Modeled Seasonal Variations of Firn Density Induced by Steady State Surface Air Temperature Cycle

NASA Technical Reports Server (NTRS)

Jun, Li; Zwally, H. Jay; Koblinsky, Chester J. (Technical Monitor)

2001-01-01

Seasonal variations of firn density in ice-sheet firn layers have been attributed to variations in deposition processes or other processes within the upper firn. A recent high-resolution (mm scale) density profile, measured along a 181 m core from Antarctica, showed small-scale density variations with a clear seasonal cycle that apparently was not-related to seasonal variations in deposition or known near-surface processes (Gerland and others 1999). A recent model of surface elevation changes (Zwally and Li, submitted) produced a seasonal variation in firn densification, and explained the seasonal surface elevation changes observed by satellite radar altimeters. In this study, we apply our 1-D time-dependent numerical model of firn densification that includes a temperature-dependent formulation of firn densification based on laboratory measurements of grain growth. The model is driven by a steady-state seasonal surface temperature and a constant accumulation rate appropriate for the measured Antarctic ice core. The modeled seasonal variations in firn density show that the layers of snow deposited during spring to mid-summer with the highest temperature history compress to the highest density, and the layers deposited during later summer to autumn with the lowest temperature history compress to the lowest density. The initial amplitude of the seasonal difference of about 0.13 reduces to about 0.09 in five years and asymptotically to 0.92 at depth, which is consistent with the core measurements.

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.

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

NASA Astrophysics Data System (ADS)

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

2007-12-01

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

Evaluating Multispectral Snowpack Reflectivity With Changing Snow Correlation Lengths

NASA Technical Reports Server (NTRS)

Kang, Do Hyuk; Barros, Ana P.; Kim, Edward J.

2016-01-01

This study investigates the sensitivity of multispectral reflectivity to changing snow correlation lengths. Matzler's ice-lamellae radiative transfer model was implemented and tested to evaluate the reflectivity of snow correlation lengths at multiple frequencies from the ultraviolet (UV) to the microwave bands. The model reveals that, in the UV to infrared (IR) frequency range, the reflectivity and correlation length are inversely related, whereas reflectivity increases with snow correlation length in the microwave frequency range. The model further shows that the reflectivity behavior can be mainly attributed to scattering rather than absorption for shallow snowpacks. The largest scattering coefficients and reflectivity occur at very small correlation lengths (approximately 10(exp -5 m) for frequencies higher than the IR band. In the microwave range, the largest scattering coefficients are found at millimeter wavelengths. For validation purposes, the ice-lamella model is coupled with a multilayer snow physics model to characterize the reflectivity response of realistic snow hydrological processes. The evolution of the coupled model simulated reflectivities in both the visible and the microwave bands is consistent with satellite-based reflectivity observations in the same frequencies. The model results are also compared with colocated in situ snow correlation length measurements (Cold Land Processes Field Experiment 2002-2003). The analysis and evaluation of model results indicate that the coupled multifrequency radiative transfer and snow hydrology modeling system can be used as a forward operator in a data-assimilation framework to predict the status of snow physical properties, including snow correlation length.

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.

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.

Improvement of a snow albedo parameterization in the Snow-Atmosphere-Soil Transfer model: evaluation of impacts of aerosol on seasonal snow cover

NASA Astrophysics Data System (ADS)

Zhong, Efang; Li, Qian; Sun, Shufen; Chen, Wen; Chen, Shangfeng; Nath, Debashis

2017-11-01

The presence of light-absorbing aerosols (LAA) in snow profoundly influence the surface energy balance and water budget. However, most snow-process schemes in land-surface and climate models currently do not take this into consideration. To better represent the snow process and to evaluate the impacts of LAA on snow, this study presents an improved snow albedo parameterization in the Snow-Atmosphere-Soil Transfer (SAST) model, which includes the impacts of LAA on snow. Specifically, the Snow, Ice and Aerosol Radiation (SNICAR) model is incorporated into the SAST model with an LAA mass stratigraphy scheme. The new coupled model is validated against in-situ measurements at the Swamp Angel Study Plot (SASP), Colorado, USA. Results show that the snow albedo and snow depth are better reproduced than those in the original SAST, particularly during the period of snow ablation. Furthermore, the impacts of LAA on snow are estimated in the coupled model through case comparisons of the snowpack, with or without LAA. The LAA particles directly absorb extra solar radiation, which accelerates the growth rate of the snow grain size. Meanwhile, these larger snow particles favor more radiative absorption. The average total radiative forcing of the LAA at the SASP is 47.5 W m-2. This extra radiative absorption enhances the snowmelt rate. As a result, the peak runoff time and "snow all gone" day have shifted 18 and 19.5 days earlier, respectively, which could further impose substantial impacts on the hydrologic cycle and atmospheric processes.

Predicting snowpack stratigraphy in forested environments

NASA Astrophysics Data System (ADS)

Andreadis, K. M.; Lettenmaier, D. P.

2009-04-01

The interaction of forest canopies with snow accumulation and ablation processes is critical to the hydrology of many mid- and high-latitude areas. The layered character of snowpacks increases the complexity of representing these processes and deconvolving the return signal from remote sensors. However, it offers the opportunity to infer the metamorphic signature of the snowpack and to extract additional information by combining multiple frequencies (visible and passive/active microwave). Implementation of this approach requires knowledge of the stratigraphy of snowpack microphysical properties (temperature, density, and grain size), which as a practical matter can only be produced by predictive models. A mass and energy balance model for snow accumulation and ablation processes in forested environments was developed utilizing extensive measurements of snow interception and release in a maritime mountainous site in Oregon. A multiple layer component was added to the model that also takes into account snowpack stratigraphy resulting from snow densification, vapor transport and grain growth. The model, was evaluated using two years of weighing lysimeter data and was able to reproduce the SWE evolution throughout both winters beneath the canopy as well as the nearby clearing. The model was also evaluated using measurements from a BOReal Ecosystem-Atmosphere Study (BOREAS) field site in Canada to test the robustness of the canopy snow interception algorithm in a much different climate. Simulated SWE was relatively close to the observations for the forested sites, with discrepancies evident in some cases. Although the model formulation appeared robust for both types of climates, sensitivity to parameters such as snow roughness length, maximum interception capacity and number of layers suggested the magnitude of improvements of SWE simulations that might be achieved by calibration. Finally, the model's ability to replicate large-scale snowpack layer features and their effect on passive microwave emissivity was evaluated using observations from the Cold Land Processes Experiment (CLPX).

Numerical analysis of the heating phase and densification mechanism in polymers selective laser melting process

NASA Astrophysics Data System (ADS)

Mokrane, Aoulaiche; Boutaous, M'hamed; Xin, Shihe

2018-05-01

The aim of this work is to address a modeling of the SLS process at the scale of the part in PA12 polymer powder bed. The powder bed is considered as a continuous medium with homogenized properties, meanwhile understanding multiple physical phenomena occurring during the process and studying the influence of process parameters on the quality of final product. A thermal model, based on enthalpy approach, will be presented with details on the multiphysical couplings that allow the thermal history: laser absorption, melting, coalescence, densification, volume shrinkage and on numerical implementation using FV method. The simulations were carried out in 3D with an in-house developed FORTRAN code. After validation of the model with comparison to results from literature, a parametric analysis will be proposed. Some original results as densification process and the thermal history with the evolution of the material, from the granular solid state to homogeneous melted state will be discussed with regards to the involved physical phenomena.

Constraints on post-depositional isotope modifications in East Antarctic firn from analysing temporal changes of isotope profiles

NASA Astrophysics Data System (ADS)

Münch, Thomas; Kipfstuhl, Sepp; Freitag, Johannes; Meyer, Hanno; Laepple, Thomas

2017-09-01

The isotopic composition of water in ice sheets is extensively used to infer past climate changes. In low-accumulation regions their interpretation is, however, challenged by poorly constrained effects that may influence the initial isotope signal during and after deposition of the snow. This is reflected in snow-pit isotope data from Kohnen Station, Antarctica, which exhibit a seasonal cycle but also strong interannual variations that contradict local temperature observations. These inconsistencies persist even after averaging many profiles and are thus not explained by local stratigraphic noise. Previous studies have suggested that post-depositional processes may significantly influence the isotopic composition of East Antarctic firn. Here, we investigate the importance of post-depositional processes within the open-porous firn (≳ 10 cm depth) at Kohnen Station by separating spatial from temporal variability. To this end, we analyse 22 isotope profiles obtained from two snow trenches and examine the temporal isotope modifications by comparing the new data with published trench data extracted 2 years earlier. The initial isotope profiles undergo changes over time due to downward advection, firn diffusion and densification in magnitudes consistent with independent estimates. Beyond that, we find further modifications of the original isotope record to be unlikely or small in magnitude (≪ 1 ‰ RMSD). These results show that the discrepancy between local temperatures and isotopes most likely originates from spatially coherent processes prior to or during deposition, such as precipitation intermittency or systematic isotope modifications acting on drifting or loose surface snow.

Numerical Modeling of Coupled Water Flow and Heat Transport in Soil and Snow

NASA Astrophysics Data System (ADS)

Kelleners, T.

2015-12-01

A numerical model is developed to calculate coupled water flow and heat transport in seasonally frozen soil and snow. Both liquid water flow and water vapor flow are included. The effect of dissolved ions on soil water freezing point depression is included by combining an expression for osmotic head with the Clapeyron equation and the van Genuchten soil water retention function. The coupled water flow and heat transport equations are solved using the Thomas algorithm and Picard iteration. Ice pressure is always assumed zero and frost heave is neglected. The new model is tested using data from a high-elevation rangeland soil that is subject to significant soil freezing and a mountainous forest soil that is snow-covered for about 8 months of the year. Soil hydraulic parameters are mostly based on measurements and only vegetation parameters are fine-tuned to match measured and calculated soil water content, soil & snow temperature, and snow height. Modeling statistics for both systems show good performance for temperature, intermediate performance for snow height, and relatively low performance for soil water content, in accordance with earlier results with an older version of the model.

Glacial-interglacial dynamics of Antarctic firn columns: comparison between simulations and ice core air-δ15N measurements

NASA Astrophysics Data System (ADS)

Capron, E.; Landais, A.; Buiron, D.; Cauquoin, A.; Chappellaz, J.; Debret, M.; Jouzel, J.; Leuenberger, M.; Martinerie, P.; Masson-Delmotte, V.; Mulvaney, R.; Parrenin, F.; Prié, F.

2012-12-01

Correct estimate of the firn lock-in depth is essential for correctly linking gas and ice chronologies in ice cores studies. Here, two approaches to constrain the firn depth evolution in Antarctica are presented over the last deglaciation: output of a firn densification model and measurements of δ15N of N2 in air trapped in ice core. Since the firn densification process is largely governed by surface temperature and accumulation rate, we have investigated four ice cores drilled in coastal (Berkner Island, BI, and James Ross Island, JRI) and semi coastal (TALDICE and EPICA Dronning Maud Land, EDML) Antarctic regions. Combined with available δ15N measurements performed from the EPICA Dome C (EDC) site, the studied regions encompass a large range of surface accumulation rate and temperature conditions. While firn densification simulations are able to correctly represent most of the δ15N trends over the last deglaciation measured in the EDC, BI, TALDICE and EDML ice cores, they systematically fail to capture BI and EDML δ15N glacial levels, a mismatch previously seen for Central East Antarctic ice cores. Using empirical constraints of the EDML gas-ice depth offset during the Laschamp event (~ 41 ka), we can rule out the existence of a large convective zone as the explanation of the glacial firn model-δ15N data mismatch for this site. The good match between modelled and measured δ15N at TALDICE as well as the lack of any clear correlation between insoluble dust concentration in snow and δ15N records in the different ice cores suggest that past changes in loads of impurities are not the only main driver of glacial-interglacial changes in firn lock-in depth. We conclude that firn densification dynamics may instead be driven mostly by accumulation rate changes. The mismatch between modelled and measured δ15N may be due to inaccurate reconstruction of past accumulation rate or underestimated influence of accumulation rate in firnification models.

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

Recent research in snow hydrology

NASA Technical Reports Server (NTRS)

Dozier, Jeff

1987-01-01

Recent work on snow-pack energy exchange has involved detailed investigations on snow albedo and attempts to integrate energy-balance calculations over drainage basins. Along with a better understanding of the EM properties of snow, research in remote sensing has become more focused toward estimation of snow-pack properties. In snow metamorphism, analyses of the physical processes must now be coupled to better descriptions of the geometry of the snow microstructure. The dilution method now appears to be the best direct technique for measuring the liquid water content of snow; work on EM methods continues. Increasing attention to the chemistry of the snow pack has come with the general focus on acid precipitation in hydrology.

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

NASA Technical Reports Server (NTRS)

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

2000-01-01

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

An Integrated Uncertainty Analysis and Ensemble-based Data Assimilation Framework for Operational Snow Predictions

NASA Astrophysics Data System (ADS)

He, M.; Hogue, T. S.; Franz, K.; Margulis, S. A.; Vrugt, J. A.

2009-12-01

The National Weather Service (NWS), the agency responsible for short- and long-term streamflow predictions across the nation, primarily applies the SNOW17 model for operational forecasting of snow accumulation and melt. The SNOW17-forecasted snowmelt serves as an input to a rainfall-runoff model for streamflow forecasts in snow-dominated areas. The accuracy of streamflow predictions in these areas largely relies on the accuracy of snowmelt. However, no direct snowmelt measurements are available to validate the SNOW17 predictions. Instead, indirect measurements such as snow water equivalent (SWE) measurements or discharge are typically used to calibrate SNOW17 parameters. In addition, the forecast practice is inherently deterministic, lacking tools to systematically address forecasting uncertainties (e.g., uncertainties in parameters, forcing, SWE and discharge observations, etc.). The current research presents an Integrated Uncertainty analysis and Ensemble-based data Assimilation (IUEA) framework to improve predictions of snowmelt and discharge while simultaneously providing meaningful estimates of the associated uncertainty. The IUEA approach uses the recently developed DiffeRential Evolution Adaptive Metropolis (DREAM) to simultaneously estimate uncertainties in model parameters, forcing, and observations. The robustness and usefulness of the IUEA-SNOW17 framework is evaluated for snow-dominated watersheds in the northern Sierra Mountains, using the coupled IUEA-SNOW17 and an operational soil moisture accounting model (SAC-SMA). Preliminary results are promising and indicate successful performance of the coupled IUEA-SNOW17 framework. Implementation of the SNOW17 with the IUEA is straightforward and requires no major modification to the SNOW17 model structure. The IUEA-SNOW17 framework is intended to be modular and transferable and should assist the NWS in advancing the current forecasting system and reinforcing current operational forecasting skill.

Efficient coupling of high intensity short laser pulses into snow clusters

NASA Astrophysics Data System (ADS)

Palchan, T.; Pecker, S.; Henis, Z.; Eisenmann, S.; Zigler, A.

2007-01-01

Measurements of energy absorption of high intensity laser pulses in snow clusters are reported. Targets consisting of sapphire coated with snow nanoparticles were found to absorb more than 95% of the incident light compared to 50% absorption in flat sapphire targets.

Polar Environmental Monitoring

NASA Technical Reports Server (NTRS)

Nagler, R. G.; Schulteis, A. C.

1979-01-01

The present and projected benefits of the polar regions were reviewed and then translated into information needs in order to support the array of polar activities anticipated. These needs included measurement sensitivities for polar environmental data (ice/snow, atmosphere, and ocean data for integrated support) and the processing and delivery requirements which determine the effectiveness of environmental services. An assessment was made of how well electromagnetic signals can be converted into polar environmental information. The array of sensor developments in process or proposed were also evaluated as to the spectral diversity, aperture sizes, and swathing capabilities available to provide these measurements from spacecraft, aircraft, or in situ platforms. Global coverage and local coverage densification options were studied in terms of alternative spacecraft trajectories and aircraft flight paths.

Aeolian snow transport from wind tunnel experiments

NASA Astrophysics Data System (ADS)

Paterna, E.; Crivelli, P.; Lehning, M.

2016-12-01

Aeolian snow transport has a significant impact on snow redistribution in mountains, prairies as well as on glaciers, ice shelves, and sea ice. In all these environments, the local mass balance is highly influenced by Aeolian snow transport. The dynamics of snow saltation has a high impact on the land surface processes shaping these regions. More specifically, the observed high intermittency of saltation fluxes poses a problem for saltation models and needs to be better understood. We therefore aimed at unveiling the mechanisms underlying snow saltation at different saltation strengths and its coupling with the turbulent fluctuations of the wind. We conducted wind tunnel measurements of the momentum and mass-fluxes during snow saltation. For the mass-flux measurements we employed a shadowgraphy system which acquires images of the snow particle's shadows at high spatial and temporal resolution. The size and displacement of the particles are then determined by means of image analysis and Particle Tracking Velocimetry (PTV), allowing to estimate both snow mass-flux and flow velocity. Our controlled wind tunnel experiments revealed the existence of two regimes of saltation. In a turbulence-dependent regime occurring during weak saltation activity, we observed a strong coupling between snow transport and turbulent flow. Conversely during stronger saltation activity a turbulence-independent regime emerges, where the saltation develops its own length scale and it efficiently decouples from the wind fluctuations. We argue that different entrainment mechanisms could explain the existence of the two different saltation regimes as well as the observed high level of mass-flux intermittency.

Simulation of snow and soil water content as a basis for satellite retrievals

USDA-ARS?s Scientific Manuscript database

It is not yet possible to determine whether the snow has changed over time despite collection of passive microwave data for more than thirty years. Physically-based, but computationally simple snow and soil models have been coupled to form the basis of a data assimilation system for retrievals of sn...

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.

Numerical modeling of coupled water flow and heat transport in soil and snow

Treesearch

Thijs J. Kelleners; Jeremy Koonce; Rose Shillito; Jelle Dijkema; Markus Berli; Michael H. Young; John M. Frank; William Massman

2016-01-01

A one-dimensional vertical numerical model for coupled water flow and heat transport in soil and snow was modified to include all three phases of water: vapor, liquid, and ice. The top boundary condition in the model is driven by incoming precipitation and the surface energy balance. The model was applied to three different terrestrial systems: A warm desert bare...

How autumn Eurasian snow anomalies affect east asian winter monsoon: a numerical study

NASA Astrophysics Data System (ADS)

Luo, Xiao; Wang, Bin

2018-03-01

Previous studies have found that snow Eurasian anomalies in autumn can affect East Asian winter monsoon (EAWM), but the mechanisms remain controversial and not well understood. The possible mechanisms by which Eurasian autumn snow anomalies affect EAWM are investigated by numerical experiments with a coupled general circulation model and its atmospheric general circulation model component. The leading empirical orthogonal function mode of the October-November mean Eurasian snow cover is characterized by a uniform anomaly over a broad region of central Eurasia (40°N-65°N, 60°E-140°E). However, the results from a 150-ensemble mean simulation with snow depth anomaly specified in October and November reveal that the Mongolian Plateau and Vicinity (MPV, 40°-55°N, 80°-120°E) is the key region for autumn snow anomalies to affect EAWM. The excessive snow forcing can significantly enhance EAWM and the snowfall over the northwestern China and along the EAWM front zone stretching from the southeast China to Japan. The physical process involves a snow-monsoon feedback mechanism. The excessive autumn snow anomalies over the MPV region can persist into the following winter, and significantly enhance winter snow anomalies, which increase surface albedo, reduce incoming solar radiation and cool the boundary layer air, leading to an enhanced Mongolian High and a deepened East Asian trough. The latter, in turn, strengthen surface northwesterly winds, cooling East Asia and increasing snow accumulation over the MPV region and the southeastern China. The increased snow covers feedback to EAWM system through changing albedo, extending its influence southeastward. It is also found that the atmosphere-ocean coupling process can amplify the delayed influence of Eurasian snow mass anomaly on EAWM. The autumn surface albedo anomalies, however, do not have a lasting "memory" effect. Only if the albedo anomalies are artificially extended into December and January, will the EAWM be affected in a similar way as the impacts of autumn snow mass anomalies.

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.

Recent accumulation rates of an alpine glacier derived from firn cores and repeated helicopter-borne GPR

NASA Astrophysics Data System (ADS)

Sold, L.; Huss, M.; Eichler, A.; Schwikowski, M.; Hoelzle, M.

2014-08-01

The spatial representation of accumulation measurements is a major limitation for current glacier mass balance monitoring approaches. Here, we present a new method for estimating annual accumulation rates on a temperate alpine glacier based on the interpretation of internal reflection horizons (IRH) in helicopter-borne ground-penetrating radar (GPR) data. For each individual GPR measurement, the signal traveltime is combined with a simple model for firn densification and refreezing of meltwater. The model is calibrated at locations where GPR profiles intersect in two subsequent years and the densification can be tracked over time. Two 10.5 m long firn cores provide a reference for the density and chronology of firn layers. Thereby, IRH correspond to density maxima, but not exclusively to former summer glacier surfaces. From GPR profiles across the accumulation area, we obtain spatial distributions of water equivalent for at least four annual firn layers, reaching a mean density of 0.74 g cm-3. Refreezing accounts for 9% of the density increase over time and depth. The strongest limitation to our method is the dependence on layer chronology assumptions. The uncertainties inherent to the modelling approach itself are in the same order of conventional point measurements in snow pits. We show that GPR can be used to complement existing mass balance monitoring programs on temperate alpine glaciers, but also to retrospectively extend newly initiated time series.

Glacial-interglacial dynamics of Antarctic firn columns: comparison between simulations and ice core air-?15N measurements

NASA Astrophysics Data System (ADS)

Capron, E.; Landais, A.; Buiron, D.; Cauquoin, A.; Chappellaz, J. A.; Debret, M.; Jouzel, J.; Leuenberger, M.; Martinerie, P.; Masson-Delmotte, V.; Mulvaney, R.; Parrenin, F.; Prié, F.

2013-12-01

Correct estimation of the firn lock-in depth is essential for correctly linking gas and ice chronologies in ice core studies. Here, two approaches to constrain the firn depth evolution in Antarctica are presented over the last deglaciation: outputs of a firn densification model, and measurements of δ15N of N2 in air trapped in ice core, assuming that δ15N is only affected by gravitational fractionation in the firn column. Since the firn densification process is largely governed by surface temperature and accumulation rate, we have investigated four ice cores drilled in coastal (Berkner Island, BI, and James Ross Island, JRI) and semi-coastal (TALDICE and EPICA Dronning Maud Land, EDML) Antarctic regions. Combined with available ice core air- δ15N measurements from the EPICA Dome C (EDC) site, the studied regions encompass a large range of surface accumulation rates and temperature conditions. Our δ15N profiles reveal a heterogeneous response of the firn structure to glacial-interglacial climatic changes. While firn densification simulations correctly predict TALDICE δ15N variations, they systematically fail to capture the large millennial-scale δ15N variations measured at BI and the δ15N glacial levels measured at JRI and EDML - a mismatch previously reported for central East Antarctic ice cores. New constraints of the EDML gas-ice depth offset during the Laschamp event (41 ka) and the last deglaciation do not favour the hypothesis of a large convective zone within the firn as the explanation of the glacial firn model- δ15N data mismatch for this site. While we could not conduct an in-depth study of the influence of impurities in snow for firnification from the existing datasets, our detailed comparison between the δ15N profiles and firn model simulations under different temperature and accumulation rate scenarios suggests that the role of accumulation rate may have been underestimated in the current description of firnification models.

Glacial-interglacial dynamics of Antarctic firn columns: comparison between simulations and ice core air-δ15N measurements

NASA Astrophysics Data System (ADS)

Capron, E.; Landais, A.; Buiron, D.; Cauquoin, A.; Chappellaz, J.; Debret, M.; Jouzel, J.; Leuenberger, M.; Martinerie, P.; Masson-Delmotte, V.; Mulvaney, R.; Parrenin, F.; Prié, F.

2013-05-01

Correct estimation of the firn lock-in depth is essential for correctly linking gas and ice chronologies in ice core studies. Here, two approaches to constrain the firn depth evolution in Antarctica are presented over the last deglaciation: outputs of a firn densification model, and measurements of δ15N of N2 in air trapped in ice core, assuming that δ15N is only affected by gravitational fractionation in the firn column. Since the firn densification process is largely governed by surface temperature and accumulation rate, we have investigated four ice cores drilled in coastal (Berkner Island, BI, and James Ross Island, JRI) and semi-coastal (TALDICE and EPICA Dronning Maud Land, EDML) Antarctic regions. Combined with available ice core air-δ15N measurements from the EPICA Dome C (EDC) site, the studied regions encompass a large range of surface accumulation rates and temperature conditions. Our δ15N profiles reveal a heterogeneous response of the firn structure to glacial-interglacial climatic changes. While firn densification simulations correctly predict TALDICE δ15N variations, they systematically fail to capture the large millennial-scale δ15N variations measured at BI and the δ15N glacial levels measured at JRI and EDML - a mismatch previously reported for central East Antarctic ice cores. New constraints of the EDML gas-ice depth offset during the Laschamp event (~41 ka) and the last deglaciation do not favour the hypothesis of a large convective zone within the firn as the explanation of the glacial firn model-δ15N data mismatch for this site. While we could not conduct an in-depth study of the influence of impurities in snow for firnification from the existing datasets, our detailed comparison between the δ15N profiles and firn model simulations under different temperature and accumulation rate scenarios suggests that the role of accumulation rate may have been underestimated in the current description of firnification models.

Albedo of bare ice near the Trans-Antarctic Mountains to represent sea-glaciers on the tropical ocean of Snowball Earth

NASA Astrophysics Data System (ADS)

Warren, S. G.; Dadic, R.; Mullen, P.; Schneebeli, M.; Brandt, R. E.

2012-12-01

The albedos of snow and ice surfaces are, because of their positive feedback, crucial to the initiation, maintenance, and termination of a snowball event, as well as for determining the ice thickness on the ocean. Despite the name, Snowball Earth would not have been entirely snow-covered. As on modern Earth, evaporation would exceed precipitation over much of the tropical ocean. After a transient period with sea ice, the dominant ice type would probably be sea-glaciers flowing in from higher latitude. As they flowed equatorward into the tropical region of net sublimation, their surface snow and subsurface firn would sublimate away, exposing bare glacier ice to the atmosphere and to solar radiation. This ice would be freshwater (meteoric) ice, which originated from snow and firn, so it would contain numerous air bubbles, which determine the albedo. The modern surrogate for this type of ice (glacier ice exposed by sublimation, which has never experienced melting), are the bare-ice surfaces of the Antarctic Ice Sheet near the Trans-Antarctic Mountains. These areas have been well mapped because of their importance in the search for meteorites. A transect across an icefield can sample ice of different ages that has traveled to different depths en route to the sublimation front. On a 6-km transect from snow to ice near the Allan Hills, spectral albedo was measured and 1-m core samples were collected. This short transect is meant to represent a north-south transect across many degrees of latitude on the snowball ocean. Surfaces on the transect transitioned through the sequence: new snow - old snow - firn - young white ice - old blue ice. The transect from snow to ice showed a systematic progression of decreasing albedo at all wavelengths, as well as decreasing specific surface area (SSA; ratio of air-ice interface area to ice mass) and increasing density. The measured spectral albedos are integrated over wavelength and weighted by the spectral solar flux to obtain broadband albedos. These range from 0.8 for snow to 0.55-0.6 for blue ice, which is in the range that favors thick ice over the tropical ocean of Snowball Earth. Air bubbles in the ice, as well as cracks, are responsible for the reflection of sunlight; their contributions to SSA were determined by micro-computed tomography. Scattering by bubbles dominates; removing cracks from the radiative-transfer calculation causes only a slight reduction of albedo. Although what determines the albedo is the SSA of bubbles or snow grains, the broadband albedo also shows a systematic relation to the snow or ice density, suggesting that density might serve as a surrogate variable that will be easier to predict than SSA in an ice-sheet model, using a parameterization for firn densification.

Everywhere and nowhere: snow and its linkages

NASA Astrophysics Data System (ADS)

Hiemstra, C. A.

2017-12-01

Interest has grown in quantifying higher latitude precipitation change and snow-related ecosystem and economic impacts. There is a high demand for creating and using snow-related datasets, yet available datasets contain limitations, aren't scale appropriate, or lack thorough validation. Much of the uncertainty in snow estimates relates to ongoing snow measurement problems that are chronic and pervasive in windy, Arctic environments. This, coupled with diminishing support for long-term snow field observations, creates formidable hydrologic gaps in snow dominated landscapes. Snow touches most aspects of high latitude landscapes and spans albedo, ecosystems, soils, permafrost, and sea ice. In turn, snow can be impacted by disturbances, landscape change, ecosystem, structure, and later arrival of sea or lake ice. Snow, and its changes touch infrastructure, housing, and transportation. Advances in snow measurements, modeling, and data assimilation are under way, but more attention and a concerted effort is needed in a time of dwindling resources to make required advances during a time of rapid change.

Decoupling of mass flux and turbulent wind fluctuations in drifting snow

NASA Astrophysics Data System (ADS)

Paterna, E.; Crivelli, P.; Lehning, M.

2016-05-01

The wind-driven redistribution of snow has a significant impact on the climate and mass balance of polar and mountainous regions. Locally, it shapes the snow surface, producing dunes and sastrugi. Sediment transport has been mainly represented as a function of the wind strength, and the two processes assumed to be stationary and in equilibrium. The wind flow in the atmospheric boundary layer is unsteady and turbulent, and drifting snow may never reach equilibrium. Our question is therefore: what role do turbulent eddies play in initiating and maintaining drifting snow? To investigate the interaction between drifting snow and turbulence experimentally, we conducted several wind tunnel measurements of drifting snow over naturally deposited snow covers. We observed a coupling between snow transport and turbulent flow only in a weak saltation regime. In stronger regimes it self-organizes developing its own length scales and efficiently decoupling from the wind forcing.

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

PubMed

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

2017-02-01

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

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.

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

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.

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.

Albedo of bare ice near the Trans-Antarctic Mountains as an analogue of sea-glaciers on the tropical ocean of Snowball Earth

NASA Astrophysics Data System (ADS)

Dadic, R.; Mullen, P.; Schneebeli, M.; Brandt, R. E.; Fitzpatric, M.; Carns, R.; Warren, S. G.

2012-04-01

The albedos of snow and ice surfaces are, because of their positive feedback, crucial to the initiation, continuation, and termination of a snowball event, as well as for determining the ice thickness on the ocean. Despite the name, Snowball Earth would not have been entirely snow-covered. As on modern Earth, evaporation would exceed precipitation over much of the tropical ocean. After a transient period with sea ice, the dominant ice type would probably be sea-glaciers flowing in from higher latitude. As they flowed equatorward into the tropical region of net sublimation, their surface snow and subsurface firn would sublimate away, exposing bare glacier ice to the atmosphere and to solar radiation. This ice would be freshwater (meteoric) ice, which originated from snow and firn, so it would contain numerous air bubbles, which determine the albedo. The modern surrogate for this type of ice (glacier ice exposed by pure sublimation, which has never experienced melting), are the bare-ice surfaces of the East Antarctic Ice Sheet near the Trans-Antarctic Mountains. These areas have been well mapped because of their importance in the search for meteorites. A transect across an icefield can potentially sample ice of different ages that has traveled to different depths en route to the sublimation front. We examined a 6-km transect from snow to ice near the Allan Hills (77 S, 158 E, 2000 m ASL), measuring spectral albedo and collecting 1-m core samples. This short transect is a surrogate of a north-south transect across many degrees of latitude on the Snowball ocean. Surfaces on the transect transitioned through the sequence: new snow - old snow - firn - young white ice - old blue ice. The transect from snow to ice showed a systematic progression of decreasing albedo at all wavelengths, as well as decreasing specific surface area (SSA; ratio of air-ice interface area to ice mass) and increasing density. The measured spectral albedos are integrated over wavelength and weighted by the spectral solar flux to obtain broadband albedos. These range from 0.8 for snow to 0.55 for blue ice. Although what determines the albedo is the SSA of bubbles or snow grains, the broadband albedo also shows a systematic relation to the snow or ice density, suggesting that density might serve as a surrogate variable that will be easier to predict than SSA in an ice-sheet model, using a parameterization for firn densification. The ice cores were analyzed by micro-CT (computer tomography) for bubble morphology, cracks (mainly thermal cracks), and SSA. The SSA is used in a radiative transfer model to explain the measured albedo spectra. We found that thermal cracks in the Allan Hills may be more important than in the equatorial region of Snowball Earth. We tried to separate the effects of cracks from original air bubbles by separately computing their individual SSAs in the CT images, and using those SSAs in the albedo model. These methods allow us to estimate a range of albedos for the different possible regions and climatic conditions on low latitudes of Snowball Earth.

Evaluation of a distributed energy balance model for a high-altitude glacier on the Tibetan Plateau using a time lapse camera system

NASA Astrophysics Data System (ADS)

Huintjes, Eva; Sauter, Tobias; Krenscher, Tobias; Maussion, Fabien; Kropacek, Jan; Yang, Wei; Zhang, Guoshuai; Kang, Shichang; Buchroithner, Manfred; Scherer, Dieter; Schneider, Christoph

2013-04-01

In the remote and high-altitude mountain areas of the Tibetan Plateau, climate observations as well as glacier-wide mass and energy balance determinations are scarce. Therefore, the application of models to determine reliable information on mass balance and runoff is important. Simultaneously, these circumstances make it difficult to evaluate the models. Since 2009, we operate an automatic weather station (AWS) in the ablation zone of Zhadang Glacier (5.665 m a.s.l.). The glacier is easily accessible. It is situated in the southern-central part of the Tibetan Plateau (30.5°N) in the Nam Co drainage basin and ranges between 5.400 and 5.900 m a.s.l. Based on these measurements over 2009-2012, we run and evaluate a physically based, distributed energy and mass balance model. The applied model couples an energy balance to a multilayer snow model and therefore accounts for subsurface processes like refreezing, subsurface melt and densification of the snowpack. First, the model is evaluated at point scale against measurements from the AWS. The results show that modelled accumulation and ablation patterns reproduce the observed changes in surface height very well. To evaluate the distributed model, we use daily images of a time lapse camera system installed nearby the glacier over 2010-2012. Therefore the non calibrated slope images had to be orthorectified using ground control points measured during field campaigns. The temporally and spatially highly resolved time series allows a detailed evaluation of the distributed energy balance model by analyzing the spatial and temporal heterogeneity of the snow line during the ablation season. First results show that the model captures the observed spatial heterogeneity of melt on the glacier surface. Subsequently to the evaluation the model will be applied on several glaciers and small ice caps in remote areas on the Tibetan Plateau to determine the linkages between climate fluctuations and glacier variability. The work is part of research projects funded by the DFG Priority Programme 1372: "Tibetan Plateau: Formation-Climate-Ecosystems" (TiP) and the BMBF research program "Central Asia and Tibet: Monsoon dynamics and geo-ecosystems" (CAME).

[Multi-Scale Convergence of Cold-Land Process Representation in Land-Surface Models, Microwave Remote Sensing, and Field Observations

NASA Technical Reports Server (NTRS)

Shi, Jiancheng

2005-01-01

The cryosphere is a major component of the hydrosphere and interacts significantly with the global climate system, the geosphere, and the biosphere. Measurement of the amount of water stored in the snow pack and forecasting the rate of melt are thus essential for managing water supply and flood control systems. Snow hydrologists are confronted with the dual problems of estimating both the quantity of water held by seasonal snow packs and time of snow melt. Monitoring these snow parameters is essential for one of the objectives of the Earth Science Enterprise-understanding of the global hydrologic cycle. Measuring spatially distributed snow properties, such as snow water equivalence (SWE) and wetness, from space is a key component for improvement of our understanding of coupled atmosphere-surface processes. Through the GWEC project, we have significantly advanced our understandings and improved modeling capabilities of the microwave signatures in response to snow and underground properties.

Evaluation of snowmelt simulation in the Weather Research and Forecasting model

NASA Astrophysics Data System (ADS)

Jin, Jiming; Wen, Lijuan

2012-05-01

The objective of this study is to better understand and improve snowmelt simulations in the advanced Weather Research and Forecasting (WRF) model by coupling it with the Community Land Model (CLM) Version 3.5. Both WRF and CLM are developed by the National Center for Atmospheric Research. The automated Snow Telemetry (SNOTEL) station data over the Columbia River Basin in the northwestern United States are used to evaluate snowmelt simulations generated with the coupled WRF-CLM model. These SNOTEL data include snow water equivalent (SWE), precipitation, and temperature. The simulations cover the period of March through June 2002 and focus mostly on the snowmelt season. Initial results show that when compared to observations, WRF-CLM significantly improves the simulations of SWE, which is underestimated when the release version of WRF is coupled with the Noah and Rapid Update Cycle (RUC) land surface schemes, in which snow physics is oversimplified. Further analysis shows that more realistic snow surface energy allocation in CLM is an important process that results in improved snowmelt simulations when compared to that in Noah and RUC. Additional simulations with WRF-CLM at different horizontal spatial resolutions indicate that accurate description of topography is also vital to SWE simulations. WRF-CLM at 10 km resolution produces the most realistic SWE simulations when compared to those produced with coarser spatial resolutions in which SWE is remarkably underestimated. The coupled WRF-CLM provides an important tool for research and forecasts in weather, climate, and water resources at regional scales.

Development of a Coupled Framework for Simulating Interactive Effects of Frozen Soil Hydrological Dynamics in Permafrost Regions

DTIC Science & Technology

2013-11-01

Permafrost Input Database Geology, Lithologic Data, Snow Cover, Air Temperature, Ground Temperatures, Vegetation Precipitation Soil Properties GIPL...be found in Nicolsky et al. (2007). Required input data include climate data, snow cover, soil thermal properties, lithological data, and vegetative

Short Trips and a Traverse

NASA Technical Reports Server (NTRS)

Cameron, Richard

2012-01-01

Dr. Cameron joined the Arctic Institute of North America in 1956 to participate in IGY-related activities in Antarctica. He served as Chief Glaciologist at Wilkes Station, on the coast of East Antarctica. This was a joint Navy-civilian operation consisting of 17 Navy personnel and 10 scientists. Specifically, his glaciological team consisted of two colleagues with whom he had worked before - Olav Loken in Norway in the summer of 1953, and John Molholm in Greenland in the summer of 1954. This team spent much of its time at a remote station established 80 kilometers (50 miles) inland, where they conducted both meteorological and glaciological studies. One of the glaciological studies entailed digging a 35-meter (approx.115-foot) vertical pit to study snow densification and stratigraphy. The assignment for the Navy Seabees was to first establish a joint US-NZ base at Cape Hallett and then go along the coast of East Antarctica and set up Wilkes Station.

Radiative transfer model of snow for bare ice regions

NASA Astrophysics Data System (ADS)

Tanikawa, T.; Aoki, T.; Niwano, M.; Hosaka, M.; Shimada, R.; Hori, M.; Yamaguchi, S.

2016-12-01

Modeling a radiative transfer (RT) for coupled atmosphere-snow-bare ice systems is of fundamental importance for remote sensing applications to monitor snow and bare ice regions in the Greenland ice sheet and for accurate climate change predictions by regional and global climate models. Recently, the RT model for atmosphere-snow system was implemented for our regional and global climate models. However, the bare ice region where recently it has been expanded on the Greenland ice sheet due to the global warming, has not been implemented for these models, implying that this region leads miscalculations in these climate models. Thus, the RT model of snow for bare ice regions is needed for accurate climate change predictions. We developed the RT model for coupled atmosphere-snow-bare ice systems, and conducted a sensitivity analysis of the RT model to know the effect of snow, bare ice and geometry parameters on the spectral radiant quantities. The RT model considers snow and bare-ice inherent optical properties (IOPs), including snow grain size, air bubble size and its concentration and bare ice thickness. The conventional light scattering theory, Mie theory, was used for IOP calculations. Monte Carlo method was used for the multiple scattering. The sensitivity analyses showed that spectral albedo for the bare ice increased with increasing the concentration of the air bubble in the bare ice for visible wavelengths because the air bubble is scatterer with no absorption. For near infrared wavelengths, spectral albedo has no dependence on the air bubble due to the strong light absorption by ice. When increasing solar zenith angle, the spectral albedo were increased for all wavelengths. This is the similar trend with spectral snow albedo. Cloud cover influenced the bare ice spectral albedo by covering direct radiation into diffuse radiation. The purely diffuse radiation has an effective solar zenith angle near 50°. Converting direct into diffuse radiation reduces the effective solar zenith angle, resulting in reducing the spectral albedo. This is also the similar trend with spectral snow albedo. Further work should focus on the validation of the RT model using in situ measurement data through field and laboratory experiments.

Verification of Advances in a Coupled Snow-runoff Modeling Framework for Operational Streamflow Forecasts

NASA Astrophysics Data System (ADS)

Barik, M. G.; Hogue, T. S.; Franz, K. J.; He, M.

2011-12-01

The National Oceanic and Atmospheric Administration's (NOAA's) River Forecast Centers (RFCs) issue hydrologic forecasts related to flood events, reservoir operations for water supply, streamflow regulation, and recreation on the nation's streams and rivers. The RFCs use the National Weather Service River Forecast System (NWSRFS) for streamflow forecasting which relies on a coupled snow model (i.e. SNOW17) and rainfall-runoff model (i.e. SAC-SMA) in snow-dominated regions of the US. Errors arise in various steps of the forecasting system from input data, model structure, model parameters, and initial states. The goal of the current study is to undertake verification of potential improvements in the SNOW17-SAC-SMA modeling framework developed for operational streamflow forecasts. We undertake verification for a range of parameters sets (i.e. RFC, DREAM (Differential Evolution Adaptive Metropolis)) as well as a data assimilation (DA) framework developed for the coupled models. Verification is also undertaken for various initial conditions to observe the influence of variability in initial conditions on the forecast. The study basin is the North Fork America River Basin (NFARB) located on the western side of the Sierra Nevada Mountains in northern California. Hindcasts are verified using both deterministic (i.e. Nash Sutcliffe efficiency, root mean square error, and joint distribution) and probabilistic (i.e. reliability diagram, discrimination diagram, containing ratio, and Quantile plots) statistics. Our presentation includes comparison of the performance of different optimized parameters and the DA framework as well as assessment of the impact associated with the initial conditions used for streamflow forecasts for the NFARB.

An Investigation of the Radiative Effects and Climate Feedbacks of Sea Ice Sources of Sea Salt Aerosol

NASA Astrophysics Data System (ADS)

Horowitz, H. M.; Alexander, B.; Bitz, C. M.; Jaegle, L.; Burrows, S. M.

2017-12-01

In polar regions, sea ice is a major source of sea salt aerosol through lofting of saline frost flowers or blowing saline snow from the sea ice surface. Under continued climate warming, an ice-free Arctic in summer with only first-year, more saline sea ice in winter is likely. Previous work has focused on climate impacts in summer from increasing open ocean sea salt aerosol emissions following complete sea ice loss in the Arctic, with conflicting results suggesting no net radiative effect or a negative climate feedback resulting from a strong first aerosol indirect effect. However, the radiative forcing from changes to the sea ice sources of sea salt aerosol in a future, warmer climate has not previously been explored. Understanding how sea ice loss affects the Arctic climate system requires investigating both open-ocean and sea ice sources of sea-salt aerosol and their potential interactions. Here, we implement a blowing snow source of sea salt aerosol into the Community Earth System Model (CESM) dynamically coupled to the latest version of the Los Alamos sea ice model (CICE5). Snow salinity is a key parameter affecting blowing snow sea salt emissions and previous work has assumed constant regional snow salinity over sea ice. We develop a parameterization for dynamic snow salinity in the sea ice model and examine how its spatial and temporal variability impacts the production of sea salt from blowing snow. We evaluate and constrain the snow salinity parameterization using available observations. Present-day coupled CESM-CICE5 simulations of sea salt aerosol concentrations including sea ice sources are evaluated against in situ and satellite (CALIOP) observations in polar regions. We then quantify the present-day radiative forcing from the addition of blowing snow sea salt aerosol with respect to aerosol-radiation and aerosol-cloud interactions. The relative contributions of sea ice vs. open ocean sources of sea salt aerosol to radiative forcing in polar regions is discussed.

High-Energy-Density LCA-Coupled Structural Energetic Materials for Counter WMD Applications

DTIC Science & Technology

2014-04-01

reactive ( thermite ) fillers as high-energy-density structural energetic materials. The specific objectives include performing fundamental studies to...a) investigate mechanics of dynamic densification and reaction initiation in Ta+Fe2O3 and Ta+Bi2O3 thermite powder mixtures and to (b) design and...initiation in the thermite filler and allow controlled fragmentation. Linear Cellular A; counter WMDs; shock-compression and impact-initiated reactions

Comparison of antioxidant activities of different parts from snow chrysanthemum (Coreopsis tinctoria Nutt.) and identification of their natural antioxidants using high performance liquid chromatography coupled with diode array detection and mass spectrometry and 2,2'-azinobis(3-ethylbenzthiazoline-sulfonic acid)diammonium salt-based assay.

PubMed

Chen, L X; Hu, D J; Lam, S C; Ge, L; Wu, D; Zhao, J; Long, Z R; Yang, W J; Fan, B; Li, S P

2016-01-08

Snow chrysanthemum (Coreopsis tinctoria Nutt.), a world-widely well-known flower tea material, has attracted more and more attention because of its beneficial health effects such as antioxidant activity and special flavor. In this study, a high performance liquid chromatography coupled with diode array detection and mass spectrometry (HPLC-DAD-MS) and 2,2'-azinobis(3-ethylbenzthiazoline-sulfonic acid)diammonium salt (ABTS) based assay was employed for comparison and identification of antioxidants in different samples of snow chrysanthemum. The results showed that snow chrysanthemum flowers possessed the highest while stems presented the lowest antioxidant capacities. Fourteen detected peaks with antioxidant activity were temporarily identified as 3,4',5,6,7-pentahydroxyflavanone-O-hexoside, chlorogenic acid, 2R-3',4',8-trihydroxyflavanone-7-O-glucoside, flavanomarein, flavanocorepsin, flavanokanin, quercetagitin-7-O-glucoside, 3',5,5',7-tetrahydroxyflavanone-O-hexoside, marein, maritimein, 1,3-dicaffeoylquinic acid, coreopsin, okanin and acetyl-marein by comparing their UV spectra, retention times and MS data with standards or literature data. Antioxidants existed in snow chrysanthemum are quite different from those reported in Chrysanthemum morifolium, a well-known traditional beverage in China, which indicated that snow chrysanthemum may be a promising herbal tea material with obvious antioxidant activity. Copyright © 2015 Elsevier B.V. All rights reserved.

Modeling the Interaction of Radiation Between Vegetation and the Seasonal Snowcover

NASA Astrophysics Data System (ADS)

Tribbeck, M. J.; Gurney, R. J.; Morris, E. M.; Pearson, D.

2001-12-01

Prediction of meltwater runoff is crucial to communities where the seasonal snowpack is the major water supply. Water is itself a vital resource and it carries nutrients both in solution and in suspension. Simulation of snowpack depletion at a point in open areas has previously been shown to produce accurate results using physically based models such as SNTHERM. However, the radiation balance is more complex under a forest canopy as radiation is scattered and absorbed by canopy elements. This can alter the timing and magnitude of snowpack runoff substantially. The interaction of radiation between a forest canopy and its underlying snowcover is modeled by the coupling of a physically based snow model and an optical and thermal radiation canopy model. The snow model, which is based on SNTHERM (Jordan, 1991), is a discrete, multi-layer, one-dimensional mass and energy budget model for snow and is formulated with an adaptive grid system that compresses with the compacting snowpack and allows retention of snowpack stratigraphy. The vegetation canopy model approximates the canopy as a series of discrete, randomly orientated elements that scatter and absorb optical and thermal radiation. Multiple scattering of radiation between canopy and snow surface is modeled to conserve energy. The coupled model SNOWCAN differs from other vegetation-snow models such as GORT or SNOBAL as it models the albedo feedback mechanism. This is important as the albedo both affects and is affected by (through grain growth) the radiation balance. SNOWCAN is driven by standard atmospheric variables (including incident solar and thermal radiation) measured outside of the canopy and simulates snowpack properties such as temperature and density profiles as well as the sub-canopy radiation balance. The coupled snow and vegetation energy budget model was used to simulate snow depth at an old jack pine site during the 1994 BOREAS campaign. Measured and simulated snow depth showed good agreement throughout the accumulation and ablation periods, yielding an r2 correlation coefficient of 0.94. The snowpack development was also simulated at a point site within a fir stand in Reynolds Creek Experimental Watershed, Idaho, USA for the water year 2000-2001. A sensitivity analysis was carried out and comparisons were made with field observations of snowpack properties and sub-canopy radiation data for model validation.

Task 4 supporting technology. Densification requirements definition and test objectives. Propellant densification requirements definition

NASA Technical Reports Server (NTRS)

Lak, Tibor; Weeks, D. P.

1995-01-01

The primary challenge of the X-33 CAN is to build and test a prototype LO2 and LH2 densification ground support equipment (GSE) unit, and perform tank thermodynamic testing within the 15 month phase 1 period. The LO2 and LH2 propellant densification system will be scaled for the IPTD LO2 and LH2 tank configurations. The IPTD tanks were selected for the propellant technology demonstration because of the potential benefits to the phase 1 plan: tanks will be built in time to support thermodynamic testing; minimum cost; minimum schedule risk; future testing at MSFC will build on phase 1 data base; and densification system will be available to support X-33 and RLV engine test at IPTD. The objective of the task 1 effort is to define the preliminary requirements of the propellant densification GSE and tank recirculation system. The key densification system design parameters to be established in Task 1 are: recirculation flow rate; heat exchanger inlet temperature; heat exchanger outlet temperature; maximum heat rejection rate; vent flow rate (GN2 and GH2); densification time; and tank pressure level.

Phenomenological analysis of densification mechanism during spark plasma sintering of MgAl2O4

NASA Astrophysics Data System (ADS)

Bernard-Granger, Guillaume; Benameur, Nassira; Addad, Ahmed; Nygren, Mats; Guizard, Christian; Deville, Sylvain

2009-05-01

Spark plasma sintering (SPS) of MgAl2O4 powder was investigated at temperatures between 1200 and 1300{\\deg}C. A significant grain growth was observed during densification. The densification rate always exhibits at least one strong minimum, and resumes after an incubation period. Transmission electron microscopy investigations performed on sintered samples never revealed extensive dislocation activity in the elemental grains. The densification mechanism involved during SPS was determined by anisothermal (investigation of the heating stage of a SPS run) and isothermal methods (investigation at given soak temperatures). Grain-boundary sliding, accommodated by an in-series {interface-reaction/lattice diffusion of the O$^2$-anions} mechanism controlled by the interface-reaction step, governs densification. The zero-densification-rate period, detected for all soak temperatures, arise from the difficulty of annealing vacancies, necessary for the densification to proceed. The detection of atomic ledges at grain boundaries and the modification of the stoichiometry of spinel during SPS could be related to the difficulty to anneal vacancies at temperature soaks.

Mobility of lightweight robots over snow

NASA Astrophysics Data System (ADS)

Lever, James H.; Shoop, Sally A.

2006-05-01

Snowfields are challenging terrain for lightweight (<50 kg) unmanned ground vehicles. Deep sinkage, high snowcompaction resistance, traction loss while turning and ingestion of snow into the drive train can cause immobility within a few meters of travel. However, for suitably designed vehicles, deep snow offers a smooth, uniform surface that can obliterate obstacles. Key requirements for good over-snow mobility are low ground pressure, large clearance relative to vehicle size and a drive system that tolerates cohesive snow. A small robot will invariably encounter deep snow relative to its ground clearance. Because a single snowstorm can easily deposit 30 cm of fresh snow, robots with ground clearance less than about 10 cm must travel over the snow rather than gain support from the underlying ground. This can be accomplished using low-pressure tracks (< 1.5 kPa). Even still, snow-compaction resistance can exceed 20% of vehicle weight. Also, despite relatively high traction coefficients for low track pressures, differential or skid steering is difficult because the outboard track can easily break traction as the vehicle attempts to turn against the snow. Short track lengths (relative to track separation) or coupled articulated robots offer steering solutions for deep snow. This paper presents preliminary guidance to design lightweight robots for good mobility over snow based on mobility theory and tests of PackBot, Talon and SnoBot, a custom-designed research robot. Because many other considerations constrain robot designs, this guidance can help with development of winterization kits to improve the over-snow performance of existing robots.

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.

Modeling and measuring snow for assessing climate change impacts in Glacier National Park, Montana

USGS Publications Warehouse

Fagre, Daniel B.; Selkowitz, David J.; Reardon, Blase; Holzer, Karen; Mckeon, Lisa L.

2002-01-01

A 12-year program of global change research at Glacier National Park by the U.S. Geological Survey and numerous collaborators has made progress in quantifying the role of snow as a driver of mountain ecosystem processes. Spatially extensive snow surveys during the annual accumulation/ablation cycle covered two mountain watersheds and approximately 1,000 km2 . Over 7,000 snow depth and snow water equivalent (SWE) measurements have been made through spring 2002. These augment two SNOTEL sites, 9 NRCS snow courses, and approximately 150 snow pit analyses. Snow data were used to establish spatially-explicit interannual variability in snowpack SWE. East of the Continental Divide, snowpack SWE was lower but also less variable than west of the Divide. Analysis of snowpacks suggest downward trends in SWE, a reduction in snow cover duration, and earlier melt-out dates during the past 52 years. Concurrently, high elevation forests and treelines have responded with increased growth. However, the 80 year record of snow from 3 NRCS snow courses reflects a strong influence from the Pacific Decadal Oscillation, resulting in 20-30 year phases of greater or lesser mean SWE. Coupled with the fine-resolution spatial snow data from the two watersheds, the ecological consequences of changes in snowpack can be empirically assessed at a habitat patch scale. This will be required because snow distribution models have had varied success in simulating snowpack accumulation/ablation dynamics in these mountain watersheds, ranging from R2=0.38 for individual south-facing forested snow survey routes to R2=0.95 when aggregated to the watershed scale. Key ecological responses to snowpack changes occur below the watershed scale, such as snow-mediated expansion of forest into subalpine meadows, making continued spatially-explicit snow surveys a necessity. 

Study of aerosol effect on accelerated snow melting over the Tibetan Plateau during boreal spring

NASA Astrophysics Data System (ADS)

Lee, Woo-Seop; Bhawar, Rohini L.; Kim, Maeng-Ki; Sang, Jeong

2013-08-01

In the present study, a coupled atmosphere-ocean global climate model (CSIRO-Mk3.6) is used to investigate the role of aerosol forcing agents as drivers of snow melting trends in the Tibetan Plateau (TP) region. Anthropogenic aerosol-induced snow cover changes in a warming climate are calculated from the difference between historical run (HIST) and all forcing except anthropogenic aerosol (NoAA). Absorbing aerosols can influence snow cover by warming the atmosphere, reducing snow reflectance after deposition. The warming the rate of snow melt, exposing darker surfaces below to short-wave radiation sooner, and allowing them to heat up even faster in the Himalayas and TP. The results show a strong spring snow cover decrease over TP when absorbing anthropogenic aerosol forcing is considered, whereas snow cover fraction (SCF) trends in NoAA are weakly negative (but insignificant) during 1951-2005. The enhanced spring snow cover trends in HIST are due to overall effects of different forcing agents: When aerosol forcing (AERO) is considered, a significant reduction of SCF than average can be found over the western TP and Himalayas. The large decreasing trends in SCF over the TP, with the maximum reduction of SCF around 12-15% over the western TP and Himalayas slope. Also accelerated snow melting during spring is due to effects of aerosol on snow albedo, where aerosol deposition cause decreases snow albedo. However, the SCF change in the “NoAA” simulations was observed to be less.

Reconfiguration of a flexible flat plate under snow loading

NASA Astrophysics Data System (ADS)

Gosselin, Frédérick; de Langre, Emmanuel

2015-11-01

Snow and wind constitute two of the main sources of mechanical loading on terrestrial plants. Plants bend and twist with large amplitude to bear these loads. For the past ten years, various authors have sought to decompose the problem of plant reconfiguration under fluid flow into its fundamental mechanical ingredients by studying the reconfiguration of simple flexible structures such as beams, plates, rods and strips. Here, we adopt a similar approach to these studies and consider the snow interception of a flexible flat plate. We performed two sets of experiments on thin flexible rectangular plates supported at their center: in the first one, a plate was subjected to real snowing events; in the second one, a plate was loaded with glass beads acting as a granular media similar to snow. Moreover, a theoretical model coupling the Elastica formulation to a loading with a set angle of repose is developed. The model is found to be in good agreement with the experiments on glass beads. Asymptotic scaling laws can be found similarly to the Vogel exponents of reconfiguring structures. For the real snow loading, it is found that the cohesive force in snow which is highly dependent on the snow temperature complicate things greatly.

