.M., 2014). They are different both from physical (various physical processes) and numerical (spatial resolution) points of view, thus giving different results representing various physical processes. An analysis of some parameters of atmospheric dynamics shows that top of atmosphere and vertical resolution set in INMCM models play important role in reproduction of influence of the Siberian autumn snow cover anomalies on the Northern Hemisphere atmospheric dynamics in the following winter. Acknowledgements Author acknowledges Dr. Volodin E.M. for providing INMCM data and valued advices. This work is partially supported by SB RAS project VIII.80.2.1, RFBR grant 13-05-12034, 13-05-00480, 14-05-00502 and grant of the President of the Russian Federation. References Allen R.J. and Zender C.S. Forcing of the Arctic Oscillation by Eurasian snow cover. // J. Climate. 2011. Volume 24. P. 6528-6539. Cohen J., Barlow M., Kushner P.J., Saito K. Stratosphere-troposphere coupling and links with Eurasian land-surface variability. // J. Climate. 2007. Volume 20. P. 5335-5343. Gong G., Entekhabi D., Cohen J. Modeled Northern Hemisphere winter climate response to realistic Siberian snow anomalies. // J. Climate, 2003. -- V. 16. -- P. 3917-3931. Martynova Yu.V. and Krupchatnikov V.N. A study of the sensitivity of the surface temperature in Eurasia in winter to snow-cover anomalies: The role of the stratosphere // Izvestiya, Atmospheric and Oceanic Physics. 2010. V 46, Issue 6, pp 757-769. Volodin E.M., Dianskii N.A., Gusev A.V. Simulating Present-Day Climate with the INMCM4.0 Coupled Model of the Atmospheric and Oceanic General Circulations // Izvestiya, Atmospheric and Oceanic Physics. 2010. V 46, No. 4, pp 414-431. Volodin E.M. Possible reasons for low climate-model sensitivity to increased carbon dioxide concentrations // Izvestiya, Atmospheric and Oceanic Physics. 2014. V 50, Issue 4 , pp 350-355.

Modeling the Physical Multi-Phase Interactions of HNO3 Between Snow and Air on the Antarctic Plateau (Dome C) and coast (Halley)

NASA Astrophysics Data System (ADS)

Chan, Hoi Ga; Frey, Markus M.; King, Martin D.

2017-04-01

Nitrogen oxides (NOx = NO + NO2) emissions from nitrate (NO3-) photolysis in snow affect the oxidising capacity of the lower troposphere especially in remote regions of the high latitudes with low pollution levels. The porous structure of snowpack allows the exchange of gases with the atmosphere driven by physicochemical processes, and hence, snow can act as both source and sink of atmospheric chemical trace gases. Current models are limited by poor process understanding and often require tuning parameters. Here, two multi-phase physical models were developed from first principles constrained by observed atmospheric nitrate, HNO3, to describe the air-snow interaction of nitrate. Similar to most of the previous approaches, the first model assumes that below a threshold temperature, To, the air-snow grain interface is pure ice and above To, a disordered interface (DI) emerges assumed to be covering the entire grain surface. The second model assumes that Air-Ice interactions dominate over the entire temperature range below melting and that only above the eutectic temperature, liquid is present in the form of micropockets in grooves. The models are validated with available year-round observations of nitrate in snow and air at a cold site on the Antarctica Plateau (Dome C, 75°06'S, 123°33'E, 3233 m a.s.l.) and at a relatively warm site on the Antarctica coast (Halley, 75°35'S, 26°39'E, 35 m a.s.l). The first model agrees reasonably well with observations at Dome C (Cv(RMSE) = 1.34), but performs poorly at Halley (Cv(RMSE) = 89.28) while the second model reproduces with good agreement observations at both sites without any tuning (Cv(RMSE) = 0.84 at both sites). It is therefore suggested that air-snow interactions of nitrate in the winter are determined by non-equilibrium surface adsorption and co-condensation on ice coupled with solid-state diffusion inside the grain. In summer, however, the air-snow exchange of nitrate is mainly driven by solvation into liquid micropockets following Henry's law with contributions to total NO3- concentrations of 75% and 80% at Dome C and Halley respectively. It is also found that liquid volume of the snow grain and air-micropocket partitioning of HNO3 are sensitive to total solute concentration and pH. In conclusion, the second model can be used to predict nitrate concentration in surface snow over the entire range of environ- mental conditions typical for Antarctica and forms a basis for parameterisations in regional or global atmospheric chemistry models.

Characterization of Air and Ground Temperature Relationships within the CMIP5 Historical and Future Climate Simulations

NASA Astrophysics Data System (ADS)

García-García, A.; Cuesta-Valero, F. J.; Beltrami, H.; Smerdon, J. E.

2017-12-01

The relationships between air and ground surface temperatures across North America are examined in the historical and future projection simulations from 32 General Circulation Models (GCMs) included in the fifth phase of the Coupled Model Intercomparison Project (CMIP5). The covariability between surface air (2 m) and ground surface temperatures (10 cm) is affected by simulated snow cover, vegetation cover and precipitation through changes in soil moisture at the surface. At high latitudes, the differences between air and ground surface temperatures, for all CMIP5 simulations, are related to the insulating effect of snow cover and soil freezing phenomena. At low latitudes, the differences between the two temperatures, for the majority of simulations, are inversely proportional to leaf area index and precipitation, likely due to induced-changes in latent and sensible heat fluxes at the ground surface. Our results show that the transport of energy across the air-ground interface differs from observations and among GCM simulations, by amounts that depend on the components of the land-surface models that they include. The large variability among GCMs and the marked dependency of the results on the choice of the land-surface model, illustrate the need for improving the representation of processes controlling the coupling of the lower atmosphere and the land surface in GCMs as a means of reducing the variability in their representation of weather and climate phenomena, with potentially important implications for positive climate feedbacks such as permafrost and soil carbon stability.

Impacts of Aerosols on Seasonal Precipitation and Snowpack in California Based on Convection-Permitting WRF-Chem Simulations

NASA Astrophysics Data System (ADS)

Gu, Y.; Wu, L.; Jiang, J. H.; Su, H.; Yu, N.; Zhao, C.; Qian, Y.; Zhao, B.; Liou, K. N.; Choi, Y. S.

2017-12-01

A version of the WRF-Chem model with fully coupled aerosol-meteorology-snowpack is employed to investigate the impacts of various aerosol sources on precipitation and snowpack in California. In particular, the impacts of locally emitted anthropogenic and dust aerosols, and aerosols transported from outside of California are studied. We differentiate three pathways of aerosol effects including aerosol-radiation interaction (ARI), aerosol-snow interaction (ASI), and aerosol-cloud interaction (ACI). The convection-permitting model simulations show that precipitation, snow water equivalent (SWE), and surface air temperature averaged over the whole domain (34-42°N, 117-124°W, not including ocean points) are reduced when aerosols are included, therefore reducing the high model biases of these variables when aerosol effects are not considered. Aerosols affect California water resources through the warming of mountain tops and anomalously low precipitation, however, different aerosol sources play different roles in changing surface temperature, precipitation and snowpack in California by means of various weights of the three pathways. ARI by all aerosols mainly cools the surface, leading to slightly increased SWE over the mountains. Locally emitted dust aerosols warm the surface of mountain tops through ASI, in which the reduced snow albedo associated with dirty snow leads to more surface absorption of solar radiation and reduced SWE. Transported and local anthropogenic aerosols play a dominant role in increasing cloud water amount but reducing precipitation through ACI, leading to reduced SWE and runoff over the Sierra Nevada, as well as the warming of mountain tops associated with decreased SWE and hence lower surface albedo. The average changes in surface temperature from October to June are about -0.19 K and 0.22 K for the whole domain and over mountain tops, respectively. Overall, the averaged reduction during October to June is about 7% for precipitation, 3% for SWE, and 7% for surface runoff for the whole domain, while the corresponding numbers are 12%, 10%, and 10% for mountain tops. The reduction in SWE is more significant in a dry year, with 9% for the whole domain and 16% for mountain tops.

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

Dong, B.; Valdes, P.J.

The U.K. University Global Atmospheric Modeling Programme GCM is used to investigate whether the growth of Northern Hemisphere ice sheets could have been initiated by changes of orbital parameters and sea surface temperatures. Two different orbital configurations, corresponding to the present day and 115 kyr BP are used. The reduced summer solar insolation in the Northern Hemisphere results in a decrease of the surface temperature by 4{degrees} to 10{degrees}C in the northern continents and to perennial snow in some high-latitude regions. Therefore, the model results support the hypothesis that a deficit of summer insolation can create conditions favorable for initiationmore » of ice sheet growth in the Northern Hemisphere. A decreased sea surface temperature northward of 65{degrees}N during the Northern Hemisphere summer may contribute to the maintenance of ice sheets. A simple mixed-layer ocean model coupled to the GCM indicates that the changes of sea surface temperature and extension of sea ice due to insolation changes play an important role in inception of the Fennoscandian, Laurentide, and Cordilleran ice sheets. The model results suggest that the regions of greatest sensitivity for ice initiation are the Canadian Archipelago, Baffin Island, Tibetan Plateau, Scandinavia, Siberia, Alaska, and Keewatin, where changing orbital parameters to 115 kyr BP results in the snow cover remaining throughout the warmer summer, leading to long-term snow accumulation. The model results are in general agreement with geological evidence and are the first time that a GCM coupled with a mixed layer ocean has reproduced the inception of the Northern Hemisphere ice sheets. 69 refs., 21 figs., 3 tabs.« less

A comparison between modeled and measured permafrost temperatures at Ritigraben borehole, Switzerland

NASA Astrophysics Data System (ADS)

Mitterer-Hoinkes, Susanna; Lehning, Michael; Phillips, Marcia; Sailer, Rudolf

2013-04-01

The area-wide distribution of permafrost is sparsely known in mountainous terrain (e.g. Alps). Permafrost monitoring can only be based on point or small scale measurements such as boreholes, active rock glaciers, BTS measurements or geophysical measurements. To get a better understanding of permafrost distribution, it is necessary to focus on modeling permafrost temperatures and permafrost distribution patterns. A lot of effort on these topics has been already expended using different kinds of models. In this study, the evolution of subsurface temperatures over successive years has been modeled at the location Ritigraben borehole (Mattertal, Switzerland) by using the one-dimensional snow cover model SNOWPACK. The model needs meteorological input and in our case information on subsurface properties. We used meteorological input variables of the automatic weather station Ritigraben (2630 m) in combination with the automatic weather station Saas Seetal (2480 m). Meteorological data between 2006 and 2011 on an hourly basis were used to drive the model. As former studies showed, the snow amount and the snow cover duration have a great influence on the thermal regime. Low snow heights allow for deeper penetration of low winter temperatures into the ground, strong winters with a high amount of snow attenuate this effect. In addition, variations in subsurface conditions highly influence the temperature regime. Therefore, we conducted sensitivity runs by defining a series of different subsurface properties. The modeled subsurface temperature profiles of Ritigraben were then compared to the measured temperatures in the Ritigraben borehole. This allows a validation of the influence of subsurface properties on the temperature regime. As expected, the influence of the snow cover is stronger than the influence of sub-surface material properties, which are significant, however. The validation presented here serves to prepare a larger spatial simulation with the complex hydro-meteorological 3-dimensional model Alpine 3D, which is based on a distributed application of SNOWPACK.

Spring snow albedo feedback in daily data over Russia: Comparing in-situ measurements with reanalysis products.

NASA Astrophysics Data System (ADS)

Wegmann, M.; Zolina, O.; Jacobi, H. W.

2016-12-01

Global warming is enhanced at high northern latitudes where the Arctic surface air temperature has risen at twice the rate of the global average in recent decades - a feature called Arctic amplification. This recent Arctic warming signal likely results from several factors such as the albedo feedback due to a diminishing cryosphere, enhanced poleward atmospheric and oceanic heat transport, and changes in humidity. Surface albedo feedback is stating that the additional amount of shortwave radiation at the top of the atmosphere decreases with decreasing surface albedo whereas surface air temperature increases with decreasing surface albedo. It is considered a positive feedback in that an initial warming perturbation than kicks off a strengthening warming. Looking at the Northern Hemisphere with its large landmasses, snow albedo feedback is especially strong since most of these landmasses experience snow cover during boreal wintertime. Unfortunately, so far there remains a lack of reliable observational data over large parts of the cryosphere. Satellite products cover large parts of the NH, however lack high temporal resolution and have problems with large solar zenith angles as well as over complex terrain (eg. Wang et al. 2014). Our analysis focuses at the Russian territory where we utilize in-situ radiation and snow depth measurements. We found 50 stations which measure both variables on a daily basis for the period 2000-2013. Since Hall (2004) found that 50% of the notal NH snow albedo feedback caused by global warming occurs during NH spring, we focus on the transition period of March to June (MAMJ). Thackeray & Fletcher 2006 compared albedo feedback processes CMIP3 and CMIP5 model families and found while the models represent the feedback process accurately, there are still inherent biases and outdated parameterizations. Therefore we use the daily observations and state of the art reanalysis products to 1) evaluate reanalysis and model products in respect to radiation properties, 2) investigate snow albedo feedbacks on a daily scale during spring and 3) to suggest climate change signals over Russia in albedo feedback between 2000 - 2013 based on in-situ measurements.

The Impact Of Snow Melt On Surface Runoff Of Sava River In Slovenia

NASA Astrophysics Data System (ADS)

Horvat, A.; Brilly, M.; Vidmar, A.; Kobold, M.

2009-04-01

Snow is a type of precipitation in the form of crystalline water ice, consisting of a multitude of snowflakes that fall from clouds. Snow remains on the ground until it melts or sublimates. Spring snow melt is a major source of water supply to areas in temperate zones near mountains that catch and hold winter snow, especially those with a prolonged dry summer. In such places, water equivalent is of great interest to water managers wishing to predict spring runoff and the water supply of cities downstream. In temperate zone like in Slovenia the snow melts in the spring and contributes certain amount of water to surface flow. This amount of water can be great and can cause serious floods in case of fast snow melt. For this reason we tried to determine the influence of snow melt on the largest river basin in Slovenia - Sava River basin, on surface runoff. We would like to find out if snow melt in Slovenian Alps can cause spring floods and how serious it can be. First of all we studied the caracteristics of Sava River basin - geology, hydrology, clima, relief and snow conditions in details for each subbasin. Furtermore we focused on snow and described the snow phenomenom in Slovenia, detailed on Sava River basin. We collected all available data on snow - snow water equivalent and snow depth. Snow water equivalent is a much more useful measurement to hydrologists than snow depth, as the density of cool freshly fallen snow widely varies. New snow commonly has a density of between 5% and 15% of water. But unfortunately there is not a lot of available data of SWE available for Slovenia. Later on we compared the data of snow depth and river runoff for some of the 40 winter seasons. Finally we analyzed the use of satellite images for Slovenia to determine the snow cover for hydrology reason. We concluded that snow melt in Slovenia does not have a greater influence on Sava River flow. The snow cover in Alps can melt fast due to higher temperatures but the water distributes and runs off slowly and does not cause floods. About use of satellite images we concluded that first of all, weather is unfavorable - lots of cloudiness in winter, and furthermore a grater part of land is covered by forest which prevents to see the snow cover on image clearly.

Towards better understanding of high-mountain cryosphere changes using GPM data: A Joint Snowfall and Snow-cover Passive Microwave Retrieval Algorithm

NASA Astrophysics Data System (ADS)

Ebtehaj, A.; Foufoula-Georgiou, E.

2016-12-01

Scientific evidence suggests that the duration and frequency of snowfall and the extent of snow cover are rapidly declining under global warming. Both precipitation and snow cover scatter the upwelling surface microwave emission and decrease the observed high-frequency brightness temperatures. The mixture of these two scattering signals is amongst the largest sources of ambiguities and errors in passive microwave retrievals of both precipitation and snow-cover. The dual frequency radar and the high-frequency radiometer on board the GPM satellite provide a unique opportunity to improve passive retrievals of precipitation and snow-cover physical properties and fill the gaps in our understating of their variability in view of climate change. Recently, a new Bayesian rainfall retrieval algorithm (called ShARP) was developed using modern approximation methods and shown to yield improvements against other algorithms in retrieval of rainfall over radiometrically complex land surfaces. However, ShARP uses a large database of input rainfall and output brightness temperatures, which might be undersampled. Furthermore, it is not capable to discriminate between solid and liquid phase of precipitation and specifically discriminate the background snow-cover emission and its contamination effects on the retrievals. We address these problems by extending it to a new Bayesian land-atmosphere retrieval framework (ShARP-L) that allows joint retrievals of atmospheric constituents and land surface physical properties. Using modern sparse approximation techniques, the database is reduced to atomic microwave signatures in a family of compact class consistent dictionaries. These dictionaries can efficiently represent the entire database and allow us to discriminate between different land-atmosphere states. First the algorithm makes use of the dictionaries to detect the phase of the precipitation and type of the land-cover and then it estimates the physical properties of precipitation and snow cover using an extended version of the Dantzig Selector, which is robust to non-Gaussian and correlated geophysical noise. Promising results are presented in retrievals of snowfall and snow-cover over coastal orographic features of North America's Coast Range and South America's Andes.

Biggs AAF, El Paso, Texas. Revised Uniform Summary of Surface Weather Observations (RUSSWO). Parts A-F

DTIC Science & Technology

1981-01-14

wet-bulb temperature depression versus dry -bulb temperature, means and standard deviations of d-j-bulb, wet-bulb (over) SDD, 1473 UNCLASS IF I ED FC...distribution tables Dry -bulb temperature versud wet-bulb temperature Cumulative percentage frequency of distribution tables 20. and dew point...PART 5 PRECIPITATION PSYCHROMETRIC.DRY VS WET BULB SNOWFALL MEAN & STO 0EV SNOW EPTH DRY BULB, WET BULB, &DEW POINtI RELATIVE HUMIDITY PARTC SURFACE

Measured Two-Dimensional Ice-Wedge Polygon Thermal and Active Layer Dynamics

NASA Astrophysics Data System (ADS)

Cable, W.; Romanovsky, V. E.; Busey, R.

2016-12-01

Ice-wedge polygons are perhaps the most dominant permafrost related features in the arctic landscape. The microtopography of these features, that includes rims, troughs, and high and low polygon centers, alters the local hydrology. During winter, wind redistribution of snow leads to an increased snowpack depth in the low areas, while the slightly higher areas often have very thin snow cover, leading to differences across the landscape in vegetation communities and soil moisture between higher and lower areas. To investigate the effect of microtopographic caused variation in surface conditions on the ground thermal regime, we established temperature transects, composed of five vertical array thermistor probes (VATP), across four different development stages of ice-wedge polygons near Barrow, Alaska. Each VATP had 16 thermistors from the surface to a depth of 1.5 m, for a total of 80 temperature measurements per polygon. We found snow cover, timing and depth, and active layer soil moisture to be major controlling factors in the observed thermal regimes. In troughs and in the centers of low-centered polygons, the combined effect of typically saturated soils and increased snow accumulation resulted in the highest mean annual ground temperatures (MAGT) and latest freezeback dates. While the centers of high-centered polygons, with thinner snow cover and a dryer active layer, had the lowest MAGT, earliest freezeback dates, and shallowest active layer. Refreezing of the active layer initiated at nearly the same time for all locations and polygons however, we found large differences in the proportion of downward versus upward freezing and the length of time required to complete the refreezing process between polygon types and locations. Using our four polygon stages as a space for time substitution, we conclude that ice-wedge degradation resulting in surface subsidence and trough deepening can lead to overall drying of the active layer and increased skewedness of snow distribution. Which in turn leads to shallower active layers, earlier freezeback dates, and lower MAGT. We also find that the large variation in active layer dynamics (active layer depth, downward vs upward freezing, and freezeback date) are important considerations to understanding and scaling biological processes occurring in these landscapes.

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.

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

Snowmelt and Surface Freeze/Thaw Timings over Alaska derived from Passive Microwave Observations using a Wavelet Classifier

NASA Astrophysics Data System (ADS)

Steiner, N.; McDonald, K. C.; Dinardo, S. J.; Miller, C. E.

2015-12-01

Arctic permafrost soils contain a vast amount of organic carbon that will be released into the atmosphere as carbon dioxide or methane when thawed. Surface to air greenhouse gas fluxes are largely dependent on such surface controls as the frozen/thawed state of the snow and soil. Satellite remote sensing is an important means to create continuous mapping of surface properties. Advances in the ability to determine soil and snow freeze/thaw timings from microwave frequency observations improves upon our ability to predict the response of carbon gas emission to warming through synthesis with in-situ observation, such as the 2012-2015 Carbon in Arctic Reservoir Vulnerability Experiment (CARVE). Surface freeze/thaw or snowmelt timings are often derived using a constant or spatially/temporally variable threshold applied to time-series observations. Alternately, time-series singularity classifiers aim to detect discontinuous changes, or "edges", in time-series data similar to those that occur from the large contrast in dielectric constant during the freezing or thaw of soil or snow. We use multi-scale analysis of continuous wavelet transform spectral gradient brightness temperatures from various channel combinations of passive microwave radiometers, Advanced Microwave Scanning Radiometer (AMSR-E, AMSR2) and Special Sensor Microwave Imager (SSM/I F17) gridded at a 10 km posting with resolution proportional to the observational footprint. Channel combinations presented here aim to illustrate and differentiate timings of "edges" from transitions in surface water related to various landscape components (e.g. snow-melt, soil-thaw). To support an understanding of the physical basis of observed "edges" we compare satellite measurements with simple radiative transfer microwave-emission modeling of the snow, soil and vegetation using in-situ observations from the SNOw TELemetry (SNOTEL) automated weather stations. Results of freeze/thaw and snow-melt timings and trends are reported for Alaska and the North-West Canadian Arctic for the period 2002 to 2015.

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 rate gets faster than the diffusion rate (under condition of warm outside temperatures), as it was observed at the end of the experiment reported here, dark material starts accumulating into the surface [5]. The BC deposited on snow at warm temperatures initiates rapid melting process and may cause dramatic changes on the snow surface. References 1 Peltoniemi J.I., Hakala T., Suomalainen J., Honkavaara E., Markelin L., Gritsevich M., Eskelinen J., Jaanson P., Ikonen E. (2014): Technical notes: A detailed study for the provision of measurement uncertainty and traceability for goniospectrometers. Journal of Quantitative Spectroscopy & Radiative Transfer 146, 376-390, http://dx.doi.org/10.1016/j.jqsrt.2014.04.011 2 Zubko N., Gritsevich M., Zubko E., Hakala T., Peltoniemi J.I. (2016): Optical measurements of chemically heterogeneous particulate surfaces // Journal of Quantitative Spectroscopy and Radiative Transfer, 178, 422-431, http://dx.doi.org/10.1016/j.jqsrt.2015.12.010 3 Peltoniemi J.I., Gritsevich M., Hakala T., Dagsson-Waldhauserová P., Arnalds Ó., Anttila K., Hannula H.-R., Kivekäs N., Lihavainen H., Meinander O., Svensson J., Virkkula A., de Leeuw G. (2015): Soot on snow exper- iment: bidirectional reflectance factor measurements of contaminated snow // The Cryosphere, 9, 2323-2337, http://dx.doi.org/10.5194/tc-9-2323-2015 4 Svensson J., Virkkula A., Meinander O., Kivekäs N., Hannula H.-R., Järvinen O., Peltoniemi J.I., Gritsevich M., Heikkilä A., Kontu A., Neitola K., Brus D., Dagsson-Waldhauserova P., Anttila K., Vehkamäki M., Hienola A., de Leeuw G. & Lihavainen H. (2016): Soot-doped natural snow and its albedo — results from field experiments. Boreal Environment Research, 21, 481-503, http://www.borenv.net/BER/pdfs/preprints/Svensson1498.pdf 5 Meinander O., Kontu A., Virkkula A., Arola A., Backman L., Dagsson-Waldhauserová P., Järvinen O., Manninen T., Svensson J., de Leeuw G., and Leppäranta M. (2014): Brief communication: Light-absorbing impurities can reduce the density of melting snow, The Cryosphere, 8, 991-995, doi:10.5194/tc-8-991-2014.

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.

Detection Thresholds of Falling Snow from Satellite-Borne Active and Passive Sensors

NASA Technical Reports Server (NTRS)

Jackson, Gail

2012-01-01

Precipitation, including rain and snow, is a critical part of the Earth's energy and hydrology cycles. In order to collect information on the complete global precipitation cycle and to understand the energy budget in terms of precipitation, uniform global estimates of both liquid and frozen precipitation must be collected. Active observations of falling snow are somewhat easier to estimate since the radar will detect the precipitation particles and one only needs to know surface temperature to determine if it is liquid rain or snow. The challenges of estimating falling snow from passive spaceborne observations still exist though progress is being made. While these challenges are still being addressed, knowledge of their impact on expected retrieval results is an important key for understanding falling snow retrieval estimations. Important information to assess falling snow retrievals includes knowing thresholds of detection for active and passive sensors, various sensor channel configurations, snow event system characteristics, snowflake particle assumptions, and surface types. For example, can a lake effect snow system with low (2.5 km) cloud tops having an ice water content (Iwe) at the surface of 0.25 g m-3 and dendrite snowflakes be detected? If this information is known, we can focus retrieval efforts on detectable storms and concentrate advances on achievable results. Here, the focus is to determine thresholds of detection for falling snow for various snow conditions over land and lake surfaces. The analysis relies on simulated Weather Research Forecasting (WRF) simulations of falling snow cases since simulations provide all the information to determine the measurements from space and the ground truth. Results are presented for active radar at Ku, Ka, and W-band and for passive radiometer channels from 10 to 183 GHz (Skofronick-Jackson, et al. submitted to IEEE TGRS, April 2012). The notable results show: (1) the W-Band radar has detection thresholds more than an order of magnitude lower than the future GPM sensors, (2) the cloud structure macrophysics influences the thresholds of detection for passive channels, (3) the snowflake microphysics plays a large role in the detection threshold for active and passive instruments, (4) with reasonable assumptions, the passive 166 GHz channel has detection threshold values comparable to the GPM DPR Ku and Ka band radars with 0.05 g m-3 detected at the surface, or an 0.5-1 mm hr-l melted snow rate (equivalent to 0.5-2 cm hr-l solid fluffy snowflake rate).

Preliminary results and assessment of the MAR outputs over High Mountain Asia

NASA Astrophysics Data System (ADS)

Linares, M.; Tedesco, M.; Margulis, S. A.; Cortés, G.; Fettweis, X.

2017-12-01

Lack of ground measurements has made the use of regional climate models (RCMs) over the High Mountain Asia (HMA) pivotal for understanding the impact of climate change on the hydrological cycle and on the cryosphere. Here, we show an analysis of the assessment of the outputs of Modèle Atmosphérique Régionale (MAR) model RCM over the HMA region as part of the NASA-funded project `Understanding and forecasting changes in High Mountain Asia snow hydrology via a novel Bayesian reanalysis and modeling approach'. The first step was to evaluate the impact of the different forcings on MAR outputs. To this aim, we performed simulations for the 2007 - 2008 and 2014 - 2015 years forcing MAR at its boundaries either with reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF) or from the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2). The comparison between the outputs obtained with the two forcings indicates that the impact on MAR simulations depends on specific parameters. For example, in case of surface pressure the maximum percentage error is 0.09 % while the 2-m air temperature has a maximum percentage error of 103.7%. Next, we compared the MAR outputs with reanalysis data fields over the region of interest. In particular, we evaluated the following parameters: surface pressure, snow depth, total cloud cover, two meter temperature, horizontal wind speed, vertical wind speed, wind speed, surface new solar radiation, skin temperature, surface sensible heat flux, and surface latent heat flux. Lastly, we report results concerning the assessment of MAR surface albedo and surface temperature over the region through MODIS remote sensing products. Next steps are to determine whether RCMs and reanalysis datasets are effective at capturing snow and snowmelt runoff processes in the HMA region through a comparison with in situ datasets. This will help determine what refinements are necessary to improve RCM outputs.

Direct mapping of the temperature and velocity gradients in discs. Imaging the vertical CO snow line around IM Lupi

NASA Astrophysics Data System (ADS)

Pinte, C.; Ménard, F.; Duchêne, G.; Hill, T.; Dent, W. R. F.; Woitke, P.; Maret, S.; van der Plas, G.; Hales, A.; Kamp, I.; Thi, W. F.; de Gregorio-Monsalvo, I.; Rab, C.; Quanz, S. P.; Avenhaus, H.; Carmona, A.; Casassus, S.

2018-01-01

Accurate measurements of the physical structure of protoplanetary discs are critical inputs for planet formation models. These constraints are traditionally established via complex modelling of continuum and line observations. Instead, we present an empirical framework to locate the CO isotopologue emitting surfaces from high spectral and spatial resolution ALMA observations. We apply this framework to the disc surrounding IM Lupi, where we report the first direct, i.e. model independent, measurements of the radial and vertical gradients of temperature and velocity in a protoplanetary disc. The measured disc structure is consistent with an irradiated self-similar disc structure, where the temperature increases and the velocity decreases towards the disc surface. We also directly map the vertical CO snow line, which is located at about one gas scale height at radii between 150 and 300 au, with a CO freeze-out temperature of 21 ± 2 K. In the outer disc (>300 au), where the gas surface density transitions from a power law to an exponential taper, the velocity rotation field becomes significantly sub-Keplerian, in agreement with the expected steeper pressure gradient. The sub-Keplerian velocities should result in a very efficient inward migration of large dust grains, explaining the lack of millimetre continuum emission outside of 300 au. The sub-Keplerian motions may also be the signature of the base of an externally irradiated photo-evaporative wind. In the same outer region, the measured CO temperature above the snow line decreases to ≈15 K because of the reduced gas density, which can result in a lower CO freeze-out temperature, photo-desorption, or deviations from local thermodynamic equilibrium.

Methods for Improving Fine-Scale Applications of the WRF-CMAQ Modeling System

EPA Science Inventory

Presentation on the work in AMAD to improve fine-scale (e.g. 4km and 1km) WRF-CMAQ simulations. Includes iterative analysis, updated sea surface temperature and snow cover fields, and inclusion of impervious surface information (urban parameterization).

Snow: a reliable indicator for global warming in the future?

NASA Astrophysics Data System (ADS)

Jacobi, H.-W.

2012-03-01

The cryosphere consists of water in the solid form at the Earth's surface and includes, among others, snow, sea ice, glaciers and ice sheets. Since the 1990s the cryosphere and its components have often been considered as indicators of global warming because rising temperatures can enhance the melting of solid water (e.g. Barry et al 1993, Goodison and Walker 1993, Armstrong and Brun 2008). Changes in the cryosphere are often easier to recognize than a global temperature rise of a couple of degrees: many locals and tourists have hands-on experience in changes in the extent of glaciers or the duration of winter snow cover on the Eurasian and North American continents. On a more scientific basis, the last IPCC report left no doubt: the amount of snow and ice on Earth is decreasing (Lemke et al 2007). Available data showed clearly decreasing trends in the sea ice and frozen ground extent of the Northern Hemisphere (NH) and the global glacier mass balance. However, the trend in the snow cover extent (SCE) of the NH was much more ambiguous; a result that has since been confirmed by the online available up-to-date analysis of the SCE performed by the Rutgers University Global Snow Lab (climate.rutgers.edu/snowcover/). The behavior of snow is not the result of a simple cause-and-effect relationship between air temperature and snow. It is instead related to a rather complex interplay between external meteorological parameters and internal processes in the snowpack. While air temperature is of course a crucial parameter for snow and its melting, precipitation and radiation are also important. Further physical properties like snow grain size and the amount of absorbing impurities in the snow determine the fraction of absorbed radiation. While all these parameters affect the energy budget of the snowpack, each of these variables can dominate depending on the season or, more generally, on environmental conditions. As a result, the reduction in SCE in spring and summer in the NH was attributed to faster melting because of higher air temperatures, while the winter months (December to February) saw an increase in the SCE due to increased precipitation (Lemke et al >2007). Cohen et al (2012) confirmed these opposing effects in the SCE and showed that on the Eurasian continent the average SCE in October has increased by approximately 3 × 106 km2 in the last two decades; a growth of almost 40%, corresponding to roughly 1.5 times the area of Greenland. For the same period, Cohen et al (2012) found a negligible trend in the average temperatures above the continents of the NH for the winter months despite a significant increase in the annual mean temperature for the same regions. Cohen et al (2012) propose the following link between temperatures and snow: the reduced sea ice cover of the Arctic Ocean and the enhanced air temperatures in fall cause higher evaporation from the Arctic Ocean, leading to increased tropospheric moisture in the Arctic. More moisture results in more snowfall over the Eurasian continent, increasing the SCE. The increased snow cover strengthens the Siberian High, a strong anticyclonic system generally persistent between October and April. This system is strong enough to affect weather patterns in large parts of the NH, resulting in changes in the large-scale circulation of the NH (Panagiotopoulos et al 2005). As a result, outbreaks of cold Arctic air masses into the mid-latitudes are more frequent, leading to low temperatures over the eastern part of North America and Northern Eurasia. According to Cohen et al (2012), these are exactly the same regions that have experienced a cooling trend in the winter temperature over the past twenty years. While this chain of events is plausible (and some are confirmed by observations), existing climate models are not yet capable of reproducing these processes. On the contrary, Cohen et al (2012) showed that they predict a slightly decreasing SCE in October for Eurasia and an increase in winter temperatures over the continents in the NH. This is not surprising because the simulation of snow and its interactions with the atmosphere in global models is imperfect (Armstrong and Brun 2008). Most models have difficulty in simulating successfully the complex behavior of snow cover. A better representation of snow in the models is vital in order to understand the possible far-reaching consequences of changes in the SCE and its effects on the local climate and on large-scale circulations in the atmosphere to utilize snow as a reliable indicator for a changing climate. However, the SCE is only one of many possible snow parameters that can be used (Goodison and Walker 1993). Although omni-present in many regions and during many seasons, there is still much to be learned about snow and how it is linked to the global climate system. References Armstrong R L and Brun E 2008 Snow and Climate: Physical Processes, Surface Energy Exchange and Modeling (Cambridge: Cambridge University Press) Barry R G, Goodison B E and LeDrew E F (ed) 1993 Snow watch '92—detection strategies for snow and ice Glaciological Data Report GD-25 (Boulder, CO: World Data Center A: Glaciology (Snow and Ice)) p 273 Cohen J L, Furtado J C, Barlow M A, Alexeev V A and Cherry J E 2012 Arctic warming, increasing snow cover and widespread boreal winter cooling Environ. Res. Lett. 7 014007 Goodison B E and Walker A E 1993 Use of snow cover derived from satellite passive microwave data as indicator for climate change Ann. Glaciol. 17 137-42 Lemke P et al 2007 Observations: changes in snow, ice and frozen ground Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (Cambridge: Cambridge University Press) Panagiotopoulos F, Shahgedanova M, Hannachi A and Stephenson D B 2005 Observed trends and teleconnections of the Siberian high: a recently declining center of action J. Clim. 18 1411-22

Evaluation of energy fluxes in the NCEP climate forecast system version 2.0 (CFSv2)

NASA Astrophysics Data System (ADS)

Rai, Archana; Saha, Subodh Kumar

2018-01-01

The energy fluxes at the surface and top of the atmosphere (TOA) from a long free run by the NCEP climate forecast system version 2.0 (CFSv2) are validated against several observation and reanalysis datasets. This study focuses on the annual mean energy fluxes and tries to link it with the systematic cold biases in the 2 m air temperature, particularly over the land regions. The imbalance in the long term mean global averaged energy fluxes are also evaluated. The global averaged imbalance at the surface and at the TOA is found to be 0.37 and 6.43 Wm-2, respectively. It is shown that CFSv2 overestimates the land surface albedo, particularly over the snow region, which in turn contributes to the cold biases in 2 m air temperature. On the other hand, surface albedo is highly underestimated over the coastal region around Antarctica and that may have contributed to the warm bias over that oceanic region. This study highlights the need for improvements in the parameterization of snow/sea-ice albedo scheme for a realistic simulation of surface temperature and that may have implications on the global energy imbalance in the model.

Perspectives on the causes of exceptionally low 2015 snowpack in the western United States

NASA Astrophysics Data System (ADS)

Mote, Philip W.; Rupp, David E.; Li, Sihan; Sharp, Darrin J.; Otto, Friederike; Uhe, Peter F.; Xiao, Mu; Lettenmaier, Dennis P.; Cullen, Heidi; Allen, Myles R.

2016-10-01

Augmenting previous papers about the exceptional 2011-2015 California drought, we offer new perspectives on the "snow drought" that extended into Oregon in 2014 and Washington in 2015. Over 80% of measurement sites west of 115°W experienced record low snowpack in 2015, and we estimate a return period of 400-1000 years for California's snowpack under the questionable assumption of stationarity. Hydrologic modeling supports the conclusion that 2015 was the most severe on record by a wide margin. Using a crowd-sourced superensemble of regional climate model simulations, we show that both human influence and sea surface temperature (SST) anomalies contributed strongly to the risk of snow drought in Oregon and Washington: the contribution of SST anomalies was about twice that of human influence. By contrast, SSTs and humans appear to have played a smaller role in creating California's snow drought. In all three states, the anthropogenic effect on temperature exacerbated the snow drought.

Effects of Changing Climate During the Snow Ablation Season on Seasonal Streamflow Forecasts

NASA Astrophysics Data System (ADS)

Gutzler, D. S.; Chavarria, S. B.

2017-12-01

Seasonal forecasts of total surface runoff (Q) in snowmelt-dominated watersheds derive most of their prediction skill from the historical relationship between late winter snowpack (SWE) and subsequent snowmelt runoff. Across the western US, however, the relationship between SWE and Q is weakening as temperatures rise. We describe the effects of climate variability and change during the springtime snow ablation season on water supply outlooks (forecasts of Q) for southwestern rivers. As snow melts earlier, the importance of post-snow rainfall increases: interannual variability of spring season precipitation accounts for an increasing fraction of the variability of Q in recent decades. The results indicate that improvements to the skill of S2S forecasts of spring season temperature and precipitation would contribute very significantly to water supply outlooks that are now based largely on observed SWE. We assess this hypothesis using historical data from several snowpack-dominated basins in the American Southwest (Rio Grande, Pecos, and Gila Rivers) which are undergoing rapid climate change.

Spatiotemporal variations in the difference between satellite-observed daily maximum land surface temperature and station-based daily maximum near-surface air temperature

NASA Astrophysics Data System (ADS)

Lian, Xu; Zeng, Zhenzhong; Yao, Yitong; Peng, Shushi; Wang, Kaicun; Piao, Shilong

2017-02-01

There is an increasing demand to integrate land surface temperature (LST) into climate research due to its global coverage, which requires a comprehensive knowledge of its distinctive characteristics compared to near-surface air temperature (Tair). Using satellite observations and in situ station-based data sets, we conducted a global-scale assessment of the spatial and seasonal variations in the difference between daily maximum LST and daily maximum Tair (δT, LST - Tair) during 2003-2014. Spatially, LST is generally higher than Tair over arid and sparsely vegetated regions in the middle-low latitudes, but LST is lower than Tair in tropical rainforests due to strong evaporative cooling, and in the high-latitude regions due to snow-induced radiative cooling. Seasonally, δT is negative in tropical regions throughout the year, while it displays a pronounced seasonality in both the midlatitudes and boreal regions. The seasonality in the midlatitudes is a result of the asynchronous responses of LST and Tair to the seasonal cycle of radiation and vegetation abundance, whereas in the boreal regions, seasonality is mainly caused by the change in snow cover. Our study identified substantial spatial heterogeneity and seasonality in δT, as well as its determinant environmental drivers, and thus provides a useful reference for monitoring near-surface air temperature changes using remote sensing, particularly in remote regions.

The significance of vertical moisture diffusion on drifting snow sublimation near snow surface

NASA Astrophysics Data System (ADS)

Huang, Ning; Shi, Guanglei

2017-12-01

Sublimation of blowing snow is an important parameter not only for the study of polar ice sheets and glaciers, but also for maintaining the ecology of arid and semi-arid lands. However, sublimation of near-surface blowing snow has often been ignored in previous studies. To study sublimation of near-surface blowing snow, we established a sublimation of blowing snow model containing both a vertical moisture diffusion equation and a heat balance equation. The results showed that although sublimation of near-surface blowing snow was strongly reduced by a negative feedback effect, due to vertical moisture diffusion, the relative humidity near the surface does not reach 100 %. Therefore, the sublimation of near-surface blowing snow does not stop. In addition, the sublimation rate near the surface is 3-4 orders of magnitude higher than that at 10 m above the surface and the mass of snow sublimation near the surface accounts for more than half of the total snow sublimation when the friction wind velocity is less than about 0.55 m s-1. Therefore, the sublimation of near-surface blowing snow should not be neglected.

Snowmelt in a High Latitude Mountain Catchment: Effect of Vegetation Cover and Elevation

NASA Astrophysics Data System (ADS)

Pomeroy, J. W.; Essery, R. L.; Ellis, C. R.; Hedstrom, N. R.; Janowicz, R.; Granger, R. J.

2004-12-01

The energetics and mass balance of snowpacks in the premelt and melt period were compared from three elevation bands in a high latitude mountain catchment, Wolf Creek Research Basin, Yukon. Elevation is strongly correlated with vegetation cover and in this case the three elevation bands (low, middle, high) correspond to mature spruce forest, dense shrub tundra and sparse tundra (alpine). Measurements of radiation, ground heat flux, snow depth, snowfall, air temperature, wind speed were made on a half-hourly basis at the three elevations for a 10 year period. Sondes provided vertical gradients of air temperature, humidity, wind speed and air pressure. Snow depth and density surveys were conducted monthly. Comparisons of wind speed, air temperature and humidity at three elevations show that the expected elevational gradients in the free atmosphere were slightly enhanced just above the surface canopies, but that the climate at the snow surface was further influenced by complex canopy effects. Premelt snow accumulation was strongly affected by intercepted snow in the forest and blowing snow sublimation in the sparse tundra but not by the small elevational gradients in snowfall. As a result the maximum premelt SWE was found in the mid-elevation shrub tundra and was roughly double that of the sparse tundra or forest. Minimum variability of SWE was observed in the forest and shrub tundra (CV=0.25) while in the sparse tundra variability doubled (CV=0.5). Snowmelt was influenced by differences in premelt accumulation as well as differences in the net energy fluxes to snow. Elevation had a strong effect on the initiation of melt with the forest melt starting on average 16 days before the shrub tundra and 19 days before the sparse tundra. Mean melt rates showed a maximum in middle elevations and increased from 860 kJ/day in the forest to 1460 kJ/day in the sparse tundra and 2730 kJ/day in the shrub tundra. The forest canopy reduced melt while the shrub canopy enhanced it relative to the sparsely vegetated tundra. Duration of melt was similar in the forest and shrub tundra at 20 days while the sparse tundra was shorter at 13 days; the differences due to differing snow accumulation and melt rates. The greatest variability in the timing and rate of melt was found in the shrub tundra, where the effect of the shrub canopy over snow depends on snow depth and insolation and is reduced in years with high snow accumulation or extensive cloudy periods in spring. The results show that it is necessary to consider the combination of elevation and vegetation effects on snow microclimate and melt processes in high latitude mountain catchments, but that weather patterns induce substantial variability on the effect these factors.

The AMSR2 Satellite-based Microwave Snow Algorithm (SMSA) to estimate regional to global snow depth and snow water equivalent

NASA Astrophysics Data System (ADS)

Kelly, R. E. J.; Saberi, N.; Li, Q.

2017-12-01

With moderate to high spatial resolution (<1 km) regional to global snow water equivalent (SWE) observation approaches yet to be fully scoped and developed, the long-term satellite passive microwave record remains an important tool for cryosphere-climate diagnostics. A new satellite microwave remote sensing approach is described for estimating snow depth (SD) and snow water equivalent (SWE). The algorithm, called the Satellite-based Microwave Snow Algorithm (SMSA), uses Advanced Microwave Scanning Radiometer - 2 (AMSR2) observations aboard the Global Change Observation Mission - Water mission launched by the Japan Aerospace Exploration Agency in 2012. The approach is unique since it leverages observed brightness temperatures (Tb) with static ancillary data to parameterize a physically-based retrieval without requiring parameter constraints from in situ snow depth observations or historical snow depth climatology. After screening snow from non-snow surface targets (water bodies [including freeze/thaw state], rainfall, high altitude plateau regions [e.g. Tibetan plateau]), moderate and shallow snow depths are estimated by minimizing the difference between Dense Media Radiative Transfer model estimates (Tsang et al., 2000; Picard et al., 2011) and AMSR2 Tb observations to retrieve SWE and SD. Parameterization of the model combines a parsimonious snow grain size and density approach originally developed by Kelly et al. (2003). Evaluation of the SMSA performance is achieved using in situ snow depth data from a variety of standard and experiment data sources. Results presented from winter seasons 2012-13 to 2016-17 illustrate the improved performance of the new approach in comparison with the baseline AMSR2 algorithm estimates and approach the performance of the model assimilation-based approach of GlobSnow. Given the variation in estimation power of SWE by different land surface/climate models and selected satellite-derived passive microwave approaches, SMSA provides SWE estimates that are independent of real or near real-time in situ and model data.

Effect of snow cover on soil frost penetration

NASA Astrophysics Data System (ADS)

Rožnovský, Jaroslav; Brzezina, Jáchym

2017-12-01

Snow cover occurrence affects wintering and lives of organisms because it has a significant effect on soil frost penetration. An analysis of the dependence of soil frost penetration and snow depth between November and March was performed using data from 12 automated climatological stations located in Southern Moravia, with a minimum period of measurement of 5 years since 2001, which belong to the Czech Hydrometeorological institute. The soil temperatures at 5 cm depth fluctuate much less in the presence of snow cover. In contrast, the effect of snow cover on the air temperature at 2 m height is only very small. During clear sky conditions and no snow cover, soil can warm up substantially and the soil temperature range can be even higher than the range of air temperature at 2 m height. The actual height of snow is also important - increased snow depth means lower soil temperature range. However, even just 1 cm snow depth substantially lowers the soil temperature range and it can therefore be clearly seen that snow acts as an insulator and has a major effect on soil frost penetration and soil temperature range.

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 inform the development of adaptation and mitigation measures. The CHARIS Project is funded by USAID.

Spatial analysis and statistical modelling of snow cover dynamics in the Central Himalayas, Nepal

NASA Astrophysics Data System (ADS)

Weidinger, Johannes; Gerlitz, Lars; Böhner, Jürgen

2017-04-01

General circulation models are able to predict large scale climate variations in global dimensions, however small scale dynamic characteristics, such as snow cover and its temporal variations in high mountain regions, are not represented sufficiently. Detailed knowledge about shifts in seasonal ablation times and spatial distribution of snow cover are crucial for various research interests. Since high mountain areas, for instance the Central Himalayas in Nepal, are generally remote, it is difficult to obtain data in high spatio-temporal resolutions. Regional climate models and downscaling techniques are implemented to compensate coarse resolution. Furthermore earth observation systems, such as MODIS, also permit bridging this gap to a certain extent. They offer snow (cover) data in daily temporal and medium spatial resolution of around 500 m, which can be applied as evaluation and training data for dynamical hydrological and statistical analyses. Within this approach two snow distribution models (binary snow cover and fractional snow cover) as well as one snow recession model were implemented for a research domain in the Rolwaling Himal in Nepal, employing the random forest technique, which represents a state of the art machine learning algorithm. Both bottom-up strategies provide inductive reasoning to derive rules for snow related processes out of climate (temperature, precipitation and irradiance) and climate-related topographic data sets (elevation, aspect and convergence index) obtained by meteorological network stations, remote sensing products (snow cover - MOD10-A1 and land surface temperatures - MOD11-A1) along with GIS. Snow distribution is predicted reliably on a daily basis in the research area, whereas further effort is necessary for predicting daily snow cover recession processes adequately. Swift changes induced by clear sky conditions with high insolation rates are well represented, whereas steady snow loss still needs continuing effort. All approaches underline the technical difficulties of snow cover modelling during the monsoon season, in accordance with previous studies. The developed methods in combination with continuous in situ measurements provide a basis for further downscaling approaches.

Improvements in AVHRR Daytime Cloud Detection Over the ARM NSA Site

NASA Technical Reports Server (NTRS)

Chakrapani, V.; Spangenberg, D. A.; Doelling, D. R.; Minnis, P.; Trepte, Q. Z.; Arduini, R. F.

2001-01-01

Clouds play an important role in the radiation budget over Arctic and Antarctic. Because of limited surface observing capabilities, it is necessary to detect clouds over large areas using satellite imagery. At low and mid-latitudes, satellite-observed visible (VIS; 0.65 micrometers) and infrared (IR; 11 micrometers) radiance data are used to derive cloud fraction, temperature, and optical depth. However, the extreme variability in the VIS surface albedo makes the detection of clouds from satellite a difficult process in polar regions. The IR data often show that the surface is nearly the same temperature or even colder than clouds, further complicating cloud detection. Also, the boundary layer can have large areas of haze, thin fog, or diamond dust that are not seen in standard satellite imagery. Other spectral radiances measured by satellite imagers provide additional information that can be used to more accurately discriminate clouds from snow and ice. Most techniques currently use a fixed reflectance or temperature threshold to decide between clouds and clear snow. Using a subjective approach, Minnis et al. (2001) found that the clear snow radiance signatures vary as a function of viewing and illumination conditions as well as snow condition. To routinely process satellite imagery over polar regions with an automated algorithm, it is necessary to account for this angular variability and the change in the background reflectance as snow melts, vegetation grows over land, and melt ponds form on pack ice. This paper documents the initial satellite-based cloud product over the Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) site at Barrow for use by the modeling community. Cloud amount and height are determined subjectively using an adaptation of the methodology of Minnis et al. (2001) and the radiation fields arc determined following the methods of Doelling et al. (2001) as applied to data taken during the Surface Heat and Energy Budget of the Arctic (SHEBA). The procedures and data produced in this empirically based analysis will also facilitate the development of the automated algorithm for future processing of satellite data over the ARM NSA domain. Results are presented for May, June, and July 1998. ARM surface data are use to partially validate the results taken directly over the ARM site.

Sensitivity studies on the impacts of Tibetan Plateau snowpack pollution on the Asian hydrological cycle and monsoon climate

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

Qian, Yun; Flanner, M G; Leung, Lai-Yung R

2011-03-02

The Tibetan Plateau (TP), the highest and largest plateau in the world, has long been identified to be critical in regulating the Asian monsoon climate and hydrological cycle. The snowpack and glaciers over the TP provide fresh water to billions of people in Asian countries, but the TP glaciers have been retreating extensively at a speed faster than any other part of the world. In this study a series of experiments with a global climate model are designed to simulate black carbon (BC) and dust in snow and their radiative forcing and to assess the relative impacts of anthropogenic COmore » 2 and carbonaceous particles in the atmosphere and snow, respectively, on the snowpack over the TP, as well as their subsequent impacts on the Asian monsoon climate and hydrological cycle. Results show a large BC content in snow over the TP, especially the southern slope, with concentration larger than 100 µk/kg. Because of the high aerosol content in snow and large incident solar radiation in the low latitude and high elevation, the TP exhibits the largest surface radiative forcing induced by aerosols (e.g. BC, Dust) in snow compared to other snow-covered regions in the world. The aerosol-induced snow albedo perturbations generate surface radiative forcing of 5-25 W m -2 during spring, with a maximum in April or May. BC-in-snow increases the surface air temperature by around 1.0°C averaged over the TP and reduces snowpack over the TP more than that induced by pre-industrial to present CO 2 increase and carbonaceous particles in the atmosphere during spring. As a result, runoff increases during late winter and early spring but decreases during late spring and early summer (i.e. a trend toward earlier melt dates). The snowmelt efficacy, defined as the snowpack reduction per unit degree of warming induced by the forcing agent, is 1-4 times larger for BC-in-snow than CO 2 increase during April-July, indicating that BC-in-snow more efficiently accelerates snowmelt because the increased net solar radiation induced by reduced albedo melts the snow more efficiently than snow melt due to warming in the air. The TP also influences the South (SAM) and East (EAM) Asian monsoon through its dynamical and thermal forcing. During boreal spring, aerosols are transported by the southwesterly and reach the higher altitude and/or deposited in the snowpack over the TP. While BC and OM in the atmosphere directly absorb sunlight and warm the air, the darkened snow surface polluted by BC absorbs more solar radiation and increases the skin temperature, which warms the air above by the increased sensible heat flux over the TP. Both effects enhance the upward motion of air and spur deep convection along the TP during pre-monsoon season, resulting in earlier onset of the SAM and increase of moisture, cloudiness and convective precipitation over northern India. BC-in-snow has a more significant impact on the EAM in July than CO 2 increase and carbonaceous particles in the atmosphere. Contributed by the significant increase of both sensible heat flux associated with the warm skin temperature and latent heat flux associated with increased soil moisture with long memory, the role of the TP as a heat pump is elevated from spring through summer as the land-sea thermal contrast increases to strengthen the EAM. As a result, both southern China and northern China become wetter, but central China (i.e. Yangtze River Basin) becomes drier - a near zonal anomaly pattern that is consistent with the dominant mode of precipitation variability in East Asia.« less

Unusually Low Snow Cover in the U.S.

NASA Technical Reports Server (NTRS)

2002-01-01

New maps of snow cover produced by NASA's Terra satellite show that this year's snow line stayed farther north than normal. When combined with land surface temperature measurements, the observations confirm earlier National Oceanic and Atmospheric Administration reports that the United States was unusually warm and dry this past winter. The above map shows snow cover over the continental United States from February 2002 and is based on data acquired by the Moderate-Resolution Imaging Spectroradiometer (MODIS). The amount of land covered by snow during this period was much lower than usual. With the exception of the western mountain ranges and the Great Lakes region, the country was mostly snow free. The solid red line marks the average location of the monthly snow extent; white areas are snow-covered ground. Snow was mapped at approximately 5 kilometer pixel resolution on a daily basis and then combined, or composited, every eight days. If a pixel was at least 50 percent snow covered during all of the eight-day periods that month, it was mapped as snow covered for the whole month. For more information, images, and animations, read: Terra Satellite Data Confirm Unusually Warm, Dry U.S. Winter Image by Robert Simmon, based on data from the MODIS Snow/Ice Global Mapping Project

Interpretation of snow-climate feedback as produced by 17 general circulation models

NASA Technical Reports Server (NTRS)

Cess, R. D.; Zhang, M.-H.; Potter, G. L.; Blanchet, J.-P.; Chalita, S.; Colman, R.; Dazlich, D. A.; Del Genio, A. D.; Lacis, A. A.; Dymnikov, V.

1991-01-01

Snow feedback is expected to amplify global warming caused by increasing concentrations of atmospheric greenhouse gases. The conventional explanation is that a warmer earth will have less snow cover, resulting in a darker planet that absorbs more solar radiation. An intercomparison of 17 general circulation models, for which perturbations of sea surface temperature were used as a surrogate climate change, suggests that this explanation is overly simplistic. The results instead indicate that additional amplification or moderation may be caused both by cloud interactions and longwave radiation. One measure of this net effect of snow feedback was found to differ markedly among the 17 climate models, ranging from weak negative feedback in some models to strong positive feedback in others.

A Prognostic Methodology for Precipitation Phase Detection using GPM Microwave Observations —With Focus on Snow Cover

NASA Astrophysics Data System (ADS)

Takbiri, Z.; Ebtehaj, A.; Foufoula-Georgiou, E.; Kirstetter, P.

2017-12-01

Improving satellite retrieval of precipitation requires increased understanding of its passive microwave signature over different land surfaces. Passive microwave signals over snow-covered surfaces are notoriously difficult to interpret because they record both emission from the land below and absorption/scattering from the liquid/ice crystals. Using data from the Global Precipitation Measurement (GPM) core satellite, we demonstrate that the microwave brightness temperatures of rain and snowfall shifts from a scattering to an emission regime from summer to winter, due to expansion of the less emissive snow cover underneath. We present evidence that the combination of low- (10-19 GHz) and high-frequency (89-166 GHz) channels provides the maximum amount of information for snowfall detection. The study also examines a prognostic nearest neighbor matching method for the detection of precipitation and its phase from passive microwave observations using GPM data. The nearest neighbor uses the weighted Euclidean distance metric to search through an a priori database that is populated with coincident GPM radiometer and radar data as well as ancillary snow cover fraction. The results demonstrate prognostic capabilities of the proposed method in detection of terrestrial snowfall. At the global scale, the average probability of hit and false alarm reaches to 0.80 and remains below 0.10, respectively. Surprisingly, the results show that the snow cover may help to better detect precipitation as the detection rate of terrestrial precipitation is increased from 0.75 (no snow cover) to 0.84 (snow-covered surfaces). For solid precipitation, this increased rate of detection is larger than its liquid counterpart by almost 8%. The main reasons are found to be related to the multi-frequency capabilities of the nearest neighbor matching that can properly isolate the atmospheric signal from the background emission and the fact that the precipitation can exhibit an emission-like (warmer than surface) signature over fresh snow cover.

Effects of changing environmental conditions on synthetic aperture radar backscattering coefficient, scattering mechanisms, and class separability in a forest area

NASA Astrophysics Data System (ADS)

Mahdavi, Sahel; Maghsoudi, Yasser; Amani, Meisam

2017-07-01

Environmental conditions have considerable effects on synthetic aperture radar (SAR) imagery. Therefore, assessing these effects is important for obtaining accurate and reliable results. In this study, three series of RADARSAT-2 SAR images were evaluated. In each of these series, the sensor configuration was fixed, but the environmental conditions differed. The effects of variable environmental conditions were also investigated on co- and cross-polarized backscattering coefficients, Freeman-Durden scattering contributions, and the pedestal height in different classes of a forest area in Ottawa, Ontario. It was observed that the backscattering coefficient of wet snow was up to 2 dB more than that of dry snow. The absence of snow also caused a decrease of up to 3 dB in the surface scattering of ground and up to 5 dB in that of trees. In addition, the backscatter coefficients of ground vegetation, hardwood species, and softwood species were more similar at temperatures below 0°C than those at temperatures above 0°C. Moreover, the pedestal height was generally greater at temperatures above 0°C than at temperatures below 0°C. Finally, the highest class separability was observed when the temperature was at or above 0°C and there was no snow on the ground or trees.

Evaluation of snow and frozen soil parameterization in a cryosphere land surface modeling framework in the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Zhou, J.

2017-12-01

Snow and frozen soil are important components in the Tibetan Plateau, and influence the water cycle and energy balances through snowpack accumulation and melt and soil freeze-thaw. In this study, a new cryosphere land surface model (LSM) with coupled snow and frozen soil parameterization 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.

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.

Spatiotemporal Variations in the Difference between Satellite-observed Land Surface Temperature and Station-based Near-surface Air Temperature

NASA Astrophysics Data System (ADS)

Lian, X.

2016-12-01

There is an increasing demand to integrate land surface temperature (LST) into climate research due to its global coverage, which requires a comprehensive knowledge of its distinctive characteristics compared to near-surface air temperature ( ). Using satellite observations and in-situ station-based datasets, we conducted a global-scale assessment of the spatial, seasonal, and interannual variations in the difference between daytime maximum LST and daytime maximum ( , LST - ) during 2003-2014. Spatially, LST is generally higher than over arid and sparsely vegetated regions in the mid-low latitudes, but LST is lower than in the tropical rainforests due to strong evaporative cooling, and in the high-latitude regions due to snow-induced radiative cooling. Seasonally, is negative in tropical regions throughout the year, while it displays a pronounced seasonality in both the mid-latitudes and boreal regions. The seasonality in the mid-latitudes is a result of the asynchronous responses of LST and to the seasonal cycle of radiation and vegetation abundance, whereas in the boreal regions, seasonality is mainly caused by the change in snow cover. At an interannual scale, only a small proportion of the land surface displays a statistically significant trend (P <0.05) due to the short time span of current measurements. Our study identified substantial spatial heterogeneity and seasonality in , as well as its determinant environmental drivers, and thus provides a useful reference for monitoring near-surface temperature changes using remote sensing, particularly in remote regions.

Towards Year-round Estimation of Terrestrial Water Storage over Snow-Covered Terrain via Multi-sensor Assimilation of GRACE/GRACE-FO and AMSR-E/AMSR-2.

NASA Astrophysics Data System (ADS)

Wang, J.; Xue, Y.; Forman, B. A.; Girotto, M.; Reichle, R. H.

2017-12-01

The Gravity and Recovery Climate Experiment (GRACE) has revolutionized large-scale remote sensing of the Earth's terrestrial hydrologic cycle and has provided an unprecedented observational constraint for global land surface models. However, the coarse-scale (in space and time), vertically-integrated measure of terrestrial water storage (TWS) limits GRACE's applicability to smaller scale hydrologic applications. In order to enhance model-based estimates of TWS while effectively adding resolution (in space and time) to the coarse-scale TWS retrievals, a multi-variate, multi-sensor data assimilation framework is presented here that simultaneously assimilates gravimetric retrievals of TWS in conjunction with passive microwave (PMW) brightness temperature (Tb) observations over snow-covered terrain. The framework uses the NASA Catchment Land Surface Model (Catchment) and an ensemble Kalman filter (EnKF). A synthetic assimilation experiment is presented for the Volga river basin in Russia. The skill of the output from the assimilation of synthetic observations is compared with that of model estimates generated without the benefit of assimilating the synthetic observations. It is shown that the EnKF framework improves modeled estimates of TWS, snow depth, and snow mass (a.k.a. snow water equivalent). The data assimilation routine produces a conditioned (updated) estimate that is more accurate and contains less uncertainty during both the snow accumulation phase of the snow season as well as during the snow ablation season.

The Breathing Snowpack: Pressure-induced Vapor Flux of Temperate Snow

NASA Astrophysics Data System (ADS)

Drake, S. A.; Selker, J. S.; Higgins, C. W.

2017-12-01

As surface air pressure increases, hydrostatic compression of the air column forces atmospheric air into snowpack pore space. Likewise, as surface air pressure decreases, the atmospheric air column decompresses and saturated air exits the snow. Alternating influx and efflux of air can be thought of as a "breathing" process that produces an upward vapor flux when air above the snow is not saturated. The impact of pressure-induced vapor exchange is assumed to be small and is thus ignored in model parameterizations of surface processes over snow. Rationale for disregarding this process is that large amplitude pressure changes as caused by synoptic weather patterns are too infrequent to credibly impact vapor flux. The amplitude of high frequency pressure changes is assumed to be too small to affect vapor flux, however, the basis for this hypothesis relies on pressure measurements collected over an agricultural field (rather than snow). Resolution of the impact of pressure changes on vapor flux over seasonal cycles depends on an accurate representation of the magnitude of pressure changes caused by changes in wind as a function of the frequency of pressure changes. High precision in situ pressure measurements in a temperature snowpack allowed us to compute the spectra of pressure changes vs. wind forcing. Using a simplified model for vapor exchange we then computed the frequency of pressure changes that maximize vapor exchange. We examine and evaluate the seasonal impact of pressure-induced vapor exchange relative to other snow ablation processes.

The intraannual variability of land-atmosphere coupling over North America in the Canadian Regional Climate Model (CRCM5)

NASA Astrophysics Data System (ADS)

Yang Kam Wing, G.; Sushama, L.; Diro, G. T.

2016-12-01

This study investigates the intraannual variability of soil moisture-temperature coupling over North America. To this effect, coupled and uncoupled simulations are performed with the fifth-generation Canadian Regional Climate Model (CRCM5), driven by ERA-Interim. In coupled simulations, land and atmosphere interact freely; in uncoupled simulations, the interannual variability of soil moisture is suppressed by prescribing climatological values for soil liquid and frozen water contents. The study also explores projected changes to coupling by comparing coupled and uncoupled CRCM5 simulations for current (1981-2010) and future (2071-2100) periods, driven by the Canadian Earth System Model. Coupling differs for the northern and southern parts of North America. Over the southern half, it is persistent throughout the year while for the northern half, strongly coupled regions generally follow the freezing line during the cold months. Detailed analysis of the southern Canadian Prairies reveals seasonal differences in the underlying coupling mechanism. During spring and fall, as opposed to summer, the interactive soil moisture phase impacts the snow depth and surface albedo, which further impacts the surface energy budget and thus the surface air temperature; the air temperature then influences the snow depth in a feedback loop. Projected changes to coupling are also season specific: relatively drier soil conditions strengthen coupling during summer, while changes in soil moisture phase, snow depth, and cloud cover impact coupling during colder months. Furthermore, results demonstrate that soil moisture variability amplifies the frequency of temperature extremes over regions of strong coupling in current and future climates.

Site-level model intercomparison of high latitude and high altitude soil thermal dynamics in tundra and barren landscapes

NASA Astrophysics Data System (ADS)

Ekici, A.; Chadburn, S.; Chaudhary, N.; Hajdu, L. H.; Marmy, A.; Peng, S.; Boike, J.; Burke, E.; Friend, A. D.; Hauck, C.; Krinner, G.; Langer, M.; Miller, P. A.; Beer, C.

2015-07-01

Modeling soil thermal dynamics at high latitudes and altitudes requires representations of physical processes such as snow insulation, soil freezing and thawing and subsurface conditions like soil water/ice content and soil texture. We have compared six different land models: JSBACH, ORCHIDEE, JULES, COUP, HYBRID8 and LPJ-GUESS, at four different sites with distinct cold region landscape types, to identify the importance of physical processes in capturing observed temperature dynamics in soils. The sites include alpine, high Arctic, wet polygonal tundra and non-permafrost Arctic, thus showing how a range of models can represent distinct soil temperature regimes. For all sites, snow insulation is of major importance for estimating topsoil conditions. However, soil physics is essential for the subsoil temperature dynamics and thus the active layer thicknesses. This analysis shows that land models need more realistic surface processes, such as detailed snow dynamics and moss cover with changing thickness and wetness, along with better representations of subsoil thermal dynamics.

Snow cover retrieval over Rhone and Po river basins from MODIS optical satellite data (2000-2009).

NASA Astrophysics Data System (ADS)

Dedieu, Jean-Pierre, ,, Dr.; Boos, Alain; Kiage, Wiliam; Pellegrini, Matteo

2010-05-01

Estimation of the Snow Covered Area (SCA) is an important issue for meteorological application and hydrological modeling of runoff. With spectral bands in the visible, near and middle infrared, the MODIS optical satellite sensor can be used to detect snow cover because of large differences between reflectance from snow covered and snow free surfaces. At the same time, it allows separation between snow and clouds. Moreover, the sensor provides a daily coverage of large areas (2,500 km range). However, as the pixel size is 500m x 500m, a MODIS pixel may be partially covered by snow, particularly in Alpine areas, where snow may not be present in valleys lying at lower altitudes. Also, variation of reflectance due to differential sunlit effects as a function of slope and aspect, as well as bidirectional effects may be present in images. Nevertheless, it is possible to estimate snow cover at the Sub-Pixel level with a relatively good accuracy and with very good results if the sub-pixel estimations are integrated for a few pixels relative to an entire watershed. Integrated into the EU-FP7 ACQWA Project (www.acqwa.ch), this approach was first applied over Alpine area of Rhone river basin upper Geneva Lake: Canton du Valais, Switzerland (5 375 km²). In a second step over Alps, rolling hills and plain areas in Po catchment for Val d'Aosta and Piemonte regions, Italy (37 190 km²). Watershed boundaries were provided respectively by GRID (Ch) and ARPA (It) partners. The complete satellite images database was extracted from the U.S. MODIS/NASA website (http://modis.gsfc.nasa.gov/) for MOD09_B1 Reflectance images, and from the MODIS/NSIDC website (http://nsidc.org/index.html) for MOD10_A2 snow cover images. Only the Terra platform was used because images are acquired in the morning and are therefore better correlated with dry snow surface, avoiding cloud coverage of the afternoon (Aqua Platform). The MOD9 Image reflectance and MOD10_A2 products were respectively analyzed to retrieve (i) Fractional Snow cover at sub-pixel scale, and (ii) maximum snow cover. All products were retrieved at 8-days over a complete time period of 10 years (2000-2009), giving 500 images for each river basin. Digital Model Elevation was given by NASA/SRTM database at 90-m resolution and used (i) for illumination versus topography correction on snow cover, (ii) geometric rectification of images. Geographic projection is WGS84, UTM 32. Fractional Snow cover mapping was derived from the NDSI linear regression method (Salomonson et al., 2004). Cloud mask was given by MODIS-NASA library (radiometric threshold) and completed by inverse slope regression to avoid lowlands fog confusing with thin snow cover (Po river basin). Maximum Snow Cover mapping was retrieved from the NSIDC database classification (Hall et al., 2001). Validation step was processed using comparison between MODIS Snow maps outputs and meteorological data provided by network of 87 meteorological stations: temperature, precipitation, snow depth measurement. A 0.92 correlation was observed for snow/non snow cover and can be considered as quite satisfactory, given the radiometric problems encountered in mountainous areas, particularly in snowmelt season. The 10-years time period results indicates a main difference between (i) regular snow accumulation and depletion in Rhone and (ii) the high temporal and spatial variability of snow cover for Po. Then, a high sensitivity to low variation of air temperature, often close to 1° C was observed. This is the case in particular for the beginning and the end of the winter season. The regional snow cover depletion is both influenced by thermal positives anomalies (e.g. 2000 and 2006), and the general trend of rising atmospheric temperatures since the late 1980s, particularly for Po river basin. Results will be combined with two hydrological models: Topkapi and Fest.

10-Year Observations of Cloud and Surface Longwave Radiation at Ny-Ålesund, Svalbard

NASA Astrophysics Data System (ADS)

Yeo, H.; Kim, S. W.; Kim, B. M.; Kim, J. H.; Shiobara, M.; Choi, T. J.; Son, S. W.; Kim, M. H.; Jeong, J. H.; Kim, S. J.

2015-12-01

Arctic clouds play a key role in surface radiation budget and may influence sea ice and snow melting. In this study, 10-year (2004-2013) observations of cloud from Micro-Pulse Lidar (MPL) and surface longwave (LW) radiation at Ny-Ålesund, Svalbard are analyzed to investigate cloud radiative effect. The cloud fraction (CF) derived from MPL shows distinct monthly variation, having higher CF (0.90) in summer and lower CF (0.79) in winter. Downward longwave radiation (DLW) during wintertime (Nov., Dec., Jan., and Feb.) decreases as cloud base height (CBH) increases. The DLW for CBH < 1km (264.7±35.4 W m-2) is approximately 1.46 times larger than that for cloud-free (181.8±25.8 W m-2) conditions. The temperature difference (ΔT) and DLW difference (ΔDLW), which are calculated as the difference of monthly mean temperature and DLW between all-sky and cloud-free conditions, are positively correlated (R2 = 0.83). This implies that an increase of DLW may influence surface warming, which can result in snow and sea ice melting. However, dramatic changes in surface temperature, cloud and DLW are observed with a time scale of a few days. The averaged surface temperature on the presence of low-level clouds (CBH < 2km) and under cloud-free conditions are estimated to be -6.9±6.1°C and -14.5±5.7°C, respectively. The duration of low-level clouds, showing relatively high DLW and high surface temperature, is about 2.5 days. This suggests that DLW induced by low-level clouds may not have a critical effect on surface temperature rising and sea ice melting.

CO2 flux over young and snow-covered Arctic pack ice in winter and spring

NASA Astrophysics Data System (ADS)

Nomura, Daiki; Granskog, Mats A.; Fransson, Agneta; Chierici, Melissa; Silyakova, Anna; Ohshima, Kay I.; Cohen, Lana; Delille, Bruno; Hudson, Stephen R.; Dieckmann, Gerhard S.

2018-06-01

Rare CO2 flux measurements from Arctic pack ice show that two types of ice contribute to the release of CO2 from the ice to the atmosphere during winter and spring: young, thin ice with a thin layer of snow and older (several weeks), thicker ice with thick snow cover. Young, thin sea ice is characterized by high salinity and high porosity, and snow-covered thick ice remains relatively warm ( > -7.5 °C) due to the insulating snow cover despite air temperatures as low as -40 °C. Therefore, brine volume fractions of these two ice types are high enough to provide favorable conditions for gas exchange between sea ice and the atmosphere even in mid-winter. Although the potential CO2 flux from sea ice decreased due to the presence of the snow, the snow surface is still a CO2 source to the atmosphere for low snow density and thin snow conditions. We found that young sea ice that is formed in leads without snow cover produces CO2 fluxes an order of magnitude higher than those in snow-covered older ice (+1.0 ± 0.6 mmol C m-2 day-1 for young ice and +0.2 ± 0.2 mmol C m-2 day-1 for older ice).

EXTASE - An Experimental Thermal Probe For Applications In Snow Research And Earth Sciences

NASA Astrophysics Data System (ADS)

Schröer, K.; Seiferlin, K.; Marczewski, W.; Spohn, T.

EXTASE is a spin-off project from the Rosetta Lander (MUPUS) thermal probe, both funded by DLR. The application of this probe is to be tested in different fields e.g. in snow research, agriculture, permafrost etc. The probe penetrates the surface ca. 32 cm and provides a temperature profile (16 sensors) and thermal conductivity profile of the penetrated layer. The main advantages of the probe in comparison to common temperature profile measurement methods are: -no need to excavate material -minimized influence of the probe on the temperature field -minimized modification of the microstructure of the studied medium. Presently we are concentrating on agriculture (soil humidity) and snow research. Fur- ther applications could be: monitoring waste deposits and the heat set free by decom- position, volcanology and ground truth for remote sensing. We present the general concept of the probe, some temperature profiles measured during a field measurement campaign to demonstrate the capability of this new technique and first experiments made in the laboratory. First attempts to calculate thermal diffusivity and conductivity from the data are also given.

Separating local topography from snow effects on momentum roughness in mountain regions

NASA Astrophysics Data System (ADS)

Diebold, M.; Katul, G. G.; Calaf, M.; Lehning, M.; Parlange, M. B.

2013-12-01

Parametrization of momentum surface roughness length in mountainous regions continues to be an active research topic given its application to improved weather forecasting and sub-grid scale representation of mountainous regions in climate models. A field campaign was conducted in the Val Ferret watershed (Swiss Alps) to assess the role of topographic variability and snow cover on momentum roughness. To this end, turbulence measurements in a mountainous region with and without snow cover have been analyzed. A meteorological mast with four sonic anemometers together with temperature and humidity sensors was installed at an elevation of 2500 m and data were obtained from October 2011 until May 2012. Because of the long-term nature of these experiments, natural variability in mean wind direction allowed a wide range of terrain slopes and snow depths to be sampled. A theoretical framework that accounted only for topographically induced pressure perturbations in the mean momentum balance was used to diagnose the role of topography on the effective momentum roughness height as inferred from the log-law. Surface roughness depended systematically on wind direction but was not significantly influenced by the presence of snow depth variation. Moreover, the wind direction and so the surface roughness influenced the normalized turbulent kinetic energy, which in theory should not depend on these factors in the near-neutral atmospheric surface layer. The implications of those findings to modeling momentum roughness heights and turbulent kinetic energy (e.g. in conventional K-epsilon closure) in complex terrain are briefly discussed.

Satellite-observed snow cover variations over the Tibetan Plateau for the period 2001-2014

NASA Astrophysics Data System (ADS)

Long, D.; Chen, X.

2016-12-01

Snow is an integral component of the global climate system. Owing to its high albedo and thermal and water storage properties, snow has important linkages and feedbacks through its influence on surface energy and moisture fluxes, clouds, precipitation, hydrology, and atmospheric circulation. As the "Roof of the World" and the "Third Pole" with the highest mountains in middle latitudes, the Tibetan Plateau (TP) is one of the most hot spots in climate change and hydrological studies, in which seasonal snow cover is a critical aspect. Unlike large-scale snow cover and regional-scale glaciers over other cryospheric regions, changes in snow cover over the TP has been largely unknown due mostly to the quality of observations. Based on improved MODIS daily snow cover products, this study aims to quantify the distribution and changes in snow cover over the TP for the period 2001 to 2014. Results show that the spatial distribution of changes in snow cover fraction (SCF) over the 14-year study period exhibited a general negative trend over the TP driven primarily by increasing land surface temperature (LST), except some areas of the upper Golden-Sanded River and upper Brahmaputra River basins. However, decreased LST and increased precipitation in the accumulation season (September to the following February) resulted in increased SCF in the accumulation season, coinciding with large-scale cold snaps and heavy snowfall events at middle latitudes. Detailed analyses of the intra-annual variability of SCF in the TP regions show an increase in SCF in the accumulation season but a decrease in SCF in the melting season (March to August), indicating that the intra-annual amplitude of SCF increased during the study period and more snow cover was released as snowmelt in the spring season.

Influencing factors on the cooling effect of coarse blocky top-layers on relict rock glaciers

NASA Astrophysics Data System (ADS)

Pauritsch, Marcus; Wagner, Thomas; Mayaud, Cyril; Thalheim, Felix; Kellerer-Pirklbauer, Andreas; Winkler, Gerfried

2017-04-01

Coarse blocky material widely occurs in alpine landscapes particularly at the surface of bouldery rock glaciers. Such blocky layers are known to have a cooling effect on the subjacent material because of the enhanced non-conductive heat exchange with the atmosphere. This effect is used for instance by the construction of blocky embankments in the building of railways and roads in permafrost regions to prevent thawing processes. In alpine regions, this cooling effect may have a strong influence on the distribution and conservation of permafrost related to climate warming. The thermal regimes of the blocky surface layers of two comparable - in terms of size, elevation and geology - relict rock glaciers with opposing slope aspects are investigated. Therefore, the influence of the slope aspect-related climatic conditions (mainly the incident solar radiation, wind conditions and snow cover) on the cooling effect of the blocky layers is investigated. Air temperature, ground surface temperature and ground temperature at one meter depth were continuously measured over a period of four years at several locations at the NE-oriented Schöneben Rock Glacier and the adjacent SW-oriented Dürrtal Rock Glacier. At the former, additional data about wind speed and wind direction as well as precipitation are available, which are used to take wind-forced convection and snow cover into consideration. Statistical analyses of the data reveal that the blocky top layer of the Dürrtal Rock Glacier generally exhibits lower temperatures compared to the Schöneben Rock Glacier despite the more radiation-exposed aspect and the related higher solar radiation. However, the data show that the thermal regimes of the surface layers are highly heterogeneous and that data from the individual measurement sites have to be interpreted with caution. High Rayleigh numbers at both rock glaciers show that free convection occurs particularly during winter. Furthermore, wind-forced convection has a high impact on the thermal regime of the Schöneben Rock Glacier and, as the major wind direction, especially for higher wind speeds, is from west towards east, it is suspected that wind-forced convection is even more important at the Dürrtal Rock Glacier. The limited incident solar radiation at the Schöneben Rock Glacier results in a longer seasonal snow cover that appears earlier in autumn and can persist longer during the melting season. Moreover, with the predominant westerly wind, snow is supposedly transported from neighboring catchments (i.a. the Dürrtal Rock Glacier catchment) towards the Schöneben Rock Glacier catchment. Thus, in times with relatively cold air temperatures the coarse blocky surface at the Dürrtal Rock Glacier is better connected to the atmosphere than the more northern exposed Schöneben rock glacier because of the missing or only partial snow cover, which results in an enhanced cooling effect. It can be concluded that the cooling effect of coarse blocky debris is highly variable in alpine environments and can show considerable variations, depending on the heterogeneous structure of the layer itself and a complex interplay of slope aspect-related microclimatic effects such as incident solar radiation, predominant wind direction and snow cover dynamics.

Hydro-meteorological processes on the Qinghai - Tibet Plateau observed from space

NASA Astrophysics Data System (ADS)

Menenti, Massimo; Colin, Jerome; Jia, Li; D'Urso, Guido; Foken, Thomas; Immerzeel, Walter; Jha, Ramakar; Liu, Qinhuo; Liu, Changming; Ma, Yaoming; Sobrino, Jose Antonio; Yan, Guangjian; Pelgrum, Henk; Porcu, Federico; Wang, Jian; Wang, Jiemin; Shen, Xueshun; Su, Zhongbo; Ueno, Kenichi

2014-05-01

The Qinghai - Tibet Plateau is characterized by a significant intra-annual variability and spatial heterogeneity of surface conditions. Snow and vegetation cover, albedo, surface temperature and wetness change very significantly during the year and from place to place. The influence of temporal changes on convective events and the onset of the monsoon has been documented by ground based measurements of land - atmosphere exchanges of heat and water. The state of the land surface over the entire Plateau can be determined by space observation of surface albedo, temperature, snow and vegetation cover and soil moisture. Fully integrated use of satellite and ground observations is necessary to support water resources management in SE Asia and to clarify the roles of the interactions between the land surface and the atmosphere over the Tibetan Plateau in the Asian monsoon system. New or significantly improved algorithms have been developed and evaluated against ground measurements. Variables retrieved include land surface properties, rain rate, aerosol optical depth, water vapour, snow cover and water equivalent, soil moisture and lake level. The three years time series of gap-free daily and hourly evaporation derived from geostationary data collected by the FY-2D satellite was a major achievement. The hydrologic modeling system has been implemented and applied to the Qinghai Tibet Plateau and the headwaters of the major rivers in South and East Asia. Case studies on response of atmospheric circulation and specifically of convective activity to land surface conditions have been completed and the controlling land surface conditions and processes have been documented. Two new drought indicators have been developed: Normalized Temperature Anomaly Index (NTAI) and Normalized Vegetation Anomaly Index (NVAI). Case study in China and India showed that these indicators capture effectively drought severity and evolution. A new method has been developed for monitoring and early warning of flooded areas at the regional scale.

Improving Simulations of Precipitation Phase and Snowpack at a Site Subject to Cold Air Intrusions: Snoqualmie Pass, WA

NASA Astrophysics Data System (ADS)

Wayand, N. E.; Stimberis, J.; Zagrodnik, J.; Mass, C.; Lundquist, J. D.

2016-12-01

Low-level cold air from eastern Washington state often flows westward through mountain passes in the Washington Cascades, creating localized inversions and locally reducing climatological temperatures. The persistence of this inversion during a frontal passage can result in complex patterns of snow and rain that are difficult to predict. Yet, these predictions are critical to support highway avalanche control, ski resort operations, and modeling of headwater snowpack storage. In this study we used observations of precipitation phase from a disdrometer and snow depth sensors across Snoqualmie Pass, WA, to evaluate surface-air-temperature-based and mesoscale-model-based predictions of precipitation phase during the anomalously warm 2014-2015 winter. The skill of surface-based methods was greatly improved by using air temperature from a nearby higher-elevation station, which was less impacted by low-level inversions. Alternatively, we found a hybrid method that combines surface-based predictions with output from the Weather Research and Forecasting mesoscale model to have improved skill over both parent models. These results suggest that prediction of precipitation phase in mountain passes can be improved by incorporating observations or models from above the surface layer.

Snow-cover dynamics monitored by automatic digital photography at the rooting zone of an active rock glacier in the Hinteres Lantal Cirque, Austria

NASA Astrophysics Data System (ADS)

Kellerer-Pirklbauer, Andreas; Rieckh, Matthias; Avian, Michael

2010-05-01

Knowledge regarding snow-cover dynamics and climatic conditions in the rooting zone of active rock glaciers is still limited. The number of meteorological stations on the surface of or close to active rock glaciers is increasing. However, areal information on snow-cover distribution and its spatial dynamics caused by different processes on rock glaciers surfaces with a high temporal resolution from such remote alpine areas are mostly difficult to obtain. To face this problem an automatic remote digital camera (RDC) system was proprietary developed. The core parts of the RDC system are a standard hand-held digital camera, a remote control, a water proof casing with a transparent opening, a 12V/25Ah battery and solar panels with a charge controller. Three such devices were constructed and installed at different sites in the Central Alps of Austria. One RDC system is used to monitor the rooting zone of the highly active rock glacier in the Hinteres Langtal Cirque (46°59'N, 12°47'E), Central Schober Mountains, Austria. The 0.15 km² large NW-facing rock glaciers is tongue-shaped with a fast moving lower part (>1m/a) and a substantially slower upper part, ranging in elevation between 2455-2700 m a.s.l. The RDC system was set up in September 2006 and is located since than at 2770 m a.s.l. on a pronounced ridge crest that confines the Hinteres Langtal Cirque to the SW. The water proof casing was attached to a 1.5 m high metal pole which itself was fixed to the bedrock by screws and concrete glue. The viewing direction of the camera is NE. Hence, the image section of the RDC focuses on the rooting zone of the rock glacier and its headwalls up to c. 3000 m a.s.l. Photographs were taken daily at 3 pm providing the optimal lighting conditions in the relevant part of the cirque. 720 photographs were taken continuously in the period 12.09.2006 to 31.08.2008. These optical data were analysed by applying GIS and remote sensing techniques regarding snow-cover distribution, redistribution and duration in the foreground (i.e. ridge crest with cornice during winter) as well as in the background of the image section (i.e. the rooting zone of the rock glacier and headwalls). Snow was present on 75% of the photographs (used for further analysis) whereas on 25% of the photographs snow was absent also indicating the absence of perennial snow patches in the rooting zone. The results of the snow-cover analysis were combined with (a) climatic data - air temperature, air humidity, wind speed, wind direction and global radiation - from our meteorological station next to the rock glacier as well as with (b) ground surface and near ground surface temperature data recorded by miniature temperature dataloggers (MTD) at several sites in the cirque within and near the RDC image section. Results of detected relationships between different snow-cover and climatic parameters will be presented.

Impacts of absorbing aerosol deposition on snowpack and hydrologic cycle in the Rocky Mountain region based on variable-resolution CESM (VR-CESM) simulations

NASA Astrophysics Data System (ADS)

Wu, Chenglai; Liu, Xiaohong; Lin, Zhaohui; Rahimi-Esfarjani, Stefan R.; Lu, Zheng

2018-01-01

The deposition of light-absorbing aerosols (LAAs), such as black carbon (BC) and dust, onto snow cover has been suggested to reduce the snow albedo and modulate the snowpack and consequent hydrologic cycle. In this study we use the variable-resolution Community Earth System Model (VR-CESM) with a regionally refined high-resolution (0.125°) grid to quantify the impacts of LAAs in snow in the Rocky Mountain region during the period 1981-2005. We first evaluate the model simulation of LAA concentrations both near the surface and in snow and then investigate the snowpack and runoff changes induced by LAAs in snow. The model simulates similar magnitudes of near-surface atmospheric dust concentrations as observations in the Rocky Mountain region. Although the model underestimates near-surface atmospheric BC concentrations, the model overestimates BC-in-snow concentrations by 35 % on average. The regional mean surface radiative effect (SRE) due to LAAs in snow reaches up to 0.6-1.7 W m-2 in spring, and dust contributes to about 21-42 % of total SRE. Due to positive snow albedo feedbacks induced by the LAA SRE, snow water equivalent is reduced by 2-50 mm and snow cover fraction by 5-20 % in the two regions around the mountains (eastern Snake River Plain and southwestern Wyoming), corresponding to an increase in surface air temperature by 0.9-1.1 °C. During the snow melting period, LAAs accelerate the hydrologic cycle with monthly runoff increases of 0.15-1.00 mm day-1 in April-May and reductions of 0.04-0.18 mm day-1 in June-July in the mountainous regions. Of all the mountainous regions, the Southern Rockies experience the largest reduction of total runoff by 15 % during the later stage of snowmelt (i.e., June and July). Compared to previous studies based on field observations, our estimation of dust-induced SRE is generally 1 order of magnitude smaller in the Southern Rockies, which is ascribed to the omission of larger dust particles (with the diameter > 10 µm) in the model. This calls for the inclusion of larger dust particles in the model to reduce the discrepancies. Overall these results highlight the potentially important role of LAA interactions with snowpack and the subsequent impacts on the hydrologic cycles across the Rocky Mountains.

Influence of projected snow and sea-ice changes on future climate in heavy snowfall region

NASA Astrophysics Data System (ADS)

Matsumura, S.; Sato, T.

2011-12-01

Snow/ice albedo and cloud feedbacks are critical for climate change projection in cryosphere regions. However, future snow and sea-ice distributions are significantly different in each GCM. Thus, surface albedo in cryosphere regions is one of the causes of the uncertainty for climate change projection. Northern Japan is one of the heaviest snowfall regions in the world. In particular, Hokkaido is bounded on the north by the Okhotsk Sea, where is the southernmost ocean in the Northern Hemisphere that is covered with sea ice during winter. Wintertime climate around Hokkaido is highly sensitive to fluctuations in snow and sea-ice. The purpose of this study is to evaluate the influence of global warming on future climate around Hokkaido, using the Pseudo-Global-Warming method (PGW) by a regional climate model. The boundary conditions of the PGW run were obtained by adding the difference between the future (2090s) and past (1990s) climates simulated by coupled general circulation model (MIROC3.2 medres), which is from the CMIP3 multi-model dataset, into the 6-hourly NCEP reanalysis (R-2) and daily OISST data in the past climate (CTL) run. The PGW experiments show that snow depth significantly decreases over mountainous areas and snow cover mainly decreases over plain areas, contributing to higher surface warming due to the decreased snow albedo. Despite the snow reductions, precipitation mainly increases over the mountainous areas because of enhanced water vapor content. However, precipitation decreases over the Japan Sea and the coastal areas, indicating the weakening of a convergent cloud band, which is formed by convergence between cold northwesteries from the Eurasian continent and anticyclonic circulation over the Okhotsk Sea. These results suggest that Okhotsk sea-ice decline may change the atmospheric circulation and the resulting effect on cloud formation, resulting in changes in winter snow or precipitation. We will also examine another CMIP3 model (MRI-CGCM2.3.2), which sensitivity of surface albedo to surface air temperature is the lowest in the CMIP3 models.

The impact of boundary layer turbulence on snow growth and precipitation: Idealized Large Eddy Simulations

NASA Astrophysics Data System (ADS)

Chu, Xia; Xue, Lulin; Geerts, Bart; Kosović, Branko

2018-05-01

Ice particles and supercooled droplets often co-exist in planetary boundary-layer (PBL) clouds. The question examined in this numerical study is how large turbulent PBL eddies affect snow growth and surface precipitation from mixed-phase PBL clouds. In order to simplify this question, this study assumes an idealized BL with well-developed turbulence but no surface heat fluxes or radiative heat exchanges. Large Eddy Simulations with and without resolved PBL turbulence are compared. This comparison demonstrates that the impact on snow growth in mixed-phase clouds is controlled by two opposing mechanisms, a microphysical and a dynamical one. The cloud microphysical impact of large turbulent eddies is based on the difference in saturation vapor pressure over water and over ice. The net outcome of alternating turbulent up- and downdrafts is snow growth by diffusion and/or accretion (riming). On the other hand, turbulence-induced entrainment and detrainment may suppress snow growth. In the case presented herein, the net effect of these microphysical and dynamical processes is positive, but in general the net effect depends on ambient conditions, in particular the profiles of temperature, humidity, and wind.

A tentative record of the last 1,000 years of Greenland temperature from occluded air in the GISP2 ice core

NASA Astrophysics Data System (ADS)

Kobashi, T.; Severinghaus, J. P.; Barnola, J.; Kawamura, K.; Beaudette, R.

2005-12-01

Ice borehole temperature inversion has been used to reconstruct Greenland surface temperature during the last millennium (Dahl-Jensen et al, Science, 1998). However, this technique does not preserve high frequencies because of diffusion of heat in the ice. Here, we present a tentative reconstruction of the past 1,000 years of central Greenland temperature using nitrogen and argon isotopes from occluded air in the GISP2 ice core. This technique preserves decadal-to-centennial-scale temperature variations and complements the borehole technique. Nitrogen and argon isotopes in the porous snow layer (~80m) experience two isotopic fractionations by gravitation and temperature gradients (ΔT) between the top and bottom of the snow layer. The simultaneous analysis of argon and nitrogen isotopes allows us to separate these two effects, and obtain a history of ΔT in the layer. To a first approximation, ΔT change on decadal to centennial time scales is a surface temperature history because the heat conductivity of snow is much smaller than that of ice, and the heat capacity of the ice sheet is quite large. The preliminary ΔT history (20-year interval) shows a Medieval Warm Period in the 11th to 12th centuries and the Little Ice Age in the 15th to 19th centuries. Furthermore, the record shows a clear similarity with the Be-10 record (a proxy for solar activity) with Wolf, Sporer, Maunder, and Dalton minima clearly seen in the cold periods. This finding is consistent with the hypothesis that solar activity influenced Greenland temperature during the past 1000 years.

Remote sensing as a research tool. [sea ice surveillance from aircraft and spacecraft

NASA Technical Reports Server (NTRS)

Carsey, F. D.; Zwally, H. J.

1986-01-01

The application of aircraft and spacecraft remote sensing techniques to sea ice surveillance is evaluated. The effects of ice in the air-sea-ice system are examined. The measurement principles and characteristics of remote sensing methods for aircraft and spacecraft surveillance of sea ice are described. Consideration is given to ambient visible light, IR, passive microwave, active microwave, and laser altimeter and sonar systems. The applications of these systems to sea ice surveillance are discussed and examples are provided. Particular attention is placed on the use of microwave data and the relation between ice thickness and sea ice interactions. It is noted that spacecraft and aircraft sensing techniques can successfully measure snow cover; ice thickness; ice type; ice concentration; ice velocity field; ocean temperature; surface wind vector field; and air, snow, and ice surface temperatures.

Near-surface temperature inversion during summer at Summit, Greenland, and its relation to MODIS-derived surface temperatures

NASA Astrophysics Data System (ADS)

Adolph, Alden C.; Albert, Mary R.; Hall, Dorothy K.

2018-03-01

As rapid warming of the Arctic occurs, it is imperative that climate indicators such as temperature be monitored over large areas to understand and predict the effects of climate changes. Temperatures are traditionally tracked using in situ 2 m air temperatures and can also be assessed using remote sensing techniques. Remote sensing is especially valuable over the Greenland Ice Sheet, where few ground-based air temperature measurements exist. Because of the presence of surface-based temperature inversions in ice-covered areas, differences between 2 m air temperature and the temperature of the actual snow surface (referred to as skin temperature) can be significant and are particularly relevant when considering validation and application of remote sensing temperature data. We present results from a field campaign extending from 8 June to 18 July 2015, near Summit Station in Greenland, to study surface temperature using the following measurements: skin temperature measured by an infrared (IR) sensor, 2 m air temperature measured by a National Oceanic and Atmospheric Administration (NOAA) meteorological station, and a Moderate Resolution Imaging Spectroradiometer (MODIS) surface temperature product. Our data indicate that 2 m air temperature is often significantly higher than snow skin temperature measured in situ, and this finding may account for apparent biases in previous studies of MODIS products that used 2 m air temperature for validation. This inversion is present during our study period when incoming solar radiation and wind speed are both low. As compared to our in situ IR skin temperature measurements, after additional cloud masking, the MOD/MYD11 Collection 6 surface temperature standard product has an RMSE of 1.0 °C and a mean bias of -0.4 °C, spanning a range of temperatures from -35 to -5 °C (RMSE = 1.6 °C and mean bias = -0.7 °C prior to cloud masking). For our study area and time series, MODIS surface temperature products agree with skin surface temperatures better than previous studies indicated, especially at temperatures below -20 °C, where other studies found a significant cold bias. We show that the apparent cold bias present in other comparisons of 2 m air temperature and MODIS surface temperature may be a result of the near-surface temperature inversion. Further investigation of how in situ IR skin temperatures compare to MODIS surface temperature at lower temperatures (below -35 °C) is warranted to determine whether a cold bias exists for those temperatures.

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 combination of in-situ field data and satellite information allows an estimation of the water volume that is stored in the form of snow on Mount Aragatz. Using numerical modelling, we extend these results to other years, and calculate past and future water yields from snow melt from Mount Aragatz. This study is performed in the frame of the Armenian-Swiss project "Freezwater" that aims at an artificial managing of snow melting to better time the release of melt water at low cost. In the past few years, an artificial glacier was built up successfully, and geotextiles were used to reduce the melt rates of snow cornices. In order to estimate the efficiency of geotextiles in delaying the melt-down, ablation rates of protected snow surfaces were compared to those of uncovered areas. This study will contribute to the understanding of aeolian processes within the cryosphere as well as it will help to gain engineering knowledge concerning a new and efficient water storage technique.

Comparison of Satellite-Derived and In-Situ Observations of Ice and Snow Surface Temperatures over Greenland

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Box, Jason E.; Casey, Kimberly A.; Hook, Simon J.; Shuman, Christopher A.; Steffen, Konrad

2008-01-01

The most practical way to get a spatially broad and continuous measurements of the surface temperature in the data-sparse cryosphere is by satellite remote sensing. The uncertainties in satellite-derived LSTs must be understood to develop internally-consistent decade-scale land-surface temperature (LST) records needed for climate studies. In this work we assess satellite-derived "clear-sky" LST products from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), and LSTs derived from the Enhanced Thematic Mapper Plus (ETM+) over snow and ice on Greenland. When possible, we compare satellite-derived LSTs with in-situ air-temperature observations from Greenland Climate Network (GC-Net) automatic-weather stations (AWS). We find that MODIS, ASTER and ETM+ provide reliable and consistent LSTs under clear-sky conditions and relatively-flat terrain over snow and ice targets over a range of temperatures from -40 to 0 C. The satellite-derived LSTs agree within a relative RMS uncertainty of approx.0.5 C. The good agreement among the LSTs derived from the various satellite instruments is especially notable since different spectral channels and different retrieval algorithms are used to calculate LST from the raw satellite data. The AWS record in-situ data at a "point" while the satellite instruments record data over an area varying in size from: 57 X 57 m (ETM+), 90 X 90 m (ASTER), or to 1 X 1 km (MODIS). Surface topography and other factors contribute to variability of LST within a pixel, thus the AWS measurements may not be representative of the LST of the pixel. Without more information on the local spatial patterns of LST, the AWS LST cannot be considered valid ground truth for the satellite measurements, with RMS uncertainty approx.2 C. Despite the relatively large AWS-derived uncertainty, we find LST data are characterized by high accuracy but have uncertain absolute precision.

Downscaling of snow depth and river discharge in Japan by the Pseudo-Global-Warming Method

NASA Astrophysics Data System (ADS)

Kimura, F.; Ma, X.; Hara, M.; Advanced Atmosphere-Ocean-Land Modeling Program

2010-12-01

Although a heavy snowfall often brings disaster, snow cover is one of the major water resources in Japan. Even during the winter, the monthly mean of the surface air temperature often exceeds 0 deg. in large parts of the heavy snow areas along the Sea of Japan. Thus, snow cover may be seriously reduced in these areas as a result of global warming, which is caused by an increase in greenhouse gases. This study estimates the impact of global warming on the snow depth in Japan during early winter. Some dynamical downscaling experiments are conducted by the Pseudo-Global-Warming method for the future projection of snow cover. By the hindcast runs, precipitation, snow depth, and surface air temperature show good agreement with the AMeDAS station data observed in a High-Snow-Cover (HSC) year and a Low-Snow-Cover (LSC) yea. Pseudo-Global-Warming runs for these years indicate that the decreasing ratios of the snow water are more significant in the areas whose altitude is less than 1500 m. The increase of the air temperature is one of the major factors for the decrease in snow water, since the present mean air temperature in most of these areas is near 0 deg. even in winter. On the other hand, the change in the aerial-mean precipitation due to global warming is less than 15% in both years. To evaluate the impact of the reduction of snow cover to water resource, a hydrological simulation is also made for the Agano River basin, which locates in Niigata and Fukushima Prefectures. The Agano River drains into the Sea of Japan and is the second largest river in Japan with annual discharge of about 12.9 billion m3. A hind cast experiment is carried out for the two decades from 1980 to 1999. The average correlation coefficient of 0.79 for the monthly mean discharge in the winter season indicates that the interannual variation of the river discharge could be reproduced and that the method is useful for climate change study. Then the hydrological response to the future global warming in the 2070s is investigated. Assuming the reference present climate period of 1990s, the monthly mean discharge for the 2070s is projected to increase by approximately 43% in January and 55% in February, but to decrease by approximately 38% in April and 32% in May. The flood peak in the hydrograph will shift to approximately one month earlier, i.e., from April in the 1990s to March in the 2070s. Furthermore, the 10-year average of snowfall amount is projected to be approximately 49.5% lower in the 2070s than that in the 1990s. Acknowledgment: This work was supported by the Global Environment Research Fund (S-5-3) of the Ministry of the Environment, Japan. References 1. Ma, X., T. Yoshikane, M. Hara, Y. Wakazuki, H. G Takahashi, and F. Kimura, 2010: Hydrological response to future climate change in the Agano River basin, Japan, Hydrological Research Letters, 4, 25-29 2. Hara,M., T.Yoshikane, H.Kawase and F.Kimura 2008:Impact of the Estimation of Global Warming on Snow Depth in Japan by the Pseudo-Global-Warming Method. Hydrological Research Letters 2 61-64.

Percentage Contributions from Atmospheric and Surface Features to Computed Brightness Temperatures

NASA Technical Reports Server (NTRS)

Jackson, Gail Skofronick

2006-01-01

Over the past few years, there has become an increasing interest in the use of millimeter-wave (mm-wave) and sub-millimeter-wave (submm-wave) radiometer observations to investigate the properties of ice particles in clouds. Passive radiometric channels respond to both the integrated particle mass throughout the volume and field of view, and to the amount, location, and size distribution of the frozen (and liquid) particles with the sensitivity varying for different frequencies and hydrometeor types. One methodology used since the 1960's to discern the relationship between the physical state observed and the brightness temperature (TB) is through the temperature weighting function profile. In this research, the temperature weighting function concept is exploited to analyze the sensitivity of various characteristics of the cloud profile, such as relative humidity, ice water path, liquid water path, and surface emissivity. In our numerical analysis, we compute the contribution (in Kelvin) from each of these cloud and surface characteristics, so that the sum of these various parts equals the computed TB. Furthermore, the percentage contribution from each of these characteristics is assessed. There is some intermingling/contamination of the contributions from various components due to the integrated nature of passive observations and the absorption and scattering between the vertical layers, but all in all the knowledge gained is useful. This investigation probes the sensitivity over several cloud classifications, such as cirrus, blizzards, light snow, anvil clouds, and heavy rain. The focus is on mm-wave and submm-wave frequencies, however discussions of the effects of cloud variations to frequencies as low as 10 GHz and up to 874 GHz will also be presented. The results show that nearly 60% of the TB value at 89 GHz comes from the earth's surface for even the heaviest blizzard snow rates. On the other hand, a significant percentage of the TB value comes from the snow in the cloud for 166, and 183 plus or minus 7 GHz for the heavy and medium snow rates. For submm-wave channels, there is no contribution from the surface because these channels cannot probe through clouds, nor normal water vapor amounts in clear air regions. This work is extremely valuable in physically-based retrieval algorithm development research.

The application of Heat Capacity Mapping Mission (HCMM) thermal data to snow hydrology. [Salt Verde Watershed and the southern Sierra Nevada

NASA Technical Reports Server (NTRS)

Barnes, J. C. (Principal Investigator); Bowley, C. J.; Smallwood, M. D.; Willand, J. H.

1981-01-01

The application of HCMM thermal infrared data to snow hydrology and the prediction of snowmelt runoff was evaluated. Data for the Salt Verde watershed in central Arizona and the southern Sierra Nevada in California were analyzed and compared to LANDSAT and NOAA satellite data, U-2 thermal data, and other correlative data. It was determined that HCMM thermal imagery provides data as accurate for snow mapping as does visible imagery, and that in comparison with the reslution of other satellite imagery, it may be the most useful. Data from the HCMM thermal channel, with careful calibration, provides useful snow surface temperature data for hydrological purposes. An approach to an automated method of analysis is presented.

Water, ice, and meteorological measurements at South Cascade Glacier, Washington, 1986-1991 balance years

USGS Publications Warehouse

Krimmel, Robert M.

2000-01-01

Mass balance and climate variables are reported for South Cascade Glacier, Washington, for the years 1986-91. These variables include air temperature, precipitation, water runoff, snow accumulation, snow and ice melt terminus position, surface level, and ice speed. Data are reduced to daily and monthly values where appropriate. The glacier-averaged values of spring snow accumulation and fall net balance given in this report differ from previous results because amore complete analysis is made. Snow accumulation values for the1986-91 period ranged from 3.54 (water equivalent) meters in 1991 to2.04 meters in 1987. Net balance values ranged from 0.07 meters in1991 to -2.06 meters in 1987. The glacier became much smaller during the 1986-91 period and retreated a cumulative 50 meters.

Surface and Atmospheric Contributions to Passive Microwave Brightness Temperatures

NASA Technical Reports Server (NTRS)

Jackson, Gail Skofronick; Johnson, Benjamin T.