Quantitative and Qualitative Analysis of Flavonoids and Phenolic Acids in Snow Chrysanthemum (Coreopsis tinctoria Nutt.) by HPLC-DAD and UPLC-ESI-QTOF-MS.

PubMed

Yang, Yinjun; Sun, Xinguang; Liu, Jinjun; Kang, Liping; Chen, Sibao; Ma, Baiping; Guo, Baolin

2016-09-30

A simple, accurate and reliable high performance liquid chromatography coupled with photodiode array detection (HPLC-DAD) method was developed and then successfully applied for simultaneous quantitative analysis of eight compounds, including chlorogenic acid ( 1 ), ( R / S )-flavanomarein ( 2 ), butin-7- O -β-d-glucopyranoside ( 3 ), isookanin ( 4 ), taxifolin ( 5 ), 5,7,3',5'-tetrahydroxyflavanone-7- O -β-d-glucopyranoside ( 6 ), marein ( 7 ) and okanin ( 8 ), in 23 batches of snow chrysanthemum of different seed provenance and from various habitats. The results showed total contents of the eight compounds in the samples with seed provenance from Keliyang (Xinjiang, China), are higher than in samples from the other five provenances by 52.47%, 15.53%, 19.78%, 21.17% and 5.06%, respectively, which demonstrated that provenance has a great influence on the constituents in snow chrysanthemum. Meanwhile, an ultra performance liquid chromatography coupled with electrospray ionization and quadrupole time-of-flight-mass spectrometry (UPLC-ESI-QTOF-MS) was also employed to rapidly separate and identify flavonoids and phenolic acids in snow chrysanthemum from Keliyang. As a result, a total of 30 constituents, including 26 flavonoids and four phenolic acids, were identified or tentatively identified based on the exact mass information, the fragmentation characteristics, and retention times of eight reference standards. This work may provide an efficient approach to comprehensively evaluate the quality of snow chrysanthemum.

Alluvial Fans on Dunes in Kaiser Crater Suggest Niveo-Aeolian and Denivation Processes on Mars

NASA Technical Reports Server (NTRS)

Bourke, M. C.

2005-01-01

On Earth, cold region sand dunes often contain inter-bedded sand, snow, and ice. These mixed deposits of wind-driven snow, sand, silt, vegetal debris, or other detritus have been termed Niveo-aeolian deposits. These deposits are often coupled with features that are due to melting or sublimation of snow, called denivation features. Snow and ice may be incorporated into dunes on Mars in three ways. Diffusion of water vapour into pore spaces is the widely accepted mechanism for the accretion of premafrost ice. Additional mechanisms may include the burial by sand of snow that has fallen on the dune surface or the synchronous transportation and deposition of snow, sand and ice. Both of these mechanisms have been reported for polar dunes on Earth. Niveo-aeolian deposits in polar deserts on Earth have unique morphologies and sedimentary structures that are generally not found in warm desert dunes. Recent analysis of MOC-scale data have found evidence for potential niveo-aeolian and denivation deposits in sand dunes on Mars.

Snow Micro-Structure Model

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

Micah Johnson, Andrew Slaughter

PIKA is a MOOSE-based application for modeling micro-structure evolution of seasonal snow. The model will be useful for environmental, atmospheric, and climate scientists. Possible applications include application to energy balance models, ice sheet modeling, and avalanche forecasting. The model implements physics from published, peer-reviewed articles. The main purpose is to foster university and laboratory collaboration to build a larger multi-scale snow model using MOOSE. The main feature of the code is that it is implemented using the MOOSE framework, thus making features such as multiphysics coupling, adaptive mesh refinement, and parallel scalability native to the application. PIKA implements three equations:more » the phase-field equation for tracking the evolution of the ice-air interface within seasonal snow at the grain-scale; the heat equation for computing the temperature of both the ice and air within the snow; and the mass transport equation for monitoring the diffusion of water vapor in the pore space of the snow.« less

An integrated uncertainty analysis and data assimilation approach for improved streamflow predictions

NASA Astrophysics Data System (ADS)

Hogue, T. S.; He, M.; Franz, K. J.; Margulis, S. A.; Vrugt, J. A.

2010-12-01

The current study presents an integrated uncertainty analysis and data assimilation approach to improve streamflow predictions while simultaneously providing meaningful estimates of the associated uncertainty. Study models include the National Weather Service (NWS) operational snow model (SNOW17) and rainfall-runoff model (SAC-SMA). The proposed approach uses the recently developed DiffeRential Evolution Adaptive Metropolis (DREAM) to simultaneously estimate uncertainties in model parameters, forcing, and observations. An ensemble Kalman filter (EnKF) is configured with the DREAM-identified uncertainty structure and applied to assimilating snow water equivalent data into the SNOW17 model for improved snowmelt simulations. Snowmelt estimates then serves as an input to the SAC-SMA model to provide streamflow predictions at the basin outlet. The robustness and usefulness of the approach is evaluated for a snow-dominated watershed in the northern Sierra Mountains. This presentation describes the implementation of DREAM and EnKF into the coupled SNOW17 and SAC-SMA models and summarizes study results and findings.

Environmental and natural resource implications of sustainable urban infrastructure systems

NASA Astrophysics Data System (ADS)

Bergesen, Joseph D.; Suh, Sangwon; Baynes, Timothy M.; Kaviti Musango, Josephine

2017-12-01

As cities grow, their environmental and natural resource footprints also tend to grow to keep up with the increasing demand on essential urban services such as passenger transportation, commercial space, and thermal comfort. The urban infrastructure systems, or socio-technical systems providing these services are the major conduits through which natural resources are consumed and environmental impacts are generated. This paper aims to gauge the potential reductions in environmental and resources footprints through urban transformation, including the deployment of resource-efficient socio-technical systems and strategic densification. Using hybrid life cycle assessment approach combined with scenarios, we analyzed the greenhouse gas (GHG) emissions, water use, metal consumption and land use of selected socio-technical systems in 84 cities from the present to 2050. The socio-technical systems analyzed are: (1) bus rapid transit with electric buses, (2) green commercial buildings, and (3) district energy. We developed a baseline model for each city considering gross domestic product, population density, and climate conditions. Then, we overlaid three scenarios on top of the baseline model: (1) decarbonization of electricity, (2) aggressive deployment of resource-efficient socio-technical systems, and (3) strategic urban densification scenarios to each city and quantified their potentials in reducing the environmental and resource impacts of cities by 2050. The results show that, under the baseline scenario, the environmental and natural resource footprints of all 84 cities combined would increase 58%-116% by 2050. The resource-efficient scenario along with strategic densification, however, has the potential to curve down GHG emissions to 17% below the 2010 level in 2050. Such transformation can also limit the increase in all resource footprints to less than 23% relative to 2010. This analysis suggests that resource-efficient urban infrastructure and decarbonization of electricity coupled with strategic densification have a potential to mitigate resources and environmental footprints of growing cities.

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.

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

The competition of densification and structure ordering during crystallization of HCP-Mg in the framework of layering

NASA Astrophysics Data System (ADS)

Luo, Jie; Jiang, Yewei; Yu, Ronggang; Wu, Yongquan

2017-06-01

In this paper, we performed an NPT molecular dynamics simulation of crystallization process of HCP-Mg to probe the competition between densification and structural ordering. Two opposite layering patterns, i.e. outward and inward, were designed for analysis. From the perspective of solid-like cluster (SLC) itself, structural ordering always precedes densification; but from the perspective of SLC's precursor, structural ordering always lags behind densification; the reversion occurs at the closest two liquid layers around SLC. We call it dip-rebound phenomenon. This phenomenon is a completely new finding. It resolves, to some extent, recent debate about whether densification or structural ordering triggers crystallization.

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.

Stochastic parameterization for light absorption by internally mixed BC/dust in snow grains for application to climate models

NASA Astrophysics Data System (ADS)

Liou, K. N.; Takano, Y.; He, C.; Yang, P.; Leung, L. R.; Gu, Y.; Lee, W. L.

2014-06-01

A stochastic approach has been developed to model the positions of BC (black carbon)/dust internally mixed with two snow grain types: hexagonal plate/column (convex) and Koch snowflake (concave). Subsequently, light absorption and scattering analysis can be followed by means of an improved geometric-optics approach coupled with Monte Carlo photon tracing to determine BC/dust single-scattering properties. For a given shape (plate, Koch snowflake, spheroid, or sphere), the action of internal mixing absorbs substantially more light than external mixing. The snow grain shape effect on absorption is relatively small, but its effect on asymmetry factor is substantial. Due to a greater probability of intercepting photons, multiple inclusions of BC/dust exhibit a larger absorption than an equal-volume single inclusion. The spectral absorption (0.2-5 µm) for snow grains internally mixed with BC/dust is confined to wavelengths shorter than about 1.4 µm, beyond which ice absorption predominates. Based on the single-scattering properties determined from stochastic and light absorption parameterizations and using the adding/doubling method for spectral radiative transfer, we find that internal mixing reduces snow albedo substantially more than external mixing and that the snow grain shape plays a critical role in snow albedo calculations through its forward scattering strength. Also, multiple inclusion of BC/dust significantly reduces snow albedo as compared to an equal-volume single sphere. For application to land/snow models, we propose a two-layer spectral snow parameterization involving contaminated fresh snow on top of old snow for investigating and understanding the climatic impact of multiple BC/dust internal mixing associated with snow grain metamorphism, particularly over mountain/snow topography.

Stochastic Parameterization for Light Absorption by Internally Mixed BC/dust in Snow Grains for Application to Climate Models

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

Liou, K. N.; Takano, Y.; He, Cenlin

2014-06-27

A stochastic approach to model the positions of BC/dust internally mixed with two snow-grain types has been developed, including hexagonal plate/column (convex) and Koch snowflake (concave). Subsequently, light absorption and scattering analysis can be followed by means of an improved geometric-optics approach coupled with Monte Carlo photon tracing to determine their single-scattering properties. For a given shape (plate, Koch snowflake, spheroid, or sphere), internal mixing absorbs more light than external mixing. The snow-grain shape effect on absorption is relatively small, but its effect on the asymmetry factor is substantial. Due to a greater probability of intercepting photons, multiple inclusions ofmore » BC/dust exhibit a larger absorption than an equal-volume single inclusion. The spectral absorption (0.2 – 5 um) for snow grains internally mixed with BC/dust is confined to wavelengths shorter than about 1.4 um, beyond which ice absorption predominates. Based on the single-scattering properties determined from stochastic and light absorption parameterizations and using the adding/doubling method for spectral radiative transfer, we find that internal mixing reduces snow albedo more than external mixing and that the snow-grain shape plays a critical role in snow albedo calculations through the asymmetry factor. Also, snow albedo reduces more in the case of multiple inclusion of BC/dust compared to that of an equal-volume single sphere. For application to land/snow models, we propose a two-layer spectral snow parameterization containing contaminated fresh snow on top of old snow for investigating and understanding the climatic impact of multiple BC/dust internal mixing associated with snow grain metamorphism, particularly over mountains/snow topography.« less

Sol-gel synthesis and densification of aluminoborosilicate powders. Part 2: Densification

NASA Technical Reports Server (NTRS)

Bull, Jeffrey; Selvaduray, Guna; Leiser, Daniel

1992-01-01

Aluminoborosilicate (ABS) powders, high in alumina content, were synthesized by the sol-gel process utilizing four different methods of synthesis. The effect of these methods on the densification behavior of ABS powder compacts was studied. Five regions of shrinkage in the temperature range 25-1184 C were identified. In these regions, the greatest shrinkage occurred between the gel-to-glass transition temperature (T sub g approximately equal to 835 C) and the crystallization transformation temperature (T sub t approximately equal 900 C). The dominant mechanism of densification in this range was found to be viscous sintering. ABS powders were amorphous to x-rays up to T sub t at which a multiphasic structure crystallized. No 2Al2O3.B2O3 was found in these powders as predicted in the phase diagram. Above T sub t, densification was the result of competing mechanisms including grain growth and boria fluxed viscous sintering. Apparent activation energies for densification in each region varied according to the method of synthesis.

Effects of enzyme loading, densification, and storage on AFEX-pretreated biomass for ethanol production.

PubMed

Biersbach, Gwen; Rijal, Binod; Pryor, Scott W; Gibbons, William R

2015-12-01

Corn stover, switchgrass, and prairie cordgrass were treated with an ammonia fiber expansion (AFEX) process and a novel densification method (ComPAKco). Separate hydrolysis and fermentation (SHF) and simultaneous saccharification and fermentation (SSF) were used to evaluate impacts of densification. ComPAKco densification is characterized by low-temperature and low-energy requirements, resulting in compacted biomass briquettes (CBB) 1-2 cm square, with a bulk density of 380-460 kg/m(3). Feedstocks were evaluated before and following AFEX pretreatment, after densification, and after storage. Two enzyme doses were tested. The low rate used 5 filter paper units (FPU) of Spezyme CP (cellulase) and 21.3 cellobiase units (CBU) of Novozyme 188 (aka NS50010 [β-glucosidase]) per gram of glucan. The high dosage rate was three times higher and resulted in 40-56 % and 33-82 % higher ethanol yields with SHF and SSF, respectively. Trials revealed no adverse effect on ethanol yield following densification or 6-month storage of densified, AFEX-pretreated feedstocks.

Fabrication of Mechanically Tunable and Bioactive Metal Scaffolds for Biomedical Applications

PubMed Central

Jung, Hyun-Do; Lee, Hyun; Kim, Hyoun-Ee; Koh, Young-Hag; Song, Juha

2015-01-01

Biometal systems have been widely used for biomedical applications, in particular, as load-bearing materials. However, major challenges are high stiffness and low bioactivity of metals. In this study, we have developed a new method towards fabricating a new type of bioactive and mechanically reliable porous metal scaffolds-densified porous Ti scaffolds. The method consists of two fabrication processes, 1) the fabrication of porous Ti scaffolds by dynamic freeze casting, and 2) coating and densification of the porous scaffolds. The dynamic freeze casting method to fabricate porous Ti scaffolds allowed the densification of porous scaffolds by minimizing the chemical contamination and structural defects. The densification process is distinctive for three reasons. First, the densification process is simple, because it requires a control of only one parameter (degree of densification). Second, it is effective, as it achieves mechanical enhancement and sustainable release of biomolecules from porous scaffolds. Third, it has broad applications, as it is also applicable to the fabrication of functionally graded porous scaffolds by spatially varied strain during densification. PMID:26709604

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.

Nosocomial rapidly growing mycobacterial infections following laparoscopic surgery: CT imaging findings.

PubMed

Volpato, Richard; de Castro, Claudio Campi; Hadad, David Jamil; da Silva Souza Ribeiro, Flavya; Filho, Ezequiel Leal; Marcal, Leonardo P

2015-09-01

To identify the distribution and frequency of computed tomography (CT) findings in patients with nosocomial rapidly growing mycobacterial (RGM) infection after laparoscopic surgery. A descriptive retrospective study in patients with RGM infection after laparoscopic surgery who underwent CT imaging prior to initiation of therapy. The images were analyzed by two radiologists in consensus, who evaluated the skin/subcutaneous tissues, the abdominal wall, and intraperitoneal region separately. The patterns of involvement were tabulated as: densification, collections, nodules (≥1.0 cm), small nodules (<1.0 cm), pseudocavitated nodules, and small pseudocavitated nodules. Twenty-six patients met the established criteria. The subcutaneous findings were: densification (88.5%), small nodules (61.5%), small pseudocavitated nodules (23.1 %), nodules (38.5%), pseudocavitated nodules (15.4%), and collections (26.9%). The findings in the abdominal wall were: densification (61.5%), pseudocavitated nodules (3.8%), and collections (15.4%). The intraperitoneal findings were: densification (46.1%), small nodules (42.3%), nodules (15.4%), and collections (11.5%). Subcutaneous CT findings in descending order of frequency were: densification, small nodules, nodules, small pseudocavitated nodules, pseudocavitated nodules, and collections. The musculo-fascial plane CT findings were: densification, collections, and pseudocavitated nodules. The intraperitoneal CT findings were: densification, small nodules, nodules, and collections. • Rapidly growing mycobacterial infection may occur following laparoscopy. • Post-laparoscopy mycobacterial infection CT findings are densification, collection, and nodules. • Rapidly growing mycobacterial infection following laparoscopy may involve the peritoneal cavity. • Post-laparoscopy rapidly growing mycobacterial intraperitoneal infection is not associated with ascites or lymphadenopathy.

Measuring snow water equivalent from common-offset GPR records through migration velocity analysis

NASA Astrophysics Data System (ADS)

St. Clair, James; Holbrook, W. Steven

2017-12-01

Many mountainous regions depend on seasonal snowfall for their water resources. Current methods of predicting the availability of water resources rely on long-term relationships between stream discharge and snowpack monitoring at isolated locations, which are less reliable during abnormal snow years. Ground-penetrating radar (GPR) has been shown to be an effective tool for measuring snow water equivalent (SWE) because of the close relationship between snow density and radar velocity. However, the standard methods of measuring radar velocity can be time-consuming. Here we apply a migration focusing method originally developed for extracting velocity information from diffracted energy observed in zero-offset seismic sections to the problem of estimating radar velocities in seasonal snow from common-offset GPR data. Diffractions are isolated by plane-wave-destruction (PWD) filtering and the optimal migration velocity is chosen based on the varimax norm of the migrated image. We then use the radar velocity to estimate snow density, depth, and SWE. The GPR-derived SWE estimates are within 6 % of manual SWE measurements when the GPR antenna is coupled to the snow surface and 3-21 % of the manual measurements when the antenna is mounted on the front of a snowmobile ˜ 0.5 m above the snow surface.

Impacts of the thawing-freezing process on runoff generation in the Sources Area of the Yellow River on the northeastern Qinghai-Tibet Plateau

NASA Astrophysics Data System (ADS)

Wu, Xiaoling; Xiang, Xiaohua; Qiu, Chao; Li, Li

2018-06-01

In cold regions, precipitation, air temperature and snow cover significantly influence soil water, heat transfer, the freezing-thawing processes of the active soil layer, and runoff generation. Hydrological regimes of the world's major rivers in cold regions have changed remarkably since the 1960s, but the mechanisms underlying the changes have not yet been fully understood. Using the basic physical processes for water and heat balances and transfers in snow covered soil, a water-heat coupling model for snow cover and its underlying soil layers was established. We found that freezing-thawing processes can affect the thickness of the active layer, storage capacity for liquid water, and subsequent surface runoffs. Based on calculations of thawing-freezing processes, we investigated hydrological processes at Qumalai. The results show that the water-heat coupling model can be used in this region to provide an understanding of the local movement of hydrological regimes.

Screening variability and change of soil moisture under wide-ranging climate conditions: Snow dynamics effects.

PubMed

Verrot, Lucile; Destouni, Georgia

2015-01-01

Soil moisture influences and is influenced by water, climate, and ecosystem conditions, affecting associated ecosystem services in the landscape. This paper couples snow storage-melting dynamics with an analytical modeling approach to screening basin-scale, long-term soil moisture variability and change in a changing climate. This coupling enables assessment of both spatial differences and temporal changes across a wide range of hydro-climatic conditions. Model application is exemplified for two major Swedish hydrological basins, Norrström and Piteälven. These are located along a steep temperature gradient and have experienced different hydro-climatic changes over the time period of study, 1950-2009. Spatially, average intra-annual variability of soil moisture differs considerably between the basins due to their temperature-related differences in snow dynamics. With regard to temporal change, the long-term average state and intra-annual variability of soil moisture have not changed much, while inter-annual variability has changed considerably in response to hydro-climatic changes experienced so far in each basin.

Optical characterization of multi-scale morphologically complex heterogeneous media - Application to snow with soot impurities

NASA Astrophysics Data System (ADS)

Dai, Xiaoyu; Haussener, Sophia

2018-02-01

A multi-scale methodology for the radiative transfer analysis of heterogeneous media composed of morphologically-complex components on two distinct scales is presented. The methodology incorporates the exact morphology at the various scales and utilizes volume-averaging approaches with the corresponding effective properties to couple the scales. At the continuum level, the volume-averaged coupled radiative transfer equations are solved utilizing (i) effective radiative transport properties obtained by direct Monte Carlo simulations at the pore level, and (ii) averaged bulk material properties obtained at particle level by Lorenz-Mie theory or discrete dipole approximation calculations. This model is applied to a soot-contaminated snow layer, and is experimentally validated with reflectance measurements of such layers. A quantitative and decoupled understanding of the morphological effect on the radiative transport is achieved, and a significant influence of the dual-scale morphology on the macroscopic optical behavior is observed. Our results show that with a small amount of soot particles, of the order of 1ppb in volume fraction, the reduction in reflectance of a snow layer with large ice grains can reach up to 77% (at a wavelength of 0.3 μm). Soot impurities modeled as compact agglomerates yield 2-3% lower reduction of the reflectance in a thick show layer compared to snow with soot impurities modeled as chain-like agglomerates. Soot impurities modeled as equivalent spherical particles underestimate the reflectance reduction by 2-8%. This study implies that the morphology of the heterogeneities in a media significantly affects the macroscopic optical behavior and, specifically for the soot-contaminated snow, indicates the non-negligible role of soot on the absorption behavior of snow layers. It can be equally used in technical applications for the assessment and optimization of optical performance in multi-scale media.

Simulating Black Carbon and Dust and their Radiative Forcing in Seasonal Snow: A Case Study over North China with Field Campaign Measurements

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

Zhao, Chun; Hu, Zhiyuan; Qian, Yun

2014-10-30

A state-of-the-art regional model, WRF-Chem, is coupled with the SNICAR model that includes the sophisticated representation of snow metamorphism processes available for climate study. The coupled model is used to simulate the black carbon (BC) and dust concentrations and their radiative forcing in seasonal snow over North China in January-February of 2010, with extensive field measurements used to evaluate the model performance. In general, the model simulated spatial variability of BC and dust mass concentrations in the top snow layer (hereafter BCS and DSTS, respectively) are quantitatively or qualitatively consistent with observations. The model generally moderately underestimates BCS in themore » clean regions but significantly overestimates BCS in some polluted regions. Most model results fall into the uncertainty ranges of observations. The simulated BCS and DSTS are highest with >5000 ng g-1 and up to 5 mg g-1, respectively, over the source regions and reduce to <50 ng g-1 and <1 μg g-1, respectively, in the remote regions. BCS and DSTS introduce similar magnitude of radiative warming (~10 W m-2) in snowpack, which is comparable to the magnitude of surface radiative cooling due to BC and dust in the atmosphere. This study represents the first effort in using a regional modeling framework to simulate BC and dust and their direct radiative forcing in snow. Although a variety of observational datasets have been used to attribute model biases, some uncertainties in the results remain, which highlights the need for more observations, particularly concurrent measurements of atmospheric and snow aerosols and the deposition fluxes of aerosols, in future campaigns.« less

Physically Accurate Soil Freeze-Thaw Processes in a Global Land Surface Scheme

NASA Astrophysics Data System (ADS)

Cuntz, Matthias; Haverd, Vanessa

2018-01-01

The model Soil-Litter-Iso (SLI) calculates coupled heat and water transport in soil. It was recently implemented into the Australian land surface model CABLE, which is the land component of the Australian Community Climate and Earth System Simulator (ACCESS). Here we extended SLI to include accurate freeze-thaw processes in the soil and snow. SLI provides thence an implicit solution of the energy and water balances of soil and snow as a standalone model and within CABLE. The enhanced SLI was tested extensively against theoretical formulations, laboratory experiments, field data, and satellite retrievals. The model performed well for all experiments at wide-ranging temporal and spatial scales. SLI melts snow faster at the end of the cold season compared to observations though because there is no subgrid variability within SLI given by the implicit, coupled solution of energy and water. Combined CABLE-SLI shows very realistic dynamics and extent of permafrost on the Northern hemisphere. It illustrated, however, also the limits of possible comparisons between large-scale land surface models and local permafrost observations. CABLE-SLI exhibits the same patterns of snow depth and snow water equivalent on the Northern hemisphere compared to satellite-derived observations but quantitative comparisons depend largely on the given meteorological input fields. Further extension of CABLE-SLI with depth-dependence of soil carbon will allow realistic projections of the development of permafrost and frozen carbon stocks in a changing climate.

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.

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

NASA Astrophysics Data System (ADS)

Dhakal, S.; Ojha, S.

2017-12-01

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

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.

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.

Enhancement of the MODIS Daily Snow Albedo Product

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Schaaf, Crystal B.; Wang, Zhuosen; Riggs, George A.

2009-01-01

The MODIS daily snow albedo product is a data layer in the MOD10A1 snow-cover product that includes snow-covered area and fractional snow cover as well as quality information and other metadata. It was developed to augment the MODIS BRDF/Albedo algorithm (MCD43) that provides 16-day maps of albedo globally at 500-m resolution. But many modelers require daily snow albedo, especially during the snowmelt season when the snow albedo is changing rapidly. Many models have an unrealistic snow albedo feedback in both estimated albedo and change in albedo over the seasonal cycle context, Rapid changes in snow cover extent or brightness challenge the MCD43 algorithm; over a 16-day period, MCD43 determines whether the majority of clear observations was snow-covered or snow-free then only calculates albedo for the majority condition. Thus changes in snow albedo and snow cover are not portrayed accurately during times of rapid change, therefore the current MCD43 product is not ideal for snow work. The MODIS daily snow albedo from the MOD10 product provides more frequent, though less robust maps for pixels defined as "snow" by the MODIS snow-cover algorithm. Though useful, the daily snow albedo product can be improved using a daily version of the MCD43 product as described in this paper. There are important limitations to the MOD10A1 daily snow albedo product, some of which can be mitigated. Utilizing the appropriate per-pixel Bidirectional Reflectance Distribution Functions (BRDFs) can be problematic, and correction for anisotropic scattering must be included. The BRDF describes how the reflectance varies with view and illumination geometry. Also, narrow-to-broadband conversion specific for snow on different surfaces must be calculated and this can be difficult. In consideration of these limitations of MOD10A1, we are planning to improve the daily snow albedo algorithm by coupling the periodic per-pixel snow albedo from MCD43, with daily surface ref|outanoom, In this paper, we compare a daily version of MCD43B3 with the daily albedo from MOD10A1. and MCD43B3 with a 16-day average of MOD10A1, over Greenland. We also discuss some near-future planned enhancements to MOD10A1.

Estimation de la superficie du couvert nival a partir d'une combinaison des donnees de teledetection MODIS et AMSR-E dans un contexte de prevision des crues printanieres au Quebec

NASA Astrophysics Data System (ADS)

Bergeron, Jean

Snow cover estimation is a principal source of error for spring streamflow simulations in Québec, Canada. Optical and near infrared remote sensing can improve snow cover area (SCA) estimation due to high spatial resolution but is limited by cloud cover and incoming solar radiation. Passive microwave remote sensing is complementary by its near-transparence to cloud cover and independence to incoming solar radiation, but is limited by its coarse spatial resolution. The study aims to create an improved SCA product from blended passive microwave (AMSR-E daily L3 Brightness Temperature) and optical (MODIS Terra and Aqua daily snow cover L3) remote sensing data in order to improve estimation of river streamflow caused by snowmelt with Québec's operational MOHYSE hydrological model through direct-insertion of the blended SCA product in a coupled snowmelt module (SPH-AV). SCA estimated from AMSR-E data is first compared with SCA estimated with MODIS, as well as with in situ snow depth measurements. Results show good agreement (+95%) between AMSR-E-derived and MODIS-derived SCA products in spring but comparisons with Environment Canada ground stations and SCA derived from Advanced Very High Resolution Radiometer (AVHRR) data show lesser agreements (83 % and 74% respectively). Results also show that AMSR-E generally underestimates SCA. Assimilating the blended snow product in SPH-AV coupled with MOHYSE yields significant improvement of simulated streamflow for the aux Écorces et au Saumon rivers overall when compared with simulations with no update during thaw events, These improvements are similar to results driven by biweekly ground data. Assimilation of remotely-sensed passive microwave data was also found to have little positive impact on springflood forecast due to the difficulty in differentiating melting snow from snow-free surfaces. Considering the direct-insertion and Newtonian nudging assimilation methods, the study also shows the latter method to be superior to the former, notably when assimilating noisy data. Keywords: Snow cover, spring streamflow, MODIS, AMSR-E, hydrological model.

Thermal Patterns in the Snow: Icicles as Indicators of Heat Loss

ERIC Educational Resources Information Center

Bartlett, Albert A.

2008-01-01

On Dec. 27, 2006, we drove with our children and their families to a cabin we rented on the grounds of the "YMCA of the Rockies" in Estes Park, CO, for a few days of winter relaxation and recreation. On the night of the 27th a snowstorm dropped over half a meter of new snow, creating a beautiful winter wonderland. For the next couple of days the…

Enhanced densification, strength and molecular mechanisms in shock compressed porous silicon

NASA Astrophysics Data System (ADS)

Lane, J. Matthew D.; Vogler, Tracy J.

2015-06-01

In most porous materials, void collapse during shock compression couples mechanical energy to thermal energy. Increased temperature drives up pressures and lowers densities in the final Hugoniot states as compared to full-density samples. Some materials, however, exhibit an anomalous enhanced densification in their Hugoniot states when porosity is introduced. We have recently shown that silicon is such a material, and demonstrated a molecular mechanism for the effect using molecular simulation. We will review results from large-scale non-equilibrium molecular dynamics (NEMD) and Hugoniotstat simulations of shock compressed porous silicon, highlighting the mechanism by which porosity produces local shear which nucleate partial phase transition and localized melting at shock pressures below typical thresholds in these materials. Further, we will characterize the stress states and strength of the material as a function of porosity from 5 to 50 percent and with various porosity microstructures. Sandia National Laboratories is a multi program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

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.

Tailoring Magnetic Properties in Bulk Nanostructured Solids

NASA Astrophysics Data System (ADS)

Morales, Jason Rolando

Important magnetic properties and behaviors such as coercivity, remanence, susceptibility, energy product, and exchange coupling can be tailored by controlling the grain size, composition, and density of bulk magnetic materials. At nanometric length scales the grain size plays an increasingly important role since magnetic domain behavior and grain boundary concentration determine bulk magnetic behavior. This has spurred a significant amount of work devoted to developing magnetic materials with nanometric features (thickness, grain/crystallite size, inclusions or shells) in 0D (powder), 1D (wires), and 2D (thin films) materials. Large 3D nanocrystalline materials are more suitable for many applications such as permanent magnets, magneto-optical Faraday isolators etc. Yet there are relatively few successful demonstrations of 3D magnetic materials with nanoscale influenced properties available in the literature. Making dense 3D bulk materials with magnetic nanocrystalline microstructures is a challenge because many traditional densification techniques (HIP, pressureless sintering, etc.) move the microstructure out of the "nano" regime during densification. This dissertation shows that the Current Activated Pressure Assisted Densification (CAPAD) method, also known as spark plasma sintering, can be used to create dense, bulk, magnetic, nanocrystalline solids with varied compositions suited to fit many applications. The results of my research will first show important implications for the use of CAPAD for the production of exchange-coupled nanocomposite magnets. Decreases in grain size were shown to have a significant role in increasing the magnitude of exchange bias. Second, preferentially ordered bulk magnetic materials were produced with highly anisotropic material properties. The ordered microstructure resulted in changing magnetic property magnitudes (ex. change in coercivity by almost 10x) depending on the relative orientation (0° vs. 90°) of an externally applied magnetic field to the sample. Third, a dense magneto-optical material (rare earth oxide) was produced that rotates transmitted polarized light under an externally applied magnetic field, called the Faraday Effect. The magnitude of the rare earth oxide Faraday Effect surpasses that of the current market leader (terbium gallium garnet) in Faraday isolators by ˜2.24x.

Ion-irradiation-induced densification of zirconia sol-gel thin films

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

Levine, T.E.; Giannelis, E.P.; Kodali, P.

1994-02-01

We have investigated the densification behavior of sol-gel zirconia films resulting from ion irradiation. Three sets of films were implanted with neon, krypton, or xenon. The ion energies were chosen to yield approximately constant energy loss through the film and the doses were chosen to yield similar nuclear energy deposition. Ion irradiation of the sol-gel films resulted in carbon and hydrogen loss as indicated by Rutherford backscattering spectrometry and forward recoil energy spectroscopy. Although the densification was hypothesized to result from target atom displacement, the observed densification exhibits a stronger dependence on electronic energy deposition.

Pika: A snow science simulation tool built using the open-source framework MOOSE

NASA Astrophysics Data System (ADS)

Slaughter, A.; Johnson, M.

2017-12-01

The Department of Energy (DOE) is currently investing millions of dollars annually into various modeling and simulation tools for all aspects of nuclear energy. An important part of this effort includes developing applications based on the open-source Multiphysics Object Oriented Simulation Environment (MOOSE; mooseframework.org) from Idaho National Laboratory (INL).Thanks to the efforts of the DOE and outside collaborators, MOOSE currently contains a large set of physics modules, including phase-field, level set, heat conduction, tensor mechanics, Navier-Stokes, fracture and crack propagation (via the extended finite-element method), flow in porous media, and others. The heat conduction, tensor mechanics, and phase-field modules, in particular, are well-suited for snow science problems. Pika--an open-source MOOSE-based application--is capable of simulating both 3D, coupled nonlinear continuum heat transfer and large-deformation mechanics applications (such as settlement) and phase-field based micro-structure applications. Additionally, these types of problems may be coupled tightly in a single solve or across length and time scales using a loosely coupled Picard iteration approach. In addition to the wide range of physics capabilities, MOOSE-based applications also inherit an extensible testing framework, graphical user interface, and documentation system; tools that allow MOOSE and other applications to adhere to nuclear software quality standards. The snow science community can learn from the nuclear industry and harness the existing effort to build simulation tools that are open, modular, and share a common framework. In particular, MOOSE-based multiphysics solvers are inherently parallel, dimension agnostic, adaptive in time and space, fully coupled, and capable of interacting with other applications. The snow science community should build on existing tools to enable collaboration between researchers and practitioners throughout the world, and advance the state-of-the-art in line with other scientific research efforts.

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.

Modeling Snow Regime in Cores of Small Planetary Bodies

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Resilience to Changing Snow Depth in a Shrubland Ecosystem.

NASA Astrophysics Data System (ADS)

Loik, M. E.

2008-12-01

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

A Method for Snow Reanalysis: The Sierra Nevada (USA) Example

NASA Technical Reports Server (NTRS)

Girotto, Manuela; Margulis, Steven; Cortes, Gonzalo; Durand, Michael

2017-01-01

This work presents a state-of-the art methodology for constructing snow water equivalent (SWE) reanalysis. The method is comprised of two main components: (1) a coupled land surface model and snow depletion curve model, which is used to generate an ensemble of predictions of SWE and snow cover area for a given set of (uncertain) inputs, and (2) a reanalysis step, which updates estimation variables to be consistent with the satellite observed depletion of the fractional snow cover time series. This method was applied over the Sierra Nevada (USA) based on the assimilation of remotely sensed fractional snow covered area data from the Landsat 5-8 record (1985-2016). The verified dataset (based on a comparison with over 9000 station years of in situ data) exhibited mean and root-mean-square errors less than 3 and 13 cm, respectively, and correlation greater than 0.95 compared with in situ SWE observations. The method (fully Bayesian), resolution (daily, 90-meter), temporal extent (31 years), and accuracy provide a unique dataset for investigating snow processes. This presentation illustrates how the reanalysis dataset was used to provide a basic accounting of the stored snowpack water in the Sierra Nevada over the last 31 years and ultimately improve real-time streamflow predictions.

Macroscopic modeling for heat and water vapor transfer in dry snow by homogenization.

PubMed

Calonne, Neige; Geindreau, Christian; Flin, Frédéric

2014-11-26

Dry snow metamorphism, involved in several topics related to cryospheric sciences, is mainly linked to heat and water vapor transfers through snow including sublimation and deposition at the ice-pore interface. In this paper, the macroscopic equivalent modeling of heat and water vapor transfers through a snow layer was derived from the physics at the pore scale using the homogenization of multiple scale expansions. The microscopic phenomena under consideration are heat conduction, vapor diffusion, sublimation, and deposition. The obtained macroscopic equivalent model is described by two coupled transient diffusion equations including a source term arising from phase change at the pore scale. By dimensional analysis, it was shown that the influence of such source terms on the overall transfers can generally not be neglected, except typically under small temperature gradients. The precision and the robustness of the proposed macroscopic modeling were illustrated through 2D numerical simulations. Finally, the effective vapor diffusion tensor arising in the macroscopic modeling was computed on 3D images of snow. The self-consistent formula offers a good estimate of the effective diffusion coefficient with respect to the snow density, within an average relative error of 10%. Our results confirm recent work that the effective vapor diffusion is not enhanced in snow.

Assimilating Merged Remote Sensing and Ground based Snowpack Information for Runoff Simulation and Forecasting using Hydrological Models

NASA Astrophysics Data System (ADS)

Infante Corona, J. A.; Lakhankar, T.; Khanbilvardi, R.; Pradhanang, S. M.

2013-12-01

Stream flow estimation and flood prediction influenced by snow melting processes have been studied for the past couple of decades because of their destruction potential, money losses and demises. It has been observed that snow, that was very stationary during its seasons, now is variable in shorter time-scales (daily and hourly) and rapid snowmelt can contribute or been the cause of floods. Therefore, good estimates of snowpack properties on ground are necessary in order to have an accurate prediction of these destructive events. The snow thermal model (SNTHERM) is a 1-dimensional model that analyzes the snowpack properties given the climatological conditions of a particular area. Gridded data from both, in-situ meteorological observations and remote sensing data will be produced using interpolation methods; thus, snow water equivalent (SWE) and snowmelt estimations can be obtained. The soil and water assessment tool (SWAT) is a hydrological model capable of predicting runoff quantity and quality of a watershed given its main physical and hydrological properties. The results from SNTHERM will be used as an input for SWAT in order to have simulated runoff under snowmelt conditions. This project attempts to improve the river discharge estimation considering both, excess rainfall runoff and the snow melting process. Obtaining a better estimation of the snowpack properties and evolution is expected. A coupled use of SNTHERM and SWAT based on meteorological in situ and remote sensed data will improve the temporal and spatial resolution of the snowpack characterization and river discharge estimations, and thus flood prediction.

Effects of loading modes on densification efficiency of spark plasma sintering: sample study of zirconium carbide consolidation

NASA Astrophysics Data System (ADS)

Wei, Xialu; Maximenko, Andrey L.; Back, Christina; Izhvanov, Oleg; Olevsky, Eugene A.

2017-07-01

Theoretical studies on the densification kinetics of the new spark plasma sinter-forging (SPS-forging) consolidation technique and of the regular SPS have been carried out based on the continuum theory of sintering. Both modelling and verifying experimental results indicate that the loading modes play important roles in the densification efficiency of SPS of porous ZrC specimens. Compared to regular SPS, SPS-forging is shown to be able to enhance the densification more significantly during later sintering stages. The derived analytical constitutive equations are utilised to evaluate the high-temperature creep parameters of ZrC under SPS conditions. SPS-forging and regular SPS setups are combined to form a new SPS hybrid loading mode with the purpose of reducing shape irregularity in the SPS-forged specimens. Loading control is imposed to secure the geometry as well as the densification of ZrC specimens during hybrid SPS process.

Comparison of snow melt properties across multiple spatial scales and landscape units in interior sub-Arctic boreal Alaskan watersheds

NASA Astrophysics Data System (ADS)

Bennett, K. E.; Cherry, J. E.; Hiemstra, C. A.; Bolton, W. R.

2013-12-01

Interior sub-Arctic Alaskan snow cover is rapidly changing and requires further study for correct parameterization in physically based models. This project undertook field studies during the 2013 snow melt season to capture snow depth, snow temperature profiles, and snow cover extent to compare with observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor at four different sites underlain by discontinuous permafrost. The 2013 melt season, which turned out to be the latest snow melt period on record, was monitored using manual field measurements (SWE, snow depth data collection), iButtons to record temperature of the snow pack, GoPro cameras to capture time lapse of the snow melt, and low level orthoimagery collected at ~1500 m using a Navion L17a plane mounted with a Nikon D3s camera. Sites were selected across a range of landscape conditions, including a north facing black spruce hill slope, a south facing birch forest, an open tundra site, and a high alpine meadow. Initial results from the adjacent north and south facing sites indicate a highly sensitive system where snow cover melts over just a few days, illustrating the importance of high resolution temporal data capture at these locations. Field observations, iButtons and GoPro cameras show that the MODIS data captures the melt conditions at the south and the north site with accuracy (2.5% and 6.5% snow cover fraction present on date of melt, respectively), but MODIS data for the north site is less variable around the melt period, owing to open conditions and sparse tree cover. However, due to the rapid melt rate trajectory, shifting the melt date estimate by a day results in a doubling of the snow cover fraction estimate observed by MODIS. This information can assist in approximating uncertainty associated with remote sensing data that is being used to populate hydrologic and snow models (the Sacramento Soil Moisture Accounting model, coupled with SNOW-17, and the Variable Infiltration Capacity hydrologic model) and provide greater understanding of error and resultant model sensitivities associated with regional observations of snow cover across the sub-Arctic boreal landscape.

Characterization of errors in a coupled snow hydrology-microwave emission model

USGS Publications Warehouse

Andreadis, K.M.; Liang, D.; Tsang, L.; Lettenmaier, D.P.; Josberger, E.G.

2008-01-01

Traditional approaches to the direct estimation of snow properties from passive microwave remote sensing have been plagued by limitations such as the tendency of estimates to saturate for moderately deep snowpacks and the effects of mixed land cover within remotely sensed pixels. An alternative approach is to assimilate satellite microwave emission observations directly, which requires embedding an accurate microwave emissions model into a hydrologic prediction scheme, as well as quantitative information of model and observation errors. In this study a coupled snow hydrology [Variable Infiltration Capacity (VIC)] and microwave emission [Dense Media Radiative Transfer (DMRT)] model are evaluated using multiscale brightness temperature (TB) measurements from the Cold Land Processes Experiment (CLPX). The ability of VIC to reproduce snowpack properties is shown with the use of snow pit measurements, while TB model predictions are evaluated through comparison with Ground-Based Microwave Radiometer (GBMR), air-craft [Polarimetric Scanning Radiometer (PSR)], and satellite [Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E)] TB measurements. Limitations of the model at the point scale were not as evident when comparing areal estimates. The coupled model was able to reproduce the TB spatial patterns observed by PSR in two of three sites. However, this was mostly due to the presence of relatively dense forest cover. An interesting result occurs when examining the spatial scaling behavior of the higher-resolution errors; the satellite-scale error is well approximated by the mode of the (spatial) histogram of errors at the smaller scale. In addition, TB prediction errors were almost invariant when aggregated to the satellite scale, while forest-cover fractions greater than 30% had a significant effect on TB predictions. ?? 2008 American Meteorological Society.

Two-stage agglomeration of fine-grained herbal nettle waste

NASA Astrophysics Data System (ADS)

Obidziński, Sławomir; Joka, Magdalena; Fijoł, Olga

2017-10-01

This paper compares the densification work necessary for the pressure agglomeration of fine-grained dusty nettle waste, with the densification work involved in two-stage agglomeration of the same material. In the first stage, the material was pre-densified through coating with a binder material in the form of a 5% potato starch solution, and then subjected to pressure agglomeration. A number of tests were conducted to determine the effect of the moisture content in the nettle waste (15, 18 and 21%), as well as the process temperature (50, 70, 90°C) on the values of densification work and the density of the obtained pellets. For pre-densified pellets from a mixture of nettle waste and a starch solution, the conducted tests determined the effect of pellet particle size (1, 2, and 3 mm) and the process temperature (50, 70, 90°C) on the same values. On the basis of the tests, we concluded that the introduction of a binder material and the use of two-stage agglomeration in nettle waste densification resulted in increased densification work (as compared to the densification of nettle waste alone) and increased pellet density.

A new isolation method for biomass-burning tracers in snow: Measurements of p-hydroxybenzoic, vanillic, and dehydroabietic acids

NASA Astrophysics Data System (ADS)

Gao, Shaopeng; Liu, Dameng; Kang, Shichang; Kawamura, Kimitaka; Wu, Guangming; Zhang, Guoshuai; Cong, Zhiyuan

2015-12-01

Organic acids such as p-hydroxybenzoic, vanillic, and dehydroabietic acids are unique biomass-burning tracers for black carbon (BC) and dissolved organic carbon (DOC) in the snow of mountain glaciers, Arctic and Antarctic ice sheets. In this study, we developed a method by solid-phase extraction (SPE) coupled with gas chromatography/ion trap mass spectrometry for the determination of those organic acids in snow. The limit of detection (LOD) is 0.002, 0.001, 0.004 ng mL-1 for p-hydroxybenzoic, vanillic, and dehydroabietic acids, respectively. For p-hydroxybenzoic and vanillic acids, all the four SPE cartridges used produce good recoveries (>75%). However, for dehydroabietic acid, HLB cartridge has much better performance than DPA, FEP-2 and PAX cartridges. The method was applied to the snow samples collected from Zhadang Glacier in the Tibetan Plateau (TP), and demonstrated its feasibility in pretreating and detecting of these target compounds. We found that BC and DOC accumulated in the snow during winter and spring over the TP glaciers are mainly derived from biomass burning. This result demonstrates the capability of our analytical method for a deep understanding on the source of carbonaceous materials in snow.

A comprehensive analysis of the content of heavy rare-earth elements and platinum in snow samples to assess the ecological hazard of air pollution in urban areas

NASA Astrophysics Data System (ADS)

Vinokurov, S. F.; Tarasova, N. P.; Trunova, A. N.; Sychkova, V. A.

2017-07-01

Snow samples from the territory of the Setun River Valley Wildlife Sanctuary are analyzed for the content of rare-earth elements, heavy metals, and other hazardous elements by the inductively coupled plasma mass-spectrometry method. The changes in the concentrations of rare-earth elements, Pt, Pd, and indicator ratios of elements in the solid fractions of snow are revealed. A trend toward a decrease in the content of several elements northeastward of the Moscow Ring Road (MRR) is established. The level of seasonal atmospheric contamination of the area under study is assessed, and a possible source is identified.

Snow water equivalent monitoring retrieved by assimilating passive microwave observations in a coupled snowpack evolution and microwave emission models over North-Eastern Canada

NASA Astrophysics Data System (ADS)

Royer, A.; Larue, F.; De Sève, D.; Roy, A.; Vionnet, V.; Picard, G.; Cosme, E.

2017-12-01

Over northern snow-dominated basins, the snow water equivalent (SWE) is of primary interest for spring streamflow forecasting. SWE retrievals from satellite data are still not well resolved, in particular from microwave (MW) measurements, the only type of data sensible to snow mass. Also, the use of snowpack models is challenging due to the large uncertainties in meteorological input forcings. This project aims to improve SWE prediction by assimilation of satellite brightness temperature (TB), without any ground-based observations. The proposed approach is the coupling of a detailed multilayer snowpack model (Crocus) with a MW snow emission model (DMRT-ML). The assimilation scheme is a Sequential Importance Resampling Particle filter, through ensembles of perturbed meteorological forcings according to their respective uncertainties. Crocus simulations driven by operational meteorological forecasts from the Canadian Global Environmental Multiscale model at 10 km spatial resolution were compared to continuous daily SWE measurements over Québec, North-Eastern Canada (56° - 45°N). The results show a mean bias of the maximum SWE overestimated by 16% with variations up to +32%. This observed large variability could lead to dramatic consequences on spring flood forecasts. Results of Crocus-DMRT-ML coupling compared to surface-based TB measurements (at 11, 19 and 37 GHz) show that the Crocus snowpack microstructure described by sticky hard spheres within DMRT has to be scaled by a snow stickiness of 0.18, significantly reducing the overall RMSE of simulated TBs. The ability of assimilation of daily TBs to correct the simulated SWE is first presented through twin experiments with synthetic data, and then with AMSR-2 satellite time series of TBs along the winter taking into account atmospheric and forest canopy interferences (absorption and emission). The differences between TBs at 19-37 GHz and at 11-19 GHz, in vertical polarization, were assimilated. This assimilation test with synthetic data gives a SWE RMSE reduced by a factor of 2 after assimilation. Assimilation of AMSR-2 TBs shows improvement in SWE retrievals compared to continuous in-situ SWE measurements. The accuracy is discussed as a function of boreal forest density and LAI (MODIS-based data), having significant effects.

Design of an 8-40 GHz Antenna for the Wideband Instrument for Snow Measurements (WISM)

NASA Technical Reports Server (NTRS)

Durham, Timothy E.; Vanhille, Kenneth J.; Trent, Christopher; Lambert, Kevin M.; Miranda, Felix A.

2015-01-01

Measurement of land surface snow remains a significant challenge in the remote sensing arena. Developing the tools needed to remotely measure Snow Water Equivalent (SWE) is an important priority. The Wideband Instrument for Snow Measurements (WISM) is being developed to address this need. WISM is an airborne instrument comprised of a dual-frequency (X- and Ku-bands) Synthetic Aperture Radar (SAR) and dual-frequency (K- and Ka-bands) radiometer. A unique feature of this instrument is that all measurement bands share a common antenna aperture consisting of an array feed reflector that covers the entire bandwidth. This paper covers the design and fabrication of the wideband array feed which is based on tightly coupled dipole arrays. Implementation using a relatively new multi-layer microfabrication process results in a small, 6x6 element, dual-linear polarized array with beamformer that operates from 8 to 40 gigahertz.

Arctic plant ecophysiology and water source utilization in response to altered snow: isotopic (δ18O and δ2H) evidence for meltwater subsidies to deciduous shrubs.

PubMed

Jespersen, R Gus; Leffler, A Joshua; Oberbauer, Steven F; Welker, Jeffrey M

2018-06-28

Warming-linked woody shrub expansion in the Arctic has critical consequences for ecosystem processes and climate feedbacks. The snow-shrub interaction model has been widely implicated in observed Arctic shrub increases, yet equivocal experimental results regarding nutrient-related components of this model have highlighted the need for a consideration of the increased meltwater predicted in expanding shrub stands. We used a 22-year snow manipulation experiment to simultaneously address the unexplored role of snow meltwater in arctic plant ecophysiology and nutrient-related components of the snow-shrub hypothesis. We coupled measurements of leaf-level gas exchange and leaf tissue chemistry (%N and δ 13 C) with an analysis of stable isotopes (δ 18 O and δ 2 H) in soil water, precipitation, and stem water. In deeper snow areas photosynthesis, conductance, and leaf N increased and δ 13 C values decreased in the deciduous shrubs, Betula nana and Salix pulchra, and the graminoid, Eriophorum vaginatum, with the strongest treatment effects observed in deciduous shrubs, consistent with predictions of the snow-shrub hypothesis. We also found that deciduous shrubs, especially S. pulchra, obtained much of their water from snow melt early in the growing season (40-50%), more than either E. vaginatum or the evergreen shrub, Rhododendron tomentosum (Ledum palustre). This result provides the basis for adding a meltwater-focused feedback loop to the snow-shrub interaction model of shrub expansion in the Arctic. Our results highlight the critical role of winter snow in the ecophysiology of Arctic plants, particularly deciduous shrubs, and underline the importance of understanding how global warming will affect the Arctic winter snowpack.

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.

Merging a Terrain-Based Parameter and Snow Particle Counter Data for the Assessment of Snow Redistribution in the Col du Lac Blanc Area

NASA Astrophysics Data System (ADS)

Schön, Peter; Prokop, Alexander; Naaim-Bouvet, Florence; Vionnet, Vincent; Guyomarc'h, Gilbert; Heiser, Micha; Nishimura, Kouichi

2015-04-01

Wind and the associated snow drift are dominating factors determining the snow distribution and accumulation in alpine areas, resulting in a high spatial variability of snow depth that is difficult to evaluate and quantify. The terrain-based parameter Sx characterizes the degree of shelter or exposure of a grid point provided by the upwind terrain, without the computational complexity of numerical wind field models. The parameter has shown to qualitatively predict snow redistribution with good reproduction of spatial patterns. It does not, however, provide a quantitative estimate of changes in snow depths. The objective of our research was to introduce a new parameter to quantify changes in snow depths in our research area, the Col du Lac Blanc in the French Alps. The area is at an elevation of 2700 m and particularly suited for our study due to its consistently bi-modal wind directions. Our work focused on two pronounced, approximately 10 m high terrain breaks, and we worked with 1 m resolution digital snow surface models (DSM). The DSM and measured changes in snow depths were obtained with high-accuracy terrestrial laser scan (TLS) measurements. First we calculated the terrain-based parameter Sx on a digital snow surface model and correlated Sx with measured changes in snow-depths (Δ SH). Results showed that Δ SH can be approximated by Δ SHestimated = α * Sx, where α is a newly introduced parameter. The parameter α has shown to be linked to the amount of snow deposited influenced by blowing snow flux. At the Col du Lac Blanc test side, blowing snow flux is recorded with snow particle counters (SPC). Snow flux is the number of drifting snow particles per time and area. Hence, the SPC provide data about the duration and intensity of drifting snow events, two important factors not accounted for by the terrain parameter Sx. We analyse how the SPC snow flux data can be used to estimate the magnitude of the new variable parameter α . To simulate the development of the snow surface in dependency of Sx, SPC flux and time, we apply a simple cellular automata system. The system consists of raster cells that develop through discrete time steps according to a set of rules. The rules are based on the states of neighboring cells. Our model assumes snow transport in dependency of Sx gradients between neighboring cells. The cells evolve based on difference quotients between neighbouring cells. Our analyses and results are steps towards using the terrain-based parameter Sx, coupled with SPC data, to quantitatively estimate changes in snow depths, using high raster resolutions of 1 m.

Bond-breaking mechanism of vitreous silica densification by IR femtosecond laser pulses

NASA Astrophysics Data System (ADS)

Shcheblanov, Nikita S.; Povarnitsyn, Mikhail E.

2016-04-01

The densification of the vitreous silica (v-SiO2) due to laser irradiation appears reasonable to cause the change in refractive index. In this letter, the v-SiO2 densification under IR femtosecond laser irradiation is studied within molecular-dynamics simulation. The single- and multi-pulse interactions are explored numerically with an account of the bond-breaking mechanism. By analyzing the network at nanoscale, the nature of v-SiO2 densification is assigned to the reduction of major ring fractions of six- and seven-membered rings to minor fractions of three- and four-membered rings (related to D 2 and D 1 Raman signatures, respectively). The athermal behavior of v-SiO2 densification is disclosed at different degrees of ionization for both the single- and multi-pulse cases at sub-threshold regimes. The good agreement between calculated and measured D2 defect line and Si-O-Si angle changes argues in favor of the found mechanism.

Research of interaction between technological and material parameters during densification of sunflower hulls

NASA Astrophysics Data System (ADS)

Križan, Peter; Matúš, Miloš; Beniak, Juraj; Šooš, Ľubomír

2018-01-01

During the biomass densification can be recognized various technological variables and also material parameters which significantly influences the final solid biofuels (pellets) quality. In this paper, we will present the research findings concerning relationships between technological and material variables during densification of sunflower hulls. Sunflower hulls as an unused source is a typical product of agricultural industry in Slovakia and belongs to the group of herbaceous biomass. The main goal of presented experimental research is to determine the impact of compression pressure, compression temperature and material particle size distribution on final biofuels quality. Experimental research described in this paper was realized by single-axis densification, which was represented by experimental pressing stand. The impact of mentioned investigated variables on the final briquettes density and briquettes dilatation was determined. Mutual interactions of these variables on final briquettes quality are showing the importance of mentioned variables during the densification process. Impact of raw material particle size distribution on final biofuels quality was also proven by experimental research on semi-production pelleting plant.

Elastic Moduli of Permanently Densified Silica Glasses

PubMed Central

Deschamps, T.; Margueritat, J.; Martinet, C.; Mermet, A.; Champagnon, B.

2014-01-01

Modelling the mechanical response of silica glass is still challenging, due to the lack of knowledge concerning the elastic properties of intermediate states of densification. An extensive Brillouin Light Scattering study on permanently densified silica glasses after cold compression in diamond anvil cell has been carried out, in order to deduce the elastic properties of such glasses and to provide new insights concerning the densification process. From sound velocity measurements, we derive phenomenological laws linking the elastic moduli of silica glass as a function of its densification ratio. The found elastic moduli are in excellent agreement with the sparse data extracted from literature, and we show that they do not depend on the thermodynamic path taken during densification (room temperature or heating). We also demonstrate that the longitudinal sound velocity exhibits an anomalous behavior, displaying a minimum for a densification ratio of 5%, and highlight the fact that this anomaly has to be distinguished from the compressibility anomaly of a-SiO2 in the elastic domain. PMID:25431218

Estimation of Coastal Freshwater Discharge into Prince William Sound using a High-Resolution Hydrological Model

NASA Astrophysics Data System (ADS)

Beamer, J. P.; Hill, D. F.; Liston, G. E.; Arendt, A. A.; Hood, E. W.

2013-12-01

In Prince William Sound (PWS), Alaska, there is a pressing need for accurate estimates of the spatial and temporal variations in coastal freshwater discharge (FWD). FWD into PWS originates from streamflow due to rainfall, annual snowmelt, and changes in stored glacier mass and is important because it helps establish spatial and temporal patterns in ocean salinity and temperature, and is a time-varying boundary condition for oceanographic circulation models. Previous efforts to model FWD into PWS have been heavily empirical, with many physical processes absorbed into calibration coefficients that, in many cases, were calibrated to streams and rivers not hydrologically similar to those discharging into PWS. In this work we adapted and validated a suite of high-resolution (in space and time), physically-based, distributed weather, snowmelt, and runoff-routing models designed specifically for snow melt- and glacier melt-dominated watersheds like PWS in order to: 1) provide high-resolution, real-time simulations of snowpack and FWD, and 2) provide a record of historical variations of FWD. SnowModel, driven with gridded topography, land cover, and 32 years (1979-2011) of 3-hourly North American Regional Reanalysis (NARR) atmospheric forcing data, was used to simulate snowpack accumulation and melt across a PWS model domain. SnowModel outputs of daily snow water equivalent (SWE) depth and grid-cell runoff volumes were then coupled with HydroFlow, a runoff-routing model which routed snowmelt, glacier-melt, and rainfall to each watershed outlet (PWS coastline) in the simulation domain. The end product was a continuous 32-year simulation of daily FWD into PWS. In order to validate the models, SWE and snow depths from SnowModel were compared with observed SWE and snow depths from SnoTel and snow survey data, and discharge from HydroFlow was compared with observed streamflow measurements. As a second phase of this research effort, the coupled models will be set-up to run in real-time, where daily measurements from weather stations in the PWS will be used to drive simulations of snow cover and streamflow. In addition, we will deploy a strategic array of instrumentation aimed at validating the simulated weather estimates and the calculations of freshwater discharge. Upon successful implementation and validation of the modeling system, it will join established and ongoing computational and observational efforts that have a common goal of establishing a comprehensive understanding of the physical behavior of PWS.

Integration, Validation, and Application of a PV Snow Coverage Model in SAM

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

Freeman, Janine M.; Ryberg, David Severin

2017-08-01

Due to the increasing deployment of PV systems in snowy climates, there is significant interest in a method capable of estimating PV losses resulting from snow coverage that has been verified for a variety of system designs and locations. Many independent snow coverage models have been developed over the last 15 years; however, there has been very little effort verifying these models beyond the system designs and locations on which they were based. Moreover, major PV modeling software products have not yet incorporated any of these models into their workflows. In response to this deficiency, we have integrated the methodologymore » of the snow model developed in the paper by Marion et al. (2013) into the National Renewable Energy Laboratory's (NREL) System Advisor Model (SAM). In this work, we describe how the snow model is implemented in SAM and we discuss our demonstration of the model's effectiveness at reducing error in annual estimations for three PV arrays. Next, we use this new functionality in conjunction with a long term historical data set to estimate average snow losses across the United States for two typical PV system designs. The open availability of the snow loss estimation capability in SAM to the PV modeling community, coupled with our results of the nationwide study, will better equip the industry to accurately estimate PV energy production in areas affected by snowfall.« less

The Fate of Aspen in a World with Diminishing Snowpacks

NASA Astrophysics Data System (ADS)

Kavanagh, K.; Link, T. E.; Seyfried, M. S.; Kemp, K. B.

2010-12-01

Aspen (Populus tremuloides) productivity is tightly coupled with soil moisture. In the mountainous regions of the western USA, annual replenishment of soil moisture commonly occurs during snowmelt. Therefore, snow pack depth and duration can play an important role in sustaining aspen productivity. The presence of almost 50 years of detailed climate data across an elevational transect in the Reynolds Creek Experimental Watershed (RCEW) in southwestern Idaho offers a novel opportunity to better understand the role of shifting precipitation patterns on aspen productivity. Over the past 50 years, the proportion of the precipitation falling in the form of snow decreased by almost a factor of 2 at mid to low elevations in the RCEW, coupled with a roughly four week advance of snow ablation, and decline of large snow drifts that release moisture into the early summer. Results from growth ring increment, stable isotope analysis, sapflux and a process model (Biome BGC), will be used to determine the impact of shifting precipitation patterns on tree productivity along this transect over the past 50 years. Aspen trees located on moist microsites continue to transpire water and maintain high stomatal conductance 21 days later in the growing season relative to individuals on drier microsites. Predictions of net primary productivity (NPP) in aspen are very sensitive to precipitation patterns. NPP becomes negative as early as day 183 (90 days post budbreak) for years with little winter and spring precipitation whereas, in years with ample winter and spring precipitation, NPP remains positive until day 260 when leaf fall occurs. These results give unique insight into the conditions that deciduous tree species will encounter in a warming climate where snow water equivalent continues to diminish and soil moisture declines soon after budbreak occurs.

Review: Pressure-Induced Densification of Oxide Glasses at the Glass Transition

NASA Astrophysics Data System (ADS)

Kapoor, Saurabh; Wondraczek, Lothar; Smedskjaer, Morten M.

2017-02-01

Densification of oxide glasses at the glass transition offers a novel route to develop bulk glasses with tailored properties for emerging applications. Such densification can be achieved in the technologically relevant pressure regime of up to 1GPa. However, the present understanding of the composition-structure-property relationships governing these glasses is limited, with key questions, e.g., related to densification mechanism, remaining largely unanswered. Recent advances in structural characterization tools and high-pressure apparatuses have prompted new research efforts. Here, we review this recent progress and the insights gained in the understanding of the influence of isostatic compression at elevated temperature (so-called hot compression) on the composition-structure-property relationships of oxide glasses. We focus on compression at temperatures at or around the glass transition temperature (Tg), with relevant comparisons made to glasses prepared by pressure quenching and cold compression. We show that permanent densification at 1 GPa sets-in at temperatures above 0.7Tg and the degree of densification increases with increasing compression temperature and time, until attaining an approximately constant value for temperatures above Tg. For glasses compressed at the same temperature/pressure conditions, we demonstrate direct relations between the degree of volume densification and the pressure-induced change in micro-mechanical properties such as hardness, elastic moduli, and extent of the indentation size effect across a variety of glass families. Furthermore, we summarize the results on relaxation behavior of hot compressed glasses. All the pressure-induced changes in the structure and properties exhibit strong composition dependence. The experimental results highlight new opportunities for future investigation and identify research challenges that need to be overcome to advance the field.

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.

Distributed Assimilation of Satellite-based Snow Extent for Improving Simulated Streamflow in Mountainous, Dense Forests: An Example Over the DMIP2 Western Basins

NASA Technical Reports Server (NTRS)

Yatheendradas, Soni; Peters-Lidard, Christa D.; Koren, Victor; Cosgrove, Brian A.; DeGoncalves, Luis G. D.; Smith, Michael; Geiger, James; Cui, Zhengtao; Borak, Jordan; Kumar, Sujay V.;

Consolidation and densification methods for fibrous monolith processing

DOEpatents

Sutaria, Manish P.; Rigali, Mark J.; Cipriani, Ronald A.; Artz, Gregory J.; Mulligan, Anthony C.

2006-06-20

Methods for consolidation and densification of fibrous monolith composite structures are provided. Consolidation and densification of two- and three-dimensional fibrous monolith components having complex geometries can be achieved by pressureless sintering. The fibrous monolith composites are formed from filaments having at least a first material composition generally surrounded by a second material composition. The composites are sintered at a pressure of no more than about 30 psi to provide consolidated and densified fibrous monolith composites.

Enhanced Densification of White Cast Iron Powders by Cyclic Phase Transformations under Stress.

DTIC Science & Technology

1981-08-01

Little or no significant enhancement in densification was reported in these cases where no applied stresses were used. Kohara [9) extended this work...enhancement of densification observed by Kohara , although limited, was attributed to the occurrence of transformation superplasticity. As will be shown... Kohara : Metall. Trans., 1976, vol. 7, p. 1239. 10. Y. Oshida, J. Jpn. Soc, Powder and Powder Metall., 1975, vol. 22, p. 147. 11. M. de Jong and G. W

Spatio-temporal dynamics of alpine snow algae measured with multi-year imaging spectrometer data

NASA Astrophysics Data System (ADS)

Painter, T.; Thomas, W. H.; Duval, B.

2003-04-01

The spatio-temporal dynamics of alpine snow algae have not been documented at the basin scale. This study focuses on the interannual variability of the concentration of alga chlamydomonas nivalis as mapped with the Airborne Visible Infrared Imaging Spectrometer (AVIRIS) over the Sierra Nevada, California, USA in the springs of 2000, 2001, and 2002. AVIRIS was flown at high spatial resolution (1.5 m) and medium spatial resolution (8 m) on board the NOAA Twin Otter and the NASA ER-2. AVIRIS data were atmospherically-corrected to apparent surface reflectance using a non-linear least squares vapor-fitting algorithm coupled with the atmospheric transmission MODTRAN4. We calculated algal concentration using a model that relates concentration to the continuum-normalized integral of the coupled chlorophyll-a, b absorption features with peak at 680 nm wavelength in the snow spectral reflectance signatures (Painter et al., 2001, Applied and Environmental Microbiology). The AVIRIS data were georeferenced to a digital elevation model of the Tioga Pass, CA region generated in the NASA Shuttle Radar Topography Mission. Interannual variability in basin-wide concentration and pixel-by-pixel concentration trajectories were evaluated.

Ultrasonic assisted hot metal powder compaction.

PubMed

Abedini, Rezvan; Abdullah, Amir; Alizadeh, Yunes

2017-09-01

Hot pressing of metal powders is used in production of parts with similar properties to wrought materials. During hot pressing processes, particle rearrangement, plastic deformation, creep, and diffusion are of the most effective powder densification mechanisms. Applying ultrasonic vibration is thought to result in great rates of densification and therefore higher efficiency of the process is expected. This paper deals with the effects of power ultrasonic on the densification of AA1100 aluminum powder under constant applied stress. The effects of particle size and process temperature on the densification behavior are discussed. The results show that applying ultrasonic vibration leads to an improved homogeneity and a higher relative density. Also, it is found that the effect of ultrasonic vibration is greater for finer particles. Copyright © 2016 Elsevier B.V. All rights reserved.

Gaseous Elemental Mercury (GEM) Emissions from Snow Surfaces in Northern New York

PubMed Central

Maxwell, J. Alexander; Holsen, Thomas M.; Mondal, Sumona

2013-01-01

Snow surface-to-air exchange of gaseous elemental mercury (GEM) was measured using a modified Teflon fluorinated ethylene propylene (FEP) dynamic flux chamber (DFC) in a remote, open site in Potsdam, New York. Sampling was conducted during the winter months of 2011. The inlet and outlet of the DFC were coupled with a Tekran Model 2537A mercury (Hg) vapor analyzer using a Tekran Model 1110 two port synchronized sampler. The surface GEM flux ranged from −4.47 ng m−2 hr−1 to 9.89 ng m−2 hr−1. For most sample periods, daytime GEM flux was strongly correlated with solar radiation. The average nighttime GEM flux was slightly negative and was not well correlated with any of the measured meteorological variables. Preliminary, empirical models were developed to estimate GEM emissions from snow surfaces in northern New York. These models suggest that most, if not all, of the Hg deposited with and to snow is reemitted to the atmosphere. PMID:23874951

Saharan dust particles in snow samples of Alps and Apennines during an exceptional event of transboundary air pollution.

PubMed

Telloli, Chiara; Chicca, Milvia; Pepi, Salvatore; Vaccaro, Carmela

2017-12-21

Southern European countries are often affected in summer by transboundary air pollution from Saharan dust. However, very few studies deal with Saharan dust pollution at high altitudes in winter. In Italy, the exceptional event occurred on February 19, 2014, colored in red the entire mountain range (Alps and Apennines) and allowed to characterize the particulate matter deposited on snow from a morphological and chemical point of view. Snow samples were collected after this event in four areas in the Alps and one in the Apennines. The particulate matter of the melted snow samples was analyzed by scanning electron microscopy with energy dispersive X-ray spectrometry (SEM-EDS) and by inductively coupled plasma mass spectrometry (ICP-MS). These analyses confirmed the presence of Saharan dust particle components in all areas with similar percentages, supported also by the positive correlations between Mg-Ca, Al-Ca, Al-Mg, and Al-K in all samples.

Tracing the origin of pollution in French Alpine snow and aerosols using lead isotopic ratios.

PubMed

Veysseyre, A M; Bollhöfer, A F; Rosman, K J; Ferrari, C P; Boutron, C F

2001-11-15

Fresh snow samples collected at 15 remote locations and aerosols collected at one location in the French Alps between November 1998 and April 1999 have been analyzed for Pb concentration and isotopic composition by thermal ionization mass spectrometry. The snow samples contained 19-1300 pg/g of Pb with isotopic ratios 206Pb/207Pb (208Pb/207Pb) of 1.1279-1.1607 (2.3983-2.4302). Airborne Pb concentrations at one sampling site ranged from 0.42 to 6.0 ng/m3 with isotopic ratios of 1.1321-1.1427 (2.4029-2.4160). Air mass trajectory analysis combined with isotopic compositions of potential source regions did not show discernible evidence of the long-range atmospheric transport of pollutants. Isotopic ratios in the Alpine snow samples and thus the free troposphere were generally higher than airborne Pb isotopic ratios in urban France, which coupled with the relatively high Pb concentrations suggested a regional anthropogenic Pb source, probably Italy but possibly Eastern Europe.

Gaseous elemental mercury (GEM) emissions from snow surfaces in northern New York.

PubMed

Maxwell, J Alexander; Holsen, Thomas M; Mondal, Sumona

2013-01-01

Snow surface-to-air exchange of gaseous elemental mercury (GEM) was measured using a modified Teflon fluorinated ethylene propylene (FEP) dynamic flux chamber (DFC) in a remote, open site in Potsdam, New York. Sampling was conducted during the winter months of 2011. The inlet and outlet of the DFC were coupled with a Tekran Model 2537A mercury (Hg) vapor analyzer using a Tekran Model 1110 two port synchronized sampler. The surface GEM flux ranged from -4.47 ng m(-2) hr(-1) to 9.89 ng m(-2) hr(-1). For most sample periods, daytime GEM flux was strongly correlated with solar radiation. The average nighttime GEM flux was slightly negative and was not well correlated with any of the measured meteorological variables. Preliminary, empirical models were developed to estimate GEM emissions from snow surfaces in northern New York. These models suggest that most, if not all, of the Hg deposited with and to snow is reemitted to the atmosphere.

Investigating the role of capacitive coupling between the operating table and the return electrode of an electrosurgery unit in the modification of the current density distribution within the patients' body.

PubMed

Bifulco, Paolo; Massa, Rita; Cesarelli, Mario; Romano, Maria; Fratini, Antonio; Gargiulo, Gaetano D; McEwan, Alistair L

2013-08-12

Electrosurgery units are widely employed in modern surgery. Advances in technology have enhanced the safety of these devices, nevertheless, accidental burns are still regularly reported. This study focuses on possible causes of sacral burns as complication of the use of electrosurgery. Burns are caused by local densifications of the current, but the actual pathway of current within patient's body is unknown. Numerical electromagnetic analysis can help in understanding the issue. To this aim, an accurate heterogeneous model of human body (including seventy-seven different tissues), electrosurgery electrodes, operating table and mattress was build to resemble a typical surgery condition. The patient lays supine on the mattress with the active electrode placed onto the thorax and the return electrode on his back. Common operating frequencies of electrosurgery units were considered. Finite Difference Time Domain electromagnetic analysis was carried out to compute the spatial distribution of current density within the patient's body. A differential analysis by changing the electrical properties of the operating table from a conductor to an insulator was also performed. Results revealed that distributed capacitive coupling between patient body and the conductive operating table offers an alternative path to the electrosurgery current. The patient's anatomy, the positioning and the different electromagnetic properties of tissues promote a densification of the current at the head and sacral region. In particular, high values of current density were located behind the sacral bone and beneath the skin. This did not occur in the case of non-conductive operating table. Results of the simulation highlight the role played from capacitive couplings between the return electrode and the conductive operating table. The concentration of current density may result in an undesired rise in temperature, originating burns in body region far from the electrodes. This outcome is concordant with the type of surgery-related sacral burns reported in literature. Such burns cannot be immediately detected after surgery, but appear later and can be confused with bedsores. In addition, the dosimetric analysis suggests that reducing the capacity coupling between the return electrode and the operating table can decrease or avoid this problem.

Integration, Validation, and Application of a PV Snow Coverage Model in SAM

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

Ryberg, David; Freeman, Janine

2015-09-01

Due to the increasing deployment of PV systems in snowy climates, there is significant interest in a method capable of estimating PV losses resulting from snow coverage that has been verified for a wide variety of system designs and locations. A scattering of independent snow coverage models have been developed over the last 15 years; however, there has been very little effort spent on verifying these models beyond the system design and location on which they were based. Moreover, none of the major PV modeling software products have incorporated any of these models into their workflow. In response to thismore » deficiency, we have integrated the methodology of the snow model developed in the paper by Marion et al. [1] into the National Renewable Energy Laboratory's (NREL) System Advisor Model (SAM). In this work we describe how the snow model is implemented in SAM and discuss our demonstration of the model's effectiveness at reducing error in annual estimations for two PV arrays. Following this, we use this new functionality in conjunction with a long term historical dataset to estimate average snow losses across the United States for a typical PV system design. The open availability of the snow loss estimation capability in SAM to the PV modeling community, coupled with our results of the nation-wide study, will better equip the industry to accurately estimate PV energy production in areas affected by snowfall.« less

Photochemical degradation of PCBs in snow.

PubMed

Matykiewiczová, Nina; Klánová, Jana; Klán, Petr

2007-12-15

This work represents the first laboratory study known to the authors describing photochemical behavior of persistent organic pollutants in snow at environmentally relevant concentrations. The snow samples were prepared by shock freezing of the corresponding aqueous solutions in liquid nitrogen and were UV-irradiated in a photochemical cold chamber reactor at -25 degrees C, in which simultaneous monitoring of snow-air exchange processeswas also possible. The main photodegradation pathway of two model snow contaminants, PCB-7 and PCB-153 (c approximately 100 ng kg(-1)), was found to be reductive dehalogenation. Possible involvement of the water molecules of snow in this reaction has been excluded by performing the photolyses in D2O snow. Instead, trace amounts of volatile organic compounds have been proposed to be the major source of hydrogen atom in the reduction, and this hypothesis was confirmed by the experiments with deuterated organic cocontaminants, such as d6-ethanol or d8-tetrahydrofuran. It is argued that bimolecular photoreduction of PCBs was more efficient or feasible than any other phototransformations under the experimental conditions used, including the coupling reactions. The photodegradation of PCBs, however, competed with a desorption process responsible for the pollutant loss from the snow samples, especially in case of lower molecular-mass congeners. Organic compounds, apparently largely located or photoproduced on the surface of snow crystals, had a predisposition to be released to the air but, at the same time, to react with other species in the gas phase. It is concluded that physicochemical properties of the contaminants and trace co-contaminants, their location and local concentrations in the matrix, and the wavelength and intensity of radiation are the most important factors in the evaluation of organic contaminants' lifetime in snow. Based on the results, it has been estimated that the average lifetime of PCBs in surface snow, connected exclusively to the photoreductive dechlorination process, is 1-2 orders of magnitude longer than that in surface waters when subjected to the equivalent solar radiation. However, in case that the concentration of the hydrogen peroxide in natural snow is sufficient, the photoinduced oxidation process could succeed the photoreductive dechlorination and evaporative fluxes as the major sink.

Assimilation of ground and satellite snow observations in a distributed hydrologic model to improve water supply forecasts in the Upper Colorado River Basin

NASA Astrophysics Data System (ADS)

Micheletty, P. D.; Day, G. N.; Quebbeman, J.; Carney, S.; Park, G. H.

2016-12-01

The Upper Colorado River Basin above Lake Powell is a major source of water supply for 25 million people and provides irrigation water for 3.5 million acres. Approximately 85% of the annual runoff is produced from snowmelt. Water supply forecasts of the April-July runoff produced by the National Weather Service (NWS) Colorado Basin River Forecast Center (CBRFC), are critical to basin water management. This project leverages advanced distributed models, datasets, and snow data assimilation techniques to improve operational water supply forecasts made by CBRFC in the Upper Colorado River Basin. The current work will specifically focus on improving water supply forecasts through the implementation of a snow data assimilation process coupled with the Hydrology Laboratory-Research Distributed Hydrologic Model (HL-RDHM). Three types of observations will be used in the snow data assimilation system: satellite Snow Covered Area (MODSCAG), satellite Dust Radiative Forcing in Snow (MODDRFS), and SNOTEL Snow Water Equivalent (SWE). SNOTEL SWE provides the main source of high elevation snowpack information during the snow season, however, these point measurement sites are carefully selected to provide consistent indices of snowpack, and may not be representative of the surrounding watershed. We address this problem by transforming the SWE observations to standardized deviates and interpolating the standardized deviates using a spatial regression model. The interpolation process will also take advantage of the MODIS Snow Covered Area and Grainsize (MODSCAG) product to inform the model on the spatial distribution of snow. The interpolated standardized deviates are back-transformed and used in an Ensemble Kalman Filter (EnKF) to update the model simulated SWE. The MODIS Dust Radiative Forcing in Snow (MODDRFS) product will be used more directly through temporary adjustments to model snowmelt parameters, which should improve melt estimates in areas affected by dust on snow. In order to assess the value of different data sources, reforecasts will be produced for a historical period and performance measures will be computed to assess forecast skill. The existing CBRFC Ensemble Streamflow Prediction (ESP) reforecasts will provide a baseline for comparison to determine the added-value of the data assimilation process.

Consolidation and densification methods for fibrous monolith processing

DOEpatents

Sutaria, Manish P.; Rigali, Mark J.; Cipriani, Ronald A.; Artz, Gregory J.; Mulligan, Anthony C.

2004-05-25

Methods for consolidation and densification of fibrous monolith composite structures are provided. Consolidation and densification of two- and three-dimensional fibrous monolith components having complex geometries can be achieved by pressureless sintering. The fibrous monolith composites are formed from filaments having at least a first material composition generally surrounded by a second material composition. The composites are sintered in an inert gas or nitrogen gas at a pressure of no more than about 30 psi to provide consolidated and densified fibrous monolith composites.

Numerical simulation of distributed snow processes in complex terrain utilizing triangulated irregular networks (TINs)

NASA Astrophysics Data System (ADS)

Rinehart, A. J.; Vivoni, E. R.

2005-12-01

Snow processes play a significant role in the hydrologic cycle of mountainous and high-latitude catchments in the western United States. Snowmelt runoff contributes to a large percentage of stream runoff while snow covered regions remain highly localized to small portions of the catchment area. The appropriate representation of snow dynamics at a given range of spatial and temporal scales is critical for adequately predicting runoff responses in snowmelt-dominated watersheds. In particular, the accurate depiction of snow cover patterns is important as a range of topographic, land-use and geographic parameters create zones of preferential snow accumulation or ablation that significantly affect the timing of a region's snow melt and the persistence of a snow pack. In this study, we present the development and testing of a distributed snow model designed for simulations over complex terrain. The snow model is developed within the context of the TIN-based Real-time Integrated Basin Simulator (tRIBS), a fully-distributed watershed model capable of continuous simulations of coupled hydrological processes, including unsaturated-saturated zone dynamics, land-atmosphere interactions and runoff generation via multiple mechanisms. The use of triangulated irregular networks as a domain discretization allows tRIBS to accurately represent topography with a reduced number of computational nodes, as compared to traditional grid-based models. This representation is developed using a Delauney optimization criterion that causes areas of topographic homogeneity to be represented at larger spatial scales than the original grid, while more heterogeneous areas are represented at higher resolutions. We utilize the TIN-based terrain representation to simulate microscale (10-m to 100-m) snow pack dynamics over a catchment. The model includes processes such as the snow pack energy balance, wind and bulk redistribution, and snow interception by vegetation. For this study, we present tests from a distributed one-layer energy balance model as applied to a northern New Mexico hillslope in a ponderosa pine forest using both synthetic and real meteorological forcing. We also provide tests of the model's capability to represent spatial patterns within a small watershed in the Jemez Mountain region. Finally, we discuss the interaction of the tested snow process module with existing components in the watershed model and additional applications and capabilities under development.

Hydrothermal Cold Sintering

NASA Astrophysics Data System (ADS)

Kang, Xiaoyu

Solid state sintering transforms particle compact to a physically robust and dense polycrystalline monolith driven by reduction of surface energy and curvature. Since bulk diffusion is required for neck formation and pore elimination, sintering temperature about 2/3 of melting point is needed. It thus places limitations for materials synthesis and integration, and contributes to significant energy consumption in ceramic processing. Furthermore, since surface transport requires lower temperature than bulk processes, grain growth is often rapid and can be undesired for physical properties. For these reasons, several techniques have been developed including Liquid Phase Sintering (LPS), Hot Pressing (HP) and Field Assisted Sintering Technique (FAST), which introduce either viscous melt, external pressure or electric field to speed up densification rates at lower temperature. However, because of their inherent reliability on bulk diffusion, temperatures required are often too high for integrating polymers and non-noble metals. Reduction of sintering temperature below 400 °C would require a different densification mechanism that is based on surface transport with external forces to drive volume shrinkage. Densification method combining uniaxial pressure and solution under hydrothermal condition was first demonstrated by Kanahara's group at Kochi University in 1986 and was brought to our attention by the work of Kahari, etc, from University of Oulu on densification of Li2MoO 4 in 2015. This relatively new process showed promising ultra-low densification temperature below 300 °C, however little was known about its fundamental mechanism and scope of applications, which became the main focus of this dissertation. In this work, a uniaxial hydraulic press, a standard stainless steel 1/2 inch diameter die with heating band were utilized in densifying metal oxides. Applied pressure and sintering temperature were between 100 MPa and 700 MPa and from room temperature to 300 °C, respectively. Process variables were defined and effects of individual parameters were studied systematically through control variable method with Li2MoO4-water system. Crystalline structure, fractured surface morphology and chemical bonding information of the cold sintered pellets were studied with X-ray diffraction (XRD), field effect scanning electron microscopy (FE-SEM) and Raman spectroscopy, etc. Densification mechanism studies were conducted on ZnO. Through comparison experiments, it was found that the Zn2+ concentration in the solution is critical for densification, while dissolution of grains only serves as a means to the former. Through pressure dependent studies, a critical value was found, which correlated well with the hydrostatic pressure keeping liquid water from thermal expansion. These results confirmed establishment of hydrothermal condition that would be important for mass transport in densification. Densification rate variations with process time was estimated and similar time dependence to Kingery's model was found. The densification process was proposed to be consist of three consecutive stages, which are quick initial compaction, grain rearrangement and dissolution-reprecipitation events. Binary metal oxides with different acidities were subjected to cold sintering with various aqueous solutions in establishing a criteria for material selection. It was found that in general materials with high solubility at around neutral pH, high dissolution kinetics and similar free energy to their hydroxides or hydrates at ambient would be more likely for full densification with high phase purity. The anions in solution should also be wisely selected to avoid stable compound or complex formation. To extend the applicable material list for full densification, non-aqueous solvent of dimethyl sulfoxide (DMSO) based solution was studied for cold sintering. Both improvement of pellet density and suppression of hydroxide formation were achieved for MnO by using DMSO-HOAc solution. With this strategy, densification of other metal oxides with strong hydroxide formation may also be improved, for example oxides of alkaline earth and many transition metals. Finally, the author's previous work on Zn1-xMg xO thin films is included in Chapter 7.

A spatially distributed energy balance snowmelt model for application in mountain basins

USGS Publications Warehouse

Marks, D.; Domingo, J.; Susong, D.; Link, T.; Garen, D.

1999-01-01

Snowmelt is the principal source for soil moisture, ground-water re-charge, and stream-flow in mountainous regions of the western US, Canada, and other similar regions of the world. Information on the timing, magnitude, and contributing area of melt under variable or changing climate conditions is required for successful water and resource management. A coupled energy and mass-balance model ISNOBAL is used to simulate the development and melting of the seasonal snowcover in several mountain basins in California, Idaho, and Utah. Simulations are done over basins varying from 1 to 2500 km2, with simulation periods varying from a few days for the smallest basin, Emerald Lake watershed in California, to multiple snow seasons for the Park City area in Utah. The model is driven by topographically corrected estimates of radiation, temperature, humidity, wind, and precipitation. Simulation results in all basins closely match independently measured snow water equivalent, snow depth, or runoff during both the development and depletion of the snowcover. Spatially distributed estimates of snow deposition and melt allow us to better understand the interaction between topographic structure, climate, and moisture availability in mountain basins of the western US. Application of topographically distributed models such as this will lead to improved water resource and watershed management.Snowmelt is the principal source for soil moisture, ground-water re-charge, and stream-flow in mountainous regions of the western US, Canada, and other similar regions of the world. Information on the timing, magnitude, and contributing area of melt under variable or changing climate conditions is required for successful water and resource management. A coupled energy and mass-balance model ISNOBAL is used to simulate the development and melting of the seasonal snowcover in several mountain basins in California, Idaho, and Utah. Simulations are done over basins varying from 1 to 2500 km2, with simulation periods varying from a few days for the smallest basin, Emerald Lake watershed in California, to multiple snow seasons for the Park City area in Utah. The model is driven by topographically corrected estimates of radiation, temperature, humidity, wind, and precipitation. Simulation results in all basins closely match independently measured snow water equivalent, snow depth, or runoff during both the development and depletion of the snowcover. Spatially distributed estimates of snow deposition and melt allow us to better understand the interaction between topographic structure, climate, and moisture availability in mountain basins of the western US. Application of topographically distributed models such as this will lead to improved water resource and watershed management.

IceChrono v1: a probabilistic model to compute a common and optimal chronology for several ice cores

NASA Astrophysics Data System (ADS)

Parrenin, Frédéric

2015-04-01

Polar ice cores provide exceptional archives of past environmental conditions. The dating of ice cores is essential to interpret the paleo records that they contain, but it is a complicated problem since it involves different dating methods. Here I present IceChrono v1, a new probabilistic model to combine different kinds of chronological information to obtain a common and optimized chronology for several ice cores, as well as its uncertainty. It is based on the inversion of three quantities: the surface accumulation rate, the Lock-In Depth (LID) of air bubbles and the vertical thinning function. The chronological information used are: models of the sedimentation process (accumulation of snow, densification of snow into ice and air trapping, ice flow), ice and gas dated horizons, ice and gas dated depth intervals, Δdepth observations (depth shift between synchronous events recorded in the ice and in the air), stratigraphic links in between ice cores (ice-ice, air-air or mix ice-air and air-ice links). The optimization problem is formulated as a least squares problems, that is, all densities of probabilities are assumed gaussian. It is numerically solved using the Levenberg-Marquardt algorithm and a numerical evaluation of the model's Jacobian. IceChrono is similar in scope to the Datice model, but has differences from the mathematical, numerical and programming point of views. I apply IceChrono on an AICC2012-like experiment and I find similar results than Datice within a few centuries, which is a confirmation of both IceChrono and Datice codes. IceChrono v1 is freely available under the GPL v3 open source license.

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.

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.

Coupled long-term summer warming and deeper snow alters species composition and stimulates gross primary productivity in tussock tundra.

PubMed

Leffler, A Joshua; Klein, Eric S; Oberbauer, Steven F; Welker, Jeffrey M

2016-05-01

Climate change is expected to increase summer temperature and winter precipitation throughout the Arctic. The long-term implications of these changes for plant species composition, plant function, and ecosystem processes are difficult to predict. We report on the influence of enhanced snow depth and warmer summer temperature following 20 years of an ITEX experimental manipulation at Toolik Lake, Alaska. Winter snow depth was increased using snow fences and warming was accomplished during summer using passive open-top chambers. One of the most important consequences of these experimental treatments was an increase in active layer depth and rate of thaw, which has led to deeper drainage and lower soil moisture content. Vegetation concomitantly shifted from a relatively wet system with high cover of the sedge Eriophorum vaginatum to a drier system, dominated by deciduous shrubs including Betula nana and Salix pulchra. At the individual plant level, we observed higher leaf nitrogen concentration associated with warmer temperatures and increased snow in S. pulchra and B. nana, but high leaf nitrogen concentration did not lead to higher rates of net photosynthesis. At the ecosystem level, we observed higher GPP and NEE in response to summer warming. Our results suggest that deeper snow has a cascading set of biophysical consequences that include a deeper active layer that leads to altered species composition, greater leaf nitrogen concentration, and higher ecosystem-level carbon uptake.

The Dominant Snow-forming Process in Warm and Cold Mixed-phase Orographic Clouds: Effects of Cloud Condensation Nuclei and Ice Nuclei

NASA Astrophysics Data System (ADS)

Fan, J.; Rosenfeld, D.; Leung, L. R.; DeMott, P. J.

2014-12-01

Mineral dust aerosols often observed over California in winter and spring from long-range transport can be efficient ice nuclei (IN) and enhance snow precipitation in mixed-phase orographic clouds. On the other hand, local pollution particles can serve as good CCN and suppress warm rain, but their impacts on cold rain processes are uncertain. The main snow-forming mechanism in warm and cold mixed-phase orographic clouds (refer to as WMOC and CMOC, respectively) could be very different, leading to different precipitation response to CCN and IN. We have conducted 1-km resolution model simulations using the Weather Research and Forecasting (WRF) model coupled with a spectral-bin cloud microphysical model for WMOC and CMOC cases from CalWater2011. We investigated the response of cloud microphysical processes and precipitation to CCN and IN with extremely low to extremely high concentrations using ice nucleation parameterizations that connect with dust and implemented based on observational evidences. We find that riming is the dominant process for producing snow in WMOC while deposition plays a more important role than riming in CMOC. Increasing IN leads to much more snow precipitation mainly due to an increase of deposition in CMOC and increased rimming in WMOC. Increasing CCN decreases precipitation in WMOC by efficiently suppressing warm rain, although snow is increased. In CMOC where cold rain dominates, increasing CCN significantly increases snow, leading to a net increase in precipitation. The sensitivity of supercooled liquid to CCN and IN has also been analyzed. The mechanism for the increased snow by CCN and caveats due to uncertainties in ice nucleation parameterizations will be discussed.

Regional sensitivities of seasonal snowpack to elevation, aspect, and vegetation cover in western North America

NASA Astrophysics Data System (ADS)

Tennant, Christopher J.; Harpold, Adrian A.; Lohse, Kathleen Ann; Godsey, Sarah E.; Crosby, Benjamin T.; Larsen, Laurel G.; Brooks, Paul D.; Van Kirk, Robert W.; Glenn, Nancy F.

2017-08-01

In mountains with seasonal snow cover, the effects of climate change on snowpack will be constrained by landscape-vegetation interactions with the atmosphere. Airborne lidar surveys used to estimate snow depth, topography, and vegetation were coupled with reanalysis climate products to quantify these interactions and to highlight potential snowpack sensitivities to climate and vegetation change across the western U.S. at Rocky Mountain (RM), Northern Basin and Range (NBR), and Sierra Nevada (SNV) sites. In forest and shrub areas, elevation captured the greatest amount of variability in snow depth (16-79%) but aspect explained more variability (11-40%) in alpine areas. Aspect was most important at RM sites where incoming shortwave to incoming net radiation (SW:NetR↓) was highest (˜0.5), capturing 17-37% of snow depth variability in forests and 32-37% in shrub areas. Forest vegetation height exhibited negative relationships with snow depth and explained 3-6% of its variability at sites with greater longwave inputs (NBR and SNV). Variability in the importance of physiography suggests differential sensitivities of snowpack to climate and vegetation change. The high SW:NetR↓ and importance of aspect suggests RM sites may be more responsive to decreases in SW:NetR↓ driven by warming or increases in humidity or cloud cover. Reduced canopy-cover could increase snow depths at SNV sites, and NBR and SNV sites are currently more sensitive to shifts from snow to rain. The consistent importance of aspect and elevation indicates that changes in SW:NetR↓ and the elevation of the rain/snow transition zone could have widespread and varied effects on western U.S. snowpacks.

A Coupled Snow Operations-Skier Demand Model for the Ontario (Canada) Ski Region

NASA Astrophysics Data System (ADS)

Pons, Marc; Scott, Daniel; Steiger, Robert; Rutty, Michelle; Johnson, Peter; Vilella, Marc

2016-04-01

The multi-billion dollar global ski industry is one of the tourism subsectors most directly impacted by climate variability and change. In the decades ahead, the scholarly literature consistently projects decreased reliability of natural snow cover, shortened and more variable ski seasons, as well as increased reliance on snowmaking with associated increases in operational costs. In order to develop the coupled snow, ski operations and demand model for the Ontario ski region (which represents approximately 18% of Canada's ski market), the research utilized multiple methods, including: a in situ survey of over 2400 skiers, daily operations data from ski resorts over the last 10 years, climate station data (1981-2013), climate change scenario ensemble (AR5 - RCP 8.5), an updated SkiSim model (building on Scott et al. 2003; Steiger 2010), and an agent-based model (building on Pons et al. 2014). Daily snow and ski operations for all ski areas in southern Ontario were modeled with the updated SkiSim model, which utilized current differential snowmaking capacity of individual resorts, as determined from daily ski area operations data. Snowmaking capacities and decision rules were informed by interviews with ski area managers and daily operations data. Model outputs were validated with local climate station and ski operations data. The coupled SkiSim-ABM model was run with historical weather data for seasons representative of an average winter for the 1981-2010 period, as well as an anomalously cold winter (2012-13) and the record warm winter in the region (2011-12). The impact on total skier visits and revenues, and the geographic and temporal distribution of skier visits were compared. The implications of further climate adaptation (i.e., improving the snowmaking capacity of all ski areas to the level of leading resorts in the region) were also explored. This research advances system modelling, especially improving the integration of snow and ski operations models with demand and socioeconomic implications. This innovative integrated systems model approach can be exported to other major ski tourism markets (e.g., Canada, USA, Western and Eastern Europe, Australia, Japan) to facilitate global comparative assessments of ski tourism vulnerability to climate change, establishing the standard for ski tourism vulnerability assessments and advancing scholarly work on sustainable tourism and climate-compatible development in mountain communities.

Observed high-altitude warming and snow cover retreat over Tibet and the Himalayas enhanced by black carbon aerosols

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

Xu, Y.; Ramanathan, V.; Washington, W. M.

Himalayan mountain glaciers and the snowpack over the Tibetan Plateau provide the headwater of several major rivers in Asia. In situ observations of snow cover extent since the 1960s suggest that the snowpack in the region have retreated significantly, accompanied by a surface warming of 2–2.5°C observed over the peak altitudes (5000 m). Using a high-resolution ocean–atmosphere global climate model and an observationally constrained black carbon (BC) aerosol forcing, we attribute the observed altitude dependence of the warming trends as well as the spatial pattern of reductions in snow depths and snow cover extent to various anthropogenic factors. At themore » Tibetan Plateau altitudes, the increase in atmospheric CO 2 concentration exerted a warming of 1.7°C, BC 1.3°C where as cooling aerosols cause about 0.7°C cooling, bringing the net simulated warming consistent with the anomalously large observed warming. We therefore conclude that BC together with CO 2 has contributed to the snow retreat trends. In particular, BC increase is the major factor in the strong elevation dependence of the observed surface warming. The atmospheric warming by BC as well as its surface darkening of snow is coupled with the positive snow albedo feedbacks to account for the disproportionately large role of BC in high-elevation regions. Here, these findings reveal that BC impact needs to be properly accounted for in future regional climate projections, in particular on high-altitude cryosphere.« less

Observed high-altitude warming and snow cover retreat over Tibet and the Himalayas enhanced by black carbon aerosols

DOE PAGES

Xu, Y.; Ramanathan, V.; Washington, W. M.

2016-02-05

Himalayan mountain glaciers and the snowpack over the Tibetan Plateau provide the headwater of several major rivers in Asia. In situ observations of snow cover extent since the 1960s suggest that the snowpack in the region have retreated significantly, accompanied by a surface warming of 2–2.5°C observed over the peak altitudes (5000 m). Using a high-resolution ocean–atmosphere global climate model and an observationally constrained black carbon (BC) aerosol forcing, we attribute the observed altitude dependence of the warming trends as well as the spatial pattern of reductions in snow depths and snow cover extent to various anthropogenic factors. At themore » Tibetan Plateau altitudes, the increase in atmospheric CO 2 concentration exerted a warming of 1.7°C, BC 1.3°C where as cooling aerosols cause about 0.7°C cooling, bringing the net simulated warming consistent with the anomalously large observed warming. We therefore conclude that BC together with CO 2 has contributed to the snow retreat trends. In particular, BC increase is the major factor in the strong elevation dependence of the observed surface warming. The atmospheric warming by BC as well as its surface darkening of snow is coupled with the positive snow albedo feedbacks to account for the disproportionately large role of BC in high-elevation regions. Here, these findings reveal that BC impact needs to be properly accounted for in future regional climate projections, in particular on high-altitude cryosphere.« less

Effects of torrefaction and densification on switchgrass pyrolysis products

DOE PAGES

Yang, Zixu; Sarkar, Madhura; Kumar, Ajay; ...

2014-12-01

Abstract The pyrolysis behaviors of four types of pretreated switchgrass (torrefied at 230 and 270 °C, densification, and torrefaction at 270 ºC followed by densification) were studied at three temperatures (500, 600, 700 ºC) using a pyroprobe attached to a gas chromatogram mass spectroscopy (Py-GC/MS). The torrefaction of switchgrass improved its oxygen to carbon ratio and energy content. Contents of anhydrous sugars and phenols in pyrolysis products of torrefied switchgrass were higher than those in pyrolysis products of raw switchgrass. As the torrefaction temperature increased from 230 to 270 °C, the contents of anhydrous sugars and phenols in pyrolysis productsmore » increased whereas content of guaiacols decreased. High pyrolysis temperature (600 and 700 °C as compared to 500 °C) enhanced decomposition of lignin and anhydrous sugars, leading to increase in phenols, aromatics and furans. Densification enhanced depolymerization of cellulose and hemicellulose during pyrolysis.« less

Relationship between the trajectory of mid-latitude cyclones in the eastern Pacific Ocean and the isotopic composition of snowfall in the Sierra Nevada, California

NASA Astrophysics Data System (ADS)

Vasquez, K. T.; Sickman, J. O.; Heard, A.; Lucero, D.

2013-12-01

Diatoms, preserved in lake sediments, provide a potential archive of snowfall variability in the Sierra Nevada through their sensitivity to changes in water chemistry (a proxy for runoff volume) and by recording the isotopic composition of snow-melt (potentially a proxy for sources of atmospheric moisture). In the Sierra Nevada, we hypothesize that the oxygen isotopic composition of diatom silica is principally controlled by snow and that the isotopic composition of snow varies as a function of the tracks of mid-latitude cyclonic storms in the eastern Pacific Ocean. Snow samples from discrete storms were collected from December 2012 to March 2013 at 2042 meters a.s.l. in Sequoia National Park. The δ18O and δ2H values of the snow samples were measured using a temperature-conversion elemental analyzer coupled to a Delta V isotope ratio mass spectrometer. The isotopic measurements were then coupled to 3, 5 and 7-day air mass back trajectories using the NOAA HYSPLIT model. The measured δ18O values ranged from -17.6 to -7.8 per mil and the δ2H ranged from -119.8 to -73.3 per mil. Both δ18O and δ2H were inversely related to the latitude of the storm origin (R^2 values of 0.67 and 0.57, respectively). Winter storms from the Gulf of Alaska were the most isotopically depleted while storms originating in the subtropical/tropical Pacific were the most isotopically enriched, reflecting the overall latitudinal pattern of ocean-water isotope composition in the Pacific Ocean. Our results suggest that the isotopic composition of Sierra Nevada snowfall is influenced by storm track trajectory and this relationship could be useful in interpreting the climatic significance of δ18O of diatom silica preserved in lake cores.

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.

A multiphysical ensemble system of numerical snow modelling

NASA Astrophysics Data System (ADS)

Lafaysse, Matthieu; Cluzet, Bertrand; Dumont, Marie; Lejeune, Yves; Vionnet, Vincent; Morin, Samuel

2017-05-01

Physically based multilayer snowpack models suffer from various modelling errors. To represent these errors, we built the new multiphysical ensemble system ESCROC (Ensemble System Crocus) by implementing new representations of different physical processes in the deterministic coupled multilayer ground/snowpack model SURFEX/ISBA/Crocus. This ensemble was driven and evaluated at Col de Porte (1325 m a.s.l., French alps) over 18 years with a high-quality meteorological and snow data set. A total number of 7776 simulations were evaluated separately, accounting for the uncertainties of evaluation data. The ability of the ensemble to capture the uncertainty associated to modelling errors is assessed for snow depth, snow water equivalent, bulk density, albedo and surface temperature. Different sub-ensembles of the ESCROC system were studied with probabilistic tools to compare their performance. Results show that optimal members of the ESCROC system are able to explain more than half of the total simulation errors. Integrating members with biases exceeding the range corresponding to observational uncertainty is necessary to obtain an optimal dispersion, but this issue can also be a consequence of the fact that meteorological forcing uncertainties were not accounted for. The ESCROC system promises the integration of numerical snow-modelling errors in ensemble forecasting and ensemble assimilation systems in support of avalanche hazard forecasting and other snowpack-modelling applications.

Impacts of 1, 1.5, and 2 Degree Warming on Arctic Terrestrial Snow and Sea Ice

NASA Astrophysics Data System (ADS)

Derksen, C.; Mudryk, L.; Howell, S.; Flato, G. M.; Fyfe, J. C.; Gillett, N. P.; Sigmond, M.; Kushner, P. J.; Dawson, J.; Zwiers, F. W.; Lemmen, D.; Duguay, C. R.; Zhang, X.; Fletcher, C. G.; Dery, S. J.

2017-12-01

The 2015 Paris Agreement of the United Nations Framework Convention on Climate Change (UNFCCC) established the global temperature goal of "holding the increase in the global average temperature to below 2°C above pre-industrial levels and pursuing efforts to limit the temperature increase to 1.5°C above pre-industrial levels." In this study, we utilize multiple gridded snow and sea ice products (satellite retrievals; assimilation systems; physical models driven by reanalyses) and ensembles of climate model simulations to determine the impacts of observed warming, and project the relative impacts of the UNFCC future warming targets on Arctic seasonal terrestrial snow and sea ice cover. Observed changes during the satellite era represent the response to approximately 1°C of global warming. Consistent with other studies, analysis of the observational record (1970's to present) identifies changes including a shorter snow cover duration (due to later snow onset and earlier snow melt), significant reductions in spring snow cover and summer sea ice extent, and the loss of a large proportion of multi-year sea ice. The spatial patterns of observed snow and sea ice loss are coherent across adjacent terrestrial/marine regions. There are strong pattern correlations between snow and temperature trends, with weaker association between sea ice and temperature due to the additional influence of dynamical effects such wind-driven redistribution of sea ice. Climate model simulations from the Coupled Model Inter-comparison Project Phase 5(CMIP-5) multi-model ensemble, large initial condition ensembles of the Community Earth System Model (CESM) and Canadian Earth System Model (CanESM2) , and warming stabilization simulations from CESM were used to identify changes in snow and ice under further increases to 1.5°C and 2°C warming. The model projections indicate these levels of warming will be reached over the coming 2-4 decades. Warming to 1.5°C results in an increase in the number of melting days over snow and sea ice (and resultant increases in snow-free and ice-free duration), which are similar in magnitude to the change from pre-industrial conditions to present day. Continued warming to 2°C further intensifies the cryospheric response consistent with amplified Arctic warming relative to the global average trend.

Determining Greenland Ice Sheet Accumulation Rates from Radar Remote Sensing

NASA Technical Reports Server (NTRS)

Jezek, Kenneth C.

2001-01-01

An important component of NASA's Program for Arctic Regional Climate Assessment (PARCA) is a mass balance investigation of the Greenland Ice Sheet. The mass balance is calculated by taking the difference between the snow accumulation and the ice discharge of the ice sheet. Uncertainties in this calculation include the snow accumulation rate, which has traditionally been determined by interpolating data from ice core samples taken throughout the ice sheet. The sparse data associated with ice cores, coupled with the high spatial and temporal resolution provided by remote sensing, have motivated scientists to investigate relationships between accumulation rate and microwave observations.

Performance Tests of a Liquid Hydrogen Propellant Densification Ground System for the X33/RLV

NASA Technical Reports Server (NTRS)

Tomsik, Thomas M.

1997-01-01

A concept for improving the performance of propulsion systems in expendable and single-stage-to-orbit (SSTO) launch vehicles much like the X33/RLV has been identified. The approach is to utilize densified cryogenic liquid hydrogen (LH2) and liquid oxygen (LOX) propellants to fuel the propulsion stage. The primary benefit for using this relatively high specific impulse densified propellant mixture is the subsequent reduction of the launch vehicle gross lift-off weight. Production of densified propellants however requires specialized equipment to actively subcool both the liquid oxygen and liquid hydrogen to temperatures below their normal boiling point. A propellant densification unit based on an external thermodynamic vent principle which operates at subatmospheric pressure and supercold temperatures provides a means for the LH2 and LOX densification process to occur. To demonstrate the production concept for the densification of the liquid hydrogen propellant, a system comprised of a multistage gaseous hydrogen compressor, LH2 recirculation pumps and a cryogenic LH2 heat exchanger was designed, built and tested at the NASA Lewis Research Center (LeRC). This paper presents the design configuration of the LH2 propellant densification production hardware, analytical details and results of performance testing conducted with the hydrogen densifier Ground Support Equipment (GSE).

Assessment of densification and mechanical property of AISI 8630 steel composition on different heat treatments produced through hot upsetting powder preform forging

NASA Astrophysics Data System (ADS)

Bala, Y. G.; Sankaranarayanan, S. Raman; Pandey, K. S.

2015-11-01

The present investigation was carried out to evaluate the densification, mechanical properties, microstructural and fractrography effects of AISI 8630 steel composition developed through powder preform forging under different heat treated conditions. Sintered preforms of different aspect ratios such as 0.6, 0.9, and 1.2 were hot upset forged to disc shape to different height strain to analysis the densification mechanism. Certain relationships relating strains, Poisson's ratio relating densification have revealed the effect of preform geometry on densification kinetics and resulted in the polynomial expression with justified regression coefficient greater the 0.9 or unity. The preforms of aspect ratio of 1.1 were hot upset forged to square cross section bars and transferred to different quenching medium like oil, water, furnace and air to assess its mechanical properties. Comparing the temperament of the heat treatments, sintered forged homogenised water quenched sample upshot in the maximum Tensile strength with least per centage elongation andthe furnace cooled sample shows the maximum toughness with desirable per centage elongation and least tensile strength. Microstructure stated the presence of varying ferrite and pearlite distribution and fractograph studies has disclosed the mixed mode of failure on the effect of varying heat treatments progression has affected the properties significantly.

Development of Macroscale Models of UO 2 Fuel Sintering and Densification using Multiscale Modeling and Simulation

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

Greenquist, Ian; Tonks, Michael

2016-10-01

Light water reactor fuel pellets are fabricated using sintering to final densities of 95% or greater. During reactor operation, the porosity remaining in the fuel after fabrication decreases further due to irradiation-assisted densification. While empirical models have been developed to describe this densification process, a mechanistic model is needed as part of the ongoing work by the NEAMS program to develop a more predictive fuel performance code. In this work we will develop a phase field model of sintering of UO 2 in the MARMOT code, and validate it by comparing to published sintering data. We will then add themore » capability to capture irradiation effects into the model, and use it to develop a mechanistic model of densification that will go into the BISON code and add another essential piece to the microstructure-based materials models. The final step will be to add the effects of applied fields, to model field-assisted sintering of UO 2. The results of the phase field model will be validated by comparing to data from field-assisted sintering. Tasks over three years: 1. Develop a sintering model for UO 2 in MARMOT 2. Expand model to account for irradiation effects 3. Develop a mechanistic macroscale model of densification for BISON« less

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

Elemental carbon (EC) and light absorbing organic carbon (OC) are important particulate impurities in snow and ice which significantly reduce the albedo of glaciers and accelerate their melting. Snow and ice samples were collected from Karakorum-Himalayan region of North Pakistan during the summer campaign (May-Jun) 2015 and only snow samples were collected during winter (Dec 2015- Jan 2016). Total 41 surface snow/ice samples were collected during summer campaign along different elevation ranges (2569 to 3895 a.m.s.l) from six glaciers: Sachin, Henarche, Barpu, Mear, Gulkin and Passu. Similarly 18 snow samples were collected from Sust, Hoper, Tawas, Astore, Shangla, and Kalam regions during the winter campaign. Quartz filters were used for filtering of melted snow and ice samples which were then analyzed by thermal optical reflectance (TOR) method to determine the concentration of EC and OC. The average concentration of EC (ng/g), OC (ng/g) and dust (ppm) were found as follows: Passu (249.5, 536.8, 475), Barpu (1190, 397.6, 1288), Gulkin (412, 793, 761), Sachin (911, 2130, 358), Mear (678, 2067, 83) and Henarche (755, 1868, 241) respectively during summer campaign. Similarly, average concentration of EC (ng/g), OC (ng/g) and dust (ppm) was found in the samples of Sust (2506, 1039, 131), Hoper (646, 1153, 76), Tawas (650, 1320, 16), Astore (1305, 2161, 97), Shangla (739, 2079, 31) and Kalam (107, 347, 5) respectively during winter campaign. Two methods were adopted to identify the source regions: one coupled emissions inventory with back trajectories, second with a simple region tagged chemical transport modeling analysis. In addition, CALIPSO subtype aerosol composition indicated that frequency of smoke in the atmosphere over the region was highest followed by dust and then polluted dust. SNICAR model was used to estimate the snow albedo reduction from our in-situ measurements. Snow albedo reduction was observed to be 0.3% to 27.6%. The derived results were used with SBDART clear sky solar fluxes to calculate the radiative forcing (RF). The RF values were observed to in the range of 0.43 to 36.75 W/m2 depending upon location.

Monitoring of the Liquid Water Content During Snowmelt Using C-Band SAR Data and the Snow Model CROCUS

NASA Astrophysics Data System (ADS)

Rondeau-Genesse, G.; Trudel, M.; Leconte, R.

2014-12-01

Coupling C-Band synthetic aperture radar (SAR) data to a multilayer snow model is a step in better understanding the temporal evolution of the radar backscattering coefficient during snowmelt. The watershed used for this study is the Nechako River Basin, located in the Rocky Mountains of British-Columbia (Canada). This basin has a snowpack of several meters in depth and part of its water is diverted to the Kemano hydropower system, managed by Rio-Tinto Alcan. Eighteen RADARSAT-2 ScanSAR Wide archive images were acquired in VV/VH polarization for the winter of 2011-2012, under different snow conditions. They are interpreted along with CROCUS, a multilayer physically-based snow model developed by Météo-France. This model discretizes the snowpack into 50 layers, which makes it possible to monitor various characteristics, such as liquid water content (LWC), throughout the season. CROCUS is used to model three specific locations of the Nechako River Basin. Results vary from one site to another, but in general there is a good agreement between the modeled LWC of the first layer of the snowpack and the backscattering coefficient of the RADARSAT-2 images, with a coefficient of determination (R²) of 0.80 and more. The radar images themselves were processed using an updated version of Nagler's methodology, which consists of subtracting an image in wet snow conditions to one in dry snow conditions, as wet snow can then be identified using a soft threshold centered around -3 dB. A second filter was used in order to differentiate dry snow and bare soil. That filter combines a VH/VV ratio threshold and an altitude criterion. The ensuing maps show a good agreement with the MODIS snow-covered area, which is already obtained daily over the Nechako River Basin, but with additional information on the location of wet snow and without sensibility to cloud cover. As a next step, the outputs of CROCUS will be used in Mätzler's Microwave Emission Model of Layered Snowpacks (MEMLS) to simulate the backscattering coefficient at different locations in the basin.

Enhancing the ABAQUS Thermomechanics Code to Simulate Steady and Transient Fuel Rod Behavior

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

R. L. Williamson; D. A. Knoll

2009-09-01

A powerful multidimensional fuels performance capability, applicable to both steady and transient fuel behavior, is developed based on enhancements to the commercially available ABAQUS general-purpose thermomechanics code. Enhanced capabilities are described, including: UO2 temperature and burnup dependent thermal properties, solid and gaseous fission product swelling, fuel densification, fission gas release, cladding thermal and irradiation creep, cladding irradiation growth , gap heat transfer, and gap/plenum gas behavior during irradiation. The various modeling capabilities are demonstrated using a 2D axisymmetric analysis of the upper section of a simplified multi-pellet fuel rod, during both steady and transient operation. Computational results demonstrate the importancemore » of a multidimensional fully-coupled thermomechanics treatment. Interestingly, many of the inherent deficiencies in existing fuel performance codes (e.g., 1D thermomechanics, loose thermo-mechanical coupling, separate steady and transient analysis, cumbersome pre- and post-processing) are, in fact, ABAQUS strengths.« less

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.