2010-01-01

Physically-based passive microwave precipitation retrieval algorithms require a set of relationships between satellite observed brightness temperatures (TB) and the physical state of the underlying atmosphere and surface. These relationships are typically non-linear, such that inversions are ill-posed especially over variable land surfaces. In order to better understand these relationships, this work presents a theoretical analysis using brightness temperature weighting functions to quantify the percentage of the TB resulting from absorption/emission/reflection from the surface, absorption/emission/scattering by liquid and frozen hydrometeors in the cloud, the emission from atmospheric water vapor, and other contributors. The results are presented for frequencies from 10 to 874 GHz and for several individual precipitation profiles as well as for three cloud resolving model simulations of falling snow. As expected, low frequency channels (<89 GHz) respond to liquid hydrometeors and the surface, while the higher frequency channels become increasingly sensitive to ice hydrometeors and the water vapor sounding channels react to water vapor in the atmosphere. Low emissivity surfaces (water and snow-covered land) permit energy downwelling from clouds to be reflected at the surface thereby increasing the percentage of the TB resulting from the hydrometeors. The slant path at a 53deg viewing angle increases the hydrometeor contributions relative to nadir viewing channels and show sensitivity to surface polarization effects. The TB percentage information presented in this paper answers questions about the relative contributions to the brightness temperatures and provides a key piece of information required to develop and improve precipitation retrievals over land surfaces.

Comparison of AMSR-E and SSM/I snow parameter retrievals over the Ob river basin

USGS Publications Warehouse

Mognard, N.M.; Grippa, M.; LeToan, T.; Kelly, R.E.J.; Chang, A.T.C.; Josberger, E.G.

2004-01-01

Passive microwave observations from the Advanced Microwave Scanning Radiometer - EOS (AMSR-E) and from the Special Sensor Microwave Imager (SSM/I) are used to analyse the evolution of the snow pack in the Ob river basin during the snow season of 2002-03. The Ob river is the biggest Russian river with respect to its watershed area (2 975 000 km2). The Ob originates in the Altai mountains and flows northward across the vast West Siberian lowland towards the Arctic Ocean. The majority of snow cover is contained in the lowlands rather than in mountainous regions and persists for six months or more. During the snow season, surface air temperatures are very cold. Therefore, the combination of cold dry snow and large areas of uniform topography is ideal for snowpack extent and water equivalent retrievals from passive microwave observations. The thermal gradient through the snow pack is estimated and used to model the growth of the snow grain size and to compute the evolution of the passive microwave derived snow depth over the region. A comparison between the AMSR-E and SSM/I estimates is performed and the differences between the snow parameters from the two satellite instruments are analysed.

Modelling the influence of elevation and snow regime on winter stream temperature in the rain-on-snow zone

NASA Astrophysics Data System (ADS)

Leach, J.; Moore, D.

2015-12-01

Winter stream temperature of coastal mountain catchments influences fish growth and development. Transient snow cover and advection associated with lateral throughflow inputs are dominant controls on stream thermal regimes in these regions. Existing stream temperature models lack the ability to properly simulate these processes. Therefore, we developed and evaluated a conceptual-parametric catchment-scale stream temperature model that includes the role of transient snow cover and lateral advection associated with throughflow. The model provided reasonable estimates of observed stream temperature at three test catchments. We used the model to simulate winter stream temperature for virtual catchments located at different elevations within the rain-on-snow zone. The modelling exercise examined stream temperature response associated with interactions between elevation, snow regime, and changes in air temperature. Modelling results highlight that the sensitivity of winter stream temperature response to changes in climate may be dependent on catchment elevation and landscape position.

Uncertainty in solid precipitation and snow depth prediction for Siberia using the Noah and Noah-MP land surface models

NASA Astrophysics Data System (ADS)

Suzuki, Kazuyoshi; Zupanski, Milija

2018-01-01

In this study, we investigate the uncertainties associated with land surface processes in an ensemble predication context. Specifically, we compare the uncertainties produced by a coupled atmosphere-land modeling system with two different land surface models, the Noah- MP land surface model (LSM) and the Noah LSM, by using the Maximum Likelihood Ensemble Filter (MLEF) data assimilation system as a platform for ensemble prediction. We carried out 24-hour prediction simulations in Siberia with 32 ensemble members beginning at 00:00 UTC on 5 March 2013. We then compared the model prediction uncertainty of snow depth and solid precipitation with observation-based research products and evaluated the standard deviation of the ensemble spread. The prediction skill and ensemble spread exhibited high positive correlation for both LSMs, indicating a realistic uncertainty estimation. The inclusion of a multiple snowlayer model in the Noah-MP LSM was beneficial for reducing the uncertainties of snow depth and snow depth change compared to the Noah LSM, but the uncertainty in daily solid precipitation showed minimal difference between the two LSMs. The impact of LSM choice in reducing temperature uncertainty was limited to surface layers of the atmosphere. In summary, we found that the more sophisticated Noah-MP LSM reduces uncertainties associated with land surface processes compared to the Noah LSM. Thus, using prediction models with improved skill implies improved predictability and greater certainty of prediction.

Validation of EOS Aqua AMSR Sea Ice Products for East Antarctica

NASA Technical Reports Server (NTRS)

Massom, Rob; Lytle, Vicky; Allison, Ian; Worby, Tony; Markus, Thorsten; Scambos, Ted; Haran, Terry; Enomoto, Hiro; Tateyama, Kazu; Pfaffling, Andi

2004-01-01

This paper presents results from AMSR-E validation activities during a collaborative international cruise onboard the RV Aurora Australis to the East Antarctic sea ice zone (64-65 deg.S, 110-120 deg.E) in the early Austral spring of 2003. The validation strategy entailed an IS-day survey of the statistical characteristics of sea ice and snowcover over a Lagrangian grid 100 x 50 km in size (demarcated by 9 drifting ice beacons) i.e. at a scale representative of Ah4SR pixels. Ice conditions ranged h m consolidated first-year ice to a large polynya offshore from Casey Base. Data sets collected include: snow depth and snow-ice interface temperatures on 24 (?) randomly-selected floes in grid cells within a 10 x 50 km area (using helicopters); detailed snow and ice measurements at 13 dedicated ice stations, one of which lasted for 4 days; time-series measurements of snow temperature and thickness at selected sites; 8 aerial photography and thermal-IR radiometer flights; other satellite products (SAR, AVHRR, MODIS, MISR, ASTER and Envisat MERIS); ice drift data; and ancillary meteorological (ship-based, meteorological buoys, twice-daily radiosondes). These data are applied to a validation of standard AMSR-E ice concentration, snowcover thickness and ice-temperature products. In addition, a validation is carried out of ice-surface skin temperature products h m the NOAA AVHRR and EOS MODIS datasets.

A passive microwave snow depth algorithm with a proxy for snow metamorphism

USGS Publications Warehouse

Josberger, E.G.; Mognard, N.M.

2002-01-01

Passive microwave brightness temperatures of snowpacks depend not only on the snow depth, but also on the internal snowpack properties, particularly the grain size, which changes through the winter. Algorithms that assume a constant grain size can yield erroneous estimates of snow depth or water equivalent. For snowpacks that are subject to temperatures well below freezing, the bulk temperature gradient through the snowpack controls the metamorphosis of the snow grains. This study used National Weather Service (NWS) station measurements of snow depth and air temperature from the Northern US Great Plains to determine temporal and spatial variability of the snow depth and bulk snowpack temperature gradient. This region is well suited for this study because it consists primarily of open farmland or prairie, has little relief, is subject to very cold temperatures, and has more than 280 reporting stations. A geostatistical technique called Kriging was used to grid the randomly spaced snow depth measurements. The resulting snow depth maps were then compared with the passive microwave observations from the Special Sensor Microwave Imager (SSM/I). Two snow seasons were examined: 1988-89, a typical snow year, and 1996-97, a record year for snow that was responsible for extensive flooding in the Red River Basin. Inspection of the time series of snow depth and microwave spectral gradient (the difference between the 19 and 37 GHz bands) showed that while the snowpack was constant, the spectral gradient continued to increase. However, there was a strong correlation (0.6 < R2 < 0.9) between the spectral gradient and the cumulative bulk temperature gradient through the snowpack (TGI). Hence, TGI is an index of grain size metamorphism that has occurred within the snowpack. TGI time series from 21 representative sites across the region and the corresponding SSM/I observations were used to develop an algorithm for snow depth that requires daily air temperatures. Copyright ?? 2002 John Wiley & Sons, Ltd.

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

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

Wu, Longtao; Gu, Yu; Jiang, Jonathan H.

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

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

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

Wu, Longtao; Gu, Yu; Jiang, Jonathan H.

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

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

NASA Astrophysics Data System (ADS)

Wu, Longtao; Gu, Yu; Jiang, Jonathan H.; Su, Hui; Yu, Nanpeng; Zhao, Chun; Qian, Yun; Zhao, Bin; Liou, Kuo-Nan; Choi, Yong-Sang

2018-04-01

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

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

DOE PAGES

Wu, Longtao; Gu, Yu; Jiang, Jonathan H.; ...

2018-04-23

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

Impact of the springtime Himalayan-Tibetan Plateau on the onset on the Indian summer monsoon in coupled forecasts

NASA Astrophysics Data System (ADS)

Orsolini, Yvan; Senan, Retish; Weisheimer, Antje; Vitart, Frederic; Balsamo, Gianpaolo; Doblas-Reyes, Francisco; Stockdale, Timothy; Dutra, Emanuel

2016-04-01

The springtime snowpack over the Himalayan-Tibetan Plateau (HTP) region has long been suggested to be an influential factor on the onset of the Indian summer monsoon. In the frame of the SPECS project, we have assessed the impact of realistic snow initialization in springtime over HTP on the onset of the Indian summer monsoon. We examine a suite of coupled ocean-atmosphere 4-month ensemble reforecasts made at the European Centre for Medium-Range Weather Forecasts (ECMWF), using the Seasonal Forecasting System 4. The reforecasts were initialized on 1 April every year for the period 1981-2010. In these seasonal reforecasts, the snow is initialized "realistically" with ERA-Interim/Land Reanalysis. In addition, we carried out an additional set of forecasts, identical in all aspects except that initial conditions for snow-related land surface variables over the HTP region are randomized. We show that high snow depth over HTP influences the meridional tropospheric temperature gradient reversal that marks the monsoon onset. Composite difference based on a normalized HTP snow index reveal that, in high snow years, (i) the onset is delayed by about 8 days, and (ii) negative precipitation anomalies and warm surface conditions prevail over India. We show that about half of this delay can be attributed to the realistic initialization of snow over the HTP region. We further demonstrate that high April snow depths over HTP are not uniquely influenced by either the El Nino-Southern Oscillation, the Indian Ocean Dipole or the North Atlantic Oscillation.

Daytime Cloud Property Retrievals Over the Arctic from Multispectral MODIS Data

NASA Technical Reports Server (NTRS)

Spangenberg, Douglas A.; Trepte, Qing; Minnis, Patrick; Uttal, Taneil

2004-01-01

Improving climate model predictions over Earth's polar regions requires a complete understanding of polar clouds properties. Passive satellite remote sensing techniques can be used to retrieve macro and microphysical properties of polar cloud systems. However, over the Arctic, there is minimal contrast between clouds and the background snow surface observed in satellite data, especially for visible wavelengths. This makes it difficult to identify clouds and retrieve their properties from space. Variable snow and ice cover, temperature inversions, and the predominance of mixed-phase clouds further complicate cloud property identification. For this study, the operational Clouds and the Earth s Radiant Energy System (CERES) cloud mask is first used to discriminate clouds from the background surface in Terra Moderate Resolution Imaging Spectroradiometer (MODIS) data. A solar-infrared infrared nearinfrared technique (SINT) first used by Platnick et al. (2001) is used here to retrieve cloud properties over snow and ice covered regions.

Comparison of snow depth retrieval algorithm in Northeastern China based on AMSR2 and FY3B-MWRI data

NASA Astrophysics Data System (ADS)

Fan, Xintong; Gu, Lingjia; Ren, Ruizhi; Zhou, Tingting

2017-09-01

Snow accumulation has a very important influence on the natural environment and human activities. Meanwhile, improving the estimation accuracy of passive microwave snow depth (SD) retrieval is a hotspot currently. Northeastern China is a typical snow study area including many different land cover types, such as forest, grassland and farmland. Especially, there is relatively stable snow accumulation in January every year. The brightness temperatures which are observed by the Advanced Microwave Scanning Radiometer 2 (AMSR2) on GCOM-W1 and FengYun3B Microwave Radiation Imager (FY3B-MWRI) in the same period in 2013 are selected as the study data in the research. The results of snow depth retrieval using AMSR2 standard algorithm and Jiang's FY operational algorithm are compared in the research. Moreover, to validate the accuracy of the two algorithms, the retrieval results are compared with the SD data observed at the national meteorological stations in Northeastern China. Furthermore, the retrieval SD is also compared with AMSR2 and FY standard SD products, respectively. The root mean square errors (RMSE) results using AMSR2 standard algorithms and FY operational algorithm are close in the forest surface, which are 6.33cm and 6.28cm, respectively. However, The FY operational algorithm shows a better result than the AMSR2 standard algorithms in the grassland and farmland surface. The RMSE results using FY operational algorithm in the grassland and farmland surface are 2.44cm and 6.13cm, respectively.

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 protection for mid-elevation (approx. 1500 m a.s.l.) Alpine climates and can be managed with reasonable effort.

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, relative air humidity, precipitation and incident solar radiation) to provide a complete estimate of snowpack state. The implementation of a DA scheme enables to assimilate simultaneously ground-based observations of different snow-related variables (snow depth, snow density, surface temperature and albedo). SMASH performances are evaluated by using observed data supplied by meteorological stations located in three experimental Alpine sites: Col de Porte (1325 m, France); Torgnon (2160 m, Italy); Weissfluhjoch (2540 m, Switzerland). A comparison analysis between the resulting performaces of Particle Filter and Ensemble Kalman Filter schemes is shown.

A satellite snow depth multi-year average derived from SSM/I for the high latitude regions

USGS Publications Warehouse

Biancamaria, S.; Mognard, N.M.; Boone, A.; Grippa, M.; Josberger, E.G.

2008-01-01

The hydrological cycle for high latitude regions is inherently linked with the seasonal snowpack. Thus, accurately monitoring the snow depth and the associated aerial coverage are critical issues for monitoring the global climate system. Passive microwave satellite measurements provide an optimal means to monitor the snowpack over the arctic region. While the temporal evolution of snow extent can be observed globally from microwave radiometers, the determination of the corresponding snow depth is more difficult. A dynamic algorithm that accounts for the dependence of the microwave scattering on the snow grain size has been developed to estimate snow depth from Special Sensor Microwave/Imager (SSM/I) brightness temperatures and was validated over the U.S. Great Plains and Western Siberia. The purpose of this study is to assess the dynamic algorithm performance over the entire high latitude (land) region by computing a snow depth multi-year field for the time period 1987-1995. This multi-year average is compared to the Global Soil Wetness Project-Phase2 (GSWP2) snow depth computed from several state-of-the-art land surface schemes and averaged over the same time period. The multi-year average obtained by the dynamic algorithm is in good agreement with the GSWP2 snow depth field (the correlation coefficient for January is 0.55). The static algorithm, which assumes a constant snow grain size in space and time does not correlate with the GSWP2 snow depth field (the correlation coefficient with GSWP2 data for January is - 0.03), but exhibits a very high anti-correlation with the NCEP average January air temperature field (correlation coefficient - 0.77), the deepest satellite snow pack being located in the coldest regions, where the snow grain size may be significantly larger than the average value used in the static algorithm. The dynamic algorithm performs better over Eurasia (with a correlation coefficient with GSWP2 snow depth equal to 0.65) than over North America (where the correlation coefficient decreases to 0.29). ?? 2007 Elsevier Inc. All rights reserved.

Air and Ground Surface Temperature Relations in a Mountainous Basin, Wolf Creek, Yukon Territory

NASA Astrophysics Data System (ADS)

Roadhouse, Emily A.

The links between climate and permafrost are well known, but the precise nature of the relationship between air and ground temperatures remains poorly understood, particularly in complex mountain environments. Although previous studies indicate that elevation and potential incoming solar radiation (PISR) are the two leading factors contributing to the existence of permafrost at a given location, additional factors may also contribute significantly to the existence of mountain permafrost, including vegetation cover, snow accumulation and the degree to which individual mountain landscapes are prone to air temperature inversions. Current mountain permafrost models consider only elevation and aspect, and have not been able to deal with inversion effects in a systematic fashion. This thesis explores the relationship between air and ground surface temperatures and the presence of surface-based inversions at 27 sites within the Wolf Creek basin and surrounding area between 2001 and 2006, as a first step in developing an improved permafrost distribution TTOP model. The TTOP model describes the relationship between the mean annual air temperature and the temperature at the top of permafrost in terms of the surface and thermal offsets (Smith and Riseborough, 2002). Key components of this model are n-factors which relate air and ground climate by establishing the ratio between air and surface freezing (winter) and thawing (summer) degree-days, thus summarizing the surface energy balance on a seasonal basis. Here we examine (1) surface offsets and (2) freezing and thawing n-factor variability at a number of sites through altitudinal treeline in the southern Yukon. Thawing n-factors (nt) measured at individual sites remained relatively constant from one year to the next and may be related to land cover. During the winter, the insulating effect of a thick snow cover results in higher surface temperatures, while thin snow cover results in low surface temperatures more closely related to the winter air temperatures. The application of n-factor modeling techniques within the permafrost region, and the verification of these techniques for a range of natural surfaces, is essential to the determination of the thermal and physical response to potential climate warming in permafrost regions. The presence of temperature inversions presents a unique challenge to permafrost probability mapping in mountainous terrain. While elsewhere the existence of permafrost can be linearly related to elevation, the presence of frequent inversions challenges this assumption, affecting permafrost distribution in ways that the current modeling techniques cannot accurately predict. At sites across the Yukon, inversion-prone sites were predominantly situated in U-shaped valleys, although open slopes, mid-slope ridges and plains were also identified. Within the Wolf Creek basin and surrounding area, inversion episodes have a measurable effect on local air temperatures, occurring during the fall and winter seasons along the Mount Sima trail, and year-round in the palsa valley. Within the discontinuous permafrost zone, where average surface temperatures are often close to zero, even a relatively small change in temperature in the context of future climate change could have a widespread impact on permafrost distribution.

Effects of Planting of Calluna Vulgaris for Stable Snow Accumulation in Winter

NASA Astrophysics Data System (ADS)

Ibuki, R.; Harada, K.

2017-12-01

Recent year climate of the winter season is changing and the period of snow accumulation is reduced compared with before. It affects the management of the ski resort. Snowfall had occurred in December 2016, but the snow accumulated after January 2017 at the ski resort located in the Pacific Ocean side of the Northeast region of Japan. This situation is thought to be originated from two reasons, one is snow thawing, another is to be blown away by the strong monsoon wind. We are considering utilizing planting to stabilize snow accumulation. Currently building rock gardens with shrubs, mainly Calluna Vulgaris in the ski resort for attracting customers in the summer. These are difficult to raise in the lowlands of Japan because they are too hot, but because of their good growth in relatively low-temperature highlands, it is rare for local residents to appreciate the value of these. In addition, it is excellent in low temperature resistance, and it will not die even under the snow. We investigated the pressure resistance performance due to snowfall and the appropriateness of growth under the weather conditions of the area. Regarding Calluna Vulgaris, Firefly, the plants were not damaged even under snow more than 1 m. In addition, three years have passed since planting, relatively good growth is shown, and the stock has been growing every year. Based on these results, we plan to stabilize the snow accumulation by carrying out planting of Calluna vulgaris inside the slope. The growth of the Calluna species is gentle and the tree height grows only about 50 cm even if 15 years have passed since planting. Therefore, it is considered that the plant body is hard to put out their head on the snow surface during the ski season. Next season will monitor the snow accumulation around the planting area through the snow season.

Ultra-Wideband Radiometry Remote Sensing of Polar Ice Sheet Temperature Profile, Sea Ice and Terrestrial Snow Thickness: Forward Modeling and Data Analysis

NASA Astrophysics Data System (ADS)

Tsang, L.; Tan, S.; Sanamzadeh, M.; Johnson, J. T.; Jezek, K. C.; Durand, M. T.

2017-12-01

The recent development of an ultra-wideband software defined radiometer (UWBRAD) operating over the unprotected spectrum of 0.5 2.0 GHz using radio-frequency interference suppression techniques offers new methodologies for remote sensing of the polar ice sheets, sea ice, and terrestrial snow. The instrument was initially designed for remote sensing of the intragalcial temperature profile of the ice sheet, where a frequency dependent penetration depth yields a frequency dependent brightness temperature (Tb) spectrum that can be linked back to the temperature profile of the ice sheet. The instrument was tested during a short flight over Northwest Greenland in September, 2016. Measurements were successfully made over the different snow facies characteristic of Greenland including the ablation, wet snow and percolation facies, and ended just west of Camp Century during the approach to the dry snow zone. Wide-band emission spectra collected during the flight have been processed and analyzed. Results show that the spectra are highly sensitive to the facies type with scattering from ice lenses being the dominant reason for low Tbs in the percolation zone. Inversion of Tb to physical temperature at depth was conducted on the measurements near Camp Century, achieving a -1.7K ten-meter error compared to borehole measurements. However, there is a relatively large uncertainty in the lower part possibly due to the large scattering near the surface. Wideband radiometry may also be applicable to sea ice and terrestrial snow thickness retrieval. Modeling studies suggest that the UWBRAD spectra reduce ambiguities inherent in other sea ice thickness retrievals by utilizing coherent wave interferences that appear in the Tb spectrum. When applied to a lossless medium such as terrestrial snow, this coherent oscillation turns out to be the single key signature that can be used to link back to snow thickness. In this paper, we report our forward modeling findings in support of instrument development and data analysis. The effects of density fluctuations and layered roughness are examined using a partially coherent model; we also report the results of applying such models to analyze the UWBRAD Greenland data. The approach of combining active L- band observations from PALSAR with UWBRAD Tb spectra is also discussed.

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, to assess the most suitable threshold, we firstly analyzed hourly MEB values to detect if ablation occurs and how long this phenomenon takes (number of hours per day). The largest part of the melting (97.7%) resulted occurring on days featuring at least 6 melting hours thus suggesting to consider their minimum average daily temperature value as a suitable threshold (268.1 K). Then we ran a simple T-index model applying different threshold values. The threshold which better reproduces snow melting results the value 268.1 K. Summarizing using a 5.0 K lower threshold value (with respect to the largely applied 273.15 K) permits the best reconstruction of glacier melt and it results in agreement with findings by van den Broeke et al. (2010) in Greenland ice sheet. Then probably the choice of a 268 K value as threshold for computing degree days amount could be generalized and applied not only on Greenland glaciers but also on Mid latitude and Alpine ones. This work was carried out under the umbrella of the SHARE Stelvio Project funded by the Lombardy Region and managed by FLA and EvK2-CNR Committee.

Hydraulic, water-quality, and temperature performance of three types of permeable pavement under high sediment loading conditions

USGS Publications Warehouse

Selbig, William R.; Buer, Nicolas

2018-05-11

Three permeable pavement surfaces - asphalt (PA), concrete (PC), and interlocking pavers (PIP) - were evaluated side-by-side to measure changes to the infiltrative capacity and water quality of stormwater runoff originating from a conventional asphalt parking lot in Madison, Wisconsin. During the 24-month monitoring period (2014-16), all three permeable pavements resulted in statistically significant reductions in the cumulative load of solids (total suspended solids and suspended sediment), total phosphorus, Escherichia coli (E. coli), and Enterococci. Most of the removal occurred through capture and retention in the void spaces of each permeable surface and aggregate base. The largest reduction in total suspended solids was for PC at 80 percent, followed by PIP and PA at 69 and 65 percent, respectively. Reductions (generally less than 50 percent) in total phosphorus also were observed, which might have been tempered by increases in the dissolved fraction observed in PIP and PA. Conversely, PC results indicated a slight reduction in dissolved phosphorus but failed to meet statistical significance. E. coli and Enterococci were reduced by about 80 percent for PC, almost twice the amount observed for PIP and PA.Results for the PIP and PC surfaces initially indicated higher pollutant load reduction than results for the PA surface. The efficiency of PIP and PC surfaces capturing sediment, however, led to a decline in infiltration rates that resulted in more runoff flowing over, not through, the permeable surface. This result led to a decline in treatment until the permeable surface was partially restored through maintenance practices, to which PIP responded more dramatically than PC or PA. Conversely, the PA surface was capable of infiltrating most of the influent runoff volume during the monitoring period and, thus, continued to provide some level of treatment. The combined effect of underdrain and overflow drainage resulted in similar pollutant treatment for all three permeable surfaces.Temperatures below each permeable surface generally followed changes in air temperature with a more gradual response observed in deeper layers. Therefore, permeable pavement may do little to mitigate heated runoff during summer. During winter, deeper layers remained above freezing even when air temperature was below freezing. Although temperatures were not high enough to melt snow or ice accumulated on the surface, temperatures below each permeable pavement did allow void spaces to remain open, which promoted infiltration of melted ice and snow as air temperatures rose above freezing. These open void spaces could potentially reduce the need for application of deicing agents in winter because melted snow and ice would infiltrate, thereby preventing refreezing of pooled water in what is known as the “black ice” effect.

The Impact of Surface Boundary Forcing on Simulation of the 1998 Summer Drought Over the US Midwest Using Factor Separation Technique

NASA Technical Reports Server (NTRS)

Stein, Uri; Fox-Rabinovitz, Michael

1999-01-01

The factor separation (FS) technique has been utilized to evaluate quantitatively the impact of surface boundary forcings on simulation of the 1988 summer drought over the Midwestern part of the U.S. The four surface boundary forcings used are: (1)Sea Surface Temperature (SST), (2) soil moisture, (3) snow cover, and (4) sea ice. The Goddard Earth Observing System(GEOS) General Circulation Model (GCM) is used to simulate the 1988 U.S. drought. A series of sixteen simulations are performed with climatological and real 1988 surface boundary conditions. The major single and mutual synergistic factors/impacts are analyzed. The results show that SST and soil moisture are the major single pro-drought factors. The couple synergistic effect of SST and soil moisture is the major anti-drought factor. The triple synergistic impact of SST, soil moisture, and snow cover is the strongest pro-drought impact and is, therefore, the main contributor to the generation of the drought. The impact of the snow cover and sea ice anomalies for June 1988 on the drought is significant only when combined with the SST and soil moisture anomalies.

Influence of Western Tibetan Plateau Summer Snow Cover on East Asian Summer Rainfall

NASA Astrophysics Data System (ADS)

Wang, Zhibiao; Wu, Renguang; Chen, Shangfeng; Huang, Gang; Liu, Ge; Zhu, Lihua

2018-03-01

The influence of boreal winter-spring eastern Tibetan Plateau snow anomalies on the East Asian summer rainfall variability has been the focus of previous studies. The present study documents the impacts of boreal summer western and southern Tibetan Plateau snow cover anomalies on summer rainfall over East Asia. Analysis shows that more snow cover in the western and southern Tibetan Plateau induces anomalous cooling in the overlying atmospheric column. The induced atmospheric circulation changes are different corresponding to more snow cover in the western and southern Tibetan Plateau. The atmospheric circulation changes accompanying the western Plateau snow cover anomalies are more obvious over the midlatitude Asia, whereas those corresponding to the southern Plateau snow cover anomalies are more prominent over the tropics. As such, the western and southern Tibetan Plateau snow cover anomalies influence the East Asian summer circulation and precipitation through different pathways. Nevertheless, the East Asian summer circulation and precipitation anomalies induced by the western and southern Plateau snow cover anomalies tend to display similar distribution so that they are more pronounced when the western and southern Plateau snow cover anomalies work in coherence. Analysis indicates that the summer snow cover anomalies over the Tibetan Plateau may be related to late spring snow anomalies due to the persistence. The late spring snow anomalies are related to an obvious wave train originating from the western North Atlantic that may be partly associated with sea surface temperature anomalies in the North Atlantic Ocean.

A Physical Based Formula for Calculating the Critical Stress of Snow Movement

NASA Astrophysics Data System (ADS)

He, S.; Ohara, N.

2016-12-01

In snow redistribution modeling, one of the most important parameters is the critical stress of snow movement, which is difficult to estimate from field data because it is influenced by various factors. In this study, a new formula for calculating critical stress of snow movement was derived based on the ice particle sintering process modeling and the moment balance of a snow particle. Through this formula, the influences of snow particle size, air temperature, and deposited time on the critical stress were explicitly taken into consideration. It was found that some of the model parameters were sensitive to the critical stress estimation through the sensitivity analysis using Sobol's method. The two sensitive parameters of the sintering process modeling were determined by a calibration-validation procedure using the observed snow flux data via FlowCapt. Based on the snow flux and metrological data observed at the ISAW stations (http://www.iav.ch), it was shown that the results of this formula were able to describe very well the evolution of the minimum friction wind speed required for the snow motion. This new formula suggested that when the snow just reaches the surface, the smaller snowflake can move easier than the larger particles. However, smaller snow particles require more force to move as the sintering between the snowflakes progresses. This implied that compact snow with small snow particles may be harder to erode by wind although smaller particles may have a higher chance to be suspended once they take off.

Vegetation masking effect on future warming and snow albedo feedback in a boreal forest region of northern Eurasia according to MIROC-ESM

NASA Astrophysics Data System (ADS)

Abe, Manabu; Takata, Kumiko; Kawamiya, Michio; Watanabe, Shingo

2017-09-01

The Earth system model, Model for Interdisciplinary Research on Climate-Earth system model (MIROC-ESM), in which the leaf area index (LAI) is calculated interactively with an ecological land model, simulated future changes in the snow water equivalent under the scenario of global warming. Using MIROC-ESM, the effects of the snow albedo feedback (SAF) in a boreal forest region of northern Eurasia were examined under the possible climate future scenario RCP8.5. The simulated surface air temperature (SAT) in spring greatly increases across Siberia and the boreal forest region, whereas the snow cover decreases remarkably only in western Eurasia. The large increase in SAT across Siberia is attributed to strong SAF, which is caused by both the reduced snow-covered fraction and the reduced surface albedo of the snow-covered portion due to the vegetation masking effect in those grid cells. A comparison of the future changes with and without interactive LAI changes shows that in Siberia, the vegetation masking effect increases the spring SAF by about two or three times and enhances the spring warming by approximately 1.5 times. This implies that increases in vegetation biomass in the future are a potential contributing factor to warming trends and that further research on the vegetation masking effect is needed for reliable future projection.

Progress in radar snow research. [Brookings, South Dakota

NASA Technical Reports Server (NTRS)

Stiles, W. H.; Ulaby, F. T.; Fung, A. K.; Aslam, A.

1981-01-01

Multifrequency measurements of the radar backscatter from snow-covered terrain were made at several sites in Brookings, South Dakota, during the month of March of 1979. The data are used to examine the response of the scattering coefficient to the following parameters: (1) snow surface roughness, (2) snow liquid water content, and (3) snow water equivalent. The results indicate that the scattering coefficient is insensitive to snow surface roughness if the snow is drv. For wet snow, however, surface roughness can have a strong influence on the magnitude of the scattering coefficient. These observations confirm the results predicted by a theoretical model that describes the snow as a volume of Rayleig scatterers, bounded by a Gaussian random surface. In addition, empirical models were developed to relate the scattering coefficient to snow liquid water content and the dependence of the scattering coefficient on water equivalent was evaluated for both wet and dry snow conditions.

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 incorporating the snow into the first soil layer) the new snow model has better insulating properties, thus preventing the ground from overcooling in winter. It also provides better simulation for water retention and release by the snow which results in more physical ground water runoff.

The Role of the Snow Covers in the Permafrost Temperature Dynamics at the Northern Yakutia over the last 30 Years

NASA Astrophysics Data System (ADS)

Kholodov, A. L.

2011-12-01

This report concerns the changes of the dynamics of snow warming influence on the permafrost temperature at the northern Yakutia. Snow is a key factor determines the thermal state of permafrost here. Despite of the absence of air temperature latitudinal zonality mean annual ground temperature decreases northward approximately 1 centigrade per latitude degree due to changes of the snow warming impact. At the north-western part with a relatively maritime climate warming influence of the snow is 0.5 to 1.5°C, while in the southern and eastern part with more continental climate it is 3.5 to 4.5°C. Snow redistribution within the some types of landscape at the beginning of the winter season can lead to the extremely fast freezing of the active layer and cooling of the permafrost within such types of landscapes. The main goal of the current research was to estimate snow warming impact dynamics over the last 30 years in the northern Yakutia. We took in consideration changes of the three main parameters, are determining snow cover thermal state: - snow thickness; - amplitude of air temperature seasonal oscillation; - temperature during the winter period during. Following conclusion can be done based on the data analysis: Interannual changes of snow warming influence are tenth to first centigrades, what is comparable with air temperature fluctuations. During the 1980-90s snow impact on the permafrost stood stable in the south-eastern part of the region or had a slightly negative trend in the western part. It could be explained by the changes of snow thickness, reduced thermal resistivity of snow due to winter warming and decreasing of the amplitude of seasonal temperature oscillation in the western part of the region. Since the end of 90s general increasing of the snow cover warming influence was noticed for the entire investigated territory. These results correspond with data of modern permafrost temperature observations have been done in the region during the last decades. Most of monitoring sites did not show sustainable changes of the permafrost temperature until the end of 90s years of the XX century, but recent measurements record increasing of the mean annual ground temperature at the most of monitoring sites in the region.

Arctic Sea Salt Aerosol from Blowing Snow and Sea Ice Surfaces - a Missing Natural Source in Winter

NASA Astrophysics Data System (ADS)

Frey, M. M.; Norris, S. J.; Brooks, I. M.; Nishimura, K.; Jones, A. E.

2015-12-01

Atmospheric particles in the polar regions consist mostly of sea salt aerosol (SSA). SSA plays an important role in regional climate change through influencing the surface energy balance either directly or indirectly via cloud formation. SSA irradiated by sunlight also releases very reactive halogen radicals, which control concentrations of ozone, a pollutant and greenhouse gas. However, models under-predict SSA concentrations in the Arctic during winter pointing to a missing source. It has been recently suggested that salty blowing snow above sea ice, which is evaporating, to be that source as it may produce more SSA than equivalent areas of open ocean. Participation in the 'Norwegian Young Sea Ice Cruise (N-ICE 2015)' on board the research vessel `Lance' allowed to test this hypothesis in the Arctic sea ice zone during winter. Measurements were carried out from the ship frozen into the pack ice North of 80º N during February to March 2015. Observations at ground level (0.1-2 m) and from the ship's crows nest (30 m) included number concentrations and size spectra of SSA (diameter range 0.3-10 μm) as well as snow particles (diameter range 50-500 μm). During and after blowing snow events significant SSA production was observed. In the aerosol and snow phase sulfate is fractionated with respect to sea water, which confirms sea ice surfaces and salty snow, and not the open ocean, to be the dominant source of airborne SSA. Aerosol shows depletion in bromide with respect to sea water, especially after sunrise, indicating photochemically driven release of bromine. We discuss the SSA source strength from blowing snow in light of environmental conditions (wind speed, atmospheric turbulence, temperature and snow salinity) and recommend improved model parameterisations to estimate regional aerosol production. N-ICE 2015 results are then compared to a similar study carried out previously in the Weddell Sea during the Antarctic winter.

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 different altitudes and land cover in this remote area with significant hazards from snow melt and glacier discharge. The improved spatial resolution, enhanced to 3-6 km, and retaining twice daily observations is a key improvement to fully analyze snowpack melt characteristics in remote mountainous regions.

Confronting the surface temperature cold bias in AGCMs over the Tibetan Plateau and improving climate simulations

NASA Astrophysics Data System (ADS)

Wu, G. X.; Liu, Y.; Bao, Q.; Chen, X.; Li, J.

2017-12-01

One of the mid-term progresses of the NSFC- Key Research Program "Land-air Coupling over the Tibetan Plateau and Its Climate Impact " is presented. The elevated heating in summer and cooling in winter of the Tibetan Plateau significantly regulate the seasonal change of the atmospheric circulation and exert remarkable impacts on world climate. Recent studies have demonstrated that the majority of the Phase-5 Coupled Model Inter-comparison Project (CMIP5) models underestimate annual and seasonal mean surface air temperatures (Ta) over the Tibetan Plateau (TP). In addition, more than half of the models underestimate annual and seasonal mean surface temperatures (Ts) over the TP. These cold biases are larger over the western TP. By decomposing the Ts bias using the surface energy budget equation, it was demonstrated that this TP's cold bias can be attributed to various factors, in which the stronger bias in surface albedo (a-) and the weaker bias in clear-sky downward Longwave radiation (DLR) play the most significant roles. Since a- and DLR are respectively affected by snow coverage fraction at the ground surface and water vapor content in the atmosphere, these results then imply that the cold bias over the TP is caused by too large snow coverage fraction and too less water vapor content over the TP in the models. The FAMIL AGCM model developed at LASG also suffers from the similar cold bias over the TP. By introducing the 3D- Radiative Transfer Parameterization Over Mountains/Snow (Liou, 2013) into the model, the total solar radiation reaching the ground surface is increased during the daytime, resulting in more snowmelt and less snow coverage. Accordingly, surface albedo is decreased on the sunny side of the mountains, and the surface cold bias over mountain areas is decreased. It is shown that the improvement is sensitive to the model resolution: increased the horizontal resolution of Community Land Model version 4.0 (CLM 4.0) from nearly 200km (1.9o×2.5o) to about 25km (0.23o×0.31o) can significantly improve the parameterization effect and accuracy, with more notably improvement appearing in Spring. It is demonstrated that, by stimulating a Rossby wave and strengthen the precipitation in subtropical frontal zone of East Asia, the decrement of clod bias over the TP can greatly improve the climate simulations of the model.

Cloud Masking and Surface Temperature Distribution in the Polar Regions Using AVHRR and other Satellite Data

NASA Technical Reports Server (NTRS)

Comiso, Joey C.

1995-01-01

Surface temperature is one of the key variables associated with weather and climate. Accurate measurements of surface air temperatures are routinely made in meteorological stations around the world. Also, satellite data have been used to produce synoptic global temperature distributions. However, not much attention has been paid on temperature distributions in the polar regions. In the polar regions, the number of stations is very sparse. Because of adverse weather conditions and general inaccessibility, surface field measurements are also limited. Furthermore, accurate retrievals from satellite data in the region have been difficult to make because of persistent cloudiness and ambiguities in the discrimination of clouds from snow or ice. Surface temperature observations are required in the polar regions for air-sea-ice interaction studies, especially in the calculation of heat, salinity, and humidity fluxes. They are also useful in identifying areas of melt or meltponding within the sea ice pack and the ice sheets and in the calculation of emissivities of these surfaces. Moreover, the polar regions are unique in that they are the sites of temperature extremes, the location of which is difficult to identify without a global monitoring system. Furthermore, the regions may provide an early signal to a potential climate change because such signal is expected to be amplified in the region due to feedback effects. In cloud free areas, the thermal channels from infrared systems provide surface temperatures at relatively good accuracies. Previous capabilities include the use of the Temperature Humidity Infrared Radiometer (THIR) onboard the Nimbus-7 satellite which was launched in 1978. Current capabilities include the use of the Advance Very High Resolution Radiometer (AVHRR) aboard NOAA satellites. Together, these two systems cover a span of 16 years of thermal infrared data. Techniques for retrieving surface temperatures with these sensors in the polar regions have been developed. Errors have been estimated to range from 1K to 5K mainly due to cloud masking problems. With many additional channels available, it is expected that the EOS-Moderate Resolution Imaging Spectroradiometer (MODIS) will provide an improved characterization of clouds and a good discrimination of clouds from snow or ice surfaces.

Ecophysiology, secondary pigments and ultrastructure of Chlainomonas sp. (Chlorophyta) from the European Alps compared with Chlamydomonas nivalis forming red snow

PubMed Central

Remias, Daniel; Pichrtová, Martina; Pangratz, Marion; Lütz, Cornelius; Holzinger, Andreas

2016-01-01

Red snow is a well-known phenomenon caused by microalgae thriving in alpine and polar regions during the melting season. The ecology and biodiversity of these organisms, which are adapted to low temperatures, high irradiance and freeze–thaw events, are still poorly understood. We compared two different snow habitats containing two different green algal genera in the European Alps, namely algae blooming in seasonal rock-based snowfields (Chlamydomonas nivalis) and algae dominating waterlogged snow bedded over ice (Chlainomonas sp.). Despite the morphological similarity of the red spores found at the snow surface, we found differences in intracellular organization investigated by light and transmission electron microscopy and in secondary pigments investigated by chromatographic analysis in combination with mass spectrometry. Spores of Chlainomonas sp. show clear differences from Chlamydomonas nivalis in cell wall arrangement and plastid organization. Active photosynthesis at ambient temperatures indicates a high physiological activity, despite no cell division being present. Lipid bodies containing the carotenoid astaxanthin, which produces the red color, dominate cells of both species, but are modified differently. While in Chlainomonas sp. astaxanthin is mainly esterified with two fatty acids and is more apolar, in Chamydomonas nivalis, in contrast, less apolar monoesters prevail. PMID:26884467

Snow cover monitoring over French Alps based on Spot-Vegetation S-10 products. Application to the Vercors area for the time period 1998-2008.

NASA Astrophysics Data System (ADS)

Bigot, S.; Dedieu, Jp.; Rome, S.

2009-04-01

Sylvain.bigot@ujf-grenoble.fr Jean-pierre.dedieu@hmg.inpg.fr Sandra.rome@ujf-grenoble.fr Estimation of the Snow Covered Area (SCA) is an important issue for meteorological application and hydrological modeling of runoff. With spectral bands in the visible, near and middle infrared, the SPOT-4 and -5 VEGETATION sensors are used to detect snow cover because of large differences between reflectance from snow covered and snow free surfaces. At the same time, it allows separation between snow and clouds. Moreover, the sensor provides a daily coverage of large areas. However, as the pixel size is 1km x 1km, a VGT pixel may be partially covered by snow, particularly in Alpine areas, where snow may not be present in valleys lying at lower altitudes. Also, variation of reflectance due to differential sunlit effects as a function of slope and aspect, as well as bidirectional effects may be present in images. Nevertheless, it is possible to estimate snow cover at the sub-pixel level with a relatively good accuracy and with very good results if the sub-pixel estimations are integrated for a few pixels relative to an entire watershed. Application of this approach in the French Alps is presented over the Vercors Natural Park area (N 44°.50' / E 05°.30'), based on 10-day Synthetic products for the 1998-2008 time period, and using the NDSII (Normalized Difference Snow/Ice Index) as numerical threshold. This work performs an analysis of climate impact on snow cover spatial and temporal variability, at mid-elevation mountain range (1500 m asl) under temperate climate conditions. The results indicates (i) a increasing temporal and spatial variability of snow coverage, and (ii) a high sensitivity to low variation of air temperature, often close to 1° C. This is the case in particular for the beginning and the end of the winter season. The regional snow cover depletion is both influenced by thermal positives anomalies (e.g. 2000 and 2006), and the general trend of rising atmospheric temperatures since the late 1980s.

Modeling soil temperature change in Seward Peninsula, Alaska

NASA Astrophysics Data System (ADS)

Debolskiy, M. V.; Nicolsky, D.; Romanovsky, V. E.; Muskett, R. R.; Panda, S. K.

2017-12-01

Increasing demand for assessment of climate change-induced permafrost degradation and its consequences promotes creation of high-resolution modeling products of soil temperature changes. This is especially relevant for areas with highly vulnerable warm discontinuous permafrost in the Western Alaska. In this study, we apply ecotype-based modeling approach to simulate high-resolution permafrost distribution and its temporal dynamics in Seward Peninsula, Alaska. To model soil temperature dynamics, we use a transient soil heat transfer model developed at the Geophysical Institute Permafrost Laboratory (GIPL-2). The model solves one dimensional nonlinear heat equation with phase change. The developed model is forced with combination of historical climate and different future scenarios for 1900-2100 with 2x2 km resolution prepared by Scenarios Network for Alaska and Arctic Planning (2017). Vegetation, snow and soil properties are calibrated by ecotype and up-scaled by using Alaska Existing Vegetation Type map for Western Alaska (Flemming, 2015) with 30x30 m resolution provided by Geographic Information Network of Alaska (UAF). The calibrated ecotypes cover over 75% of the study area. We calibrate the model using a data assimilation technique utilizing available observations of air, surface and sub-surface temperatures and snow cover collected by various agencies and research groups (USGS, Geophysical Institute, USDA). The calibration approach takes into account a natural variability between stations in the same ecotype and finds an optimal set of model parameters (snow and soil properties) within the study area. This approach allows reduction in microscale heterogeneity and aggregated soil temperature data from shallow boreholes which is highly dependent on local conditions. As a result of this study we present a series of preliminary high resolution maps for the Seward Peninsula showing changes in the active layer depth and ground temperatures for the current climate and future climate change scenarios.

Accuracy of sea ice temperature derived from the advanced very high resolution radiometer

NASA Technical Reports Server (NTRS)

Yu, Y.; Rothrock, D. A.; Lindsay, R. W.

1995-01-01

The accuracy of Arctic sea ice surface temperatures T(sub s) dericed from advanced very high resolution radiometer (AVHRR) thermal channels is evaluated in the cold seasons by comparing them with surface air temperatures T(sub air) from drifting buoys and ice stations. We use three different estimates of satellite surface temperatures, a direct estimate from AVHRR channel 4 with only correction for the snow surface emissivity but not for the atmosphere, a single-channel regression of T(sub s) with T(sub air), and Key and Haefliger's (1992) polar multichannel algorithm. We find no measurable bias in any of these estimates and few differences in their statistics. The similar performance of all three methods indicates that an atmospheric water vapor correction is not important for the dry winter atmosphere in the central Arctic, given the other sources of error that remain in both the satellite and the comparison data. A record of drifting station data shows winter air temperature to be 1.4 C warmer than the snow surface temperature. `Correcting' air temperatures to skin temperature by subtracting this amount implies that satellite T(sub s) estimates are biased warm with respect to skin temperature by about this amount. A case study with low-flying aircraft data suggests that ice crystal precipitation can cause satellite estimates of T(sub s) to be several degrees warmer than radiometric measurements taken close to the surface, presumably below the ice crystal precipitation layer. An analysis in which errors are assumed to exist in all measurements, not just the satellite measurements, gives a standard deviation in the satellite estimates of 0.9 C, about half the standard deviation of 1.7 C estimated by assigning all the variation between T(sub s) and T(sub air) to errors in T(sub s).

Improvements to the WRF-Chem 3.5.1 model for quasi-hemispheric simulations of aerosols and ozone in the Arctic

DOE PAGES

Marelle, Louis; Raut, Jean-Christophe; Law, Kathy S.; ...

2017-01-01

In this study, the WRF-Chem regional model is updated to improve simulated short-lived pollutants (e.g., aerosols, ozone) in the Arctic. Specifically, we include in WRF-Chem 3.5.1 (with SAPRC-99 gas-phase chemistry and MOSAIC aerosols) (1) a correction to the sedimentation of aerosols, (2) dimethyl sulfide (DMS) oceanic emissions and gas-phase chemistry, (3) an improved representation of the dry deposition of trace gases over seasonal snow, and (4) an UV-albedo dependence on snow and ice cover for photolysis calculations. We also (5) correct the representation of surface temperatures over melting ice in the Noah Land Surface Model and (6) couple and further test the recent KF-CuP (Kain–Fritsch +more » Cumulus Potential) cumulus parameterization that includes the effect of cumulus clouds on aerosols and trace gases. The updated model is used to perform quasi-hemispheric simulations of aerosols and ozone, which are evaluated against surface measurements of black carbon (BC), sulfate, and ozone as well as airborne measurements of BC in the Arctic. The updated model shows significant improvements in terms of seasonal aerosol cycles at the surface and root mean square errors (RMSEs) for surface ozone, aerosols, and BC aloft, compared to the base version of the model and to previous large-scale evaluations of WRF-Chem in the Arctic. These improvements are mostly due to the inclusion of cumulus effects on aerosols and trace gases in KF-CuP (improved RMSE for surface BC and BC profiles, surface sulfate, and surface ozone), the improved surface temperatures over sea ice (surface ozone, BC, and sulfate), and the updated trace gas deposition and UV albedo over snow and ice (improved RMSE and correlation for surface ozone). DMS emissions and chemistry improve surface sulfate at all Arctic sites except Zeppelin, and correcting aerosol sedimentation has little influence on aerosols except in the upper troposphere.« less

Improvements to the WRF-Chem 3.5.1 model for quasi-hemispheric simulations of aerosols and ozone in the Arctic

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

Marelle, Louis; Raut, Jean-Christophe; Law, Kathy S.

In this study, the WRF-Chem regional model is updated to improve simulated short-lived pollutants (e.g., aerosols, ozone) in the Arctic. Specifically, we include in WRF-Chem 3.5.1 (with SAPRC-99 gas-phase chemistry and MOSAIC aerosols) (1) a correction to the sedimentation of aerosols, (2) dimethyl sulfide (DMS) oceanic emissions and gas-phase chemistry, (3) an improved representation of the dry deposition of trace gases over seasonal snow, and (4) an UV-albedo dependence on snow and ice cover for photolysis calculations. We also (5) correct the representation of surface temperatures over melting ice in the Noah Land Surface Model and (6) couple and further test the recent KF-CuP (Kain–Fritsch +more » Cumulus Potential) cumulus parameterization that includes the effect of cumulus clouds on aerosols and trace gases. The updated model is used to perform quasi-hemispheric simulations of aerosols and ozone, which are evaluated against surface measurements of black carbon (BC), sulfate, and ozone as well as airborne measurements of BC in the Arctic. The updated model shows significant improvements in terms of seasonal aerosol cycles at the surface and root mean square errors (RMSEs) for surface ozone, aerosols, and BC aloft, compared to the base version of the model and to previous large-scale evaluations of WRF-Chem in the Arctic. These improvements are mostly due to the inclusion of cumulus effects on aerosols and trace gases in KF-CuP (improved RMSE for surface BC and BC profiles, surface sulfate, and surface ozone), the improved surface temperatures over sea ice (surface ozone, BC, and sulfate), and the updated trace gas deposition and UV albedo over snow and ice (improved RMSE and correlation for surface ozone). DMS emissions and chemistry improve surface sulfate at all Arctic sites except Zeppelin, and correcting aerosol sedimentation has little influence on aerosols except in the upper troposphere.« less

Improvements to the WRF-Chem 3.5.1 model for quasi-hemispheric simulations of aerosols and ozone in the Arctic

NASA Astrophysics Data System (ADS)

Marelle, Louis; Raut, Jean-Christophe; Law, Kathy S.; Berg, Larry K.; Fast, Jerome D.; Easter, Richard C.; Shrivastava, Manish; Thomas, Jennie L.

2017-10-01

In this study, the WRF-Chem regional model is updated to improve simulated short-lived pollutants (e.g., aerosols, ozone) in the Arctic. Specifically, we include in WRF-Chem 3.5.1 (with SAPRC-99 gas-phase chemistry and MOSAIC aerosols) (1) a correction to the sedimentation of aerosols, (2) dimethyl sulfide (DMS) oceanic emissions and gas-phase chemistry, (3) an improved representation of the dry deposition of trace gases over seasonal snow, and (4) an UV-albedo dependence on snow and ice cover for photolysis calculations. We also (5) correct the representation of surface temperatures over melting ice in the Noah Land Surface Model and (6) couple and further test the recent KF-CuP (Kain-Fritsch + Cumulus Potential) cumulus parameterization that includes the effect of cumulus clouds on aerosols and trace gases. The updated model is used to perform quasi-hemispheric simulations of aerosols and ozone, which are evaluated against surface measurements of black carbon (BC), sulfate, and ozone as well as airborne measurements of BC in the Arctic. The updated model shows significant improvements in terms of seasonal aerosol cycles at the surface and root mean square errors (RMSEs) for surface ozone, aerosols, and BC aloft, compared to the base version of the model and to previous large-scale evaluations of WRF-Chem in the Arctic. These improvements are mostly due to the inclusion of cumulus effects on aerosols and trace gases in KF-CuP (improved RMSE for surface BC and BC profiles, surface sulfate, and surface ozone), the improved surface temperatures over sea ice (surface ozone, BC, and sulfate), and the updated trace gas deposition and UV albedo over snow and ice (improved RMSE and correlation for surface ozone). DMS emissions and chemistry improve surface sulfate at all Arctic sites except Zeppelin, and correcting aerosol sedimentation has little influence on aerosols except in the upper troposphere.