Analysis of MODIS snow cover time series over the alpine regions as input for hydrological modeling

NASA Astrophysics Data System (ADS)

Notarnicola, Claudia; Rastner, Philipp; Irsara, Luca; Moelg, Nico; Bertoldi, Giacomo; Dalla Chiesa, Stefano; Endrizzi, Stefano; Zebisch, Marc

2010-05-01

Snow extent and relative physical properties are key parameters in hydrology, weather forecast and hazard warning as well as in climatological models. Satellite sensors offer a unique advantage in monitoring snow cover due to their temporal and spatial synoptic view. The Moderate Resolution Imaging Spectrometer (MODIS) from NASA is especially useful for this purpose due to its high frequency. However, in order to evaluate the role of snow on the water cycle of a catchment such as runoff generation due to snowmelt, remote sensing data need to be assimilated in hydrological models. This study presents a comparison on a multi-temporal basis between snow cover data derived from (1) MODIS images, (2) LANDSAT images, and (3) predictions by the hydrological model GEOtop [1,3]. The test area is located in the catchment of the Matscher Valley (South Tyrol, Northern Italy). The snow cover maps derived from MODIS-images are obtained using a newly developed algorithm taking into account the specific requirements of mountain regions with a focus on the Alps [2]. This algorithm requires the standard MODIS-products MOD09 and MOD02 as input data and generates snow cover maps at a spatial resolution of 250 m. The final output is a combination of MODIS AQUA and MODIS TERRA snow cover maps, thus reducing the presence of cloudy pixels and no-data-values due to topography. By using these maps, daily time series starting from the winter season (November - May) 2002 till 2008/2009 have been created. Along with snow maps from MODIS images, also some snow cover maps derived from LANDSAT images have been used. Due to their high resolution (< 30 m) they have been considered as an evaluation tool. The snow cover maps are then compared with the hydrological GEOtop model outputs. The main objectives of this work are: 1. Evaluation of the MODIS snow cover algorithm using LANDSAT data 2. Investigation of snow cover, and snow cover duration for the area of interest for South Tyrol 3. Derivation and interpretation of the snow line for the seven winter seasons 4. An evaluation of the model outputs in order to determine the situations in which the remotely sensed data can be used to improve the model prediction of snow coverage and related variables References [1] Rigon R., Bertoldi G. and Over T.M. 2006. GEOtop: A Distributed Hydrological Model with Coupled Water and Energy Budgets, Journal of Hydrometeorology, 7: 371-388. [2] Rastner P., Irsara L., Schellenberger T., Della Chiesa S., Bertoldi G., Endrizzi S., Notarnicola C., Steurer C., Zebisch M. 2009. Monitoraggio del manto nevoso in aree alpine con dati MODIS multi-temporali e modelli idrologici, 13th ASITA National Conference, 1-4.12.2009, Bari, Italy. [3] Zanotti F., Endrizzi S., Bertoldi G. and Rigon R. 2004. The GEOtop snow module. Hydrological Processes, 18: 3667-3679. DOI:10.1002/hyp.5794.

Uncertainty, Sensitivity Analysis, and Causal Identification in the Arctic using a Perturbed Parameter Ensemble of the HiLAT Climate Model

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

Hunke, Elizabeth Clare; Urrego Blanco, Jorge Rolando; Urban, Nathan Mark

Coupled climate models have a large number of input parameters that can affect output uncertainty. We conducted a sensitivity analysis of sea ice proper:es and Arc:c related climate variables to 5 parameters in the HiLAT climate model: air-ocean turbulent exchange parameter (C), conversion of water vapor to clouds (cldfrc_rhminl) and of ice crystals to snow (micro_mg_dcs), snow thermal conduc:vity (ksno), and maximum snow grain size (rsnw_mlt). We used an elementary effect (EE) approach to rank their importance for output uncertainty. EE is an extension of one-at-a-time sensitivity analyses, but it is more efficient in sampling multi-dimensional parameter spaces. We lookedmore » for emerging relationships among climate variables across the model ensemble, and used causal discovery algorithms to establish potential pathways for those relationships.« less

Seismic signals of snow-slurry lahars in motion: 25 September 2007, Mt Ruapehu, New Zealand

NASA Astrophysics Data System (ADS)

Cole, S. E.; Cronin, S. J.; Sherburn, S.; Manville, V.

2009-05-01

Detection of ground shaking forms the basis of many lahar-warning systems. Seismic records of two lahar types at Ruapehu, New Zealand, in 2007 are used to examine their nature and internal dynamics. Upstream detection of a flow depends upon flow type and coupling with the ground. 3-D characteristics of seismic signals can be used to distinguish the dominant rheology and gross physical composition. Water-rich hyperconcentrated flows are turbulent; common inter-particle and particle-substrate collisions engender higher energy in cross-channel vibrations relative to channel-parallel. Plug-like snow-slurry lahars show greater energy in channel-parallel signals, due to lateral deposition insulating channel margins, and low turbulence. Direct comparison of flow size must account for flow rheology; a water-rich lahar will generate signals of greater amplitude than a similar-sized snow-slurry flow.

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

Spatial-temporal dynamics of chemical composition of surface snow in East Antarctica along the Progress station-Vostok station transect

NASA Astrophysics Data System (ADS)

Khodzher, T. V.; Golobokova, L. P.; Osipov, E. Yu.; Shibaev, Yu. A.; Lipenkov, V. Ya.; Osipova, O. P.; Petit, J. R.

2014-05-01

In January of 2008, during the 53rd Russian Antarctic Expedition, surface snow samples were taken from 13 shallow (0.7 to 1.5 m depth) snow pits along the first tractor traverse from Progress to Vostok stations, East Antarctica. Sub-surface snow/firn layers are dated from 2.1 to 18 yr. The total length of the coast to inland traverse is more than 1280 km. Here we analysed spatial variability of concentrations of sulphate ions and elements and their fluxes in the snow deposited within the 2006-2008 time interval. Anions were analysed by high-performance liquid chromatography (HPLC), and the determination of selected metals, including Na, K, Mg, Ca and Al, was carried out by mass spectroscopy with atomization by induced coupled plasma (ICP-MS). Surface snow concentration records were examined for trends versus distance inland, elevation, accumulation rate and slope gradient. Na shows a significant positive correlation with accumulation rate, which decreases as distance from the sea and altitude increase. K, Ca and Mg concentrations do not show any significant relationship either with distance inland or with elevation. Maximal concentrations of these elements with a prominent Al peak are revealed in the middle part of the traverse (500-600 km from the coast). Analysis of element correlations and atmospheric circulation patterns allow us to suggest their terrestrial origin (e.g. aluminosilicates carried as a continental dust) from the Antarctic nunatak areas. Sulphate concentrations show no significant relationship with distance inland, elevation, slope gradient and accumulation rate. Non-sea salt secondary sulphate is the most important contribution to the total sulphate budget along the traverse. Sulphate of volcanic origin attributed to the Pinatubo eruption (1991) was revealed in the snow pit at 1276 km (depth 120-130 cm).

Enhanced Surface Warming and Accelerated Snow Melt in the Himalayas and Tibetan Plateau Induced by Absorbing Aerosols

NASA Technical Reports Server (NTRS)

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

2010-01-01

Numerical experiments with the NASA finite-volume general circulation model show that heating of the atmosphere by dust and black carbon can lead to widespread enhanced warming over the Tibetan Plateau (TP) and accelerated snow melt in the western TP and Himalayas. During the boreal spring, a thick aerosol layer, composed mainly of dust transported from adjacent deserts and black carbon from local emissions, builds up over the Indo-Gangetic Plain, against the foothills of the Himalaya and the TP. The aerosol layer, which extends from the surface to high elevation (approx.5 km), heats the mid-troposphere by absorbing solar radiation. The heating produces an atmospheric dynamical feedback the so-called elevated-heat-pump (EHP) effect, which increases moisture, cloudiness, and deep convection over northern India, as well as enhancing the rate of snow melt in the Himalayas and TP. The accelerated melting of snow is mostly confined to the western TP, first slowly in early April and then rapidly from early to mid-May. The snow cover remains reduced from mid-May through early June. The accelerated snow melt is accompanied by similar phases of enhanced warming of the atmosphere-land system of the TP, with the atmospheric warming leading the surface warming by several days. Surface energy balance analysis shows that the short-wave and long-wave surface radiative fluxes strongly offset each other, and are largely regulated by the changes in cloudiness and moisture over the TP. The slow melting phase in April is initiated by an effective transfer of sensible heat from a warmer atmosphere to land. The rapid melting phase in May is due to an evaporation-snow-land feedback coupled to an increase in atmospheric moisture over the TP induced by the EHP effect.

Greenland meltwater storage in firn limited by near-surface ice formation

NASA Astrophysics Data System (ADS)

Machguth, Horst; Macferrin, Mike; van As, Dirk; Box, Jason E.; Charalampidis, Charalampos; Colgan, William; Fausto, Robert S.; Meijer, Harro A. J.; Mosley-Thompson, Ellen; van de Wal, Roderik S. W.

2016-04-01

Approximately half of Greenland’s current annual mass loss is attributed to runoff from surface melt. At higher elevations, however, melt does not necessarily equal runoff, because meltwater can refreeze in the porous near-surface snow and firn. Two recent studies suggest that all or most of Greenland’s firn pore space is available for meltwater storage, making the firn an important buffer against contribution to sea level rise for decades to come. Here, we employ in situ observations and historical legacy data to demonstrate that surface runoff begins to dominate over meltwater storage well before firn pore space has been completely filled. Our observations frame the recent exceptional melt summers in 2010 and 2012 (refs ,), revealing significant changes in firn structure at different elevations caused by successive intensive melt events. In the upper regions (more than ~1,900 m above sea level), firn has undergone substantial densification, while at lower elevations, where melt is most abundant, porous firn has lost most of its capability to retain meltwater. Here, the formation of near-surface ice layers renders deep pore space difficult to access, forcing meltwater to enter an efficient surface discharge system and intensifying ice sheet mass loss earlier than previously suggested.

Determination of total arsenic and arsenic species in drinking water, surface water, wastewater, and snow from Wielkopolska, Kujawy-Pomerania, and Lower Silesia provinces, Poland.

PubMed

Komorowicz, Izabela; Barałkiewicz, Danuta

2016-09-01

Arsenic is a ubiquitous element which may be found in surface water, groundwater, and drinking water. In higher concentrations, this element is considered genotoxic and carcinogenic; thus, its level must be strictly controlled. We investigated the concentration of total arsenic and arsenic species: As(III), As(V), MMA, DMA, and AsB in drinking water, surface water, wastewater, and snow collected from the provinces of Wielkopolska, Kujawy-Pomerania, and Lower Silesia (Poland). The total arsenic was analyzed by inductively coupled plasma mass spectrometry (ICP-MS), and arsenic species were analyzed with use of high-performance liquid chromatography inductively coupled plasma mass spectrometry (HPLC/ICP-MS). Obtained results revealed that maximum total arsenic concentration determined in drinking water samples was equal to 1.01 μg L(-1). The highest concentration of total arsenic in surface water, equal to 3778 μg L(-1) was determined in Trująca Stream situated in the area affected by geogenic arsenic contamination. Total arsenic concentration in wastewater samples was comparable to those determined in drinking water samples. However, significantly higher arsenic concentration, equal to 83.1 ± 5.9 μg L(-1), was found in a snow sample collected in Legnica. As(V) was present in all of the investigated samples, and in most of them, it was the sole species observed. However, in snow sample collected in Legnica, more than 97 % of the determined concentration, amounting to 81 ± 11 μg L(-1), was in the form of As(III), the most toxic arsenic species.

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%.

Design and Verification of Blast Densification for Highway Embankments of Liquefiable Sands

DOT National Transportation Integrated Search

2012-10-26

As part of a larger effort to investigate the effects of blast densification on the properties and : behavior of compacted sand deposits, this study presents a procedure for replicating in the : laboratory the occluded gas bubbles believed to exist i...

Application of powder densification models to the consolidation processing of composites

NASA Technical Reports Server (NTRS)

Wadley, H. N. G.; Elzey, D. M.

1991-01-01

Unidirectional fiber reinforced metal matrix composite tapes (containing a single layer of parallel fibers) can now be produced by plasma deposition. These tapes can be stacked and subjected to a thermomechanical treatment that results in a fully dense near net shape component. The mechanisms by which this consolidation step occurs are explored, and models to predict the effect of different thermomechanical conditions (during consolidation) upon the kinetics of densification are developed. The approach is based upon a methodology developed by Ashby and others for the simpler problem of HIP of spherical powders. The complex problem is devided into six, much simpler, subproblems, and then their predicted contributions are added to densification. The initial problem decomposition is to treat the two extreme geometries encountered (contact deformation occurring between foils and shrinkage of isolated, internal pores). Deformation of these two geometries is modelled for plastic, power law creep and diffusional flow. The results are reported in the form of a densification map.

Technoeconomic analysis of wheat straw densification in the Canadian Prairie Province of Manitoba.

PubMed

Mupondwa, Edmund; Li, Xue; Tabil, Lope; Phani, Adapa; Sokhansanj, Shahab; Stumborg, Mark; Gruber, Margie; Laberge, Serge

2012-04-01

This study presents a technoeconomic analysis of wheat straw densification in Canada's prairie province of Manitoba as an integral part of biomass-to-cellulosic-ethanol infrastructure. Costs of wheat straw bale and pellet transportation and densification are analysed, including densification plant profitability. Wheat straw collection radius increases nonlinearly with pellet plant capacity, from 9.2 to 37km for a 2-35tonnesh(-1) plant. Bales are cheaper under 250km, beyond which the cheapest feedstocks are pellets from the largest pellet plant that can be built to exploit economies of scale. Feedstocks account for the largest percentage of variable costs. Marginal and average cost curves suggest Manitoba could support a pellet plant up to 35tonnesh(-1). Operating below capacity (75-50%) significantly erodes a plant's net present value (NPV). Smaller plants require higher NPV break-even prices. Very large plants have considerable risk under low pellet prices and increased processing costs. Crown Copyright © 2012. Published by Elsevier Ltd. All rights reserved.

Spark Plasma Sintering of Commercial Zirconium Carbide Powders: Densification Behavior and Mechanical Properties

PubMed Central

Wei, Xialu; Back, Christina; Izhvanov, Oleg; Khasanov, Oleg L.; Haines, Christopher D.; Olevsky, Eugene A.

2015-01-01

Commercial zirconium carbide (ZrC) powder is consolidated by Spark Plasma Sintering (SPS). Processing temperatures range from 1650 to 2100 °C. Specimens with various density levels are obtained when performing single-die SPS at different temperatures. Besides the single-die tooling setup, a double-die tooling setup is employed to largely increase the actual applied pressure to achieve higher densification in a shorter processing time. In order to describe the densification mechanism of ZrC powder under SPS conditions, a power-law creep constitutive equation is utilized, whose coefficients are determined by the inverse regression of the obtained experimental data. The densification of the selected ZrC powder is shown to be likely associated with grain boundary sliding and dislocation glide controlled creep. Transverse rupture strength and microhardness of sintered specimens are measured to be up to 380 MPa and 24 GPa, respectively. Mechanical properties are correlated with specimens’ average grain size and relative density to elucidate the co-factor dependencies. PMID:28793550

Canadian snow and sea ice: assessment of snow, sea ice, and related climate processes in Canada's Earth system model and climate-prediction system

NASA Astrophysics Data System (ADS)

Kushner, Paul J.; Mudryk, Lawrence R.; Merryfield, William; Ambadan, Jaison T.; Berg, Aaron; Bichet, Adéline; Brown, Ross; Derksen, Chris; Déry, Stephen J.; Dirkson, Arlan; Flato, Greg; Fletcher, Christopher G.; Fyfe, John C.; Gillett, Nathan; Haas, Christian; Howell, Stephen; Laliberté, Frédéric; McCusker, Kelly; Sigmond, Michael; Sospedra-Alfonso, Reinel; Tandon, Neil F.; Thackeray, Chad; Tremblay, Bruno; Zwiers, Francis W.

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. This study presents an assessment from the CanSISE Network of the ability of the second-generation Canadian Earth System Model (CanESM2) and the Canadian Seasonal to Interannual Prediction System (CanSIPS) to simulate and predict snow and sea ice from seasonal to multi-decadal timescales, with a focus on the Canadian sector. To account for observational uncertainty, model structural uncertainty, and internal climate variability, the analysis uses multi-source observations, multiple Earth system models (ESMs) in Phase 5 of the Coupled Model Intercomparison Project (CMIP5), and large initial-condition ensembles of CanESM2 and other models. It is found that the ability of the CanESM2 simulation to capture snow-related climate parameters, such as cold-region surface temperature and precipitation, lies within the range of currently available international models. Accounting for the considerable disagreement among satellite-era observational datasets on the distribution of snow water equivalent, CanESM2 has too much springtime snow mass over Canada, reflecting a broader northern hemispheric positive bias. Biases in seasonal snow cover extent are generally less pronounced. CanESM2 also exhibits retreat of springtime snow generally greater than observational estimates, after accounting for observational uncertainty and internal variability. Sea ice is biased low in the Canadian Arctic, which makes it difficult to assess the realism of long-term sea ice trends there. The strengths and weaknesses of the modelling system need to be understood as a practical tradeoff: the Canadian models are relatively inexpensive computationally because of their moderate resolution, thus enabling their use in operational seasonal prediction and for generating large ensembles of multidecadal simulations. Improvements in climate-prediction systems like CanSIPS rely not just on simulation quality but also on using novel observational constraints and the ready transfer of research to an operational setting. Improvements in seasonal forecasting practice arising from recent research include accurate initialization of snow and frozen soil, accounting for observational uncertainty in forecast verification, and sea ice thickness initialization using statistical predictors available in real time.

Densification of PZT Ceramics with V2O5 Additive.

DTIC Science & Technology

1979-01-01

Additions of V2O5 from 0.1 to 8.0 w/o to a coprecipitated Pb(Zr.53 Ti.47) O3 ceramic promoted rapid densification below 1025 C, eliminating the need...for PbO atmosphere control. Dielectric properties were found to be dependent on the amount of V2O5 added and on the microstructure developed, but were...comparable to reported values for this PZT composition for additions of V2O5 or = 1.5 W/O. The indicated densification mechanism is one of activated sintering catalyzed by generation of oxygen defects on decomposition of the V2O5 .

Enhanced Densification and Hardness of Titanium Bodies Sintered by Advanced Hydrogen Sintering Process

NASA Astrophysics Data System (ADS)

Oh, Jung-Min; Koo, Ja-Geon; Lim, Jae-Won

2018-05-01

A new sintering technique for enhancing a densification and hardness of sintered titanium body by supplying hydrogen was developed (Hydrogen Sintering Process, HSP). The HSP was developed by only injecting hydrogen into an argon atmosphere during the core time. As a result, sound titanium sintered bodies with high density and hardness were obtained by the HSP. In addition, a pore size and number of the HSP specimens were smaller than those of the argon atmosphere specimen. It was found that the injecting hydrogen into the argon atmosphere by HSP can prevent the formation of oxide layers, resulting in enhanced densification and hardness.

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

USGS Publications Warehouse

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

2017-01-01

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

Spatial and seasonal variations of elemental composition in Mt. Everest (Qomolangma) snow/firn

NASA Astrophysics Data System (ADS)

Kang, Shichang; Zhang, Qianggong; Kaspari, Susan; Qin, Dahe; Cong, Zhiyuan; Ren, Jiawen; Mayewski, Paul A.

In May 2005, a total of 14 surface snow (0-10 cm) samples were collected along the climbing route from the advanced base camp to the summit (6500-8844 m a.s.l.) on the northern slope of Mt. Everest (Qomolangma). A 108 m firn/ice core was retrieved from the col of the East Rongbuk Glacier (28.03°N, 86.96°E, 6518 m a.s.l.) on the north eastern saddle of Mt. Everest in September 2002. Surface snow and the upper 3.5 m firn samples from the core were analyzed for major and trace elements by inductively coupled plasma mass spectroscopy (ICP-MS). Measurements show that crustal elements dominated both surface snow and the firn core, suggesting that Everest snow chemistry is mainly influenced by crustal aerosols from local rock or prevalent spring dust storms over southern/central Asia. There are no clear trends for element variations with elevation due to local crustal aerosol inputs or redistribution of surface snow by strong winds during the spring. Seasonal variability in snow/firn elements show that high elemental concentrations occur during the non-monsoon season and low values during the monsoon season. Ca, Cr, Cs, and Sr display the most distinct seasonal variations. Elemental concentrations (especially for heavy metals) at Mt. Everest are comparable with polar sites, generally lower than in suburban areas, and far lower than in large cities. This indicates that anthropogenic activities and heavy metal pollution have little effect on the Mt. Everest atmospheric environment. Everest firn core REE concentrations are the first reported in the region and seem to be comparable with those measured in modern and Last Glacial Maximum snow/ice samples from Greenland and Antarctica, and with precipitation samples from Japan and the East China Sea. This suggests that REE concentrations measured at Everest are representative of the background atmospheric environment.

Classification of Snowfall Events and Their Effect on Canopy Interception Efficiency in a Temperate Montane Forest.

NASA Astrophysics Data System (ADS)

Roth, T. R.; Nolin, A. W.

2015-12-01

Forest canopies intercept as much as 60% of snowfall in maritime environments, while processes of sublimation and melt can reduce the amount of snow transferred from the canopy to the ground. This research examines canopy interception efficiency (CIE) as a function of forest and event-scale snowfall characteristics. We use a 4-year dataset of continuous meteorological measurements and monthly snow surveys from the Forest Elevation Snow Transect (ForEST) network that has forested and open sites at three elevations spanning the rain-snow transition zone to the upper seasonal snow zone. Over 150 individual storms were classified by forest and storm type characteristics (e.g. forest density, vegetation type, air temperature, snowfall amount, storm duration, wind speed, and storm direction). The between-site comparisons showed that, as expected, CIE was highest for the lower elevation (warmer) sites with higher forest density compared with the higher elevation sites where storm temperatures were colder, trees were smaller and forests were less dense. Within-site comparisons based on storm type show that this classification system can be used to predict CIE.Our results suggest that the coupling of forest type and storm type information can improve estimates of canopy interception. Understanding the effects of temperature and storm type in temperate montane forests is also valuable for future estimates of canopy interception under a warming climate.

The Influence of Simulated Home and Neighbourhood Densification on Perceived Liveability

ERIC Educational Resources Information Center

Thomas, J. A.; Walton, D.; Lamb, S.

2011-01-01

This study experimentally manipulated neighbourhood density and home location to reveal the effect of these changes on perceived liveability. Two hypothetical scenarios were provided to 106 households using a Computer-Aided Personal Interview (CAPI). The first scenario examined a densification of the participant's current property, and the second…

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.

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.

High resolution climate scenarios for snowmelt modelling in small alpine catchments

NASA Astrophysics Data System (ADS)

Schirmer, M.; Peleg, N.; Burlando, P.; Jonas, T.

2017-12-01

Snow in the Alps is affected by climate change with regard to duration, timing and amount. This has implications with respect to important societal issues as drinking water supply or hydropower generation. In Switzerland, the latter received a lot of attention following the political decision to phase out of nuclear electricity production. An increasing number of authorization requests for small hydropower plants located in small alpine catchments was observed in the recent years. This situation generates ecological conflicts, while the expected climate change poses a threat to water availability thus putting at risk investments in such hydropower plants. Reliable high-resolution climate scenarios are thus required, which account for small-scale processes to achieve realistic predictions of snowmelt runoff and its variability in small alpine catchments. We therefore used a novel model chain by coupling a stochastic 2-dimensional weather generator (AWE-GEN-2d) with a state-of-the-art energy balance snow cover model (FSM). AWE-GEN-2d was applied to generate ensembles of climate variables at very fine temporal and spatial resolution, thus providing all climatic input variables required for the energy balance modelling. The land-surface model FSM was used to describe spatially variable snow cover accumulation and melt processes. The FSM was refined to allow applications at very high spatial resolution by specifically accounting for small-scale processes, such as a subgrid-parametrization of snow covered area or an improved representation of forest-snow processes. For the present study, the model chain was tested for current climate conditions using extensive observational dataset of different spatial and temporal coverage. Small-scale spatial processes such as elevation gradients or aspect differences in the snow distribution were evaluated using airborne LiDAR data. 40-year of monitoring data for snow water equivalent, snowmelt and snow-covered area for entire Switzerland was used to verify snow distribution patterns at coarser spatial and temporal scale. The ability of the model chain to reproduce current climate conditions in small alpine catchments makes this model combination an outstanding candidate to produce high resolution climate scenarios of snowmelt in small alpine catchments.

Spaceborne Radar Observations of High Mountain Asia Snow and Ice

NASA Astrophysics Data System (ADS)

Lund, J.

2016-12-01

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

Snow water equivalent in the Alps as seen by gridded data sets, CMIP5 and CORDEX climate models

NASA Astrophysics Data System (ADS)

Terzago, Silvia; von Hardenberg, Jost; Palazzi, Elisa; Provenzale, Antonello

2017-07-01

The estimate of the current and future conditions of snow resources in mountain areas would require reliable, kilometre-resolution, regional-observation-based gridded data sets and climate models capable of properly representing snow processes and snow-climate interactions. At the moment, the development of such tools is hampered by the sparseness of station-based reference observations. In past decades passive microwave remote sensing and reanalysis products have mainly been used to infer information on the snow water equivalent distribution. However, the investigation has usually been limited to flat terrains as the reliability of these products in mountain areas is poorly characterized.This work considers the available snow water equivalent data sets from remote sensing and from reanalyses for the greater Alpine region (GAR), and explores their ability to provide a coherent view of the snow water equivalent distribution and climatology in this area. Further we analyse the simulations from the latest-generation regional and global climate models (RCMs, GCMs), participating in the Coordinated Regional Climate Downscaling Experiment over the European domain (EURO-CORDEX) and in the Fifth Coupled Model Intercomparison Project (CMIP5) respectively. We evaluate their reliability in reproducing the main drivers of snow processes - near-surface air temperature and precipitation - against the observational data set EOBS, and compare the snow water equivalent climatology with the remote sensing and reanalysis data sets previously considered. We critically discuss the model limitations in the historical period and we explore their potential in providing reliable future projections.The results of the analysis show that the time-averaged spatial distribution of snow water equivalent and the amplitude of its annual cycle are reproduced quite differently by the different remote sensing and reanalysis data sets, which in fact exhibit a large spread around the ensemble mean. We find that GCMs at spatial resolutions equal to or finer than 1.25° longitude are in closer agreement with the ensemble mean of satellite and reanalysis products in terms of root mean square error and standard deviation than lower-resolution GCMs. The set of regional climate models from the EURO-CORDEX ensemble provides estimates of snow water equivalent at 0.11° resolution that are locally much larger than those indicated by the gridded data sets, and only in a few cases are these differences smoothed out when snow water equivalent is spatially averaged over the entire Alpine domain. ERA-Interim-driven RCM simulations show an annual snow cycle that is comparable in amplitude to those provided by the reference data sets, while GCM-driven RCMs present a large positive bias. RCMs and higher-resolution GCM simulations are used to provide an estimate of the snow reduction expected by the mid-21st century (RCP 8.5 scenario) compared to the historical climatology, with the main purpose of highlighting the limits of our current knowledge and the need for developing more reliable snow simulations.

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

PubMed

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

2014-09-15

Observed climate change has already led to a wide range of impacts on environmental systems and society. In this context, many mountain regions seem to be particularly sensitive to a changing climate, through increases in temperature coupled with changes in precipitation regimes that are often larger than the global average (EEA, 2012). In mid-latitude mountains, these driving factors strongly influence the variability of the mountain snow-pack, through a decrease in seasonal reserves and earlier melting of the snow pack. These in turn impact on hydrological systems in different watersheds and, ultimately, have consequences for water management. Snow monitoring from remote sensing provides a unique opportunity to address the question of snow cover regime changes at the regional scale. This study outlines the results retrieved from the MODIS satellite images over a time period of 10 hydrological years (2000-2010) and applied to two case studies of the EU FP7 ACQWA project, namely the upper Rhone and Po in Europe and the headwaters of the Syr Darya in Kyrgyzstan (Central Asia). The satellite data were provided by the MODIS Terra MOD-09 reflectance images (NASA) and MOD-10 snow products (NSIDC). Daily snow maps were retrieved over that decade and the results presented here focus on the temporal and spatial changes in snow cover. This paper highlights the statistical bias observed in some specific regions, expressed by the standard deviation values (STD) of annual snow duration. This bias is linked to the response of snow cover to changes in elevation and can be used as a signal of strong instability in regions sensitive to climate change: with alternations of heavy snowfalls and rapid snow melting processes. The interest of the study is to compare the methodology between the medium scales (Europe) and the large scales (Central Asia) in order to overcome the limits of the applied methodologies and to improve their performances. Results show that the yearly snow cover duration increases by 4-5 days per 100 m elevation during the accumulation period, depending of the watershed, while during the melting season the snow depletion rate is 0.3% per day of surface loss for the upper Rhone catchment, 0.4%/day for the Syr Darya headwater basins, and 0.6%/day for the upper Po, respectively. Then, the annual STD maps of snow cover indicate higher values (more than 45 days difference compared to the mean values) for (i) the Po foothill region at medium elevation (SE orientation) and (ii) the Kyrgyzstan high plateaux (permafrost areas). These observations cover only a time-period of 10 years, but exhibit a signal under current climate that is already consistent with the expected decline in snow in these regions in the course of the 21st century. Copyright © 2014 Elsevier B.V. All rights reserved.

Densification kinetics of nanocrystalline zirconia powder using microwave and spark plasma sintering--a comparative study.

PubMed

Vasylkiv, Oleg; Demirskyi, Dmytro; Sakka, Yoshio; Ragulya, Andrey; Borodianska, Hanna

2012-06-01

Two-stage densification process of nanosized 3 mol% yttria-stabilized zirconia (3Y-SZ) polycrystalline compacts during consolidation via microwave and spark-plasma sintering have been observed. The values of activation energies obtained for microwave and spark-plasma sintering 260-275 kJ x mol(-1) are quite similar to that of conventional sintering of zirconia, suggesting that densification during initial stage is controlled by the grain-boundary diffusion mechanism. The sintering behavior during microwave sintering was significantly affected by preliminary pressing conditions, as the surface diffusion mechanism (230 kJ x mol(-1)) is active in case of cold-isostatic pressing procedure was applied.

Liquid Oxygen Propellant Densification Unit Ground Tested With a Large-Scale Flight-Weight Tank for the X-33 Reusable Launch Vehicle

NASA Technical Reports Server (NTRS)

Tomsik, Thomas M.

2002-01-01

Propellant densification has been identified as a critical technology in the development of single-stage-to-orbit reusable launch vehicles. Technology to create supercooled high-density liquid oxygen (LO2) and liquid hydrogen (LH2) is a key means to lowering launch vehicle costs. The densification of cryogenic propellants through subcooling allows 8 to 10 percent more propellant mass to be stored in a given unit volume, thereby improving the launch vehicle's overall performance. This allows for higher propellant mass fractions than would be possible with conventional normal boiling point cryogenic propellants, considering the normal boiling point of LO2 and LH2.

The Sensitivity of Soil Moisture in Western U.S. Mountains to Changes in Snowmelt

NASA Astrophysics Data System (ADS)

Harpold, A. A.

2014-12-01

Snowmelt is the primary water source for human needs and ecosystems services in much of the Western U.S. Regional warming is expected to hasten snow disappearance and reduce snowpacks. The soil water budget strongly mediates the effects of changing snowmelt patterns by storing water and altering is partitioning to evaporation, transpiration, and runoff. This study therefore asked the research question, "Under what conditions was soil water availability coupled to snowmelt magnitudes and timing across Western U.S. mountains?" We posed three potential hypotheses to explain decoupling between soil water availability and snowmelt: 1. Contributions from post-snowmelt rainfall, 2. Longer growing season length and/or greater water demand, and/or 3. Insufficient soil water storage. Using 259 Snow Telemetry (SNOTEL) stations, we showed that the timing of Peak Soil Moisture (PSM) was strongly explained by snow disappearance (Pearson r-value of 0.62). However, differences in the coupling of PSM with DSD were dependent on soil and bedrock type, with well-drained areas having earlier PSM relative to DSD. A second analysis focused on 48 SNOTEL and Soil Climate Analysis Network (SCAN) stations in the Northwest and Intermountain Western U.S. where detailed soil hydraulic properties existed. We found the timing of snow disappearance was a strong influence (p<0.01) on the number of days per year that soil moisture was below wilting point at individual stations, whereas summer precipitation was a weaker predictor. We develop a framework to classify stations into three classes: 1. stations that were not subject to water stress from changing snowmelt patterns over the historical records, 2. stations subject to water stress during poor snowmelt years, and 3. stations that relied on rainfall to avoid water stress across historical records. Our combined results demonstrate that snow disappearance timing is a first-order control on soil water availability across many Western U.S. mountain ecosystems. However, soils properties could make areas more/less sensitive to changing snowpacks depending on seasonal precipitation patterns. This type of simple framework could be used to identify areas at risk of changing snowpacks and help constrain vegetation distributions as a consequence of climate change.

Increased photosynthesis compensates for shorter growing season in subarctic tundra - seven years of snow accumulation manipulations

NASA Astrophysics Data System (ADS)

Bosiö, Julia; Johansson, Margareta; Njuabe, Herbert; Christensen, Torben R.

2013-04-01

This study was initiated to analyze the effect of snow cover on photosynthesis and plant growth in subarctic mires underlain by permafrost. Due to their narrow environmental window these raised bogs, often referred to as palsa mires, are highly sensitive to climatic changes. In Fennoscandia palsa mires are currently subjected to climate related thawing and shift in vegetational and hydrological patterns. Yet, we know little of how these subarctic permafrost mires react and feed back to such changes. By using snow fences to hinder snow drift the accumulation of snow was increased in six plots (10x20 m) in a snow manipulation experiment on a subarctic permafrost mire in northern Sweden. The thicker snow pack prolongs the duration of the snow cover in spring, causing a delay in the onset, as well as an overall shortening of the growing season. By measuring incoming and reflected photosynthetic active radiation (PAR) we wanted to address the question whether the increased snow thickness and associated delay of the growing season start affected the absorbed PAR and the accumulated gross primary production (GPP) over the season. The reflected PAR was measured at twelve plots where six of the plots experienced increased snow accumulation (treatment), and remaining six plots were untreated (control). Minikin QT sensors with integrated data loggers logged incoming and reflected PAR hourly throughout the growing seasons of 2011 and 2012. In July - September 2010 PAR measurements were coupled with flux chamber measurements to assess GPP and light use efficiency of the plots. The increased accumulation of snow prolonged the duration of the snow cover in spring, causing a delay in the onset, as well as an overall shortening of the growing season in the treated plots. The end of the growing season was not affected by the snow manipulation. The delay of the growing season start and hence overall shortening of the growing season in the treatment plots was 18 days in 2011 and 3 days in 2012 in relation to control plots. Results show higher PAR absorption together with almost 50% higher light use efficiency in treatment plots compared with control plots. Estimations of GPP suggest that the loss in early season photosynthesis due to the shortening of the growing season in the treatment plots is well compensated for by the increased absorption of PAR and higher light use efficiency throughout the whole growing seasons. This compensation is likely to be explained by increased soil moisture and nutrient availability together with a shift in vegetation composition associated with the accelerated permafrost thaw in the treatment plots. In our presentation implications and possible feedbacks of the increased absorbed PAR and estimated change in GPP will be discussed.

Meso-scopic Densification in Brittle Granular Materials

NASA Astrophysics Data System (ADS)

Neal, William; Appleby-Thomas, Gareth; Collins, Gareth

2013-06-01

Particulate materials are ideally suited to shock absorbing applications due to the large amounts of energy required to deform their inherently complex meso-structure. Significant effort is being made to improve macro-scale material models to represent these atypical materials. On the long road towards achieving this capability, an important milestone would be to understand how particle densification mechanisms are affected by loading rate. In brittle particulate materials, the majority of densification is caused by particle fracture. Macro-scale quasi-static and dynamic compaction curves have been measured that show good qualitative agreement. There are, however, some differences that appear to be dependent on the loading rate that require further investigation. This study aims to investigate the difference in grain-fracture behavior between the quasi-static and shock loading response of brittle glass microsphere beds using a combination of quasi-static and dynamic loading techniques. Results from pressure-density measurements, sample recovery, and meso-scale hydrocode models (iSALE, an in-house simulation package) are discussed to explain the differences in particle densification mechanisms between the two loading rate regimes. Gratefully funded by AWE.plc.

Frost Growth and Densification in Laminar Flow Over Flat Surfaces

NASA Technical Reports Server (NTRS)

Kandula, Max

2011-01-01

One-dimensional frost growth and densification in laminar flow over flat surfaces has been theoretically investigated. Improved representations of frost density and effective thermal conductivity applicable to a wide range of frost circumstances have been incorporated. The validity of the proposed model considering heat and mass diffusion in the frost layer is tested by a comparison of the predictions with data from various investigators for frost parameters including frost thickness, frost surface temperature, frost density and heat flux. The test conditions cover a range of wall temperature, air humidity ratio, air velocity, and air temperature, and the effect of these variables on the frost parameters has been exemplified. Satisfactory agreement is achieved between the model predictions and the various test data considered. The prevailing uncertainties concerning the role air velocity and air temperature on frost development have been elucidated. It is concluded that that for flat surfaces increases in air velocity have no appreciable effect on frost thickness but contribute to significant frost densification, while increase in air temperatures results in a slight increase the frost thickness and appreciable frost densification.

Understanding the densification process of Bi2Sr2CaCu2Ox round wires with overpressure processing and its effect on critical current density

PubMed Central

Matras, M. R.; Jiang, J.; Larbalestier, D. C.; Hellstrom, E. E.

2016-01-01

Overpressure (OP) processing increases the critical current density (JC) of Bi2Sr2CaCu2Ox (2212) round wires by shrinking the surrounding Ag matrix around the 2212 filaments, driving them close to full density and greatly increasing the 2212 grain connectivity. Indeed densification is vital for attaining the highest JC. Here, we investigate the time and temperature dependence of the wire densification. We find that the wire diameter decreases by 3.8 ± 0.3 % after full heat treatment at 50 atm and 100 atm OP. At 50 atm OP pressure, the filaments start densifying above 700 °C and reach a 3.30 ± 0.07 % smaller diameter after 2 h at 820 °C, which is below the melting point of 2212 powder. The densification is homogeneous and does not change the filament shape before melting. The growth of non-superconducting phases is observed at 820 °C, suggesting that time should be minimized at high temperature prior to melting the 2212 powder. Study of an open-ended 2.2 m long wire sample shows that full densification and the high OP JC (JC varies by about 3.1 times over the 2.2 m long wire) is reached about 1 m from the open ends, thus showing that coil-length wires can be protected from leaky seals by adding at least 1 m of sacrificial wire at each end. PMID:28479675

Si-Ge Nano-Structured with Tungsten Silicide Inclusions

NASA Technical Reports Server (NTRS)

Mackey, Jon; Sehirlioglu, Alp; Dynys, Fred

2014-01-01

Traditional silicon germanium high temperature thermoelectrics have potential for improvements in figure of merit via nano-structuring with a silicide phase. A second phase of nano-sized silicides can theoretically reduce the lattice component of thermal conductivity without significantly reducing the electrical conductivity. However, experimentally achieving such improvements in line with the theory is complicated by factors such as control of silicide size during sintering, dopant segregation, matrix homogeneity, and sintering kinetics. Samples are prepared using powder metallurgy techniques; including mechanochemical alloying via ball milling and spark plasma sintering for densification. In addition to microstructural development, thermal stability of thermoelectric transport properties are reported, as well as couple and device level characterization.

WSi2 in Si(1-x)Ge(x) Composites: Processing and Thermoelectric Properties

NASA Technical Reports Server (NTRS)

Mackey, Jonathan A.; Sehirlioglu, Alp; Dynys, Fred

2015-01-01

Traditional SiGe thermoelectrics have potential for enhanced figure of merit (ZT) via nano-structuring with a silicide phase, such as WSi2. A second phase of nano-sized silicides can theoretically reduce the lattice component of thermal conductivity without significantly reducing the electrical conductivity. However, experimentally achieving such improvements in line with the theory is complicated by factors such as control of silicide size during sintering, dopant segregation, matrix homogeneity, and sintering kinetics. Samples were prepared using powder metallurgy techniques; including mechano-chemical alloying, via ball milling, and spark plasma sintering for densification. Processing, micro-structural development, and thermoelectric properties will be discussed. Additionally, couple and device level characterization will be introduced.

Cross-Regional Assessment Of Coupling And Variability In Precipitation-Runoff Relationships

NASA Astrophysics Data System (ADS)

Carey, S. K.; Tetzlaff, D.; Soulsby, C.; Buttle, J. M.; Laudon, H.; McDonnell, J. J.; McGuire, K. J.; Seibert, J.; Shanley, J. B.

2011-12-01

The higher mid-latitudes of the northern hemisphere are particularly sensitive to change due to the important role the zero-degree isotherm plays in the phase of precipitation and intermediate storage as snow. An international inter-catchment comparison program North-Watch seeks to improve our understanding of the sensitivity of northern catchments to change by examining their hydrological and biogeochemical variability and response. The catchments are located in Sweden (Krycklan), Scotland (Mharcaidh, Girnock and Strontian), the United States (Sleepers River, Hubbard Brook and HJ Andrews) and Canada (Catamaran, Dorset and Wolf Creek). For this study, 8 catchments with 10 continuous years of daily precipitation and runoff data were selected to assess the seasonal coupling of rainfall and runoff and the memory effect of runoff events on the hydrograph at different time scales. To assess the coupling and synchroneity of precipitation, continuous wavelet transforms and wavelet coherence were used. Wavelet spectra identified the relative importance of both annual versus seasonal flows while wavelet coherence was applied to identify over different time scales along the 10-year window how well precipitation and runoff were coupled. For example, while on a given day, precipitation may be closely coupled to runoff, a wet year may not necessarily be a high runoff year in catchments with large storage. Assessing different averaging periods in the variation of daily flows highlights the importance of seasonality in runoff response and the relative influence of rain versus snowmelt on flow magnitude and variability. Wet catchments with limited seasonal precipitation variability (Strontian, Girnock) have precipitation signals more closely coupled with runoff, whereas dryer catchments dominated by snow (Wolf Creek, Krycklan) have strongly coupling only during freshet. Most catchments with highly seasonal precipitation show strong intermittent coupling during their wet season. At longer time scales, some catchments do not exhibit coupling in their input-output relations, which is related to catchment storage.

A novel fast ion chromatographic method for the analysis of fluoride in Antarctic snow and ice.

PubMed

Severi, Mirko; Becagli, Silvia; Frosini, Daniele; Marconi, Miriam; Traversi, Rita; Udisti, Roberto

2014-01-01

Ice cores are widely used to reconstruct past changes of the climate system. For instance, the ice core record of numerous water-soluble and insoluble chemical species that are trapped in snow and ice offer the possibility to investigate past changes of various key compounds present in the atmosphere (i.e., aerosol, reactive gases). We developed a new method for the quantitative determination of fluoride in ice cores at sub-μg L(-1) levels by coupling a flow injection analysis technique with a fast ion chromatography separation based on the "heart cut" column switching technology. Sensitivity, linear range (up to 60 μg L(-1)), reproducibility, and detection limit (0.02 μg L(-1)) were evaluated for the new method. This method was successfully applied to the analysis of fluoride at trace levels in more than 450 recent snow samples collected during the 1998-1999 International Trans-Antarctica Scientific Expedition traverse in East Antarctica at sites located between 170 and 850 km from the coastline.

Densification and state transition across the Missouri Ozarks landscape

Treesearch

Brice B. Hanberry; John M. Kabrick; Hong S. He

2014-01-01

World-wide, some biomes are densifying, or increasing in dense woody vegetation, and shifting to alternative stable states. We quantified densification and state transition between forests ecosystems in historical (ca. 1815-1850) and current (2004-2008) surveys of the Missouri Ozark Highlands, a 5-million ha landscape in southern Missouri, USA. To estimate density of...

Effect of hot densification on tribotechnical properties of sintered (Al-12Si)-40Sn alloy

NASA Astrophysics Data System (ADS)

Rusin, N. M.; Skorentsev, A. L.; Kolubaev, E. A.

2017-12-01

The paper describes the effect of hot densification on mechanical and tribotechnical properties of sintered samples of (Al-12Si)-40Sn composition. It proves that such treatment increases the strength and ductility of the studied materials and makes higher their wear resistant under dry friction against a steel counterbody.

Confinement induced densification in supported unentangled polymer films

NASA Astrophysics Data System (ADS)

Pradipkanti, L.; Satapathy, Dillip K.

2017-05-01

We report the densification phenomena inunentangled and low-molecular weight polystyrene (PS) thin films supported on solid substrates having thickness from 25 nm to 230 nm. The mass density of the thin polymer films were extracted from X-ray reflectivity profiles and also from the refractive index by using Clausius and Mossotti equation. The mass densityof polymeris found to increasesignificantly with decrease in film thickness below ten times the radius of gyration of the polymer. The net increase in mass density of the polymer film upon reduction in thickness is discussed in terms of three-layer model and the presence of unentangled polymer chains. We conjecture that, the densification of ultra-thin polymer films can strongly alter the polymer conformations at film/substrate interface.

One step sintering of homogenized bauxite raw material and kinetic study

NASA Astrophysics Data System (ADS)

Gao, Chang-he; Jiang, Peng; Li, Yong; Sun, Jia-lin; Zhang, Jun-jie; Yang, Huan-ying

2016-10-01

A one-step sintering process of bauxite raw material from direct mining was completed, and the kinetics of this process was analyzed thoroughly. The results show that the sintering kinetics of bauxite raw material exhibits the liquid-phase sintering behavior. A small portion of impurities existed in the raw material act as a liquid phase. After X-ray diffraction analyses, scanning electron microscopy observations, and kinetics calculations, sintering temperature and heating duration were determined as the two major factors contributing to the sintering process and densification of bauxite ore. An elevated heating temperature and longer duration favor the densification process. The major obstacle for the densification of bauxite material is attributed to the formation of the enclosed blowhole during liquid-phase sintering.

Densifying carbon nanotubes on assembly surface by the self-contraction of silk fibroin

NASA Astrophysics Data System (ADS)

Jiang, Chunyang; Yang, Xueqin; Zhao, Jingna; Li, Qingsong; Zhang, Ke-Qin; Zhang, Xiaohua; Li, Qingwen

2018-04-01

High densification of carbon nanotubes (CNTs) is important for high utilization efficiency of their superior properties in macroscopic assemblies. However, the conventional "top-down" compressing strategies have met problems to modify CNT assemblies at and below the micrometer scale. Here we report a molecular way to strap CNTs together via the self-contraction of silk fibroin (SF) during its drying process, resulting in a localized densification below the micrometer scale. Importantly, after the thermal removal of SF molecules, the densified assembly was well maintained. The SF-induced densification increased the average strength from 355 MPa to 960 MPa for CNT fibers, and from 1.45 GPa to 1.82 GPa for CNT ribbons, which contain much more CNTs on the surface.

Improving simulations of snow water equivalent and total water storage changes over the Upper Yangtze River basin using multi-source remote sensing data

NASA Astrophysics Data System (ADS)

Han, P.; Long, D.

2017-12-01

Snow water equivalent (SWE) and total water storage (TWS) changes are important hydrological state variables over cryospheric regions, such as China's Upper Yangtze River (UYR) basin. Accurate simulation of these two state variables plays a critical role in understanding hydrological processes over this region and, in turn, benefits water resource management, hydropower development, and ecological integrity over the lower reaches of the Yangtze River, one of the largest rivers globally. In this study, an improved CREST model coupled with a snow and glacier melting module was used to simulate SWE and TWS changes over the UYR, and to quantify contributions of snow and glacier meltwater to the total runoff. Forcing, calibration, and validation data are mainly from multi-source remote sensing observations, including satellite-based precipitation estimates, passive microwave remote sensing-based SWE, and GRACE-derived TWS changes, along with streamflow measurements at the Zhimenda gauging station. Results show that multi-source remote sensing information can be extremely valuable in model forcing, calibration, and validation over the poorly gauged region. The simulated SWE and TWS changes and the observed counterparts are highly consistent, showing NSE coefficients higher than 0.8. The results also show that the contributions of snow and glacier meltwater to the total runoff are 8% and 6%, respectively, during the period 2003‒2014, which is an important source of runoff. Moreover, from this study, the TWS is found to increase at a rate of 5 mm/a ( 0.72 Gt/a) for the period 2003‒2014. The snow melting module may overestimate SWE for high precipitation events and was improved in this study. Key words: CREST model; Remote Sensing; Melting model; Source Region of the Yangtze River

Commodifying snow, taming the waters. Socio-ecological niche construction in an Alpine village.

PubMed

Gross, Robert; Winiwarter, Verena

White belts of snow clad mountains all over the world each winter. Even if there is no snow, the tourism industry is able to produce the white finery at the push of the button, thereby consuming large amounts of water. Studying Damüls, a well-known ski resort in Austria's westernmost province Vorarlberg, we can show that the development of a service sector within agro-pastoral landscapes was connected with novel water uses and massive interventions into Alpine landscapes. Human niche construction theory offers a unique avenue for studying the development of Alpine communities, but also highlights side effects accompanying the change from agrarian to tourism livelihoods. One aim of this paper is to broaden the scope of human niche construction theory. Inceptive, counteractive and relocational niche construction activities were coupled to the differentiation of actor groups. To incorporate social dynamics, indispensable for studies in environmental history, we propose the concept of socio-ecological niche construction. The paper investigates how villagers balanced resource limitations typical for an agrarian society with the differentiation of sub-niches, mediating selective forces on the population. When the valleys were industrialized, Damüls was almost given up as a permanent settlement. Then, tourists entered the stage, by and by turning the wheel of local development into a different direction. A tourism niche based on natural snow evolved from the 1930s onwards. While the socio-ecological niches of agriculture and tourism coexisted in the interwar years, this changed when ski lifts were built, embedded into a debt-based economy that made the tourism niche vulnerable to snow availability. Snow-dependency became a powerful selective force. It was mediated by the ski lift companies through a range of niche construction activities that turned water into an important resource of snowmaking systems.

Towards development of an operational snow on sea ice product

NASA Astrophysics Data System (ADS)

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

2017-12-01

Sea ice has been visibly changing over the past couple of decades; most notably the annual minimum extent which has shown a distinct downward, and recently accelerating, trend. September mean sea ice extent was over 7×106 km2 in the 1980's, but has averaged less than 5×106 km2 in the last decade. Should this loss continue, there will be wide-ranging impacts on marine ecosystems, coastal communities, prospects for resource extraction and marine activity, and weather conditions in the Arctic and beyond. While changes in the spatial extent of sea ice have been routinely monitored since the 1970s, less is known about how the thickness of the ice cover has changed. While estimates of ice thickness across the Arctic Ocean have become available over the past 20 years based on data from ERS-1/2, Envisat, ICESat, CryoSat-2 satellites and Operation IceBridge aircraft campaigns, the variety of these different measurement approaches, sensor technologies and spatial coverage present formidable challenges. Key among these is that measurement techniques do not measure ice thickness directly - retrievals also require snow depth and density. Towards that end, a sophisticated snow accumulation model is tested in a Lagrangian framework to map daily snow depths across the Arctic sea ice cover using atmospheric reanalysis data as input. Accuracy of the snow accumulation is assessed through comparison with Operation IceBridge data and ice mass balance buoys (IMBs). Impacts on ice thickness retrievals are further discussed.

Clovamide and Flavonoids from Leaves of Trifolium pratense and T. pratense subsp. nivale Grown in Italy.

PubMed

Tava, Aldo; Pecio, Łukasz; Stochmal, Anna; Pecetti, Luciano

2015-06-01

The phenolic content and composition in leaves of Trifolium pratense (red clover) and T. pratense subsp. nivale (snow clover) grown in Italy were evaluated by means of ultraperformance liquid chromatography (UPLC) coupled with photodiode array and mass spectrometry detectors. Compound identification was based on UV and MS data comparing results with those of reference compounds. Quantitative evaluation of all detected compounds was based on calibration curves obtained with available standards. Several phenolics were identified in both extracts, including clovamide, flavonols and isoflavones as their glycosilated and malonated derivatives. The total phenolic content was higher in red clover (53.7 ± 2.2 mg/g dry weight) than in snow clover (44.4 ± 4.9 mg/g dry weight). Red clover contained higher amounts of clovamide and isoflavones (15.6 ± 0.6 and 24.6 ± 1.6 mg/g dry weight, respectively) than snow clover (8.2 ± 0.1 mg/g and 16.9 ± 0.4 mg/g dry weight, respectively), while flavonols were quantified almost in the same amount in both extracts (13.2 ± 0.6 mg/g and 15.8 ± 0.6 mg/g dry weight in red clover and snow clover, respectively). Red clover was characterized by the presence of quercetin, formononetin and biochanin A derivatives as the most abundant flavonoids, whereas snow clover was characterized by higher amounts of quercetin and prunetin derivatives. This investigation, conducted for the first time on phenolics from T. pratense subsp. nivale, revealed the presence in this plant of several flavonoid derivatives the same as in T. pratense. The higher amount of prunetin in snow clover suggest a possible role of this isoflavone as a chemotaxonomic marker for this subspecies. Moreover, snow clover may represent an interesting new source of natural isoflavones with a different concentration pattern than in red clover.

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.

High Arctic summer warming tracked by increased Cassiope tetragona growth in the world's northernmost polar desert.

PubMed

Weijers, Stef; Buchwal, Agata; Blok, Daan; Löffler, Jörg; Elberling, Bo

2017-11-01

Rapid climate warming has resulted in shrub expansion, mainly of erect deciduous shrubs in the Low Arctic, but the more extreme, sparsely vegetated, cold and dry High Arctic is generally considered to remain resistant to such shrub expansion in the next decades. Dwarf shrub dendrochronology may reveal climatological causes of past changes in growth, but is hindered at many High Arctic sites by short and fragmented instrumental climate records. Moreover, only few High Arctic shrub chronologies cover the recent decade of substantial warming. This study investigated the climatic causes of growth variability of the evergreen dwarf shrub Cassiope tetragona between 1927 and 2012 in the northernmost polar desert at 83°N in North Greenland. We analysed climate-growth relationships over the period with available instrumental data (1950-2012) between a 102-year-long C. tetragona shoot length chronology and instrumental climate records from the three nearest meteorological stations, gridded climate data, and North Atlantic Oscillation (NAO) and Arctic Oscillation (AO) indices. July extreme maximum temperatures (JulT emx ), as measured at Alert, Canada, June NAO, and previous October AO, together explained 41% of the observed variance in annual C. tetragona growth and likely represent in situ summer temperatures. JulT emx explained 27% and was reconstructed back to 1927. The reconstruction showed relatively high growing season temperatures in the early to mid-twentieth century, as well as warming in recent decades. The rapid growth increase in C. tetragona shrubs in response to recent High Arctic summer warming shows that recent and future warming might promote an expansion of this evergreen dwarf shrub, mainly through densification of existing shrub patches, at High Arctic sites with sufficient winter snow cover and ample water supply during summer from melting snow and ice as well as thawing permafrost, contrasting earlier notions of limited shrub growth sensitivity to summer warming in the High Arctic. © 2017 John Wiley & Sons Ltd.

Key parameters governing the densification of cubic-Li7La3Zr2O12 Li+ conductors

NASA Astrophysics Data System (ADS)

Yi, Eongyu; Wang, Weimin; Kieffer, John; Laine, Richard M.

2017-06-01

Cubic-Li7La3Zr2O12 (LLZO) is regarded as one of the most promising solid electrolytes for the construction of inherently safe, next generation all-solid-state Li batteries. Unfortunately, sintering these materials to full density with controlled grain sizes, mechanical and electrochemical properties relies on energy and equipment intensive processes. In this work, we elucidate key parameters dictating LLZO densification by tracing the compositional and structural changes during processing calcined and ball-milled Al3+ doped LLZO powders. We find that the powders undergo ion (Li+/H+) exchange during room temperature processing, such that on heating, the protonated LLZO lattice collapses and crystallizes to its constituent oxides, leading to reaction driven densification at < 1000 °C, prior to sintering of LLZO grains at higher temperatures. It is shown that small particle sizes and protonation cannot be decoupled, and actually aid densification. We conclude that using fully decomposed nanoparticle mixtures, as obtained by liquid-feed flame spray pyrolysis, provides an ideal approach to use high surface and reaction energy to drive densification, resulting in pressureless sintering of Ga3+ doped LLZO thin films (25 μm) at 1130 °C/0.3 h to ideal microstructures (95 ± 1% density, 1.2 ± 0.2 μm average grain size) normally accessible only by pressure-assisted sintering. Such films offer both high ionic conductivity (1.3 ± 0.1 mS cm-1) and record low ionic area specific resistance (2 Ω cm2).