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 to the final 38 cm. The major ion composition (IC), pH, conductivity and cell abundances were measured. Results and conlusions The removal of microbial cells from a high arctic snowpack resembles an elution sequence similar to that of hydrophobic compounds a process that helps glaciers retain a microbial biomass upon their surface, even after the demise of the snow cover. The snowpack and the glacier surface therefore act as an accumulator of cells during the melt season. This suggests that wet snowpacks, even on the surface of high arctic glaciers, are likely to be dynamic ecosystems in their own right. In our study, a clear ion elution sequence was observed that resembled earlier reports and caused high concentrations of ions in snowpack runoff at the start of the snow melt, which rapidly decreased as snow melt proceeded. Chloride, sulfate, nitrate, sodium and potassium experienced a 50 % elution before 20 - 25 % of the snowpack water content was lost. By contrast, cell removal only reached the 50 % level after ~70 % snowpack depletion. In contrast to our expectations, the calculated cell budget between the initial and final snowpack (including the cell loss by elution), revealed a significant increase of the total cell numbers, i.e. more than twice the original number. Assuming aeolian deposition processes to be low, this suggests cell proliferation as a contribution to the observed "retention effect". Precipitation was the major cell contributor to the snowpack upon Midtre Lovénbreen. An overall low cell concentration was therefore found within the snowpack stratigraphy, where snow layers frequently showed cell abundances similar to those of cloud water. This was in contrast to the nearby and more wind exposed sites examined in the Kongsfjorden area in 2007. However, layers of higher dust deposition were concomitant with one order of magnitude higher cell abundances, indicating that wind dispersal from locally exposed rocks supplements the atmospheric cell input.

EXTASE - An Experimental Thermal Probe for Applications in Snow Research and Earth Sciences

NASA Astrophysics Data System (ADS)

Schroeer, K.; Seiferlin, K.; Marczewski, W.; Gadomski, S.; Spohn, T.

2002-12-01

EXTASE is a spin-off project from the Rosetta Lander (MUPUS) thermal probe, funded by DLR. The application of this probe is to be tested in different fields, e.g. in snow research, agriculture, permafrost etc. The system consists of the probe itself with a portable field electronic and a computer for control of the system and storage of the data. The probe penetrates the surface ca. 32 cm deep and provides a temperature profile (16 sensors) and thermal conductivity profile of the penetrated layer. The main advantages of the probe in comparison to common temperature profile measurement methods are: - no need to excavate material - minimized influence of the probe on the temperature field - minimized modification of the microstructure of the studied medium. Presently we are concentrating on agriculture (soil humidity) and snow research. Further applications could be e.g.: monitoring waste deposits and the heat released by decomposition, volcanology and ground truth for remote sensing. We present the general concept of the probe and also data obtained during different field measurement campaigns with prototypes of the probe.

Does Temperature Modify the Effects of Rain and Snow Precipitation on Road Traffic Injuries?

PubMed

Lee, Won-Kyung; Lee, Hye-Ah; Hwang, Seung-sik; Kim, Ho; Lim, Youn-Hee; Hong, Yun-Chul; Ha, Eun-Hee; Park, Hyesook

2015-01-01

There are few data on the interaction between temperature and snow and rain precipitation, although they could interact in their effects on road traffic injuries. The integrated database of the Korea Road Traffic Authority was used to calculate the daily frequency of road traffic injuries in Seoul. Weather data included rain and snow precipitation, temperature, pressure, and fog from May 2007 to December 2011. Precipitation of rain and snow were divided into nine and six temperature range categories, respectively. The interactive effects of temperature and rain and snow precipitation on road traffic injuries were analyzed using a generalized additive model with a Poisson distribution. The risk of road traffic injuries during snow increased when the temperature was below freezing. Road traffic injuries increased by 6.6% when it was snowing and above 0 °C, whereas they increased by 15% when it was snowing and at or below 0 °C. In terms of heavy rain precipitation, moderate temperatures were related to an increased prevalence of injuries. When the temperature was 0-20 °C, we found a 12% increase in road traffic injuries, whereas it increased by 8.5% and 6.8% when it was <0 °C and >20 °C, respectively. The interactive effect was consistent across the traffic accident subtypes. The effect of adverse weather conditions on road traffic injuries differed depending on the temperature. More road traffic injuries were related to rain precipitation when the temperature was moderate and to snow when it was below freezing.

Does Temperature Modify the Effects of Rain and Snow Precipitation on Road Traffic Injuries?

PubMed Central

Lee, Won-Kyung; Lee, Hye-Ah; Hwang, Seung-sik; Kim, Ho; Lim, Youn-Hee; Hong, Yun-Chul; Ha, Eun-Hee; Park, Hyesook

2015-01-01

Background There are few data on the interaction between temperature and snow and rain precipitation, although they could interact in their effects on road traffic injuries. Methods The integrated database of the Korea Road Traffic Authority was used to calculate the daily frequency of road traffic injuries in Seoul. Weather data included rain and snow precipitation, temperature, pressure, and fog from May 2007 to December 2011. Precipitation of rain and snow were divided into nine and six temperature range categories, respectively. The interactive effects of temperature and rain and snow precipitation on road traffic injuries were analyzed using a generalized additive model with a Poisson distribution. Results The risk of road traffic injuries during snow increased when the temperature was below freezing. Road traffic injuries increased by 6.6% when it was snowing and above 0°C, whereas they increased by 15% when it was snowing and at or below 0°C. In terms of heavy rain precipitation, moderate temperatures were related to an increased prevalence of injuries. When the temperature was 0–20°C, we found a 12% increase in road traffic injuries, whereas it increased by 8.5% and 6.8% when it was <0°C and >20°C, respectively. The interactive effect was consistent across the traffic accident subtypes. Conclusions The effect of adverse weather conditions on road traffic injuries differed depending on the temperature. More road traffic injuries were related to rain precipitation when the temperature was moderate and to snow when it was below freezing. PMID:26073021

The Asian-Bering-North American teleconnection: seasonality, maintenance, and climate impact on North America

NASA Astrophysics Data System (ADS)

Yu, Bin; Lin, H.; Wu, Z. W.; Merryfield, W. J.

2018-03-01

The Asian-Bering-North American (ABNA) teleconnection index is constructed from the normalized 500-hPa geopotential field by excluding the Pacific-North American pattern contribution. The ABNA pattern features a zonally elongated wavetrain originating from North Asia and flowing downstream across Bering Sea and Strait towards North America. The large-scale teleconnection is a year-round phenomenon that displays strong seasonality with the peak variability in winter. North American surface temperature and temperature extremes, including warm days and nights as well as cold days and nights, are significantly controlled by this teleconnection. The ABNA pattern has an equivalent barotropic structure in the troposphere and is supported by synoptic-scale eddy forcing in the upper troposphere. Its associated sea surface temperature anomalies exhibit a horseshoe-shaped structure in the North Pacific, most prominent in winter, which is driven by atmospheric circulation anomalies. The snow cover anomalies over the West Siberian plain and Central Siberian Plateau in autumn and spring and over southern Siberia in winter may act as a forcing influence on the ABNA pattern. The snow forcing influence in winter and spring can be traced back to the preceding season, which provides a predictability source for this teleconnection and for North American temperature variability. The ABNA associated energy budget is dominated by surface longwave radiation anomalies year-round, with the temperature anomalies supported by anomalous downward longwave radiation and damped by upward longwave radiation at the surface.

Hydrological variability in the Fraser River Basin during the 20th century: A sensitivity study with the VIC model

NASA Astrophysics Data System (ADS)

Kang, D.; Gao, H.; Dery, S. J.

2012-12-01

The Variable Infiltration Capacity (VIC) model, a macroscale surface hydrology model, was applied to the Fraser River Basin (FRB) of British Columbia, Canada. Previous modeling studies have demonstrated that the FRB is a snow-dominated system but with climate change may evolve to a pluvial regime. The ultimate goal of this model application is to evaluate the changing contribution of snowmelt to streamflow in the FRB both spatially and temporally. To this end, the National Centers for Environmental Prediction (NCEP) reanalysis data combined with meteorological observations over 1953 to 2006 are used to drive the model at a resolution of 0.25°. Model simulations are first validated with daily discharge observations from the Water Survey of Canada (WSC). In addition, the snow water equivalent (SWE) results from VIC are compared with snow pillow observations from the B.C. Ministry of Environment. Then peak SWE values simulated each winter are compared with the annual runoff data to quantify the changing contribution of snowmelt to the hydrology of the FRB. With perturbed model forcings such as precipitation and air temperature, how streamflow and surface energy-mass balance are changed is evaluated. Finally, interactions between the land surface and ambient atmosphere are evaluated by analyzing VIC results such as evaporation, soil moisture, snowmelt and sensible-latent heat flux with corresponding meteorological forcings, i.e. precipitation and air temperature.

Using Air Temperature to Quantitatively Predict the MODIS Fractional Snow Cover Retrieval Errors over the Continental US (CONUS)

NASA Technical Reports Server (NTRS)

Dong, Jiarui; Ek, Mike; Hall, Dorothy K.; Peters-Lidard, Christa; Cosgrove, Brian; Miller, Jeff; Riggs, George A.; Xia, Youlong

2013-01-01

In the middle to high latitude and alpine regions, the seasonal snow pack can dominate the surface energy and water budgets due to its high albedo, low thermal conductivity, high emissivity, considerable spatial and temporal variability, and ability to store and then later release a winters cumulative snowfall (Cohen, 1994; Hall, 1998). With this in mind, the snow drought across the U.S. has raised questions about impacts on water supply, ski resorts and agriculture. Knowledge of various snow pack properties is crucial for short-term weather forecasts, climate change prediction, and hydrologic forecasting for producing reliable daily to seasonal forecasts. One potential source of this information is the multi-institution North American Land Data Assimilation System (NLDAS) project (Mitchell et al., 2004). Real-time NLDAS products are used for drought monitoring to support the National Integrated Drought Information System (NIDIS) and as initial conditions for a future NCEP drought forecast system. Additionally, efforts are currently underway to assimilate remotely-sensed estimates of land-surface states such as snowpack information into NLDAS. It is believed that this assimilation will not only produce improved snowpack states that better represent snow evolving conditions, but will directly improve the monitoring of drought.

Comparison of effects of cold-region soil/snow processes and the uncertainties from model forcing data on permafrost physical characteristics

DOE PAGES

Barman, Rahul; Jain, Atul K.

2016-03-28

Here, we used a land surface model to (1) evaluate the influence of recent improvements in modeling cold-region soil/snow physics on near-surface permafrost physical characteristics (within 0–3 m soil column) in the northern high latitudes (NHL) and (2) compare them with uncertainties from climate and land-cover data sets. Specifically, four soil/snow processes are investigated: deep soil energetics, soil organic carbon (SOC) effects on soil properties, wind compaction of snow, and depth hoar formation. In the model, together they increased the contemporary NHL permafrost area by 9.2 × 10 6 km 2 (from 2.9 to 12.3—without and with these processes, respectively)more » and reduced historical degradation rates. In comparison, permafrost area using different climate data sets (with annual air temperature difference of ~0.5°C) differed by up to 2.3 × 10 6 km 2, with minimal contribution of up to 0.7 × 10 6 km 2 from substantial land-cover differences. Individually, the strongest role in permafrost increase was from deep soil energetics, followed by contributions from SOC and wind compaction, while depth hoar decreased permafrost. The respective contribution on 0–3 m permafrost stability also followed a similar pattern. However, soil temperature and moisture within vegetation root zone (~0–1 m), which strongly influence soil biogeochemistry, were only affected by the latter three processes. The ecosystem energy and water fluxes were impacted the least due to these soil/snow processes. While it is evident that simulated permafrost physical characteristics benefit from detailed treatment of cold-region biogeophysical processes, we argue that these should also lead to integrated improvements in modeling of biogeochemistry.« less

Interannual variability of March snow mass over Northern Eurasia and its relation to the concurrent and preceding surface air temperature, precipitation and atmospheric circulation

NASA Astrophysics Data System (ADS)

Ye, Kunhui

2018-06-01

The interannual variability of March snow water equivalent (SWE) in Northern Eurasia and its influencing factors are studied. The surface air temperature (SAT) and precipitation are the dominant factors for the snow accumulation in northern Europe and the remaining region, respectively. The strongest contribution of SAT to snow accumulation is mainly found in those months with moderate mean SAT. The strongest contribution of precipitation is not collocated with the climatological maxima in precipitation. The leading mode of March SWE variability is obtained and characterized by a spatial dipole. Anomalies in atmospheric water vapor divergence, storm activity and the associated atmospheric circulation can explain many of the associated precipitation and SAT features. Anomalies in autumn Arctic sea ice concentration (SIC) over the Barents Sea and Kara Sea (B/K Sea) and a dipole pattern of November snow cover (SC) in Eurasia are also observed. The atmospheric circulation anomalies that resemble a negative phase of North Atlantic Oscillation (NAO)/Arctic Oscillation (AO) are strongly projected onto the wintertime atmospheric circulation. Both observations and model experiment support that the autumn B/K Sea SIC has some impacts on the autumn and AO/NAO-like wintertime atmospheric circulation patterns. The dipole pattern of November Eurasian SC seems to be strongly forced by the autumn B/K Sea SIC and its feedback to the atmospheric circulation is important. Therefore, the impacts of autumn B/K Sea SIC on the autumn/wintertime atmospheric circulation and thus the March SWE variability may be modulated by both constructive and destructive interference of autumn Eurasian SC.

Effects of nontropical forest cover on climate

NASA Technical Reports Server (NTRS)

Otterman, J.; Chou, M.-D.; Arking, A.

1984-01-01

The albedo of a forest with snow on the ground is much less than that of snow-covered low vegetation such as tundra. As a result, simulation of the Northern Hemisphere climate, when fully forested south of a suitably chosen taiga/tundra boundary (ecocline), produces a hemispheric surface air temperature 1.9 K higher than that of an earth devoid of trees. Using variations of the solar constant to force climate changes in the GLAS Multi-Layer Energy Balance Model, the role of snow-albedo feedback in increasing the climate sensitivity to external perturbations is reexamined. The effect of snow-albedo feedback is found to be significantly reduced when a low albedo is used for snow over taiga, south of the fixed latitude of the ecocline. If the ecocline shifts to maintain equilibrium with the new climate - which is presumed to occur in a prolonged perturbation when time is sufficient for trees to grow or die and fall - the feedback is stronger than for a fixed ecocline, especially at high latitudes. However, this snow/vegetation-albedo feedback is still essentially weaker than the snow-albedo feedback in the forest-free case. The loss of forest to agriculture and other land-use would put the present climate further away from that associated with the fully forested earth south of the ecocline and closer to the forest-free case. Thus, the decrease in nontropical forest cover since prehistoric times has probably affected the climate by reducing the temperatures and by increasing the sensitivity to perturbations, with both effects more pronounced at high latitudes.

Snow and ice ecosystems: not so extreme.

PubMed

Maccario, Lorrie; Sanguino, Laura; Vogel, Timothy M; Larose, Catherine

2015-12-01

Snow and ice environments cover up to 21% of the Earth's surface. They have been regarded as extreme environments because of their low temperatures, high UV irradiation, low nutrients and low water availability, and thus, their microbial activity has not been considered relevant from a global microbial ecology viewpoint. In this review, we focus on why snow and ice habitats might not be extreme from a microbiological perspective. Microorganisms interact closely with the abiotic conditions imposed by snow and ice habitats by having diverse adaptations, that include genetic resistance mechanisms, to different types of stresses in addition to inhabiting various niches where these potential stresses might be reduced. The microbial communities inhabiting snow and ice are not only abundant and taxonomically diverse, but complex in terms of their interactions. Altogether, snow and ice seem to be true ecosystems with a role in global biogeochemical cycles that has likely been underestimated. Future work should expand past resistance studies to understanding the function of these ecosystems. Copyright © 2015 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved.

Snow-atmosphere coupling and its impact on temperature variability and extremes over North America

NASA Astrophysics Data System (ADS)

Diro, G. T.; Sushama, L.; Huziy, O.

2018-04-01

The impact of snow-atmosphere coupling on climate variability and extremes over North America is investigated using modeling experiments with the fifth generation Canadian Regional Climate Model (CRCM5). To this end, two CRCM5 simulations driven by ERA-Interim reanalysis for the 1981-2010 period are performed, where snow cover and depth are prescribed (uncoupled) in one simulation while they evolve interactively (coupled) during model integration in the second one. Results indicate systematic influence of snow cover and snow depth variability on the inter-annual variability of soil and air temperatures during winter and spring seasons. Inter-annual variability of air temperature is larger in the coupled simulation, with snow cover and depth variability accounting for 40-60% of winter temperature variability over the Mid-west, Northern Great Plains and over the Canadian Prairies. The contribution of snow variability reaches even more than 70% during spring and the regions of high snow-temperature coupling extend north of the boreal forests. The dominant process contributing to the snow-atmosphere coupling is the albedo effect in winter, while the hydrological effect controls the coupling in spring. Snow cover/depth variability at different locations is also found to affect extremes. For instance, variability of cold-spell characteristics is sensitive to snow cover/depth variation over the Mid-west and Northern Great Plains, whereas, warm-spell variability is sensitive to snow variation primarily in regions with climatologically extensive snow cover such as northeast Canada and the Rockies. Furthermore, snow-atmosphere interactions appear to have contributed to enhancing the number of cold spell days during the 2002 spring, which is the coldest recorded during the study period, by over 50%, over western North America. Additional results also provide useful information on the importance of the interactions of snow with large-scale mode of variability in modulating temperature extreme characteristics.

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

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%.

Combined Effects of the North Atlantic Oscillation and the Arctic Oscillation on Sea Surface Temperature in the Alborán Sea

PubMed Central

Báez, José C.; Gimeno, Luis; Gómez-Gesteira, Moncho; Ferri-Yáñez, Francisco; Real, Raimundo

2013-01-01

We explored the possible effects of the North Atlantic Oscillation (NAO) and Arctic Oscillation (AO) on interannual sea surface temperature (SST) variations in the Alborán Sea, both separately and combined. The probability of observing mean annual SST values higher than average was related to NAO and AO values of the previous year. The effect of NAO on SST was negative, while that of AO was positive. The pure effects of NAO and AO on SST are obscuring each other, due to the positive correlation between them. When decomposing SST, NAO and AO in seasonal values, we found that variation in mean annual SST and mean winter SST was significantly related to the mean autumn NAO of the previous year, while mean summer SST was related to mean autumn AO of the previous year. The one year delay in the effect of the NAO and AO on the SST could be partially related to the amount of accumulated snow, as we found a significant correlation between the total snow in the North Alborán watershed for a year with the annual average SST of the subsequent year. A positive AO implies a colder atmosphere in the Polar Regions, which could favour occasional cold waves over the Iberian Peninsula which, when coupled with precipitations favoured by a negative NAO, may result in snow precipitation. This snow may be accumulated in the high peaks and melt down in spring-summer of the following year, which consequently increases the runoff of freshwater to the sea, which in turn causes a diminution of sea surface salinity and density, and blocks the local upwelling of colder water, resulting in a higher SST. PMID:23638005

Decorrelation of L-band and C-band interferometry to volcanic risk prevention

NASA Astrophysics Data System (ADS)

Malinverni, E. S.; Sandwell, D.; Tassetti, A. N.; Cappelletti, L.

2013-10-01

SAR has several strong key features: fine spatial resolution/precision and high temporal pass frequency. Moreover, the InSAR technique allows the accurate detection of ground deformations. This high potential technology can be invaluable to study volcanoes: it provides important information on pre-eruption surface deformation, improving the understanding of volcanic processes and the ability to predict eruptions. As a downside, SAR measurements are influenced by artifacts such as atmospheric effects or bad topographic data. Correlation gives a measure of these interferences, quantifying the similarity of the phase of two SAR images. Different approaches exists to reduce these errors but the main concern remain the possibility to correlate images with different acquisition times: snow-covered or heavily-vegetated areas produce seasonal changes on the surface. Minimizing the time between passes partly limits decorrelation. Though, images with a short temporal baseline aren't always available and some artifacts affecting correlation are timeindependent. This work studies correlation of pairs of SAR images focusing on the influence of surface and climate conditions, especially snow coverage and temperature. Furthermore, the effects of the acquisition band on correlation are taken into account, comparing L-band and C-band images. All the chosen images cover most of the Yellowstone caldera (USA) over a span of 4 years, sampling all the seasons. Interferograms and correlation maps are generated. To isolate temporal decorrelation, pairs of images with the shortest baseline are chosen. Correlation maps are analyzed in relation to snow depth and temperature. Results obtained with ENVISAT and ERS satellites (C-band) are compared with the ones from ALOS (L-band). Results show a good performance during winter and a bad attitude towards wet snow (spring and fall). During summer both L-band and C-band maintain a good coherence with L-band performing better over vegetation.

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, respectively. Since Ganymede's core heat flux does not exceed values of 4 mW/m2 [2], we consider the snow zone to be stable against thermal convection. The time necessary to grow the snow zone across the core is between 230-1900 Myr. For representative models we calculate the temporal evolution of the surface dipolar magnetic field strength according to [5]. All models show surface dipolar magnetic field strengths during the evolution of the snow zone that match the observed value of |Bdip|≡719 nT. In conclusion, we find that the Fe-snow regime produces a stably-stratified liquid layer in the snow zone below which a magnetic field of observed strength can be generated. Such a chemical dynamo is restricted in time and stops as soon as an inner solid core starts to grow suggesting the absence of such an inner core in Ganymede. The present model further suggests a core with high initial sulfur concentration, because this leads to a late start and a long duration of the dynamo necessary to explain the present magnetic field. References [1] Kivelson, M et al. (1996), Nature, 384(6609), [2] Hauck II, S. et al. (2006), JGR, 111(E9), [3] Williams, Q. (2009), EPSL, 284(3), [4] Christensen, U. and J. Wicht (2007), Treatise of Geophysics, Elsevier, [5] Christensen, U., and J. Aubert (2006), GJI, 166(1)

Simulations of a Canadian snowpack brightness temperatures using SURFEX-Crocus for Snow Water Equivalent (SWE) retrievals

NASA Astrophysics Data System (ADS)

Larue, Fanny; Royer, Alain; De Sève, Danielle; Langlois, Alexandre; Roy, Alexandre; Saint-Jean-Rondeau, Olivier

2016-04-01

In Quebec, the water associated to snowmelt represents 30% of the annual electricity production so that the snow cover evaluation in real time is of primary interest. The key variable is snow water equivalent (SWE) which describes the evolution of a global seasonal snow cover. However, the sparse distribution of meteorological stations in northern Québec generates great uncertainty in the extrapolation of SWE. On the contrary, the spatial and temporal coverage of satellite data offer a source of information with a high potential when considered as an alternative to the poor spatial distribution of in-situ information. Thus, this project aims to improve the prediction of SWE by assimilation of satellite passive microwave brightness temperatures (Tb) observations, independently of any ground observations. The snowpack evolution is simulated by the French snow model SURFEX-Crocus, driven by the Canadian atmospheric model GEM with a spatial resolution of 10 km. The bias of the atmospheric model and the impact of initialization errors on the simulated SWE were quantified from our ground measurements. To assimilate satellite observations, the multi-layered snow model is first coupled with a radiative transfer model using the Dense Media Radiative transfer theory (the DMRT-ML model) to estimate the microwave snow emission of the simulated snowpack. In order to retrieve simulated Tb in frequencies of interest (i.e. sensitive to snow dielectric properties), the snow microstructure needs to be well parameterized. It was shown in previous studies that the specific surface area (SSA) of snow grains is a well-defined parameter to describe the size and the shape of snow grains and which allows reproducible field measurements. SURFEX-Crocus estimates a SSA for each simulated snow layer, however, the snow microstructure in DMRT-ML is defined per layer by monodisperse optical radius of grain (~ 1/SSA) and by the stickiness which is not known. It thus becomes necessary to introduce an empirical factor (noted φ) due to the simplification of the representation of snow as non-sticky spheres of ice in the model. In other words, the measured and simulated SSA has to be converted in an effective snow grain metric by optimizing this scaling factor to minimize the root-mean-square error between the measured and simulated brightness temperatures. The φ factor scaling the Crocus simulated SSA was estimated using ground-based radiometric measurements made during several field campaigns in the James Bay territory, Nunavik (in 2013 and 2015), and Churchill, Manitoba in 2010. This new parameterization, adapted to the Canadian arctic and subarctic snowpack, represents an essential step to optimize SWE maps in this remote region which have yet to be proven accurate.

Snow cover and temperature relationships in North America and Eurasia

NASA Technical Reports Server (NTRS)

Foster, J.; Owe, M.; Rango, A.

1983-01-01

In this study the snow cover extent during the autumn months in both North America and Eurasia has been related to the ensuing winter temperature as measured at several locations near the center of each continent. The relationship between autumn snow cover and the ensuing winter temperatures was found to be much better for Eurasia than for North America. For Eurasia the average snow cover extent during the autumn explained as much as 52 percent of the variance in the winter (December-February) temperatures compared to only 12 percent for North America. However, when the average winter snow cover was correlated with the average winter temperature it was found that the relationship was better for North America than for Eurasia. As much as 46 percent of the variance in the winter temperature was explained by the winter snow cover in North America compared to only 12 percent in Eurasia.

Refreezing on the Greenland ice sheet: a model comparison

NASA Astrophysics Data System (ADS)

Steger, Christian; Reijmer, Carleen; van den Broeke, Michiel; Ligtenberg, Stefan; Kuipers Munneke, Peter; Noël, Brice

2016-04-01

Mass loss of the Greenland ice sheet (GrIS) is an important contributor to global sea level rise. Besides calving, surface melt is the dominant source of mass loss. However, only part of the surface melt leaves the ice sheet as runoff whereas the other part percolates into the snow cover and refreezes. Due to this process, part of the meltwater is (intermediately) stored. Refreezing thus impacts the surface mass balance of the ice sheet but it also affects the vertical structure of the snow cover due to transport of mass and energy. Due to the sparse availability of in situ data and the demand of future projections, it is inevitable to use numerical models to simulate refreezing and related processes. Currently, the magnitude of refrozen mass is neither well constrained nor well validated. In this study, we model the snow and firn layer, and compare refreezing on the GrIS as modelled with two different numerical models. Both models are forced with meteorological data from the regional climate model RACMO 2 that has been shown to simulate realistic conditions for Greenland. One model is the UU/IMAU firn densification model (FDM) that can be used both in an on- and offline mode with RACMO 2. The other model is SNOWPACK; a model originally designed to simulate seasonal snow cover in alpine conditions. In contrast to FDM, SNOWPACK accounts for snow metamorphism and microstructure and contains a more physically based snow densification scheme. A first comparison of the models indicates that both seem to be able to capture the general spatial and temporal pattern of refreezing. Spatially, refreezing occurs mostly in the ablation zone and decreases in the accumulation zone towards the interior of the ice sheet. Below the equilibrium line altitude (ELA) where refreezing occurs in seasonal snow cover on bare ice, the storage effect is only intermediate. Temporal patterns on a seasonal range indicate two peaks in refreezing; one at the beginning of the melt season where water infiltrates the cold snow pack and one in early winter where the penetration of the cold surface temperature refreezes the retained liquid water. However, the model comparison reveals differences especially close to the equilibrium line where refreezing and runoff seem to be highly sensitive to the exact model formulation and fresh snow density initialization. Furthermore, SNOWPACK's densification scheme generally underestimates densification rates in case of high overburden pressure.

Improved NLDAS-2 Noah-simulated Hydrometeorological Products with an Interim Run

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

Xia, Youlong; Peter-Lidard, Christa; Huang, Maoyi

2015-02-28

In NLDAS-2 Noah simulation, the NLDAS team introduced an intermediate fix suggested by Slater et al. (2007) and Livneh et al. (2010) to reduce large sublimation. The fix is used to constraint surface exchange coefficient (CH) using CH =CHoriginal x max (1.0-RiB/0.5, 0.05) when atmospheric boundary layer is stable. RiB is Richardson number. In NLDAS-2 Noah version, this fix was used for all stable cases including snow-free grid cells. In this study, we simply applied this fix to the grid cells in which both stable atmospheric boundary layer and snow exist simultaneously excluding the snow-free grid cells as we recognizemore » that the fix constraint in NLDAS-2 is too strong. We make a 31-year (1979-2009) Noah NLDAS-2 interim (NoahI) run. We use observed streamflow, evapotranspiration, land surface temperature, soil temperature, and ground heat flux to evaluate the results simulated from NoahI and make the reasonable comparison with those simulated from NLDAS-2 Noah (Xia et al., 2012). The results show that NoahI has the same performance as Noah does for snow water equivalent simulation. However, NoahI significantly improved the other hydrometeorological products’ simulation as described above when compared to Noah and the observations. This simple modification is being installed to the next Noah version. The hydrometeorological products simulated from NoahI will be staged on NCEP public server for the public in future.« less

Potential weathering by freeze-thaw action in alpine rocks in the European Alps during a nine year monitoring period

NASA Astrophysics Data System (ADS)

Kellerer-Pirklbauer, Andreas

2017-11-01

A quantification of rock weathering by freeze-thaw processes in alpine rocks requires at least rock temperature data in high temporal resolution, in high quality, and over a sufficient period of time. In this study up to nine years of rock temperature data (2006-2015) from eleven rock monitoring sites in two of the highest mountain ranges of Austria were analyzed. Data were recorded at a half-hourly or hourly logging interval and at rock depths of 3, 10, and 30-40 cm. These data have been used to quantify mean conditions, ranges, and relationships of the potential near-surface weathering by freeze-thaw action considering volumetric-expansion of ice and ice segregation. For the former, freeze-thaw cycles and effective freeze-thaw cycles for frost shattering have been considered. For the latter, the intensity and duration of freezing events as well as time within the 'frost cracking window' have been analyzed. Results show that the eleven sites are in rather extreme topoclimatic positions and hence represent some of the highest and coolest parts of Austria and therefore the Eastern Alps. Only four sites are presumably affected by permafrost. Most sites are influenced by a long-lasting seasonal snow cover. Freeze-thaw cycles and effective freeze-thaw cycles for frost shattering are mainly affecting the near-surface and are unimportant at few tens of centimeters below the rock surface. The lowest temperatures during freezing events and the shortest freezing events have been quantified at all eleven monitoring sites very close to the surface. The time within the frost cracking window decreases in most cases from the rock surface inwards apart from very cold years/sites with very low temperatures close to the surface. As shown by this study and predicted climate change scenarios, assumed warmer rock temperature conditions in the future at alpine rock walls in Austria will lead to less severe freezing events and to shorter time periods within the frost-cracking window. Statistical correlation analyses showed furthermore that the longer the duration of the seasonal snow cover, the fewer are freeze-thaw cycles, the fewer are effective freeze-thaw cycles, the longer is the mean and the maximum duration of freezing events, and the lower is the mean annual ground temperature. The interaction of the winter snow cover history and the winter thermal regime has a complex effect on the duration of the frost cracking window but also on the number of freeze-thaw cycles as shown by a conceptual model. Predicted future warmer and snow-depleted winters in the European Alps will therefore have a complex impact on the potential weathering of alpine rocks by frost action which makes potential weathering predictions difficult. Neglecting rock moisture and rock properties in determining rock weathering limits the usefulness of solely rock temperature data. However, rock temperature data allow getting an estimate about potential weathering by freeze-thaw action which is often substantially more than previously known.

The Role of Snow Thickness over Arctic Winter Sea Ice in the Survival and Dispersal of Brine-Derived Microbes

NASA Astrophysics Data System (ADS)

Deming, J. W.; Ewert, M.; Bowman, J. S.

2013-12-01

The brines of polar winter sea ice are inhabited by significant densities of microbes (Bacteria and Archaea) that experience a range of extreme conditions depending on location in, and age of, the ice. Newly formed sea ice in winter expels microbes (and organic exudates) onto the surface of the ice, where they can be wicked into frost flowers or into freshly deposited snow, resulting in populations at the ice-air and air-snow interfaces characterized by even more extreme conditions. The influence of snow thickness over the ice on the fate of these microbes, and their potential for dispersal or mediation of exchanges with other components of the ice-snow system, is not well known. Examination of in situ temperature data from the Mass Balance Observatory (MBO) offshore of Barrow, Alaska, during the winter of 2011 allowed recognition of an hierarchy of fluctuation regimes in temperature and (by calculation) brine salinity, where the most stable conditions were encountered within the sea ice and the least stable highest in the snow cover, where temperature fluctuations were significantly more energetic as determined by an analysis of power spectral density. A prior analysis of snow thickness near the MBO had already revealed significant ablation events, potentially associated with bacterial mortality, that would have exposed the saline (microbe-rich) snow layer to wind-based dispersal. To better understand the survival of marine bacteria under these dynamic and extreme conditions, we conducted laboratory experiments with Arctic bacterial isolates, subjecting them to simulations of the freezing regimes documented at the MBS. The impact of the fluctuation regime was shown to be species-specific, with the organism of narrower temperature and salinity growth ranges suffering 30-50% mortality (which could be partially relieved by providing protection against salt-shock). This isolate, the psychrophilic marine bacterium Colwellia psychrerythraea strain 34H (temperature range of -12 to 18°C, salinity range of 20 to 50), was originally isolated from Arctic marine sediments. The other isolate, the psychrotolerant and extremely halophilic bacterium Psychrobacter sp. strain 7E (temperature range of -1 [possibly lower] to 25°C, salinity range of 32 to 125), not only survived the most extreme conditions but demonstrated a potentially effective dispersal strategy of cell fragmentation and miniaturization (resulting in higher cell numbers). This extremophile was isolated from upper winter sea-ice brine in the Beaufort Sea. Bacterial survival and dispersal from sea-ice brines in Arctic winter thus appears to depend on the nature of the organisms involved and on the thickness of snow cover, which determines how dynamic and extreme are the exposure conditions. The observed species-specific reactions to extreme and fluctuating conditions may help to explain the different structures of microbial communities inhabiting the range of environments defined by the ice-snow system and provide model organisms and research directions for future work to evaluate potential activity or exchanges with other components of the system.

The classification of the Arctic Sea ice types and the determination of surface temperature using advanced very high resolution radiometer data

NASA Technical Reports Server (NTRS)

Massom, Robert; Comiso, Josefino C.

1994-01-01

The accurate quantification of new ice and open water areas and surface temperatures within the sea ice packs is a key to the realistic parameterization of heat, moisture, and turbulence fluxes between ocean and atmosphere in the polar regions. Multispectral NOAA advanced very high resolution radiometer/2 (AVHRR/2) satellite images are analyzed to evaluate how effectively the data can be used to characterize sea ice in the Bering and Greenland seas, both in terms of surface type and physical temperature. The basis of the classification algorithm, which is developed using a late wintertime Bering Sea ice cover data, is that frequency distributions of 10.8- micrometers radiances provide four distinct peaks, represeting open water, new ice, young ice, and thick ice with a snow cover. The results are found to be spatially and temporally consistent. Possible sources of ambiguity, especially associated with wider temporal and spatial application of the technique, are discussed. An ice surface temperature algorithm is developed for the same study area by regressing thermal infrared data from 10.8- and 12.0- micrometers channels against station air temperatures, which are assumed to approximate the skin temperatures of adjacent snow and ice. The standard deviations of the results when compared with in situ data are about 0.5 K over leads and polynyas to about 0.5-1.5 K over thick ice. This study is based upon a set of in situ data limited in scope and coverage. Cloud masks are applied using a thresholding technique that utilizes 3.74- and 10.8- micrometers channel data. The temperature maps produced show coherence with surface features like new ice and leads, and consistency with corresponding surface type maps. Further studies are needed to better understand the effects of both the spatial and temporal variability in emissivity, aerosol and precipitable atmospheric ice particle distribution, and atmospheric temperature inversions.

Altitude dependency of future snow cover changes over Central Japan evaluated by a regional climate model

NASA Astrophysics Data System (ADS)

Kawase, Hiroaki; Hara, Masayuki; Yoshikane, Takao; Ishizaki, Noriko N.; Uno, Fumichika; Hatsushika, Hiroaki; Kimura, Fujio

2013-11-01

Sea of Japan side of Central Japan is one of the heaviest snowfall areas in the world. We investigate near-future snow cover changes on the Sea of Japan side using a regional climate model. We perform the pseudo global warming (PGW) downscaling based on the five global climate models (GCMs). The changes in snow cover strongly depend on the elevation; decrease in the ratios of snow cover is larger in the lower elevations. The decrease ratios of the maximum accumulated snowfall in the short term, such as 1 day, are smaller than those in the long term, such as 1 week. We conduct the PGW experiments focusing on specific periods when a 2 K warming at 850 hPa is projected by the individual GCMs (PGW-2K85). The PGW-2K85 experiments show different changes in precipitation, resulting in snow cover changes in spite of similar warming conditions. Simplified sensitivity experiments that assume homogenous warming of the atmosphere (2 K) and the sea surface show that the altitude dependency of snow cover changes is similar to that in the PGW-2K85 experiments, while the uncertainty of changes in the sea surface temperature influences the snow cover changes both in the lower and higher elevations. The decrease in snowfall is, however, underestimated in the simplified sensitivity experiments as compared with the PGW experiments. Most GCMs project an increase in dry static stability and some GCMs project an anticyclonic anomaly over Central Japan, indicating the inhibition of precipitation, including snowfall, in the PGW experiments.

Summertime evolution of snow specific surface area close to the surface on the Antarctic Plateau

NASA Astrophysics Data System (ADS)

Libois, Q.; Picard, G.; Arnaud, L.; Dumont, M.; Lafaysse, M.; Morin, S.; Lefebvre, E.

2015-12-01

On the Antarctic Plateau, snow specific surface area (SSA) close to the surface shows complex variations at daily to seasonal scales which affect the surface albedo and in turn the surface energy budget of the ice sheet. While snow metamorphism, precipitation and strong wind events are known to drive SSA variations, usually in opposite ways, their relative contributions remain unclear. Here, a comprehensive set of SSA observations at Dome C is analysed with respect to meteorological conditions to assess the respective roles of these factors. The results show an average 2-to-3-fold SSA decrease from October to February in the topmost 10 cm in response to the increase of air temperature and absorption of solar radiation in the snowpack during spring and summer. Surface SSA is also characterized by significant daily to weekly variations due to the deposition of small crystals with SSA up to 100 m2 kg-1 onto the surface during snowfall and blowing snow events. To complement these field observations, the detailed snowpack model Crocus is used to simulate SSA, with the intent to further investigate the previously found correlation between interannual variability of summer SSA decrease and summer precipitation amount. To this end, some Crocus parameterizations have been adapted to Dome C conditions, and the model was forced by ERA-Interim reanalysis. It successfully matches the observations at daily to seasonal timescales, except for the few cases when snowfalls are not captured by the reanalysis. On the contrary, the interannual variability of summer SSA decrease is poorly simulated when compared to 14 years of microwave satellite data sensitive to the near-surface SSA. A simulation with disabled summer precipitation confirms the weak influence in the model of the precipitation on metamorphism, with only 6 % enhancement. However, we found that disabling strong wind events in the model is sufficient to reconciliate the simulations with the observations. This suggests that Crocus reproduces well the contributions of metamorphism and precipitation on surface SSA, but snow compaction by the wind might be overestimated in the model.

Summertime evolution of snow specific surface area close to the surface on the Antarctic Plateau

NASA Astrophysics Data System (ADS)

Libois, Q.; Picard, G.; Arnaud, L.; Dumont, M.; Lafaysse, M.; Morin, S.; Lefebvre, E.

2015-08-01

On the Antarctic Plateau, snow specific surface area (SSA) close to the surface shows complex variations at daily to seasonal scales which affect the surface albedo and in turn the surface energy budget of the ice sheet. While snow metamorphism, precipitation and strong wind events are known to drive SSA variations, usually in opposite ways, their relative contributions remain unclear. Here, a comprehensive set of SSA observations at Dome C is analysed with respect to meteorological conditions to assess the respective roles of these factors. The results show an average two-to-three-fold SSA decrease from October to February in the topmost 10 cm, in response to the increase of air temperature and absorption of solar radiation in the snowpack during spring and summer. Surface SSA is also characterised by significant daily to weekly variations, due to the deposition of small crystals with SSA up to 100 m2 kg-1 onto the surface during snowfall and blowing snow events. To complement these field observations, the detailed snowpack model Crocus is used to simulate SSA, with the intent to further investigate the previously found correlation between inter-annual variability of summer SSA decrease and summer precipitation amount. To this end, Crocus parameterizations have been adapted to Dome C conditions, and the model was forced by ERA-Interim reanalysis. It successfully matches the observations at daily to seasonal time scales, except for few cases when snowfalls are not captured by the reanalysis. On the contrary, the inter-annual variability of summer SSA decrease is poorly simulated when compared to 14 years of microwave satellite data sensititve to the near surface SSA. A simulation with disabled summer precipitation confirms the weak influence in the model of the precipitation on metamorphism, with only 6 % enhancement. However we found that disabling strong wind events in the model is sufficient to reconciliate the simulations with the observations. This suggests that Crocus reproduces well the contributions of metamorphism and precipitation on surface SSA, but that snow compaction by the wind might be overestimated in the model.

Simulating polarized light scattering in terrestrial snow based on bicontinuous random medium and Monte Carlo ray tracing

NASA Astrophysics Data System (ADS)

Xiong, Chuan; Shi, Jiancheng

2014-01-01

To date, the light scattering models of snow consider very little about the real snow microstructures. The ideal spherical or other single shaped particle assumptions in previous snow light scattering models can cause error in light scattering modeling of snow and further cause errors in remote sensing inversion algorithms. This paper tries to build up a snow polarized reflectance model based on bicontinuous medium, with which the real snow microstructure is considered. The accurate specific surface area of bicontinuous medium can be analytically derived. The polarized Monte Carlo ray tracing technique is applied to the computer generated bicontinuous medium. With proper algorithms, the snow surface albedo, bidirectional reflectance distribution function (BRDF) and polarized BRDF can be simulated. The validation of model predicted spectral albedo and bidirectional reflectance factor (BRF) using experiment data shows good results. The relationship between snow surface albedo and snow specific surface area (SSA) were predicted, and this relationship can be used for future improvement of snow specific surface area (SSA) inversion algorithms. The model predicted polarized reflectance is validated and proved accurate, which can be further applied in polarized remote sensing.

The influence of air temperature inversions on snowmelt and glacier mass-balance simulations, Ammassalik island, SE Greenland

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

Mernild, Sebastian Haugard; Liston, Glen

2009-01-01

In many applications, a realistic description of air temperature inversions is essential for accurate snow and glacier ice melt, and glacier mass-balance simulations. A physically based snow-evolution modeling system (SnowModel) was used to simulate eight years (1998/99 to 2005/06) of snow accumulation and snow and glacier ice ablation from numerous small coastal marginal glaciers on the SW-part of Ammassalik Island in SE Greenland. These glaciers are regularly influenced by inversions and sea breezes associated with the adjacent relatively low temperature and frequently ice-choked fjords and ocean. To account for the influence of these inversions on the spatiotemporal variation of airmore » temperature and snow and glacier melt rates, temperature inversion routines were added to MircoMet, the meteorological distribution sub-model used in SnowModel. The inversions were observed and modeled to occur during 84% of the simulation period. Modeled inversions were defined not to occur during days with strong winds and high precipitation rates due to the potential of inversion break-up. Field observations showed inversions to extend from sea level to approximately 300 m a.s.l., and this inversion level was prescribed in the model simulations. Simulations with and without the inversion routines were compared. The inversion model produced air temperature distributions with warmer lower elevation areas and cooler higher elevation areas than without inversion routines due to the use of cold sea-breeze base temperature data from underneath the inversion. This yielded an up to 2 weeks earlier snowmelt in the lower areas and up to 1 to 3 weeks later snowmelt in the higher elevation areas of the simulation domain. Averaged mean annual modeled surface mass-balance for all glaciers (mainly located above the inversion layer) was -720 {+-} 620 mm w.eq. y{sup -1} for inversion simulations, and -880 {+-} 620 mm w.eq. y{sup -1} without the inversion routines, a difference of 160 mm w.eq. y{sup -1}. The annual glacier loss for the two simulations was 50.7 x 10{sup 6} m{sup 3} y{sup -1} and 64.4 x 10{sup 6} m{sup 3} y{sup -1} for all glaciers - a difference of {approx}21%. The average equilibrium line altitude (ELA) for all glaciers in the simulation domain was located at 875 m a.s.l. and at 900 m a.s.l. for simulations with or without inversion routines, respectively.« less

Land Surface Temperature Measurements from EOD MODIS Data

NASA Technical Reports Server (NTRS)

Wan, Zheng-Ming

1998-01-01

We made more tests of the version 2.0 daily Level 2 and Level 3 Land-Surface Temperature (LST) code (PGE 16) jointly with the MODIS Science Data Support Team (SDST). After making minor changes a few times, the PGE16 code has been successfully integrated and tested by MODIS SDST, and recently has passed the inspection at the Goddard Distributed Active Archive Center (DAAC). We conducted a field campaign in the area of Mono Lake, California on March 10, 1998, in order to validate the MODIS LST algorithm in cold and dry conditions. Two MODIS Airborne Simulator (MAS) flights were completed during the field campaign, one before noon, and another around 10 pm PST. The weather condition for the daytime flight was perfect: clear sky, the column water vapor measured by radiosonde around 0.3 cm, and wind speed less than a half meter per second. The quality of MAS data is good for both day and night flights. We analyzed the noise equivalent temperature difference (NE(delta)T) and the calibration accuracy of the seven MAS thermal infrared (TIR) bands, that are used in the MODIS day/night LST algorithm, with daytime MAS data over four flat homogeneous study areas: two on Grant Lake (covered with ice and snow, respectively), one on Mono Lake, and another on the snow field site where we made field measurements. NE(delta)T ranges from 0.2 to 0.6 k for bands 42, 45, 46, and 48. It ranges from 0.8 to 1.1 K for bands 30-32. The day and night MAS data have been used to retrieve surface temperature and emissivities in these bands. A simple method to correct the effect of night thin cirrus has been incorporated into the day/night LST algorithm in dry atmospheric conditions. We compared the retrieved surface temperatures with those measured with TIR spectrometer, radiometers and thermistors in the snow test site, and the retrieved emissivity images with topographic map. The daytime LST values match well within 1 K. The night LST retrieved from MAS data is 3.3 K colder than those from field measurements most likely because of the effect of haze at night. The good agreement among the regional averaged surface temperatures obtained from LST values retrieved at different resolutions increased our confidence in the MODIS day/night LST algorithm.

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...

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.

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.

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.

Spatiotemporal variability of snow depth across the Eurasian continent from 1966 to 2012

NASA Astrophysics Data System (ADS)

Zhong, Xinyue; Zhang, Tingjun; Kang, Shichang; Wang, Kang; Zheng, Lei; Hu, Yuantao; Wang, Huijuan

2018-01-01

Snow depth is one of the key physical parameters for understanding land surface energy balance, soil thermal regime, water cycle, and assessing water resources from local community to regional industrial water supply. Previous studies by using in situ data are mostly site specific; data from satellite remote sensing may cover a large area or global scale, but uncertainties remain large. The primary objective of this study is to investigate spatial variability and temporal change in snow depth across the Eurasian continent. Data used include long-term (1966-2012) ground-based measurements from 1814 stations. Spatially, long-term (1971-2000) mean annual snow depths of >20 cm were recorded in northeastern European Russia, the Yenisei River basin, Kamchatka Peninsula, and Sakhalin. Annual mean and maximum snow depth increased by 0.2 and 0.6 cm decade-1 from 1966 through 2012. Seasonally, monthly mean snow depth decreased in autumn and increased in winter and spring over the study period. Regionally, snow depth significantly increased in areas north of 50° N. Compared with air temperature, snowfall had greater influence on snow depth during November through March across the former Soviet Union. This study provides a baseline for snow depth climatology and changes across the Eurasian continent, which would significantly help to better understanding climate system and climate changes on regional, hemispheric, or even global scales.

Modeling Episodic Surface Runoff in an Arid Environment

NASA Astrophysics Data System (ADS)

Waichler, S. R.; Wigmosta, M. S.

2003-12-01

Methods were developed for estimating episodic surface runoff in arid eastern Washington, USA. Small (1--10 km2) catchments in this region with mean annual precipitation around 180 mm produce runoff in about half the years, and such events usually occur during winter when a widespread cold snap and possible snow accumulation is followed by warmer temperatures and rainfall. Existence of frozen soil appears to be a key factor, and a moving average of air temperature is an effective predictor of soil temperature. The watershed model DHSVM simulates snow accumulation and ablation reasonably well at a monitoring location, but the same model applied in distributed mode across a 850 km2 basin overpredicts runoff. Inadequate definition of local meteorology appears to limit the accuracy of runoff predictions. However, runoff estimates of sufficient quality to support modeling of long-term groundwater recharge and sediment transport may be found in focusing on recurrence intervals and volumes rather than hydrographs. Usefulness of upland watershed modeling to environmental management of the Hanford Site and an adjacent military reservation will likely improve through sensitivity analysis of basic assumptions about upland water balance.

Modeling the influence of snow cover temperature and water content on wet-snow avalanche runout

NASA Astrophysics Data System (ADS)

Valero, Cesar Vera; Wever, Nander; Christen, Marc; Bartelt, Perry

2018-03-01

Snow avalanche motion is strongly dependent on the temperature and water content of the snow cover. In this paper we use a snow cover model, driven by measured meteorological data, to set the initial and boundary conditions for wet-snow avalanche calculations. The snow cover model provides estimates of snow height, density, temperature and liquid water content. This information is used to prescribe fracture heights and erosion heights for an avalanche dynamics model. We compare simulated runout distances with observed avalanche deposition fields using a contingency table analysis. Our analysis of the simulations reveals a large variability in predicted runout for tracks with flat terraces and gradual slope transitions to the runout zone. Reliable estimates of avalanche mass (height and density) in the release and erosion zones are identified to be more important than an exact specification of temperature and water content. For wet-snow avalanches, this implies that the layers where meltwater accumulates in the release zone must be identified accurately as this defines the height of the fracture slab and therefore the release mass. Advanced thermomechanical models appear to be better suited to simulate wet-snow avalanche inundation areas than existing guideline procedures if and only if accurate snow cover information is available.

The Implement of a Multi-layer Frozen Soil Scheme into SSiB3 and its Evaluation over Cold Regions

NASA Astrophysics Data System (ADS)

Li, Q.

2016-12-01

The SSiB3 is a biophysics-based model of land-atmosphere interactions and is designed for global and regional studies. It has three soil layers, three snow layers, as well as one vegetation layer. Soil moisture of the three soil layers, interception water store for the canopy, subsurface soil temperature, ground temperature, canopy temperature and snow water equivalent are all predicted based on the water and energy balance at canopy, soil and snow. SSiB3 substantially enhances the model's capability for cold season studies and produces reasonable results compared with observations. However, frozen soil processes are ignored in the SSiB3 and may have effects on the interannual variability of soil temperature and deep soil memory. A multi-layer comprehensive frozen soil scheme (FSM), which is developed for climate study has been implemented into the SSiB3 to describe soil heat transfer and water flow affected by frozen processed in soil. In the coupled SSiB3-FSM, both liquid water and ice content have been taken into account in the frozen soil hydrologic and thermal property parameterization. The maximum soil layer depth could reach 10 meters thick depending on land conditions. To better evaluate the models' performance, the coupled offline SSiB3-FSM and SSiB3 have been driven from 1948 to 1958 by the Princeton global meteorological data set, respectively. For the 10yrs run, the coupled SSiB3-FSM almost captures the features over different regions, especially cold regions. In order to analysis and compare the differences of SSIB3-FSM and SSIB3 in detail, monthly mean surface temperature for different regions are compared with CAMS data. The statistical results of surface skin temperature show that high latitude regions, Africa, Eastern Australia, and North American monsoon regions have been greatly improved in SSIB3-FSM. For the global statistics, the RMSE of the surface temperature simulated by SSiB3-FSM can be improved about 0.6K compared to SSiB3. In this study, the improvements in the coupled SSiB3-FSM have also been analyzed.