Understanding the densification process of Bi2Sr2CaCu2O x round wires with overpressure processing and its effect on critical current density

NASA Astrophysics Data System (ADS)

Matras, M. R.; Jiang, J.; Larbalestier, D. C.; Hellstrom, E. E.

2016-10-01

Overpressure (OP) processing increases the critical current density ({{\\boldsymbol{J}}}{{C}}) of Bi2Sr2CaCu2O x (2212) round wires by shrinking the surrounding Ag matrix around the 2212 filaments, driving them close to full density and greatly increasing the 2212 grain connectivity. Indeed densification is vital for attaining the highest {{\\boldsymbol{J}}}{{C}}. Here, we investigate the time and temperature dependence of the wire densification. We find that the wire diameter decreases by 3.8 ± 0.3% after full heat treatment at 50 atm and 100 atm OP. At 50 atm OP pressure, the filaments start densifying above 700 °C and reach a 3.30 ± 0.07% smaller diameter after 2 h at 820 °C, which is below the melting point of 2212 powder. The densification is homogeneous and does not change the filament shape before melting. The growth of non-superconducting phases is observed at 820 °C, suggesting that time should be minimized at high temperature prior to melting the 2212 powder. Study of an open-ended 2.2 m long wire sample shows that full densification and the high OP {{\\boldsymbol{J}}}{{C}} ({{\\boldsymbol{J}}}{{C}} varies by about 3.1 times over the 2.2 m long wire) is reached about 1 m from the open ends, thus showing that coil-length wires can be protected from leaky seals by adding at least 1 m of sacrificial wire at each end.

Enhancing the ABAQUS thermomechanics code to simulate multipellet steady and transient LWR fuel rod behavior

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

R. L. Williamson

A powerful multidimensional fuels performance analysis capability, applicable to both steady and transient fuel behavior, is developed based on enhancements to the commercially available ABAQUS general-purpose thermomechanics code. Enhanced capabilities are described, including: UO2 temperature and burnup dependent thermal properties, solid and gaseous fission product swelling, fuel densification, fission gas release, cladding thermal and irradiation creep, cladding irradiation growth, gap heat transfer, and gap/plenum gas behavior during irradiation. This new capability is demonstrated using a 2D axisymmetric analysis of the upper section of a simplified multipellet fuel rod, during both steady and transient operation. Comparisons are made between discrete andmore » smeared-pellet simulations. Computational results demonstrate the importance of a multidimensional, multipellet, fully-coupled thermomechanical approach. Interestingly, many of the inherent deficiencies in existing fuel performance codes (e.g., 1D thermomechanics, loose thermomechanical coupling, separate steady and transient analysis, cumbersome pre- and post-processing) are, in fact, ABAQUS strengths.« less

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

NASA Astrophysics Data System (ADS)

Li, Y.; Flanner, M.

2017-12-01

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

Historical record of European emissions of heavy metals to the atmosphere since the 1650s from alpine snow/ice cores drilled near Monte Rosa.

PubMed

Barbante, Carlo; Schwikowski, Margit; Döring, Thomas; Gäggeler, Heinz W; Schotterer, Ulrich; Tobler, Leo; van de Velde, Katja; Ferrari, Christophe; Cozzi, Giulio; Turetta, Andrea; Rosman, Kevin; Bolshov, Michael; Capodaglio, Gabriele; Cescon, Paolo; Boutron, Claude

2004-08-01

Cr, Cu, Zn, Co, Ni, Mo, Rh, Pd, Ag, Cd, Sb, Pt, Au, and U have been determined in clean room conditions by inductively coupled plasma sector field mass spectrometry and other analytical techniques, in various sections of two dated snow/ice cores from the high-altitude (4450 m asl) glacier saddle Colle Gnifetti, Monte Rosa massif, located in the Swiss-Italian Alps. These cores cover a 350-year time period, from 1650 to 1994. The results show highly enhanced concentrations for most metals in snow/ice dated from the second half of the 20th century, compared with concentrations in ancient ice dated from the 17th and 18th centuries. The highest increase factors from the pre-1700 period to the post-1970 period are observed for Cd (36), Zn (19), Bi (15), Cu (11), and Ni (9), confirming the importance of atmospheric pollution by heavy metals in Europe. Metal concentrations observed in Colle Gnifetti snow around 1980 appear to be quantitatively related to metal emissions from Italy, Switzerland, Germany, France, Belgium, and Austria at that time, making it possible to reconstruct past changes in metal emission in these countries during the last centuries.

Retrospective forecasts of the upcoming winter season snow accumulation in the Inn headwaters (European Alps)

NASA Astrophysics Data System (ADS)

Förster, Kristian; Hanzer, Florian; Stoll, Elena; Scaife, Adam A.; MacLachlan, Craig; Schöber, Johannes; Huttenlau, Matthias; Achleitner, Stefan; Strasser, Ulrich

2018-02-01

This article presents analyses of retrospective seasonal forecasts of snow accumulation. Re-forecasts with 4 months' lead time from two coupled atmosphere-ocean general circulation models (NCEP CFSv2 and MetOffice GloSea5) drive the Alpine Water balance and Runoff Estimation model (AWARE) in order to predict mid-winter snow accumulation in the Inn headwaters. As snowpack is hydrological storage that evolves during the winter season, it is strongly dependent on precipitation totals of the previous months. Climate model (CM) predictions of precipitation totals integrated from November to February (NDJF) compare reasonably well with observations. Even though predictions for precipitation may not be significantly more skilful than for temperature, the predictive skill achieved for precipitation is retained in subsequent water balance simulations when snow water equivalent (SWE) in February is considered. Given the AWARE simulations driven by observed meteorological fields as a benchmark for SWE analyses, the correlation achieved using GloSea5-AWARE SWE predictions is r = 0.57. The tendency of SWE anomalies (i.e. the sign of anomalies) is correctly predicted in 11 of 13 years. For CFSv2-AWARE, the corresponding values are r = 0.28 and 7 of 13 years. The results suggest that some seasonal prediction of hydrological model storage tendencies in parts of Europe is possible.

Memory versus irreversibility in the thermal densification of amorphous glasses

NASA Astrophysics Data System (ADS)

Ovadyahu, Z.

2017-06-01

We report on dynamic effects associated with thermally annealing amorphous indium-oxide films. In this process, the resistance of a given sample may decrease by several orders of magnitude at room temperatures, while its amorphous structure is preserved. The main effect of the process is densification, i.e., increased system density. The study includes the evolution of the system resistivity during and after the thermal treatment, the changes in the conductance noise, and the accompanying changes in the optical properties. The sample resistance is used to monitor the system dynamics during the annealing period as well as the relaxation that ensues after its termination. These reveal slow processes that fit well with a stretched-exponential law, a behavior that is commonly observed in structural glasses. There is an intriguing similarity between these effects and those obtained in high-pressure densification experiments. Both protocols exhibit the "slow spring-back" effect, a familiar response of memory foams. A heuristic picture based on a modified Lennard-Jones potential for the effective interparticle interaction is argued to qualitatively account for these densification-rarefaction phenomena in amorphous materials, whether affected by thermal treatment or by application of high pressure.

Comparative spring-staging ecology of sympatric arctic-nesting geese in south-central Nebraska

USGS Publications Warehouse

Pearse, Aaron T.; Krapu, Gary L.; Cox, Robert R.

2013-01-01

The Rainwater Basin in Nebraska has been a historic staging area for midcontinent greater white-fronted geese (Anser albifrons frontalis) since the 1950s and, in the mid-1990s, millions of midcontinent lesser snow geese (Chen caerulescens caerulescens) expanded their spring migration route to include this region. In response to speculation that snow geese may be in direct competition with white-fronted geese, we compared staging ecology by quantifying diet, habitat use, movement patterns, and time budgets during springs 1998–1999. Collected white-fronted geese (n  =  190) and snow geese (n  =  203) consumed primarily corn (Zea mays; 97–98% aggregate dry mass) while staging in Nebraska; thus, diet overlap was nearly complete. Both species used cornfields most frequently during the morning (54–55%) and wetlands more during the afternoon (51–65%). When found grouped together, snow goose abundance was greater than white-fronted goose abundance by an average of 57 times (se  =  11, n  =  131 groups) in crop fields and 28 times (se  =  9, n  =  84 groups) in wetlands. Snow geese and white-fronted geese flew similar distances between roosting and feeding sites, leaving and returning to wetland roost sties at similar times in mornings and afternoons. Overlap in habitat-specific time budgets was high; resting was the most common behavior on wetlands, and foraging was a common behavior in fields. We observed 111 interspecific agonistic interactions while observing white-fronted and snow geese. White-fronted geese initiated and dominated more interactions with other waterfowl species than did snow geese (32 vs. 14%). Certain aspects of spring-staging niches (i.e., diet, habitat use, movement patterns, and habitat-specific behavior) of white-fronted and snow geese overlapped greatly at this mid-latitude staging site, creating opportunity for potential food- and habitat-based competition between species. Snow geese did not consistently dominate interactions with white-fronted geese; yet large differences in their numbers coupled with high degrees of spatial, temporal, and ecological overlap support potential for exploitative competition during years when waste corn may be in short supply and dry years when few wetlands are available for staging waterfowl.

Collaborative Project. 3D Radiative Transfer Parameterization Over Mountains/Snow for High-Resolution Climate Models. Fast physics and Applications

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

Liou, Kuo-Nan

2016-02-09

Under the support of the aforementioned DOE Grant, we have made two fundamental contributions to atmospheric and climate sciences: (1) Develop an efficient 3-D radiative transfer parameterization for application to intense and intricate inhomogeneous mountain/snow regions. (2) Innovate a stochastic parameterization for light absorption by internally mixed black carbon and dust particles in snow grains for understanding and physical insight into snow albedo reduction in climate models. With reference to item (1), we divided solar fluxes reaching mountain surfaces into five components: direct and diffuse fluxes, direct- and diffuse-reflected fluxes, and coupled mountain-mountain flux. “Exact” 3D Monte Carlo photon tracingmore » computations can then be performed for these solar flux components to compare with those calculated from the conventional plane-parallel (PP) radiative transfer program readily available in climate models. Subsequently, Parameterizations of the deviations of 3D from PP results for five flux components are carried out by means of the multiple linear regression analysis associated with topographic information, including elevation, solar incident angle, sky view factor, and terrain configuration factor. We derived five regression equations with high statistical correlations for flux deviations and successfully incorporated this efficient parameterization into WRF model, which was used as the testbed in connection with the Fu-Liou-Gu PP radiation scheme that has been included in the WRF physics package. Incorporating this 3D parameterization program, we conducted simulations of WRF and CCSM4 to understand and evaluate the mountain/snow effect on snow albedo reduction during seasonal transition and the interannual variability for snowmelt, cloud cover, and precipitation over the Western United States presented in the final report. With reference to item (2), we developed in our previous research a geometric-optics surface-wave approach (GOS) for the computation of light absorption and scattering by complex and inhomogeneous particles for application to aggregates and snow grains with external and internal mixing structures. We demonstrated that a small black (BC) particle on the order of 1 μm internally mixed with snow grains could effectively reduce visible snow albedo by as much as 5–10%. Following this work and within the context of DOE support, we have made two key accomplishments presented in the attached final report.« less

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.

Assimilating AmeriFlux Site Data into the Community Land Model with Carbon-Nitrogen Coupling via the Ensemble Kalman Filter

NASA Astrophysics Data System (ADS)

Pettijohn, J. C.; Law, B. E.; Williams, M. D.; Stoeckli, R.; Thornton, P. E.; Hudiburg, T. M.; Thomas, C. K.; Martin, J.; Hill, T. C.

2009-12-01

The assimilation of terrestrial carbon, water and nutrient cycle measurements into land surface models of these processes is fundamental to improving our ability to predict how these ecosystems may respond to climate change. A combination of measurements and models, each with their own systematic biases, must be considered when constraining the nonlinear behavior of these coupled dynamics. As such, we use the sequential Ensemble Kalman Filter (EnKF) to assimilate eddy covariance (EC) and other site-level AmeriFlux measurements into the NCAR Community Land Model with Carbon-Nitrogen coupling (CLM-CN v3.5), run in single-column mode at a 30-minute time step, to improve estimates of relatively unconstrained model state variables and parameters. Specifically, we focus on a semi-arid ponderosa pine site (US-ME2) in the Pacific Northwest to identify the mechanisms by which this ecosystem responds to severe late summer drought. Our EnKF analysis includes water, carbon, energy and nitrogen state variables (e.g., 10 volumetric soil moisture levels (0-3.43 m), ponderosa pine and shrub evapotranspiration and net ecosystem exchange of carbon dioxide stocks and flux components, snow depth, etc.) and associated parameters (e.g., PFT-level rooting distribution parameters, maximum subsurface runoff coefficient, soil hydraulic conductivity decay factor, snow aging parameters, maximum canopy conductance, C:N ratios, etc.). The effectiveness of the EnKF in constraining state variables and associated parameters is sensitive to their relative frequencies, in that C-N state variables and parameters with long time constants require similarly long time series in the analysis. We apply the EnKF kernel perturbation routine to disrupt preliminary convergence of covariances, which has been found in recent studies to be a problem more characteristic of low frequency vegetation state variables and parameters than high frequency ones more heavily coupled with highly varying climate (e.g., shallow soil moisture, snow depth). Preliminary results demonstrate that the assimilation of EC and other available AmeriFlux site physical, chemical and biological data significantly helps quantify and reduce CLM-CN model uncertainties and helps to constrain ‘hidden’ states and parameters that are essential in the coupled water, carbon, energy and nutrient dynamics of these sites. Such site-level calibration of CLM-CN is an initial step in identifying model deficiencies and in forecasts of future ecosystem responses to climate change.

Monitoring the spatio-temporal evolution of the snow cover in the eastern Alps from MODIS data

NASA Astrophysics Data System (ADS)

Cianfarra, P.; Salvini, F.; Valt, M.

2009-04-01

Estimating the snow cover extent in mountain ranges is important for a wide variety purposes including of scientific studies, environmental and meteo-climatic applications, as well as predicting water availability for energy resource and agriculture. Moreover, the monitoring of the spatio-temporal variation of the snow cover thickness, coupled with ground data from weather stations, allows to identify avalanche risk areas after heavy snowfall. The aim of this study is to test an automatic procedure to identify and map the snow coverage for different altitude interval in the eastern part of the Alpine range. There has been much progress since 1966 when the first operational snow mapping was done by NOAA with spaceborne sensors that provide daily, global observations to monitor the variability in space and time in the extent of snow cover. MODIS sensors offer increased improvements relative to the AVHRR that has been operational for many years on the NOAA Polar Operational Environmental Satellite System. In this context the MODIS provides observations at a nominal spatial resolution of 500 m versus the 1.1 km spatial resolution of the AVHRR and continuously available (spatially and temporally), spectral band observation that span the visible and short-wave infrared wavelengths, including those useful for recognize snow cover. The other advantage of using MODIS data is its availability and cost by the NASA's server. In this work we used MOD02 (L1B) data providing calibrated radiance values at the sensor (without atmospheric correction). Snow cover map production included the following steps: selection of the images with clear sky conditions, geometric correction and georeferencing to UTM zone 32 ,WSG 84 ellipsoid, to eliminate the distortion of and the typical bow-tie effect that produces the observed not alignment of the scan lines in the row image; spatial sub setting to produce an image covering an area of about 200 x 120 km; identification of the snow cover was done by computing the Normalised Difference Snow Index (NDSI) knowing that snow reflectance is higher in the visible (0.5-0.7 mm) wavelengths and has lower reflectance in the short wave infrared (1-4 mm) wavelengths. This allowed to separate snow from clouds and other non-snow-covered pixels. The NDSI for MODIS images is defined as the difference of reflectances observed in the visible band 4 (0.555 mm) and the short wave infrared band 6 (1.640 mm) divided by the sum of the two reflectances: NDSI=(B4 - B6)/ (B4 + B6) This approach allowed to reduce (yet not totally eliminate) the influence of the atmospheric effects and lighting conditions. A series of thresholds were tested to the ratio image to establish the best value for snow cover identification. Eventually, the snow cover extent was computed for 6 altitude intervals. Results from the different processed images were compared and statistically analysed. A complete set of ground truth of these preliminary results is still missing; yet we are confident that once the tuning of the processing will be completed, the automated processing of MODIS data will provide low cost, near real-time estimates of the snow cover distribution over the eastern Alps. This product would be a valuable tool for public administrations and authorities for environmental protection, control and risk management.

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.

Enhanced densification under shock compression in porous silicon

NASA Astrophysics Data System (ADS)

Lane, J. Matthew D.; Thompson, Aidan P.; Vogler, Tracy J.

2014-10-01

Under shock compression, most porous materials exhibit lower densities for a given pressure than that of a full-dense sample of the same material. However, some porous materials exhibit an anomalous, or enhanced, densification under shock compression. We demonstrate a molecular mechanism that drives this behavior. We also present evidence from atomistic simulation that silicon belongs to this anomalous class of materials. Atomistic simulations indicate that local shear strain in the neighborhood of collapsing pores nucleates a local solid-solid phase transformation even when bulk pressures are below the thermodynamic phase transformation pressure. This metastable, local, and partial, solid-solid phase transformation, which accounts for the enhanced densification in silicon, is driven by the local stress state near the void, not equilibrium thermodynamics. This mechanism may also explain the phenomenon in other covalently bonded materials.

Concentrations and source regions of light-absorbing particles in snow/ice in northern Pakistan and their impact on snow albedo

NASA Astrophysics Data System (ADS)

Gul, Chaman; Praveen Puppala, Siva; Kang, Shichang; Adhikary, Bhupesh; Zhang, Yulan; Ali, Shaukat; Li, Yang; Li, Xiaofei

2018-04-01

Black carbon (BC), water-insoluble organic carbon (OC), and mineral dust are important particles in snow and ice which significantly reduce albedo and accelerate melting. Surface snow and ice samples were collected from the Karakoram-Himalayan region of northern Pakistan during 2015 and 2016 in summer (six glaciers), autumn (two glaciers), and winter (six mountain valleys). The average BC concentration overall was 2130 ± 1560 ng g-1 in summer samples, 2883 ± 3439 ng g-1 in autumn samples, and 992 ± 883 ng g-1 in winter samples. The average water-insoluble OC concentration overall was 1839 ± 1108 ng g-1 in summer samples, 1423 ± 208 ng g-1 in autumn samples, and 1342 ± 672 ng g-1 in winter samples. The overall concentration of BC, OC, and dust in aged snow samples collected during the summer campaign was higher than the concentration in ice samples. The values are relatively high compared to reports by others for the Himalayas and the Tibetan Plateau. This is probably the result of taking more representative samples at lower elevation where deposition is higher and the effects of ageing and enrichment are more marked. A reduction in snow albedo of 0.1-8.3 % for fresh snow and 0.9-32.5 % for aged snow was calculated for selected solar zenith angles during daytime using the Snow, Ice, and Aerosol Radiation (SNICAR) model. The daily mean albedo was reduced by 0.07-12.0 %. The calculated radiative forcing ranged from 0.16 to 43.45 W m-2 depending on snow type, solar zenith angle, and location. The potential source regions of the deposited pollutants were identified using spatial variance in wind vector maps, emission inventories coupled with backward air trajectories, and simple region-tagged chemical transport modeling. Central, south, and west Asia were the major sources of pollutants during the sampling months, with only a small contribution from east Asia. Analysis based on the Weather Research and Forecasting (WRF-STEM) chemical transport model identified a significant contribution (more than 70 %) from south Asia at selected sites. Research into the presence and effect of pollutants in the glaciated areas of Pakistan is economically significant because the surface water resources in the country mainly depend on the rivers (the Indus and its tributaries) that flow from this glaciated area.

Densification behavior of ceramic and crystallizable glass materials constrained on a rigid substrate

NASA Astrophysics Data System (ADS)

Calata, Jesus N.

2005-11-01

Constrained sintering is an important process for many applications. The sintering process almost always involves some form of constraint, both internal and external, such as rigid particles, reinforcing fibers and substrates to which the porous body adheres. The densification behavior of zinc oxide and cordierite-base crystallizable glass constrained on a rigid substrate was studied to add to the understanding of the behavior of various materials undergoing sintering when subjected to external substrate constraint. Porous ZnO films were isothermally sintered at temperatures between 900°C and 1050°C. The results showed that the densification of films constrained on substrates is severely reduced. This was evident in the sintered microstructures where the particles are joined together by narrower necks forming a more open structure, instead of the equiaxed grains with wide grain boundaries observed in the freestanding films. The calculated activation energies of densification were also different. For the density range of 60 to 64%, the constrained film had an activation energy of 391 +/- 34 kJ/mole compared to 242 +/- 21 kJ/mole for the freestanding film, indicating a change in the densification mechanism. In-plane stresses were observed during the sintering of the constrained films. Yielding of the films, in which the stresses dropped slight or remained unchanged, occurred at relative densities below 60% before the stresses climbed linearly with increasing density followed by a gradual relaxation. A substantial amount of the stresses remained after cooling. Free and constrained films of the cordierite-base crystallizable glass (glass-ceramic) were sintered between 900°C and 1000°C. The substrate constraint did not have a significant effect on the densification rate but the constrained films eventually underwent expansion. Calculations of the densification activation energy showed that, on average, it was close to 1077 kJ/mole, the activation energy of the glass, indicating that the prevailing mechanism was still viscous flow. The films expanded earlier and faster with increasing sintering temperature. The expansion was traced to the formation of pores at the interface with the silicon substrate and to a lesser extent on aluminum nitride. It was significantly reduced when the silicon substrate was pre-oxidized at 900°C, leading to the conclusion that the pore formation at the interface was due to poor wetting, which in turn was caused by the loss of the thin oxide layer through a reaction with the glass.

Effect of PF impregnation and surface densification on the mechanical properties of small-scale wood laminated poles

Treesearch

Huaqiang Yu; Chung Y. Hse; Zehui Jiang

2009-01-01

The wood poles in the United States are from high-valued trees that are becoming more expensive and less available. Wood laminated composite poles (LCP) are a kind of alternative to solid poles. Considerable interest has developed in last century in the resin impregnation and wood surface densification to improve its physical and mechanical properties. In this...

Effects of particle packing on the sintered microstructure

NASA Astrophysics Data System (ADS)

Barringer, E. A.; Bowen, H. K.

1988-04-01

The sintering process is shown to be critically dependent on particle-packing density and porosity uniformity. Sintering experiments were conducted on compacts consisting of monodisperse, spherical TiO2 particles. Densification kinetics and microstructure evolution for two initial packing densities, 55% and 69% of theoretical, were investigated. The lower-density compacts sintered rapidly to theoretical density, yet improved particle-packing density and uniformity significantly enhanced densification.

Use of silicon in liquid sintered silicon nitrides and sialons

DOEpatents

Raj, Rishi; Baik, Sunggi

1984-12-11

This invention relates to the production of improved high density nitrogen based ceramics by liquid-phase densification of silicon nitride or a compound of silicon-nitrogen-oxygen-metal, e.g. a sialon. In the process and compositions of the invention minor amounts of finely divided silicon are employed together with the conventional liquid phase producing additives to enhance the densification of the resultant ceramic.

Mechanisms and mechanics of shape loss during supersolidus liquid-phase sintering

NASA Astrophysics Data System (ADS)

Lal, Anand

Rapid sinter densification of relatively coarse prealloyed powders is possible by exceeding the solidus temperature in an approach termed supersolidus liquid phase sintering (SLPS). However, narrow processing windows for densification without distortion often limit this process. The liquid films at the grain boundaries that are responsible for densification also reduce the structural rigidity of components. Hence, components tend to slump under their own weight. Thus, the present study investigates shape loss during SLPS and rationalizes the processing and material factors with regard to separating densification from distortion. Experiments are performed on various prealloyed powders, including bronze, 316L stainless steel, and T15 tool steel. Differential thermal analysis, dilatometry, and in situ video imaging of sintering compacts are used to follow melting, densification, and distortion, respectively. Further, density and dimensional measurements are performed on sintered compacts. Results indicate a dependence of distortion on the sintering temperature and time, compact size, and melting behavior of the alloy. It is shown that the sintering temperature window, where high-density, precise components are obtained, can be widened for 316L stainless steel by boron addition. For the first time, a beam bending technique is used to measure the macroscopic apparent viscosity of semisolid bronze. The viscosity drops with temperature above the solidus and lies in the range of 108 to 106 Pa-s. Additionally, the in situ transverse rupture strength of bronze is measured to demonstrate the softening above the solidus temperature. Further, microstructural measurements are performed to enable correlation with the slumping behavior and viscosity. A model combining the deformation mechanisms, driving forces, and microstructural characteristics is developed to predict the conditions for densification and distortion onset. The microstructure is also correlated with the magnitude of shape loss and viscosity of a semisolid aggregate. A mechanistic model, based on the semisolid rheological characteristics, is developed to predict the magnitude and nature of shape loss. The model shows good correlation with experimental data for bronze. This study offers critical insight into SLPS and provides processing strategies for fabrication of high-density components without shape loss.

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.

Assimilation of Remotely-Sensed Snow information to improve streamflow predictions in the Southwestern US

NASA Astrophysics Data System (ADS)

López-Burgos, V.; Rajagopal, S.; Martinez Baquero, G. F.; Gupta, H. V.

2009-12-01

Rapidly growing population in the southwestern US is leading to increasing demand and decreasing availability of water, requiring a detailed quantification of hydrological processes. The integration of detailed spatial information of water fluxes from remote sensing platforms, and hydrological models coupled with ground based data is an important step towards this goal. This project is exploring the use of Snow Water Equivalent (SWE) estimates to update the snow component of the Variable Infiltration Capacity model (VIC). SWE estimates are obtained by combining SNOTEL data with MODIS Snow Cover Area (SCA) information. Because, cloud cover corrupts the estimates of SCA, a rule-based method is used to clean up the remotely sensed images. The rules include a time interpolation method, and the probability of a pixel for been covered with snow based on the relationships between elevation, temperature, lapse rate, aspect and topographic shading. The approach is used to improve streamflow predictions on two rivers managed by the Salt River Project, a water and energy supplier in central Arizona. This solution will help improve the management of reservoirs in the Salt and Verde River in Phoenix, Arizona (tributaries of the lower Colorado River basin), by incorporating physically based distributed models and remote sensing observations into their Decision Support Tools and planning tools. This research seeks to increase the knowledge base used to manage reservoirs and groundwater resources in a region affected by a long-term drought. It will be applicable and relevant for other water utility companies facing the challenges of climate change and decreasing water resources.

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.

Tailored Net-Shape Powder Composites by Spark Plasma Sintering

NASA Astrophysics Data System (ADS)

Khaleghi, Evan Aryan

This dissertation investigates the ability to produce net-shape and tailored composites in spark plasma sintering (SPS), with an analysis of how grain growth, densification, and mechanical properties are affected. Using alumina and four progressively anisotropic dies, we studied the impact of specimen shape on densification. We found specimen shape had an impact on overall densification, but no impact on localized properties. We expected areas of the specimen to densify differently, or have higher grain growth, based on current anisotropy in the specimen during sintering, and preliminary results indicated this, but further investigation showed this did not occur. Overall average grain size and porosity decreased as shape complexity increased. In Fe-V-C steel, we mechanical alloyed two rapidly solidified powders, and used spark sintering to retain the properties imparted during the rapid solidification. We noticed VC grains being produced during densification, which improved the final properties. We conducted spark plasma extrusion (SPE) of aluminum to understand the effect on microstructure. We found, through an analysis of the grain structure, that SPE did have a grain deformation potential, and grain size was severely decreased compared to conventional sintering. Dynamic recrystallization did not occur, due to the reduced temperatures we were able to extrude with SPS. Finally, we examined whether there were particular sintering conditions for SPS that reduced the complexity of the grain growth and porosity relationship to one similar to conventional sintering, of the form G = k G0 ε -1/. We found that although a reasonable case could be made for free sintering, as found in the literature, for hot-pressing and SPS the conditions required go against the common knowledge in grain growth and densification kinetics. We were able to fit our data very well to the model, but the correlated results do not make physical sense.

Use of silicon in liquid sintered silicon nitrides and sialons

DOEpatents

Raj, R.; Baik, S.

1984-12-11

This invention relates to the production of improved high density nitrogen based ceramics by liquid-phase densification of silicon nitride or a compound of silicon-nitrogen-oxygen-metal, e.g. a sialon. In the process and compositions of the invention minor amounts of finely divided silicon are employed together with the conventional liquid phase producing additives to enhance the densification of the resultant ceramic. 4 figs.

Use of free silicon in liquid phase sintering of silicon nitrides and sialons

DOEpatents

Raj, R.; Baik, S.

1985-11-12

This invention relates to the production of improved high density nitrogen based ceramics by liquid-phase densification of silicon nitride or a compound of silicon-nitrogen-oxygen-metal, e.g. a sialon. In the process and compositions of the invention minor amounts of finely divided silicon are employed together with the conventional liquid phase producing additives to enhance the densification of the resultant ceramic. 4 figs.

Use of free silicon in liquid phase sintering of silicon nitrides and sialons

DOEpatents

Raj, Rishi; Baik, Sunggi

1985-11-12

This invention relates to the production of improved high density nitrogen based ceramics by liquid-phase densification of silicon nitride or a compound of silicon-nitrogen-oxygen-metal, e.g. a sialon. In the process and compositions of the invention minor amounts of finely divided silicon are employed together with the conventional liquid phase producing additives to enhance the densification of the resultant ceramic.

Physical and chemical evaluation of furniture waste briquettes.

PubMed

Moreno, Ana Isabel; Font, Rafael; Conesa, Juan A

2016-03-01

Furniture waste is mainly composed of wood and upholstery foam (mostly polyurethane foam). Both of these have a high calorific value, therefore, energy recovery would be an appropriate process to manage these wastes. Nevertheless, the drawback is that the energy content of these wastes is limited due to their low density mainly that of upholstery foam. Densification of separate foam presents difficulties due to its elastic character. The significance of this work lies in obtaining densified material by co-densification of furniture wood waste and polyurethane foam waste. Densification of furniture wood and the co-densification of furniture wood waste with polyurethane foam have been studied. On the one hand, the parameters that have an effect on the quality of the furniture waste briquettes have been analysed, i.e., moisture content, compaction pressure, presence of lignin, etc. The maximum weight percentage of polyurethane foam that can be added with furniture wood waste to obtain durable briquettes and the optimal moisture were determined. On the other hand, some parameters were analysed in order to evaluate the possible effect on the combustion. The chemical composition of waste wood was compared with untreated wood biomass; the higher nitrogen content and the concentration of some metals were the most important differences, with a significant difference of Ti content. Copyright © 2016 Elsevier Ltd. All rights reserved.

Finite element method analysis of cold forging for deformation and densification of Mo alloyed sintered steel

NASA Astrophysics Data System (ADS)

Kamakoshi, Y.; Nishida, S.; Kanbe, K.; Shohji, I.

2017-10-01

In recent years, powder metallurgy (P/M) materials have been expected to be applied to automobile products. Then, not only high cost performance but also more strength, wear resistance, long-life and so on are required for P/M materials. As an improvement method of mechanical properties of P/M materials, a densification is expected to be one of effective processes. In this study, to examine behaviours of the densification of Mo-alloyed sintered steel in a cold-forging process, finite element method (FEM) analysis was performed. Firstly, a columnar specimen was cut out from the inner part of a sintered specimen and a load-stroke diagram was obtained by the compression test. 2D FEM analysis was performed using the obtained load-stroke diagram. To correct the errors of stress between the porous mode and the rigid-elastic mode of analysis software, the analysis of a polynominal approximation was performed. As a result, the modified true stress-true strain diagram was obtained for the sintered steel with the densification. Afterwards, 3D FEM analysis of backward extrusion was carried out using the modified true stress-true strain diagram. It was confirmed that both the shape and density of the sintered steel analyzed by new FEM analysis that we suggest correspond well with experimental ones.

Processing, characterization, and in vitro/in vivo evaluations of powder metallurgy processed Ti-13Nb-13Zr alloys.

PubMed

Bottino, Marco C; Coelho, Paulo G; Henriques, Vinicius A R; Higa, Olga Z; Bressiani, Ana H A; Bressiani, José C

2009-03-01

This article presents details of processing, characterization and in vitro as well as in vivo evaluations of powder metallurgy processed Ti-13Nb-13Zr samples with different levels of porosity. Sintered samples were characterized for density, crystalline phases (XRD), and microstructure (SEM and EDX). Samples sintered at 1000 degrees C showed the highest porosity level ( approximately 30%), featuring open and interconnected pores ranging from 50 to 100 mum in diameter but incomplete densification. In contrast, samples sintered at 1300 and 1500 degrees C demonstrated high densification with 10% porosity level distributed in a homogeneous microstructure. The different sintering conditions used in this study demonstrated a coherent trend that is increase in temperature lead to higher sample densification, even though densification represents a drawback for bone ingrowth. Cytotoxicity tests did not reveal any toxic effects of the starting and processed materials on surviving cell percentage. After an 8-week healing period in rabbit tibias, the implants were retrieved, processed for nondecalcified histological evaluation, and then assessed by backscattered electron images (BSEI-SEM) and EDX. Bone growth into the microstructure was observed only in samples sintered at 1000 degrees C. Overall, a close relation between newly formed bone and all processed samples was observed. (c) 2008 Wiley Periodicals, Inc.

Correlation between triple phase boundary and the microstructure of Solid Oxide Fuel Cell anodes: The role of composition, porosity and Ni densification

NASA Astrophysics Data System (ADS)

Lu, Xuekun; Heenan, Thomas M. M.; Bailey, Josh J.; Li, Tao; Li, Kang; Brett, Daniel J. L.; Shearing, Paul R.

2017-10-01

This study aims to correlate the active triple phase boundaries (TPBs) to the variation of as-prepared anode microstructures and Ni densifications based on the reconstructed 3D volume of an SOFC anode, providing a point of comparison with theoretical studies that reveal the relationship of TPBs and the material microstructure using randomly packed spheres models. The TPB degradation mechanisms are explained using a particle network model. The results indicate that in low porosity regime, the TPBs sharply increase with the porosity until the percolation threshold (10%); at intermediate porosity (10%-25%), a balance of surface area between three phases is more critical than that of volume fraction to reach the optimal TPB density; in the high porosity regime (>25%), the TPBs start to drop due to the shrinkage and detachment of Ni/YSZ interfaces. The TPB density is inversely proportional to the degree of Ni densification as long as the Ni content is above the percolation threshold (35%) and can be improved by 70% within 7% change of porosity provided that the over-densification is mitigated. This has implications for the design of SOFC microstructures as well for electrode durability, where Ni agglomeration is known to deleteriously impact long-term operation.

Influence of crystal habit on the compression and densification mechanism of ibuprofen

NASA Astrophysics Data System (ADS)

Di Martino, Piera; Beccerica, Moira; Joiris, Etienne; Palmieri, Giovanni F.; Gayot, Anne; Martelli, Sante

2002-08-01

Ibuprofen was recrystallized from several solvents by two different methods: addition of a non-solvent to a drug solution and cooling of a drug solution. Four samples, characterized by different crystal habit, were selected: sample A, sample E and sample T, recrystallized respectively from acetone, ethanol and THF by addition of water as non-solvent and sample M recrystallized from methanol by temperature decrease. By SEM analysis, sample were characterized with the respect of their crystal habit, mean particle diameter and elongation ratio. Sample A appears stick-shaped, sample E acicular with lamellar characteristics, samples T and M polyhedral. DSC and X-ray diffraction studies permit to exclude a polymorphic modification of ibuprofen during crystallization. For all samples micromeritics properties, densification behaviour and compression ability was analysed. Sample M shows a higher densification tendency, evidenciated by its higher apparent and tapped particle density. The ability to densificate is also pointed out by D0' value of Heckel's plot, which indicate the rearrangement of original particles at the initial stage of compression. This fact is related to the crystal habit of sample M, which is characterized by strongly smoothed coins. The increase in powder bed porosity permits a particle-particle interaction of greater extent during the subsequent stage of compression, which allows higher tabletability and compressibility.

Hot isostatic pressing (HIP) of powder mixtures and composites: Packing, densification, and microstructural effects

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

Li, E.K.H.; Funkenbusch, P.D.

1993-06-01

Hot isostatic pressing (HIP) of powder mixtures (containing differently sized components) and of composite powders is analyzed. Recent progress, including development of a simple scheme for estimating radial distribution functions, has made modeling of these systems practical. Experimentally, powders containing bimodal or continuous size distributions are observed to hot isostatically press to a higher density tinder identical processing conditions and to show large differences in the densification rate as a function of density when compared with the monosize powders usually assumed for modeling purposes. Modeling correctly predicts these trends and suggests that they can be partially, but not entirely, attributedmore » to initial packing density differences. Modeling also predicts increased deformation in the smaller particles within a mixture. This effect has also been observed experimentally and is associated with microstructural changes, such as preferential recrystallization of small particles. Finally, consolidation of a composite mixture containing hard, but deformable, inclusions has been modeled for comparison with existing experimental data. Modeling results match both the densification and microstructural observations reported experimentally. Densification is retarded due to contacts between the reinforcing particles which support a significant portion of the applied pressure. In addition, partitioning of deformation between soft matrix and hard inclusion powders results in increased deformation of the softer material.« less

How snowpack heterogeneity affects diurnal streamflow timing

USGS Publications Warehouse

Lundquist, J.D.; Dettinger, M.D.

2005-01-01

Diurnal cycles of streamflow in snow-fed rivers can be used to infer the average time a water parcel spends in transit from the top of the snowpack to a stream gauge in the river channel. This travel time, which is measured as the difference between the hour of peak snowmelt in the afternoon and the hour of maximum discharge each day, ranges from a few hours to almost a full day later. Travel times increase with longer percolation times through deeper snowpacks, and prior studies of small basins have related the timing of a stream's diurnal peak to the amount of snow stored in a basin. However, in many larger basins the time of peak flow is nearly constant during the first half of the melt season, with little or no variation between years. This apparent self-organization at larger scales can be reproduced by employing heterogeneous observations of snow depths and melt rates in a model that couples porous medium flow through an evolving snowpack with free surface flow in a channel. Copyright 2005 by the American Geophysical Union.

High-resolution dynamic downscaling of CMIP5 output over the Tropical Andes

NASA Astrophysics Data System (ADS)

Reichler, Thomas; Andrade, Marcos; Ohara, Noriaki

2015-04-01

Our project is targeted towards making robust predictions of future changes in climate over the tropical part of the South American Andes. This goal is challenging, since tropical lowlands, steep mountains, and snow covered subarctic surfaces meet over relatively short distances, leading to distinct climate regimes within the same domain and pronounced spatial gradients in virtually every climate quantity. We use an innovative approach to solve this problem, including several quadruple nested versions of WRF, a systematic validation strategy to find the version of WRF that best fits our study region, spatial resolutions at the kilometer scale, 20-year-long simulation periods, and bias-corrected output from various CMIP5 simulations that also include the multi-model mean of all CMIP5 models. We show that the simulated changes in climate are consistent with the results from the global climate models and also consistent with two different versions of WRF. We also discuss the expected changes in snow and ice, derived from off-line coupling the regional simulations to a carefully calibrated snow and ice model.

Coupling a glacier evolution model and a hydrological model to simulate future runoff scenarios in the Oetztal Alps, Austria

NASA Astrophysics Data System (ADS)

Stoll, Elena; Oesterle, Felix; Hanzer, Florian; Nemec, Johanna; Berlin, Stefan; Schöber, Johannes; Huttenlau, Matthias; Strasser, Ulrich; Achleitner, Stefan; Förster, Kristian

2017-04-01

Fluctuations of glacier and snow runoff play a key role in water management of alpine catchments. Consequently, the catchment water balance is strongly influenced by the variability of the seasonal snow cover and the glacier melt. The huge water storages enable a shift of the hydrological response of glaciers across time scales, leading to response times in the range of decades. In the future, an initial increase of water availability connected to higher temperatures and respective melt rates is expected to turn into a decrease as the glaciers dwindle. One key question is to predict the "moment of peak discharge" when water availability will start to decrease as a consequence of the reduction of glacierized areas. To assess the influence of a warming climate on runoff regimes of glaciated catchments, we couple a simple glacier evolution model (GEM), based on a statistical approach, with a semi-distributed hydrological model (HQsim). Climate scenarios are taken from downscaled EURO-CORDEX data for the scenarios RCP2.6, RCP4.5, and RCP8.5, respectively. The results indicate that the impact of the glaciers on runoff regimes will very likely change towards the second half of the 21st century. Given the scenarios in which most glaciers will attain their minimum extent and sustain only at high elevation levels, the resulting runoff regime is dominated by precipitation and seasonal snow cover, since the "moment of peak discharge" is assumed to occur in the first half of the 21st century.

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

Analysis of the spatial and temporal variability of mountain snowpack and terrestrial water storage in the Upper Snake River, USA

EPA Science Inventory

The spatial and temporal relationships of winter snowpack and terrestrial water storage (TWS) in the Upper Snake River were analyzed for water years 2001–2010 at a monthly time step. We coupled a regionally validated snow model with gravimetric measurements of the Earth’s water...

Data-model integration to interpret connectivity between biogeochemical cycling, and vegetation phenology and productivity in mountainous ecosystems under changing hydrologic regimes

NASA Astrophysics Data System (ADS)

Brodie, E.; Arora, B.; Beller, H. R.; Bill, M.; Bouskill, N.; Chakraborty, R.; Conrad, M. E.; Dafflon, B.; Enquist, B. J.; Falco, N.; Henderson, A.; Karaoz, U.; Polussa, A.; Sorensen, P.; Steltzer, H.; Wainwright, H. M.; Wang, S.; Williams, K. H.; Wilmer, C.; Wu, Y.

2017-12-01

In mountainous systems, snow-melt is associated with a large pulse of nutrients that originates from under-snow microbial mineralization of organic matter and microbial biomass turnover. Vegetation phenology in these systems is regulated by environmental cues such as air temperature ranges and photoperiod, such that, under typical conditions, vegetation greening and nutrient uptake occur in sync with microbial biomass turnover and nutrient release, closing nutrient cycles and enhancing nutrient retention. However, early snow-melt has been observed with increasing frequency in the mountainous west and is hypothesized to disrupt coupled plant-microbial behavior, potentially resulting in a temporal discontinuity between microbial nutrient release and vegetation greening. As part of the Watershed Function Scientific Focus Area (SFA) at Berkeley Lab we are quantifying below-ground biogeochemistry and above-ground phenology and vegetation chemistry and their relationships to hydrologic events at a lower montane hillslope in the East River catchment, Crested Butte, CO. This presentation will focus on data-model integration to interpret connectivity between biogeochemical cycling of nitrogen and vegetation nitrogen demand. Initial model results suggest that early snow-melt will result in an earlier accumulation and leaching loss of nitrate from the upper soil depths but that vegetation productivity may not decline as traits such as greater rooting depth and resource allocation to stems are favored.

Trace metal concentrations of surface snow from Ingrid Christensen Coast, East Antarctica--spatial variability and possible anthropogenic contributions.

PubMed

Thamban, Meloth; Thakur, Roseline C

2013-04-01

To investigate the distribution and source pathways of environmentally critical trace metals in coastal Antarctica, trace elemental concentrations were analyzed in 36 surface snow samples along a coast to inland transect in the Ingrid Christensen Coast of East Antarctica. The samples were collected and analyzed using the clean protocols and an inductively coupled plasma mass spectrometer. Within the coastal ice-free and ice-covered region, marine elements (Na, Ca, Mg, K, Li, and Sr) revealed enhanced concentrations as compared with inland sites. Along with the sea-salt elements, the coastal ice-free sites were also characterized by enhanced concentrations of Al, Fe, Mn, V, Cr, and Zn. The crustal enrichment factors (Efc) confirm a dominant crustal source for Fe and Al and a significant source for Cr, V, Co, and Ba, which clearly reflects the influence of petrological characteristics of the Larsemann Hills on the trace elemental composition of surface snow. The Efc of elements revealed that Zn, Cu, Mo, Cd, As, Se, Sb, and Pb are highly enriched compared with the known natural sources, suggesting an anthropogenic origin for these elements. Evaluation of the contributions to surface snow from the different sources suggests that while contribution from natural sources is relatively significant, local contamination from the increasing research station and logistic activities within the proximity of study area cannot be ignored.

Greenland snow evidence of large scale atmospheric contamination for platinum, palladium, and rhodium.

PubMed

Barbante, C; Veysseyre, A; Ferrari, C; van de Velde, K; Morel, C; Capodaglio, G; Cescon, P; Scarponi, G; Boutron, C

2001-03-01

Since 1976 in the United States, Canada, and Japan, and later in other countries, the exhaust system of gasoline powered cars has been equipped with catalytic converters containing Pt and/or Pd and/or Rh. This has resulted in a very significant decrease in urban air pollution for various chemical species such as NOx, CO, and hydrocarbons. There has however been concern that their ever increasing use might lead to Platinum Group Metals (PGMs) becoming widely dispersed in the environment. From the analysis of Pt, Pd, and Rh in central Greenland recent snow and ancient ice using the ultrasensitive inductively coupled plasma sector field mass spectrometry technique, we show here that the concentrations of these metals in snow dated from the mid 1990s are indeed approximately 40-120 times higher than in ice dated from 7000 years ago. The fact that such an increase is observed far away from populated areas at a high altitude location indicates there is now a large scale contamination of the troposphere of the Northern Hemisphere for PGMs. Pt/Rh mass ratio in the most recent snow samples is close to the same ratio documented for catalytic converter exhausts in a recent study, which suggests that a large fraction of the recent increase for Pt and Rh might originate from automobile catalytic converters.

California's Snow Gun and its implications for mass balance predictions under greenhouse warming

NASA Astrophysics Data System (ADS)

Howat, I.; Snyder, M.; Tulaczyk, S.; Sloan, L.

2003-12-01

Precipitation has received limited treatment in glacier and snowpack mass balance models, largely due to the poor resolution and confidence of precipitation predictions relative to temperature predictions derived from atmospheric models. Most snow and glacier mass balance models rely on statistical or lapse rate-based downscaling of general or regional circulation models (GCM's and RCM's), essentially decoupling sub-grid scale, orographically-driven evolution of atmospheric heat and moisture. Such models invariably predict large losses in the snow and ice volume under greenhouse warming. However, positive trends in the mass balance of glaciers in some warming maritime climates, as well as at high elevations of the Greenland Ice Sheet, suggest that increased precipitation may play an important role in snow- and glacier-climate interactions. Here, we present a half century of April snowpack data from the Sierra Nevada and Cascade mountains of California, USA. This high-density network of snow-course data indicates that a gain in winter snow accumulation at higher elevations has compensated loss in snow volume at lower elevations by over 50% and has led to glacier expansion on Mt. Shasta. These trends are concurrent with a region-wide increase in winter temperatures up to 2° C. They result from the orographic lifting and saturation of warmer, more humid air leading to increased precipitation at higher elevations. Previous studies have invoked such a "Snow Gun" effect to explain contemporaneous records of Tertiary ocean warming and rapid glacial expansion. A climatological context of the California's "snow gun" effect is elucidated by correlation between the elevation distribution of April SWE observations and the phase of the Pacific Decadal Oscillation and the El Nino Southern Oscillation, both controlling the heat and moisture delivered to the U.S. Pacific coast. The existence of a significant "Snow Gun" effect presents two challenges to snow and glacier mass balance modeling. Firstly, the link between amplification of orographic precipitation and the temporal evolution of ocean-climate oscillations indicates that prediction of future mass balance trends requires consideration of the timing and amplitude of such oscillations. Only recently have ocean-atmosphere models begun to realistically produce such temporal variability. Secondly, the steepening snow mass-balance elevation-gradient associated with the "Snow Gun" implies greater spatial variability in balance with warming. In a warming climate, orographic processes at a scale finer that the highest resolution RCM (>20km grid) become increasingly important and predictions based on lower elevations become increasingly inaccurate for higher elevations. Therefore, thermodynamic interaction between atmospheric heat, moisture and topography must be included in downscaling techniques. In order to demonstrate the importance of the thermodynamic downscaling in mass balance predictions, we nest a high-resolution (100m grid), coupled Orographic Precipitation and Surface Energy balance Model (OPSEM) into the RegC2.5 RCM (40 km grid) and compare results. We apply this nesting technique to Mt. Shasta, California, an area of high topography (~4000m) relative to its RegCM2.5 grid elevation (1289m). These models compute average April snow volume under present and doubled-present Atmospheric CO2 concentrations. While the RegCM2.5 regional model predicts an 83% decrease in April SWE, OPSEM predicts a 16% increase. These results indicate that thermodynamic interactions between the atmosphere and topography at sub- RCM grid resolution must be considered in mass balance models.

Infrasound and seismic array analysis of snow avalanches: results from the 2015-2017 experiment in Dischma valley above Davos, Switzerland

NASA Astrophysics Data System (ADS)

Marchetti, Emanuele; van Herwijnen, Alec; Ripepe, Maurizio

2017-04-01

While flowing downhill a snow avalanche radiates seismic and infrasonic waves being coupled both with the ground and the atmosphere. Infrasound waves are mostly generated by the powder cloud of the avalanche, while seismic waves are mostly generated by the dense flowing snow mass on the ground, resulting in different energy partitioning between seismic and infrasound for different kinds of avalanches. This results into a general uncertainty on the efficiency of seismic and infrasound monitoring, in terms of the size and source-to-receiver distance of detectable events. Nevertheless, both seismic and infrasound have been used as monitoring systems for the remote detection of snow avalanches, being the reliable detection of snow avalanches of crucial importance to better understand triggering mechanisms, identify possible precursors, or improve avalanche forecasting. We present infrasonic and seismic array data collected during the winters of 2015- 2016 and 2016-2017 in the Dischma valley above Davos, Switzerland, where a five element infrasound array and a 7 element seismic array had been deployed at short distance from each other and with several avalanche paths nearby. Avalanche observation in the area is performed through automatic cameras providing additional information on the location, type (dry or wet), size and occurrence time of the avalanches released. The use of arrays instead of single sensors allows increasing the signal-to-noise ratio and identifying events in terms of back-azimuth and apparent velocity of the wave-field, thus providing indication on the source position of the recorded signal. For selected snow avalanches captured with automatic cameras, we therefore perform seismic and infrasound array processing to constrain the avalanche path and dynamics and investigate the partitioning of seismic and infrasound energy for the different portions of the avalanche path. Moreover we compare results of seismic and infrasound array processing for the whole 2015-2016 winter season in order to investigate the ability of the two monitoring systems to identify and characterize snow avalanches and the benefit of the combined seismo-acoustic analysis.

Quantifying Temperature Effects on Snow, Plant and Streamflow Dynamics in Headwater Catchments

NASA Astrophysics Data System (ADS)

Wainwright, H. M.; Sarah, T.; Siirila-Woodburn, E. R.; Newcomer, M. E.; Williams, K. H.; Hubbard, S. S.; Enquist, B. J.; Steltzer, H.; Carroll, R. W. H.

2017-12-01

Quantifying Temperature Effects on Snow, Plant and Streamflow Dynamics in Headwater Catchments Snow-dominated headwater catchments are critical for water resource throughout the world; particularly in Western US. Under climate change, temperature increases are expected to be amplified in mountainous regions. We use a data-driven approach to better understand the coupling among inter-annual variability in temperature, snow and plant community dynamics and stream discharge. We apply data mining methods (e.g., principal component analysis, random forest) to historical spatiotemporal datasets, including the SNOTEL data, Landsat-based normalized difference vegetation index (NDVI) and airborne LiDAR-based snow distribution. Although both snow distribution and NDVI are extremely heterogeneous spatially, the inter-annual variability and temporal responses are spatially consistent, providing an opportunity to quantify the effect of temperature in the catchment-scale. We demonstrate our approach in the East River Watershed of the Upper Colorado River Basin, including Rocky Mountain Biological Laboratory, where the changes in plant communities and their dynamics have been extensively documented. Results indicate that temperature - particularly spring temperature - has a significant control not only on the timing of snowmelt, plant NDVI and peak flow but also on the magnitude of peak NDVI, peak flow and annual discharge. Monthly temperature in spring explains the variability of snowmelt by the equivalent standard deviation of 3.4-4.4 days, and total discharge by 10-11%. In addition, the high correlation among June temperature, peak NDVI and annual discharge suggests a primary role of spring evapotranspiration on plant community phenology, productivity, and streamflow volume. On the other hand, summer monsoon precipitation does not contribute significantly to annual discharge, further emphasizing the importance of snowmelt. This approach is mostly based on a set of datasets typically available throughout the US, providing a powerful approach to link remote sensing techniques with long-term monitoring of temperature, snowfall, plant, and streamflow dynamics.

Optimal Base Station Density of Dense Network: From the Viewpoint of Interference and Load.

PubMed

Feng, Jianyuan; Feng, Zhiyong

2017-09-11

Network densification is attracting increasing attention recently due to its ability to improve network capacity by spatial reuse and relieve congestion by offloading. However, excessive densification and aggressive offloading can also cause the degradation of network performance due to problems of interference and load. In this paper, with consideration of load issues, we study the optimal base station density that maximizes the throughput of the network. The expected link rate and the utilization ratio of the contention-based channel are derived as the functions of base station density using the Poisson Point Process (PPP) and Markov Chain. They reveal the rules of deployment. Based on these results, we obtain the throughput of the network and indicate the optimal deployment density under different network conditions. Extensive simulations are conducted to validate our analysis and show the substantial performance gain obtained by the proposed deployment scheme. These results can provide guidance for the network densification.

Silicon nitride-aluminum oxide solid solution (SiAION) formation and densification by pressure sintering

NASA Technical Reports Server (NTRS)

Yeh, H. C.; Sanders, W. A.; Fiyalko, J. L.

1975-01-01

Stirred-ball-mill-blended Si3N4 and Al2O3 powders were pressure sintered in order to investigate the mechanism of solid solution formation and densification in the Si3N4-Al2O3 system. Powder blends with Si3N4:Al2O3 mole ratios of 4:1, 3:2, and 2:3 were pressure sintered at 27.6-MN/sq m pressure at temperatures to 17000 C (3090 F). The compaction behavior of the powder blends during pressure sintering was determined by observing the density of the powder compact as a function of temperature and time starting from room temperature. This information, combined with the results of X-ray diffraction and metallographic analyses regarding solutioning and phase transformation phenomena in the Si3N4-Al2O3 system, was used to describe the densification behavior.

Enhanced densification under shock compression in porous silicon

DOE PAGES

Lane, J. Matthew; Thompson, Aidan Patrick; Vogler, Tracy

2014-10-27

Under shock compression, most porous materials exhibit lower densities for a given pressure than that of a full-dense sample of the same material. However, some porous materials exhibit an anomalous, or enhanced, densification under shock compression. The mechanism driving this behavior was not completely determined. We present evidence from atomistic simulation that pure silicon belongs to this anomalous class of materials and demonstrate the associated mechanisms responsible for the effect in porous silicon. Atomistic response indicates that local shear strain in the neighborhood of collapsing pores catalyzes a local solid-solid phase transformation even when bulk pressures are below the thermodynamicmore » phase transformation pressure. This metastable, local, and partial, solid-solid phase transformation, which accounts for the enhanced densification in silicon, is driven by the local stress state near the void, not equilibrium thermodynamics. This mechanism may also explain the phenomenon in other covalently bonded materials.« less

Fabrication and characterization of Si3N4 ceramics without additives by high pressure hot pressing

NASA Technical Reports Server (NTRS)

Shimada, M.; Tanaka, A.; Yamada, T.; Koizumi, M.

1984-01-01

High pressure hot-pressing of Si3N4 without additives was performed using various kinds of Si3N4 powder as starting materials, and the relation between densification and alpha-beta phase transformation was studied. The temperature dependences of Vickers microhardness and fracture toughness were also examined. Densification of Si3N4 was divided into three stages, and it was found that densification and phase transformation of Si3N4 under pressure were closely associated. The results of the temperature dependence of Vickers microhardness indicated that the high-temperature hardness was strongly influenced not only by the density and microstructure of sintered body but also by the purity of starting powder. The fracture toughness values of Si3N4 bodies without additives were 3.29-4.39 MN/m to the 3/2 power and independent of temperature up to 1400 C.

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

Myers, M.A.; LaSalvia, J.C.; Hoke, D.