What Does a Multilayer Canopy Model Tell Us About Our Current Understanding of Snow-Canopy Unloading?

NASA Astrophysics Data System (ADS)

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

2017-12-01

In the Western U.S., future water resources depend on the forested mountain snowpack. The variations in and estimates of forest mountain snow volume are vital to projecting annual water availability; yet, snow forest processes are not fully known. Most snow models calculate snow-canopy unloading based on time, temperature, Leaf Area Index (LAI), and/or wind speed. While models crudely consider the canopy shape via LAI, current models typically do not consider the vertical canopy structure or varied energetics within multiple canopy layers. Vertical canopy structure influences the spatiotemporal distribution of snow, and therefore ultimately determines the degree and extent by which snow alters both the surface energy balance and water availability. Within the canopy both the snowpack and energetic exposures to the snowpack (wind, shortwave and longwave radiation, turbulent heat fluxes etc.) vary widely in the vertical. The water and energy balance in each layer is dependent on all other layers. For example, increased snow canopy content in the top of the canopy will reduce available shortwave radiation at the bottom and snow unloading in a mid-layer can cascade and remove snow from all the lower layers. We examined vertical interactions and structures of the forest canopy on the impact of unloading utilizing the Advanced Canopy-Atmosphere-Soil-Algorithm (ACASA), a multilayer soil-vegetation-atmosphere numerical model based on higher-order closure of turbulence equations. Our results demonstrate how a multilayer model can be used to elucidate the physical processes of snow unloading, and could help researchers better parameterize unloading in snow-hydrology models.

European In-Situ Snow Measurements: Practices and Purposes.

PubMed

Pirazzini, Roberta; Leppänen, Leena; Picard, Ghislain; Lopez-Moreno, Juan Ignacio; Marty, Christoph; Macelloni, Giovanni; Kontu, Anna; von Lerber, Annakaisa; Tanis, Cemal Melih; Schneebeli, Martin; de Rosnay, Patricia; Arslan, Ali Nadir

2018-06-22

In-situ snow measurements conducted by European institutions for operational, research, and energy business applications were surveyed in the framework of the European Cooperation in Science and Technology (COST) Action ES1404, called "A European network for a harmonised monitoring of snow for the benefit of climate change scenarios, hydrology, and numerical weather prediction". Here we present the results of this survey, which was answered by 125 participants from 99 operational and research institutions, belonging to 38 European countries. The typologies of environments where the snow measurements are performed range from mountain to low elevated plains, including forests, bogs, tundra, urban areas, glaciers, lake ice, and sea ice. Of the respondents, 93% measure snow macrophysical parameters, such as snow presence, snow depth (HS), snow water equivalent (SWE), and snow density. These describe the bulk characteristics of the whole snowpack or of a snow layer, and they are the primary snow properties that are needed for most operational applications (such as hydrological monitoring, avalanche forecast, and weather forecast). In most cases, these measurements are done with manual methods, although for snow presence, HS, and SWE, automatized methods are also applied by some respondents. Parameters characterizing precipitating and suspended snow (such as the height of new snow, precipitation intensity, flux of drifting/blowing snow, and particle size distribution), some of which are crucial for the operational services, are measured by 74% of the respondents. Parameters characterizing the snow microstructural properties (such as the snow grain size and shape, and specific surface area), the snow electromagnetic properties (such as albedo, brightness temperature, and backscatter), and the snow composition (such as impurities and isotopes) are measured by 41%, 26%, and 13% of the respondents, respectively, mostly for research applications. The results of this survey are discussed from the perspective of the need of enhancing the efficiency and coverage of the in-situ observational network applying automatic and cheap measurement methods. Moreover, recommendations for the enhancement and harmonization of the observational network and measurement practices are provided.

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 exchanges. The model is driven by observed forcing meteorological data (air temperature, wind velocity, relative air humidity, precipitation and incident solar radiation) to provide an estimation of the snowpack state. In this study, no DA is used. For more details on the DA scheme, please see EGU2017-7777. Observed data supplied by meteorological stations located in three experimental Alpine sites are used: Col de Porte (1325 m, France); Torgnon (2160 m, Italy); Weissfluhjoch (2540 m, Switzerland). Performances of the two models are compared through evaluations of snow mass, snow depth, albedo and surface temperature simulations in order to better understand and pinpoint limits and potentialities of the analyzed schemes and the impact of different parameterizations on models simulations.

How much can we save? Impact of different emission scenarios on future snow cover in the Alps

NASA Astrophysics Data System (ADS)

Marty, Christoph; Schlögl, Sebastian; Bavay, Mathias; Lehning, Michael

2017-02-01

This study focuses on an assessment of the future snow depth for two larger Alpine catchments. Automatic weather station data from two diverse regions in the Swiss Alps have been used as input for the Alpine3D surface process model to compute the snow cover at a 200 m horizontal resolution for the reference period (1999-2012). Future temperature and precipitation changes have been computed from 20 downscaled GCM-RCM chains for three different emission scenarios, including one intervention scenario (2 °C target) and for three future time periods (2020-2049, 2045-2074, 2070-2099). By applying simple daily change values to measured time series of temperature and precipitation, small-scale climate scenarios have been calculated for the median estimate and extreme changes. The projections reveal a decrease in snow depth for all elevations, time periods and emission scenarios. The non-intervention scenarios demonstrate a decrease of about 50 % even for elevations above 3000 m. The most affected elevation zone for climate change is located below 1200 m, where the simulations show almost no snow towards the end of the century. Depending on the emission scenario and elevation zone the winter season starts half a month to 1 month later and ends 1 to 3 months earlier in this last scenario period. The resulting snow cover changes may be roughly equivalent to an elevation shift of 500-800 or 700-1000 m for the two non-intervention emission scenarios. At the end of the century the number of snow days may be more than halved at an elevation of around 1500 m and only 0-2 snow days are predicted in the lowlands. The results for the intervention scenario reveal no differences for the first scenario period but clearly demonstrate a stabilization thereafter, comprising much lower snow cover reductions towards the end of the century (ca. 30 % instead of 70 %).

Ultraviolet radiation and the snow alga Chlamydomonas nivalis (Bauer) Wille.

PubMed

Gorton, Holly L; Vogelmann, Thomas C

2003-06-01

Aplanospores of Chlamydomonas nivalis are frequently found in high-altitude, persistent snowfields where they are photosynthetically active despite cold temperatures and high levels of visible and ultraviolet (UV) radiation. The goals of this work were to characterize the UV environment of the cells in the snow and to investigate the existence and localization of screening compounds that might prevent UV damage. UV irradiance decreased precipitously in snow, with UV radiation of wavelengths 280-315 nm and UV radiation of wavelengths 315-400 nm dropping to 50% of incident levels in the top 1 and 2 cm, respectively. Isolated cell walls exhibited UV absorbance, possibly by sporopollenin, but this absorbance was weak in images of broken or plasmolyzed cells observed through a UV microscope. The cells also contained UV-absorbing cytoplasmic compounds, with the extrachloroplastic carotenoid astaxanthin providing most of the screening. Additional screening compound(s) soluble in aqueous methanol with an absorption maximum at 335 nm played a minor role. Thus, cells are protected against potentially high levels of UV radiation by the snow itself when they live several centimeters beneath the surface, and they rely on cellular screening compounds, chiefly astaxanthin, when located near the surface where UV fluxes are high.

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.

Computational design of the basic dynamical processes of the UCLA general circulation model

NASA Technical Reports Server (NTRS)

Arakawa, A.; Lamb, V. R.

1977-01-01

The 12-layer UCLA general circulation model encompassing troposphere and stratosphere (and superjacent 'sponge layer') is described. Prognostic variables are: surface pressure, horizontal velocity, temperature, water vapor and ozone in each layer, planetary boundary layer (PBL) depth, temperature, moisture and momentum discontinuities at PBL top, ground temperature and water storage, and mass of snow on ground. Selection of space finite-difference schemes for homogeneous incompressible flow, with/without a free surface, nonlinear two-dimensional nondivergent flow, enstrophy conserving schemes, momentum advection schemes, vertical and horizontal difference schemes, and time differencing schemes are discussed.

On the relationship between the snowflake type aloft and the surface precipitation types at temperatures near 0 °C

NASA Astrophysics Data System (ADS)

Sankaré, Housseyni; Thériault, Julie M.

2016-11-01

Winter precipitation types can have major consequences on power outages, road conditions and air transportation. The type of precipitation reaching the surface depends strongly on the vertical temperature of the atmosphere, which is often composed of a warm layer aloft and a refreezing layer below it. A small variation of the vertical structure can lead to a change in the type of precipitation near the surface. It has been shown in previous studies that the type of precipitation depends also on the precipitation rate, which is directly linked to the particle size distribution and that a difference as low as 0.5 °C in the vertical temperature profile could change the type of precipitation near the surface. Given the importance of better understanding the formation of winter precipitation type, the goal of this study is to assess the impact of the snowflake habit aloft on the type of precipitation reaching the surface when the vertical temperature is near 0 °C. To address this, a one dimensional cloud model coupled with a bulk microphysics scheme was used. Four snowflake types (dendrite, bullet, column and graupel) have been added to the scheme. The production of precipitation at the surface from these types of snow has been compared to available observations. The results showed that the thickness of the snow-rain transition is four times deeper when columns and graupel only fall through the atmosphere compared to dendrites. Furthermore, a temperature of the melting layer that is three (four) times warmer is required to completely melt columns and graupel (dendrites). Finally, the formation of freezing rain is associated with the presence of lower density snowflakes (dendrites) aloft compared to the production of ice pellets (columns). Overall, this study demonstrated that the type of snowflakes has an impact on the type of precipitation reaching the surface when the temperature is near 0 °C.

Assessment of the Barren Ground Caribou Die-off During Winter 2015-2016 Using Passive Microwave Observations

NASA Astrophysics Data System (ADS)

Dolant, C.; Montpetit, B.; Langlois, A.; Brucker, L.; Zolina, O.; Johnson, C. A.; Royer, A.; Smith, P.

2018-05-01

In summer 2016, more than 50 Arctic Barren Ground caribous were found dead on Prince Charles Island (Nunavut, Canada), a species recently classified as threatened. Neither predator nor sign of diseases was observed and reported. The main hypothesis is that caribous were not able to access food due to a very dense snow surface, created by a strong storm system in spring. Using satellite microwave data, a significant increase in brightness temperature polarization ratio at 19 and 37 GHz was observed in spring 2016 (60% higher than previous two winter seasons). Based on microwave radiative transfer simulations, such anomaly can be explained with a very dense snow surface. This is consistent with the succession of storms and strong winds highlighted in ERA-Interim over Prince Charles Island in spring 2016. Using several sources of data, this study shows that changes in snow conditions explain the caribou die-off due to restricted foraging.

Melting Frozen Droplets Using Photo-Thermal Traps

NASA Astrophysics Data System (ADS)

Dash, Susmita; de Ruiter, Jolet; Varanasi, Kripa

2017-11-01

Ice buildup is an operational and safety hazard in wind turbines, power lines, and airplanes. While traditional de-icing methods are energy-intensive or environmentally unfriendly, passive anti-icing approach using superhydrophobic surfaces fails under humid conditions, which necessitates development of passive deicing methods. Here, we investigate a passive technique for deicing using a multi-layer surface design that can efficiently absorb and convert the incident solar radiation to heat. The corresponding increase in substrate temperature allows for easy removal of frozen droplets from the surface. We demonstrate the deicing performance of the designed surface both at very low temperatures, and under frost and snow coverage.

NASA Cold Land Processes Experiment (CLPX 2002/03): Field measurements of snowpack properties and soil moisture

Treesearch

Kelly Elder; Don Cline; Glen E. Liston; Richard Armstrong

2009-01-01

A field measurement program was undertaken as part NASA's Cold Land Processes Experiment (CLPX). Extensive snowpack and soil measurements were taken at field sites in Colorado over four study periods during the two study years (2002 and 2003). Measurements included snow depth, density, temperature, grain type and size, surface wetness, surface roughness, and...

The snowmaker: nature identical snow production in the laboratory

NASA Astrophysics Data System (ADS)

Schleef, S.; Jaggi, M.; Loewe, H.; Schneebeli, M.

2013-12-01

Using natural snow for laboratory experiments can be tricky due to shortage of winter periods and snowfall, difficulties of sample casting and transport, and the great variability of natural snow due to the varying conditions of crystal growth in the clouds. This hinders repeatable laboratory experiments with reproducible specimen and microstructural characteristics. To minimize experimental uncertainties we designed an improved machine called snowmaker, which enables us to produce nature-identical snow in a cold laboratory under well defined conditions. The snowmaker is based on well-known principles: warm humid air from a heated water basin is advected into a cold nucleation chamber where the vapor resublimates on stretched Nylon wires. Crystals are automatically harvested by a motor driven brush rack and collected in a box, thereby several kilograms of snow can be produced per day with minimum maintenance. The excess vapor is collected in a moisture trap to avoid frost in the laboratory. The entire construction is designed as a rolling, modular assembly system which can easily carried out of the laboratory for defrosting. In addition to previous attempts we focus on the reproducibility of the samples and the comparison to natural snow down to the microscale. We show that the settings of water temperature and cold laboratory temperature facilitates the production of different crystal shapes like dendrites and needles in a reproducible way. Besides photography, we analyzed the microstructure of snowmaker crystals in aggregated specimen by X-ray microtomography. Depending on the settings we can create reproducible samples with density of 50-170 kg/m3 and specific surface areas of 50-80 mm-1. We briefly touch similarities between artificial and natural snow samples with respect to crystal habit, microstructural parameters and short-time metamorphism.

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.

Evaluating the temporal variability of concentrations of POPs in a glacier-fed stream food chain using a combined modeling approach.

PubMed

Morselli, Melissa; Semplice, Matteo; Villa, Sara; Di Guardo, Antonio

2014-09-15

Falling snow acts as an efficient scavenger of contaminants from the atmosphere and, accumulating on the ground surface, behaves as a temporary storage reservoir; during snow aging and metamorphosis, contaminants may concentrate and be subject to pulsed release during intense snow melt events. In high-mountain areas, firn and ice play a similar role. The consequent concentration peaks in surface waters can pose a risk to high-altitude ecosystems, since snow and ice melt often coincide with periods of intense biological activity. In such situations, the role of dynamic models can be crucial when assessing environmental behavior of contaminants and their accumulation patterns in aquatic organisms. In the present work, a dynamic fate modeling approach was combined to a hydrological module capable of estimating water discharge and snow/ice melt contributions on an hourly basis, starting from hourly air temperatures. The model was applied to the case study of the Frodolfo glacier-fed stream (Italian Alps), for which concentrations of a number of persistent organic pollutants (POPs), such as polychlorinated biphenyl (PCBs) and p,p'-dichlorodiphenyldichloroethylene (p,p'-DDE) in stream water and four macroinvertebrate groups were available. Considering the uncertainties in input data, results showed a satisfying agreement for both water and organism concentrations. This study showed the model adequacy for the estimation of pollutant concentrations in surface waters and bioaccumulation in aquatic organisms, as well as its possible role in assessing the consequences of climate change on the cycle of POPs. Copyright © 2014 Elsevier B.V. All rights reserved.

Improving the Representation of Snow Crystal Properties Within a Single-Moment Microphysics Scheme

NASA Technical Reports Server (NTRS)

Molthan, Andrew L.; Petersen, Walter A.; Case, Jonathan L.; Dembek, S. R.

2010-01-01

As computational resources continue their expansion, weather forecast models are transitioning to the use of parameterizations that predict the evolution of hydrometeors and their microphysical processes, rather than estimating the bulk effects of clouds and precipitation that occur on a sub-grid scale. These parameterizations are referred to as single-moment, bulk water microphysics schemes, as they predict the total water mass among hydrometeors in a limited number of classes. Although the development of single moment microphysics schemes have often been driven by the need to predict the structure of convective storms, they may also provide value in predicting accumulations of snowfall. Predicting the accumulation of snowfall presents unique challenges to forecasters and microphysics schemes. In cases where surface temperatures are near freezing, accumulated depth often depends upon the snowfall rate and the ability to overcome an initial warm layer. Precipitation efficiency relates to the dominant ice crystal habit, as dendrites and plates have relatively large surface areas for the accretion of cloud water and ice, but are only favored within a narrow range of ice supersaturation and temperature. Forecast models and their parameterizations must accurately represent the characteristics of snow crystal populations, such as their size distribution, bulk density and fall speed. These properties relate to the vertical distribution of ice within simulated clouds, the temperature profile through latent heat release, and the eventual precipitation rate measured at the surface. The NASA Goddard, single-moment microphysics scheme is available to the operational forecast community as an option within the Weather Research and Forecasting (WRF) model. The NASA Goddard scheme predicts the occurrence of up to six classes of water mass: vapor, cloud ice, cloud water, rain, snow and either graupel or hail.

Feedback mechanisms between snow and atmospheric mercury: Results and observations from field campaigns on the Antarctic plateau.

PubMed

Spolaor, Andrea; Angot, Hélène; Roman, Marco; Dommergue, Aurélien; Scarchilli, Claudio; Vardè, Massimiliano; Del Guasta, Massimo; Pedeli, Xanthi; Varin, Cristiano; Sprovieri, Francesca; Magand, Olivier; Legrand, Michel; Barbante, Carlo; Cairns, Warren R L

2018-04-01

The Antarctic Plateau snowpack is an important environment for the mercury geochemical cycle. We have extensively characterized and compared the changes in surface snow and atmospheric mercury concentrations that occur at Dome C. Three summer sampling campaigns were conducted between 2013 and 2016. The three campaigns had different meteorological conditions that significantly affected mercury deposition processes and its abundance in surface snow. In the absence of snow deposition events, the surface mercury concentration remained stable with narrow oscillations, while an increase in precipitation results in a higher mercury variability. The Hg concentrations detected confirm that snowfall can act as a mercury atmospheric scavenger. A high temporal resolution sampling experiment showed that surface concentration changes are connected with the diurnal solar radiation cycle. Mercury in surface snow is highly dynamic and it could decrease by up to 90% within 4/6 h. A negative relationship between surface snow mercury and atmospheric concentrations has been detected suggesting a mutual dynamic exchange between these two environments. Mercury concentrations were also compared with the Br concentrations in surface and deeper snow, results suggest that Br could have an active role in Hg deposition, particularly when air masses are from coastal areas. This research presents new information on the presence of Hg in surface and deeper snow layers, improving our understanding of atmospheric Hg deposition to the snow surface and the possible role of re-emission on the atmospheric Hg concentration. Copyright © 2018 Elsevier Ltd. All rights reserved.

Variability of AVHRR-Derived Clear-Sky Surface Temperature over the Greenland Ice Sheet.

NASA Astrophysics Data System (ADS)

Stroeve, Julienne; Steffen, Konrad

1998-01-01

The Advanced Very High Resolution Radiometer is used to derive surface temperatures for one satellite pass under clear skies over the Greenland ice sheet from 1989 through 1993. The results of these temperatures are presented as monthly means, and their spatial and temporal variability are discussed. Accuracy of the dry snow surface temperatures is estimated to be better than 1 K during summer. This error is expected to increase during polar night due to problems in cloud identification. Results indicate the surface temperature of the Greenland ice sheet is strongly dominated by topography, with minimum surface temperatures associated with the high elevation regions. In the summer, maximum surface temperatures occur during July along the western coast and southern tip of the ice sheet. Minimum temperatures are found at the summit during summer and move farther north during polar night. Large interannual variability in surface temperatures occurs during winter associated with katabatic storm events. Summer temperatures show little variation, although 1992 stands out as being colder than the other years. The reason for the lower temperatures during 1992 is believed to be a result of the 1991 eruption of Mount Pinatubo.

Rate acceleration of the heterogeneous reaction of ozone with a model alkene at the air-ice interface at low temperatures.

PubMed

Ray, Debajyoti; Malongwe, Joseph K'Ekuboni; Klán, Petr

2013-07-02

The kinetics of the ozonation reaction of 1,1-diphenylethylene (DPE) on the surface of ice grains (also called "artificial snow"), produced by shock-freezing of DPE aqueous solutions or DPE vapor-deposition on pure ice grains, was studied in the temperature range of 268 to 188 K. A remarkable and unexpected increase in the apparent ozonation rates with decreasing temperature was evaluated using the Langmuir-Hinshelwood and Eley-Rideal kinetic models, and by estimating the apparent specific surface area of the ice grains. We suggest that an increase of the number of surface reactive sites, and possibly higher ozone uptake coefficients are responsible for the apparent rate acceleration of DPE ozonation at the air-ice interface at lower temperatures. The increasing number of reactive sites is probably related to the fact that organic molecules are displaced more to the top of a disordered interface (or quasi-liquid) layer on the ice surface, which makes them more accessible to the gas-phase reactants. The effect of NaCl as a cocontaminant on ozonation rates was also investigated. The environmental implications of this phenomenon for natural ice/snow are discussed. DPE was selected as an example of environmentally relevant species which can react with ozone. For typical atmospheric ozone concentrations in polar areas (20 ppbv), we estimated that its half-life on the ice surface would decrease from ∼5 days at 258 K to ∼13 h at 188 K at submonolayer DPE loadings.

Simulating 3-D radiative transfer effects over the Sierra Nevada Mountains using WRF

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

Gu, Y.; Liou, K. N.; Lee, W. -L.

2012-01-01

A surface solar radiation parameterization based on deviations between 3-D and conventional plane-parallel radiative transfer models has been incorporated into the Weather Research and Forecasting (WRF) model to understand the solar insolation over mountain/snow areas and to investigate the impact of the spatial and temporal distribution and variation of surface solar fluxes on land-surface processes. Using the Sierra-Nevada in the western United States as a testbed, we show that mountain effect could produce up to -50 to + 50 W m -2 deviations in the surface solar fluxes over the mountain areas, resulting in a temperature increase of up tomore » 1 °C on the sunny side. Upward surface sensible and latent heat fluxes are modulated accordingly to compensate for the change in surface solar fluxes. Snow water equivalent and surface albedo both show decreases on the sunny side of the mountains, indicating more snowmelt and hence reduced snow albedo associated with more solar insolation due to mountain effect. Soil moisture increases on the sunny side of the mountains due to enhanced snowmelt, while decreases on the shaded side. Substantial differences are found in the morning hours from 8–10 a.m. and in the afternoon around 3–5 p.m., while differences around noon and in the early morning and late afternoon are comparatively smaller. Variation in the surface energy balance can also affect atmospheric processes, such as cloud fields, through the modulation of vertical thermal structure. Negative changes of up to -40 g m -2 are found in the cloud water path, associated with reductions in the surface insolation over the cloud region. The day-averaged deviations in the surface solar flux are positive over the mountain areas and negative in the valleys, with a range between -12~12 W m -2. Changes in sensible and latent heat fluxes and surface skin temperature follow the solar insolation pattern. Differences in the domain-averaged diurnal variation over the Sierras show that the mountain area receives more solar insolation during early morning and late afternoon, resulting in enhanced upward sensible heat and latent heat fluxes from the surface and a corresponding increase in surface skin temperature. During the middle of the day, however, the surface insolation and heat fluxes show negative changes, indicating a cooling effect. Hence overall, the diurnal variations of surface temperature and surface fluxes in the Sierra-Nevada are reduced through the interactions of radiative transfer and mountains. Finally, the hourly differences of the surface solar insolation in higher elevated regions, however, show smaller magnitude in negative changes during the middle of the day and possibly more solar fluxes received during the whole day.« less

Mapping snow depth in alpine terrain with remotely piloted aerial systems and structure-from-motion photogrammetry - first results from a pilot study

NASA Astrophysics Data System (ADS)

Adams, Marc; Fromm, Reinhard; Bühler, Yves; Bösch, Ruedi; Ginzler, Christian

2016-04-01

Detailed information on the spatio-temporal distribution of seasonal snow in the alpine terrain plays a major role for the hydrological cycle, natural hazard management, flora and fauna, as well as tourism. Current methods are mostly only valid on a regional scale or require a trade-off between the data's availability, cost and resolution. During a one-year pilot study, we investigated the potential of remotely piloted aerial systems (RPAS) and structure-from-motion photogrammetry for snow depth mapping. We employed multi-copter and fixed-wing RPAS, equipped with different low-cost, off-the shelf sensors, at four test sites in Austria and Switzerland. Over 30 flights were performed during the winter 2014/15, where different camera settings, filters and lenses, as well as data collection routines were tested. Orthophotos and digital surface models (DSM) where calculated from the imagery using structure-from-motion photogrammetry software. Snow height was derived by subtracting snow-free from snow-covered DSMs. The RPAS-results were validated against data collected using a variety of well-established remote sensing (i.e. terrestrial laser scanning, large frame aerial sensors) and in-situ measurement techniques. The results show, that RPAS i) are able to map snow depth within accuracies of 0.07-0.15 m root mean square error (RMSE), when compared to traditional in-situ data; ii) can be operated at lower cost, easier repeatability, less operational constraints and higher GSD than large frame aerial sensors on-board manned aircraft, while achieving significantly higher accuracies; iii) are able to acquire meaningful data even under harsh environmental conditions above 2000 m a.s.l. (turbulence, low temperature and high irradiance, low air density). While providing a first prove-of-concept, the study also showed future challenges and limitations of RPAS-based snow depth mapping, including a high dependency on correct co-registration of snow-free and snow-covered height measurements, as well as a significant impact of the underlying vegetation and illumination of the snow surface on the fidelity of the results.

Accuracy of snow depth estimation in mountain and prairie environments by an unmanned aerial vehicle

NASA Astrophysics Data System (ADS)

Harder, Phillip; Schirmer, Michael; Pomeroy, John; Helgason, Warren

2016-11-01

Quantifying the spatial distribution of snow is crucial to predict and assess its water resource potential and understand land-atmosphere interactions. High-resolution remote sensing of snow depth has been limited to terrestrial and airborne laser scanning and more recently with application of structure from motion (SfM) techniques to airborne (manned and unmanned) imagery. In this study, photography from a small unmanned aerial vehicle (UAV) was used to generate digital surface models (DSMs) and orthomosaics for snow cover at a cultivated agricultural Canadian prairie and a sparsely vegetated Rocky Mountain alpine ridgetop site using SfM. The accuracy and repeatability of this method to quantify snow depth, changes in depth and its spatial variability was assessed for different terrain types over time. Root mean square errors in snow depth estimation from differencing snow-covered and non-snow-covered DSMs were 8.8 cm for a short prairie grain stubble surface, 13.7 cm for a tall prairie grain stubble surface and 8.5 cm for an alpine mountain surface. This technique provided useful information on maximum snow accumulation and snow-covered area depletion at all sites, while temporal changes in snow depth could also be quantified at the alpine site due to the deeper snowpack and consequent higher signal-to-noise ratio. The application of SfM to UAV photographs returns meaningful information in areas with mean snow depth > 30 cm, but the direct observation of snow depth depletion of shallow snowpacks with this method is not feasible. Accuracy varied with surface characteristics, sunlight and wind speed during the flight, with the most consistent performance found for wind speeds < 10 m s-1, clear skies, high sun angles and surfaces with negligible vegetation cover.

Estimation of snow albedo reduction by light absorbing impurities using Monte Carlo radiative transfer model

NASA Astrophysics Data System (ADS)

Sengupta, D.; Gao, L.; Wilcox, E. M.; Beres, N. D.; Moosmüller, H.; Khlystov, A.

2017-12-01

Radiative forcing and climate change greatly depends on earth's surface albedo and its temporal and spatial variation. The surface albedo varies greatly depending on the surface characteristics ranging from 5-10% for calm ocean waters to 80% for some snow-covered areas. Clean and fresh snow surfaces have the highest albedo and are most sensitive to contamination with light absorbing impurities that can greatly reduce surface albedo and change overall radiative forcing estimates. Accurate estimation of snow albedo as well as understanding of feedbacks on climate from changes in snow-covered areas is important for radiative forcing, snow energy balance, predicting seasonal snowmelt, and run off rates. Such information is essential to inform timely decision making of stakeholders and policy makers. Light absorbing particles deposited onto the snow surface can greatly alter snow albedo and have been identified as a major contributor to regional climate forcing if seasonal snow cover is involved. However, uncertainty associated with quantification of albedo reduction by these light absorbing particles is high. Here, we use Mie theory (under the assumption of spherical snow grains) to reconstruct the single scattering parameters of snow (i.e., single scattering albedo ῶ and asymmetry parameter g) from observation-based size distribution information and retrieved refractive index values. The single scattering parameters of impurities are extracted with the same approach from datasets obtained during laboratory combustion of biomass samples. Instead of using plane-parallel approximation methods to account for multiple scattering, we have used the simple "Monte Carlo ray/photon tracing approach" to calculate the snow albedo. This simple approach considers multiple scattering to be the "collection" of single scattering events. Using this approach, we vary the effective snow grain size and impurity concentrations to explore the evolution of snow albedo over a wide wavelength range (300 nm - 2000 nm). Results will be compared with the SNICAR model to better understand the differences in snow albedo computation between plane-parallel methods and the statistical Monte Carlo methods.

Frost risk for overwintering crops in a changing climate

NASA Astrophysics Data System (ADS)

Vico, Giulia; Weih, Martin

2013-04-01

Climate change scenarios predict a general increase in daily temperatures and a decline in snow cover duration. On the one hand, higher temperature in fall and spring may facilitate the development of overwintering crops and allow the expansion of winter cropping in locations where the growing season is currently too short. On the other hand, higher temperatures prior to winter crop dormancy slow down frost hardening, enhancing crop vulnerability to temperature fluctuation. Such vulnerability may be exacerbated by reduced snow cover, with potential further negative impacts on yields in extremely low temperatures. We propose a parsimonious probabilistic model to quantify the winter frost damage risk for overwintering crops, based on a coupled model of air temperature, snow cover, and crop minimum tolerable temperature. The latter is determined by crop features, previous history of temperature, and snow cover. The temperature-snow cover model is tested against meteorological data collected over 50 years in Sweden and applied to winter wheat varieties differing in their ability to acquire frost resistance. Hence, exploiting experimental results assessing crop frost damage under limited temperature and snow cover realizations, this probabilistic framework allows the quantification of frost risk for different crop varieties, including in full temperature and precipitation unpredictability. Climate change scenarios are explored to quantify the effects of changes in temperature mean and variance and precipitation regime over crops differing in winter frost resistance and response to temperature.

Recent Warming and Cooling in the Antarctic Peninsula Region has Rapid and Large Effects on Lichen Vegetation.

PubMed

Sancho, Leopoldo G; Pintado, Ana; Navarro, Francisco; Ramos, Miguel; De Pablo, Miguel Angel; Blanquer, Jose Manuel; Raggio, Jose; Valladares, Fernando; Green, Thomas George Allan

2017-07-24

The Antarctic Peninsula has had a globally large increase in mean annual temperature from the 1951 to 1998 followed by a decline that still continues. The challenge is now to unveil whether these recent, complex and somewhat unexpected climatic changes are biologically relevant. We were able to do this by determining the growth of six lichen species on recently deglaciated surfaces over the last 24 years. Between 1991 and 2002, when mean summer temperature (MST) rose by 0.42 °C, five of the six species responded with increased growth. MST declined by 0.58 °C between 2002 and 2015 with most species showing a fall in growth rate and two of which showed a collapse with the loss of large individuals due to a combination of increased snow fall and longer snow cover duration. Increased precipitation can, counter-intuitively, have major negative effects when it falls as snow at cooler temperatures. The recent Antarctic cooling is having easily detectable and deleterious impacts on slow growing and highly stress-tolerant crustose lichens, which are comparable in extent and dynamics, and reverses the gains observed over the previous decades of exceptional warming.

Response of seasonal soil freeze depth to climate change across China

NASA Astrophysics Data System (ADS)

Peng, Xiaoqing; Zhang, Tingjun; Frauenfeld, Oliver W.; Wang, Kang; Cao, Bin; Zhong, Xinyue; Su, Hang; Mu, Cuicui

2017-05-01

The response of seasonal soil freeze depth to climate change has repercussions for the surface energy and water balance, ecosystems, the carbon cycle, and soil nutrient exchange. Despite its importance, the response of soil freeze depth to climate change is largely unknown. This study employs the Stefan solution and observations from 845 meteorological stations to investigate the response of variations in soil freeze depth to climate change across China. Observations include daily air temperatures, daily soil temperatures at various depths, mean monthly gridded air temperatures, and the normalized difference vegetation index. Results show that soil freeze depth decreased significantly at a rate of -0.18 ± 0.03 cm yr-1, resulting in a net decrease of 8.05 ± 1.5 cm over 1967-2012 across China. On the regional scale, soil freeze depth decreases varied between 0.0 and 0.4 cm yr-1 in most parts of China during 1950-2009. By investigating potential climatic and environmental driving factors of soil freeze depth variability, we find that mean annual air temperature and ground surface temperature, air thawing index, ground surface thawing index, and vegetation growth are all negatively associated with soil freeze depth. Changes in snow depth are not correlated with soil freeze depth. Air and ground surface freezing indices are positively correlated with soil freeze depth. Comparing these potential driving factors of soil freeze depth, we find that freezing index and vegetation growth are more strongly correlated with soil freeze depth, while snow depth is not significant. We conclude that air temperature increases are responsible for the decrease in seasonal freeze depth. These results are important for understanding the soil freeze-thaw dynamics and the impacts of soil freeze depth on ecosystem and hydrological process.

Experimental Investigation of Concrete Runway Snow Melting Utilizing Heat Pipe Technology

PubMed Central

Su, Xin; Ye, Qing; Fu, Jianfeng

2018-01-01

A full scale snow melting system with heat pipe technology is built in this work, which avoids the negative effects on concrete structure and environment caused by traditional deicing chemicals. The snow melting, ice-freezing performance and temperature distribution characteristics of heat pipe concrete runway were discussed by the outdoor experiments. The results show that the temperature of the concrete pavement is greatly improved with the heat pipe system. The environment temperature and embedded depth of heat pipe play a dominant role among the decision variables of the snow melting system. Heat pipe snow melting pavement melts the snow completely and avoids freezing at any time when the environment temperature is below freezing point, which is secure enough for planes take-off and landing. Besides, the exportation and recovery of geothermal energy indicate that this system can run for a long time. This paper will be useful for the design and application of the heat pipe used in the runway snow melting. PMID:29551957

Experimental Investigation of Concrete Runway Snow Melting Utilizing Heat Pipe Technology.

PubMed

Chen, Fengchen; Su, Xin; Ye, Qing; Fu, Jianfeng

2018-01-01

A full scale snow melting system with heat pipe technology is built in this work, which avoids the negative effects on concrete structure and environment caused by traditional deicing chemicals. The snow melting, ice-freezing performance and temperature distribution characteristics of heat pipe concrete runway were discussed by the outdoor experiments. The results show that the temperature of the concrete pavement is greatly improved with the heat pipe system. The environment temperature and embedded depth of heat pipe play a dominant role among the decision variables of the snow melting system. Heat pipe snow melting pavement melts the snow completely and avoids freezing at any time when the environment temperature is below freezing point, which is secure enough for planes take-off and landing. Besides, the exportation and recovery of geothermal energy indicate that this system can run for a long time. This paper will be useful for the design and application of the heat pipe used in the runway snow melting.

Mountain glaciers darkening: geochemical characterizazion of cryoconites and their radiative impact on the Vadret da Morteratsch (Swiss Alps)

NASA Astrophysics Data System (ADS)

Di Mauro, Biagio; Baccolo, Giovanni; Garzonio, Roberto; Piazzalunga, Andrea; Massabò, Dario; Colombo, Roberto

2016-04-01

Mountain glaciers represent an important source of fresh water across the globe. It is well known that these reservoirs are seriously threatened by global climate change, and a widespread reduction of glacier extension has been observed in recent years. Surface processes that promote ice melting are driven both by air temperature/precipitation and surface albedo. This latter is mainly influenced by the growth of snow grains and by the impurities content (such as mineral dust, soot, ash etc.). The origin of these light-absorbing impurities can be local or distal, and often, as a consequence of melting processes, they can aggregate on the glacier tongue, forming characteristics cryoconites, that decrease ice albedo and hence promote the melting. In this contribution, we coupled satellite images (EO1 - Hyperion and Landsat 8 - OLI) and ground hyperspectral data (ASD field spectrometer) for characterizing ice and snow surface reflectance of the Vadret da Morteratsch glacier (Swiss Alps). On the glacier ablation zone, we sampled ice, snow, surface dust and cryoconite material. To evaluate the possible impact of anthropogenic and natural emissions on cryoconites formation, we determined their geochemical composition (through the Neutron Activation Analysis, NAA) and the concentration of Black Carbon (BC), Organic Carbon (OC), Elemental Carbon (EC) and Levoglucosan. From satellite data, we computed the Snow Darkening Index (SDI), which is non-linearly correlated with dust content in snow. Results showed that, during 2015 summer season, ice albedo in the ablation zone reached very low values of about 0.1-0.2. The darkening of the glacier can be attributed to the impact of surface dust (from lateral moraine and Saharan desert) and cryoconites, coupled with grain growth driven by the extremely warm 2015 summer. The geochemical characterization of non-ice material contained in the cryoconites can provide important information regarding their source and the possible impact of anthropogenic emissions on cryoconites formation and evolution.

Hydrologic Remote Sensing and Land Surface Data Assimilation.

PubMed

Moradkhani, Hamid

2008-05-06

Accurate, reliable and skillful forecasting of key environmental variables such as soil moisture and snow are of paramount importance due to their strong influence on many water resources applications including flood control, agricultural production and effective water resources management which collectively control the behavior of the climate system. Soil moisture is a key state variable in land surface-atmosphere interactions affecting surface energy fluxes, runoff and the radiation balance. Snow processes also have a large influence on land-atmosphere energy exchanges due to snow high albedo, low thermal conductivity and considerable spatial and temporal variability resulting in the dramatic change on surface and ground temperature. Measurement of these two variables is possible through variety of methods using ground-based and remote sensing procedures. Remote sensing, however, holds great promise for soil moisture and snow measurements which have considerable spatial and temporal variability. Merging these measurements with hydrologic model outputs in a systematic and effective way results in an improvement of land surface model prediction. Data Assimilation provides a mechanism to combine these two sources of estimation. Much success has been attained in recent years in using data from passive microwave sensors and assimilating them into the models. This paper provides an overview of the remote sensing measurement techniques for soil moisture and snow data and describes the advances in data assimilation techniques through the ensemble filtering, mainly Ensemble Kalman filter (EnKF) and Particle filter (PF), for improving the model prediction and reducing the uncertainties involved in prediction process. It is believed that PF provides a complete representation of the probability distribution of state variables of interests (according to sequential Bayes law) and could be a strong alternative to EnKF which is subject to some limitations including the linear updating rule and assumption of jointly normal distribution of errors in state variables and observation.

Impacts of microtopographic snow redistribution and lateral subsurface processes on hydrologic and thermal states in an Arctic polygonal ground ecosystem: a case study using ELM-3D v1.0

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

Bisht, Gautam; Riley, William J.; Wainwright, Haruko M.

Microtopographic features, such as polygonal ground, are characteristic sources of landscape heterogeneity in the Alaskan Arctic coastal plain. In this study, we analyze the effects of snow redistribution (SR) and lateral subsurface processes on hydrologic and thermal states at a polygonal tundra site near Barrow, Alaska. We extended the land model integrated in the E3SM to redistribute incoming snow by accounting for microtopography and incorporated subsurface lateral transport of water and energy (ELM-3D v1.0). Multiple 10-year-long simulations were performed for a transect across a polygonal tundra landscape at the Barrow Environmental Observatory in Alaska to isolate the impact of SRmore » and subsurface process representation. When SR was included, model predictions better agreed (higher R 2, lower bias and RMSE) with observed differences in snow depth between polygonal rims and centers. The model was also able to accurately reproduce observed soil temperature vertical profiles in the polygon rims and centers (overall bias, RMSE, and R 2 of 0.59°C, 1.82°C, and 0.99, respectively). The spatial heterogeneity of snow depth during the winter due to SR generated surface soil temperature heterogeneity that propagated in depth and time and led to ~ 10 cm shallower and ~ 5 cm deeper maximum annual thaw depths under the polygon rims and centers, respectively. Additionally, SR led to spatial heterogeneity in surface energy fluxes and soil moisture during the summer. Excluding lateral subsurface hydrologic and thermal processes led to small effects on mean states but an overestimation of spatial variability in soil moisture and soil temperature as subsurface liquid pressure and thermal gradients were artificially prevented from spatially dissipating over time. The effect of lateral subsurface processes on maximum thaw depths was modest, with mean absolute differences of ~ 3 cm. Our integration of three-dimensional subsurface hydrologic and thermal subsurface dynamics in the E3SM land model will facilitate a wide range of analyses heretofore impossible in an ESM context.« less

Impacts of microtopographic snow-redistribution and lateral subsurface processeson hydrologic and thermal states in an Arctic polygonal ground ecosystem

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

Bisht, Gautam; Riley, William J.; Wainwright, Haruko M.

Microtopographic features, such as polygonal ground, are characteristic sources of landscape heterogeneity in the Alaskan Arctic coastal plain. We analyze the effects of snow redistribution (SR) and lateral subsurface processes on hydrologic and thermal states at a polygonal tundra site near Barrow, Alaska. We extended the land model integrated in the ACME Earth System Model (ESM) to redistribute incoming snow by accounting for microtopography and incorporated subsurface lateral transport of water and energy (ALMv0-3D). Three 10-years long simulations were performed for a transect across polygonal tundra landscape at the Barrow Environmental Observatory in Alaska to isolate the impact of SRmore » and subsurface process representation. When SR was included, model results show a better agreement (higher R 2 with lower bias and RMSE) for the observed differences in snow depth between polygonal rims and centers. The model was also able to accurately reproduce observed soil temperature vertical profiles in the polygon rims and centers (overall bias, RMSE, and R 2 of 0.59°C, 1.82°C, and 0.99, respectively). The spatial heterogeneity of snow depth during the winter due to SR generated surface soil temperature heterogeneity that propagated in depth and time and led to ~10 cm shallower and ~5 cm deeper maximum annual thaw depths under the polygon rims and centers, respectively. Additionally, SR led to spatial heterogeneity in surface energy fluxes and soil moisture during the summer. Excluding lateral subsurface hydrologic and thermal processes led to small effects on mean states but an overestimation of spatial variability in soil moisture and soil temperature as subsurface liquid pressure and thermal gradients were artificially prevented from spatially dissipating over time. The effect of lateral subsurface processes on active layer depths was modest with mean absolute difference of ~3 cm. Finally, our integration of three-dimensional subsurface hydrologic and thermal subsurface dynamics in the ACME land model will facilitate a wide range of analyses heretofore impossible in an ESM context.« less

Impacts of microtopographic snow redistribution and lateral subsurface processes on hydrologic and thermal states in an Arctic polygonal ground ecosystem: a case study using ELM-3D v1.0

DOE PAGES

Bisht, Gautam; Riley, William J.; Wainwright, Haruko M.; ...

2018-01-08

Microtopographic features, such as polygonal ground, are characteristic sources of landscape heterogeneity in the Alaskan Arctic coastal plain. In this study, we analyze the effects of snow redistribution (SR) and lateral subsurface processes on hydrologic and thermal states at a polygonal tundra site near Barrow, Alaska. We extended the land model integrated in the E3SM to redistribute incoming snow by accounting for microtopography and incorporated subsurface lateral transport of water and energy (ELM-3D v1.0). Multiple 10-year-long simulations were performed for a transect across a polygonal tundra landscape at the Barrow Environmental Observatory in Alaska to isolate the impact of SRmore » and subsurface process representation. When SR was included, model predictions better agreed (higher R 2, lower bias and RMSE) with observed differences in snow depth between polygonal rims and centers. The model was also able to accurately reproduce observed soil temperature vertical profiles in the polygon rims and centers (overall bias, RMSE, and R 2 of 0.59°C, 1.82°C, and 0.99, respectively). The spatial heterogeneity of snow depth during the winter due to SR generated surface soil temperature heterogeneity that propagated in depth and time and led to ~ 10 cm shallower and ~ 5 cm deeper maximum annual thaw depths under the polygon rims and centers, respectively. Additionally, SR led to spatial heterogeneity in surface energy fluxes and soil moisture during the summer. Excluding lateral subsurface hydrologic and thermal processes led to small effects on mean states but an overestimation of spatial variability in soil moisture and soil temperature as subsurface liquid pressure and thermal gradients were artificially prevented from spatially dissipating over time. The effect of lateral subsurface processes on maximum thaw depths was modest, with mean absolute differences of ~ 3 cm. Our integration of three-dimensional subsurface hydrologic and thermal subsurface dynamics in the E3SM land model will facilitate a wide range of analyses heretofore impossible in an ESM context.« less

Impacts of microtopographic snow-redistribution and lateral subsurface processeson hydrologic and thermal states in an Arctic polygonal ground ecosystem

DOE PAGES

Bisht, Gautam; Riley, William J.; Wainwright, Haruko M.; ...

2018-01-08

Microtopographic features, such as polygonal ground, are characteristic sources of landscape heterogeneity in the Alaskan Arctic coastal plain. We analyze the effects of snow redistribution (SR) and lateral subsurface processes on hydrologic and thermal states at a polygonal tundra site near Barrow, Alaska. We extended the land model integrated in the ACME Earth System Model (ESM) to redistribute incoming snow by accounting for microtopography and incorporated subsurface lateral transport of water and energy (ALMv0-3D). Three 10-years long simulations were performed for a transect across polygonal tundra landscape at the Barrow Environmental Observatory in Alaska to isolate the impact of SRmore » and subsurface process representation. When SR was included, model results show a better agreement (higher R 2 with lower bias and RMSE) for the observed differences in snow depth between polygonal rims and centers. The model was also able to accurately reproduce observed soil temperature vertical profiles in the polygon rims and centers (overall bias, RMSE, and R 2 of 0.59°C, 1.82°C, and 0.99, respectively). The spatial heterogeneity of snow depth during the winter due to SR generated surface soil temperature heterogeneity that propagated in depth and time and led to ~10 cm shallower and ~5 cm deeper maximum annual thaw depths under the polygon rims and centers, respectively. Additionally, SR led to spatial heterogeneity in surface energy fluxes and soil moisture during the summer. Excluding lateral subsurface hydrologic and thermal processes led to small effects on mean states but an overestimation of spatial variability in soil moisture and soil temperature as subsurface liquid pressure and thermal gradients were artificially prevented from spatially dissipating over time. The effect of lateral subsurface processes on active layer depths was modest with mean absolute difference of ~3 cm. Finally, our integration of three-dimensional subsurface hydrologic and thermal subsurface dynamics in the ACME land model will facilitate a wide range of analyses heretofore impossible in an ESM context.« less

Impacts of microtopographic snow redistribution and lateral subsurface processes on hydrologic and thermal states in an Arctic polygonal ground ecosystem: a case study using ELM-3D v1.0

NASA Astrophysics Data System (ADS)

Bisht, Gautam; Riley, William J.; Wainwright, Haruko M.; Dafflon, Baptiste; Yuan, Fengming; Romanovsky, Vladimir E.

2018-01-01

Microtopographic features, such as polygonal ground, are characteristic sources of landscape heterogeneity in the Alaskan Arctic coastal plain. Here, we analyze the effects of snow redistribution (SR) and lateral subsurface processes on hydrologic and thermal states at a polygonal tundra site near Barrow, Alaska. We extended the land model integrated in the E3SM to redistribute incoming snow by accounting for microtopography and incorporated subsurface lateral transport of water and energy (ELM-3D v1.0). Multiple 10-year-long simulations were performed for a transect across a polygonal tundra landscape at the Barrow Environmental Observatory in Alaska to isolate the impact of SR and subsurface process representation. When SR was included, model predictions better agreed (higher R2, lower bias and RMSE) with observed differences in snow depth between polygonal rims and centers. The model was also able to accurately reproduce observed soil temperature vertical profiles in the polygon rims and centers (overall bias, RMSE, and R2 of 0.59 °C, 1.82 °C, and 0.99, respectively). The spatial heterogeneity of snow depth during the winter due to SR generated surface soil temperature heterogeneity that propagated in depth and time and led to ˜ 10 cm shallower and ˜ 5 cm deeper maximum annual thaw depths under the polygon rims and centers, respectively. Additionally, SR led to spatial heterogeneity in surface energy fluxes and soil moisture during the summer. Excluding lateral subsurface hydrologic and thermal processes led to small effects on mean states but an overestimation of spatial variability in soil moisture and soil temperature as subsurface liquid pressure and thermal gradients were artificially prevented from spatially dissipating over time. The effect of lateral subsurface processes on maximum thaw depths was modest, with mean absolute differences of ˜ 3 cm. Our integration of three-dimensional subsurface hydrologic and thermal subsurface dynamics in the E3SM land model will facilitate a wide range of analyses heretofore impossible in an ESM context.

The spatial and seasonal variations in mineral particle composition on the snow surface and their possible effect on snow algae in the Tateyama Mountains, Japan

NASA Astrophysics Data System (ADS)

Umino, T.; Takeuchi, N.

2012-12-01

Snow algae are autotrophic microbes and play an important role as primary producers in food chain of glaciers and snowfield. Although their reproduction requires nutrients, snow and ice is extreamly poor in nutrients. One of the possible sources of nutrients is mineral particles blown by wind and deposited on the snow. They may contain variable elements and provide nutrients for snow algae. However, we scarcely know about the relationship between mineral particles and snow algae. In this study, we described spatial and seasonal variations in mineral particle composition and also snow algae on the snow surface in the Tateyama Mountains, Japan. We discussed the possible effect of mineral particles on snow algae. Tateyama Mountains are located in middle-north part of Japan ranging from 2000 - 3000 m above sea level and have heavy snow fall in winter due to strong monsoon wind from Siberia. The snow starts to thaw in April and remains until late summer as perennial snow patches in some valleys. Kosa eolian dust is known to be blown from Chinese deserts and deposited on the snow every spring. Also, snow algal bloom is often observed as red-colored snow in summer. Samples were collected from the snow surface during summer in 2008 - 2011 at four different sites (A - D) in this area. We examined them by X-ray diffractometer (XRD) and microscope to obtain composition of mineral particles and structure of snow algae community. XRD analysis revealed mineral particles on the snow surface were mainly composed of quartz, plagioclase, hornblende, mica, chlorite, and amorphous. In April, mineral compositions of all sites were almost similar to that of Kosa eolian dust, indicating that these mineral particles were derived from Chinese arid regions. After May, the mineral compositions changed according to sites. The proportion of hornblende at the site C significantly increased whereas that of mica increased at the site D. Since the site C was located near geological features mainly composed of hornblende, the supply of mineral particles from local sources is likely to increase after May. These results indicate mineral particles on the snow surface were blown from distant Chinese deserts in April when snow covered entire ground surface, and they may change to be supplied from the local exposed ground surface after May. Microscopy revealed over 90 % of snow algal cells attached mineral particles on their surfaces, suggesting mineral particles may be beneficial for their growth. Furthermore, algal community structure was different among study sites. The difference may be due to different composition of mineral particles. This suggests composition of mineral particles may affect algal community structure. Hornblende, which was abundant at the site C, is usually rich in Fe or Mg, and it may affect algal growth in the site.

The Dependence of the Ice-Albedo Feedback on Atmospheric Properties

PubMed Central

Selsis, F.; Kitzmann, D.; Rauer, H.

2013-01-01

Abstract Ice-albedo feedback is a potentially important destabilizing effect for the climate of terrestrial planets. It is based on the positive feedback between decreasing surface temperatures, an increase of snow and ice cover, and an associated increase in planetary albedo, which then further decreases surface temperature. A recent study shows that for M stars, the strength of the ice-albedo feedback is reduced due to the strong spectral dependence of stellar radiation and snow/ice albedos; that is, M stars primarily emit in the near IR, where the snow and ice albedo is low, and less in the visible, where the snow/ice albedo is high. This study investigates the influence of the atmosphere (in terms of surface pressure and atmospheric composition) on this feedback, since an atmosphere was neglected in previous studies. A plane-parallel radiative transfer model was used for the calculation of planetary albedos. We varied CO2 partial pressures as well as the H2O, CH4, and O3 content in the atmosphere for planets orbiting Sun-like and M type stars. Results suggest that, for planets around M stars, the ice-albedo effect is significantly reduced, compared to planets around Sun-like stars. Including the effects of an atmosphere further suppresses the sensitivity to the ice-albedo effect. Atmospheric key properties such as surface pressure, but also the abundance of radiative trace gases, can considerably change the strength of the ice-albedo feedback. For dense CO2 atmospheres of the order of a few to tens of bar, atmospheric rather than surface properties begin to dominate the planetary radiation budget. At high CO2 pressures, the ice-albedo feedback is strongly reduced for planets around M stars. The presence of trace amounts of H2O and CH4 in the atmosphere also weakens the ice-albedo effect for both stellar types considered. For planets around Sun-like stars, O3 could also lead to a very strong decrease of the ice-albedo feedback at high CO2 pressures. Key Words: Atmospheric compositions—Extrasolar terrestrial planets—Snowball Earth—Planetary atmospheres—Radiative transfer. Astrobiology 13, 899–909. PMID:24111995

Impacts of anthropogenic emissions and cold air pools on urban to montane gradients of snowpack ion concentrations in the Wasatch Mountains, Utah

NASA Astrophysics Data System (ADS)

Hall, Steven J.; Maurer, Gregory; Hoch, Sebastian W.; Taylor, Raili; Bowling, David R.