Combustion synthesis followed by densification was utilized in producing monolithic TiC and TiB2 materials, and TiC-Ni, TiB2-Ni, TiB2-Al2O3, and TiB2SiC ceramic composites. Static and dynamic densification equipments were developed with the loading applied immediately after the synthesis reaction was completed and the ceramic/composite was ductile. All the ceramics exhibited an equiaxed grain structure with alternating regions at high and low dislocation densities, indicating that recovery/recrystallization mechanisms are prevalent. The grain boundaries were, as far as could be established, devoid of impurities and second phases. Quasi-static and dynamic mechanical testing were performed and revealed that the materials exhibited strength levels comparablemore » to conventionally produced materials. Instrumented densification experiments were conducted and a temperature-dependent consitutive model was applied for plastic deformation of the porous combustion synthesis product.« less

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.

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

The Soot on the Snow (SoS-2013) experiment was carried out in Sodankylä (67°22'N, 26°39'E, 179 m a.s.l.), north of the Arctic Circle, to study the effects of deposition of Black Carbon (BC), Icelandic volcanic sand and glaciogenic silt on the surface albedo and melt of seasonal snow. The BC was soot originating from chimneys above residential wood-burning fireplaces in Helsinki, except on one experimental spot the soot was from a chimney of an oil burner, and on one from the a peat-burning power plant. The volcanic sand was near black mixture of the volcanic ash of glaciofluvial nature, originating from under the Myrdalsjokull glacier, which may be mixed with the ash of the Eyjafjallajokull eruption in 2010 and the Grimsvotn eruption in 2011. The glaciogenic silt was lighter in colour, from light-brown to slightly yellowish, consisting mainly of silt and some coarse clay sized particles, capable of being transported and deposited on the local glaciers as well as several hundreds of kilometres towards the Europe. The SoS-2013 experiment was undertaken at the Sodankylä airport with a large, flat, open space and untouched snow. Thirteen spots of different concentrations of soot, volcanic sand, and silt were generated by blowing the impurities on natural snow. We also had an untouched reference measurement spot. The impurities were deposited only once to each spot, and thereafter the spots were monitored until the snow was melted. The sites were left to develop naturally, introducing as little disturbance as possible. Continuous broadband albedo was measured using pyranometers installed on seven spots. Snow samples were collected for their elemental carbon (EC) and organic (OC) concentration analysis with the Thermal/Optical Carbon Aerosol Analyzer (OC/EC), following the NIOSH 5040 protocol. The spectral reflectance of the melting snow was measured using two ASD spectrometers, one measuring in the UV-B spectral range (325-1075 nm), and the other from UV-A up to IR (350-2500 nm). Using an ASD spectrometer coupled with the contact probe, the spectral reflectance of the volcanic sand and glaciogenic silt were determined under laboratory conditions. The SoS-2013 was a continuation of our previous SoS-2011 and SoS-2012 campaigns. Acknowledgements to the Alexander Goetz Instrument Support Program (AGISP) 'Arctic Snow Reflectance and Albedo Affected by Black Carbon'; Academy of Finland (the projects 'Arctic Absorbing Aerosols and Albedo of Snow (A4)', and 'New techniques in active remote sensing: hyperspectral laser in environmental change detection'); Maj and Tor Nessling Foundation; COST-STSM-FP0903-10960 'Reflectance and albedo of snow and vegetation for environmental studies'; J. William Fulbright Scholarship; Nordic Centre of Excellence CRAICC (Cryosphere-atmosphere interactions in a changing Arctic climate).

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

NASA Astrophysics Data System (ADS)

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

2016-11-01

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

Snow cover data records from satellite and conventional measurements

NASA Astrophysics Data System (ADS)

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

2008-12-01

A major goal of snow-related research in the Climate Research Division of Environment Canada is the development of consistent snow cover information from satellite and in situ data sources for climate monitoring and model evaluation. This work involves new satellite algorithm development for reliable mapping of snow water equivalent (SWE), snow cover extent (SCE) and snow cover onset and melt dates, evaluation of existing snow cover products such as the NOAA weekly data set with in situ and satellite data, and the reconstruction and reanalysis of snow cover information from the application of physical snow models, geostatistics and data assimilation methods. In the context of the International Polar Year, a major effort is being made to develop and evaluate snow cover information over the Arctic region with a particular focus on the dynamic spring melt period where positive feedbacks to the climate system are more pronounced. Assessment of the NOAA daily and weekly SCE products with MODIS and QuikSCAT derived datasets identified a systematic late bias of 2-3 weeks in snow-off dates over northern Canada. This bias was not observed over northern Eurasia which suggests that regional differences in variables such as lake fraction and cloud cover are systematically influencing the accuracy of the NOAA product over northern Canada. Considerable progress has been made in deriving passive microwave derived SWE information over sub- Arctic regions of North America where pre-existing algorithms were unable to account for the influence of forest cover and lake ice. Previous uncertainties in retrieving SWE across the boreal forest have been resolved with the combination of 18.7 and 10.7 GHz measurements from the Advanced Microwave Scanning Radiometer (AMSR-E; 2002-present). Full time series development (1978-onwards) remains problematic, however, because 10.7 GHz measurements are not available from the Special Sensor Microwave/Imager (1987-present). Satellite measurements coupled with lake ice model simulations have illustrated frequency dependent, seasonally evolving relationships between brightness temperature and lake fraction across tundra regions. A potential solution based on the temporal evolution of 37 GHz AMSR-E measurements shows some promise as this was found to be significantly correlated with field measurements of tundra SWE, and to be relatively insensitive to lake fraction. New pan-Arctic (N 60°N) snowmelt onset and end date records (2000-2006) were produced from enhanced resolution (4.45 km) QuikSCAT (QSCAT) Ku-band backscatter measurements. The goal is to merge this with melt onset information from other components of the cryosphere (e.g. glaciers, ice caps, ice sheets, lake ice, sea ice) to provide an integrated circumpolar melt onset and duration dataset for climate monitoring and research on cryosphere-climate links and feedbacks. A major challenge is expanding the relatively short time period of Ku-band satellite measurements with historical C-band data (i.e. from ERS-1). Geostatistical methods and snow cover modeling were used to develop a 10-km gridded SWE dataset over Quebec from 1970-2005 for climate studies and evaluation of the performance of the Canadian Regional Climate Model.

Hydrogen/Oxygen Propellant Densifier Thermoacoustic Stirling Heat Engine

NASA Astrophysics Data System (ADS)

Nguyen, C. T.; Yeckley, A. J.; Schieb, D. J.; Haberbusch, M. S.

2004-06-01

A unique, patent pending, thermoacoustic propellant densifier for the simultaneous densification of hydrogen and oxygen propellants for aerospace vehicles is introduced. The densifier uses a high-pressure amplitude, low-frequency Thermoacoustic Stirling Heat Engine (TASHE) coupled with a uniquely designed half-wave-length resonator to drive a pulse tube cryocooler using a Gas Helium (GHe) working fluid. The extremely reliable TASHE has no moving parts, is water cooled, and is electrically powered. The helium-filled TASHE is designed to ASME piping codes, which enables the safe inspection of the system while in operation. The resonator is designed to eliminate higher-order harmonics with minimal acoustic losses. A system description will be presented, and experimental data on both the TASHE and the resonator will be compared with analytical results.

The Effect of High-pressure Densification on Ballistic-penetration Resistance of a Soda-lime Glass

DTIC Science & Technology

2011-01-01

equation of state and the strength constitutive laws of an existing material model for glass. This was fol- lowed by a set of transient non-linear... of irreversible densification. These relations are next used to upgrade the equation of state and the strength constitutive laws of an existing...its effect on the conti- nuum-level pressure versus degree- of -compression (the negative of volumetric strain) relation, also known as the

Coupling the WRF model with a temperature index model based on remote sensing for snowmelt simulations in a river basin in the Altay Mountains, northwest China

NASA Astrophysics Data System (ADS)

Wu, X.; Shen, Y.; Wang, N.; Pan, X.; Zhang, W.; He, J.; Wang, G.

2017-12-01

Snowmelt water is an important freshwater resource in the Altay Mountains in northwest China, and it is also crucial for local ecological system, economic and social sustainable development; however, warming climate and rapid spring snowmelt can cause floods that endanger both eco-environment and public and personal property and safety. This study simulates snowmelt in the Kayiertesi River catchment using a temperature-index model based on remote sensing coupled with high-resolution meteorological data obtained from NCEP reanalysis fields that were downscaled using Weather Research Forecasting model, then bias-corrected using a statistical downscaled model. Validation of the forcing data revealed that the high-resolution meteorological fields derived from downscaled NCEP reanalysis were reliable for driving the snowmelt model. Parameters of temperature-index model based on remote sensing were calibrated for spring 2014, and model performance was validated using MODIS snow cover and snow observations from spring 2012. The results show that the temperature-index model based on remote sensing performed well, with a simulation mean relative error of 6.7% and a Nash-Sutchliffe efficiency of 0.98 in spring 2012 in the river of Altay Mountains. Based on the reliable distributed snow water equivalent simulation, daily snowmelt runoff was calculated for spring 2012 in the basin. In the study catchment, spring snowmelt runoff accounts for 72% of spring runoff and 21% of annual runoff. Snowmelt is the main source of runoff for the catchment and should be managed and utilized effectively. The results provide a basis for snowmelt runoff predictions, so as to prevent snowmelt-induced floods, and also provide a generalizable approach that can be applied to other remote locations where high-density, long-term observational data is lacking.

Numerical Analysis Using WRF-SBM for the Cloud Microphysical Structures in the C3VP Field Campaign: Impacts of Supercooled Droplets and Resultant Riming on Snow Microphysics

NASA Technical Reports Server (NTRS)

Iguchi, Takamichi; Matsui, Toshihisa; Shi, Jainn J.; Tao, Wei-Kuo; Khain, Alexander P.; Hao, Arthur; Cifelli, Robert; Heymsfield, Andrew; Tokay, Ali

2012-01-01

Two distinct snowfall events are observed over the region near the Great Lakes during 19-23 January 2007 under the intensive measurement campaign of the Canadian CloudSat/CALIPSO validation project (C3VP). These events are numerically investigated using the Weather Research and Forecasting model coupled with a spectral bin microphysics (WRF-SBM) scheme that allows a smooth calculation of riming process by predicting the rimed mass fraction on snow aggregates. The fundamental structures of the observed two snowfall systems are distinctly characterized by a localized intense lake-effect snowstorm in one case and a widely distributed moderate snowfall by the synoptic-scale system in another case. Furthermore, the observed microphysical structures are distinguished by differences in bulk density of solid-phase particles, which are probably linked to the presence or absence of supercooled droplets. The WRF-SBM coupled with Goddard Satellite Data Simulator Unit (G-SDSU) has successfully simulated these distinctive structures in the three-dimensional weather prediction run with a horizontal resolution of 1 km. In particular, riming on snow aggregates by supercooled droplets is considered to be of importance in reproducing the specialized microphysical structures in the case studies. Additional sensitivity tests for the lake-effect snowstorm case are conducted utilizing different planetary boundary layer (PBL) models or the same SBM but without the riming process. The PBL process has a large impact on determining the cloud microphysical structure of the lake-effect snowstorm as well as the surface precipitation pattern, whereas the riming process has little influence on the surface precipitation because of the small height of the system.

Interweaving climate research and public understanding

NASA Astrophysics Data System (ADS)

Betts, A. K.

2016-12-01

For the past 10 years I have been using research into land-atmosphere-cloud coupling to address Vermont's need to understand climate change, and develop plans for greater resilience in the face of increasing severe weather. The research side has shown that the fraction of days with snow cover determines the cold season climate, because snow acts as a fast climate switch between non-overlapping climates with and without snow cover. Clouds play opposite roles in warm and cold seasons: surface cooling in summer and warming in winter. The later fall freeze-up and earlier spring ice-out on lakes, coupled to the earlier spring phenology, are clear markers both of a warming climate, as well as the large interannual variability. Severe flooding events have come with large-scale quasi-stationary weather patterns. This past decade I have given 230 talks to schools, business and professional groups, as well as legislative committees and state government. I have written 80 environmental columns for two Vermont newspapers, as part of a weekly series I helped start in 2008. Commentaries and interviews on radio and TV enable me to explain directly the issues we face, as the burning of fossil fuels destabilizes the climate system. The public in Vermont is eager to learn and understand these issues since many have roots in the land; while professional groups need all the information and guidance possible to prepare for the future. My task as a scientist is to map out what we know in ways that can readily be grasped in terms of past experience, even though the climate system is already moving outside this range - and at the same time outline general principles and hopeful strategies for dealing with global and local climate change.

Comparison of Two Conceptually Different Physically-based Hydrological Models - Looking Beyond Streamflows

NASA Astrophysics Data System (ADS)

Rousseau, A. N.; Álvarez; Yu, X.; Savary, S.; Duffy, C.

2015-12-01

Most physically-based hydrological models simulate to various extents the relevant watershed processes occurring at different spatiotemporal scales. These models use different physical domain representations (e.g., hydrological response units, discretized control volumes) and numerical solution techniques (e.g., finite difference method, finite element method) as well as a variety of approximations for representing the physical processes. Despite the fact that several models have been developed so far, very few inter-comparison studies have been conducted to check beyond streamflows whether different modeling approaches could simulate in a similar fashion the other processes at the watershed scale. In this study, PIHM (Qu and Duffy, 2007), a fully coupled, distributed model, and HYDROTEL (Fortin et al., 2001; Turcotte et al., 2003, 2007), a pseudo-coupled, semi-distributed model, were compared to check whether the models could corroborate observed streamflows while equally representing other processes as well such as evapotranspiration, snow accumulation/melt or infiltration, etc. For this study, the Young Womans Creek watershed, PA, was used to compare: streamflows (channel routing), actual evapotranspiration, snow water equivalent (snow accumulation and melt), infiltration, recharge, shallow water depth above the soil surface (surface flow), lateral flow into the river (surface and subsurface flow) and height of the saturated soil column (subsurface flow). Despite a lack of observed data for contrasting most of the simulated processes, it can be said that the two models can be used as simulation tools for streamflows, actual evapotranspiration, infiltration, lateral flows into the river, and height of the saturated soil column. However, each process presents particular differences as a result of the physical parameters and the modeling approaches used by each model. Potentially, these differences should be object of further analyses to definitively confirm or reject modeling hypotheses.

Effect of milling and leaching on the structure of sintered silicon

NASA Technical Reports Server (NTRS)

Yeh, H. C.; Glascow, T. K.; Herbell, T. P.

1980-01-01

Sintering was performed in He for 16 hours at 1200, 1250, and 1300 C. Compacts of as-received Si did not densify during sintering. Milling reduced the average particle size to below 0.5 micrometer and enhanced densification (1.75 g/cc). Leaching milled Si further enhanced densification (1.90 g/cc max.) and decreased structural coarsening. After sintering, the structure of the milled and leached powder compacts appears favorable for the production of reaction bonded silicon nitride.

The Impact of Pore Structure on Densification Efficiency of 2-D Carbon-Carbon Composites and Its Relationship to Mechanical Properties

DTIC Science & Technology

2011-03-01

Allcomp Inc . The Impact of Pore Structure on Densification...topic. I would also like to acknowledge and thank Allcomp , Inc . for supplying the materials for all the tests in this study. I am also very... Allcomp , Inc . who assisted in other ways throughout this effort. -David Swanson                             Swanson 4    Abstract The

Modeling the interaction of ultrasound with pores

NASA Technical Reports Server (NTRS)

Lu, Yichi; Wadley, Haydn N. G.; Parthasarathi, Sanjai

1991-01-01

Factors that affect ultrasonic velocity sensing of density during consolidation of metal powders are examined. A comparison is made between experimental results obtained during the final stage of densification and the predictions of models that assume either a spherical or a spheroidal pore shape. It is found that for measurements made at low frequencies during the final stage of densification, relative density (pore fraction) and pore shape are the two most important factors determining the ultrasonic velocity, the effect of pore size is negligible.

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.

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

NASA Technical Reports Server (NTRS)

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

2011-01-01

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

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.

Glacier and snow hydrology investigation in the Upper Indus Basin using Synthetic Aperture Radar

NASA Astrophysics Data System (ADS)

Jouvet, G.; Stastny, T.; Oettershagen, P.; Hugentobler, M.; Mantel, T.; Melzer, A.; Weidmann, Y.; Funk, M.; Siegwart, R.; Lund, J.; Forster, R. R.; Burgess, E. W.

2017-12-01

The flows of the Indus River are a vital resource for food security, ecosystem services, hydropower and economy for China, India and Pakistan. Glaciers of the Karakoram Mountains are the largest drivers of discharge in the Upper Indus Basin, and combined with snowmelt constitute the majority of runoff. While recently verified in near balance, the glaciers of the Karakoram exhibit substantial variation both spatially and temporally. Complex climatology, coupled with the challenges of field study in this rugged range, illicit notable uncertainties in observation and prediction of glacial status. Satellite-borne radar sensors acquire imagery regardless of cloud cover or time of day, and offer unique insights into physical processes due to their wavelength. Here we utilize Sentinel-1 synthetic aperture radar (SAR) imagery to track transient snow lines on glaciers of the Shigar watershed throughout multiple ablation seasons, and discuss the utility of this information in relation to snow and glacier mass balance. As the Sentinel-1 sensor ascending and descending passes capture morning and evening imagery in this region, diurnal radar variations will also be explored as indicators of melt-refreeze cycles and their correlation with peak runoff.

Bloating in (Pb0.95Sn0.05Te)0.92(PbS)0.08-0.055%PbI2 Thermoelectric Specimens as a Result of Processing Conditions

NASA Astrophysics Data System (ADS)

Ni, Jennifer E.; Case, Eldon D.; Stewart, Ryan; Wu, Chun-I.; Hogan, Timothy P.; Kanatzidis, Mercouri G.

2012-06-01

Lead chalcogenides such as (Pb0.95Sn0.05Te)0.92(PbS)0.08-0.055%PbI2 have received attention due to their encouraging thermoelectric properties. For the hot pressing (HP) and pulsed electric current sintering (PECS) techniques used in this study, decomposition reactions can generate porosity (bloating). Porosity in turn can degrade electrical, thermal, and mechanical properties. In this study, microstructural observations (scanning electron microscopy) and room-temperature elasticity measurements (resonant ultrasound spectroscopy) were used to characterize bloating generated during post-densification anneals. Although every HP specimen bloated during post-densification annealing, no bloating was observed for the PECS specimens processed from dry milled only powders. The lack of bloating for the annealed PECS specimens may be related to the electrical discharge intrinsic in the PECS process, which reportedly cleans the powder particle surfaces during densification.

Experimental Research on Selective Laser Melting AlSi10Mg Alloys: Process, Densification and Performance

NASA Astrophysics Data System (ADS)

Chen, Zhen; Wei, Zhengying; Wei, Pei; Chen, Shenggui; Lu, Bingheng; Du, Jun; Li, Junfeng; Zhang, Shuzhe

2017-12-01

In this work, a set of experiments was designed to investigate the effect of process parameters on the relative density of the AlSi10Mg parts manufactured by SLM. The influence of laser scan speed v, laser power P and hatch space H, which were considered as the dominant parameters, on the powder melting and densification behavior was also studied experimentally. In addition, the laser energy density was introduced to evaluate the combined effect of the above dominant parameters, so as to control the SLM process integrally. As a result, a high relative density (> 97%) was obtained by SLM at an optimized laser energy density of 3.5-5.5 J/mm2. Moreover, a parameter-densification map was established to visually select the optimum process parameters for the SLM-processed AlSi10Mg parts with elevated density and required mechanical properties. The results provide an important experimental guidance for obtaining AlSi10Mg components with full density and gradient functional porosity by SLM.

Application of densification process in organic waste management.

PubMed

Zafari, Abedin; Kianmehr, Mohammad Hossein

2013-07-01

Densification of biomass material that usually has a low density is good way of increasing density, reducing the cost of transportation, and simplifying the storage and distribution of this material. The current study was conducted to investigate the influence of raw material parameters (moisture content and particle size), and densification process parameters (piston speed and die length) on the density and durability of pellets from compost manure. A hydraulic press and a single pelleter were used to produce pellets in controlled conditions. Ground biomass samples were compressed with three levels of moisture content [35%, 40% and 45% (wet basis)], piston speed (2, 6 and 10 mm/s), die length (8, 10 and 12 mm) and particle size (0.3., 0.9 and 1.5 mm) to establish density and durability of pellets. A response surface methodology based on the Box Behnken design was used to study the responses pattern and to understand the influence of parameters. The results revealed that all independent variables have significant (P < 0.01) effects on studied responses in this research.

Reduction reactions and densification during in situ TEM heating of iron oxide nanochains

NASA Astrophysics Data System (ADS)

Bonifacio, Cecile S.; Das, Gautom; Kennedy, Ian M.; van Benthem, Klaus

2017-12-01

The reduction reactions and densification of nanochains assembled from γ-Fe2O3 nanoparticles were investigated using in situ transmission electron microscopy (TEM). Morphological changes and reduction of the metal oxide nanochains were observed during in situ TEM annealing through simultaneous imaging and quantitative analysis of the near-edge fine structures of Fe L2,3 absorption edges acquired by spatially resolved electron energy loss spectroscopy. A change in the oxidation states during annealing of the iron oxide nanochains was observed with phase transformations due to continuous reduction from Fe2O3 over Fe3O4, FeO to metallic Fe. Phase transitions during the in situ heating experiments were accompanied with morphological changes in the nanochains, specifically rough-to-smooth surface transitions below 500 °C, neck formation between adjacent particles around 500 °C, and subsequent neck growth. At higher temperatures, coalescence of FeO particles was observed, representing densification.

IceChrono1: a probabilistic model to compute a common and optimal chronology for several ice cores

NASA Astrophysics Data System (ADS)

Parrenin, Frédéric; Bazin, Lucie; Capron, Emilie; Landais, Amaëlle; Lemieux-Dudon, Bénédicte; Masson-Delmotte, Valérie

2016-04-01

Polar ice cores provide exceptional archives of past environmental conditions. The dating of ice cores and the estimation of the age scale uncertainty are essential to interpret the climate and environmental records that they contain. It is however a complex problem which involves different methods. Here, we present IceChrono1, a new probabilistic model integrating various sources of chronological information to produce a common and optimized chronology for several ice cores, as well as its uncertainty. IceChrono1 is based on the inversion of three quantities: the surface accumulation rate, the Lock-In Depth (LID) of air bubbles and the thinning function. The chronological information integrated into the model are: models of the sedimentation process (accumulation of snow, densification of snow into ice and air trapping, ice flow), ice and air dated horizons, ice and air depth intervals with known durations, Δdepth observations (depth shift between synchronous events recorded in the ice and in the air) and finally air and ice stratigraphic links in between ice cores. The optimization is formulated as a least squares problem, implying that all densities of probabilities are assumed to be Gaussian. It is numerically solved using the Levenberg-Marquardt algorithm and a numerical evaluation of the model's Jacobian. IceChrono follows an approach similar to that of the Datice model which was recently used to produce the AICC2012 chronology for 4 Antarctic ice cores and 1 Greenland ice core. IceChrono1 provides improvements and simplifications with respect to Datice from the mathematical, numerical and programming point of views. The capabilities of IceChrono is demonstrated on a case study similar to the AICC2012 dating experiment. We find results similar to those of Datice, within a few centuries, which is a confirmation of both IceChrono and Datice codes. We also test new functionalities with respect to the original version of Datice: observations as ice intervals with known durations, correlated observations, observations as gas intervals with known durations and observations as mixed ice-air stratigraphic links. IceChrono1 is freely available under the GPL v3 open source license.

IceChrono1: a probabilistic model to compute a common and optimal chronology for several ice cores

NASA Astrophysics Data System (ADS)

Parrenin, F.; Bazin, L.; Capron, E.; Landais, A.; Lemieux-Dudon, B.; Masson-Delmotte, V.

2015-05-01

Polar ice cores provide exceptional archives of past environmental conditions. The dating of ice cores and the estimation of the age-scale uncertainty are essential to interpret the climate and environmental records that they contain. It is, however, a complex problem which involves different methods. Here, we present IceChrono1, a new probabilistic model integrating various sources of chronological information to produce a common and optimized chronology for several ice cores, as well as its uncertainty. IceChrono1 is based on the inversion of three quantities: the surface accumulation rate, the lock-in depth (LID) of air bubbles and the thinning function. The chronological information integrated into the model are models of the sedimentation process (accumulation of snow, densification of snow into ice and air trapping, ice flow), ice- and air-dated horizons, ice and air depth intervals with known durations, depth observations (depth shift between synchronous events recorded in the ice and in the air) and finally air and ice stratigraphic links in between ice cores. The optimization is formulated as a least squares problem, implying that all densities of probabilities are assumed to be Gaussian. It is numerically solved using the Levenberg-Marquardt algorithm and a numerical evaluation of the model's Jacobian. IceChrono follows an approach similar to that of the Datice model which was recently used to produce the AICC2012 (Antarctic ice core chronology) for four Antarctic ice cores and one Greenland ice core. IceChrono1 provides improvements and simplifications with respect to Datice from the mathematical, numerical and programming point of views. The capabilities of IceChrono1 are demonstrated on a case study similar to the AICC2012 dating experiment. We find results similar to those of Datice, within a few centuries, which is a confirmation of both IceChrono1 and Datice codes. We also test new functionalities with respect to the original version of Datice: observations as ice intervals with known durations, correlated observations, observations as air intervals with known durations and observations as mixed ice-air stratigraphic links. IceChrono1 is freely available under the General Public License v3 open source license.

Liquid Oxygen Propellant Densification Production and Performance Test Results With a Large-Scale Flight-Weight Propellant Tank for the X33 RLV

NASA Technical Reports Server (NTRS)

Tomsik, Thomas M.; Meyer, Michael L.

2010-01-01

This paper describes in-detail a test program that was initiated at the Glenn Research Center (GRC) involving the cryogenic densification of liquid oxygen (LO2). A large scale LO2 propellant densification system rated for 200 gpm and sized for the X-33 LO2 propellant tank, was designed, fabricated and tested at the GRC. Multiple objectives of the test program included validation of LO2 production unit hardware and characterization of densifier performance at design and transient conditions. First, performance data is presented for an initial series of LO2 densifier screening and check-out tests using densified liquid nitrogen. The second series of tests show performance data collected during LO2 densifier test operations with liquid oxygen as the densified product fluid. An overview of LO2 X-33 tanking operations and load tests with the 20,000 gallon Structural Test Article (STA) are described. Tank loading testing and the thermal stratification that occurs inside of a flight-weight launch vehicle propellant tank were investigated. These operations involved a closed-loop recirculation process of LO2 flow through the densifier and then back into the STA. Finally, in excess of 200,000 gallons of densified LO2 at 120 oR was produced with the propellant densification unit during the demonstration program, an achievement that s never been done before in the realm of large-scale cryogenic tests.

Investigation of Boron addition and compaction pressure on the compactibility, densification and microhardness of 316L Stainless Steel

NASA Astrophysics Data System (ADS)

Ali, S.; Rani, A. M. A.; Altaf, K.; Baig, Z.

2018-04-01

Powder Metallurgy (P/M) is one of the continually evolving technologies used for producing metal materials of various sizes and shapes. However, some P/M materials have limited use in engineering for their performance deficiency including fully dense components. AISI 316L Stainless Steel (SS) is one of the promising materials used in P/M that combines outstanding corrosion resistance, strength and ductility for numerous applications. It is important to analyze the material composition along with the processing conditions that lead to a superior behaviour of the parts manufactured with P/M technique. This research investigates the effect of Boron addition on the compactibility, densification, sintering characteristics and microhardness of 316L SS parts produced with P/M. In this study, 0.25% Boron was added to the 316L Stainless Steel matrix to study the increase in densification of the 316L SS samples. The samples were made at different compaction pressures ranging from 100 MPa to 600 MPa and sintered in Nitrogen atmosphere at a temperature of 1200°C. The effect of compaction pressure and sintering temperature and atmosphere on the density and microhardness was evaluated. The microstructure of the samples was examined by optical microscope and microhardness was found using Vickers hardness machine. Results of the study showed that sintered samples with Boron addition exhibited high densification with increase in microhardness as compared to pure 316L SS sintered samples.

Raman spectroscopy of femtosecond multipulse irradiation of vitreous silica: Experiment and simulation

NASA Astrophysics Data System (ADS)

Shcheblanov, N. S.; Povarnitsyn, M. E.; Mishchik, K. N.; Tanguy, A.

2018-02-01

We report an experimental and numerical study of femtosecond multipulse laser-induced densification in vitreous silica (v -SiO2 ) and its signature in Raman spectra. We compare the experimental findings to the recently developed molecular dynamics (MD) approach accounting for bond breaking due to laser irradiation, together with a dynamical matrix approach and bond polarizability model based on first-principles calculations for the estimation of Raman spectra. We observe two stages of the laser-induced densification and Raman spectrum evolution: growth during several hundreds of pulses followed by further saturation. At the medium range, the network connectivity change in v -SiO2 is expressed in reduction of the major ring fractions leading to more compacted structure. With the help of the Sen and Thorpe model, we also study the short-range order transformation and derive the interbonding Si-O-Si angle change from the Raman measurements. Experimental findings are in excellent agreement with our MD simulations and hence support a bond-breaking mechanism of laser-induced densification. Thus, our modeling explains well the laser-induced changes both in the short-range order caused by the appearance of Si coordination defects and medium-range order connected to evolution of the ring distribution. Finally, our findings disclose similarities between sheared, permanently densified, and laser-induced glass and suggest interesting future experiments in order to clarify the impact of the thermomechanical history on glasses under shear, cold and hot compression, and laser-induced densification.

Fusion of multi-temporal Airborne Snow Observatory (ASO) lidar data for mountainous vegetation ecosystems studies.

NASA Astrophysics Data System (ADS)

Ferraz, A.; Painter, T. H.; Saatchi, S.; Bormann, K. J.

2016-12-01

Fusion of multi-temporal Airborne Snow Observatory (ASO) lidar data for mountainous vegetation ecosystems studies The NASA Jet Propulsion Laboratory developed the Airborne Snow Observatory (ASO), a coupled scanning lidar system and imaging spectrometer, to quantify the spatial distribution of snow volume and dynamics over mountains watersheds (Painter et al., 2015). To do this, ASO weekly over-flights mountainous areas during snowfall and snowmelt seasons. In addition, there are additional flights in snow-off conditions to calculate Digital Terrain Models (DTM). In this study, we focus on the reliability of ASO lidar data to characterize the 3D forest vegetation structure. The density of a single point cloud acquisition is of nearly 1 pt/m2, which is not optimal to properly characterize vegetation. However, ASO covers a given study site up to 14 times a year that enables computing a high-resolution point cloud by merging single acquisitions. In this study, we present a method to automatically register ASO multi-temporal lidar 3D point clouds. Although flight specifications do not change between acquisition dates, lidar datasets might have significant planimetric shifts due to inaccuracies in platform trajectory estimation introduced by the GPS system and drifts of the IMU. There are a large number of methodologies that address the problem of 3D data registration (Gressin et al., 2013). Briefly, they look for common primitive features in both datasets such as buildings corners, structures like electric poles, DTM breaklines or deformations. However, they are not suited for our experiment. First, single acquisition point clouds have low density that makes the extraction of primitive features difficult. Second, the landscape significantly changes between flights due to snowfall and snowmelt. Therefore, we developed a method to automatically register point clouds using tree apexes as keypoints because they are features that are supposed to experience little change during winter season. We applied the method to 14 lidar datasets (12 snow-on and 2 snow-off) acquired over the Tuolumne River Basin (California) in the year of 2014. To assess the reliability of the merged point cloud, we analyze the quality of vegetation related products such as canopy height models (CHM) and vertical vegetation profiles.

Meshless modelling of dynamic behaviour of glasses under intense shock loadings: Application to matter ejection during high velocity impacts on thin brittle targets

NASA Astrophysics Data System (ADS)

Michel, Y.; Chevalier, J.-M.; Durin, C.; Espinosa, C.; Malaise, F.; Barrau, J.-J.

2006-08-01

The purpose of this study is to present a new material model adapted to SPH modelling of dynamic behaviour of glasses under shock loadings. This model has the ability to reproduce fragmentation and densification of glasses under compression as well as brittle tensile failure. It has been implemented in Ls-Dyna software and coupled with a SPH code. By comparison with CEA-CESTA experimental data the model has been validated for fused silica and Pyrex glass for stress level up to 35GPa. For Laser MegaJoule applications, the present material model was applied to 3D high velocity impacts on thin brittle targets with good agreement with experimental data obtained using CESTA's double stage light gas gun in term of damages and matter ejection.

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.

Ensemble Simulation of Sierra Nevada Snowmelt Runoff Using a Regional Climate Modeling Approach

NASA Astrophysics Data System (ADS)

Holtzman, N.; Pavelsky, T.; Wrzesien, M.

2017-12-01

The snowmelt-dominated watersheds on the western slopes of the California Sierra Nevada drain into reservoirs that generate electricity and help irrigate Central Valley farms. At the end of the wet season of each year, around April 1, most of the water that will become runoff in these basins is stored as snow at high elevations. Snow measurements provide a good estimate of the total annual runoff to come. For efficient water management, however, it is also useful to know the timing of runoff. When and how large will the peak flow into a reservoir be, and how fast will the flow decline after it peaks? We address such questions using a coupled regional climate and land surface model, WRF and Noah-MP, to dynamically downscale the North American Regional Reanalysis (NARR) with an ensemble approach. First, we assess several methods of deriving melt-season runoff from WRF. We run WRF for a complete water year, and also test initializing WRF snow from observation-based datasets at the approximate date of peak snow water equivalent. By aggregating the modeled runoffs over the drainage basins of reservoirs and comparing to naturalized flow data, we can assess the basin-scale snow accumulation accuracy of WRF and the other datasets in the Sierra. After choosing a procedure to set the model snow at the end of the wet season, we apply in WRF the melt-season meteorology from 20 different past years of NARR to produce an ensemble of simulations, each with modeled flows into 8 reservoirs spanning the Sierra. We use the ensemble to characterize the likely spread in the timing and magnitude of hydrologic outcomes during the melt season. Probabilistic forecasts can help water-energy systems operate more efficiently. The ensemble also shows the effect of warm-season temperature extremes on flow timing, allowing human systems to prepare for those possibilities. Finally, the ensemble provides a baseline estimate of the maximum variability in runoff timing that could be generated by past conditions. If future runoff patterns consistently exceed the extremes found in the ensemble, nonstationary hydroclimate can be inferred.

Effects of various additives on sintering of aluminum nitride

NASA Technical Reports Server (NTRS)

Komeya, K.; Inoue, H.; Tsuge, A.

1982-01-01

Effects of thirty additives on sintering A/N were investigated. The addition of alkali earth oxides and rare earth oxides gave fully densified aluminum nitride. This is due to the formation of nitrogen-containing aluminate liquid in the system aluminum nitride-alkali earth oxides or rare earth oxides. Microstructural studies of the sintered specimens with the above two types of additives suggested that the densification was due to the liquid phase sintering. Additions of silicon compounds resulted in poor densification by the formation of highly refractory compounds such as A/N polytypes.

Ion-beam-induced planarization, densification, and exfoliation of low-density nanoporous silica

NASA Astrophysics Data System (ADS)

Kucheyev, S. O.; Shin, S. J.

2017-09-01

Planarization of low-density nanoporous solids is challenging. Here, we demonstrate that ion bombardment to doses of ˜1015 cm-2 results in significant smoothing of silica aerogels, yielding mirror-like surfaces after metallization. The surface smoothing efficiency scales with the ion energy loss component leading to local lattice heating. Planarization is accompanied by sub-surface monolith densification, resulting in surface exfoliation with increasing ion dose. These findings have implications for the fabrication of graded-density nanofoams, aerogel-based lightweight optical components, and meso-origami.

Impact of densification on microstructure and transport properties of CaFe5O7

NASA Astrophysics Data System (ADS)

Delacotte, C.; Hébert, S.; Hardy, V.; Bréard, Y.; Maki, R.; Mori, T.; Pelloquin, D.

2016-04-01

Monophasic CaFe5O7 ceramic has been synthesized by solid state route. Its microstructural features have been studied by diffraction techniques and electron microscopy images before and after Spark Plasma Sintering (SPS) annealings. This work is completed by measurements of electrical and thermal properties. Especially, attention is focused around the structural and electronic transition at 360 K for which specific heat measurements have revealed a sharp peak. Densification by SPS techniques led to a significant improvement of electrical conductivity above 360 K.

The regional climate model REMO (v2015) coupled with the 1-D freshwater lake model FLake (v1): Fenno-Scandinavian climate and lakes

NASA Astrophysics Data System (ADS)

Pietikäinen, Joni-Pekka; Markkanen, Tiina; Sieck, Kevin; Jacob, Daniela; Korhonen, Johanna; Räisänen, Petri; Gao, Yao; Ahola, Jaakko; Korhonen, Hannele; Laaksonen, Ari; Kaurola, Jussi

2018-04-01

The regional climate model REMO was coupled with the FLake lake model to include an interactive treatment of lakes. Using this new version, the Fenno-Scandinavian climate and lake characteristics were studied in a set of 35-year hindcast simulations. Additionally, sensitivity tests related to the parameterization of snow albedo were conducted. Our results show that overall the new model version improves the representation of the Fenno-Scandinavian climate in terms of 2 m temperature and precipitation, but the downside is that an existing wintertime cold bias in the model is enhanced. The lake surface water temperature, ice depth and ice season length were analyzed in detail for 10 Finnish, 4 Swedish and 2 Russian lakes and 1 Estonian lake. The results show that the model can reproduce these characteristics with reasonably high accuracy. The cold bias during winter causes overestimation of ice layer thickness, for example, at several of the studied lakes, but overall the values from the model are realistic and represent the lake physics well in a long-term simulation. We also analyzed the snow depth on ice from 10 Finnish lakes and vertical temperature profiles from 5 Finnish lakes and the model results are realistic.

Microbial and long-range terrestrial contributions of organic matter to Antarctica

NASA Astrophysics Data System (ADS)

Antony, R.; Grannas, A. M.; Priest, A. S.; Sleighter, R. L.; Meloth, T.; Hatcher, P.

2012-12-01

Composition and cycling of dissolved organic matter in glacial systems is important because of its great significance to global carbon dynamics, snow photochemistry, and air-snow exchange processes. But, due to the trace nature of specific organic components in Polar ice sheets, detecting and studying these species in molecular level detail has been an analytical challenge. Electrospray ionization coupled with Fourier transform ion cyclotron resonance mass spectrometry (ESI FT-ICR MS) enabled the elucidation of molecular level details of natural organic matter in snow samples collected along a coast to inland transect from the Princesses Elizabeth Land, East Antarctica. Thousands of distinct molecular species comprising of different compound classes were identified providing clues to the nature and sources of organic carbon in Antarctic snow. The major biochemical classes of compounds detected were lignins, tannins, carbohydrates, proteins, amino sugars, lipids, unsaturated hydrocarbons and condensed aromatics. Specifically, lignin molecules comprising up to 50% and compounds derived from algal and microbial biomass comprising up to 45% of the total assigned formulas dominated the organic carbon pool. The identification of a variety of lignin compounds demonstrates substantial input of vascular plant-derived materials to the identified molecular species, presumably from long range atmospheric transport and deposition. The detection of proteins, lipids and amino sugars suggests that a large proportion of the identified supraglacial organic matter likely originates from in situ microbial activity. This corroborates well with the presence of significant numbers of bacteria, picoplankton and microalgae in these samples. These results suggest that organic matter in the supraglacial environments have both a microbial and terrestrial provenance.

Bayesian inference of uncertainties in precipitation-streamflow modeling in a snow affected catchment

NASA Astrophysics Data System (ADS)

Koskela, J. J.; Croke, B. W. F.; Koivusalo, H.; Jakeman, A. J.; Kokkonen, T.

2012-11-01

Bayesian inference is used to study the effect of precipitation and model structural uncertainty on estimates of model parameters and confidence limits of predictive variables in a conceptual rainfall-runoff model in the snow-fed Rudbäck catchment (142 ha) in southern Finland. The IHACRES model is coupled with a simple degree day model to account for snow accumulation and melt. The posterior probability distribution of the model parameters is sampled by using the Differential Evolution Adaptive Metropolis (DREAM(ZS)) algorithm and the generalized likelihood function. Precipitation uncertainty is taken into account by introducing additional latent variables that were used as multipliers for individual storm events. Results suggest that occasional snow water equivalent (SWE) observations together with daily streamflow observations do not contain enough information to simultaneously identify model parameters, precipitation uncertainty and model structural uncertainty in the Rudbäck catchment. The addition of an autoregressive component to account for model structure error and latent variables having uniform priors to account for input uncertainty lead to dubious posterior distributions of model parameters. Thus our hypothesis that informative priors for latent variables could be replaced by additional SWE data could not be confirmed. The model was found to work adequately in 1-day-ahead simulation mode, but the results were poor in the simulation batch mode. This was caused by the interaction of parameters that were used to describe different sources of uncertainty. The findings may have lessons for other cases where parameterizations are similarly high in relation to available prior information.

Thermal regime of an ice-wedge polygon landscape near Barrow, Alaska

NASA Astrophysics Data System (ADS)

Daanen, R. P.; Liljedahl, A. K.

2017-12-01

Tundra landscapes are changing all over the circumpolar Arctic due to permafrost degradation. Soil cracking and infilling of meltwater repeated over thousands of years form ice wedges, which produce the characteristic surface pattern of ice-wedge polygon tundra. Rapid top-down thawing of massive ice leads to differential ground subsidence and sets in motion a series of short- and long-term hydrological and ecological changes. Subsequent responses in the soil thermal regime drive further permafrost degradation and/or stabilization. Here we explore the soil thermal regime of an ice-wedge polygon terrain near Utqiagvik (formerly Barrow) with the Water balance Simulation Model (WaSiM). WaSiM is a hydro-thermal model developed to simulate the water balance at the watershed scale and was recently refined to represent the hydrological processes unique to cold climates. WaSiM includes modules that represent surface runoff, evapotranspiration, groundwater, and soil moisture, while active layer freezing and thawing is based on a direct coupling of hydrological and thermal processes. A new snow module expands the vadose zone calculations into the snow pack, allowing the model to simulate the snow as a porous medium similar to soil. Together with a snow redistribution algorithm based on local topography, this latest addition to WaSiM makes simulation of the ground thermal regime much more accurate during winter months. Effective representation of ground temperatures during winter is crucial in the simulation of the permafrost thermal regime and allows for refined predictions of future ice-wedge degradation or stabilization.

Evaluation of Liquefaction Susceptibility of Clean Sands after Blast Densification

NASA Astrophysics Data System (ADS)

Vega Posada, Carlos Alberto

The effect of earthquakes on infrastructure facilities is an important topic of interest in geotechnical research. A key design issue for such facilities is whether or not liquefaction will occur during an earthquake. The consequences of this type of ground failure are usually severe, resulting in severe damage to a facility and in some cases the loss of human life. One approach to minimize the effect of liquefaction is to improve the ground condition by controlled blasting. The main limitations of the blast densification technique are that the design is mostly empirical and verification studies of densification have resulted in contradictory results in some case studies. In such cases, even though the ground surface settles almost immediately after blasting, common verification tests such as the cone penetration test (CPT), standard penetration test (SPT), and shear wave velocity test (Vs) suggest that the soil mass has not been improved at all. This raises concerns regarding the future performance of the soil and casts doubts on whether or not the improved deposit is still susceptible to liquefaction. In this work, a blast densification program was implemented at the Oakridge Landfill located in Dorchester County, SC, to gain information regarding the condition of a loose sand deposit during and after each blast event. In addition, an extensive laboratory testing program was conducted on reconstituted sand specimens to evaluate the mechanical behavior of saturated and gassy, medium dense sands during monotonic and cyclic loading. The results from the field and laboratory program indicate that gas released during blasting can remain trapped in the soil mass for several years, and this gas greatly affects the mechanical behavior of the sand. Gas greatly increases the liquefaction resistance of the soil. If the gas remains in the sand over the life of a project, then it will maintain this increased resistance to liquefaction, whether or not the penetration resistance increases with time. As part of this work, a methodology based on the critical state concepts was described to quantify the amount of densification needed at a certain project to make the soil more resistant to liquefaction and flow.

Loading Mode Optimization and Structure Tailoring in Spark Plasma Sintering of Monocarbide Powder-based Components for High Temperature Applications

NASA Astrophysics Data System (ADS)

Wei, Xialu

In this study, the spark plasma sintering (SPS) is employed to consolidate poorly sinter-able ultra-high temperature ceramic (UHTC) powders due to the fact that the conjoint application of electric current and mechanical pressure during SPS can largely offset the required processing temperature. Zirconium carbide (ZrC) is selected as target material as it broadly represents properties of typical UHTCs. Investigations on SPS of ZrC are concurrently conducted in two correlated regimes: One regime is used to optimize the SPS densification efficiency by manipulating the loading schematics. The other regime is used to produce complex shape carbide components for high temperature applications via SPS. Both theoretical and experimental studies are involved in the achievement of the formulated research objectives. Consolidation of ZrC has been carried out to form a densification map with determining the optimal processing parameters. The densification of ZrC is studied through the continuum theory of sintering, in which the ZrC power-law creep parameters have been determined through the clarification of electrical and thermal aspects of the employed SPS system. Then the SPS-forging setup is proposed as it is theoretically and experimentally proven to be able to render more densification than the regular SPS. SPS-forging and regular SPS are eventually integrated into a hybrid loading mode SPS regime to combine the advantages of the individual setups to obtain the optimal densification kinetics. Annular shape ZrC pellets have been fabricated using SPS. Finite element modeling framework is constructed to manifest the thermomechanical interactions during the SPS of annular shape ZrC specimens. The fabrication procedures are practically adapted to produce also annular shape carbide composites with excellent high temperature structural strength being used as alternative SPS tooling components. The applicability of annular shape fuel pellet to accommodate volume swelling under its service conditions is investigated. The irradiation-induced swelling phenomena are analyzed by analytical modeling and finite element simulations, in which the generated fission products are considered to be the sources of the fuel pellet swelling.

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

NASA Technical Reports Server (NTRS)

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

2014-01-01

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

Trace metal concentrations in snow from the Yukon River Basin, Alaska and Canada

USGS Publications Warehouse

Wang, B.; Gough, L.; Hinkley, T.; Garbarino, J.; Lamothe, P.

2005-01-01

We report here on metal concentrations in snow collected from the Yukon River basin. Atmospheric transport of metals and subsequent deposition is a known mechanism for introducing metals into the northern environment. Potential sources of airborne elements are locally generated terrestrial sources, locally derived anthropogenic sources, and long range atmospheric transport. Sites were distributed along the Yukon River corridor and within the southeastern, central, and western basin areas. Snow samples were taken in the spring of 2001 and 2002 when the snow pack was at its maximum. Total-depth composite samples were taken from pits using clean techniques. Mercury was analyzed using cold vapor atomic fluorescence spectrometry. All other elements were analyzed by inductively coupled plasma-mass spectrometry. In samples from remote sites, the concentration for selected metals ranged from: 0.015 - 0.34 ug/L for V, 0.01 - 0.22 ug/L for Ni, < 0.05 - 0.52 ug/L for Cu, 0.14 - 2.8 ug/L for Zn, 0.002 - 0.046 ug/L for Cd, 0.03 - 0.13 ug/L for Pb, 0.00041 - 0.0023 ug/L for filtered-Hg. Because the entire snow pack was sampled and there was no evidence of mid-season thaw, these concentrations represent the seasonal deposition. There was no significant difference in the seasonal deposition of V, Ni, Cu, Zn, Cd, and Pb at these sites between 2001 and 2002, and no north-south or east-west trend in concentrations. Samples taken from within communities, however, had significantly higher concentrations of V, Ni, Cu, Zn, and Cd in 2001, and Ni, Cu, and Pb in 2002 relative to the remote sites. Our data indicate that the atmospheric deposition of metals in the Yukon River basin is relatively uniform both spatially and temporally. However, communities have a measurable but variable effect on metal concentrations. Copyright ASCE 2005.

Quantifying the effects of mountain pine beetle infestation on water and biogeochemical cycles at multiple spatial and temporal scales

NASA Astrophysics Data System (ADS)

Brooks, P. D.; Harpold, A. A.; Somor, A. J.; Troch, P. A.; Gochis, D. J.; Ewers, B. E.; Pendall, E.; Biederman, J. A.; Reed, D.; Barnard, H. R.; Whitehouse, F.; Aston, T.; Borkhuu, B.

2010-12-01

Unprecedented levels of bark beetle infestation over the last decade have radically altered forest structure across millions of hectares of Western U.S. montane environments. The widespread extent of this disturbance presents a major challenge for governments and resource managers who lack a predictive understanding of how water and biogeochemical cycles will respond to this disturbance over various temporal and spatial scales. There is a widespread perception, largely based on hydrological responses to fire or logging, that a reduction in both transpiration and interception following tree death will increase soil water availability and catchment water yield. However, few studies have directly addressed the effects of insect-induced forest decline on water and biogeochemical cycling. We address this knowledge gap using observations and modeling at scales from 100 to 109 m2 across study sites in CO and WY that vary in the intensity and timing of beetle infestation and tree death. Our focus on multiple sites with different levels of impact allows us to address two broad, organizing questions: How do changes in vegetation structure associated with MPB alter the partitioning of energy and water? And How do these changes in energy and water availability affect local to regional scale water and biogeochemical cycles? This presentation will focus primarily on energy balance and water partitioning, providing context for ongoing biogeochemical work. During the growing season, stand-scale transpiration declines rapidly and soil moisture increases following infestation, consistent with streamflow data from regional catchments that shows an increase in baseflow following widespread attack. During the winter and spring, stand scale snow surveys and continuous snow depth sensors suggested that the variability in snow cover decreased as the severity of beetle impact increases, but there were no significant stand-scale differences in snow depth among levels of impact. This is due both to an increase in snow under the canopies of dead trees and a decrease in snow cover in canopy gaps. For example, mean snow depth under the canopy was 86cm (CV 0.02) in unimpacted sites and 95cm (CV 0.05) in heavily impacted sites. In canopy gaps however, mean snow depth was 117cm (CV 0.11) in unimpacted sites but only 93cm (CV 0.07) in heavily impacted sites. At the watershed scale, bark beetle infestation was more likely to decrease the amount of both snowmelt and annual runoff, suggesting that the opening of the canopy increases sublimation and evaporation of the snow cover. These data suggest that the disturbance due to bark beetle infestation is both quantitatively and qualitatively different than either fire or logging. Using these observations, we develop a conceptual model for evaluating how biotic and abiotic processes couple water and biogeochemical cycles in forest ecosystems.

Temperature and speed of testing influence on the densification and recovery of polyurethane foams

NASA Astrophysics Data System (ADS)

Apostol, Dragoş Alexandru; Constantinescu, Dan Mihai

2013-02-01

Polyurethane foams with densities of 35, 93, and 200 kg/m3 were tested in compression at three levels of temperatures as: -60 °C, 23 °C, and 80 °C. The influence of speed of testing from 2 mm/min up to 6 m/s (0.0014 to 545 s-1) on the response of the foams is analyzed. Testing is done separately on the rise direction and on the in-plane direction of the foams, and differences in their behavior are commented. With interpolation functions which approximate the plateau and densification region, the specific strain energy is calculated together with the energy efficiency and onset strain of densification. A Nagy-type phenomenological strain-rate-dependent model is proposed to generate engineering stress-strain curves and is validated through comparison with experimental stress-strain curves obtained at different speeds of testing. Starting from a reference experimental curve, two material parameters which are density and temperature dependent are established. Foam recovery for each density of the polyurethane foams is analyzed as a function of direction of testing, temperature, and speed of testing.

Optimization of consolidation parameters of 18Cr-ODS ferritic steel through microstructural and microtexture characterization

NASA Astrophysics Data System (ADS)

Dash, Manmath Kumar; Mythili, R.; Dasgupta, Arup; Saroja, S.

2018-04-01

This paper reports the optimization of consolidation process based on the evolution of microstructure, microtexture and densification in 18%-Cr Oxide Dispersion Strengthened steel. The steel powder of composition Fe-18Cr-0.01C-2W-0.25Ti-0.35Y2O3 has been consolidated by cold isostatic pressing (CIP) for green compaction after mechanical milling. Sintering (1000-1250 °C) and hot isostatic pressing (HIP) at 1150 °C has been employed to achieve good densification on compacted CIP specimen. The effect of sintering temperatures on densification behavior was evaluated and sintering at 1150°C was identified to be optimum for achieving good compaction (92% density) and homogeneous polygonal microstructure with a uniform distribution of fine pores. In addition, HIP of CIP product at 1150°C was found to yield a more homogeneous microstructure as compared to sintered product with 97% density. A static/dynamic recrystallization associated with (1 1 1) texture is observed during consolidation process. A statistical comparison has been made based on frequency of grain boundary distribution and associated texture with its theoretical attributes.

Improving cylinder-type LiFePO4 battery performance via control of internal resistance

NASA Astrophysics Data System (ADS)

Purwanto, Agus; Jumari, Arif; Nizam, Muhammad; Widiyandari, Hendri; Sudaryanto; Deswita; Azmin Mohamad, Ahmad

2018-04-01

Strategies for controlling the internal resistance to improve battery performance were systematically investigated. Electrode densification of LiFePO4 cathodes significantly reduced the internal resistance of the prepared batteries. Densification by reduction to 31.25% of initial thickness resulted in optimal electrochemical performance of the prepared LiFePO4 batteries. The addition of KS 6 graphite material improved the conductivity of the cathodes, which was indicated by a lowering of the internal resistance. The internal resistance was decreased from 73 to 54 when the KS6/AB ratio was varied from 3 to 1. Another factor in controlling the internal resistance was the location of a welded aluminum tab in the cathode. The welding of an aluminum tab in a small gap in the cathode significantly reduced the internal resistance. Thus, three main factors can be performed during fabrication to reduce the internal resistance of a LiFePO4 battery: cathode densification, KS-6 graphite addition, and the arrangement of an aluminum tab welded to the cathode. By optimizing these factors, high-performance LFP batteries were produced.

Different ligand exchange solvents effect on the densification of CuIn0.7Ga0.3Se2 prepared using the heating-up method

NASA Astrophysics Data System (ADS)

Yang, Chang-Ting; Hsiang, Hsing-I.

2017-12-01

The effects of different ligand exchange solvents and heat treatment conditions on the densification and microstructure development of CuIn0.7Ga0.3Se2 (CIGS) crystallites synthesized using the heating-up method were studied in this work. The heat treatment effects on the organic molecules and crystalline structure were investigated using Fourier transform infrared spectroscopy (FTIR), Raman spectroscopy, X-ray diffraction (XRD), scanning electron microscopy (SEM) and transmission electron microscopy (TEM). It was observed that oleylamine (OLA) adsorbed onto the CIGS surface was difficult to remove during sintering. Ligand-exchange with m-xylene or 1-hexanethiol can promote the removal of oleylamine adsorbed onto the CIGS surface and prevent the residual carbon from forming during sintering, which leads to grain growth and densification. A dense CuIn0.7Ga0.3Se2 can be obtained using the precursor powders after ligand-exchange with 1-hexanethiol and m-xylene to remove organic molecules and sintering at 600 °C for 2 h under Se atmosphere.

Importance of climatological downscaling and plant phenology for red deer in heterogeneous landscapes

PubMed Central

Pettorelli, Nathalie; Mysterud, Atle; Yoccoz, Nigel G; Langvatn, Rolf; Stenseth, Nils Chr

2005-01-01

Understanding how climate influences ecosystems represents a challenge in ecology and natural resource management. Although we know that climate affects plant phenology and herbivore performances at any single site, no study has directly coupled the topography–climate interaction (i.e. the climatological downscaling process) with large-scale vegetation dynamics and animal performances. Here we show how climatic variability (measured by the North Atlantic oscillation ‘NAO’) interacts with local topography in determining the vegetative greenness (as measured by the normalized difference vegetation index ‘NDVI’) and the body masses and seasonal movements of red deer (Cervus elaphus) in Norway. Warm springs induced an earlier onset of vegetation, resulting in earlier migration and higher body masses. Increasing values of the winter-NAO corresponded to less snow at low altitude (warmer, more precipitation results in more rain), but more snow at high altitude (colder, more precipitation corresponds to more snow) relative to winters with low winter-NAO. An increasing NAO thus results in a spatially more variable phenology, offering migrating deer an extended period with access to high-quality forage leading to increased body mass. Our results emphasize the importance of incorporating spring as well as the interaction between winter climate and topography when aiming at understanding how plant and animal respond to climate change. PMID:16243701

Potential slab avalanche release area identification from estimated winter terrain: a multi-scale, fuzzy logic approach

NASA Astrophysics Data System (ADS)

Veitinger, Jochen; Purves, Ross Stuart; Sovilla, Betty

2016-10-01

Avalanche hazard assessment requires a very precise estimation of the release area, which still depends, to a large extent, on expert judgement of avalanche specialists. Therefore, a new algorithm for automated identification of potential avalanche release areas was developed. It overcomes some of the limitations of previous tools, which are currently not often applied in hazard mitigation practice. By introducing a multi-scale roughness parameter, fine-scale topography and its attenuation under snow influence is captured. This allows the assessment of snow influence on terrain morphology and, consequently, potential release area size and location. The integration of a wind shelter index enables the user to define release area scenarios as a function of the prevailing wind direction or single storm events. A case study illustrates the practical usefulness of this approach for the definition of release area scenarios under varying snow cover and wind conditions. A validation with historical data demonstrated an improved estimation of avalanche release areas. Our method outperforms a slope-based approach, in particular for more frequent avalanches; however, the application of the algorithm as a forecasting tool remains limited, as snowpack stability is not integrated. Future research activity should therefore focus on the coupling of the algorithm with snowpack conditions.

Global Metabolic Regulation of the Snow Alga Chlamydomonas nivalis in Response to Nitrate or Phosphate Deprivation by a Metabolome Profile Analysis.

PubMed

Lu, Na; Chen, Jun-Hui; Wei, Dong; Chen, Feng; Chen, Gu

2016-05-10

In the present work, Chlamydomonas nivalis, a model species of snow algae, was used to illustrate the metabolic regulation mechanism of microalgae under nutrient deprivation stress. The seed culture was inoculated into the medium without nitrate or phosphate to reveal the cell responses by a metabolome profile analysis using gas chromatography time-of-flight mass spectrometry (GC/TOF-MS). One hundred and seventy-one of the identified metabolites clustered into five groups by the orthogonal partial least squares discriminant analysis (OPLS-DA) model. Among them, thirty of the metabolites in the nitrate-deprived group and thirty-nine of the metabolites in the phosphate-deprived group were selected and identified as "responding biomarkers" by this metabolomic approach. A significant change in the abundance of biomarkers indicated that the enhanced biosynthesis of carbohydrates and fatty acids coupled with the decreased biosynthesis of amino acids, N-compounds and organic acids in all the stress groups. The up- or down-regulation of these biomarkers in the metabolic network provides new insights into the global metabolic regulation and internal relationships within amino acid and fatty acid synthesis, glycolysis, the tricarboxylic acid cycle (TCA) and the Calvin cycle in the snow alga under nitrate or phosphate deprivation stress.

The 20-22 January 2007 Snow Events over Canada: Microphysical Properties

NASA Technical Reports Server (NTRS)

Tao. W.K.; Shi, J.J.; Matsui, T.; Hao, A.; Lang, S.; Peters-Lidard, C.; Skofronick-Jackson, G.; Petersen, W.; Cifelli, R.; Rutledge, S.

2009-01-01

One of the grand challenges of the Global Precipitation Measurement (GPM) mission is to improve precipitation measurements in mid- and high-latitudes during cold seasons through the use of high-frequency passive microwave radiometry. Toward this end, the Weather Research and Forecasting (WRF) model with the Goddard microphysics scheme is coupled with a Satellite Data Simulation Unit (WRF-SDSU) that has been developed to facilitate over-land snowfall retrieval algorithms by providing a virtual cloud library and microwave brightness temperature (Tb) measurements consistent with the GPM Microwave Imager (GMI). This study tested the Goddard cloud microphysics scheme in WRF for snowstorm events (January 20-22, 2007) that took place over the Canadian CloudSAT/CALIPSO Validation Project (C3VP) ground site (Centre for Atmospheric Research Experiments - CARE) in Ontario, Canada. In this paper, the performance of the Goddard cloud microphysics scheme both with 2ice (ice and snow) and 3ice (ice, snow and graupel) as well as other WRF microphysics schemes will be presented. The results are compared with data from the Environment Canada (EC) King Radar, an operational C-band radar located near the CARE site. In addition, the WRF model output is used to drive the Goddard SDSU to calculate radiances and backscattering signals consistent with direct satellite observations for evaluating the model results.

Changes in heavy metals in Antarctic snow from Coats Land since the mid-19th to the late-20th century

NASA Astrophysics Data System (ADS)

Planchon, Frédéric A. M.; Boutron, Claude F.; Barbante, Carlo; Cozzi, Giulio; Gaspari, Vania; Wolff, Eric W.; Ferrari, Christophe P.; Cescon, Paolo

2002-06-01

V, Cr, Mn, Cu, Zn, Co, Ag, Cd, Ba, Pb, Bi and U have been measured in a series of dated snow samples, covering the period from 1834 to 1990, collected at remote, low accumulation sites in Coats Land, Antarctica. They were determined by ultrasensitive inductively coupled sector field mass spectrometry in ultraclean conditions. Concentrations are found to be extremely low, down to 3×10 -15 g/g, for most metals, then confirming the high purity of Antarctic snow. The results show contrasting time trends for the different metals. For Mn, Co, Ba, and possibly V and Cd, no clear time trends are observed. For Cr, Cu, Zn, Ag, Pb, Bi and U, on the other hand, pronounced enhancements are observed during the recent decades. They are attributed to emissions of heavy metals to the atmosphere from human activities in Southern America, Southern Africa and Australia, especially non-ferrous metal mining and smelting in Chile, Peru, Zaire, Zambia and Australia. It shows that atmospheric pollution for heavy metals in the remote Antarctic continent is not limited to Pb and Cu, as previously thought, but also affects several other metals. It is a further indication that atmospheric pollution for heavy metals is really global.

Small-area snow surveys on the northern plains of North Dakota

USGS Publications Warehouse

Emerson, Douglas G.; Carroll, T.R.; Steppuhn, Harold

1985-01-01

Snow-cover data are needed for many facets of hydrology. The variation in snow cover over small areas is the focus of this study. The feasibility of using aerial surveys to obtain information on the snow water equivalent of the snow cover in order to minimize the necessity of labor intensive ground snow surveys was- evaluated. A low-flying aircraft was used to measure attenuations of natural terrestrial gamma radiation by snow cover. Aerial and ground snow surveys of eight 1-mile snow courses and one 4-mile snow course were used in the evaluation, with ground snow surveys used as the base to evaluate aerial data. Each of the 1-mile snow courses consisted of a single land use and all had the same terrain type (plane). The 4-mile snow course consists of a variety of land uses and the same terrain type (plane). Using the aerial snow-survey technique, the snow water equivalent of the 1-mile snow courses was. measured with three passes of the aircraft. Use of more than one pass did not improve the results. The mean absolute difference between the aerial- and ground-measured snow water equivalents for the 1-mile snow courses was 26 percent (0.77 inches). The aerial snow water equivalents determined for the 1-mile snow courses were used to estimate the variations in the snow water equivalents over the 4-mile snow course. The weighted mean absolute difference for the 4-mile snow course was 27 percent (0.8 inches). Variations in snow water equivalents could not be verified adequately by segmenting the aerial snow-survey data because of the uniformity found in the snow cover. On the 4-mile snow coirse, about two-thirds of the aerial snow-survey data agreed with the ground snow-survey data within the accuracy of the aerial technique ( + 0.5 inch of the mean snow water equivalent).

Localized Overheating Phenomena and Optimization of Spark-Plasma Sintering Tooling Design

PubMed Central

Giuntini, Diletta; Olevsky, Eugene A.; Garcia-Cardona, Cristina; Maximenko, Andrey L.; Yurlova, Maria S.; Haines, Christopher D.; Martin, Darold G.; Kapoor, Deepak

2013-01-01

The present paper shows the application of a three-dimensional coupled electrical, thermal, mechanical finite element macro-scale modeling framework of Spark Plasma Sintering (SPS) to an actual problem of SPS tooling overheating, encountered during SPS experimentation. The overheating phenomenon is analyzed by varying the geometry of the tooling that exhibits the problem, namely by modeling various tooling configurations involving sequences of disk-shape spacers with step-wise increasing radii. The analysis is conducted by means of finite element simulations, intended to obtain temperature spatial distributions in the graphite press-forms, including punches, dies, and spacers; to identify the temperature peaks and their respective timing, and to propose a more suitable SPS tooling configuration with the avoidance of the overheating as a final aim. Electric currents-based Joule heating, heat transfer, mechanical conditions, and densification are imbedded in the model, utilizing the finite-element software COMSOL™, which possesses a distinguishing ability of coupling multiple physics. Thereby the implementation of a finite element method applicable to a broad range of SPS procedures is carried out, together with the more specific optimization of the SPS tooling design when dealing with excessive heating phenomena. PMID:28811398

Studies of Malagasy Eugenia - IV: Seventeen new endemic species, a new combination, and three lectotypifications; with comments on distribution, ecological and evolutionary patterns.

PubMed

Snow, Neil; Callmander, Martin; Phillipson, Peter B

2015-01-01

Seventeen new endemic species of the genus Eugenia L. (Myrtaceae) are proposed from Madagascar, including: Eugeniaandapae N. Snow, Eugeniabarriei N. Snow, Eugeniabemangidiensis N. Snow, Eugeniacalciscopulorum N. Snow, Eugeniadelicatissima N. Snow, Callm. & Phillipson, Eugeniaechinulata N. Snow, Eugeniagandhii N. Snow, Eugeniahazonjia N. Snow, Eugeniaiantarensis N. Snow, Eugeniamalcomberi N. Snow, Eugeniamanomboensis N. Snow, Eugeniaobovatifolia N. Snow, Eugeniaranomafana N. Snow & D. Turk, Eugeniaravelonarivoi N. Snow & Callm., Eugeniarazakamalalae N. Snow & Callm., Eugeniatiampoka N. Snow & Callm., and Eugeniawilsoniana N. Snow, and one new combination, Eugeniarichardii (Blume) N. Snow, Callm. & Phillipson is provided. Detailed descriptions, information on distribution and ecology, distribution maps, vernacular names (where known), digital images of types, comparisons to morphologically similar species. Preliminary assessment of IUCN risk of extinction and conservation recommendations are provided, including Vulnerable (4 species), Endangered (2 species), and Critically Endangered (4 species). Lectotpyes are designated for Eugeniahovarum H. Perrier, Eugenianompa H. Perrier, and Eugeniascottii H. Perrier respectively.

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

Poisson's ratio and the densification of glass under high pressure.

PubMed

Rouxel, T; Ji, H; Hammouda, T; Moréac, A

2008-06-06

Because of a relatively low atomic packing density, (Cg) glasses experience significant densification under high hydrostatic pressure. Poisson's ratio (nu) is correlated to Cg and typically varies from 0.15 for glasses with low Cg such as amorphous silica to 0.38 for close-packed atomic networks such as in bulk metallic glasses. Pressure experiments were conducted up to 25 GPa at 293 K on silica, soda-lime-silica, chalcogenide, and bulk metallic glasses. We show from these high-pressure data that there is a direct correlation between nu and the maximum post-decompression density change.

Effects of densification of precursor pellets on microstructures and critical current properties of YBCO melt-textured bulks

NASA Astrophysics Data System (ADS)

Setoyama, Yui; Shimoyama, Jun-ichi; Motoki, Takanori; Kishio, Kohji; Awaji, Satoshi; Kon, Koichi; Ichikawa, Naoki; Inamori, Satoshi; Naito, Kyogo

2016-12-01

Effects of densification of precursor disks on the density of residual voids and critical current properties for YBCO melt-textured bulk superconductors were systematically investigated. Six YBCO bulks were prepared from precursor pellets with different initial particle sizes of YBa2Cu3Oy (Y123) powder and applied pressures for pelletization. It was revealed that use of finer Y123 powder and consolidation using cold-isostatic-pressing (CIP) with higher pressures result in reduction of residual voids at inner regions of bulks and enhance Jc especially under low fields below the second peak.

MODIS Snow Cover Mapping Decision Tree Technique: Snow and Cloud Discrimination

NASA Technical Reports Server (NTRS)

Riggs, George A.; Hall, Dorothy K.

2010-01-01

Accurate mapping of snow cover continues to challenge cryospheric scientists and modelers. The Moderate-Resolution Imaging Spectroradiometer (MODIS) snow data products have been used since 2000 by many investigators to map and monitor snow cover extent for various applications. Users have reported on the utility of the products and also on problems encountered. Three problems or hindrances in the use of the MODIS snow data products that have been reported in the literature are: cloud obscuration, snow/cloud confusion, and snow omission errors in thin or sparse snow cover conditions. Implementation of the MODIS snow algorithm in a decision tree technique using surface reflectance input to mitigate those problems is being investigated. The objective of this work is to use a decision tree structure for the snow algorithm. This should alleviate snow/cloud confusion and omission errors and provide a snow map with classes that convey information on how snow was detected, e.g. snow under clear sky, snow tinder cloud, to enable users' flexibility in interpreting and deriving a snow map. Results of a snow cover decision tree algorithm are compared to the standard MODIS snow map and found to exhibit improved ability to alleviate snow/cloud confusion in some situations allowing up to about 5% increase in mapped snow cover extent, thus accuracy, in some scenes.

A Distributed Snow Evolution Modeling System (SnowModel)

NASA Astrophysics Data System (ADS)

Liston, G. E.; Elder, K.

2004-12-01

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

Studies of Malagasy Eugenia – IV: Seventeen new endemic species, a new combination, and three lectotypifications; with comments on distribution, ecological and evolutionary patterns

PubMed Central

Snow, Neil; Callmander, Martin; Phillipson, Peter B.

2015-01-01

Abstract Seventeen new endemic species of the genus Eugenia L. (Myrtaceae) are proposed from Madagascar, including: Eugenia andapae N. Snow, Eugenia barriei N. Snow, Eugenia bemangidiensis N. Snow, Eugenia calciscopulorum N. Snow, Eugenia delicatissima N. Snow, Callm. & Phillipson, Eugenia echinulata N. Snow, Eugenia gandhii N. Snow, Eugenia hazonjia N. Snow, Eugenia iantarensis N. Snow, Eugenia malcomberi N. Snow, Eugenia manomboensis N. Snow, Eugenia obovatifolia N. Snow, Eugenia ranomafana N. Snow & D. Turk, Eugenia ravelonarivoi N. Snow & Callm., Eugenia razakamalalae N. Snow & Callm., Eugenia tiampoka N. Snow & Callm., and Eugenia wilsoniana N. Snow, and one new combination, Eugenia richardii (Blume) N. Snow, Callm. & Phillipson is provided. Detailed descriptions, information on distribution and ecology, distribution maps, vernacular names (where known), digital images of types, comparisons to morphologically similar species. Preliminary assessment of IUCN risk of extinction and conservation recommendations are provided, including Vulnerable (4 species), Endangered (2 species), and Critically Endangered (4 species). Lectotpyes are designated for Eugenia hovarum H. Perrier, Eugenia nompa H. Perrier, and Eugenia scottii H. Perrier respectively. PMID:25987885

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

Inspiration & Insight - a tribute to Niels Reeh

NASA Astrophysics Data System (ADS)

Ahlstrom, A. P.; Vieli, A.

2009-12-01

Niels Reeh was highly regarded for his contributions to glaciology, specifically through his rigorous combination of numerical modelling and field observations. In 1966 he began his work on the application of beam mechanics to floating glaciers and ice shelves and throughout his life, Niels retained a strong interest in modelling glacier dynamics. In the early 1980s Niels developed a 3D-model for ice sheets and in the late 1980s an advanced flow-line model. Niels Reeh also took part in the early ice-core drilling efforts in Greenland and later pioneered the concept of retrieving similar records from the surface of the ice-sheet margin. Mass balance of glaciers and ice sheets was another theme in Niels Reeh’s research, with a number of important contributions and insights still used when teaching the subject to students. Niels developed elegant models for ablation and snow densification, notable for their applicability in large-scale ice-sheet models and studied the impact of climate change on ice sheets and glaciers. Niels also took his interest in ice-dynamics and mass balance into remote sensing and worked successfully on methods to utilize radar and laser data from airborne surveys and satellites in glaciology. In this, he pioneered the combination of field experiments, satellite observations and numerical modelling to solve problems on the Greenland Ice Sheet. In this presentation we will attempt to provide an overview of Niels Reeh’s many-facetted career in acknowledgement of his contributions to the field of glaciology.

Seismic surveys test on Innerhytta Pingo, Adventdalen, Svalbard Islands

NASA Astrophysics Data System (ADS)

Boaga, Jacopo; Rossi, Giuliana; Petronio, Lorenzo; Accaino, Flavio; Romeo, Roberto; Wheeler, Walter

2015-04-01

We present the preliminary results of an experimental full-wave seismic survey test conducted on the Innnerhytta a Pingo, located in the Adventdalen, Svalbard Islands, Norway. Several seismic surveys were adopted in order to study a Pingo inner structure, from classical reflection/refraction arrays to seismic tomography and surface waves analysis. The aim of the project IMPERVIA, funded by Italian PNRA, was the evaluation of the permafrost characteristics beneath this open-system Pingo by the use of seismic investigation, evaluating the best practice in terms of logistic deployment. The survey was done in April-May 2014: we collected 3 seismic lines with different spacing between receivers (from 2.5m to 5m), for a total length of more than 1 km. We collected data with different vertical geophones (with natural frequency of 4.5 Hz and 14 Hz) as well as with a seismic snow-streamer. We tested different seismic sources (hammer, seismic gun, fire crackers and heavy weight drop), and we verified accurately geophone coupling in order to evaluate the different responses. In such peculiar conditions we noted as fire-crackers allow the best signal to noise ratio for refraction/reflection surveys. To ensure the best geophones coupling with the frozen soil, we dug snow pits, to remove the snow-cover effect. On the other hand, for the surface wave methods, the very high velocity of the permafrost strongly limits the generation of long wavelengths both with these explosive sources as with the common sledgehammer. The only source capable of generating low frequencies was a heavy drop weight system, which allows to analyze surface wave dispersion below 10 Hz. Preliminary data analysis results evidence marked velocity inversions and strong velocity contrasts in depth. The combined use of surface and body waves highlights the presence of a heterogeneous soil deposit level beneath a thick layer of permafrost. This is the level that hosts the water circulation from depth controlling the Pingo structure evolution.

Imaging with hypertelescopes: a simple modal approach

NASA Astrophysics Data System (ADS)

Aime, C.

2008-05-01

Aims: We give a simple analysis of imaging with hypertelescopes, a technique proposed by Labeyrie to produce snapshot images using arrays of telescopes. The approach is modal: we describe the transformations induced by the densification onto a sinusoidal decomposition of the focal image instead of the usual point spread function approach. Methods: We first express the image formed at the focus of a diluted array of apertures as the product R_0(α) X_F(α) of the diffraction pattern of the elementary apertures R_0(α) by the object-dependent interference term X_F(α) between all apertures. The interference term, which can be written in the form of a Fourier Series for an extremely diluted array, produces replications of the object, which makes observing the image difficult. We express the focal image after the densification using the approach of Tallon and Tallon-Bosc. Results: The result is very simple for an extremely diluted array. We show that the focal image in a periscopic densification of the array can be written as R_0(α) X_F(α/γ), where γ is the factor of densification. There is a dilatation of the interference term while the diffraction term is unchanged. After de-zooming, the image can be written as γ2 X_F(α)R_0(γ α), an expression which clearly indicates that the final image corresponds to the center of the Fizeau image intensified by γ2. The imaging limitations of hypertelescopes are therefore those of the original configuration. The effect of the suppression of image replications is illustrated in a numerical simulation for a fully redundant configuration and a non-redundant one.

Gadolinium doped ceria interlayers for Solid Oxide Fuel Cells cathodes: Enhanced reactivity with sintering aids (Li, Cu, Zn), and improved densification by infiltration

NASA Astrophysics Data System (ADS)

Nicollet, Clement; Waxin, Jenny; Dupeyron, Thomas; Flura, Aurélien; Heintz, Jean-Marc; Ouweltjes, Jan Pieter; Piccardo, Paolo; Rougier, Aline; Grenier, Jean-Claude; Bassat, Jean-Marc

2017-12-01

This paper reports the study of the densification of 20% Gd doped ceria (Ce0.8Gd0.2O1.9 (GDC)) interlayers in SOFC cathodes through two different routes: the well-known addition of sintering elements, and an innovative densification process by infiltration. First, Li, Cu, and Zn nitrates were added to GDC powders. The effect of these additives on the densification was studied by dilatometry on pellets, and show a large decrease of the sintering temperature from 1330 °C (pure GDC), down to 1080 °C, 950 °C, and 930 °C for Zn, Cu, and Li addition, respectively. However, this promising result does not apply to screen-printed layers, which are more porous than pellets and in which the shrinkage is constrained by the substrate. The second approach consists in preparing a pre-sintered GDC layer, which is subsequently infiltrated with Ce and Gd nitrates and sintered at 1250 °C to increase its density. Such an approach results in highly dense GDC interlayers. Using La0.6Sr0.4Co0.2Fe0.8O3-δ (LSCF) as electrode, the influence of the interlayers on the cathode performance was studied. The addition of sintering aids dramatically increases the cell resistances, most likely because the additives increase the reactivity between GDC and either Yttria Stabilized Zirconia (YSZ) or LSCF, thus losing the expected benefit related to the decrease of sintering temperatures. The interlayers prepared by infiltration do not induce additional resistances in the cell, which results in power densities of single cells 40-50% higher than those of cells prepared with commercial GDC interlayers, making this approach a valuable alternative to sintering aids.

Remote sensing of impervious surface growth: A framework for quantifying urban expansion and re-densification mechanisms

NASA Astrophysics Data System (ADS)

Shahtahmassebi, Amir Reza; Song, Jie; Zheng, Qing; Blackburn, George Alan; Wang, Ke; Huang, Ling Yan; Pan, Yi; Moore, Nathan; Shahtahmassebi, Golnaz; Sadrabadi Haghighi, Reza; Deng, Jing Song

2016-04-01

A substantial body of literature has accumulated on the topic of using remotely sensed data to map impervious surfaces which are widely recognized as an important indicator of urbanization. However, the remote sensing of impervious surface growth has not been successfully addressed. This study proposes a new framework for deriving and summarizing urban expansion and re-densification using time series of impervious surface fractions (ISFs) derived from remotely sensed imagery. This approach integrates multiple endmember spectral mixture analysis (MESMA), analysis of regression residuals, spatial statistics (Getis_Ord) and urban growth theories; hence, the framework is abbreviated as MRGU. The performance of MRGU was compared with commonly used change detection techniques in order to evaluate the effectiveness of the approach. The results suggested that the ISF regression residuals were optimal for detecting impervious surface changes while Getis_Ord was effective for mapping hotspot regions in the regression residuals image. Moreover, the MRGU outputs agreed with the mechanisms proposed in several existing urban growth theories, but importantly the outputs enable the refinement of such models by explicitly accounting for the spatial distribution of both expansion and re-densification mechanisms. Based on Landsat data, the MRGU is somewhat restricted in its ability to measure re-densification in the urban core but this may be improved through the use of higher spatial resolution satellite imagery. The paper ends with an assessment of the present gaps in remote sensing of impervious surface growth and suggests some solutions. The application of impervious surface fractions in urban change detection is a stimulating new research idea which is driving future research with new models and algorithms.

Processing and characterization of boron carbide-hafnium diboride ceramics

NASA Astrophysics Data System (ADS)

Brown-Shaklee, Harlan James

Hafnium diboride based ceramics are promising candidate materials for advanced aerospace and nuclear reactor components. The effectiveness of boron carbide and carbon as HfB2 sintering additives was systematically evaluated. In the first stage of the research, boron carbide and carbon additives were found to improve the densification behavior of milled HfB2 powder in part by removing oxides at the HfB2 surface during processing. Boron carbide additives reduced the hot pressing temperature of HfB2 by 150°C compared to carbon, which reduced the hot pressing temperature by ˜50°C. Reduction of oxide impurities alone could not explain the difference in sintering enhancement, however, and other mechanisms of enhancement were evaluated. Boron carbides throughout the homogeneity range were characterized to understand other mechanisms of sintering enhancement in HfB2. Heavily faulted carbon rich and boron rich boron carbides were synthesized for addition to HfB2. The greatest enhancement to densification was observed in samples containing boron- and carbon-rich compositions whereas B6.5 C provided the least enhancement to densification. It is proposed that carbon rich and boron rich boron carbides create boron and hafnium point defects in HfB2, respectively, which facilitate densification. Evaluation of the thermal conductivity (kth) between room temperature and 2000°C suggested that the stoichiometry of the boron carbide additives did not significantly affect kth of HfB2-BxC composites. The improved sinterability and the high kth (˜110 W/m-K at 300K and ˜90 W/m-K at 1000°C ) of HfB2-BxC ceramics make them excellent candidates for isotopically enriched reactor control materials.

Potential for Monitoring Snow Cover in Boreal Forests by Combining MODIS Snow Cover and AMSR-E SWE Maps

NASA Technical Reports Server (NTRS)

Riggs, George A.; Hall, Dorothy K.; Foster, James L.

2009-01-01

Monitoring of snow cover extent and snow water equivalent (SWE) in boreal forests is important for determining the amount of potential runoff and beginning date of snowmelt. The great expanse of the boreal forest necessitates the use of satellite measurements to monitor snow cover. Snow cover in the boreal forest can be mapped with either the Moderate Resolution Imaging Spectroradiometer (MODIS) or the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) microwave instrument. The extent of snow cover is estimated from the MODIS data and SWE is estimated from the AMSR-E. Environmental limitations affect both sensors in different ways to limit their ability to detect snow in some situations. Forest density, snow wetness, and snow depth are factors that limit the effectiveness of both sensors for snow detection. Cloud cover is a significant hindrance to monitoring snow cover extent Using MODIS but is not a hindrance to the use of the AMSR-E. These limitations could be mitigated by combining MODIS and AMSR-E data to allow for improved interpretation of snow cover extent and SWE on a daily basis and provide temporal continuity of snow mapping across the boreal forest regions in Canada. The purpose of this study is to investigate if temporal monitoring of snow cover using a combination of MODIS and AMSR-E data could yield a better interpretation of changing snow cover conditions. The MODIS snow mapping algorithm is based on snow detection using the Normalized Difference Snow Index (NDSI) and the Normalized Difference Vegetation Index (NDVI) to enhance snow detection in dense vegetation. (Other spectral threshold tests are also used to map snow using MODIS.) Snow cover under a forest canopy may have an effect on the NDVI thus we use the NDVI in snow detection. A MODIS snow fraction product is also generated but not used in this study. In this study the NDSI and NDVI components of the snow mapping algorithm were calculated and analyzed to determine how they changed through the seasons. A blended snow product, the Air Force Weather Agency and NASA (ANSA) snow algorithm and product has recently been developed. The ANSA algorithm blends the MODIS snow cover and AMSR-E SWE products into a single snow product that has been shown to improve the performance of snow cover mapping. In this study components of the ANSA snow algorithm are used along with additional MODIS data to monitor daily changes in snow cover over the period of 1 February to 30 June 2008.

Spatiotemporal Heterogeneity of Dissolved Organic Carbon in Waters and Soils in a Snow-dominated Headwater Catchment: Investigations at Reynolds Creek Critical Zone Observatory, Owyhee County, Idaho

NASA Astrophysics Data System (ADS)

Radke, A. G.; Godsey, S.; Lohse, K. A.; Huber, D. P.; Patton, N. R.; Holbrook, S.

2017-12-01

The non-uniform distribution of precipitation in snowmelt-driven systems—the result of blowing and drifting snow—is a primary driver of spatial heterogeneity in vegetative communities and soil development. Snowdrifts may increase bedrock weathering below them, creating deeper soils and the potential for greater fracture flow. These snowdrift areas are also commonly more productive than the snow-starved, scoured areas where wind has removed snow. Warming-induced changes in the fraction of precipitation falling as snow, and therefore subject to drifting, may significantly affect carbon dynamics on multiple timescales. The focus of this study is to understand the coupled hydrological and carbon dynamics in a heterogeneous, drift-dominated watershed. We seek to determine the paths of soil water and groundwater in a small headwater catchment (Reynolds Mountain East, Reynolds Creek Critical Zone Observatory, Idaho, USA). Additionally, we anticipate quantifying the flux of dissolved organic carbon through these paths, and relate this to zones of greater vegetative productivity. We deduce likely flowpaths through a combination of soil water, groundwater, and precipitation characterization. Along a transect running from a snowdrift to the stream, we measure hydrometric and hydrochemical signatures of flow throughout the snowmelt period and summer. We then use end-member-mixing analysis to interpret flowpaths in light of inferred subsurface structure derived from drilling and electrical resistance tomography transects. Preliminary results from soil moisture sensors suggest that increased bedrock weathering creates pathways by which snowmelt bypasses portions of the soil, further increasing landscape heterogeneity. Further analysis will identify seasonal changes in carbon sourcing for this watershed, but initial indications are that spring streamwater is sourced primarily from soil water, with close associations between soil carbon and DOC.

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

Radiation survey on Fukushima Medical University premises about four years after the Fukushima nuclear disaster

PubMed Central

Omori, Yasutaka; Wakamatsu, Hiroaki; Sorimachi, Atsuyuki; Ishikawa, Tetsuo

2016-01-01

Abstract This study was conducted on the Fukushima Medical University (FMU) premises (in Fukushima City, Fukushima Prefecture) about four years after the Fukushima Daiichi Nuclear Power Plant accident.　Its objectives were (1) to create a map of the ambient gamma dose rate (air-kerma rate) distribution, (2) to evaluate the air-kerma rate originating from natural radionuclides, and (3) to investigate the effects of snow cover on changes in the air-kerma rate.　This man-borne survey revealed that the air-kerma rate varies widely, ranging from 0.038 μGy h－1 to 0.520 μGy h－1, and is higher on grass than on the other investigated surface types, such as soil, asphalt, and bricks.　In this area, the mean air-kerma rate from natural radiation was evaluated to be 0.03 ± 0.01 μGy h－1, which is close to 0.04 μGy h－1, which was measured in central Fukushima City by a local authority.Furthermore, snowfall was found to reduce the air-kerma rate by 5%-30%.　This reduction was attributed to attenuation of the primary radiation while passing through the snow cover, and the measured contribution of scattered radiation to the air-kerma rate reduction was small.　The reduction rate was found to depend on the initial snow depth but to maintain a similar value for a couple of days, after the snow had partially melted and its depth had decreased.　Finally, analysis of the daily dose due to external exposure received on the FMU premises revealed that no further health effects due to chronic radiation exposure at this site are to be expected. PMID:26911302

Radiation survey on Fukushima Medical University premises about four years after the Fukushima nuclear disaster.

PubMed

Omori, Yasutaka; Wakamatsu, Hiroaki; Sorimachi, Atsuyuki; Ishikawa, Tetsuo

2016-06-08

This study was conducted on the Fukushima Medical University (FMU) premises (in Fukushima City, Fukushima Prefecture) about four years after the Fukushima Daiichi Nuclear Power Plant accident.　Its objectives were (1) to create a map of the ambient gamma dose rate (air-kerma rate) distribution, (2) to evaluate the air-kerma rate originating from natural radionuclides, and (3) to investigate the effects of snow cover on changes in the air-kerma rate.　This man-borne survey revealed that the air-kerma rate varies widely, ranging from 0.038 μGy h(－1) to 0.520 μGy h(－1), and is higher on grass than on the other investigated surface types, such as soil, asphalt, and bricks.　In this area, the mean air-kerma rate from natural radiation was evaluated to be 0.03 ± 0.01 μGy h(－1), which is close to 0.04 μGy h(－1), which was measured in central Fukushima City by a local authority.Furthermore, snowfall was found to reduce the air-kerma rate by 5%-30%.　This reduction was attributed to attenuation of the primary radiation while passing through the snow cover, and the measured contribution of scattered radiation to the air-kerma rate reduction was small.　The reduction rate was found to depend on the initial snow depth but to maintain a similar value for a couple of days, after the snow had partially melted and its depth had decreased.　Finally, analysis of the daily dose due to external exposure received on the FMU premises revealed that no further health effects due to chronic radiation exposure at this site are to be expected.

Use of the Water, Energy, and Biogeochemical Model (WEBMOD) to Simulate Water Quality at Five U.S. Geological Survey Research Watersheds

NASA Astrophysics Data System (ADS)

Webb, R. M.; Leavesley, G. H.; Shanley, J. B.; Peters, N. E.; Aulenbach, B. T.; Blum, A. E.; Campbell, D. H.; Clow, D. W.; Mast, M. A.; Stallard, R. F.; Larsen, M. C.; Troester, J. W.; Walker, J. F.; White, A. F.

2003-12-01

The Water, Energy, and Biogeochemical Model (WEBMOD) was developed as an aid to compare and contrast basic hydrologic and biogeochemical processes active in the diverse hydroclimatic regions represented by the five U.S. Geological Survey (USGS) Water, Energy, and Biogeochemical Budget (WEBB) sites: Loch Vale, Colorado; Trout Lake, Wisconsin; Sleepers River, Vermont; Panola Mountain, Georgia; and Luquillo Experimental Forest, Puerto Rico. WEBMOD simulates solute concentrations for vegetation canopy, snow pack, impermeable ground, leaf litter, unsaturated and saturated soil zones, riparian zones and streams using selected process modules coupled within the USGS Modular Modeling System (MMS). Source codes for the MMS hydrologic modules include the USGS Precipitation Runoff Modeling System, the National Weather Service Hydro-17 snow model, and TOPMODEL. The hydrologic modules distribute precipitation and temperature to predict evapotranspiration, snow accumulation, snow melt, and streamflow. Streamflow generation mechanisms include infiltration excess, saturated overland flow, preferential lateral flow, and base flow. Input precipitation chemistry, and fluxes and residence times predicted by the hydrologic modules are input into the geochemical module where solute concentrations are computed for a series of discrete well-mixed reservoirs using calls to the geochemical engine PHREEQC. WEBMOD was used to better understand variations in water quality observed at the WEBB sites from October 1991 through September 1997. Initial calibrations were completed by fitting the simulated hydrographs with those measured at the watershed outlets. Model performance was then refined by comparing the predicted export of conservative chemical tracers such as chloride, with those measured at the watershed outlets. The model succeeded in duplicating the temporal variability of net exports of major ions from the watersheds.

Precipitation Phase Partitioning during Inland Penetrating Atmospheric River events: Role of Initial Land Surface Conditions

NASA Astrophysics Data System (ADS)

Rudisill, W. J.; Flores, A. N.; FitzGerald, K.; Masarik, M. T.

2017-12-01

In the Western US, the occurrence (or lack thereof) of a handful of cool-season Atmospheric River (AR) events exerts significant controls on the seasonal water budget in many watersheds. The occurrence of these ARs can serve to alleviate drought and can also lead to significant flooding. In winter seasons, ARs typically bring warmer than average conditions and both rain and snow. To date, there has been little effort to understand how the land surface hydrological states prior to and during the arrival of ARs, acting on the surface water and energy balance, impact the onset, extent, and evolution of precipitation intensity and phase during AR events. While precipitation arriving as snow can contribute to seasonal snowpacks that lead to runoff later in hot/dry seasons, liquid precipitation can contribute to more rapid runoff or deplete existing snowpacks. The latter case, in which latent and advected heat from fallen rain causes snowmelt, is a key mechanism of flood and landslide-producing runoff in the Western United States. Motivated by an extensive, flood producing AR in 2010, we examine the sensitivity of hydrometeor phase to land surface forcings (sensible/latent heating, short/longwave radiation) using the WRF (Weather Research and Forecasting) model in Central Idaho. Specifically, we evaluate whether pre-existing snow covered area extent, snow water equivalent (SWE), and cold-content influence the partitioning of precipitation into solid and liquid phases during inland AR events. Our experimental design leverages a long-term coupled land-atmosphere simulation with WRF over the study domain in order to evaluate how a set of particular AR events evolve when exposed to initial land surface states capturing a broad range of climatological conditions during the past 30 years.

Cloud Properties Simulated by a Single-Column Model. Part II: Evaluation of Cumulus Detrainment and Ice-phase Microphysics Using a Cloud Resolving Model

NASA Technical Reports Server (NTRS)

Luo, Yali; Krueger, Steven K.; Xu, Kuan-Man

2005-01-01

This paper is the second in a series in which kilometer-scale-resolving observations from the Atmospheric Radiation Measurement program and a cloud-resolving model (CRM) are used to evaluate the single-column model (SCM) version of the National Centers for Environmental Prediction Global Forecast System model. Part I demonstrated that kilometer-scale cirrus properties simulated by the SCM significantly differ from the cloud radar observations while the CRM simulation reproduced most of the cirrus properties as revealed by the observations. The present study describes an evaluation, through a comparison with the CRM, of the SCM's representation of detrainment from deep cumulus and ice-phase microphysics in an effort to better understand the findings of Part I. It is found that detrainment occurs too infrequently at a single level at a time in the SCM, although the detrainment rate averaged over the entire simulation period is somewhat comparable to that of the CRM simulation. Relatively too much detrained ice is sublimated when first detrained. Snow falls over too deep of a layer due to the assumption that snow source and sink terms exactly balance within one time step in the SCM. These characteristics in the SCM parameterizations may explain many of the differences in the cirrus properties between the SCM and the observations (or between the SCM and the CRM). A possible improvement for the SCM consists of the inclusion of multiple cumulus cloud types as in the original Arakawa-Schubert scheme, prognostically determining the stratiform cloud fraction and snow mixing ratio. This would allow better representation of the detrainment from deep convection, better coupling of the volume of detrained air with cloud fraction, and better representation of snow field.

Meltwater Contributions to Irrigation in High Mountain Asia Under a Changing Climate

NASA Astrophysics Data System (ADS)

Grogan, D. S.; Wisser, D.; Proussevitch, A. A.; Lammers, R. B.; Frolking, S. E.

2016-12-01

Snow melt and glacier melt are known to contribute significantly to river flows in High Mountain Asia. This region is also an important agricultural producer, and relies heavily on irrigation. In this study we use a hydrologic model coupled with a glacier model to quantify the historical contribution of snow melt and glacier melt to irrigation water use in High Mountain Asia, with detailed basin-level budgets of meltwater use, re-use, and contributions to crop evapotranspiration. We find that it is important to quantify not only how much meltwater is extracted from rivers and reservoirs for irrigation, but also to track this water through irrigation return flows and downstream re-use. We also project future basin-level meltwater use for irrigation, making use of a suite of climate model projections and associated glacier model projections. We assess the relative importance of snow melt and glacier melt to irrigation supplies across seasons, and for future projections we compare temporal shifts in meltwater hydrographs to potential shifts in crop planting dates due to increasing temperatures and shifts in monsoon onset. Results show that, historically (c. 2000), meltwater for irrigation is most important in the Indus and Ganges basins, which use 90 km3yr-1 and 20 km3yr-1 meltwater, respectively. In both basins, snow melt contributions to annual irrigation use are larger than glacier melt contributions, but the relative importance of these two meltwater sources shifts through the growing season. Uncertainties in future precipitation projections lead to large differences in the direction of change of future meltwater use for irrigation: depending upon the climate model and pathway used, we find that meltwater availability may decrease or increase in 2070-2099 compared to historical results.

A hydrogeologic framework for characterizing summer streamflow sensitivity to climate warming in the Pacific Northwest, USA

NASA Astrophysics Data System (ADS)

Safeeq, M.; Grant, G. E.; Lewis, S. L.; Kramer, M. G.; Staab, B.

2014-09-01

Summer streamflows in the Pacific Northwest are largely derived from melting snow and groundwater discharge. As the climate warms, diminishing snowpack and earlier snowmelt will cause reductions in summer streamflow. Most regional-scale assessments of climate change impacts on streamflow use downscaled temperature and precipitation projections from general circulation models (GCMs) coupled with large-scale hydrologic models. Here we develop and apply an analytical hydrogeologic framework for characterizing summer streamflow sensitivity to a change in the timing and magnitude of recharge in a spatially explicit fashion. In particular, we incorporate the role of deep groundwater, which large-scale hydrologic models generally fail to capture, into streamflow sensitivity assessments. We validate our analytical streamflow sensitivities against two empirical measures of sensitivity derived using historical observations of temperature, precipitation, and streamflow from 217 watersheds. In general, empirically and analytically derived streamflow sensitivity values correspond. Although the selected watersheds cover a range of hydrologic regimes (e.g., rain-dominated, mixture of rain and snow, and snow-dominated), sensitivity validation was primarily driven by the snow-dominated watersheds, which are subjected to a wider range of change in recharge timing and magnitude as a result of increased temperature. Overall, two patterns emerge from this analysis: first, areas with high streamflow sensitivity also have higher summer streamflows as compared to low-sensitivity areas. Second, the level of sensitivity and spatial extent of highly sensitive areas diminishes over time as the summer progresses. Results of this analysis point to a robust, practical, and scalable approach that can help assess risk at the landscape scale, complement the downscaling approach, be applied to any climate scenario of interest, and provide a framework to assist land and water managers in adapting to an uncertain and potentially challenging future.

Probing the water and CO snow lines in the young protostar NGC 1333-IRAS4B

NASA Astrophysics Data System (ADS)

Anderl, Sibylle; Maret, Sébastien; André, Philippe; Maury, Anaëlle; Belloche, Arnaud; Cabrit, Sylvie; Codella, Claudio; Lefloch, Bertrand

2015-08-01

Today, we believe that the onset of life requires free energy, water, and complex, probably carbon-based chemistry. In the interstellar medium, complex organic molecules seem to mostly form in reactions happening on the icy surface of dust grains, such that they are released into the gas phase when the dust is heated. The resulting “snow lines”, marking regions where ices start to sublimate, play an important role for planet growth and bulk composition in protoplanetary disks. However, they can already be observed in the envelopes of the much younger, low-mass Class 0 protostars that are still in their early phase of heavy accretion. The information on the sublimation regions of different kinds of ices can be used to understand the chemistry of the envelope, its temperature and density structure, and may even hint at the history of the accretion process. Accordingly, it is a crucial piece of information in order to get the full picture of how organic chemistry evolves already at the earliest stages of the formation of sun-like stars. As part of the CALYPSO Large Program (http://irfu.cea.fr/Projets/Calypso/), we have obtained observations of C18O, N2H+ and CH3OH towards the Class 0 protostar NGC 1333-IRAS4B with the IRAM Plateau de Bure interferometer at sub-arcsecond resolution. Of these we use the methanol observations as a proxy for the water snow line, assuming methanol is trapped in water ice. The observed anti-correlation of C18O and N2H+, with N2H+ forming a ring around the centrally peaked C18O emission, reveals for the first time the CO snow line in this protostellar envelope, with a radius of ~300 AU. The methanol emission is much more compact than that of C18O, and traces the water snow line with a radius of ~40 AU. We have modeled the emission using a chemical model coupled with a radiative transfer module. We find that the CO snow line appears further inwards than expected from the binding energy of pure CO ices. This may hint at CO being frozen out in H2O or CO2 dominated ices. Our observations can thereby yield clues on the widely unknown composition of interstellar ices, being the initial seeds of complex organic chemistry.

Using CREST to Model Floods for the Upper Missouri Basin

NASA Astrophysics Data System (ADS)

Rodriguez, L.; Spelman, D.; Skym, P.; Oguamanam, M.

2012-12-01

The Upper Missouri River basin in Montana is prone to frequent floods during the months of May through June. During the summer of 2011, the duration of heavy rain and high snow melt caused floods in the Missouri Watershed to last for several weeks. Although organizations and citizens are aware of the flooding, the severity of any given flood is difficult to predict. Thus, a flood forecasting system would benefit the community by providing advance notice of areas prone to floods. The team addressed these issues by calibrating a fully distributed hydrological model on this region using the University of Oklahoma's Coupled Routing Excess STorage (CREST) 2.0 model. The CREST model contains ten internal parameters that must be optimized through calibration to in-situ data which was done using only remotely sensed data as inputs; these include: rainfall from TRMM, Digital Elevation Model (DEM) from SRTM, and potential evapotranspiration (PET). At a one kilometer spatial and three hour temporal resolutions, CREST was calibrated over a three year period. This calibration was unsuccessful, resulting in a maximum NSCE of just 0.24, due to the heavy impact of snow-pack melt on the hydrology of the Upper Missouri River watershed and the lack of snow melt inputs to the model. Because of this, a modeled snow melt product, which was selected to be the Snow Data Assimilation System (SNODAS), was implemented into the model for the first time. This implementation required substantial data processing prior to input as well as substantial troubleshooting within the CREST model. Additionally, the San Bernard watershed, which is in the absence of snow, was used and calibrated in the model for comparison. The arrangement of these calibrations was performed, and the necessary steps required were documented. However, the actual calibrations were not carried out due to lack of access needed in computational power and time. Significant progress was made in understanding the fundamental steps used in the implementation of various types of input data into the CREST model. This progress was documented in the aid of future calibrations and widespread use of the model. With the information and groundwork established by the team, final calibration and validation can be done on the Upper Missouri River which will allow insight for our partners to incorporate a global application of CREST.

1D-Var multilayer assimilation of X-band SAR data into a detailed snowpack model

NASA Astrophysics Data System (ADS)

Phan, X. V.; Ferro-Famil, L.; Gay, M.; Durand, Y.; Dumont, M.; Morin, S.; Allain, S.; D'Urso, G.; Girard, A.

2014-10-01

The structure and physical properties of a snowpack and their temporal evolution may be simulated using meteorological data and a snow metamorphism model. Such an approach may meet limitations related to potential divergences and accumulated errors, to a limited spatial resolution, to wind or topography-induced local modulations of the physical properties of a snow cover, etc. Exogenous data are then required in order to constrain the simulator and improve its performance over time. Synthetic-aperture radars (SARs) and, in particular, recent sensors provide reflectivity maps of snow-covered environments with high temporal and spatial resolutions. The radiometric properties of a snowpack measured at sufficiently high carrier frequencies are known to be tightly related to some of its main physical parameters, like its depth, snow grain size and density. SAR acquisitions may then be used, together with an electromagnetic backscattering model (EBM) able to simulate the reflectivity of a snowpack from a set of physical descriptors, in order to constrain a physical snowpack model. In this study, we introduce a variational data assimilation scheme coupling TerraSAR-X radiometric data into the snowpack evolution model Crocus. The physical properties of a snowpack, such as snow density and optical diameter of each layer, are simulated by Crocus, fed by the local reanalysis of meteorological data (SAFRAN) at a French Alpine location. These snowpack properties are used as inputs of an EBM based on dense media radiative transfer (DMRT) theory, which simulates the total backscattering coefficient of a dry snow medium at X and higher frequency bands. After evaluating the sensitivity of the EBM to snowpack parameters, a 1D-Var data assimilation scheme is implemented in order to minimize the discrepancies between EBM simulations and observations obtained from TerraSAR-X acquisitions by modifying the physical parameters of the Crocus-simulated snowpack. The algorithm then re-initializes Crocus with the modified snowpack physical parameters, allowing it to continue the simulation of snowpack evolution, with adjustments based on remote sensing information. This method is evaluated using multi-temporal TerraSAR-X images acquired over the specific site of the Argentière glacier (Mont-Blanc massif, French Alps) to constrain the evolution of Crocus. Results indicate that X-band SAR data can be taken into account to modify the evolution of snowpack simulated by Crocus.

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.

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...

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).

Modeling the effect of glacier recession on streamflow response using a coupled glacio-hydrological model

DOE PAGES

Frans, Chris D.; Clarke, Garry K. C.; Burns, P.; ...

2014-02-27

Here, we describe an integrated spatially distributed hydrologic and glacier dynamic model, and use it to investigate the effect of glacier recession on streamflow variations for the Upper Bow River basin, a tributary of the South Saskatchewan River. Several recent studies have suggested that observed decreases in summer flows in the South Saskatchewan River are partly due to the retreat of glaciers in the river's headwaters. Modeling the effect of glacier changes on streamflow response in river basins such as the South Saskatchewan is complicated due to the inability of most existing physically-based distributed hydrologic models to represent glacier dynamics.more » We compare predicted variations in glacier extent, snow water equivalent and streamflow discharge made with the integrated model with satellite estimates of glacier area and terminus position, observed streamflow and snow water equivalent measurements over the period of 1980 2007. Simulations with the coupled hydrology-glacier model reduce the uncertainty in streamflow predictions. Our results suggested that on average, the glacier melt contribution to the Bow River flow upstream of Lake Louise is about 30% in summer. For warm and dry years, however, the glacier melt contribution can be as large as 50% in August, whereas for cold years, it can be as small as 20% and the timing of glacier melt signature can be delayed by a month.« less

Snow cover and snow goose Anser caerulescens caerulescens distribution during spring migration

USGS Publications Warehouse

Hupp, Jerry W.; Zacheis, Amy B.; Anthony, R. Michael; Robertson, Donna G.; Erickson, Wallace P.; Palacios, Kelly C.

2001-01-01

Arctic geese often use spring migration stopover areas when feeding habitats are partially snow covered. Melting of snow during the stopover period causes spatial and temporal variability in distribution and abundance of feeding habitat. We recorded changes in snow cover and lesser snow goose Anser caerulescens caerulescens distribution on a spring migration stopover area in south-central Alaska during aerial surveys in 1993-1994. Our objectives were to determine whether geese selected among areas with different amounts of snow cover and to assess how temporal changes in snow cover affected goose distribution. We also measured temporal changes in chemical composition of forage species after snow melt. We divided an Arc/Info coverage of the approximately 210 km2 coastal stopover area into 2-km2 cells, and measured snow cover and snow goose use of cells. Cells that had 10-49.9% snow cover were selected by snow geese, whereas cells that lacked snow cover were avoided. In both years, snow cover diminished along the coast between mid-April and early May. Flock distribution changed as snow geese abandoned snow-free areas in favour of cells where snow patches were interspersed with bare ground. Snow-free areas may have been less attractive to geese because available forage had been quickly exploited as bare ground was exposed, and because soils became drier making extraction of underground forage more difficult. Fiber content of two forage species increased whereas non-structural carbohydrate concentrations of forage plants appeared to diminish after snow melt, but changes in nutrient concentrations likely occurred too slowly to account for abandonment of snow-free areas by snow geese.

Storylines of socio-economic and climatic drivers for land use and their hydrological impacts in alpine catchments - the STELLA project example

NASA Astrophysics Data System (ADS)

Strasser, Ulrich; Formayer, Herbert; Förster, Kristian; Marke, Thomas; Meißl, Gertraud; Schermer, Markus; Stotten, Friederike; Themessl, Matthias

2016-04-01

Future land use in Alpine catchments is controlled by the evolution of socio-economy and climate. Estimates of their coupled development should hence fulfill the principles of plausibility (be convincing) and consistency (be unambiguous). In the project STELLA, coupled future climate and land use scenarios are used as input in a hydrological modelling exercise with the physically-based, distributed water balance model WaSiM. The aim of the project is to quantify the effects of these two framing components on the future water cycle. The test site for the simulations is the catchment of the Brixentaler Ache in Tyrol/Austria (47.5°N, 322 km2). The so-called „storylines" of future coupled climate and forest/land use management, policy, social cooperation, tourism and economy have jointly been developed in an inter- and transdisciplinary assessment with local actors. The climate background is given by simulations for the A1B (temperature conditions like today in Merano/Italy, 46.7°N) and RCP 8.5 (temperature conditions like today in Bologna/Italy, 44.5°N) emission scenarios. These two climate scenarios were combined with three potential socio-economic developments („local"/„glocal"/ „superglobal"), each in a positive and in a negative specification. From these twelve storylines of coupled climate/land use future, a set of four storylines was selected to be used in transient hydrological modelling experiments. Historical simulations of the water balance for the test site reveal the pattern of land use being the most prominent factor for the spatial distribution of its components. A new prototype for a snow-canopy interaction simulation module provides explicit rates of intercepted and sublimated snow from the trees and stems of the different forest stands in the catchment. This new canopy module will be used to model the coupled climate/land use future storylines for the Brixental. The aim is to quantify the effects of climate change and land use on the water balance and streamflow, both separately and in their respective combination.

Effect of milling and leaching on the structure of sintered silicon

NASA Technical Reports Server (NTRS)

Yeh, H. C.; Glasgow, T. K.; Herbell, T. P.

1980-01-01

The effects of attrition milling and acid leaching on the sintering behavior and the resultant structures of two commercial silicon powders were investigated. Sintering was performed in He for 16 hours at 1200, 1250, and 1300 C. Compacts of as-received Si did not densify during sintering. Milling reduced the average particle size to below 0.5 microns and enhanced densification (1.75 g/cc). Leaching milled Si further enhanced densification (1.90 g/cc max.) and decreased structural coarsening. After sintering, the structure of the milled and leached powder compacts appears favorable for the production of reaction bonded silicon nitride.

Poisson's Ratio and the Densification of Glass under High Pressure

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

Rouxel, T.; Ji, H.; Hammouda, T.

2008-06-06

Because of a relatively low atomic packing density, (C{sub g}) glasses experience significant densification under high hydrostatic pressure. Poisson's ratio ({nu}) is correlated to C{sub g} and typically varies from 0.15 for glasses with low C{sub g} such as amorphous silica to 0.38 for close-packed atomic networks such as in bulk metallic glasses. Pressure experiments were conducted up to 25 GPa at 293 K on silica, soda-lime-silica, chalcogenide, and bulk metallic glasses. We show from these high-pressure data that there is a direct correlation between {nu} and the maximum post-decompression density change.

High conductivity carbon nanotube wires from radial densification and ionic doping

NASA Astrophysics Data System (ADS)

Alvarenga, Jack; Jarosz, Paul R.; Schauerman, Chris M.; Moses, Brian T.; Landi, Brian J.; Cress, Cory D.; Raffaelle, Ryne P.

2010-11-01

Application of drawing dies to radially densify sheets of carbon nanotubes (CNTs) into bulk wires has shown the ability to control electrical conductivity and wire density. Simultaneous use of KAuBr4 doping solution, during wire drawing, has led to an electrical conductivity in the CNT wire of 1.3×106 S/m. Temperature-dependent electrical measurements show that conduction is dominated by fluctuation-assisted tunneling, and introduction of KAuBr4 significantly reduces the tunneling barrier between individual nanotubes. Ultimately, the concomitant doping and densification process leads to closer packed CNTs and a reduced charge transfer barrier, resulting in enhanced bulk electrical conductivity.

Densification and Electrical Properties of Zinc Oxide Varistors Microwave-Sintered Under Different Oxygen Partial Pressures

NASA Astrophysics Data System (ADS)

Lin, Cong; Wang, Bo; Xu, Zheng; Peng, Hu

2012-11-01

ZnO varistors were prepared by microwave sintering under different oxygen partial pressures. The temperature profile and the densification behavior in different atmospheres were investigated. It was found that the density of ZnO varistors during sintering was the key factor affecting the absorption of microwave energy. The electrical properties, including the nonlinear properties and capacitance-voltage ( C- V) characteristics, were also carefully studied. The results showed that the oxygen partial pressure has significant effects on the electrical properties of ZnO varistors by changing the concentration of defects through a series of reactions involving oxygen during sintering.

The Processing and Mechanical Properties of High Temperature/High Performance Composites. Book 6, Section 4: Processing: Matrices and Composites. Part 2

DTIC Science & Technology

1989-10-15

discussed in the context of the above results. [Key words: sintering, densification, zirconia , powder fz irication, grain growth] Member, American...Ceram. Soc. 71 (4) 225-35 (1988). 3. M.A.C.G. van de Graaf, A.J. Burggraaf, ’Wet-Chemical Preparation of Zirconia Powders : Their Microstructure and...40h Zr0-1OY23 30- 1 Oh Zr2IY231WC 2 (A) 1.’DENSIFICATION OF ZIRCONIA POWDER l0 W 0.7-~tr~ TIME bRYST (B CONTAN CEli RSAETL10 w S0.45-- 0.4- 1060 110

Microalloying of transition metal silicides by mechanical activation and field-activated reaction

DOEpatents

Munir, Zuhair A [Davis, CA; Woolman, Joseph N [Davis, CA; Petrovic, John J [Los Alamos, NM

2003-09-02

Alloys of transition metal suicides that contain one or more alloying elements are fabricated by a two-stage process involving mechanical activation as the first stage and densification and field-activated reaction as the second stage. Mechanical activation, preferably performed by high-energy planetary milling, results in the incorporation of atoms of the alloying element(s) into the crystal lattice of the transition metal, while the densification and field-activated reaction, preferably performed by spark plasma sintering, result in the formation of the alloyed transition metal silicide. Among the many advantages of the process are its ability to accommodate materials that are incompatible in other alloying methods.

The Impact of Densification by Means of Informal Shacks in the Backyards of Low-Cost Houses on the Environment and Service Delivery in Cape Town, South Africa

PubMed Central

Govender, Thashlin; Barnes, Jo M.; Pieper, Clarissa H.

2011-01-01

This paper investigates the state-sponsored low cost housing provided to previously disadvantaged communities in the City of Cape Town. The strain imposed on municipal services by informal densification of unofficial backyard shacks was found to create unintended public health risks. Four subsidized low-cost housing communities were selected within the City of Cape Town in this cross-sectional survey. Data was obtained from 1080 persons with a response rate of 100%. Illegal electrical connections to backyard shacks that are made of flimsy materials posed increased fire risks. A high proportion of main house owners did not pay for water but sold water to backyard dwellers. The design of state-subsidised houses and the unplanned housing in the backyard added enormous pressure on the existing municipal infrastructure and the environment. Municipal water and sewerage systems and solid waste disposal cannot cope with the increased population density and poor sanitation behaviour of the inhabitants of these settlements. The low-cost housing program in South Africa requires improved management and prudent policies to cope with the densification of state-funded low-cost housing settlements. PMID:21695092

On the die compaction of powders used in pharmaceutics.