2014-12-01

Urban montane valleys are often characterized by periodic wintertime temperature inversions (cold air pools) that increase atmospheric particulate matter concentrations, potentially stimulating the deposition of major ions to these snow-covered ecosystems. We assessed spatial and temporal patterns of ion concentrations in snow across urban to montane gradients in Salt Lake City, Utah, USA, and the adjacent Wasatch Mountains during January 2011, a period of several persistent cold air pools. Ion concentrations in fresh snow samples were greatest in urban sites, and were lower by factors of 4-130 in a remote high-elevation montane site. Adjacent undeveloped canyons experienced significant incursions of particulate-rich urban air during stable atmospheric conditions, where snow ion concentrations were lower but not significantly different from urban sites. Surface snow ion concentrations on elevation transects in and adjacent to Salt Lake City varied with temporal and spatial trends in aerosol concentrations, increasing following exposure to particulate-rich air as cold air pools developed, and peaking at intermediate elevations (1500-1600 m above sea level, or 200-300 m above the valley floor). Elevation trends in ion concentrations, especially NH4+ and NO3-, corresponded with patterns of aerosol exposure inferred from laser ceilometer data, suggesting that high particulate matter concentrations stimulated fog or dry ion deposition to snow-covered surfaces at the top of the cold air pools. Fog/dry deposition inputs were similar to wet deposition at mid-elevation montane sites, but appeared negligible at lower and higher-elevation sites. Overall, snow ion concentrations in our urban and adjacent montane sites exceeded many values reported from urban precipitation in North America, and greatly exceeded those reported for remote snowpacks. Sodium, Cl-, NH4+, and NO3- concentrations in fresh snow were high relative to previously measured urban precipitation, with means of 120, 117, 42, and 39 μeq l-1, respectively. After exposure to atmospheric particulate matter during cold pool events, surface snow concentrations peaked at 2500, 3600, 93, and 90 μeq l-1 for these ions. Median nitrogen (N) deposition in fresh urban snow samples measured 0.8 kg N ha-1 during January 2011, with similar fog/dry deposition inputs at mid-elevation montane sites. Wintertime anthropogenic air pollution represents a significant source of ions to snow-covered ecosystems proximate to urban montane areas, with important implications for ecosystem function.

Albedo Spatial Variability and Causes on the Western Greenland Ice Sheet Percolation Zone

NASA Astrophysics Data System (ADS)

Lewis, G.; Osterberg, E. C.; Hawley, R. L.; Koffman, B. G.; Marshall, H. P.; Birkel, S. D.; Dibb, J. E.

2016-12-01

Many recent studies have concluded that Greenland Ice Sheet (GIS) mass loss has been accelerating over recent decades, but spatial and temporal variations in GIS mass balance remain poorly understood due to a complex relationship among precipitation and temperature changes, increasing melt and runoff, ice discharge, and surface albedo. Satellite measurements from MODerate resolution Imaging Spectroradiometer (MODIS) indicate that albedo has been declining over the past decade, but the cause and extent of GIS albedo change remains poorly constrained by field data. As fresh snow (albedo > 0.85) warms and melts, its albedo decreases due to snow grain growth, promoting solar absorption, higher snowpack temperatures and further melt. However, dark impurities like soot and dust can also significantly reduce snow albedo, even in the dry snow zone. While many regional climate models (e.g. the Regional Atmospheric Climate MOdel - RACMO2) calculate albedo spatial resolutions on the order of 10-30 km, and MODIS averages albedo over 500 m, surface features like sastrugi can affect albedo on much smaller scales. Here we assess the relative importance of grain size and shape vs. impurity concentrations on albedo in the western GIS percolation zone. We collected broadband albedo measurements (300-2500 nm at 3-8 nm resolution) at 35 locations using an ASD FieldSpec4 spectroradiometer to simultaneously quantify radiative fluxes and spectral reflectance. Measurements were collected on 10 x 10 m, 1 x 1 km, 5 x 5 km, and 10 x 10 km grids to determine the spatial variability of albedo as part of the 850-km Greenland Traverse for Accumulation and Climate Studies (GreenTrACS) traverse from Raven/Dye 2 to Summit. Additionally, we collected shallow (0-50 cm) snow pit samples every 5 cm at ASD measurement sites to quantify black carbon and mineral dust concentrations and size distributions using a Single Particle Soot Photometer and Coulter Counter, respectively. Preliminary results indicate larger albedo variability in the infrared than visible and near infrared. We compare our in situ field measurements with co-located albedo data from airplanes, satellites, and climate models, and discuss implications for GIS surface mass balance.

Effects of different temperature treatments on biological ice nuclei in snow samples

NASA Astrophysics Data System (ADS)

Hara, Kazutaka; Maki, Teruya; Kakikawa, Makiko; Kobayashi, Fumihisa; Matsuki, Atsushi

2016-09-01

The heat tolerance of biological ice nucleation activity (INA) depends on their types. Different temperature treatments may cause varying degrees of inactivation on biological ice nuclei (IN) in precipitation samples. In this study, we measured IN concentration and bacterial INA in snow samples using a drop freezing assay, and compared the results for unheated snow and snow treated at 40 °C and 90 °C. At a measured temperature of -7 °C, the concentration of IN in untreated snow was 100-570 L-1, whereas the concentration in snow treated at 40 °C and 90 °C was 31-270 L-1 and 2.5-14 L-1, respectively. In the present study, heat sensitive IN inactivated by heating at 40 °C were predominant, and ranged 23-78% of IN at -7 °C compared with untreated samples. Ice nucleation active Pseudomonas strains were also isolated from the snow samples, and heating at 40 °C and 90 °C inactivated these microorganisms. Consequently, different temperature treatments induced varying degrees of inactivation on IN in snow samples. Differences in the concentration of IN across a range of treatment temperatures might reflect the abundance of different heat sensitive biological IN components.

MODIS Collection 6 Data at the National Snow and Ice Data Center (NSIDC)

NASA Astrophysics Data System (ADS)

Fowler, D. K.; Steiker, A. E.; Johnston, T.; Haran, T. M.; Fowler, C.; Wyatt, P.

2015-12-01

For over 15 years, the NASA National Snow and Ice Data Center Distributed Active Archive Center (NSIDC DAAC) has archived and distributed snow and sea ice products derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on the NASA Earth Observing System (EOS) Aqua and Terra satellites. Collection 6 represents the next revision to NSIDC's MODIS archive, mainly affecting the snow-cover products. Collection 6 specifically addresses the needs of the MODIS science community by targeting the scenarios that have historically confounded snow detection and introduced errors into the snow-cover and fractional snow-cover maps even though MODIS snow-cover maps are typically 90 percent accurate or better under good observing conditions, Collection 6 uses revised algorithms to discriminate between snow and clouds, resolve uncertainties along the edges of snow-covered regions, and detect summer snow cover in mountains. Furthermore, Collection 6 applies modified and additional snow detection screens and new Quality Assessment protocols that enhance the overall accuracy of the snow maps compared with Collection 5. Collection 6 also introduces several new MODIS snow products, including a daily Climate Modelling Grid (CMG) cloud gap-filled (CGF) snow-cover map which generates cloud-free maps by using the most recent clear observations.. The MODIS Collection 6 sea ice extent and ice surface temperature algorithms and products are much the same as Collection 5; however, Collection 6 updates to algorithm inputs—in particular, the L1B calibrated radiances, land and water mask, and cloud mask products—have improved the sea ice outputs. The MODIS sea ice products are currently available at NSIDC, and the snow cover products are soon to follow in 2016 NSIDC offers a variety of methods for obtaining these data. Users can download data directly from an online archive or use the NASA Reverb Search & Order Tool to perform spatial, temporal, and parameter subsetting, reformatting, and re-projection of the 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.

The ASMEx snow slab experiment: snow microwave radiative transfer (SMRT) model evaluation

NASA Astrophysics Data System (ADS)

Sandells, Melody; Löwe, Henning; Picard, Ghislain; Dumont, Marie; Essery, Richard; Floury, Nicolas; Kontu, Anna; Lemmetyinen, Juha; Maslanka, William; Mätzler, Christian; Morin, Samuel; Wiesmann, Andreas

2017-04-01

A major uncertainty in snow microwave modelling to date has been the treatment of the snow microstructure. Although observations of microstructural parameters such as the optical grain diameter, specific surface area and correlation length have improved drastically over the last few years, scale factors have been used to derive the parameters needed in microwave emission models from these observations. Previous work has shown that a major difference between electromagnetic models of scattering coefficients is due to the specific snow microstructure models used. The snow microwave radiative transfer model (SMRT) is a new model developed to advance understanding of the role of microstructure and isolate different assumptions in existing microwave models that collectively hinder interpretation of model intercomparison studies. SMRT is implemented in Python and is modular, thus allows switching between different representations in its various components. Here, the role of microstructure is examined with the Improved Born Approximation electromagnetic model. The model is evaluated against scattering and absorption coefficients derived from radiometer measurements of snow slabs taken as part of the Arctic Snow Microstructure Experiment (ASMEx), which took place in Sodankylä, Finland over two seasons. Microtomography observations of slab samples were used to determine parameters for five microstructure models: spherical, exponential, sticky hard sphere, Teubner-Strey and Gaussian random field. SMRT brightness temperature simulations are also compared with radiometric observations of the snow slabs over a reflector plate and an absorber substrate. Agreement between simulations and observations is generally good except for slabs that are highly anisotropic.

Improving the Performance of Temperature Index Snowmelt Model of SWAT by Using MODIS Land Surface Temperature Data

PubMed Central

Yang, Yan; Onishi, Takeo; Hiramatsu, Ken

2014-01-01

Simulation results of the widely used temperature index snowmelt model are greatly influenced by input air temperature data. Spatially sparse air temperature data remain the main factor inducing uncertainties and errors in that model, which limits its applications. Thus, to solve this problem, we created new air temperature data using linear regression relationships that can be formulated based on MODIS land surface temperature data. The Soil Water Assessment Tool model, which includes an improved temperature index snowmelt module, was chosen to test the newly created data. By evaluating simulation performance for daily snowmelt in three test basins of the Amur River, performance of the newly created data was assessed. The coefficient of determination (R 2) and Nash-Sutcliffe efficiency (NSE) were used for evaluation. The results indicate that MODIS land surface temperature data can be used as a new source for air temperature data creation. This will improve snow simulation using the temperature index model in an area with sparse air temperature observations. PMID:25165746

Torrejon AB, Madrid, Spain. revised uniform summary of surface weather observations (RUSSWO). parts a-f. Final report

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

Not Available

1978-10-03

This report is a six-part statistical summary of surface weather observations for Torrejon AB, Madrid Spain. It contains the following parts: (A) Weather Conditions; Atmospheric Phenomena; (B) Precipitation, Snowfall and Snow Depth (daily amounts and extreme values); (C) Surface winds; (D) Ceiling Versus Visibility; Sky Cover; (E) Psychrometric Summaries (daily maximum and minimum temperatures, extreme maximum and minimum temperatures, psychrometric summary of wet-bulb temperature depression versus dry-bulb temperature, means and standard deviations of dry-bulb, wet-bulb and dew-point temperatures and relative humidity); and (F) Pressure Summary (means, standard, deviations, and observation counts of station pressure and sea-level pressure). Data in thismore » report are presented in tabular form, in most cases in percentage frequency of occurrence or cumulative percentage frequency of occurrence tables.« less

SIMULATED CLIMATE CHANGE EFFECTS ON DISSOLVED OXYGEN CHARACTERISTICS IN ICE-COVERED LAKES. (R824801)

EPA Science Inventory

A deterministic, one-dimensional model is presented which simulates daily dissolved oxygen (DO) profiles and associated water temperatures, ice covers and snow covers for dimictic and polymictic lakes of the temperate zone. The lake parameters required as model input are surface ...

The self-organization of snow surfaces and the growth of sastrugi

NASA Astrophysics Data System (ADS)

Kochanski, K.; Bertholet, C.; Anderson, R. S.; Tucker, G. E.

2017-12-01

Seasonal snow covers approximately 15% of the surface of the Earth. The majority of this snow is found on tundra, ice sheets, and sea ice. These windswept snow surfaces self-organize into depositional bedforms, such as ripples, barchan dunes, and transverse waves, and erosional bedforms, such as anvil-shaped sastrugi. Previous researchers have shown that these bedforms influence the reflectivity, thermal conductivity, and aerodynamic roughness of the surface. For the past two winters, we have observed the growth and movement of snow bedforms on Niwot Ridge, Colorado, at an elevation of 3500m. We have observed that (1) when wind speeds are below 3m/s, snow surfaces can be smooth, (2) when winds are higher than 3m/s during and immediately following a storm, the smooth surface is unstable and self-organizes into a field of dunes, (3) as snow begins to harden, it forms erosional bedforms that are characterized by vertical edges facing upwind (4) between 12 and 48 hours after each snowfall, alternating stripes of erosional and depositional bedforms occur, and (5) within 60 hours of each storm, the surface self-organizes into a field of sastrugi, which remains stable until it melts or becomes buried by the next snowfall. Polar researchers should therefore expect snow-covered surfaces to be characterized by fields of bedforms, which evolve in response to variations in snow delivery, windspeed, and periods of sintering. Smooth drifts may be found in sheltered and forested regions. On most ice sheets and sea ice where snowfall is frequent, the typical surface is likely to consist of an evolving mix of depositional and erosional bedforms. Where snowfall is infrequent, for example in Antarctica, the surface will be dominated by sastrugi fields.

Surface Formation and Preservation of Very-Low-Porosity Thin Crusts ( "Glazes") at the WAIS Divide Site, West Antarctica

NASA Astrophysics Data System (ADS)

Fegyveresi, J. M.; Alley, R. B.; Muto, A.; Spencer, M. K.; Orsi, A. J.

2014-12-01

Observations at the WAIS Divide site show that near-surface snow is strongly altered by weather-related processes, producing features that are recognizable in the ice core. Prominent reflective "glazed" surface crusts develop frequently during the summer. Observations during austral summers 2008-09 through 2012-13, supplemented by Automated Weather Station data with insolation sensors, documented formation of such crusts during relatively low-wind, low-humidity, clear-sky periods with intense daytime sunshine. After formation, such glazed surfaces typically developed cracks in a polygonal pattern with few-meter spacing, likely from thermal contraction at night. Cracking was commonest when several clear days occurred in succession, and was generally followed by surface hoar growth. Temperature and radiation observations showed that solar heating often warmed the near-surface snow above the air temperature, contributing to mass transfer favoring crust formation. Subsequent investigation of the WDC06A deep ice core revealed that preserved surface crusts were seen in the core at an average rate of ~4.3 ± 2 yr-1 over the past 5500 years. They are about 40% more common in layers deposited during summers than during winters. The total summertime crust frequency also covaried with site temperature, with more present during warmer periods. We hypothesize that the mechanism for glaze formation producing single-grain-thick very-low-porosity thin crusts (i.e. "glazes") involves additional in-filling of open pores. The thermal conductivity of ice greatly exceeds that of air, so heat transport in firn is primarily conductive. Because heat flow is primarily through the grain structure, for a temperature inversion (colder upper surface) beneath a growing thin crust at the upper surface, pores will be colder than interconnected grains, favoring mass transport into those pores. Transport may occur by vapor, surface, or volume diffusion, although vapor diffusion and surface transport in pre-melted films are likely to dominate. On-site wintertime observations have not been made, but crust formation during winter may be favored by greater wind-packing, large meteorologically-forced temperature changes reaching as high as -15oC in midwinter, and perhaps longer intervals of surface stability.

Erosion and entrainment of snow and ice by pyroclastic density currents: some outstanding questions (Invited)

NASA Astrophysics Data System (ADS)

Walder, J. S.

2010-12-01

A pyroclastic density current moving over snow is likely to transform to a lahar if the pyroclasts incorporate enough (melting) snow and meltwater to bring the bulk water content of the mixture to about 35% by volume. However, the processes by which such a mixture forms are still not well understood. Walder (Bull. Volcanol., v. 62, 2000) showed experimentally the existence of an erosion mechanism that functions even in the absence of relative shear motion between pyroclasts and snow substrate: a portion of the snow melted by a blanket of pyroclasts is vaporized; the flux of water vapor upward through the pyroclasts may be enough to fluidize the pyroclasts, which then convect, rapidly scour the snow substrate and transform into a slurry. But these experiments do not tell us how moving pyroclasts would erode snow, and simply releasing a hot grain flow over a snow surface in the lab gives misleading results owing to improper scaling of τ/σ , the ratio of the shear stress τ exerted by the pyroclastic flow to the shear strength σ of snow. There seems to be no way around this problem for experiments with actual snow. However, it may be possible to circumvent the scaling problem by replacing the snow substrate by a gas-fluidized particle bed: by varying the gas flux, the apparent shear strength of the particle bed can be varied. Such an investigation of erosional processes could be done at room temperature. Snow-avalanche studies (for example, Gauer and Issler, Ann. Glaciol. v. 38, 2003) may provide some insight into snow erosion by a pyroclastic density current. Snow is eroded at the base of a dense snow avalanche by abrasion, particle impacts, and—at the avalanche head—by plowing and a “blasting” mechanism associated with compression of the snowpack and expulsion of pore fluid (air). Erosion at the avalanche head seems to be particularly important. Similar processes are likely to occur when the over-riding flow comprises hot grains. The laboratory release of a hot grain flow over snow, although improperly scaled for investigating erosive processes, does demonstrate that snow hydrology and snowpack stability may be critical in the transformation of pyroclastic density currents to lahars. When such an experiment is run in a sloping flume, with meltwater able to drain freely at the base of the snow layer, the hot grain flow spreads over the snow surface and then comes to rest--no slurry is produced. In contrast, if meltwater drainage is blocked, the wet snow layer fails at its bed, mobilizes as a slush flow, and mixes with the hot grains to form a slurry. Ice layers within a natural snowpack would likewise block meltwater drainage and be conducive to the formation of slush flows. Abrasion and particle impacts—processes that have been studied intensively by engineers concerned with the wear of surfaces in machinery—probably play an important role in the erosion of glacier ice by pyroclastic density currents. A prime example may be the summit ice cap of Nevado del Ruiz, Colombia, which was left grooved by the eruption of 1985 (Thouret, J. Volcanol. Geotherm. Res., v. 41, 1990). Erosion of glacier ice is also strongly controlled by the orientation of crevasses, which can “capture” pyroclastic currents. This phenomenon was well displayed at Mount Redoubt, Alaska during the eruptions of 1989-90 and 2009.

Snowcover influence on backscattering from terrain

NASA Technical Reports Server (NTRS)

Ulaby, F. T.; Abdelrazik, M.; Stiles, W. H.

1984-01-01

The effects of snowcover on the microwave backscattering from terrain in the 8-35 GHz region are examined through the analysis of experimental data and by application of a semiempirical model. The model accounts for surface backscattering contributions by the snow-air and snow-soil interfaces, and for volume backscattering contributions by the snow layer. Through comparisons of backscattering data for different terrain surfaces measured both with and without snowcover, the masking effects of snow are evaluated as a function of snow water equivalent and liquid water content. The results indicate that with dry snowcover it is not possible to discriminate between different types of ground surface (concrete, asphalt, grass, and bare ground) if the snow water equivalent is greater than about 20 cm (or a depth greater than 60 cm for a snow density of 0.3 g/cu cm). For the same density, however, if the snow is wet, a depth of 10 cm is sufficient to mask the underlying surface.

Radiative effects of light-absorbing particles deposited in snow over Himalayas using WRF-Chem simulations

NASA Astrophysics Data System (ADS)

Sarangi, C.; Qian, Y.; Painter, T. H.; Liu, Y.; Lin, G.; Wang, H.

2017-12-01

Radiative forcing induced by light-absorbing particles (LAP) deposited on snow is an important surface forcing. It has been debated that an aerosol-induced increase in atmospheric and surface warming over Tibetan Plateau (TP) prior to the South Asian summer monsoon can have a significant effect on the regional thermodynamics and South Asian monsoon circulation. However, knowledge about the radiative effects due to deposition of LAP in snow over TP is limited. In this study we have used a high-resolution WRF-Chem (coupled with online chemistry and snow-LAP-radiation model) simulations during 2013-2014 to estimate the spatio-temporal variation in LAP deposition on snow, specifically black carbon (BC) and dust particles, in Himalayas. Simulated distributions in meteorology, aerosol concentrations, snow albedo, snow grain size and snow depth are evaluated against satellite and in-situ measurements. The spatio-temporal change in snow albedo and snow grain size with variation in LAP deposition is investigated and the resulting shortwave LAP radiative forcing at surface is calculated. The LAP-radiative forcing due to aerosol deposition, both BC and dust, is higher in magnitude over Himalayan slopes (terrain height below 4 km) compared to that over TP (terrain height above 4 km). We found that the shortwave aerosol radiative forcing efficiency at surface due to increase in deposited mass of BC particles in snow layer ( 25 (W/m2)/ (mg/m2)) is manifold higher than the efficiency of dust particles ( 0.1 (W/m2)/ (mg/m2)) over TP. However, the radiative forcing of dust deposited in snow is similar in magnitude (maximum 20-30 W/m2) to that of BC deposited in snow over TP. This is mainly because the amount of dust deposited in snow over TP can be about 100 times greater than the amount of BC deposited in snow during polluted conditions. The impact of LAP on surface energy balance, snow melting and atmospheric thermodynamics is also examined.

An improved snow scheme for the ECMWF land surface model: Description and offline validation

Treesearch

Emanuel Dutra; Gianpaolo Balsamo; Pedro Viterbo; Pedro M. A. Miranda; Anton Beljaars; Christoph Schar; Kelly Elder

2010-01-01

A new snow scheme for the European Centre for Medium-Range Weather Forecasts (ECMWF) land surface model has been tested and validated. The scheme includes a new parameterization of snow density, incorporating a liquid water reservoir, and revised formulations for the subgrid snow cover fraction and snow albedo. Offline validation (covering a wide range of spatial and...

NOAA's National Snow Analyses

NASA Astrophysics Data System (ADS)

Carroll, T. R.; Cline, D. W.; Olheiser, C. M.; Rost, A. A.; Nilsson, A. O.; Fall, G. M.; Li, L.; Bovitz, C. T.

2005-12-01

NOAA's National Operational Hydrologic Remote Sensing Center (NOHRSC) routinely ingests all of the electronically available, real-time, ground-based, snow data; airborne snow water equivalent data; satellite areal extent of snow cover information; and numerical weather prediction (NWP) model forcings for the coterminous U.S. The NWP model forcings are physically downscaled from their native 13 km2 spatial resolution to a 1 km2 resolution for the CONUS. The downscaled NWP forcings drive an energy-and-mass-balance snow accumulation and ablation model at a 1 km2 spatial resolution and at a 1 hour temporal resolution for the country. The ground-based, airborne, and satellite snow observations are assimilated into the snow model's simulated state variables using a Newtonian nudging technique. The principle advantages of the assimilation technique are: (1) approximate balance is maintained in the snow model, (2) physical processes are easily accommodated in the model, and (3) asynoptic data are incorporated at the appropriate times. The snow model is reinitialized with the assimilated snow observations to generate a variety of snow products that combine to form NOAA's NOHRSC National Snow Analyses (NSA). The NOHRSC NSA incorporate all of the available information necessary and available to produce a "best estimate" of real-time snow cover conditions at 1 km2 spatial resolution and 1 hour temporal resolution for the country. The NOHRSC NSA consist of a variety of daily, operational, products that characterize real-time snowpack conditions including: snow water equivalent, snow depth, surface and internal snowpack temperatures, surface and blowing snow sublimation, and snowmelt for the CONUS. The products are generated and distributed in a variety of formats including: interactive maps, time-series, alphanumeric products (e.g., mean areal snow water equivalent on a hydrologic basin-by-basin basis), text and map discussions, map animations, and quantitative gridded products. The NOHRSC NSA products are used operationally by NOAA's National Weather Service field offices when issuing hydrologic forecasts and warnings including river and flood forecasts, water supply forecasts, and spring flood outlooks for the nation. Additionally, the NOHRSC NSA products are used by a wide variety of federal, state, local, municipal, private-sector, and general-public end-users with a requirement for real-time snowpack information. The paper discusses, in detail, the techniques and procedures used to create the NOHRSC NSA products and gives a number of examples of the real-time snow products generated and distributed over the NOHRSC web site (www.nohrsc.noaa.gov). Also discussed are major limitations of the approach, the most notable being deficiencies in observation of snow water equivalent. Snow observation networks generally lack the consistency and coverage needed to significantly improve confidence in snow model states through updating. Many regions of the world simply lack snow water equivalent observations altogether, a significant constraint on global application of the NSA approach.

Heat transfer and phase transitions of water in multi-layer cryolithozone-surface systems

NASA Astrophysics Data System (ADS)

Khabibullin, I. L.; Nigametyanova, G. A.; Nazmutdinov, F. F.

2018-01-01

A mathematical model for calculating the distribution of temperature and the dynamics of the phase transfor-mations of water in multilayer systems on permafrost-zone surface is proposed. The model allows one to perform calculations in the annual cycle, taking into account the distribution of temperature on the surface in warm and cold seasons. A system involving four layers, a snow or land cover, a top layer of soil, a layer of thermal-insulation materi-al, and a mineral soil, is analyzed. The calculations by the model allow one to choose the optimal thickness and com-position of the layers which would ensure the stability of structures built on the permafrost-zone surface.

Snowpack Chemistry of Reactive Gases at Station Concordia, Antarctica

NASA Astrophysics Data System (ADS)

Helmig, Detlev; Mass, Alex; Hueber, Jacques; Fain, Xavier; Dommergue, Aurelien; Barbero, Albane; Savarino, Joel

2013-04-01

During December 2012 a new experiment for the study of snow photochemical processes and surface gas exchange was installed at Dome Concordia, Antarctica. The experiment consists of two sampling manifolds ('snow tower') which facilitate the withdrawal of interstitial firn air from four depths in the snowpack and from above the surface. One of these snow towers can be shaded for investigation of the dependency of snow chemistry on solar radiation. A nearby 12 m meteorological tower facilitates above surface turbulence and trace gas gradient measurements. Temperature profiles and UV and IR light penetration are monitored in the snowpack. Air samples are directed through sampling lines to a nearby underground laboratory that houses the experiment control system and gas monitors. The system is fully automated, sampling gases from the array of inlet ports sequentially, and is intended to be operated continuously for a full annual cycle. The computerized control system can be accessed remotely for data retrieval and quality control and for configuring experimental details. Continuous gas measurements include ozone, nitrogen oxides, methane, carbon monoxide, and gaseous elemental mercury. Whole air samples were sampled on four occasions for volatile organic compound analysis. The objective of this research is the study of the year-round snowpack gas chemistry and its dependency on snowpack and above surface physical and environmental conditions. A particular emphasis will be the investigation of the effects of increased UV radiation during the occurrence of the stratospheric ozone hole. We will present the conceptual design of the experiment and data examples from the first three months of the experiment.

Assessment of climate variability of the Greenland Ice Sheet: Integration of in situ and satellite data

NASA Technical Reports Server (NTRS)

Steffen, K.; Abdalati, W.; Stroeve, J.; Key, J.

1994-01-01

The proposed research involves the application of multispectral satellite data in combination with ground truth measurements to monitor surface properties of the Greenland Ice Sheet which are essential for describing the energy and mass of the ice sheet. Several key components of the energy balance are parameterized using satellite data and in situ measurements. The analysis will be done for a ten year time period in order to get statistics on the seasonal and interannual variations of the surface processes and the climatology. Our goal is to investigate to what accuracy and over what geographic areas large scale snow properties and radiative fluxes can be derived based upon a combination of available remote sensing and meteorological data sets. Operational satellite sensors are calibrated based on ground measurements and atmospheric modeling prior to large scale analysis to ensure the quality of the satellite data. Further, several satellite sensors of different spatial and spectral resolution are intercompared to access the parameter accuracy. Proposed parameterization schemes to derive key component of the energy balance from satellite data are validated. For the understanding of the surface processes a field program was designed to collect information on spectral albedo, specular reflectance, soot content, grain size and the physical properties of different snow types. Further, the radiative and turbulent fluxes at the ice/snow surface are monitored for the parameterization and interpretation of the satellite data. The expected results include several baseline data sets of albedo, surface temperature, radiative fluxes, and different snow types of the entire Greenland Ice Sheet. These climatological data sets will be of potential use for climate sensitivity studies in the context of future climate change.

Measuring spatiotemporal variation in snow optical grain size under a subalpine forest canopy using contact spectroscopy

NASA Astrophysics Data System (ADS)

Molotch, Noah P.; Barnard, David M.; Burns, Sean P.; Painter, Thomas H.

2016-09-01

The distribution of forest cover exerts strong controls on the spatiotemporal distribution of snow accumulation and snowmelt. The physical processes that govern these controls are poorly understood given a lack of detailed measurements of snow states. In this study, we address one of many measurement gaps by using contact spectroscopy to measure snow optical grain size at high spatial resolution in trenches dug between tree boles in a subalpine forest. Trenches were collocated with continuous measurements of snow depth and vertical profiles of snow temperature and supplemented with manual measurements of snow temperature, geometric grain size, grain type, and density from trench walls. There was a distinct difference in snow optical grain size between winter and spring periods. In winter and early spring, when facetted snow crystal types were dominant, snow optical grain size was 6% larger in canopy gaps versus under canopy positions; a difference that was smaller than the measurement uncertainty. By midspring, the magnitude of snow optical grain size differences increased dramatically and patterns of snow optical grain size became highly directional with 34% larger snow grains in areas south versus north of trees. In winter, snow temperature gradients were up to 5-15°C m-1 greater under the canopy due to shallower snow accumulation. However, in canopy gaps, snow depths were greater in fall and early winter and therefore more significant kinetic growth metamorphism occurred relative to under canopy positions, resulting in larger snow grains in canopy gaps. Our findings illustrate the novelty of our method of measuring snow optical grain size, allowing for future studies to advance the understanding of how forest and meteorological conditions interact to impact snowpack evolution.

Space-time analysis of snow cover change in the Romanian Carpathians (2001-2016)

NASA Astrophysics Data System (ADS)

Micu, Dana; Cosmin Sandric, Ionut

2017-04-01

Snow cover is recognized as an essential climate variable, highly sensitive to the ongoing climate warming, which plays an important role in regulating mountain ecosystems. Evidence from the existing weather stations located above 800 m over the last 50 years points out that the climate of the Romanian Carpathians is visibly changing, showing an ongoing and consistent warming process. Quantifying and attributing the changes in snow cover on various spatial and temporal scales have a great environmental and socio-economic importance for this mountain region. The study is revealing the inter-seasonal changes in the timing and distribution of snow cover across the Romanian Carpathians, by combining gridded snow data (CARPATCLIM dataset, 1961-2010) and remote sensing data (2001-2016) in specific space-time assessment at regional scale. The geostatistical approach applied in this study, based on a GIS hotspot analysis, takes advantage of all the dimensions in the datasets, in order to understand the space-time trends in this climate variable at monthly time-scale. The MODIS AQUA and TERRA images available from 2001 to 2016 have been processed using ArcGIS for Desktop and Python programming language. All the images were masked out with the Carpathians boundary. Only the pixels with snow have been retained for analysis. The regional trends in snow cover distribution and timing have been analysed using Space-Time cube with ArcGIS for Desktop, according with Esri documentation using the Mann-Kendall trend test on every location with data as an independent bin time-series test. The study aimed also to assess the location of emerging hotspots of snow cover change in Carpathians. These hotspots have been calculated using Getis-Ord Gi* statistic for each bin using Hot Spot Analysis implemented in ArcGIS for Desktop. On regional scale, snow cover appear highly sensitive to the decreasing trends in air temperatures and land surface temperatures, combined with the decrease in seasonal precipitation, especially at lower elevations in all the three divisions of the Romanian Carpathians (generally below 1,700-1,800 m). The space-time patterns of snow cover change are dominated by a significant decreasing trend of snow days and earlier spring snow melt. The key findings of this study provides robust indication of a decreasing snow trends across the Carpathian Mountain region and could provide valuable spatial and temporal snow information for other related research fields as well as for an effective environmental monitoring in the mountain ecosystems of the Carpathian region

On charging of snow particles in blizzard

NASA Technical Reports Server (NTRS)

Shio, Hisashi

1991-01-01

The causes of the charge polarity on the blizzard, which consisted of fractured snow crystals and ice particles, were investigated. As a result, the charging phenomena showed that the characteristics of the blizzard are as follows: (1) In the case of the blizzard with snowfall, the fractured snow particles drifting near the surface of snow field (lower area: height 0.3 m) had positive charge, while those drifting at higher area (height 2 m) from the surface of snow field had negative charge. However, during the series of blizzards two kinds of particles positively and negatively charged were collected in equal amounts in a Faraday Cage. It may be considered that snow crystals with electrically neutral properties were separated into two kinds of snow flakes (charged positively and negatively) by destruction of the snow crystals. (2) In the case of the blizzard which consisted of irregularly formed ice drops (generated by peeling off the hardened snow field), the charge polarity of these ice drops salting over the snow field was particularly controlled by the crystallographic characteristics of the surface of the snow field hardened by the powerful wind pressure.

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.

BOREAS HYD-3 Subcanopy Meteorological Measurements

NASA Technical Reports Server (NTRS)

Hardy, Janet P.; Hall, Forrest G. (Editor); Knapp, David E. (Editor); Davis, Robert E.; Smith, David E. (Technical Monitor)

2000-01-01

The Boreal Ecosystem-Atmosphere Study (BOREAS) Hydrology (HYD)-3 team collected several data sets related to the hydrology of forested areas. This data set includes measurements of wind speed and direction; air temperature; relative humidity; and canopy, trunk, and snow surface temperatures within three forest types. The data were collected in the southern study area/Old Jack Pine (SSA-OJP) (1994), and SSA-OBS (Old Black Spruce), and SSA-OA (Old Aspen) (1996). Measurements were taken for three days in 1994 and four days at each site in 1996. These measurements were intended to be short term to allow the relationship between subcanopy measurements and those collected above the forest canopy to be determined. The subcanopy estimates of wind speed were used in a snow melt model to help predict the timing of snow ablation. The data are available in tabular ASCII files. The subcanopy meteorological measurement data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).

Assessing More than a Decade of Alaska/yukon, High Elevation, Glacier Ice/rock Landslides

NASA Astrophysics Data System (ADS)

Molnia, B. F.; Angeli, K.

2017-12-01

On September 14, 2005, an estimated 5.0x106 m3 of rock, glacier ice, and snow fell from below the summit of 3,236-m-high Mt. Steller, Alaska, onto a tributary of Bering Glacier. Next day photography of the slide and source area suggested that meltwater played a significant role in its origin. Aerial photography and space-based electro-optical imagery collected for months following the event recorded continuing evidence of meltwater flowing from the head-scarp region and continued ice and snow melt. We investigated five similar glacier ice-rock landslides. These originated from the north face of Mt. Steller in late 2005-early 2006, the south side of Waxell Ridge in late 2005-early 2006, Mt. Steele on July 24, 2007, Mt. Lituya on June 11, 2012, and Mt. La Perouse on February 16, 2014. None was triggered by a seismic event. Four were detected based on seismic events they generated. All source areas exhibited failed hanging glaciers and/or failed perennial snowfields. Five had detectable glacier hydrologic features (moulins, conduits, and collapsed englacial stream channels) in near-summit failed ice and snow margins. Four displayed fresh concave bedrock failure surfaces. All originated at locations where mean annual temperatures were below freezing. Our observations support water triggering each event. We propose that abnormally warm summer temperatures or extreme winter precipitation produced unusual volumes of water which saturated summit snow and ice and/or filled summit glacier channels and conduits with liquid water. Water reached the frozen water/bedrock interface, destabilizing the contact. Fresh concave bedrock failure surfaces suggest that glacier beds were adhering to steep bedrock surfaces composed of a mélange of freeze/thaw shattered rock held together by interstitial ice. When the mass of saturated glacier ice failed, the bedrock mélange also failed, exposing fresh bedrock scarp depressions and generating the observed gravel-dominated slide debris.

The Art and Science of Snow Microbiology: Data Paintings of the Finnish Arctic

NASA Astrophysics Data System (ADS)

Reasor, K.; Lipson, D.

2017-12-01

A challenge in science-art collaborations is to create artwork that accurately represents scientific results while standing as an independent art object. Art associated with science may merely be illustrative, serving to decorate a scientific study, or conversely, science-art may only superficially derive from data without addressing its broader scientific meaning. A fully integrated work of science-art requires copious communication between the scientist and artist. Here we present the results of a collaboration between a microbial ecologist and a painter, to study and depict the nature of microbial communities in the snowpack of the Finnish Arctic around Lake Kilpisjärvi. Snow profiles were studied along an altitudinal gradient that spanned the lake, a mountain birch forest, the transitional forest near tree line, and the alpine above tree line on the fell, Saana. Snow from the top, middle and bottom of each profile was characterized physically, chemically and microbiologically. The snowpack provided an insulating layer such that temperatures close to 0°C were found at the base of the snowpack. Windblown areas outside the protective influence of the forest (lake, alpine) had thinner, denser snowpacks. Bacterial cell counts (performed by flow cytometry) were highest in the protected area at the base of the snowpack, lowest in the middle and intermediate at the snow surface. Sequencing of the 16S rRNA gene showed a diverse assemblage of bacteria on the surface that resembled typical soil species, while the base harbored a community dominated by Gammaproteobacteria. The artist chose to depict the results using four pairs of paintings, corresponding to the four elevations. The pairs consist of a landscape oil painting of the site and a "data painting," in which a simplified version of the landscape is shown in grayscale and snow characteristics are overlaid in color. Snow density is shown using value (the lightness or darkness of a color) and temperature is coded in hue (warm to cold colors). Bacterial populations are shown as bright points, with density, color/shape and size indicative of population size, diversity and metabolic activity. The result is a set of paintings that capture the sense of the landscape while also revealing the hidden world where bacterial communities thrive under an insulative blanket of snow.

Incoming longwave radiation to melting snow: observations, sensitivity and estimation in Northern environments

NASA Astrophysics Data System (ADS)

Sicart, J. E.; Pomeroy, J. W.; Essery, R. L. H.; Bewley, D.

2006-11-01

At high latitudes, longwave radiation can provide similar, or higher, amounts of energy to snow than shortwave radiation due to the low solar elevation (cosine effect and increased scattering due to long atmospheric path lengths). This effect is magnified in mountains due to shading and longwave emissions from the complex topography. This study examines longwave irradiance at the snow surface in the Wolf Creek Research Basin, Yukon Territory, Canada (60° 36N, 134° 57W) during the springs of 2002 and 2004. Incoming longwave radiation was estimated from standard meteorological measurements by segregating radiation sources into clear sky, clouds and surrounding terrain. A sensitivity study was conducted to detect the atmospheric and topographic conditions under which emission from adjacent terrain significantly increases the longwave irradiance. The total incoming longwave radiation is more sensitive to sky view factor than to the temperature of the emitting terrain surfaces. Brutsaert's equation correctly simulates the clear-sky irradiance for hourly time steps using temperature and humidity. Longwave emissions from clouds, which raised longwave radiation above that from clear skies by 16% on average, were best estimated using daily atmospheric shortwave transmissivity and hourly relative humidity. An independent test of the estimation procedure for a prairie site near Saskatoon, Saskatchewan, Canada, indicated that the calculations are robust in late winter and spring conditions. Copyright

EOS Aqua AMSR-E Arctic Sea Ice Validation Program: Arctic2003 Aircraft Campaign Flight Report

NASA Technical Reports Server (NTRS)

Cavalieri, D. J.; Markus,T.

2003-01-01

In March 2003 a coordinated Arctic sea ice validation field campaign using the NASA Wallops P-3B aircraft was successfully completed. This campaign was part of the program for validating the Earth Observing System (EOS) Aqua Advanced Microwave Scanning Radiometer (AMSR-E) sea ice products. The AMSR-E, designed and built by the Japanese National Space Development Agency for NASA, was launched May 4, 2002 on the EOS Aqua spacecraft. The AMSR-E sea ice products to be validated include sea ice concentration, sea ice temperature, and snow depth on sea ice. This flight report describes the suite of instruments flown on the P-3, the objectives of each of the seven flights, the Arctic regions overflown, and the coordination among satellite, aircraft, and surface-based measurements. Two of the seven aircraft flights were coordinated with scientists making surface measurements of snow and ice properties including sea ice temperature and snow depth on sea ice at a study area near Barrow, AK and at a Navy ice camp located in the Beaufort Sea. Two additional flights were dedicated to making heat and moisture flux measurements over the St. Lawrence Island polynya to support ongoing air-sea-ice processes studies of Arctic coastal polynyas. The remaining flights covered portions of the Bering Sea ice edge, the Chukchi Sea, and Norton Sound.

Reconstructing thermal properties of firn at Summit, Greenland from a temperature profile

NASA Astrophysics Data System (ADS)

Giese, A. L.; Hawley, R. L.

2013-12-01

Thermodynamic properties of firn are important factors when considering energy balance and temperature-dependent physical processes in the near-surface of glaciers. Of particular interest is thermal diffusivity, which can take a range of values and which governs both the temperature gradient and its evolution through time. Given that temperature is a well-established driver of firn densification, a better understanding of heat transfer will permit greater accuracy in the compaction models essential for interpreting inter-annual and seasonal ice surface elevation changes detected by airborne and satellite altimetry. Due to its dependence on microstructure, diffusivity can vary significantly by location. Rather than directly measuring diffusivity or one of its proxies (e.g. density, hardness, shear strength), this study inverts the heat equation to reconstruct diffusivity values. This is a less logistically-intensive approach which circumvents many of the challenges associated with imperfect proxies and snow metamorphism during measurement. Hourly records (May 2004 - July 2008) from 8 thermistors placed in the top 10 m at Summit, Greenland provide temperature values for Summit's firn, which is broadly representative of firn across the ice sheet's dry snow zone. In this study, we use both physical analysis and a finite-difference numerical model to determine a diffusivity magnitude and gradient; we find that diffusivity of Summit firn falls in the lower end of the range expected from local density and temperature conditions alone (i.e. 15 - 36 m^2/a for firn at -30C). Further, we assess the utility of our modeling approach, explore the validity of assuming bulk conductive heat transfer when modeling temperature changes in non-homogeneous firn, and investigate the implications of a low-end diffusivity value for surface compaction modeling in Greenland.

Snow and Ice Applications of AVHRR in Polar Regions: Report of a Workshop

NASA Technical Reports Server (NTRS)

Steffen, K.; Bindschadler, R.; Casassa, G.; Comiso, J.; Eppler, D.; Fetterer, F.; Hawkins, J.; Key, J.; Rothrock, D.; Thomas, R.;

GPS interferometric reflectometry for ground-based remote sensing of snow depth and density

NASA Astrophysics Data System (ADS)

Nievinski, F. G.; Larson, K. M.; Gutmann, E. D.; Zavorotny, V.; Williams, M. W.

2011-12-01

GPS interferometric reflectometry (GPS-IR) is a method that exploits multipath for ground-based remote sensing in the surroundings of a GPS antenna. It operates on L-band, leveraging hundreds of conventional GPS sites existing in the U.S., with a typical footprint of 30-meter radius. Multipath is the coherent interference of line-of-sight and reflected signals; as the two go in and out of phase, the power recorded by a GPS interferometer goes through peaks and troughs that can be related to land surface characteristics, such as soil moisture and snow depth. GPS-IR has been demonstrated to be capable of retrieving snow depth during extended periods at various locations, as validated by comparisons with a continuously-operating terrestrial scanning laser, an airborne LIDAR campaign, manual stake surveys, and ultrasonic depth sensors. Here we explore the possibility of retrieving snow density, too. This will determine the feasibility and limitations of GPS-IR for monitoring of snow water equivalent (SWE). Data were collected at Niwot Ridge LTER in Colorado, at a 3,500-m altitude alpine tundra site. Niwot receives around 1,000 mm of precipitation per year and has a mean annual air temperature of -3.8°C. Snow density and temperature is measured in 10-cm vertical increments at snowpits dug approximately every week. A continuously-operating GPS system established in 2009 allows for measurement of the snowpack several times a day at multiple azimuths as satellites rise and set. The typical peak snow depth at the GPS site is 1.5 m, with a peak depth during the study period of 1.7 m in 2009/2010 and 2.5 m in 2010/2011; density ranged 200-600 kg/m3. We employ a forward/inverse model originally developed for snow depth and recently extended to account for layering to study both synthetic and real observations. We present comparisons of density estimates obtained using GPS-IR observations to snowpit field data, focusing initially on dry snow. In addition, we explore the sensitivity of the model to roughness, density, snow depth, and random noise. Synthetic observations derived from the forward model based on realistic snow profiles are utilized in the inverse model to quantify both the formal uncertainty and the expected error in parameter retrievals.

Accuracy assessment of land surface temperature retrievals from Landsat 7 ETM + in the Dry Valleys of Antarctica using iButton temperature loggers and weather station data.

PubMed

Brabyn, Lars; Zawar-Reza, Peyman; Stichbury, Glen; Cary, Craig; Storey, Bryan; Laughlin, Daniel C; Katurji, Marwan

2014-04-01

The McMurdo Dry Valleys of Antarctica are the largest snow/ice-free regions on this vast continent, comprising 1% of the land mass. Due to harsh environmental conditions, the valleys are bereft of any vegetation. Land surface temperature is a key determinate of microclimate and a driver for sensible and latent heat fluxes of the surface. The Dry Valleys have been the focus of ecological studies as they arguably provide the simplest trophic structure suitable for modelling. In this paper, we employ a validation method for land surface temperatures obtained from Landsat 7 ETM + imagery and compared with in situ land surface temperature data collected from four transects totalling 45 iButtons. A single meteorological station was used to obtain a better understanding of daily and seasonal cycles in land surface temperatures. Results show a good agreement between the iButton and the Landsat 7 ETM + product for clear sky cases. We conclude that Landsat 7 ETM + derived land surface temperatures can be used at broad spatial scales for ecological and meteorological research.

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.

Real-Time Alpine Measurement System Using Wireless Sensor Networks

PubMed Central

2017-01-01

Monitoring the snow pack is crucial for many stakeholders, whether for hydro-power optimization, water management or flood control. Traditional forecasting relies on regression methods, which often results in snow melt runoff predictions of low accuracy in non-average years. Existing ground-based real-time measurement systems do not cover enough physiographic variability and are mostly installed at low elevations. We present the hardware and software design of a state-of-the-art distributed Wireless Sensor Network (WSN)-based autonomous measurement system with real-time remote data transmission that gathers data of snow depth, air temperature, air relative humidity, soil moisture, soil temperature, and solar radiation in physiographically representative locations. Elevation, aspect, slope and vegetation are used to select network locations, and distribute sensors throughout a given network location, since they govern snow pack variability at various scales. Three WSNs were installed in the Sierra Nevada of Northern California throughout the North Fork of the Feather River, upstream of the Oroville dam and multiple powerhouses along the river. The WSNs gathered hydrologic variables and network health statistics throughout the 2017 water year, one of northern Sierra’s wettest years on record. These networks leverage an ultra-low-power wireless technology to interconnect their components and offer recovery features, resilience to data loss due to weather and wildlife disturbances and real-time topological visualizations of the network health. Data show considerable spatial variability of snow depth, even within a 1 km2 network location. Combined with existing systems, these WSNs can better detect precipitation timing and phase in, monitor sub-daily dynamics of infiltration and surface runoff during precipitation or snow melt, and inform hydro power managers about actual ablation and end-of-season date across the landscape. PMID:29120376

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.

Soil Biogeochemistry in a Changing Climate: Effect of Snow Removal

NASA Astrophysics Data System (ADS)

Patel, K.; Tatariw, C.; Fernandez, I. J.; Macrae, J. D.; Ohno, T.

2016-12-01

Winter snowpack plays an important role in ecosystem functioning, thermally insulating the subnivean soil from freezing temperatures. Wintertime microbial mineralization of organic material results in accumulation of nutrients under the snowpack, which are available post-melt for plant root uptake. The northeastern United States has experienced declining snow accumulation, and climate models project this trend will continue in the future. Intermittent and reduced snow cover increases soil freezing and frost damage, which can have implications on spring nutrient availability and forest productivity. We conducted a 2-year snow removal experiment in the Dwight B. DeMeritt Forest at the University of Maine to study subnivean winter processes, and to examine the effect of a decreased snowpack on soil winter and spring biogeochemistry. Surface organic soils were collected during winter and spring of 2015 and 2016, years with sharply contrasting snow accumulation, to track temporal changes in nutrient dynamics as the system evolved from under the snowpack. Laboratory extractions and incubations were performed to quantify the inorganic available nitrogen, dissolved organic carbon (DOC), and potential net N-mineralization (PNNM) in field moist soils. Snow removal resulted in decreased winter soil temperatures (2-8°C colder than the reference plots). There was an increased incidence of rain-on-soil events in the winter, forming concrete frost. Freeze-thaw cycles in the treatment plots resulted in higher NH4-N and DOC concentrations, but lower PNNM, compared to the reference plots. Treatment effects on DOC and NH4-N concentrations were not seen in the spring, although the effects on PNNM persisted. Our findings demonstrated that freeze-thaw cycles play an important role in the timing and magnitude of soil nutrient availability during the vernal transition. Understanding these processes becomes increasingly important when defining forest ecosystem response to a changing climate.

Real-Time Alpine Measurement System Using Wireless Sensor Networks.

PubMed

Malek, Sami A; Avanzi, Francesco; Brun-Laguna, Keoma; Maurer, Tessa; Oroza, Carlos A; Hartsough, Peter C; Watteyne, Thomas; Glaser, Steven D

2017-11-09

Monitoring the snow pack is crucial for many stakeholders, whether for hydro-power optimization, water management or flood control. Traditional forecasting relies on regression methods, which often results in snow melt runoff predictions of low accuracy in non-average years. Existing ground-based real-time measurement systems do not cover enough physiographic variability and are mostly installed at low elevations. We present the hardware and software design of a state-of-the-art distributed Wireless Sensor Network (WSN)-based autonomous measurement system with real-time remote data transmission that gathers data of snow depth, air temperature, air relative humidity, soil moisture, soil temperature, and solar radiation in physiographically representative locations. Elevation, aspect, slope and vegetation are used to select network locations, and distribute sensors throughout a given network location, since they govern snow pack variability at various scales. Three WSNs were installed in the Sierra Nevada of Northern California throughout the North Fork of the Feather River, upstream of the Oroville dam and multiple powerhouses along the river. The WSNs gathered hydrologic variables and network health statistics throughout the 2017 water year, one of northern Sierra's wettest years on record. These networks leverage an ultra-low-power wireless technology to interconnect their components and offer recovery features, resilience to data loss due to weather and wildlife disturbances and real-time topological visualizations of the network health. Data show considerable spatial variability of snow depth, even within a 1 km 2 network location. Combined with existing systems, these WSNs can better detect precipitation timing and phase in, monitor sub-daily dynamics of infiltration and surface runoff during precipitation or snow melt, and inform hydro power managers about actual ablation and end-of-season date across the landscape.

Snowpack spatial and temporal variability assessment using SMP high-resolution penetrometer

NASA Astrophysics Data System (ADS)

Komarov, Anton; Seliverstov, Yuriy; Sokratov, Sergey; Grebennikov, Pavel

2017-04-01

This research is focused on study of spatial and temporal variability of structure and characteristics of snowpack, quick identification of layers based on hardness and dispersion values received from snow micro penetrometer (SMP). We also discuss the detection of weak layers and definition of their parameters in non-alpine terrain. As long as it is the first SMP tool available in Russia, our intent is to test it in different climate and weather conditions. During two separate snowpack studies in plain and mountain landscapes, we derived density and grain size profiles by comparing snow density and grain size from snowpits and SMP measurements. The first case study was MSU meteorological observatory test site in Moscow. SMP data was obtained by 6 consecutive measurements along 10 m transects with a horizontal resolution of approximately 50 cm. The detailed description of snowpack structure, density, grain size, air and snow temperature was also performed. By comparing this information, the detailed scheme of snowpack evolution was created. The second case study was in Khibiny mountains. One 10-meter-long transect was made. SMP, density, grain size and snow temperature data was obtained with horizontal resolution of approximately 50 cm. The high-definition profile of snowpack density variation was acquired using received data. The analysis of data reveals high spatial and temporal variability in snow density and layer structure in both horizontal and vertical dimensions. It indicates that the spatial variability is exhibiting similar spatial patterns as surface topology. This suggests a strong influence from such factors as wind and liquid water pressure on the temporal and spatial evolution of snow structure. It was also defined, that spatial variation of snowpack characteristics is substantial even within homogeneous plain landscape, while in high-latitude mountain regions it grows significantly.

Bacterial responses to fluctuations and extremes in temperature and brine salinity at the surface of Arctic winter sea ice.

PubMed

Ewert, Marcela; Deming, Jody W

2014-08-01

Wintertime measurements near Barrow, Alaska, showed that bacteria near the surface of first-year sea ice and in overlying saline snow experience more extreme temperatures and salinities, and wider fluctuations in both parameters, than bacteria deeper in the ice. To examine impacts of such conditions on bacterial survival, two Arctic isolates with different environmental tolerances were subjected to winter-freezing conditions, with and without the presence of organic solutes involved in osmoprotection: proline, choline, or glycine betaine. Obligate psychrophile Colwellia psychrerythraea strain 34H suffered cell losses under all treatments, with maximal loss after 15-day exposure to temperatures fluctuating between -7 and -25 °C. Osmoprotectants significantly reduced the losses, implying that salinity rather than temperature extremes presents the greater stress for this organism. In contrast, psychrotolerant Psychrobacter sp. strain 7E underwent miniaturization and fragmentation under both fluctuating and stable-freezing conditions, with cell numbers increasing in most cases, implying a different survival strategy that may include enhanced dispersal. Thus, the composition and abundance of the bacterial community that survives in winter sea ice may depend on the extent to which overlying snow buffers against extreme temperature and salinity conditions and on the availability of solutes that mitigate osmotic shock, especially during melting. © 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved.

How Can Polarization States of Reflected Light from Snow Surfaces Inform Us on Surface Normals and Ultimately Snow Grain Size Measurements?

NASA Astrophysics Data System (ADS)

Schneider, A. M.; Flanner, M.; Yang, P.; Yi, B.; Huang, X.; Feldman, D.

2016-12-01

The Snow Grain Size and Pollution (SGSP) algorithm is a method applied to Moderate Resolution Imaging Spectroradiometer data to estimate snow grain size from space-borne measurements. Previous studies validate and quantify potential sources of error in this method, but because it assumes flat snow surfaces, however, large scale variations in surface normals can cause biases in its estimates due to its dependence on solar and observation zenith angles. To address these variations, we apply the Monte Carlo method for photon transport using data containing the single scattering properties of different ice crystals to calculate polarization states of reflected monochromatic light at 1500nm from modeled snow surfaces. We evaluate the dependence of these polarization states on solar and observation geometry at 1500nm because multiple scattering is generally a mechanism for depolarization and the ice crystals are relatively absorptive at this wavelength. Using 1500nm thus results in a higher number of reflected photons undergoing fewer scattering events, increasing the likelihood of reflected light having higher degrees of polarization. In evaluating the validity of the model, we find agreement with previous studies pertaining to near-infrared spectral directional hemispherical reflectance (i.e. black-sky albedo) and similarities in measured bidirectional reflectance factors, but few studies exist modeling polarization states of reflected light from snow surfaces. Here, we present novel results pertaining to calculated polarization states and compare dependences on solar and observation geometry for different idealized snow surfaces. If these dependencies are consistent across different ice particle shapes and sizes, then these findings could inform the SGSP algorithm by providing useful relationships between measurable physical quantities and solar and observation geometry to better understand variations in snow surface normals from remote sensing observations.

New Developments for Physically-based Falling Snow Retrievals over Land in Preparation for GPM

NASA Technical Reports Server (NTRS)

Jackson, Gail S.; Tokay, Ali; Kramer, Anne W.; Hudak, David

2008-01-01

The NASA Global Precipitation Measurement mission (GPM) concept centers on deploying a Core spacecraft carrying a dual-frequency precipitation radar and a microwave radiometric imager with channels from 10 to 183 GHz to serve as a precipitation physics observatory and a calibration reference to unify a constellation of dedicated and operational passive microwave sensors. Because of the extended orbit of the Core (plus or minus 65 deg) and the enhanced dual frequency radar and high frequency radiometer, GPM will be able to sense falling snow precipitation and light rain over land. Accordingly, GPM has partnered with the Canadian CloudSat/CALIPSO Validation Project (C3VP) to obtain observations to provide one of several important ground-based validation data sets around which the falling snow models and retrieval algorithms can be further developed and tested. In this work we compare and correlate the long time series (Nov.'06 - March '07) measurements of precipitation rate from parsivels to the passive (89, 150, 183 plus or minus 1, plus or minus 3, plus or minus 7 GHz) observations of NOAA's AMSU-B radiometer. We separate the comparisons into categories of no precipitation, liquid rain and falling snow precipitation. We found that there are similar TBs (especially at 89 and 150 GHz) for cases with falling snow and for non-precipitating cases. The comparisons indicate that surface emissivity contributions to the satellite observed TB over land can add uncertainty in detecting and estimating falling snow. The newest results show that by computing brightness temperatures based on CARE radiosonde data and a rough estimate of surface emissivity show that the cloud ice scattering signal in the AMSU-B data is detected. That is the differences in computed TB and AMSU-B TB for precipitating and non-precipitating cases are unique such that the precipitating and non-precipitating cases can be identified. These results require that the radiosonde releases are within an hour of the AMSU-B data. Forest fraction, snow cover, and measured emissivities were combined to calculate the surface emissivities.

Pyroclast/snow interactions and thermally driven slurry formation. Part 2: Experiments and theoretical extension to polydisperse tephra

USGS Publications Warehouse

Walder, J.S.

2000-01-01

Erosion of snow by pyroclastic flows and surges presumably involves mechanical scour, but there may be thermally driven phenomena involved as well. To investigate this possibility, layers of hot (up to 400??C), uniformly sized, fine- to medium-grained sand were emplaced vertically onto finely shaved ice ('snow'); thus there was no relative shear motion between sand and snow and no purely mechanical scour. In some cases large vapor bubbles, commonly more than 10 mm across, rose through the sand layer, burst at the surface, and caused complete convective overturn of the sand, which then scoured and mixed with snow and transformed into a slurry. In other cases no bubbling occurred and the sand passively melted its way downward into the snow as a wetting front moved upward into the sand. A continuum of behaviors between these two cases was observed. Vigorous bubbling and convection were generally favored by high temperature, small grain size, and small layer thickness. A physically based theory of heat- and mass transfer at the pyroclast/snow interface, developed in Part 1 of this paper, does a good job of explaining the observations as a manifestation of unstable vapor-driven fluidization. The theory, when extrapolated to the behavior of actual, poorly sorted pyroclastic flow sediments, leads to the prediction that the observed 'thermal-scour' phenomenon should also occur for many real pyroclastic flows passing over snow. 'Thermal scour' is therefore likely to be involved in the generation of lahars.

Small scale variability of snow properties on Antarctic sea ice

NASA Astrophysics Data System (ADS)

Wever, Nander; Leonard, Katherine; Paul, Stephan; Jacobi, Hans-Werner; Proksch, Martin; Lehning, Michael

2016-04-01

Snow on sea ice plays an important role in air-ice-sea interactions, as snow accumulation may for example increase the albedo. Snow is also able to smooth the ice surface, thereby reducing the surface roughness, while at the same time it may generate new roughness elements by interactions with the wind. Snow density is a key property in many processes, for example by influencing the thermal conductivity of the snow layer, radiative transfer inside the snow as well as the effects of aerodynamic forcing on the snowpack. By comparing snow density and grain size from snow pits and snow micro penetrometer (SMP) measurements, highly resolved density and grain size profiles were acquired during two subsequent cruises of the RV Polarstern in the Weddell Sea, Antarctica, between June and October 2013. During the first cruise, SMP measurements were done along two approximately 40 m transects with a horizontal resolution of approximately 30 cm. During the second cruise, one transect was made with approximately 7.5 m resolution over a distance of 500 m. Average snow densities are about 300 kg/m3, but the analysis also reveals a high spatial variability in snow density on sea ice in both horizontal and vertical direction, ranging from roughly 180 to 360 kg/m3. This variability is expressed by coherent snow structures over several meters. On the first cruise, the measurements were accompanied by terrestrial laser scanning (TLS) on an area of 50x50 m2. The comparison with the TLS data indicates that the spatial variability is exhibiting similar spatial patterns as deviations in surface topology. This suggests a strong influence from surface processes, for example wind, on the temporal development of density or grain size profiles. The fundamental relationship between variations in snow properties, surface roughness and changes therein as investigated in this study is interpreted with respect to large-scale ice movement and the 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.

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 negative spectral gradient driving the passive microwave algorithm is enhanced. Because the current generation of microwave snow algorithms is unable to consistently detect shallow and intermittent snow, we combine visible satellite data with the microwave data in a single blended product to overcome this problem. For the period 1978 to 2002 we combine data from the NOAA weekly snow charts with passive microwave data from the SMMR and SSM/I brightness temperature record. For the current and future time period we blend MODIS and AMSR-E data sets, both of which have greatly enhanced spatial resolution compared to the earlier data sources. Because it is not possible to determine snow depth or snow water equivalent from visible data, the regions where only the NOAA or MODIS data indicate snow are defined as "shallow snow". However, because our current blended product is being developed in the 25 km EASE-Grid and the MODIS data being used are in the Climate Modelers Grid (CMG) at approximately 5 km (0.05 deg.) the blended product also includes percent snow cover over the larger grid cell. A prototype version of the blended MODIS/AMSR-E product will be available in near real-time from NSIDC during the 2002-2003 winter season.

Long-term variability in Northern Hemisphere snow cover and associations with warmer winters

USGS Publications Warehouse

McCabe, Gregory J.; Wolock, David M.

2010-01-01

A monthly snow accumulation and melt model is used with gridded monthly temperature and precipitation data for the Northern Hemisphere to generate time series of March snow-covered area (SCA) for the period 1905 through 2002. The time series of estimated SCA for March is verified by comparison with previously published time series of SCA for the Northern Hemisphere. The time series of estimated Northern Hemisphere March SCA shows a substantial decrease since about 1970, and this decrease corresponds to an increase in mean winter Northern Hemisphere temperature. The increase in winter temperature has caused a decrease in the fraction of precipitation that occurs as snow and an increase in snowmelt for some parts of the Northern Hemisphere, particularly the mid-latitudes, thus reducing snow packs and March SCA. In addition, the increase in winter temperature and the decreases in SCA appear to be associated with a contraction of the circumpolar vortex and a poleward movement of storm tracks, resulting in decreased precipitation (and snow) in the low- to mid-latitudes and an increase in precipitation (and snow) in high latitudes. If Northern Hemisphere winter temperatures continue to warm as they have since the 1970s, then March SCA will likely continue to decrease.

Long-term variability in Northern Hemisphere snow cover and associations with warmer winters

USGS Publications Warehouse

McCabe, G.J.; Wolock, D.M.

2010-01-01

A monthly snow accumulation and melt model is used with gridded monthly temperature and precipitation data for the Northern Hemisphere to generate time series of March snow-covered area (SCA) for the period 1905 through 2002. The time series of estimated SCA for March is verified by comparison with previously published time series of SCA for the Northern Hemisphere. The time series of estimated Northern Hemisphere March SCA shows a substantial decrease since about 1970, and this decrease corresponds to an increase in mean winter Northern Hemisphere temperature. The increase in winter temperature has caused a decrease in the fraction of precipitation that occurs as snow and an increase in snowmelt for some parts of the Northern Hemisphere, particularly the mid-latitudes, thus reducing snow packs and March SCA. In addition, the increase in winter temperature and the decreases in SCA appear to be associated with a contraction of the circumpolar vortex and a poleward movement of storm tracks, resulting in decreased precipitation (and snow) in the low- to mid-latitudes and an increase in precipitation (and snow) in high latitudes. If Northern Hemisphere winter temperatures continue to warm as they have since the 1970s, then March SCA will likely continue to decrease. ?? 2009 Springer Science+Business Media B.V.

Snow and Ice Products from the Moderate Resolution Imaging Spectroradiometer

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Salomonson, Vincent V.; Riggs, George A.; Klein, Andrew G.

2003-01-01

Snow and sea ice products, derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument, flown on the Terra and Aqua satellites, are or will be available through the National Snow and Ice Data Center Distributed Active Archive Center (DAAC). The algorithms that produce the products are automated, thus providing a consistent global data set that is suitable for climate studies. The suite of MODIS snow products begins with a 500-m resolution, 2330-km swath snow-cover map that is then projected onto a sinusoidal grid to produce daily and 8-day composite tile products. The sequence proceeds to daily and 8-day composite climate-modeling grid (CMG) products at 0.05 resolution. A daily snow albedo product will be available in early 2003 as a beta test product. The sequence of sea ice products begins with a swath product at 1-km resolution that provides sea ice extent and ice-surface temperature (IST). The sea ice swath products are then mapped onto the Lambert azimuthal equal area or EASE-Grid projection to create a daily and 8-day composite sea ice tile product, also at 1 -km resolution. Climate-Modeling Grid (CMG) sea ice products in the EASE-Grid projection at 4-km resolution are planned for early 2003.

Goddard Laboratory for Atmospheric Sciences physical retrieval system for remote determination of weather and climate parameter from HIRS2 and MSU observations

NASA Technical Reports Server (NTRS)

Susskind, J.

1984-01-01

At the Goddard Laboratory for Atmospheric Sciences (GLAS) a physically based satellite temperature sounding retrieval system, involving the simultaneous analysis of HIRS2 and MSU sounding data, was developed for determining atmospheric and surface conditions which are consistent with the observed radiances. In addition to determining accurate atmospheric temperature profiles even in the presence of cloud contamination, the system provides global estimates of day and night sea or land surface temperatures, snow and ice cover, and parameters related to cloud cover. Details of the system are described elsewhere. A brief overview of the system is presented, as well as recent improvements and previously unpublished results, relating to the sea-surface intercomparison workshop, the diurnal variation of ground temperatures, and forecast impact tests.

Evaluation of MODIS Land Surface Temperature with In Situ Snow Surface Temperature from CREST-SAFE

NASA Astrophysics Data System (ADS)

Perez Diaz, C. L.; Lakhankar, T.; Romanov, P.; Munoz, J.; Khanbilvardi, R.; Yu, Y.

2016-12-01

This paper presents the procedure and results of a temperature-based validation approach for the Moderate Resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature (LST) product provided by the National Aeronautics and Space Administration (NASA) Terra and Aqua Earth Observing System satellites using in situ LST observations recorded at the Cooperative Remote Sensing Science and Technology Center - Snow Analysis and Field Experiment (CREST-SAFE) during the years of 2013 (January-April) and 2014 (February-April). A total of 314 day and night clear-sky thermal images, acquired by the Terra and Aqua satellites, were processed and compared to ground-truth data from CREST-SAFE with a frequency of one measurement every 3 min. Additionally, this investigation incorporated supplementary analyses using meteorological CREST-SAFE in situ variables (i.e. wind speed, cloud cover, incoming solar radiation) to study their effects on in situ snow surface temperature (T-skin) and T-air. Furthermore, a single pixel (1km2) and several spatially averaged pixels were used for satellite LST validation by increasing the MODIS window size to 5x5, 9x9, and 25x25 windows for comparison. Several trends in the MODIS LST data were observed, including the underestimation of daytime values and nighttime values. Results indicate that, although all the data sets (Terra and Aqua, diurnal and nocturnal) showed high correlation with ground measurements, day values yielded slightly higher accuracy ( 1°C), both suggesting that MODIS LST retrievals are reliable for similar land cover classes and atmospheric conditions. Results from the CREST-SAFE in situ variables' analyses indicate that T-air is commonly higher than T-skin, and that a lack of cloud cover results in: lower T-skin and higher T-air minus T-skin difference (T-diff). Additionally, the study revealed that T-diff is inversely proportional to cloud cover, wind speed, and incoming solar radiation. Increasing the MODIS window size showed an overestimation of in situ LST and some improvement in the daytime Terra and nighttime Aqua biases, with the highest accuracy achieved with the 5x5 window. A comparison between MODIS emmisivity from bands 31, 32, and in situ emissivity showed that emissivity errors (Relative error = -.003) were insignificant.

On the radiative effects of light-absorbing impurities on snowpack evolution

NASA Astrophysics Data System (ADS)

Dumont, M.; Tuzet, F.; Lafaysse, M.; Arnaud, L.; Picard, G.; Lejeune, Y.; Lamare, M.; Morin, S.; Voisin, D.; Di Mauro, B.

2017-12-01

The presence of light absorbing impurities in snow strongly decreases snow reflectance leading to an increase in the amount of solar energy absorbed by the snowpack. This effect is also known as impurities direct radiative effect. The change in the amount of energy absorbed by the snowpack modifies the temperature profile inside the snowpack and in turn snow metamorphism (impurities indirect radiative effects). In this work, we used the detailed snowpack model SURFEX/ISBA-Crocus with an explicit representation of snow light-absorbing impurities content (Tuzet et al., 2017) fed by medium-resolution ALADIN-Climate atmospheric model to represent dust and black carbon atmospheric deposition fluxes. The model is used at two sites: Col de Porte (medium elevation site in the French Alps) and Torgnon (high elevation site in the Italian Alps). The simulations are compared to in-situ observations and used to quantify the effects of light-absorbing impurities on snow melt rate and timing. The respective parts of the direct and indirect radiative effects of light-absorbing impurities in snow are also computed for the two sites, emphasizing the need to account for the interactions between snow metamorphism and LAI radiative properties, to accurately predict the effects of light-absorbing impurities in snow. Moreover, we describe how automated hyperspectral reflectance can be used to estimate effective impurities surface content in snow. Finally we demonstrate how these reflectances measurements either from in situ or satellite data can be used via an assimilation scheme to constrain snowpack ensemble simulations and better predict the snowpack state and evolution.

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...

Snowpack ground truth: Radar test site, Steamboat Springs, Colorado, 8-16 April 1976

NASA Technical Reports Server (NTRS)

Howell, S.; Jones, E. B.; Leaf, C. F.

1976-01-01

Ground-truth data taken at Steamboat Springs, Colorado is presented. Data taken during the period April 8, 1976 - April 16, 1976 included the following: (1) snow depths and densities at selected locations (using a Mount Rose snow tube); (2) snow pits for temperature, density, and liquid water determinations using the freezing calorimetry technique and vertical layer classification; (3) snow walls were also constructed of various cross sections and documented with respect to sizes and snow characteristics; (4) soil moisture at selected locations; and (5) appropriate air temperature and weather data.

Determination of cloud liquid water content using the SSM/I

NASA Technical Reports Server (NTRS)

Alishouse, John C.; Snider, Jack B.; Westwater, Ed R.; Swift, Calvin T.; Ruf, Christopher S.

1990-01-01

As part of a calibration/validation effort for the special sensor microwave/imager (SSM/I), coincident observations of SSM/I brightness temperatures and surface-based observations of cloud liquid water were obtained. These observations were used to validate initial algorithms and to derive an improved algorithm. The initial algorithms were divided into latitudinal-, seasonal-, and surface-type zones. It was found that these initial algorithms, which were of the D-matrix type, did not yield sufficiently accurate results. The surface-based measurements of channels were investigated; however, the 85V channel was excluded because of excessive noise. It was found that there is no significant correlation between the SSM/I brightness temperatures and the surface-based cloud liquid water determination when the background surface is land or snow. A high correlation was found between brightness temperatures and ground-based measurements over the ocean.

Northern Hemisphere Autumn and Winter Climate Responses to Realistic Tibetan Plateau and Mongolia Snow Anomalies

NASA Astrophysics Data System (ADS)

Wu, Q.; Yao, Y.; Liu, S.

2017-12-01

The impact of the Eurasian snow cover extent (SCE) on the Northern Hemisphere (NH) circulation is first investigated by applying a lagged maximum covariance analysis (MCA) to monthly satellite-derived SCE and NCEP reanalysis data. Wintertime atmospheric signals significantly correlated with persistently autumn-early winter SCE anomalies are found in the leading two MCA modes. The first MCA mode indicates the effect of Eurasian snow cover anomalies on the Arctic Oscillation/North Atlantic Oscillation (AO/NAO). The second MCA mode links a persistent dipole of autumn and winter SCE anomalies over the Tibetan Plateau (TP) and Mongolia with winter Pacific-North America (PNA)-like atmospheric variations. A modeling study further investigates atmospheric responses to above TP and Mongolia snow forcings using multiple ensemble transient integrations of the CAM4 and CLM4.0 models. Model boundary conditions are based on climatological sea ice extent (SIE) and sea surface temperature (SST), and satellite observations of SCE and snow water equivalent (SWE) over the TP and Mongolia from October to March in 1997/98 (heavy TP and light Mongolia snow) and 1984/85 (light TP and heavy Mongolia snow), with model derived SCE and SWE elsewhere. In various forcing experiments, the ensemble-mean difference between simulations with these two extreme snow states identifies local, distant, concurrent, and delayed climatic responses. The main atmospheric responses to a dipole of high TP and low Mongolia SCE persisting from October to March (versus the opposite extreme) are strong TP surface cooling, warming in the surrounding China and Mongolia region, and a winter positive PNA-like response. The localized response is maintained by persistent diabatic cooling or heating, and the remote PNA response results mainly from the increased horizontal eastward propagation of stationary Rossby wave energy due to persistent TP snow forcing and also a winter transient eddy feedback mechanism. With a less persistent dipole anomaly in autumn or winter only, local responses are similar depending on the specific anomalies, but the winter PNA-like response is nearly absent or noticeably reduced.

[Monitoring on spatial and temporal changes of snow cover in the Heilongjiang Basin based on remote sensing].

PubMed

Yu, Ling-Xue; Zhang, Shu-Wen; Guan, Cong; Yan, Feng-Qin; Yang, Chao-Bin; Bu, Kun; Yang, Jiu-Chun; Chang, Li-Ping

2014-09-01

This paper extracted and verified the snow cover extent in Heilongjiang Basin from 2003 to 2012 based on MODIS Aqua and Terra data, and the seasonal and interannual variations of snow cover extent were analyzed. The result showed that the double-star composite data reduced the effects of clouds and the overall accuracy was more than 91%, which could meet the research requirements. There existed significant seasonal variation of snow cover extent. The snow cover area was almost zero in July and August while in January it expanded to the maximum, which accounted for more than 80% of the basin. According to the analysis on the interannual variability of snow cover, the maximum winter snow cover areas in 2003-2004 and 2009-2010 (>180 x 10(4) km2) were higher than that of 2011 (150 x 10(4) km2). Meanwhile, there were certain correlations between the interannual fluctuations of snow cover and the changes of average annual temperature and precipitation. The year with the low snow cover was corresponding to less annual rainfall and higher average temperature, and vice versa. The spring snow cover showed a decreasing trend from 2003 to 2012, which was closely linked with decreasing precipitation and increasing temperature.

Soil temperature investigations using satellite acquired thermal-infrared data in semi-arid regions. Thesis. Final Report; [Utah

NASA Technical Reports Server (NTRS)

Day, R. L.; Petersen, G. W.

1983-01-01

Thermal-infrared data from the Heat Capacity Mapping Mission satellite were used to map the spatial distribution of diurnal surface temperatures and to estimate mean annual soil temperatures (MAST) and annual surface temperature amplitudes (AMP) in semi-arid east central Utah. Diurnal data with minimal snow and cloud cover were selected for five dates throughout a yearly period and geometrically co-registered. Rubber-sheet stretching was aided by the WARP program which allowed preview of image transformations. Daytime maximum and nighttime minimum temperatures were averaged to generation average daily temperature (ADT) data set for each of the five dates. Five ADT values for each pixel were used to fit a sine curve describing the theoretical annual surface temperature response as defined by a solution of a one-dimensinal heat flow equation. Linearization of the equation produced estimates of MAST and AMP plus associated confidence statistics. MAST values were grouped into classes and displayed on a color video screen. Diurnal surface temperatures and MAST were primarily correlated with elevation.

Mathematical Modelling of Arctic Polygonal Tundra with Ecosys: 1. Microtopography Determines How Active Layer Depths Respond to Changes in Temperature and Precipitation

NASA Astrophysics Data System (ADS)

Grant, R. F.; Mekonnen, Z. A.; Riley, W. J.; Wainwright, H. M.; Graham, D.; Torn, M. S.

2017-12-01

Microtopographic variation that develops among features (troughs, rims, and centers) within polygonal landforms of coastal arctic tundra strongly affects movement of surface water and snow and thereby affects soil water contents (θ) and active layer depth (ALD). Spatial variation in ALD among these features may exceed interannual variation in ALD caused by changes in climate and so needs to be represented in projections of changes in arctic ALD. In this study, increases in near-surface θ with decreasing surface elevation among polygon features at the Barrow Experimental Observatory (BEO) were modeled from topographic effects on redistribution of surface water and snow and from lateral water exchange with a subsurface water table during a model run from 1981 to 2015. These increases in θ caused increases in thermal conductivity that in turn caused increases in soil heat fluxes and hence in ALD of up to 15 cm with lower versus higher surface elevation which were consistent with increases measured at BEO. The modeled effects of θ caused interannual variation in maximum ALD that compared well with measurements from 1985 to 2015 at the Barrow Circumpolar Active Layer Monitoring (CALM) site (R2 = 0.61, RMSE = 0.03 m). For higher polygon features, interannual variation in ALD was more closely associated with annual precipitation than mean annual temperature, indicating that soil wetting from increases in precipitation may hasten permafrost degradation beyond that caused by soil warming from increases in air temperature. This degradation may be more rapid if increases in precipitation cause sustained wetting in higher features.

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 visible fractions of the downward shortwave radiant flux. This result suggests that it is necessary for snowpack models to consider changes in the visible and near-infrared fractions of the downward shortwave radiant flux caused by the presence of cloud cover to reproduce realistic temporal changes in the snow albedo and consequently the surface energy balance.

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 dust-laden and dust-free snow covered regions. Additionally, spatio-temporal and intra-seasonal variations of LER, along with snow cover information, are used to characterize the seasonal melt pattern and thus to distinguish the outstanding aerosol-induced snowmelt signal. Results from this observational work are expected to provide better understanding of the radiative impact of aerosols over snow surface, especially its role in the Himalayan hydro-glacialogical variability.

Sliding temperatures of ice skates

NASA Astrophysics Data System (ADS)

Colbeck, S. C.; Najarian, L.; Smith, H. B.

1997-06-01

The two theories developed to explain the low friction of ice, pressure melting and frictional heating, require opposite temperature shifts at the ice-skate interface. The arguments against pressure melting are strong, but only theoretical. A set of direct temperature measurements shows that frictional heating is the dominant mechanism because temperature behaves in the manner predicted by the theory of frictional heating. Like snow skis, ice skates are warmed by sliding and then cool when the sliding stops. The temperature increases with speed and with thermal insulation. The sliding leaves a warm track on the ice surface behind the skate and the skate sprays warm ejecta.

Snow observations in Mount Lebanon (2011-2016)

NASA Astrophysics Data System (ADS)

Fayad, Abbas; Gascoin, Simon; Faour, Ghaleb; Fanise, Pascal; Drapeau, Laurent; Somma, Janine; Fadel, Ali; Bitar, Ahmad Al; Escadafal, Richard

2017-08-01

We present a unique meteorological and snow observational dataset in Mount Lebanon, a mountainous region with a Mediterranean climate, where snowmelt is an essential water resource. The study region covers the recharge area of three karstic river basins (total area of 1092 km2 and an elevation up to 3088 m). The dataset consists of (1) continuous meteorological and snow height observations, (2) snowpack field measurements, and (3) medium-resolution satellite snow cover data. The continuous meteorological measurements at three automatic weather stations (MZA, 2296 m; LAQ, 1840 m; and CED, 2834 m a.s.l.) include surface air temperature and humidity, precipitation, wind speed and direction, incoming and reflected shortwave irradiance, and snow height, at 30 min intervals for the snow seasons (November-June) between 2011 and 2016 for MZA and between 2014 and 2016 for CED and LAQ. Precipitation data were filtered and corrected for Geonor undercatch. Observations of snow height (HS), snow water equivalent, and snow density were collected at 30 snow courses located at elevations between 1300 and 2900 m a.s.l. during the two snow seasons of 2014-2016 with an average revisit time of 11 days. Daily gap-free snow cover extent (SCA) and snow cover duration (SCD) maps derived from MODIS snow products are provided for the same period (2011-2016). We used the dataset to characterize mean snow height, snow water equivalent (SWE), and density for the first time in Mount Lebanon. Snow seasonal variability was characterized with high HS and SWE variance and a relatively high snow density mean equal to 467 kg m-3. We find that the relationship between snow depth and snow density is specific to the Mediterranean climate. The current model explained 34 % of the variability in the entire dataset (all regions between 1300 and 2900 m a.s.l.) and 62 % for high mountain regions (elevation 2200-2900 m a.s.l.). The dataset is suitable for the investigation of snow dynamics and for the forcing and validation of energy balance models. Therefore, this dataset bears the potential to greatly improve the quantification of snowmelt and mountain hydrometeorological processes in this data-scarce region of the eastern Mediterranean. The DOI for the data is https://doi.org/10.5281/zenodo.583733.

Assessing snow extent data sets over North America to inform and improve trace gas retrievals from solar backscatter

NASA Astrophysics Data System (ADS)

Cooper, Matthew J.; Martin, Randall V.; Lyapustin, Alexei I.; McLinden, Chris A.

2018-05-01

Accurate representation of surface reflectivity is essential to tropospheric trace gas retrievals from solar backscatter observations. Surface snow cover presents a significant challenge due to its variability and thus snow-covered scenes are often omitted from retrieval data sets; however, the high reflectance of snow is potentially advantageous for trace gas retrievals. We first examine the implications of surface snow on retrievals from the upcoming TEMPO geostationary instrument for North America. We use a radiative transfer model to examine how an increase in surface reflectivity due to snow cover changes the sensitivity of satellite retrievals to NO2 in the lower troposphere. We find that a substantial fraction (> 50 %) of the TEMPO field of regard can be snow covered in January and that the average sensitivity to the tropospheric NO2 column substantially increases (doubles) when the surface is snow covered.We then evaluate seven existing satellite-derived or reanalysis snow extent products against ground station observations over North America to assess their capability of informing surface conditions for TEMPO retrievals. The Interactive Multisensor Snow and Ice Mapping System (IMS) had the best agreement with ground observations (accuracy of 93 %, precision of 87 %, recall of 83 %). Multiangle Implementation of Atmospheric Correction (MAIAC) retrievals of MODIS-observed radiances had high precision (90 % for Aqua and Terra), but underestimated the presence of snow (recall of 74 % for Aqua, 75 % for Terra). MAIAC generally outperforms the standard MODIS products (precision of 51 %, recall of 43 % for Aqua; precision of 69 %, recall of 45 % for Terra). The Near-real-time Ice and Snow Extent (NISE) product had good precision (83 %) but missed a significant number of snow-covered pixels (recall of 45 %). The Canadian Meteorological Centre (CMC) Daily Snow Depth Analysis Data set had strong performance metrics (accuracy of 91 %, precision of 79 %, recall of 82 %). We use the Fscore, which balances precision and recall, to determine overall product performance (F = 85 %, 82 (82) %, 81 %, 58 %, 46 (54) % for IMS, MAIAC Aqua (Terra), CMC, NISE, MODIS Aqua (Terra), respectively) for providing snow cover information for TEMPO retrievals from solar backscatter observations. We find that using IMS to identify snow cover and enable inclusion of snow-covered scenes in clear-sky conditions across North America in January can increase both the number of observations by a factor of 2.1 and the average sensitivity to the tropospheric NO2 column by a factor of 2.7.

Inventory of File sref_nmb.t03z.pgrb212.p1.f06.grib2

Science.gov Websites

surface WEASD 6 hour fcst Water Equivalent of Accumulated Snow Depth [kg/m^2] 016 surface APCP 3-6 hour surface WEASD 3-6 hour acc Water Equivalent of Accumulated Snow Depth [kg/m^2] 019 surface CSNOW 6 hour (non-convective) [kg/m^2] 417 surface SNOM 3-6 hour acc Snow Melt [kg/m^2] 418 surface LHTFL 3-6 hour

Inventory of File sref_nmm.t03z.pgrb212.p1.f06.grib2

Science.gov Websites

surface WEASD 6 hour fcst Water Equivalent of Accumulated Snow Depth [kg/m^2] 016 surface APCP 3-6 hour surface WEASD 3-6 hour acc Water Equivalent of Accumulated Snow Depth [kg/m^2] 019 surface CSNOW 6 hour (non-convective) [kg/m^2] 417 surface SNOM 3-6 hour acc Snow Melt [kg/m^2] 418 surface LHTFL 0-6 hour

BOREAS AES Campbell Scientific Surface Meteorological Data

NASA Technical Reports Server (NTRS)

Atkinson, G. Barrie; Funk, Barrie; Knapp. David E. (Editor); Hall, Forrest G. (Editor)

2000-01-01

Canadian AES personnel collected data related to surface and atmospheric meteorological conditions over the BOREAS region. This data set contains 15-minute meteorological data from 14 automated meteorology stations located across the BOREAS region. Included in this data are parameters of date, time, mean sea level pressure, station pressure, temperature, dew point, wind speed, resultant wind speed, resultant wind direction, peak wind, precipitation, maximum temperature in the last hour, minimum temperature in the last hour, pressure tendency, liquid precipitation in the last hour, relative humidity, precipitation from a weighing gauge, and snow depth. Temporally, the data cover the period of August 1993 to December 1996. The data are provided in tabular ASCII files, and are classified as AFM-Staff data.

Role of the Soil Thermal Inertia in the short term variability of the surface temperature and consequences for the soil-moisture temperature feedback

NASA Astrophysics Data System (ADS)

Cheruy, Frederique; Dufresne, Jean-Louis; Ait Mesbah, Sonia; Grandpeix, Jean-Yves; Wang, Fuxing

2017-04-01

A simple model based on the surface energy budget at equilibrium is developed to compute the sensitivity of the climatological mean daily temperature and diurnal amplitude to the soil thermal inertia. It gives a conceptual framework to quantity the role of the atmospheric and land surface processes in the surface temperature variability and relies on the diurnal amplitude of the net surface radiation, the sensitivity of the turbulent fluxes to the surface temperature and the thermal inertia. The performances of the model are first evaluated with 3D numerical simulations performed with the atmospheric (LMDZ) and land surface (ORCHIDEE) modules of the Institut Pierre Simon Laplace (IPSL) climate model. A nudging approach is adopted, it prevents from using time-consuming long-term simulations required to account for the natural variability of the climate and allow to draw conclusion based on short-term (several years) simulations. In the moist regions the diurnal amplitude and the mean surface temperature are controlled by the latent heat flux. In the dry areas, the relevant role of the stability of the boundary layer and of the soil thermal inertia is demonstrated. In these regions, the sensitivity of the surface temperature to the thermal inertia is high, due to the high contribution of the thermal flux to the energy budget. At high latitudes, when the sensitivity of turbulent fluxes is dominated by the day-time sensitivity of the sensible heat flux to the surface temperature and when this later is comparable to the thermal inertia term of the sensitivity equation, the surface temperature is also partially controlled by the thermal inertia which can rely on the snow properties; In the regions where the latent heat flux exhibits a high day-to-day variability, such as transition regions, the thermal inertia has also significant impact on the surface temperature variability . In these not too wet (energy limited) and not too dry (moisture-limited) soil moisture (SM) ''hot spots'', it is generally admitted that the variability of the surface temperature is explained by the soil moisture trough its control on the evaporation. This work suggests that the impact of the soil moisture on the temperature through its impact on the thermal inertia can be as important as its direct impact on the evaporation. Contrarily to the evaporation related soil-moisture temperature negative feedback, the thermal inertia soil-moisture related feedback newly identified by this work is a positive feedback which limits the cooling when the soil moisture increases. These results suggest that uncertainties in the representation of the soil and snow thermal properties can be responsible of significant biases in numerical simulations and emphasize the need to carefully document and evaluate these quantities in the Land Surface Modules implemented in the climate models.

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.

Spatial variation in energy exchange across coastal environments in Greenland

NASA Astrophysics Data System (ADS)

Lund, M.; Abermann, J.; Citterio, M.; Hansen, B. U.; Larsen, S. H.; Stiegler, C.; Sørensen, L. L.; van As, D.

2015-12-01

The surface energy partitioning in Arctic terrestrial and marine areas is a crucial process, regulating snow, glacier ice and sea ice melt, and permafrost thaw, as well as modulating Earth's climate on both local, regional, and eventually, global scales. The Arctic region has warmed approximately twice as much as the global average, due to a number of feedback mechanisms related to energy partitioning, most importantly the snow and ice-albedo feedback. However, direct measurements of surface energy budgets in the Arctic are scarce, especially for the cold and dark winter period and over transects going from the ice sheet and glaciers to the sea. This study aims to describe annual cycles of the surface energy budget from various surface types in Arctic Greenland; e.g. glacier, snow, wet and dry tundra and sea ice, based on data from a number of measurement locations across coastal Greenland related to the Greenland Ecosystem Monitoring (GEM) program, including Station Nord/Kronprins Christians Land, Zackenberg/Daneborg, Disko, Qaanaq, Nuuk/Kobbefjord and Upernaviarsuk. Based on the available time series, we will analyze the sensitivity of the energy balance partitioning to variations in meteorological conditions (temperature, cloudiness, precipitation). Such analysis would allow for a quantification of the spatial variation in the energy exchange in aforementioned Arctic environments. Furthermore, this study will identify uncertainties and knowledge gaps in Arctic energy budgets and related climate feedback effects.

Comparison of methods for quantifying surface sublimation over seasonally snow-covered terrain

USGS Publications Warehouse

Sexstone, Graham A.; Clow, David W.; Stannard, David I.; Fassnacht, Steven R.

2016-01-01

Snow sublimation can be an important component of the snow-cover mass balance, and there is considerable interest in quantifying the role of this process within the water and energy balance of snow-covered regions. In recent years, robust eddy covariance (EC) instrumentation has been used to quantify snow sublimation over snow-covered surfaces in complex mountainous terrain. However, EC can be challenging for monitoring turbulent fluxes in snow-covered environments because of intensive data, power, and fetch requirements, and alternative methods of estimating snow sublimation are often relied upon. To evaluate the relative merits of methods for quantifying surface sublimation, fluxes calculated by the EC, Bowen ratio–energy balance (BR), bulk aerodynamic flux (BF), and aerodynamic profile (AP) methods and their associated uncertainty were compared at two forested openings in the Colorado Rocky Mountains. Biases between methods are evaluated over a range of environmental conditions, and limitations of each method are discussed. Mean surface sublimation rates from both sites ranged from 0.33 to 0.36 mm day−1, 0.14 to 0.37 mm day−1, 0.10 to 0.17 mm day−1, and 0.03 to 0.10 mm day−1 for the EC, BR, BF and AP methods, respectively. The EC and/or BF methods are concluded to be superior for estimating surface sublimation in snow-covered forested openings. The surface sublimation rates quantified in this study are generally smaller in magnitude compared with previously published studies in this region and help to refine sublimation estimates for forested openings in the Colorado Rocky Mountains.

Multi-year analysis of distributed glacier mass balance modelling and equilibrium line altitude on King George Island, Antarctic Peninsula

NASA Astrophysics Data System (ADS)

Falk, Ulrike; López, Damián A.; Silva-Busso, Adrián

2018-04-01

The South Shetland Islands are located at the northern tip of the Antarctic Peninsula (AP). This region was subject to strong warming trends in the atmospheric surface layer. Surface air temperature increased about 3 K in 50 years, concurrent with retreating glacier fronts, an increase in melt areas, ice surface lowering and rapid break-up and disintegration of ice shelves. The positive trend in surface air temperature has currently come to a halt. Observed surface air temperature lapse rates show a high variability during winter months (standard deviations up to ±1.0 K (100 m)-1) and a distinct spatial heterogeneity reflecting the impact of synoptic weather patterns. The increased mesocyclonic activity during the wintertime over the past decades in the study area results in intensified advection of warm, moist air with high temperatures and rain and leads to melt conditions on the ice cap, fixating surface air temperatures to the melting point. Its impact on winter accumulation results in the observed negative mass balance estimates. Six years of continuous glaciological measurements on mass balance stake transects as well as 5 years of climatological data time series are presented and a spatially distributed glacier energy balance melt model adapted and run based on these multi-year data sets. The glaciological surface mass balance model is generally in good agreement with observations, except for atmospheric conditions promoting snow drift by high wind speeds, turbulence-driven snow deposition and snow layer erosion by rain. No drift in the difference between simulated mass balance and mass balance measurements can be seen over the course of the 5-year model run period. The winter accumulation does not suffice to compensate for the high variability in summer ablation. The results are analysed to assess changes in meltwater input to the coastal waters, specific glacier mass balance and the equilibrium line altitude (ELA). The Fourcade Glacier catchment drains into Potter cove, has an area of 23.6 km2 and is glacierized to 93.8 %. Annual discharge from Fourcade Glacier into Potter Cove is estimated to q ¯ = 25±6 hm3 yr-1 with the standard deviation of 8 % annotating the high interannual variability. The average ELA calculated from our own glaciological observations on Fourcade Glacier over the time period 2010 to 2015 amounts to 260±20 m. Published studies suggest rather stable conditions of slightly negative glacier mass balance until the mid-1980s with an ELA of approx. 150 m. The calculated accumulation area ratio suggests dramatic changes in the future extent of the inland ice cap for the South Shetland Islands.

Inventory of File sref_em.t03z.pgrb212.p1.f06.grib2

Science.gov Websites

surface WEASD 6 hour fcst Water Equivalent of Accumulated Snow Depth [kg/m^2] 016 surface APCP 0-6 hour surface WEASD 0-6 hour acc Water Equivalent of Accumulated Snow Depth [kg/m^2] 019 surface CSNOW 6 hour -6 hour acc Large-Scale Precipitation (non-convective) [kg/m^2] 415 surface SNOM 0-6 hour acc Snow

Influences and interactions of inundation, peat, and snow on active layer thickness: Modeling Archive

DOE Data Explorer

Scott Painter; Ethan Coon; Cathy Wilson; Dylan Harp; Adam Atchley

2016-04-21

This Modeling Archive is in support of an NGEE Arctic publication currently in review [4/2016]. The Advanced Terrestrial Simulator (ATS) was used to simulate thermal hydrological conditions across varied environmental conditions for an ensemble of 1D models of Arctic permafrost. The thickness of organic soil is varied from 2 to 40cm, snow depth is varied from approximately 0 to 1.2 meters, water table depth was varied from -51cm below the soil surface to 31 cm above the soil surface. A total of 15,960 ensemble members are included. Data produced includes the third and fourth simulation year: active layer thickness, time of deepest thaw depth, temperature of the unfrozen soil, and unfrozen liquid saturation, for each ensemble member. Input files used to run the ensemble are also included.

Using high resolution Lidar data from SnowEx to characterize the sensitivity of snow depth retrievals to point-cloud density and vegetation

NASA Astrophysics Data System (ADS)

Patterson, V. M.; Bormann, K.; Deems, J. S.; Painter, T. H.

2017-12-01

The NASA SnowEx campaign conducted in 2016 and 2017 provides a rich source of high-resolution Lidar data from JPL's Airborne Snow Observatory (ASO - http://aso.jpl.nasa.gov) combined with extensive in-situ measurements in two key areas in Colorado: Grand Mesa and Senator Beck. While the uncertainty in the 50m snow depth retrievals from NASA's ASO been estimated at 1-2cm in non-vegetated exposed areas (Painter et al., 2016), the impact of forest cover and point-cloud density on ASO snow lidar depth retrievals is relatively unknown. Dense forest canopies are known to reduce lidar penetration and ground strikes thus affecting the elevation surface retrieved from in the forest. Using high-resolution lidar point cloud data from the ASO SnowEx campaigns (26pt/m2) we applied a series of data decimations (up to 90% point reduction) to the point cloud data to quantify the relationship between vegetation, ground point density, resulting snow-off and snow-on surface elevations and finally snow depth. We observed non-linear reductions in lidar ground point density in forested areas that were strongly correlated to structural forest cover metrics. Previously, the impacts of these data decimations on a small study area in Grand Mesa showed a sharp increase in under-canopy surface elevation errors of -0.18m when ground point densities were reduced to 1.5pt/m2. In this study, we expanded the evaluation to the more topographically challenging Senator Beck basin, have conducted analysis along a vegetation gradient and are considering snow the impacts of snow depth rather than snow-off surface elevation. Preliminary analysis suggest that snow depth retrievals inferred from airborne lidar elevation differentials may systematically underestimate snow depth in forests where canopy density exceeds 1.75 and where tree heights exceed 5m. These results provide a basis from which to identify areas that may suffer from vegetation-induced biases in surface elevation models and snow depths derived from airborne lidar data, and help quantify expected spatial distributions of errors in the snow depth that can be used to improve the accuracy of ASO basin-scale depth and water equivalent products.

Trace gas and vegetation feedback responses of Alaskan tussock tundra to long-term snow depth manipulations

NASA Astrophysics Data System (ADS)

Ebbs, L. M.; Taneva, L.; Sullivan, P.; Welker, J. M.

2009-12-01

Changes in the precipitation and temperature regimes in Northern Alaska are manifesting themselves through shifts in sea ice, vegetation traits, animal migration timing and hydrologic dynamics. Changes in precipitation and soil temperature result in changes in plant mineral nutrition, soil nutrient availability, trace gas exchanges and differential nutrient acquisition strategies by arctic plants. In this study, we report on the extent to which long-term increases in snow depth, along with reductions in snow depth alter the magnitudes and pattern of CO2 exchange, soil properties and vegetation traits. A doubling of snow depth (from ~0.5 to ~1.0m) results in a delay of the growing season by ~ 2 weeks, however, by peak season, the rates of CO2 exchange are 50% higher in areas which had experienced deeper snow depth levels. To the contrary, long-term reductions in snow depth results in accelerated rates of plant phenology, however CO2 exchange rates at peak season are 30% less than those areas under ambient snow cover in the preceding winter. Reduced snow depth areas had the coldest winter soil temperatures while the deeper areas had the warmest winter soil temperatures, which may partially explain the summer CO2 fluxes indirectly via different rates of winter N mineralization and differences in leaf N properties. Our results indicate that shifting fall, winter and spring when snow is the primary form of precipitation, may have profound effects on tussock tundra systems.

Evaluation of snow cover and snow depth on the Qinghai-Tibetan Plateau derived from passive microwave remote sensing

NASA Astrophysics Data System (ADS)

Dai, Liyun; Che, Tao; Ding, Yongjian; Hao, Xiaohua

2017-08-01

Snow cover on the Qinghai-Tibetan Plateau (QTP) plays a significant role in the global climate system and is an important water resource for rivers in the high-elevation region of Asia. At present, passive microwave (PMW) remote sensing data are the only efficient way to monitor temporal and spatial variations in snow depth at large scale. However, existing snow depth products show the largest uncertainties across the QTP. In this study, MODIS fractional snow cover product, point, line and intense sampling data are synthesized to evaluate the accuracy of snow cover and snow depth derived from PMW remote sensing data and to analyze the possible causes of uncertainties. The results show that the accuracy of snow cover extents varies spatially and depends on the fraction of snow cover. Based on the assumption that grids with MODIS snow cover fraction > 10 % are regarded as snow cover, the overall accuracy in snow cover is 66.7 %, overestimation error is 56.1 %, underestimation error is 21.1 %, commission error is 27.6 % and omission error is 47.4 %. The commission and overestimation errors of snow cover primarily occur in the northwest and southeast areas with low ground temperature. Omission error primarily occurs in cold desert areas with shallow snow, and underestimation error mainly occurs in glacier and lake areas. With the increase of snow cover fraction, the overestimation error decreases and the omission error increases. A comparison between snow depths measured in field experiments, measured at meteorological stations and estimated across the QTP shows that agreement between observation and retrieval improves with an increasing number of observation points in a PMW grid. The misclassification and errors between observed and retrieved snow depth are associated with the relatively coarse resolution of PMW remote sensing, ground temperature, snow characteristics and topography. To accurately understand the variation in snow depth across the QTP, new algorithms should be developed to retrieve snow depth with higher spatial resolution and should consider the variation in brightness temperatures at different frequencies emitted from ground with changing ground features.

Rime and graupel: Description and characterization as revealed by low-temperature scanning electron microscopy

USGS Publications Warehouse

Rango, A.; Foster, J.; Josberger, E.G.; Erbe, E.F.; Pooley, C.; Wergin, W.P.

2003-01-01

Snow crystals, which form by vapor deposition, occasionally come in contact with supercooled cloud droplets during their formation and descent. When this occurs, the droplets adhere and freeze to the snow crystals in a process known as accretion. During the early stages of accretion, discrete snow crystals exhibiting frozen cloud droplets are referred to as rime. If this process continues, the snow crystal may become completely engulfed in frozen cloud droplets. The resulting particle is known as graupel. Light microscopic investigations have studied rime and graupel for nearly 100 years. However, the limiting resolution and depth of field associated with the light microscope have prevented detailed descriptions of the microscopic cloud droplets and the three-dimensional topography of the rime and graupel particles. This study uses low-temperature scanning electron microscopy to characterize the frozen precipitates that are commonly known as rime and graupel. Rime, consisting of frozen cloud droplets, is observed on all types of snow crystals including needles, columns, plates, and dendrites. The droplets, which vary in size from 10 to 100 μm, frequently accumulate along one face of a single snow crystal, but are found more randomly distributed on aggregations consisting of two or more snow crystals (snowflakes). The early stages of riming are characterized by the presence of frozen cloud droplets that appear as a layer of flattened hemispheres on the surface of the snow crystal. As this process continues, the cloud droplets appear more sinuous and elongate as they contact and freeze to the rimed crystals. The advanced stages of this process result in graupel, a particle 1 to 3 mm across, composed of hundreds of frozen cloud droplets interspersed with considerable air spaces; the original snow crystal is no longer discernible. This study increases our knowledge about the process and characteristics of riming and suggests that the initial appearance of the flattened hemispheres may result from impact of the leading face of the snow crystal with cloud droplets. The elongated and sinuous configurations of frozen cloud droplets that are encountered on the more advanced stages suggest that aerodynamic forces propel cloud droplets to the trailing face of the descending crystal where they make contact and freeze.

Atmospheric mercury depletion event study in Ny-Alesund (Svalbard) in spring 2005. Deposition and transformation of Hg in surface snow during springtime.

PubMed

Ferrari, Christophe P; Padova, Cyril; Faïn, Xavier; Gauchard, Pierre-Alexis; Dommergue, Aurélien; Aspmo, Katrine; Berg, Torunn; Cairns, Warren; Barbante, Carlo; Cescon, Paolo; Kaleschke, Lars; Richter, Andreas; Wittrock, Folkard; Boutron, Claude

2008-07-01

A field campaign was conducted in Ny-Alesund (78 degrees 54'N, 11 degrees 53'E), Svalbard (Norway) during April and May 2005. An Atmospheric Mercury (Hg) Depletion Event (AMDE) was observed from the morning of April 24 until the evening of April 27. Transport of already Hg and ozone (O3) depleted air masses could explain this observed depletion. Due to a snowfall event during the AMDE, surface snow Hg concentrations increased two fold. Hg deposition took place over a short period of time corresponding to 3-4 days. More than 80% of the deposited Hg was estimated to be reemitted back to the atmosphere in the days following the event. During the campaign, we observed night and day variations in surface snow Hg concentrations, which may be the result of gaseous elemental mercury (GEM) oxidation to divalent Hg at the snow/air interface by daylight surface snow chemistry. Finally, a decrease in the reactive Hg (HgR) fraction of total Hg (HgT) in the surface snow was observed during spring. We postulate that the transformation of HgR to a more stable form may occur in Arctic snow during spring.

Classification of surface types using SIR-C/X-SAR, Mount Everest Area, Tibet

USGS Publications Warehouse

Albright, Thomas P.; Painter, Thomas H.; Roberts, Dar A.; Shi, Jiancheng; Dozier, Jeff; Fielding, Eric

1998-01-01

Imaging radar is a promising tool for mapping snow and ice cover in alpine regions. It combines a high-resolution, day or night, all-weather imaging capability with sensitivity to hydrologic and climatic snow and ice parameters. We use the spaceborne imaging radar-C/X-band synthetic aperture radar (SIR-C/X-SAR) to map snow and glacial ice on the rugged north slope of Mount Everest. From interferometrically derived digital elevation data, we compute the terrain calibration factor and cosine of the local illumination angle. We then process and terrain-correct radar data sets acquired on April 16, 1994. In addition to the spectral data, we include surface slope to improve discrimination among several surface types. These data sets are then used in a decision tree to generate an image classification. This method is successful in identifying and mapping scree/talus, dry snow, dry snow-covered glacier, wet snow-covered glacier, and rock-covered glacier, as corroborated by comparison with existing surface cover maps and other ancillary information. Application of the classification scheme to data acquired on October 7 of the same year yields accurate results for most surface types but underreports the extent of dry snow cover.

Modes of supraglacial lake drainage and dynamic ice sheet response

NASA Astrophysics Data System (ADS)

Das, S. B.; Behn, M. D.; Joughin, I. R.

2011-12-01

We investigate modes of supraglacial lake drainage using geophysical, ground, and remote sensing observations over the western margin of the Greenland ice sheet. Lakes exhibit a characteristic life cycle defined by a pre-drainage, drainage, and post-drainage phase. In the pre-drainage phase winter snow fills pre-existing cracks and stream channels, efficiently blocking past drainage conduits. As temperatures increase in the spring, surface melting commences, initially saturating the snow pack and subsequently forming a surface network of streams that fills the lake basins. Basins continue to fill until lake drainage commences, which for individual lakes occurs at different times depending on the previous winter snow accumulation and summer temperatures. Three styles of drainage behavior have been observed: (1) no drainage, (2) slow drainage over the side into an adjacent pre-existing crack, and (3) rapid drainage through a new crack formed beneath the lake basin. Moreover, from year-to-year individual lakes exhibit different drainage behaviors. Lakes that drain slowly often utilize the same outflow channel for multiple years, creating dramatic canyons in the ice. Ultimately, these surface channels are advected out of the lake basin and a new channel forms. In the post-drainage phase, melt water continues to access the bed typically through a small conduit (e.g. moulin) formed near a local topographic minimum along the main drainage crack, draining the lake catchment throughout the remainder of the melt season. This melt water input to the bed leads to continued basal lubrication and enhanced ice flow compared to background velocities. Lakes that do not completely drain freeze over to form a surface ice layer that persists into the following year. Our results show that supraglacial lakes show a spectrum of drainage behaviors and that these styles of drainage lead to varying rates and timing of surface meltwater delivery to the bed resulting in different dynamic ice responses.

Detecting ice lenses and melt-refreeze crusts using satellite passive microwaves (Invited)

NASA Astrophysics Data System (ADS)

Montpetit, B.; Royer, A.; Roy, A.

2013-12-01

With recent winter climate warming in high latitude regions, rain-on-snow and melt-refreeze events are more frequent creating ice lenses or ice crusts at the surface or even within the snowpack through drainage. These ice layers create an impermeable ice barrier that reduces vegetation respiration and modifies snow properties due to the weak thermal diffusivity of ice. Winter mean soil temperatures increase due to latent heat being released during the freezing process. When ice layers freeze at the snow-soil interface, they can also affect the feeding habits of the northern wild life. Ice layers also significantly affect satellite passive microwave signals that are widely used to monitor the spatial and temporal evolution of snow. Here we present a method using satellite passive microwave brightness temperatures (Tb) to detect ice lenses and/or ice crusts within a snowpack. First the Microwave Emission Model for Layered Snowpacks (MEMLS) was validated to model Tb at 10.7, 19 and 37 GHz using in situ measurements taken in multiple sub-arctic environments where ice layers where observed. Through validated modeling, the effects of ice layer insertion were studied and an ice layer index was developed using the polarization ratio (PR) at all three frequencies. The developed ice index was then applied to satellite passive microwave signals for reported ice layer events.

Influence of snow temperature on avalanche impact pressure

NASA Astrophysics Data System (ADS)

Sovilla, Betty; Koehler, Anselm; Steinkogler, Walter; Fischer, Jan-Thomas

2015-04-01

The properties of the snow entrained by an avalanche during its motion (density, temperature) significantly affect flow dynamics and can determine whether the flowing material forms granules or maintains its original fine-grained structure. In general, a cold and light snow cover typically fluidizes, while warmer and more cohesive snow may form a granular denser layer in a flowing avalanche. This structural difference has a fundamental influence not only in the mobility of the flow but also on the impact pressure of avalanches. Using measurements of impact pressure, velocity, density and snow temperature performed at the Swiss Vallée de la Sionne full-scale test site, we show that, impact pressure fundamentally changes with snow temperature. A transition threshold of about -2°C is determined, the same temperature at which snow granulation starts. On the one hand warm avalanches, characterized by temperatures larger than -2°C, move as a plug and exert impact pressures linearly proportional to the avalanche depth. For Froude numbers larger than 1, an additional square-velocity dependent contribution cannot be neglected. On the other hand cold avalanches, characterized by a temperature smaller than -2°C, move as dense sheared flows, or completely dilute powder clouds and exert impact pressures, which are mainly proportional to the square of the flow velocity. For these avalanches the impact pressures strongly depend on density variations within the flow. We suggest that the proposed temperature threshold can be used as a criterion to define the transition between the impact pressures exerted by warm and cold avalanches, thus offering a new way to elude the notorious difficulties in defining the differences between wet and dry flow, respectively.

Global Precipitation Measurement, Validation, and Applications Integrated Hydrologic Validation to Improve Physical Precipitation Retrievals for GPM

NASA Technical Reports Server (NTRS)

Peters-Lidar, Christa D.; Tian, Yudong; Kenneth, Tian; Harrison, Kenneth; Kumar, Sujay

2011-01-01

Land surface modeling and data assimilation can provide dynamic land surface state variables necessary to support physical precipitation retrieval algorithms over land. It is well-known that surface emission, particularly over the range of frequencies to be included in the Global Precipitation Measurement Mission (GPM), is sensitive to land surface states, including soil properties, vegetation type and greenness, soil moisture, surface temperature, and snow cover, density, and grain size. In order to investigate the robustness of both the land surface model states and the microwave emissivity and forward radiative transfer models, we have undertaken a multi-site investigation as part of the NASA Precipitation Measurement Missions (PMM) Land Surface Characterization Working Group. Specifically, we will demonstrate the performance of the Land Information System (LIS; http://lis.gsfc.nasa.gov; Peters-Lidard et aI., 2007; Kumar et al., 2006) coupled to the Joint Center for Satellite Data Assimilation (JCSDA's) Community Radiative Transfer Model (CRTM; Weng, 2007; van Deist, 2009). The land surface is characterized by complex physical/chemical constituents and creates temporally and spatially heterogeneous surface properties in response to microwave radiation scattering. The uncertainties in surface microwave emission (both surface radiative temperature and emissivity) and very low polarization ratio are linked to difficulties in rainfall detection using low-frequency passive microwave sensors (e.g.,Kummerow et al. 2001). Therefore, addressing these issues is of utmost importance for the GPM mission. There are many approaches to parameterizing land surface emission and radiative transfer, some of which have been customized for snow (e.g., the Helsinki University of Technology or HUT radiative transfer model;) and soil moisture (e.g., the Land Surface Microwave Emission Model or LSMEM).

Dust, Elemental Carbon and Other Impurities on Central Asian Glaciers: Origin and Radiative Forcing

NASA Astrophysics Data System (ADS)

Schmale, J.; Flanner, M.; Kang, S.; Sprenger, M.; Zhang, Q.; Li, Y.; Guo, J.; Schwikowski, M.

2015-12-01

In Central Asia, more than 60 % of the population depends on water stored in glaciers and mountain snow. While temperature, precipitation and dynamic processes are key drivers of glacial change, deposition of light absorbing impurities such as mineral dust and black carbon can lead to accelerated melting through surface albedo reduction. Here, we discuss the origin of deposited mineral dust and black carbon and their impacts on albedo change and radiative forcing (RF). 218 snow samples were taken from 13 snow pits on 4 glaciers, Abramov (Pamir), Suek, Glacier No. 354 and Golubin (Tien Shan), representing deposition between summer 2012 and 2014. They were analyzed for elemental and organic carbon by a thermo-optical method, mineral dust by gravimetry, and iron by ICP-MS. Back trajectory ensembles were released every 6 hours with the Lagranto model for the covered period at all sites. Boundary layer "footprints" were calculated to estimate general source regions and combined with MODIS fire counts for potential fire contributions. Albedo reduction due to black carbon and mineral dust was calculated with the Snow-Ice-Aerosol-Radiative model (SNICAR), and surface spectral irradiances were derived from atmospheric radiative transfer calculations to determine the RF under clear-sky and all sky conditions using local radiation measurements. Dust contributions came from Central Asia, the Arabian Peninsula, the Sahara and partly the Taklimakan. Fire contributions were higher in 2014 and generally came from the West and North. We find that EC exerts roughly 3 times more RF than mineral dust in fresh and relatively fresh snow (~5 W/m2) and up to 6 times more in snow that experienced melting (> 10 W/m2) even though EC concentrations (average per snow pit from 90 to 700 ng/g) were up to two orders of magnitude lower than mineral dust (10 to 140 μg/g).

Snow grain size and shape distributions in northern Canada

NASA Astrophysics Data System (ADS)

Langlois, A.; Royer, A.; Montpetit, B.; Roy, A.

2016-12-01

Pioneer snow work in the 1970s and 1980s proposed new approaches to retrieve snow depth and water equivalent from space using passive microwave brightness temperatures. Numerous research work have led to the realization that microwave approaches depend strongly on snow grain morphology (size and shape), which was poorly parameterized since recently, leading to strong biases in the retrieval calculations. Related uncertainties from space retrievals and the development of complex thermodynamic multilayer snow and emission models motivated several research works on the development of new approaches to quantify snow grain metrics given the lack of field measurements arising from the sampling constraints of such variable. This presentation focuses on the unknown size distribution of snow grain sizes. Our group developed a new approach to the `traditional' measurements of snow grain metrics where micro-photographs of snow grains are taken under angular directional LED lighting. The projected shadows are digitized so that a 3D reconstruction of the snow grains is possible. This device has been used in several field campaigns and over the years a very large dataset was collected and is presented in this paper. A total of 588 snow photographs from 107 snowpits collected during the European Space Agency (ESA) Cold Regions Hydrology high-resolution Observatory (CoReH2O) mission concept field campaign, in Churchill, Manitoba Canada (January - April 2010). Each of the 588 photographs was classified as: depth hoar, rounded, facets and precipitation particles. A total of 162,516 snow grains were digitized across the 588 photographs, averaging 263 grains/photo. Results include distribution histograms for 5 `size' metrics (projected area, perimeter, equivalent optical diameter, minimum axis and maximum axis), and 2 `shape' metrics (eccentricity, major/minor axis ratio). Different cumulative histograms are found between the grain types, and proposed fits are presented with the Kernel distribution function. Finally, a comparison with the Specific Surface Area (SSA) derived from reflectance values using the Infrared Integrating Sphere (IRIS) highlight different power statistical fits for the 5 `size' metrics.

Multi Satellites Monitoring of Land Use/Cover Change and Its Driving Forces in Kashgar Region, China

NASA Astrophysics Data System (ADS)

Maimaitiaili, Ayisulitan; Aji, xiaokaiti; Kondoh, Akihiko

2016-04-01

Multi Satellites Monitoring of Land Use/Cover Change and Its Driving Forces in Kashgar Region, China Ayisulitan Maimaitiaili1, Xiaokaiti Aji2 Akihiko Kondoh2 1Graduate School of Science, Chiba University, Japan 2Center for Environmental Remote Sensing, Chiba University The spatio-temporal changes of Land Use/Cover (LUCC) and its driving forces in Kashgar region, Xinjiang Province, China, are investigated by using satellite remote sensing and a geographical information system (GIS). Main goal of this paper is to quantify the drivers of LUCC. First, considering lack of the Land Cover (LC) map in whole study area, we produced LC map by using Landsat images. Land use information from Landsat data was collected using maximum likelihood classification method. Land use change was studied based on the change detection method of land use types. Second, because the snow provides a key water resources for stream flow, agricultural production and drinking water for sustaining large population in Kashgar region, snow cover are estimated by Spot Vegetation data. Normalized Difference Snow Index (NDSI) algorithm are applied to make snow cover map, which is used to screen the LUCC and climate change. The best agreement is found with threshold value of NDSI≥0.2 to generate multi-temporal snow cover and snowmelt maps. Third, driving forces are systematically identified by LC maps and statistical data such as climate and socio-economic data, regarding to i) the climate changes and ii) socioeconomic development that the spatial correlation among LUCC, snow cover change, climate and socioeconomic changes are quantified by using liner regression model and negative / positive trend analysis. Our results showed that water bodies, bare land and grass land have decreasing notably. By contrast, crop land and urban area have continually increasing significantly, which are dominated in study area. The area of snow/ice have fluctuated and has strong seasonal trends, total annual snow cover has two peaks in 2005 and 2009. With increasing population from 2,324,375 in 1984 to 4,228,200 in 2014 and crop land reclamation from 6031.4 km2 in 1972 to 16549km2 in 2014 at the study area. Water resources consumption increased with support to large population and irrigate whole crop land area, caused the water shortages that the surface water bodies decreased from 2531.43km2 in the 1972s to 1067.05km2 in the 2014. The grass land with an acreage larger than 6749km2 in 1972 decreased to 922.6 km2 in 2014. The transformations between water bodies, garss land and bare land are remarkbale. The results also suggested high linearity between the LUCC and socioeconomic changes that specific land cover change be cause of the fact that socioeconomic development. In the recent 42 years, average annual temperature have been increasing significantly, although, precipitation have increased but partly weaken effect of the rising temperature, in addition snow cover more sensitive to precipitation than temperature. Results the change of climate showed a nagitive relationship between the NDSI with decrased of the snow cover and climate with increasing of the tempreature. Morover, the relationship between the LUCC and snow cover recorded higher linearity, because the temperature have increased, consequence influence on snow cover that provides melt water for study area which expanding crop land.

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).

Comparison of Local Scale Measured and Modeled Brightness Temperatures and Snow Parameters from the CLPX 2003 by Means of a Dense Medium Radiative Transfer Theory Model

NASA Technical Reports Server (NTRS)

Tedescol, Marco; Kim, Edward J.; Cline, Don; Graf, Tobias; Koike, Toshio; Armstrong, Richard; Brodzik, Mary J.; Hardy, Janet

2004-01-01

Microwave remote sensing offers distinct advantages for observing the cryosphere. Solar illumination is not required, and spatial and temporal coverage are excellent from polar-orbiting satellites. Passive microwave measurements are sensitive to the two most useful physical quantities for many hydrological applications: physical temperature and water content/state. Sensitivity to the latter is a direct result of the microwave sensitivity to the dielectric properties of natural media, including snow, ice, soil (frozen or thawed), and vegetation. These considerations are factors motivating the development of future cryospheric satellite remote sensing missions, continuing and improving on a 26-year microwave measurement legacy. Perhaps the biggest issues regarding the use of such satellite measurements involve how to relate parameter values at spatial scales as small as a hectare to observations with sensor footprints that may be up to 25 x 25 km. The NASA Cold-land Processes Field Experiment (CLPX) generated a dataset designed to enhance understanding of such scaling issues. CLPX observations were made in February (dry snow) and March (wet snow), 2003 in Colorado, USA, at scales ranging from plot scale to 25 x 25 km satellite footprints. Of interest here are passive microwave observations from ground-based, airborne, and satellite sensors, as well as meteorological and snowpack measurements that will enable studies of the effects of spatial heterogeneity of surface conditions on the observations. Prior to performing such scaling studies, an evaluation of snowpack forward modelling at the plot scale (least heterogeneous scale) is in order. This is the focus of this paper. Many forward models of snow signatures (brightness temperatures) have been developed over the years. It is now recognized that a dense medium radiative transfer (DMRT) treatment represents a high degree of physical fidelity for snow modeling, yet dense medium models are particularly sensitive to snowpack structural parameters such as grain size, density, and depth---parameters that may vary substantially within a snowpack. Microwave radiometric data and snow pit measurements collected at the Local-Scale Observation Site (LSOS) during the third Intensive Observation Period (IOP3) of the CLPX have been used to test the capabilities of a DMRT model using the Quasi Crystalline Approximation with Coherent Potential (QCA-CP). The radiometric measurements were made by the University of Tokyo s Ground Based Microwave Radiometer-7 (GBMR-7) system. We evaluate the degree to which a DMRT-based model can accurately reproduce the GBMR-7 brightness temperatures at different frequencies and incidence angles.

Quantifying the variability of snowpack properties and processes in a small-forested catchment representative of the boreal zone

NASA Astrophysics Data System (ADS)

Parajuli, A.; Nadeau, D.; Anctil, F.; Parent, A. C.; Bouchard, B.; Jutras, S.

2017-12-01

In snow-fed catchments, it is crucial to monitor and to model snow water equivalent (SWE), particularly to simulate the melt water runoff. However, the distribution of SWE can be highly heterogeneous, particularly within forested environments, mainly because of the large variability in snow depths. Although the boreal forest is the dominant land cover in Canada and in a few other northern countries, very few studies have quantified the spatiotemporal variability of snow depths and snowpack dynamics within this biome. The objective of this paper is to fill this research gap, through a detailed monitoring of snowpack dynamics at nine locations within a 3.57 km2 experimental forested catchment in southern Quebec, Canada (47°N, 71°W). The catchment receives 6 m of snow annually on average and is predominantly covered with balsam fir stand with some traces of spruce and white birch. In this study, we used a network of nine so-called `snow profiling stations', providing automated snow depth and snowpack temperature profile measurements, as well as three contrasting sites (juvenile, sapling and open areas) where sublimation rates were directly measured with flux towers. In addition, a total of 1401 manual snow samples supported by 20 snow pits measurements were collected throughout the winter of 2017. This paper presents some preliminary analyses of this unique dataset. Simple empirical relations relying SWE with easy-to-determine proxies, such as snow depths and snow temperature, are tested. Then, binary regression trees and multiple regression analysis are used to model SWE using topographic characteristics (slope, aspect, elevation), forest features (tree height, tree diameter, forest density and gap fraction) and meteorological forcing (solar radiation, wind speed, snow-pack temperature profile, air temperature, humidity). An analysis of sublimation rates comparing open area, saplings and juvenile forest is also presented in this paper.

Surface chemical properties of eutectic and frozen NaCl solutions probed by XPS and NEXAFS.

PubMed

Křepelová, Adéla; Huthwelker, Thomas; Bluhm, Hendrik; Ammann, Markus

2010-12-17

We study the surface of sodium chloride-water mixtures above, at, and below the eutectic temperature using X-ray photoelectron spectroscopy (XPS) and electron-yield near-edge X-ray absorption fine structure (NEXAFS) spectroscopy. The NaCl frozen solutions are mimicking sea-salt deposits in ice or snow. Sea-salt particles emitted from the oceans are a major contributor to the global aerosol burden and can act as a catalyst for heterogeneous chemistry or as cloud condensation nuclei. The nature of halogen ions at ice surfaces and their influence on surface melting of ice are of significant current interest. We found that the surface of the frozen solution, depending on the temperature, consists of ice and different NaCl phases, that is, NaCl, NaCl·2H(2)O, and surface-adsorbed water.

Snow mass and river flows modelled using GRACE total water storage observations

NASA Astrophysics Data System (ADS)

Wang, S.

2017-12-01

Snow mass and river flow measurements are difficult and less accurate in cold regions due to the hash environment. Floods in cold regions are commonly a result of snowmelt during the spring break-up. Flooding is projected to increase with climate change in many parts of the world. Forecasting floods from snowmelt remains a challenge due to scarce and quality issues in basin-scale snow observations and lack of knowledge for cold region hydrological processes. This study developed a model for estimating basin-level snow mass (snow water equivalent SWE) and river flows using the total water storage (TWS) observations from the Gravity Recovery and Climate Experiment (GRACE) satellite mission. The SWE estimation is based on mass balance approach which is independent of in situ snow gauge observations, thus largely eliminates the limitations and uncertainties with traditional in situ or remote sensing snow estimates. The model forecasts river flows by simulating surface runoff from snowmelt and the corresponding baseflow from groundwater discharge. Snowmelt is predicted using a temperature index model. Baseflow is predicted using a modified linear reservoir model. The model also quantifies the hysteresis between the snowmelt and the streamflow rates, or the lump time for water travel in the basin. The model was applied to the Red River Basin, the Mackenzie River Basin, and the Hudson Bay Lowland Basins in Canada. The predicted river flows were compared with the observed values at downstream hydrometric stations. The results were also compared to that for the Lower Fraser River obtained in a separate study to help better understand the roles of environmental factors in determining flood and their variations with different hydroclimatic conditions. This study advances the applications of space-based time-variable gravity measurements in cold region snow mass estimation, river flow and flood forecasting. It demonstrates a relatively simple method that only needs GRACE TWS and temperature data for river flow or flood forecasting. The model can be particularly useful for regions with spare observation networks, and can be used in combination with other available methods to help improve the accuracy in river flow and flood forecasting over cold regions.

Inversion of AMSR-E observations for land surface temperature estimation: 2. Global comparison with infrared satellite temperature

NASA Astrophysics Data System (ADS)

Ermida, S. L.; Jiménez, C.; Prigent, C.; Trigo, I. F.; DaCamara, C. C.

2017-03-01

A comparison of land surface temperature (Ts) derived from the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) with infrared Ts is presented. The infrared Ts include clear-sky estimates from the Moderate Resolution Imaging Spectroradiometer (MODIS), the Spinning Enhanced Visible and Infrared Imager, the Geostationary Operational Environmental Satellite (GOES) Imager, and the Japanese Meteorological Imager. The higher discrepancies between AMSR-E and MODIS are observed over deserts and snow-covered areas. The former seems to be associated with Ts underestimation by MODIS, whereas the latter is mostly related to uncertainties in microwave emissivity over snow/ice. Ts differences between AMSR-E and MODIS are significantly reduced after masking out snow and deserts, with a bias change from 2.6/4.6 K to 3.0/1.4 K for daytime/nighttime and a standard deviation (STD) decrease from 7.3/7.9 K to 5.1/3.9 K. When comparing with all infrared sensors, the STD of the differences between microwave and infrared Ts is generally higher than between IR retrievals. However, the biases between microwave and infrared Ts are, in some cases, of the same order as the ones observed between infrared products. This is the case for GOES, with daytime biases with respect to AMSR-E and MODIS of 0.45 K and 0.60 K, respectively. While the infrared Ts are clear-sky estimates, AMSR-E also provides Ts under cloudy conditions. For frequently cloudy regions, this results in a large increase of available Ts estimates (>250%), making the microwave Ts a very powerful complement of the infrared estimates.

Projecting 21st century snowpack trends in western USA mountains using variable-resolution CESM

NASA Astrophysics Data System (ADS)

Rhoades, Alan M.; Ullrich, Paul A.; Zarzycki, Colin M.

2018-01-01

Climate change will impact western USA water supplies by shifting precipitation from snow to rain and driving snowmelt earlier in the season. However, changes at the regional-to-mountain scale is still a major topic of interest. This study addresses the impacts of climate change on mountain snowpack by assessing historical and projected variable-resolution (VR) climate simulations in the community earth system model (VR-CESM) forced by prescribed sea-surface temperatures along with widely used regional downscaling techniques, the coupled model intercomparison projects phase 5 bias corrected and statistically downscaled (CMIP5-BCSD) and the North American regional climate change assessment program (NARCCAP). The multi-model RCP8.5 scenario analysis of winter season SWE for western USA mountains indicates by 2040-2065 mean SWE could decrease -19% (NARCCAP) to -38% (VR-CESM), with an ensemble median change of -27%. Contrary to CMIP5-BCSD and NARCCAP, VR-CESM highlights a more pessimistic outcome for western USA mountain snowpack in latter-parts of the 21st century. This is related to temperature changes altering the snow-albedo feedback, snowpack storage, and precipitation phase, but may indicate that VR-CESM resolves more physically consistent elevational effects lacking in statistically downscaled datasets and teleconnections that are not captured in limited area models. Overall, VR-CESM projects by 2075-2100 that average western USA mountain snowfall decreases by -30%, snow cover by -44%, SWE by -69%, and average surface temperature increase of +5.0°C. This places pressure on western USA states to preemptively invest in climate adaptation measures such as alternative water storage, water use efficiency, and reassess reservoir storage operations.

High-resolution ensemble projections of near-term regional climate over the continental United States

DOE PAGES

Ashfaq, Moetasim; Rastogi, Deeksha; Mei, Rui; ...

2016-09-01

We present high-resolution near-term ensemble projections of hydro-climatic changes over the contiguous U.S. using a regional climate model (RegCM4) that dynamically downscales 11 Global Climate Models from the 5th phase of Coupled Model Inter-comparison Project at 18km horizontal grid spacing. All model integrations span 41 years in the historical period (1965 – 2005) and 41 years in the near-term future period (2010 – 2050) under Representative Concentration Pathway 8.5 and cover a domain that includes the contiguous U.S. and parts of Canada and Mexico. Should emissions continue to rise, surface temperatures in every region within the U.S. will reach amore » new climate norm well before mid 21st century regardless of the magnitudes of regional warming. Significant warming will likely intensify the regional hydrological cycle through the acceleration of the historical trends in cold, warm and wet extremes. The future temperature response will be partly regulated by changes in snow hydrology over the regions that historically receive a major portion of cold season precipitation in the form of snow. Our results indicate the existence of the Clausius-Clapeyron scaling at regional scales where per degree centigrade rise in surface temperature will lead to a 7.4% increase in precipitation from extremes. More importantly, both winter (snow) and summer (liquid) extremes are projected to increase across the U.S. These changes in precipitation characteristics will be driven by a shift towards shorter and wetter seasons. Altogether, projected changes in the regional hydro-climate can have substantial impacts on the natural and human systems across the U.S.« less

Observed Trends in West Coast Atmospheric River Temperatures

NASA Astrophysics Data System (ADS)

Gonzales, K. R.; Swain, D. L.; Barnes, E. A.; Diffenbaugh, N. S.

2017-12-01

Understanding the changing characteristics of atmospheric rivers (ARs) in a warming climate is critical in light of their importance in generating precipitation and creating the potential for flood and geophysical hazards. Numerous changes to the characteristics of ARs under the influence of a changing climate have been documented or hypothesized; one simple hypothesis is that AR precipitation will occur at increasingly warm temperatures, potentially altering the critical rain/snow balance in snowpack-dependent watersheds and causing precipitation at higher elevations to fall as rain rather than snow. Not only would warmer, primarily rain-producing ARs greatly affect snow accumulation, but they might also increase the intensity of runoff, the potential for flooding, and the occurrence of rain-on-snow events. Since the West Coast of North America relies heavily on ARs as a source of precipitation and snowpack accumulation, these regions may be profoundly affected by changes in AR temperatures and associated impacts. Using a catalog of ARs encompassing 1979-2014 and ERA-Interim reanalysis, we assess whether detectable trends exist in cool season AR temperatures over the Pacific Coast states of California, Oregon, and Washington. We define AR temperature by the mean temperature of the air mass between 1000 hPa and 750 hPa, and compare AR temperature trends to background temperature trends over the same period. We find overall AR warming over this period and particularly robust warming in March ARs coincident with an apparent poleward shift in March AR frequency. Further analysis suggests that warmer ARs have higher rates of warming than cooler ARs. AR temperature trends generally scale with background temperature trends, although some regions exhibit a near one-to-one relationship while others are largely uncorrelated. The observed warming of ARs making landfall on the West Coast may have potentially significant implications for rain vs. snow at higher elevations, the rain/snow balance, and rain-on-snow flood hazards (particularly in March).

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.

A Supplementary Clear-Sky Snow and Ice Recognition Technique for CERES Level 2 Products

NASA Technical Reports Server (NTRS)

Radkevich, Alexander; Khlopenkov, Konstantin; Rutan, David; Kato, Seiji

2013-01-01

Identification of clear-sky snow and ice is an important step in the production of cryosphere radiation budget products, which are used in the derivation of long-term data series for climate research. In this paper, a new method of clear-sky snow/ice identification for Moderate Resolution Imaging Spectroradiometer (MODIS) is presented. The algorithm's goal is to enhance the identification of snow and ice within the Clouds and the Earth's Radiant Energy System (CERES) data after application of the standard CERES scene identification scheme. The input of the algorithm uses spectral radiances from five MODIS bands and surface skin temperature available in the CERES Single Scanner Footprint (SSF) product. The algorithm produces a cryosphere rating from an aggregated test: a higher rating corresponds to a more certain identification of the clear-sky snow/ice-covered scene. Empirical analysis of regions of interest representing distinctive targets such as snow, ice, ice and water clouds, open waters, and snow-free land selected from a number of MODIS images shows that the cryosphere rating of snow/ice targets falls into 95% confidence intervals lying above the same confidence intervals of all other targets. This enables recognition of clear-sky cryosphere by using a single threshold applied to the rating, which makes this technique different from traditional branching techniques based on multiple thresholds. Limited tests show that the established threshold clearly separates the cryosphere rating values computed for the cryosphere from those computed for noncryosphere scenes, whereas individual tests applied consequently cannot reliably identify the cryosphere for complex scenes.

Sampling in the Snow: High School Winter Field Experiences Provide Relevant, Real World Connections Between Scientific Practices and Disciplinary Core Ideas

NASA Astrophysics Data System (ADS)

Hanson, E. W.; Burakowski, E. A.

2014-12-01

For much of the northern United States, the months surrounding the winter solstice are times of increased darkness, low temperatures, and frozen landscapes. It's a time when many high school science educators, who otherwise would venture outside with their classes, hunker down and are wary of the outdoors. However, a plethora of learning opportunities lies just beyond the classroom. Working collaboratively, a high school science teacher and a snow scientist have developed multiple activities to engage students in the scientific process of collecting, analyzing and interpreting the winter world using snow data to (1) learn about the insulative properties of snow, and (2) to learn about the role of snow cover on winter climate through its reflective properties while participating in a volunteer network that collects snow depth, albedo (reflectivity), and density data. These outdoor field-based snow investigations incorporate Next Generation Science Standards (NGSS) and disciplinary core ideas, including ESS2.C: The roles of water in Earth's surface processes and ESS2.D: Weather and Climate. Additionally, the lesson plans presented address Common Core State Standards (CCSS) in Mathematics, including the creation and analysis of bar graphs and time series plots (CCSS.Math.HSS-ID.A.1) and xy scatter plots (CCSS.Math.HSS-ID.B.6). High school students participating in the 2013/2014 snow sampling season described their outdoor learning experience as "authentic" and "hands-on" as compared to traditional class indoors. They emphasized that learning outdoors was essential to their understanding of underlying content and concepts because they "learn through actual experience."

Will changes in root-zone temperature in boreal spring affect recovery of photosynthesis in Picea mariana and Populus tremuloides in a future climate?

PubMed

Fréchette, Emmanuelle; Ensminger, Ingo; Bergeron, Yves; Gessler, Arthur; Berninger, Frank

2011-11-01

Future climate will alter the soil cover of mosses and snow depths in the boreal forests of eastern Canada. In field manipulation experiments, we assessed the effects of varying moss and snow depths on the physiology of black spruce (Picea -mariana (Mill.) B.S.P.) and trembling aspen (Populus tremuloides Michx.) in the boreal black spruce forest of western Québec. For 1 year, naturally regenerated 10-year-old spruce and aspen were grown with one of the following treatments: additional N fertilization, addition of sphagnum moss cover, removal of mosses, delayed soil thawing through snow and hay addition, or accelerated soil thawing through springtime snow removal. Treatments that involved the addition of insulating moss or snow in the spring caused lower soil temperature, while removing moss and snow in the spring caused elevated soil temperature and thus had a warming effect. Soil warming treatments were associated with greater temperature variability. Additional soil cover, whether moss or snow, increased the rate of photosynthetic recovery in the spring. Moss and snow removal, on the other hand, had the opposite effect and lowered photosynthetic activity, especially in spruce. Maximal electron transport rate (ETR(max)) was, for spruce, 39.5% lower after moss removal than with moss addition, and 16.3% lower with accelerated thawing than with delayed thawing. Impaired photosynthetic recovery in the absence of insulating moss or snow covers was associated with lower foliar N concentrations. Both species were affected in that way, but trembling aspen generally reacted less strongly to all treatments. Our results indicate that a clear negative response of black spruce to changes in root-zone temperature should be anticipated in a future climate. Reduced moss cover and snow depth could adversely affect the photosynthetic capacities of black spruce, while having only minor effects on trembling aspen.

The Effect of Climate Change on Snow Pack at Sleepers River, Vermont, USA

NASA Astrophysics Data System (ADS)

Shanley, J. B.; Chalmers, A.; Denner, J.; Clark, S.

2017-12-01

Sleepers River Research Watershed, a U.S. Geological Survey Water, Energy, and Biogeochemical Budgets (WEBB) site in northeastern Vermont, has a 58-year record (since 1959) of snow depth and snow water equivalence (SWE), one of the longest continuous records in eastern North America. Snow measurements occur weekly during the winter at the watershed using an Adirondack type snow tube sampler. Sleepers River averages about 1100 mm of precipitation annually of which 20 to 30 percent falls as snow. Snow cover typically persists from December to April. Length of snow cover and snow depth vary with elevation, aspect, and cover type. Sites include open field, and hardwood and conifer stand clearings from 225 to 630 meters elevation. We evaluated changes in snow depth, snow cover duration, and SWE relative to elevation, soil frost depth, air temperature, total precipitation, and the El Niño - Southern Oscillation (ENSO) cycle. Overall, warmer winter temperatures have resulted in more midwinter thaws, more rain during the winter, and more variable soil frost depth. Trends in snowpack amount and duration were compared to winter-spring streamflow center-of-mass to evaluate if shifts in the snow pack regime were leading to earlier snowmelt.

Paleotemperatures derived from the EPICA Dome-C core based on isotopic diffusion in the firn pack.

NASA Astrophysics Data System (ADS)

Gkinis, V.; Johnsen, S. J.; Vinther, B.; Sheldon, S.; Ritz, C.; Masson-Delmotte, V.

2009-04-01

Water isotope ratios as measured from ice core samples have been used as a proxy for past temperatures. Based i.a. on a Rayleigh fractionation process they record the cloud temperature during snow formation. However, changes in the temperature and humidity of the vapor source can also affect the isotopic signal of the polar precipitation, thus inducing isotopic artifacts. Furthermore, for the case of the Antarctic ice cap, temperature inversions frequently occur during snow formation. As a result, the cloud temperature as recorded by the water isotopes can differ significantly from the temperature at the surface. After the deposition of snow and until pore close off, a diffusive process occurs in the pore space of the firn pack, mixing water vapor from different layers and smoothing the isotopic profiles. The smoothing depends only on the resulting diffusion length. This process is temperature dependent and it presents a slightly different rate between the two isotopic species of water, H218O and HD16O. This is because the fractionation factors as defined for these two isotopic species have a different dependence on temperature. In this study we present a temperature reconstruction based on the different diffusion rates of H218O and HD16O water molecules in firn. The advantage of such an approach is that the temperatures estimated represent the actual conditions in the firn stack. As a result, we can surpass the artifacts that can possibly disrupt the use of the classical technique. We will present temperature estimations as extracted from two high resolution (2.5 cm) data sets, from the EPICA Dome C deep core focused on the Holoene Climatic Optimum and the Last Glacial Maximum and compare them with results obtained with the classical slope method as well as constrains imposed by the measured temperature profile. We will also address the problems of spectral power estimation for determining the diffusion lengths.

A Comparison of Snow Depth on Sea Ice Retrievals Using Airborne Altimeters and an AMSR-E Simulator

NASA Technical Reports Server (NTRS)

Cavalieri, D. J.; Marksu, T.; Ivanoff, A.; Miller, J. A.; Brucker, L.; Sturm, M.; Maslanik, J. A.; Heinrichs, J. F.; Gasiewski, A.; Leuschen, C.;

The Spectral and Chemical Measurement of Pollutants on Snow Near South Pole, Antarctica

NASA Technical Reports Server (NTRS)

Casey, K. A.; Kaspari, S. D.; Skiles, S. M.; Kreutz, K.; Handley, M. J.

2017-01-01

Remote sensing of light-absorbing particles (LAPs), or dark colored impurities, such as black carbon (BC) and dust on snow, is a key remaining challenge in cryospheric surface characterization and application to snow, ice, and climate models. We present a quantitative data set of in situ snow reflectance, measured and modeled albedo, and BC and trace element concentrations from clean to heavily fossil fuel emission contaminated snow near South Pole, Antarctica. Over 380 snow reflectance spectra (350-2500 nm) and 28 surface snow samples were collected at seven distinct sites in the austral summer season of 2014-2015. Snow samples were analyzed for BC concentration via a single particle soot photometer and for trace element concentration via an inductively coupled plasma mass spectrometer. Snow impurity concentrations ranged from 0.14 to 7000 part per billion (ppb) BC, 9.5 to 1200 ppb sulfur, 0.19 to 660 ppb iron, 0.013 to 1.9 ppb chromium, 0.13 to 120 ppb copper, 0.63 to 6.3 ppb zinc, 0.45 to 82 parts per trillion (ppt) arsenic, 0.0028 to 6.1 ppb cadmium, 0.062 to 22 ppb barium, and 0.0044 to 6.2 ppb lead. Broadband visible to shortwave infrared albedo ranged from 0.85 in pristine snow to 0.62 in contaminated snow. LAP radiative forcing, the enhanced surface absorption due to BC and trace elements, spanned from less than 1 W m(exp. -2) for clean snow to approximately 70 W m(exp. -2) for snow with high BC and trace element content. Measured snow reflectance differed from modeled snow albedo due to specific impurity-dependent absorption features, which we recommend be further studied and improved in snow albedo models.

The spectral and chemical measurement of pollutants on snow near South Pole, Antarctica

NASA Astrophysics Data System (ADS)

Casey, K. A.; Kaspari, S. D.; Skiles, S. M.; Kreutz, K.; Handley, M. J.

2017-06-01

Remote sensing of light-absorbing particles (LAPs), or dark colored impurities, such as black carbon (BC) and dust on snow, is a key remaining challenge in cryospheric surface characterization and application to snow, ice, and climate models. We present a quantitative data set of in situ snow reflectance, measured and modeled albedo, and BC and trace element concentrations from clean to heavily fossil fuel emission contaminated snow near South Pole, Antarctica. Over 380 snow reflectance spectra (350-2500 nm) and 28 surface snow samples were collected at seven distinct sites in the austral summer season of 2014-2015. Snow samples were analyzed for BC concentration via a single particle soot photometer and for trace element concentration via an inductively coupled plasma mass spectrometer. Snow impurity concentrations ranged from 0.14 to 7000 part per billion (ppb) BC, 9.5 to 1200 ppb sulfur, 0.19 to 660 ppb iron, 0.013 to 1.9 ppb chromium, 0.13 to 120 ppb copper, 0.63 to 6.3 ppb zinc, 0.45 to 82 parts per trillion (ppt) arsenic, 0.0028 to 6.1 ppb cadmium, 0.062 to 22 ppb barium, and 0.0044 to 6.2 ppb lead. Broadband visible to shortwave infrared albedo ranged from 0.85 in pristine snow to 0.62 in contaminated snow. LAP radiative forcing, the enhanced surface absorption due to BC and trace elements, spanned from <1 W m-2 for clean snow to 70 W m-2 for snow with high BC and trace element content. Measured snow reflectance differed from modeled snow albedo due to specific impurity-dependent absorption features, which we recommend be further studied and improved in snow albedo models.

Spatial scales of light transmission through Antarctic pack ice: Surface flooding vs. floe-size distribution

NASA Astrophysics Data System (ADS)

Arndt, S.; Meiners, K.; Krumpen, T.; Ricker, R.; Nicolaus, M.

2016-12-01

Snow on sea ice plays a crucial role for interactions between the ocean and atmosphere within the climate system of polar regions. Antarctic sea ice is covered with snow during most of the year. The snow contributes substantially to the sea-ice mass budget as the heavy snow loads can depress the ice below water level causing flooding. Refreezing of the snow and seawater mixture results in snow-ice formation on the ice surface. The snow cover determines also the amount of light being reflected, absorbed, and transmitted into the upper ocean, determining the surface energy budget of ice-covered oceans. The amount of light penetrating through sea ice into the upper ocean is of critical importance for the timing and amount of bottom sea-ice melt, biogeochemical processes and under-ice ecosystems. Here, we present results of several recent observations in the Weddell Sea measuring solar radiation under Antarctic sea ice with instrumented Remotely Operated Vehicles (ROV). The combination of under-ice optical measurements with simultaneous characterization of surface properties, such as sea-ice thickness and snow depth, allows the identification of key processes controlling the spatial distribution of the under-ice light. Thus, our results show how the distinction between flooded and non-flooded sea-ice regimes dominates the spatial scales of under-ice light variability for areas smaller than 100-by-100m. In contrast, the variability on larger scales seems to be controlled by the floe-size distribution and the associated lateral incidence of light. These results are related to recent studies on the spatial variability of Arctic under-ice light fields focusing on the distinctly differing dominant surface properties between the northern (e.g. summer melt ponds) and southern (e.g. year-round snow cover, surface flooding) hemisphere sea-ice cover.

Sustainability of winter tourism in a changing climate over Kashmir Himalaya.

PubMed

Dar, Reyaz Ahmad; Rashid, Irfan; Romshoo, Shakil Ahmad; Marazi, Asif

2014-04-01

Mountain areas are sensitive to climate change. Implications of climate change can be seen in less snow, receding glaciers, increasing temperatures, and decreasing precipitation. Climate change is also a severe threat to snow-related winter sports such as skiing, snowboarding, and cross-country skiing. The change in climate will put further pressure on the sensitive environment of high mountains. Therefore, in this study, an attempt has been made to know the impact of climate change on the snow precipitation, water resources, and winter tourism in the two famous tourist resorts of the Kashmir Valley. Our findings show that winters are getting prolonged with little snow falls on account of climate change. The average minimum and maximum temperatures are showing statistically significant increasing trends for winter months. The precipitation is showing decreasing trends in both the regions. A considerable area in these regions remains under the snow and glacier cover throughout the year especially during the winter and spring seasons. However, time series analysis of LandSat MODIS images using Normalized Difference Snow Index shows a decreasing trend in snow cover in both the regions from past few years. Similarly, the stream discharge, comprising predominantly of snow- and glacier-melt, is showing a statistically significant declining trend despite the melting of these glaciers. The predicted futuristic trends of temperature from Predicting Regional Climates for Impact Studies regional climate model are showing an increase which may enhance snow-melting in the near future posing a serious threat to the sustainability of winter tourism in the region. Hence, it becomes essential to monitor the changes in temperature and snow cover depletion in these basins in order to evaluate their effect on the winter tourism and water resources in the region.

Dirty Snow, Atmospheric Warming, and Climate Feedbacks from Boreal Black Carbon Emissions

NASA Astrophysics Data System (ADS)

Flanner, M. G.; Zender, C. S.; Randerson, J. T.; Jin, Y.

2005-12-01

Black carbon (BC) emitted from boreal fires darkens snow and sea-ice surfaces, increases solar absorption in the atmosphere, and decreases the incident flux at the surface. Although global surface forcing of darkened snow/ice is small relative to atmospheric forcing, the former directly triggers ice-albedo feedback, whereas the latter directly alters the atmospheric lapse rate. This highlights the importance of examining climate feedback strength as well as instantaneous forcings. We used a coupled land-atmosphere GCM (NCAR CAM3) to compare the relative forcings and climate feedbacks of BC emitted from a suite of boreal forest fires over the last decade, accounting for both enhanced snow/ice and atmospheric absorption by BC. The net change in absorbed energy at the surface was about three times greater than the instantaneous surface forcing when BC interactively heated the snow. Timing and location of fires determined the magnitude of darkened snow/ice feedback potential. We also assessed climate feedback strength from BC emitted globally during extreme high and low fire years, including the 1998 fire season.

Investigating the Effects of Environmental Solutes on the Reaction Environment in Ice and at Ice Surfaces

NASA Astrophysics Data System (ADS)

Malley, Philip Patrick Anthony

The reaction environments present in water, ice, and at ice surfaces are physically distinct from one another and studies have shown that photolytic reactions can take place at different rates in the different media. Kinetics of reactions in frozen media are measured in snow and ice prepared from deionized water. This reduces experimental artifacts, but is not relevant to snow in the environment, which contains solutes. We have monitored the effect of nonchromophoric (will not absorb sunlight) organic matter on the photolytic fate of the polycyclic aromatic hydrocarbons (PAHs) phenanthrene, pyrene, and anthracene in ice and at ice surfaces. Nonchromophoric organic matter reduced photolysis rates to below our detection limit in bulk ice, and reduced rates at ice surfaces to a lesser extent due to the PAHs partially partitioning to the organics present. In addition, we have monitored the effect of chromophoric (will absorb sunlight) dissolved organic matter (cDOM) on the fate of anthracene in water, ice, and ice surfaces. cDOM reduced rates in all three media. Suppression in liquid water was due to physical interactions between anthracene and the cDOM, rather than to competitive photon absorbance. More suppression was observed in ice cubes and ice granules than in liquid water due to a freeze concentrating effect. Sodium Chloride (NaCl) is another ubiquitous environmental solute that can influence reaction kinetics in water, ice, and at ice surfaces. Using Raman microscopy, we have mapped the surface of ice of frozen NaCl solutions at 0.02M and 0.6M, as well as the surface of frozen samples of Sargasso Sea Water. At temperatures above and below the eutectic temperature (-21.1°C). Above the eutectic, regions of ice and liquid water were observed in all samples. Liquid regions generally took the form of channels. Channel widths and fractional liquid surface coverage increased with NaCl concentration and temperature. Volume maps of the three samples at temperatures above the eutectic point, showed that liquid channels were distributed throughout the ice sample. Liquid fractions were similar at ice surfaces and in the bulk at depths of at least 80 microm.

Sensitivity of snow process simulations to precipitation-phase transition method in forested and open areas

NASA Astrophysics Data System (ADS)

Lundberg, A.; Gustafsson, D.

2009-04-01

Modeling of forest snow processes is complicated and especially problematic seems to be the separation of precipitation phase in climates where a large part of the precipitation falls at temperatures near zero degrees Celsius. When the precipitation is classified as snow, the tree crowns can carry an order of magnitude more canopy storage as compared to when the precipitation is classified as rain, and snow in the trees also alters the albedo of the forest while rain does not. Many different schemes for the precipitation phase separation are used by various snow models. Some models use just one air temperature threshold (TR/S) below which all precipitation is assumed to be snow and above which all precipitation is classified as rain. A more common approach for forest snow models is to use two temperature thresholds. The snow fraction (SF) is then set to one below the snow threshold (TS) and to zero above the rain threshold (TR) and SF is assumed to decrease linearly between these two thresholds. Also more sophisticated schemes exist, but three seems to be a lack of agreement on how the precipitation phase separations should be performed. The aim with this study is to use a hydrological model including canopy snow processes to illustrate the sensitivity for different formulations of the precipitation phase separation on a) the simulated maximum snow pack storage b) the interception evaporation loss and c) snow melt runoff. In other words, to investigate of the choice of precipitation phase separation has an impact on the simulated wintertime water balance. Simulations are made for sites in different climates and for both open fields and forest sites in different regions of Sweden from north to south. In general, precipitation phase separation methods that classified snowfall at higher temperatures resulted in a larger proportion of the precipitation lost by interception evaporation as a result of the increased interception capacity. However, the maximum snow accumulation was also increased in some cases due to the overall increased snowfall, depending on canopy density and precipitation and temperature regimes. Results show that the choice of precipitation phase separation method can have an significant impact on the simulated wintertime water balance, especially in forested regions.

Monitoring snow cover variability (2000-2014) in the Hengduan Mountains based on cloud-removed MODIS products with an adaptive spatio-temporal weighted method

NASA Astrophysics Data System (ADS)

Li, Xinghua; Fu, Wenxuan; Shen, Huanfeng; Huang, Chunlin; Zhang, Liangpei

2017-08-01

Monitoring the variability of snow cover is necessary and meaningful because snow cover is closely connected with climate and ecological change. In this work, 500 m resolution MODIS daily snow cover products from 2000 to 2014 were adopted to analyze the status in Hengduan Mountains. In order to solve the spatial discontinuity caused by clouds in the products, we propose an adaptive spatio-temporal weighted method (ASTWM), which is based on the initial result of a Terra and Aqua combination. This novel method simultaneously considers the temporal and spatial correlations of the snow cover. The simulated experiments indicate that ASTWM removes clouds completely, with a robust overall accuracy (OA) of above 93% under different cloud fractions. The spatio-temporal variability of snow cover in the Hengduan Mountains was investigated with two indices: snow cover days (SCD) and snow fraction. The results reveal that the annual SCD gradually increases and the coefficient of variation (CV) decreases with elevation. The pixel-wise trends of SCD first rise and then drop in most areas. Moreover, intense intra-annual variability of the snow fraction occurs from October to March, during which time there is abundant snow cover. The inter-annual variability, which mainly occurs in high elevation areas, shows an increasing trend before 2004/2005 and a decreasing trend after 2004/2005. In addition, the snow fraction responds to the two climate factors of air temperature and precipitation. For the intra-annual variability, when the air temperature and precipitation decrease, the snow cover increases. Besides, precipitation plays a more important role in the inter-annual variability of snow cover than temperature.

Accuracy assessment of a net radiation and temperature index snowmelt model using ground observations of snow water equivalent in an alpine basin

NASA Astrophysics Data System (ADS)

Molotch, N. P.; Painter, T. H.; Bales, R. C.; Dozier, J.

2003-04-01

In this study, an accumulated net radiation / accumulated degree-day index snowmelt model was coupled with remotely sensed snow covered area (SCA) data to simulate snow cover depletion and reconstruct maximum snow water equivalent (SWE) in the 19.1-km2 Tokopah Basin of the Sierra Nevada, California. Simple net radiation snowmelt models are attractive for operational snowmelt runoff forecasts as they are computationally inexpensive and have low input requirements relative to physically based energy balance models. The objective of this research was to assess the accuracy of a simple net radiation snowmelt model in a topographically heterogeneous alpine environment. Previous applications of net radiation / temperature index snowmelt models have not been evaluated in alpine terrain with intensive field observations of SWE. Solar radiation data from two meteorological stations were distributed using the topographic radiation model TOPORAD. Relative humidity and temperature data were distributed based on the lapse rate calculated between three meteorological stations within the basin. Fractional SCA data from the Landsat Enhanced Thematic Mapper (5 acquisitions) and the Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) (2 acquisitions) were used to derive daily SCA using a linear regression between acquisition dates. Grain size data from AVIRIS (4 acquisitions) were used to infer snow surface albedo and interpolated linearly with time to derive daily albedo values. Modeled daily snowmelt rates for each 30-m pixel were scaled by the SCA and integrated over the snowmelt season to obtain estimates of maximum SWE accumulation. Snow surveys consisting of an average of 335 depth measurements and 53 density measurements during April, May and June, 1997 were interpolated using a regression tree / co-krig model, with independent variables of average incoming solar radiation, elevation, slope and maximum upwind slope. The basin was clustered into 7 elevation / average-solar-radiation zones for SWE accuracy assessment. Model simulations did a poor job at estimating the spatial distribution of SWE. Basin clusters where the solar radiative flux dominated the melt flux were simulated more accurately than those dominated by the turbulent fluxes or the longwave radiative flux.