PubMed

Aryanpour, Gholamreza; Farzaneh, Masoud

2018-07-01

Die compaction is widely used in the compaction of pharmaceutical powders (tableting). It is well known that the powder densification is a result of particle rearrangement and particle deformation. The former is considered to be the governing mechanism of densification in an initial stage of compaction and the latter is regarded as the governing mechanism in the compaction at the higher pressure range. As a more realistic assumption, one can consider that a simultaneous performance of both the rearrangement and deformation mechanisms takes place from the beginning of compaction. To mathematically formulate this assumption, a piston equation is presented where the material relative density is given as a function of the applied pressure on the powder. From the equation, it is possible to obtain the contribution of each mechanism to the material densification at each value of the applied pressure. In the continuation, the piston equation is applied to the tabletting of some pharmaceutical powders. These are the powders of Ascorbic Acid, Avicel ® PH 101, Avicel ® PH 301, Emcompress ® , Sodium Chloride, and Tablettose ® whose tableting results have been previously published in the literature. The results show the piston equation as a suitable approach to describe the tabletting of pharmaceutical powders.

The 3D model: explaining densification and deformation mechanisms by using 3D parameter plots.

PubMed

Picker, Katharina M

2004-04-01

The aim of the study was to analyze very differently deforming materials using 3D parameter plots and consequently to gain deeper insights into the densification and deformation process described with the 3D model in order to define an ideal tableting excipient. The excipients used were dicalcium phosphate dihydrate (DCPD), sodium chloride (NaCl), microcrystalline cellulose (MCC), xylitol, mannitol, alpha-lactose monohydrate, maltose, hydroxypropyl methylcellulose (HPMC), sodium carboxymethylcellulose (NaCMC), cellulose acetate (CAC), maize starch, potato starch, pregelatinized starch, and maltodextrine. All of the materials were tableted to graded maximum relative densities (rhorel, max) using an eccentric tableting machine. The data which resulted, namely force, displacement, and time, were analyzed by the application of 3D modeling. Different particle size fractions of DCPD, CAC, and MCC were analyzed in addition. Brittle deforming materials such as DCPD exhibited a completely different 3D parameter plot, with low time plasticity, d, and low pressure plasticity, e, and a strong decrease in omega values when densification increased, in contrast to the plastically deforming MCC, which had much higher d, e, and omega values. e and omega values changed only slightly when densification increased for MCC. NaCl showed less of a decrease in omega values than DCPD did, and the d and e values were between those of MCC and DCPD. The sugar alcohols, xylitol and mannitol, behaved in a similar fashion to sodium chloride. This is also valid for the crystalline sugars, alpha-lactose monohydrate, and maltose. However, the sugars are more brittle than the sugar alcohols. The cellulose derivatives, HPMC, NaCMC, and CAC, are as plastic as MCC, however, their elasticity depends on substitution indicated by lower (more elastic) or higher (less elastic) omega values. The native starches, maize starch and potato starch, are very elastic, and pregelatinized starch and maltodextrine are less elastic and exhibited higher omega values. Deformation behavior as shown in 3D parameter plots depends on particle size for polymers such as CAC and MCC; however, it does not depend on particle size for brittle materials such as DCPD. An ideally deforming tableting excipient should exhibit high e, d, and omega values with a constant ratio of e and omega at increasing densification.

A Look at Seasonal Snow Cover and Snow Mass in the Southern Hemisphere from 1979-2006 Using SMMR and SSM/I Passive Microwave Data

NASA Technical Reports Server (NTRS)

Foster, James

2009-01-01

Seasonal snow cover in extra-tropical areas of South America was examined in this study using passive microwave satellite data from the Scanning Multichannel Microwave Radiometer (SMMR) on board the Nimbus-7 satellite and from the Special Sensor Microwave Imagers (SSM/I) on board the Defense Meteorological Satellite Program (DMSP) satellites. For the period from 1979-2006, both snow cover extent and snow mass were estimated for the months of May-September. Most of the seasonal snow in South America occurs in the Patagonia region of Argentina. The average snow cover extent for July, the month with the greatest average extent during the 28-year period of record, is 321,674 sq km. The seasonal (May-September) 2 average snow cover extent was greatest in 1984 (464,250 sq km) and least in 1990 (69,875 sq km). In terms of snow mass, 1984 was also the biggest year (1.19 x 10(exp 13) kg) and 1990 was the smallest year (0.12 X 10(exp 13) kg). A strong relationship exists between the snow cover area and snow mass, correlated at 0.95, though no significant trend was found over the 28 year record for either snow cover extent or snow mass. For this long term climatology, snow mass and snow cover extent are shown to vary considerably from month to month and season to season. This analysis presents a consistent approach to mapping and measuring snow in South America utilizing an appropriate and readily available long term snow satellite dataset. This is the optimal dataset available, thus far, for deriving seasonal snow cover and snow mass in this region. Nonetheless, shallow snow, wet snow, snow beneath forests, as well as snow along coastal areas all may confound interpretation using passive microwave approaches. More work needs to be done to reduce the uncertainties in the data and hence, increase the confidence of the interpretation

A Comparison of Satellite-Derived Snow Maps with a Focus on Ephemeral Snow in North Carolina

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Fuhrmann, Christopher M.; Perry, L. Baker; Riggs, George A.; Robinson, David A.; Foster, James L.

2010-01-01

In this paper, we focus on the attributes and limitations of four commonly-used daily snowcover products with respect to their ability to map ephemeral snow in central and eastern North Carolina. We show that the Moderate-Resolution Imaging Spectroradiometer (MODIS) fractional snow-cover maps can delineate the snow-covered area very well through the use of a fully-automated algorithm, but suffer from the limitation that cloud cover precludes mapping some ephemeral snow. The semi-automated Interactive Multi-sensor Snow and ice mapping system (IMS) and Rutgers Global Snow Lab (GSL) snow maps are often able to capture ephemeral snow cover because ground-station data are employed to develop the snow maps, The Rutgers GSL maps are based on the IMS maps. Finally, the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) provides some good detail of snow-water equivalent especially in deeper snow, but may miss ephemeral snow cover because it is often very thin or wet; the AMSR-E maps also suffer from coarse spatial resolution. We conclude that the southeastern United States represents a good test region for validating the ability of satellite snow-cover maps to capture ephemeral snow cover,

[Effect of different snow depth and area on the snow cover retrieval using remote sensing data].

PubMed

Jiang, Hong-bo; Qin, Qi-ming; Zhang, Ning; Dong, Heng; Chen, Chao

2011-12-01

For the needs of snow cover monitoring using multi-source remote sensing data, in the present article, based on the spectrum analysis of different depth and area of snow, the effect of snow depth on the results of snow cover retrieval using normalized difference snow index (NDSI) is discussed. Meanwhile, taking the HJ-1B and MODIS remote sensing data as an example, the snow area effect on the snow cover monitoring is also studied. The results show that: the difference of snow depth does not contribute to the retrieval results, while the snow area affects the results of retrieval to some extents because of the constraints of spatial resolution.

Comparison of the Snow Simulations in Community Land Model Using Two Snow Cover Fraction Parameterizations

NASA Astrophysics Data System (ADS)

Xie, Zhipeng; Hu, Zeyong

2016-04-01

Snow cover is an important component of local- and regional-scale energy and water budgets, especially in mountainous areas. This paper evaluates the snow simulations by using two snow cover fraction schemes in CLM4.5 (NY07 is the original snow-covered area parameterization used in CLM4, and SL12 is the default scheme in CLM4.5). Off-line simulations are carried out forced by the China Meteorological forcing dataset from January 1, 2001 to December 31, 2010 over the Tibetan Plateau. Simulated snow cover fraction (SCF), snow depth, and snow water equivalent (SWE) were compared against a set of observations including the Interactive Multisensor Snow and Ice Mapping System (IMS) snow cover product, the daily snow depth dataset of China, and China Meteorological Administration (CMA) in-situ snow depth and SWE observations. The comparison results indicate significant differences existing between those two SCF parameterizations simulations. Overall, the SL12 formulation shows a certain improvement compared to the NY07 scheme used in CLM4, with the percentage of correctly modeled snow/no snow being 75.8% and 81.8% when compared with the IMS snow product, respectively. Yet, this improvement varies both temporally and spatially. Both these two snow cover schemes overestimated the snow depth, in comparison with the daily snow depth dataset of China, the average biases of simulated snow depth are 7.38cm (8.77cm), 6.97cm (8.2cm) and 5.49cm (5.76cm) NY07 (and SL12) in the snow accumulation period (September through next February), snowmelt period (March through May) and snow-free period (June through August), respectively. When compared with the CMA in-situ snow depth observations, averaged biases are 3.18cm (4.38cm), 2.85cm (4.34cm) and 0.34cm (0.34cm) for NY07 (SL12), respectively. Though SL12 does worse snow depth simulation than NY07, the simulated SWE by SL12 is better than that by NY07, with average biases being 2.64mm, 6.22mm, 1.33mm for NY07, and 1.47mm, 2.63mm, 0.31mm for SL12, respectively. This study demonstrates that future improvements on snow simulation over the Tibetan Plateau are in urgent need for better representing the variability of snow in CLM. Furthermore, these findings lay a foundation for follow-up studies on the modification of snow cover parameterization in the land surface model. Keywords: snow cover, CLM, Tibetan Plateau, simulation.

River Flow Advisory Commission: Snow Survey

Science.gov Websites

Survey River Watch Home → Snow Survey RFAC Information About Us Reports Maine Cooperative Snow Survey About the Snow Survey Snow Survey Map Compare Snow Survey Data Snow Survey Graphs River Watch MEMA Home USGS (Maine) Home Maine Cooperative Snow Survey This information is provided by a partnership with

Snow Water Equivalent Variations across the western United States and its relation to of El Niño Southern Oscillation

NASA Astrophysics Data System (ADS)

Miller, W. P.; Thakur, B.; Kalra, A.; Lamb, K. W.; Fayne, J.; Tootle, G. A.; Lakshmi, V.

2017-12-01

With the recent increase in global mean temperature Western US has undergone significant decline in snowpack which is the primary source of fresh water for the region. Studies suggests the decline in snowpack also being coupled with different El Niño Southern Oscillation (ENSO) phases. The study includes 1 March, 1 April and 1 May Snow Water Equivalent (SWE) data of 56 years period (1961-2016) for the estimation of long term changes. The current study also estimates monthly snow water equivalent (SWE) variations during different ENSO phases. Mann-Kendall test was utilized for trend detection while the step was evaluated with the Pettitt's test. Kolmogorov - Smirnov test was also utilized to evaluate the differences in the SWE data distribution during different ENSO phases. The results indicated both decreasing trends and decreasing shifts in majority of the SWE stations. The decline in SWE varied with the ENSO phases and also varied spatially following the geography of the region. KS tests suggested northern regions of Western US having variations in cumulative distribution function during El Niño and non- El Niño years as compared to other regions suggesting the northern regions being more impacted by ENSO phases. This analysis can bring insights into the spatiotemporal SWE variations and lead to the better reliability on snowpack for water management issues.

The subtle role of climate change on population genetic structure in Canada lynx.

PubMed

Row, Jeffrey R; Wilson, Paul J; Gomez, Celine; Koen, Erin L; Bowman, Jeff; Thornton, Daniel; Murray, Dennis L

2014-07-01

Anthropogenically driven climatic change is expected to reshape global patterns of species distribution and abundance. Given recent links between genetic variation and environmental patterns, climate change may similarly impact genetic population structure, but we lack information on the spatial and mechanistic underpinnings of genetic-climate associations. Here, we show that current genetic variability of Canada lynx (Lynx canadensis) is strongly correlated with a winter climate gradient (i.e. increasing snow depth and winter precipitation from west-to-east) across the Pacific-North American (PNO) to North Atlantic Oscillation (NAO) climatic systems. This relationship was stronger than isolation by distance and not explained by landscape variables or changes in abundance. Thus, these patterns suggest that individuals restricted dispersal across the climate boundary, likely in the absence of changes in habitat quality. We propose habitat imprinting on snow conditions as one possible explanation for this unusual phenomenon. Coupling historical climate data with future projections, we also found increasingly diverging snow conditions between the two climate systems. Based on genetic simulations using projected climate data (2041-2070), we predicted that this divergence could lead to a threefold increase in genetic differentiation, potentially leading to isolated east-west populations of lynx in North America. Our results imply that subtle genetic structure can be governed by current climate and that substantive genetic differentiation and related ecological divergence may arise from changing climate patterns. © 2014 John Wiley & Sons Ltd.

Semi volatile organic compounds in the snow of Russian Arctic islands: Archipelago Novaya Zemlya.

PubMed

Lebedev, A T; Mazur, D M; Polyakova, O V; Kosyakov, D S; Kozhevnikov, A Yu; Latkin, T B; Andreeva Yu, I; Artaev, V B

2018-04-18

Environmental contamination of the Arctic has widely been used as a worldwide pollution marker. Various classes of organic pollutants such as pesticides, personal care products, PAHs, flame retardants, biomass burning markers, and many others emerging contaminants have been regularly detected in Arctic samples. Although numerous papers have been published reporting data from the Canadian, Danish, and Norwegian Arctic regions, the environmental situation in Russian Arctic remains mostly underreported. Snow analysis is known to be used for monitoring air pollution in the regions with cold climate in both short-term and long-term studies. This paper presents the results of a nontargeted study on the semivolatile organic compounds detected and identified in snow samples collected at the Russian Artic Archipelago Novaya Zemlya in June 2016. Gas chromatography coupled to a high-resolution time-of-flight mass spectrometer enabled the simultaneous detection and quantification of a variety of pollutants including those from the US Environmental Protection Agency (EPA) priority pollutants list, emerging contaminants (plasticizers, flame retardants-only detection), as well as the identification of novel Arctic organic pollutants, (e.g., fatty acid amides and polyoxyalkanes). The possible sources of these novel pollutants are also discussed. GC-HRMS enabled the detection and identification of emerging contaminants and novel organic pollutants in the Arctic, e.g., fatty amides and polyoxyalkanes. Copyright © 2018 Elsevier Ltd. All rights reserved.

Impacts of snow on soil temperature observed across the circumpolar north

NASA Astrophysics Data System (ADS)

Zhang, Yu; Sherstiukov, Artem B.; Qian, Budong; Kokelj, Steven V.; Lantz, Trevor C.

2018-04-01

Climate warming has significant impacts on permafrost, infrastructure and soil organic carbon at the northern high latitudes. These impacts are mainly driven by changes in soil temperature (TS). Snow insulation can cause significant differences between TS and air temperature (TA), and our understanding about this effect through space and time is currently limited. In this study, we compiled soil and air temperature observations (measured at about 0.2 m depth and 2 m height, respectively) at 588 sites from climate stations and boreholes across the northern high latitudes. Analysis of this circumpolar dataset demonstrates the large offset between mean TS and TA in the low arctic and northern boreal regions. The offset decreases both northward and southward due to changes in snow conditions. Correlation analysis shows that the coupling between annual TS and TA is weaker, and the response of annual TS to changes in TA is smaller in boreal regions than in the arctic and the northern temperate regions. Consequently, the inter-annual variation and the increasing trends of annual TS are smaller than that of TA in boreal regions. The systematic and significant differences in the relationship between TS and TA across the circumpolar north is important for understanding and assessing the impacts of climate change and for reconstruction of historical climate based on ground temperature profiles for the northern high latitudes.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Impact of Snow Grain Shape and Internal Mixing with Black Carbon Aerosol on Snow Optical Properties for use in Climate Models

NASA Astrophysics Data System (ADS)

He, C.; Liou, K. N.; Takano, Y.; Yang, P.; Li, Q.; Chen, F.

2017-12-01

A set of parameterizations is developed for spectral single-scattering properties of clean and black carbon (BC)-contaminated snow based on geometric-optic surface-wave (GOS) computations, which explicitly resolves BC-snow internal mixing and various snow grain shapes. GOS calculations show that, compared with nonspherical grains, volume-equivalent snow spheres show up to 20% larger asymmetry factors and hence stronger forward scattering, particularly at wavelengths <1 mm. In contrast, snow grain sizes have a rather small impact on the asymmetry factor at wavelengths <1 mm, whereas size effects are important at longer wavelengths. The snow asymmetry factor is parameterized as a function of effective size, aspect ratio, and shape factor, and shows excellent agreement with GOS calculations. According to GOS calculations, the single-scattering coalbedo of pure snow is predominantly affected by grain sizes, rather than grain shapes, with higher values for larger grains. The snow single-scattering coalbedo is parameterized in terms of the effective size that combines shape and size effects, with an accuracy of >99%. Based on GOS calculations, BC-snow internal mixing enhances the snow single-scattering coalbedo at wavelengths <1 mm, but it does not alter the snow asymmetry factor. The BC-induced enhancement ratio of snow single-scattering coalbedo, independent of snow grain size and shape, is parameterized as a function of BC concentration with an accuracy of >99%. Overall, in addition to snow grain size, both BC-snow internal mixing and snow grain shape play critical roles in quantifying BC effects on snow optical properties. The present parameterizations can be conveniently applied to snow, land surface, and climate models including snowpack radiative transfer processes.

Stable isotope dilution analysis of hydrologic samples by inductively coupled plasma mass spectrometry

USGS Publications Warehouse

Garbarino, John R.; Taylor, Howard E.

1987-01-01

Inductively coupled plasma mass spectrometry is employed in the determination of Ni, Cu, Sr, Cd, Ba, Ti, and Pb in nonsaline, natural water samples by stable isotope dilution analysis. Hydrologic samples were directly analyzed without any unusual pretreatment. Interference effects related to overlapping isobars, formation of metal oxide and multiply charged ions, and matrix composition were identified and suitable methods of correction evaluated. A comparability study snowed that single-element isotope dilution analysis was only marginally better than sequential multielement isotope dilution analysis. Accuracy and precision of the single-element method were determined on the basis of results obtained for standard reference materials. The instrumental technique was shown to be ideally suited for programs associated with certification of standard reference materials.

Regional Densification of a Global VTEC Model Based on B-Spline Representations

NASA Astrophysics Data System (ADS)

Erdogan, Eren; Schmidt, Michael; Dettmering, Denise; Goss, Andreas; Seitz, Florian; Börger, Klaus; Brandert, Sylvia; Görres, Barbara; Kersten, Wilhelm F.; Bothmer, Volker; Hinrichs, Johannes; Mrotzek, Niclas

2017-04-01

The project OPTIMAP is a joint initiative of the Bundeswehr GeoInformation Centre (BGIC), the German Space Situational Awareness Centre (GSSAC), the German Geodetic Research Institute of the Technical University Munich (DGFI-TUM) and the Institute for Astrophysics at the University of Göttingen (IAG). The main goal of the project is the development of an operational tool for ionospheric mapping and prediction (OPTIMAP). Two key features of the project are the combination of different satellite observation techniques (GNSS, satellite altimetry, radio occultations and DORIS) and the regional densification as a remedy against problems encountered with the inhomogeneous data distribution. Since the data from space-geoscientific mission which can be used for modeling ionospheric parameters, such as the Vertical Total Electron Content (VTEC) or the electron density, are distributed rather unevenly over the globe at different altitudes, appropriate modeling approaches have to be developed to handle this inhomogeneity. Our approach is based on a two-level strategy. To be more specific, in the first level we compute a global VTEC model with a moderate regional and spectral resolution which will be complemented in the second level by a regional model in a densification area. The latter is a region characterized by a dense data distribution to obtain a high spatial and spectral resolution VTEC product. Additionally, the global representation means a background model for the regional one to avoid edge effects at the boundaries of the densification area. The presented approach based on a global and a regional model part, i.e. the consideration of a regional densification is called the Two-Level VTEC Model (TLVM). The global VTEC model part is based on a series expansion in terms of polynomial B-Splines in latitude direction and trigonometric B-Splines in longitude direction. The additional regional model part is set up by a series expansion in terms of polynomial B-splines for both directions. The spectral resolution of both model parts is defined by the number of B-spline basis functions introduced for longitude and latitude directions related to appropriate coordinate systems. Furthermore, the TLVM has to be developed under the postulation that the global model part will be computed continuously in near real-time (NRT) and routinely predicted into the future by an algorithm based on deterministic and statistical forecast models. Thus, the additional regional densification model part, which will be computed also in NRT, but possibly only for a specified time duration, must be estimated independently from the global one. For that purpose a data separation procedure has to be developed in order to estimate the unknown series coefficients of both model parts independently. This procedure must also consider additional technique-dependent unknowns such as the Differential Code Biases (DCBs) within GNSS and intersystem biases. In this contribution we will present the concept to set up the TLVM including the data combination and the Kalman filtering procedure; first numerical results will be presented.

BOREAS HYD-3 Snow 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 contains measurements of snow depth, snow density in three cm intervals, an integrated snow pack density and snow water equivalent (SWE), and snow pack physical properties from snow pit evaluation taken in 1994 and 1996. The data were collected from several sites in both the southern study area (SSA) and the northern study area (NSA). A variety of standard tools were used to measure the snow pack properties, including a meter stick (snow depth), a 100 cc snow density cutter, a dial stem thermometer, and the Canadian snow sampler as used by HYD-4 to obtain a snow pack-integrated measure of SWE. This study was undertaken to predict spatial distributions of snow properties important to the hydrology, remote sensing signatures, and the transmissivity of gases through the snow. The data are available in tabular ASCII files. The snow 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).

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.

Comparison of MODIS and VIIRS Snow Cover Products for the 2016 Hydrological Year

NASA Astrophysics Data System (ADS)

Klein, A. G.; Thapa, S.

2017-12-01

The VIIRS (Visible Infrared Imaging Radiometer Suite) instrument on board the Suomi-NPP satellite aims to provide long-term continuity of several environmental data series including snow cover initiated with MODIS. While it is speculated that MODIS and VIIRS snow cover products may differ because of their differing spatial resolutions and spectral coverage quantitative comparisons between their snow products are currently limited. Therefore this study intercompares MODIS and VIIRS snow products for the 2016 Hydrological Year over the Midwestern United States and southern Canada. Two hundred and forty-four swath snow products from MODIS/Aqua (MYD10L2) and the VIIRS EDR (VSCMO/binary) were intercompared using confusion matrices, comparison maps and false color imagery. Thresholding the MODIS NDSI Snow Cover product at a snow cover fraction of 30% generated binary snow maps most comparable to the NOAA VIIRS binary snow product. Overall agreement between MODIS and VIIRS was found to be approximately 98%. This exceeds the VIIRS accuracy requirements of 90% probability of correct typing. Agreement was highest during the winter but lower during late fall and spring. Comparability was lowest over forest. MODIS and VIIRS often mapped snow/no-snow transition zones as cloud. The assessment of total snow and cloud pixels and comparison snow maps of MODIS and VIIRS indicates that VIIRS is mapping more snow cover and less cloud cover compared to MODIS. This is evidenced by the average area of snow in MYD10L2 and VSCMO being 5.72% and 11.43%, no-snow 26.65% and 28.67%, and cloud 65.02% and 59.91%, respectively. Visual comparisons depict good qualitative agreement between snow cover area visible in MODIS and VIIRS false color imagery and mapped in their respective snow cover products. While VIIRS and MODIS have similar capacity to map snow cover, VIIRS has the potential to more accurately map snow cover area for the successive development of climate data records.

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

PubMed

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

2014-11-01

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

Evaluation of a New SnowPaver at McMurdo Station, Antarctica

DTIC Science & Technology

2014-09-01

Center (KRC) and the National Science Foundation (NSF) to assess the feasibility of using a new SnowPaver to build snow roads in Antarctica. KRC built...rutting. The SnowPaver was also used for reworking and compacting old and slushy snow during the height of the warm season. In November 2012, the power...6 SnowPaver configured for McMurdo snow-road use (2010) .................................................. 12 7 Map detail of SnowPaver test

Close packing effects on clean and dirty snow albedo and associated climatic implications

NASA Astrophysics Data System (ADS)

He, C.; Liou, K. N.; Takano, Y.

2017-12-01

Previous modeling of snow albedo, a key climate feedback parameter, follows the independent scattering approximation (ISA) such that snow grains are considered as a number of separate units with distances longer than wavelengths. Here we develop a new snow albedo model for widely observed close-packed snow grains internally mixed with black carbon (BC) and demonstrate that albedo simulations match closer to observations. Close packing results in a stronger light absorption for clean and BC-contaminated snow. Compared with ISA, close packing reduces pure snow albedos by up to 0.05, whereas it enhances BC-induced snow albedo reduction and associated surface radiative forcing by up to 15% (20%) for fresh (old) snow, with larger enhancements for stronger structure packing. Finally, our results suggest that BC-snow albedo forcing and snow albedo feedback (climate sensitivity) are underestimated in previous modeling studies, making snow close packing consideration a necessity in climate modeling and analysis.

Close packing effects on clean and dirty snow albedo and associated climatic implications

NASA Astrophysics Data System (ADS)

He, Cenlin; Takano, Yoshi; Liou, Kuo-Nan

2017-04-01

Previous modeling of snow albedo, a key climate feedback parameter, follows the independent scattering approximation (ISA) such that snow grains are considered as a number of separate units with distances longer than wavelengths. Here we develop a new snow albedo model for widely observed close-packed snow grains internally mixed with black carbon (BC) and demonstrate that albedo simulations match closer to observations. Close packing results in a stronger light absorption for clean and BC-contaminated snow. Compared with ISA, close packing reduces pure snow albedos by up to 0.05, whereas it enhances BC-induced snow albedo reduction and associated surface radiative forcing by up to 15% (20%) for fresh (old) snow, with larger enhancements for stronger structure packing. Finally, our results suggest that BC-snow albedo forcing and snow albedo feedback (climate sensitivity) are underestimated in previous modeling studies, making snow close packing consideration a necessity in climate modeling and analysis.

Improved Snow Mapping Accuracy with Revised MODIS Snow Algorithm

NASA Technical Reports Server (NTRS)

Riggs, George; Hall, Dorothy K.

2012-01-01

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

Blowing snow detection from ground-based ceilometers: application to East Antarctica

NASA Astrophysics Data System (ADS)

Gossart, Alexandra; Souverijns, Niels; Gorodetskaya, Irina V.; Lhermitte, Stef; Lenaerts, Jan T. M.; Schween, Jan H.; Mangold, Alexander; Laffineur, Quentin; van Lipzig, Nicole P. M.

2017-12-01

Blowing snow impacts Antarctic ice sheet surface mass balance by snow redistribution and sublimation. However, numerical models poorly represent blowing snow processes, while direct observations are limited in space and time. Satellite retrieval of blowing snow is hindered by clouds and only the strongest events are considered. Here, we develop a blowing snow detection (BSD) algorithm for ground-based remote-sensing ceilometers in polar regions and apply it to ceilometers at Neumayer III and Princess Elisabeth (PE) stations, East Antarctica. The algorithm is able to detect (heavy) blowing snow layers reaching 30 m height. Results show that 78 % of the detected events are in agreement with visual observations at Neumayer III station. The BSD algorithm detects heavy blowing snow 36 % of the time at Neumayer (2011-2015) and 13 % at PE station (2010-2016). Blowing snow occurrence peaks during the austral winter and shows around 5 % interannual variability. The BSD algorithm is capable of detecting blowing snow both lifted from the ground and occurring during precipitation, which is an added value since results indicate that 92 % of the blowing snow is during synoptic events, often combined with precipitation. Analysis of atmospheric meteorological variables shows that blowing snow occurrence strongly depends on fresh snow availability in addition to wind speed. This finding challenges the commonly used parametrizations, where the threshold for snow particles to be lifted is a function of wind speed only. Blowing snow occurs predominantly during storms and overcast conditions, shortly after precipitation events, and can reach up to 1300 m a. g. l. in the case of heavy mixed events (precipitation and blowing snow together). These results suggest that synoptic conditions play an important role in generating blowing snow events and that fresh snow availability should be considered in determining the blowing snow onset.

Precipitation and Topography as Drivers of Tree Water Use and Productivity at Multiple Scales

NASA Astrophysics Data System (ADS)

Martin, J. T.; Hu, J.; Looker, N. T.; Jencso, K. G.

2014-12-01

Water is commonly the primary limiting factor for tree growth in semi-arid regions of the Western U.S. and tree productivity can vary drastically across landscapes as a function of water availability. The role of topography as a first order control on soil and ground water has been well studied; however, the strategies trees use to cope with water limitation in different landscape positions and across time remain unclear. As growing seasons progress, the availability of water changes temporally, as water inputs transition from snowmelt to rainfall, and spatially, as divergent positions dry more than convergent ones. We seek to understand how the interaction of these processes dictate where trees access water and which strategies most successfully avert water limitation of growth. We take advantage of clear differences in the isotopic signatures of snow and summer rain to track water utilized by Douglas fir, Ponderosa pine, Subalpine fir, Engelmann spruce, and Western larch in both convergent and divergent landscape positions and across time. We couple these data with evidence of growth limitation inferred from reductions in lateral growth rates observed by continuous dendrometer measurements to link tree water use and productivity. Xylem waters reflect both the precipitation type and soil profile distribution of water used by trees for growth and dendrometer measurements reflect the effects of water limitation through changes in the lateral growth curve as soil moistures decline. Isotope signatures from rain, snow and stream water fell predictably along the local meteoric water line with values from xylem samples falling between those of rain and snow. Trees on southern aspects exhibit more growth limitation in divergent than convergent positions while this effect appears muted or non-existent on northern aspects. Trees in convergent hollow positions rely more on snow water while trees on slopes utilize more rain water. Surprisingly, trees at lower elevation rely more on snow water than trees at higher elevation, suggesting that trees in drier, low elevation sites are accessing deeper, older water from snowmelt throughout the growing season. Our research suggests previously under-recognized topographic and hydrologic modulation of tree growth at surprisingly small spatial and temporal scales.

A remote sensing data assimilation system for cold land processes hydrologic estimation

NASA Astrophysics Data System (ADS)

Andreadis, Konstantinos M.

2009-12-01

Accurate forecasting of snow properties is important for effective water resources management, especially in mountainous areas. Model-based approaches are limited by biases and uncertainties. Remote sensing offers an opportunity for observation of snow properties over larger areas. Traditional approaches to direct estimation of snow properties from passive microwave remote sensing have been plagued by limitations such as the tendency of estimates to saturate for moderately deep snowpacks and the effects of mixed land cover. To address these complications, a data assimilation system is developed and evaluated in a three-part research. The data assimilation system requires the embedding of a microwave emissions model which uses modeled snowpack properties. In the first part of this study, such a model is evaluated using multi-scale TB measurements from the Cold Land Processes Experiment. The model's ability to reproduce snowpack microphysical properties is evaluated through comparison with snowpit measurements, while TB predictions are evaluated through comparison with in-situ, aircraft and satellite measurements. Point comparisons showed limitations in the model, while the spatial averaging and the effects of forest cover suppressed errors in comparisons with aircraft measurements. The layered character of snowpacks increases the complexity of algorithms intended to retrieve snow properties from the snowpack microwave return signal. Implementation of a retrieval strategy requires knowledge of stratigraphy, which practically can only be produced by models. In the second part of this study, we describe a multi-layer model designed for such applications. The model coupled with a radiative transfer scheme improved the estimation of TB, while potential impacts when assimilating radiances are explored. A system that merges SWE model predictions and observations of SCE and TB, is evaluated in the third part of this study over one winter season in the Upper Snake River basin. Two data assimilation techniques, the Ensemble Kalman filter and the Ensemble Multiscale Kalman filter are tested with the multilayer snow model forced by downscaled re-analysis meteorological observations. Both the EnKF and EnMKF showed modest improvements when compared with the open-loop simulation, relative to a baseline simulation which used in-situ meteorological data, while comparisons with in-situ SWE measurements showed an overall improvement.

Snow driven Radiative Forcing in High Latitude Areas of Disturbance Using Higher Resolution Albedo Products from Landsat and Sentinel-2

NASA Astrophysics Data System (ADS)

Erb, A.; Li, Z.; Schaaf, C.; Wang, Z.; Rogers, B. M.

2017-12-01

Land surface albedo plays an important role in the surface energy budget and radiative forcing by determining the proportion of absorbed incoming solar radiation available to drive photosynthesis and surface heating. In Arctic regions, albedo is particularly sensitive to land cover and land use change (LCLUC) and modeling efforts have shown it to be the primary driver of effective radiative forcing from the biogeophysical effects of LCLUC. In boreal forests, the effects of these changes are complicated during snow covered periods when newly exposed, highly reflective snow can serve as the primary driver of radiative forcing. In Arctic biomes disturbance scars from fire, pest and harvest can remain in the landscape for long periods of time. As such, understanding the magnitude and persistence of these disturbances, especially in the shoulder seasons, is critical. The Landsat and Sentinel-2 Albedo Products couple 30m and 20m surface reflectances with concurrent 500m BRDF Products from the MODerate resolution Imaging Spectroradiometer (MODIS). The 12 bit radiometric fidelity of Sentinel-2 and Landsat-8 allow for the inclusion of high-quality, unsaturated albedo calculations over snow covered surfaces at scales more compatible with fragmented landscapes. Recent work on the early spring albedo of fire scars has illustrated significant post-fire spatial heterogeneity of burn severity at the landscape scale and highlights the need for a finer spatial resolution albedo record. The increased temporal resolution provided by multiple satellite instruments also allows for a better understanding of albedo dynamics during the dynamic shoulder seasons and in historically difficult high latitude locations where persistent cloud cover limits high quality retrievals. Here we present how changes in the early spring albedo of recent boreal forest disturbance in Alaska and central Canada affects landscape-scale radiative forcing. We take advantage of the long historical Landsat record to examine pre-disturbance albedo trends and to link historical land cover and disturbance history to post-disturbance early spring albedo values. We examine the impact of landscape heterogeneity on albedo in the growing and dormant seasons and quantify the effects of snow exposure changes from over-story canopy loss.

Snow Sublimation in Mountain Environments and Its Sensitivity to Forest Disturbance and Climate Warming

NASA Astrophysics Data System (ADS)

Sexstone, Graham A.; Clow, David W.; Fassnacht, Steven R.; Liston, Glen E.; Hiemstra, Christopher A.; Knowles, John F.; Penn, Colin A.

2018-02-01

Snow sublimation is an important component of the snow mass balance, but the spatial and temporal variability of this process is not well understood in mountain environments. This study combines a process-based snow model (SnowModel) with eddy covariance (EC) measurements to investigate (1) the spatio-temporal variability of simulated snow sublimation with respect to station observations, (2) the contribution of snow sublimation to the ablation of the snowpack, and (3) the sensitivity and response of snow sublimation to bark beetle-induced forest mortality and climate warming across the north-central Colorado Rocky Mountains. EC-based observations of snow sublimation compared well with simulated snow sublimation at stations dominated by surface and canopy sublimation, but blowing snow sublimation in alpine areas was not well captured by the EC instrumentation. Water balance calculations provided an important validation of simulated sublimation at the watershed scale. Simulated snow sublimation across the study area was equivalent to 28% of winter precipitation on average, and the highest relative snow sublimation fluxes occurred during the lowest snow years. Snow sublimation from forested areas accounted for the majority of sublimation fluxes, highlighting the importance of canopy and sub-canopy surface sublimation in this region. Simulations incorporating the effects of tree mortality due to bark-beetle disturbance resulted in a 4% reduction in snow sublimation from forested areas. Snow sublimation rates corresponding to climate warming simulations remained unchanged or slightly increased, but total sublimation losses decreased by up to 6% because of a reduction in snow covered area and duration.

Snow sublimation in mountain environments and its sensitivity to forest disturbance and climate warming

USGS Publications Warehouse

Sexstone, Graham A.; Clow, David W.; Fassnacht, Steven R.; Liston, Glen E.; Hiemstra, Christopher A.; Knowles, John F.; Penn, Colin A.

2018-01-01

Snow sublimation is an important component of the snow mass balance, but the spatial and temporal variability of this process is not well understood in mountain environments. This study combines a process‐based snow model (SnowModel) with eddy covariance (EC) measurements to investigate (1) the spatio‐temporal variability of simulated snow sublimation with respect to station observations, (2) the contribution of snow sublimation to the ablation of the snowpack, and (3) the sensitivity and response of snow sublimation to bark beetle‐induced forest mortality and climate warming across the north‐central Colorado Rocky Mountains. EC‐based observations of snow sublimation compared well with simulated snow sublimation at stations dominated by surface and canopy sublimation, but blowing snow sublimation in alpine areas was not well captured by the EC instrumentation. Water balance calculations provided an important validation of simulated sublimation at the watershed scale. Simulated snow sublimation across the study area was equivalent to 28% of winter precipitation on average, and the highest relative snow sublimation fluxes occurred during the lowest snow years. Snow sublimation from forested areas accounted for the majority of sublimation fluxes, highlighting the importance of canopy and sub‐canopy surface sublimation in this region. Simulations incorporating the effects of tree mortality due to bark‐beetle disturbance resulted in a 4% reduction in snow sublimation from forested areas. Snow sublimation rates corresponding to climate warming simulations remained unchanged or slightly increased, but total sublimation losses decreased by up to 6% because of a reduction in snow covered area and duration.

Observed Differences between North American Snow Extent and Snow Depth Variability

NASA Astrophysics Data System (ADS)

Ge, Y.; Gong, G.

2006-12-01

Snow extent and snow depth are two related characteristics of a snowpack, but they need not be mutually consistent. Differences between these two variables at local scales are readily apparent. However at larger scales which interact with atmospheric circulation and climate, snow extent is typically the variable used, while snow depth is often assumed to be minor and/or mutually consistent compared to snow extent, though this is rarely verified. In this study, a new regional/continental-scale gridded dataset derived from field observations is utilized to quantitatively evaluate the relationship between snow extent and snow depth over North America. Various statistical methods are applied to assess the mutual consistency of monthly snow depth vs. snow extent, including correlations, composites and principal components. Results indicate that snow depth variations are significant in their own rights, and that depth and extent anomalies are largely unrelated, especially over broad high latitude regions north of the snowline. In the vicinity of the snowline, where precipitation and ablation can affect both snow extent and snow depth, the two variables vary concurrently, especially in autumn and spring. It is also found that deeper winter snow translates into larger snow-covered area in the subsequent spring/summer season, which suggests a possible influence of winter snow depth on summer climate. The observed lack of mutual consistency at continental/regional scales suggests that snowpack depth variations may be of sufficiently large magnitude, spatial scope and temporal duration to influence regional-hemispheric climate, in a manner unrelated to the more extensively studied snow extent variations.

Multi-Decadal Averages of Basal Melt for Ross Ice Shelf, Antarctica Using Airborne Observations

NASA Astrophysics Data System (ADS)

Das, I.; Bell, R. E.; Tinto, K. J.; Frearson, N.; Kingslake, J.; Padman, L.; Siddoway, C. S.; Fricker, H. A.

2017-12-01

Changes in ice shelf mass balance are key to the long term stability of the Antarctic Ice Sheet. Although the most extensive ice shelf mass loss currently is occurring in the Amundsen Sea sector of West Antarctica, many other ice shelves experience changes in thickness on time scales from annual to ice age cycles. Here, we focus on the Ross Ice Shelf. An 18-year record (1994-2012) of satellite radar altimetry shows substantial variability in Ross Ice Shelf height on interannual time scales, complicating detection of potential long-term climate-change signals in the mass budget of this ice shelf. Variability of radar signal penetration into the ice-shelf surface snow and firn layers further complicates assessment of mass changes. We investigate Ross Ice Shelf mass balance using aerogeophysical data from the ROSETTA-Ice surveys using IcePod. We use two ice-penetrating radars; a 2 GHz unit that images fine-structure in the upper 400 m of the ice surface and a 360 MHz radar to identify the ice shelf base. We have identified internal layers that are continuous along flow from the grounding line to the ice shelf front. Based on layer continuity, we conclude that these layers must be the horizons between the continental ice of the outlet glaciers and snow accumulation once the ice is afloat. We use the Lagrangian change in thickness of these layers, after correcting for strain rates derived using modern day InSAR velocities, to estimate multidecadal averaged basal melt rates. This method provides a novel way to quantify basal melt, avoiding the confounding impacts of spatial and short-timescale variability in surface accumulation and firn densification processes. Our estimates show elevated basal melt rates (> -1m/yr) around Byrd and Mullock glaciers within 100 km from the ice shelf front. We also compare modern InSAR velocity derived strain rates with estimates from the comprehensive ground-based RIGGS observations during 1973-1978 to estimate the potential magnitude of strain-driven thickness changes over four decades. Combining maps of basal melt rate with radar derived basal reflectivity, we identify regions that are undergoing melting and freezing and provide a comprehensive understanding of how ocean processes may be changing the base of Ross Ice Shelf in recent decades.

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.

Obtaining sub-daily new snow density from automated measurements in high mountain regions

NASA Astrophysics Data System (ADS)

Helfricht, Kay; Hartl, Lea; Koch, Roland; Marty, Christoph; Olefs, Marc

2018-05-01

The density of new snow is operationally monitored by meteorological or hydrological services at daily time intervals, or occasionally measured in local field studies. However, meteorological conditions and thus settling of the freshly deposited snow rapidly alter the new snow density until measurement. Physically based snow models and nowcasting applications make use of hourly weather data to determine the water equivalent of the snowfall and snow depth. In previous studies, a number of empirical parameterizations were developed to approximate the new snow density by meteorological parameters. These parameterizations are largely based on new snow measurements derived from local in situ measurements. In this study a data set of automated snow measurements at four stations located in the European Alps is analysed for several winter seasons. Hourly new snow densities are calculated from the height of new snow and the water equivalent of snowfall. Considering the settling of the new snow and the old snowpack, the average hourly new snow density is 68 kg m-3, with a standard deviation of 9 kg m-3. Seven existing parameterizations for estimating new snow densities were tested against these data, and most calculations overestimate the hourly automated measurements. Two of the tested parameterizations were capable of simulating low new snow densities observed at sheltered inner-alpine stations. The observed variability in new snow density from the automated measurements could not be described with satisfactory statistical significance by any of the investigated parameterizations. Applying simple linear regressions between new snow density and wet bulb temperature based on the measurements' data resulted in significant relationships (r2 > 0.5 and p ≤ 0.05) for single periods at individual stations only. Higher new snow density was calculated for the highest elevated and most wind-exposed station location. Whereas snow measurements using ultrasonic devices and snow pillows are appropriate for calculating station mean new snow densities, we recommend instruments with higher accuracy e.g. optical devices for more reliable investigations of the variability of new snow densities at sub-daily intervals.

Transport of intercepted snow from trees during snow storms

Treesearch

David H. Miller

1966-01-01

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

Indices for estimating fractional snow cover in the western Tibetan Plateau

NASA Astrophysics Data System (ADS)

Shreve, Cheney M.; Okin, Gregory S.; Painter, Thomas H.

Snow cover in the Tibetan Plateau is highly variable in space and time and plays a key role in ecological processes of this cold-desert ecosystem. Resolution of passive microwave data is too low for regional-scale estimates of snow cover on the Tibetan Plateau, requiring an alternate data source. Optically derived snow indices allow for more accurate quantification of snow cover using higher-resolution datasets subject to the constraint of cloud cover. This paper introduces a new optical snow index and assesses four optically derived MODIS snow indices using Landsat-based validation scenes: MODIS Snow-Covered Area and Grain Size (MODSCAG), Relative Multiple Endmember Spectral Mixture Analysis (RMESMA), Relative Spectral Mixture Analysis (RSMA) and the normalized-difference snow index (NDSI). Pearson correlation coefficients were positively correlated with the validation datasets for all four optical snow indices, suggesting each provides a good measure of total snow extent. At the 95% confidence level, linear least-squares regression showed that MODSCAG and RMESMA had accuracy comparable to validation scenes. Fusion of optical snow indices with passive microwave products, which provide snow depth and snow water equivalent, has the potential to contribute to hydrologic and energy-balance modeling in the Tibetan Plateau.

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.

Determination of Hg Content in a Shallow Firn Core From Summit, Greenland Using Isotope Dilution Cold Vapor Inductively Coupled Plasma - Mass Spectrometry

NASA Astrophysics Data System (ADS)

Mann, J. L.; Long, S. E.; Shuman, C. A.

2002-05-01

Considerable attention has recently been focused on mercury (Hg) owing to its ability to bioaccumulate as highly toxic species in the biosphere. Hg in the environment is derived from both natural and anthropogenic sources and present day emissions for both are thought to be of similar magnitude. Once introduced into the atmosphere, Hgo can be transported long distances and as a result is considered to have global environmental influence. High levels of Hg have been found in Arctic food supplies and elevated levels have been observed in the native people of the circumpolar countries including Greenland. Mercury content was determined in surface snow and a 7 m shallow snow/firn core, recovered in May 2001 from Summit, Greenland (72.58oN, 38.53oW; elevation 3238 m), using a new method employing isotope dilution cold vapor inductively coupled plasma - mass spectrometry (ID-CV-ICPMS). The method, recently developed at the National Institute of Standards and Technology, uses a 201Hg spike that is equilibrated with the sample. Hg is measured by chemical reduction with tin (II) chloride and generation of a "cold vapor" (elemental Hg vapor) whereby the Hg vapor is separated from the matrix using a gas-liquid separator and is collected on gold guaze. Hg is then released by thermal desorption and the Hg isotope ratio (201Hg/202Hg) measured by quadrapole ICP-MS. There are considerable advantages to this new method in the analysis of very low concentration snow/firn/ice samples which include: 1) very high sensitivity (detection limit < 1 pg/mL, 3 sigma); 2) accuracy and precision of the order of one percent or better; and 3) complete freedom from spectral and matrix interferences. The concentrations determined ranged from 0.1 to 1.1 pg/g, which fall within the range of those previously determined by Boutron et al. (1998). Hg contributed from core processing, storage in LDPE bottles, and the analytical procedure yielded a blank value of 0.10 pg Hg/g equivalent. This was used to correct the measured Hg values. The uncertainty in the reported Hg concentrations was 0.1 to 0.2 pg Hg/g for a 10 mL aliquot. This new method may allow the examination of the high-resolution (sub-seasonal) snow/firn/ice record for better understanding of the short-term variability in Hg concentrations and their relationship to atmospheric mercury depletion events.

[Analysis of influencing factors of snow hyperspectral polarized reflections].

PubMed

Sun, Zhong-Qiu; Zhao, Yun-Sheng; Yan, Guo-Qian; Ning, Yan-Ling; Zhong, Gui-Xin

2010-02-01

Due to the need of snow monitoring and the impact of the global change on the snow, on the basis of the traditional research on snow, starting from the perspective of multi-angle polarized reflectance, we analyzed the influencing factors of snow from the incidence zenith angles, the detection zenith angles, the detection azimuth angles, polarized angles, the density of snow, the degree of pollution, and the background of the undersurface. It was found that these factors affected the spectral reflectance values of the snow, and the effect of some factors on the polarization hyperspectral reflectance observation is more evident than in the vertical observation. Among these influencing factors, the pollution of snow leads to an obvious change in the snow reflectance spectrum curve, while other factors have little effect on the shape of the snow reflectance spectrum curve and mainly impact the reflection ratio of the snow. Snow reflectance polarization information has not only important theoretical significance, but also wide application prospect, and provides new ideas and methods for the quantitative research on snow using the remote sensing technology.

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Impact of Grain Shape and Multiple Black Carbon Internal Mixing on Snow Albedo: Parameterization and Radiative Effect Analysis

NASA Astrophysics Data System (ADS)

He, Cenlin; Liou, Kuo-Nan; Takano, Yoshi; Yang, Ping; Qi, Ling; Chen, Fei

2018-01-01

We quantify the effects of grain shape and multiple black carbon (BC)-snow internal mixing on snow albedo by explicitly resolving shape and mixing structures. Nonspherical snow grains tend to have higher albedos than spheres with the same effective sizes, while the albedo difference due to shape effects increases with grain size, with up to 0.013 and 0.055 for effective radii of 1,000 μm at visible and near-infrared bands, respectively. BC-snow internal mixing reduces snow albedo at wavelengths < 1.5 μm, with negligible effects at longer wavelengths. Nonspherical snow grains show less BC-induced albedo reductions than spheres with the same effective sizes by up to 0.06 at ultraviolet and visible bands. Compared with external mixing, internal mixing enhances snow albedo reduction by a factor of 1.2-2.0 at visible wavelengths depending on BC concentration and snow shape. The opposite effects on albedo reductions due to snow grain nonsphericity and BC-snow internal mixing point toward a careful investigation of these two factors simultaneously in climate modeling. We further develop parameterizations for snow albedo and its reduction by accounting for grain shape and BC-snow internal/external mixing. Combining the parameterizations with BC-in-snow measurements in China, North America, and the Arctic, we estimate that nonspherical snow grains reduce BC-induced albedo radiative effects by up to 50% compared with spherical grains. Moreover, BC-snow internal mixing enhances the albedo effects by up to 30% (130%) for spherical (nonspherical) grains relative to external mixing. The overall uncertainty induced by snow shape and BC-snow mixing state is about 21-32%.

Antarctic Sea Ice Thickness and Snow-to-Ice Conversion from Atmospheric Reanalysis and Passive Microwave Snow Depth

NASA Technical Reports Server (NTRS)

Markus, Thorsten; Maksym, Ted

2007-01-01

Passive microwave snow depth, ice concentration, and ice motion estimates are combined with snowfall from the European Centre for Medium Range Weather Forecasting (ECMWF) reanalysis (ERA-40) from 1979-200 1 to estimate the prevalence of snow-to-ice conversion (snow-ice formation) on level sea ice in the Antarctic for April-October. Snow ice is ubiquitous in all regions throughout the growth season. Calculated snow- ice thicknesses fall within the range of estimates from ice core analysis for most regions. However, uncertainties in both this analysis and in situ data limit the usefulness of snow depth and snow-ice production to evaluate the accuracy of ERA-40 snowfall. The East Antarctic is an exception, where calculated snow-ice production exceeds observed ice thickness over wide areas, suggesting that ERA-40 precipitation is too high there. Snow-ice thickness variability is strongly controlled not just by snow accumulation rates, but also by ice divergence. Surprisingly, snow-ice production is largely independent of snow depth, indicating that the latter may be a poor indicator of total snow accumulation. Using the presence of snow-ice formation as a proxy indicator for near-zero freeboard, we examine the possibility of estimating level ice thickness from satellite snow depths. A best estimate for the mean level ice thickness in September is 53 cm, comparing well with 51 cm from ship-based observations. The error is estimated to be 10-20 cm, which is similar to the observed interannual and regional variability. Nevertheless, this is comparable to expected errors for ice thickness determined by satellite altimeters. Improvement in satellite snow depth retrievals would benefit both of these methods.

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.

Fabrication, Densification and Thermionic Emission Property of Lanthanum Hexaboride

NASA Astrophysics Data System (ADS)

Yu, Yiping; Wang, Song; Li, Wei; Chen, Hongmei; Chen, Zhaohui

2018-03-01

An effective way to improve sintering densification of LaB6 was proposed and confirmed experimentally. Firstly, LaB6 nanopowders with a cube-like shape of 94.7 nm were fabricated by molten salt synthesis route at 800 °C for 1 h. Then, LaB6 bulk material of 98% density was prepared by hot pressing sintering of as-synthesized LaB6 nanopowders under 1800 °C/50 MPa/30 min. The acquired LaB6 bulk material had a work function of 2.87 eV and exhibited an excellent thermionic emission property. The saturation emission current density at 1500 and 1600 °C reached 37.4 and 44.3 A/cm2, respectively.

Validation of the Daily Passive Microwave Snow Depth Products Over Northern China

NASA Astrophysics Data System (ADS)

Qiao, D.; Li, Z.; Wang, N.; Zhou, J.; Zhang, P.; Gao, S.

2018-04-01

Passive microwave sensors have the capability to provide information on snow depth (SD), which is critically important for hydrological modeling and water resource management. However, the different algorithms used to produce SD products lead to discrepancies in the data. To determine which products might be most suitable for Northern China, this paper assesses the accuracy of the existing snow depth products in the period of 2002-2011. By comparing three daily snow depth products, including NSIDC, WESTDC and ESA Globsnow, with snow cover product and meteorological stations data, the accuracies of the different SD products are analyzed for different snow class and forest cover fraction. The results show that comparison between snow cover derived from snow depth of NSIDC, ESA GlobSnow and WESTDC with snow cover product shows that accuracy of WESTDC and ESA GlobSnow in snow cover detecting can reach 0.70. Compared to meteorological stations data below 20 cm, NSIDC consistently overestimate, WESTDC and ESA Globsnow underestimate, furthermore the product from WESTDC is superior to the others. The three products have the same tendency of significant undervaluation over 20 cm. The WESTDC is superior to the ESA Globsnow and NSIDC in non-forest regions, whereas the ESA GlobSnow estimate is superior to the WESTDC and NSIDC in forest regions. As for the prairie and alpine snow, WESTDC has smaller bias and RMSE, meanwhile Globsnow has advantages in the snow depth retrieval in tundra and taiga snow. Therefore, we should choose the more suitable snow depth products according to different needs.

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.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Seasonal Snow Extent and Snow Volume in South America Using SSM/I Passive Microwave Data

NASA Technical Reports Server (NTRS)

Foster, James L.; Chang, A. T. C.; Hall, D. K.; Kelly, R.; Houser, Paul (Technical Monitor)

2001-01-01

Seasonal snow cover in South America was examined in this study using passive microwave satellite data from the Special Sensor Microwave Imagers (SSM/I) on board Defense Meteorological Satellite Program (DMSP) satellites. For the period from 1992-1998, both snow cover extent and snow depth (snow mass) were investigated during the winter months (May-August) in the Patagonia region of Argentina. Since above normal temperatures in this region are typically above freezing, the coldest winter month was found to be not only the month having the most extensive snow cover but also the month having the deepest snows. For the seven-year period of this study, the average snow cover extent (May-August) was about 0.46 million sq km and the average monthly snow mass was about 1.18 x 10(exp 13) kg. July 1992 was the month having the greatest snow extent (nearly 0.8 million sq km) and snow mass (approximately 2.6 x 10(exp 13) kg).

Finland Validation of the New Blended Snow Product

NASA Technical Reports Server (NTRS)

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

2008-01-01

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

File-Based One-Way BISON Coupling Through VERA: User's Manual

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

Stimpson, Shane G.

Activities to incorporate fuel performance capabilities into the Virtual Environment for Reactor Applications (VERA) are receiving increasing attention [1–6]. The multiphysics emphasis is expanding as the neutronics (MPACT) and thermal-hydraulics (CTF) packages are becoming more mature. Capturing the finer details of fuel phenomena (swelling, densification, relocation, gap closure, etc.) is the natural next step in the VERA development process since these phenomena are currently not directly taken into account. While several codes could be used to accomplish this, the BISON fuel performance code [8,9] being developed by the Idaho National Laboratory (INL) is the focus of ongoing work in themore » Consortium for Advanced Simulation of Light Water Reactors (CASL). Built on INL’s MOOSE framework [10], BISON uses the finite element method for geometric representation and a Jacobian-free Newton-Krylov (JFNK) scheme to solve systems of partial differential equations for various fuel characteristic relationships. There are several modes of operation in BISON, but, this work uses a 2D azimuthally symmetric (R-Z) smeared-pellet model. This manual is intended to cover (1) the procedure pertaining to the standalone BISON one-way coupling from VERA and (2) the procedure to generate BISON fuel temperature tables that VERA can use.« less

Towards a well-founded and reproducible snow load map for Austria

NASA Astrophysics Data System (ADS)

Winkler, Michael; Schellander, Harald

2017-04-01

"EN 1991-1-3 Eurocode 1: Part 1-3: Snow Loads" provides standard for the determination of the snow load to be used for the structural design of buildings etc. Since 2006 national specifications for Austria define a snow load map with four "load zones", allowing the calculation of the characteristic ground snow load sk for locations below 1500 m asl. A quadratic regression between altitude and sk is used, as suggested by EN 1991-1-3. The actual snow load map is based on best meteorological practice, but still it is somewhat subjective and non-reproducible. Underlying snow data series often end in the 1980s; in the best case data until about 2005 is used. Moreover, extreme value statistics only rely on the Gumbel distribution and the way in which snow depths are converted to snow loads is generally unknown. This might be enough reasons to rethink the snow load standard for Austria, all the more since today's situation is different to what it was some 15 years ago: Firstly, Austria is rich of multi-decadal, high quality snow depth measurements. These data are not well represented in the actual standard. Secondly, semi-empirical snow models allow sufficiently precise calculations of snow water equivalents and snow loads from snow depth measurements without the need of other parameters like temperature etc. which often are not available at the snow measurement sites. With the help of these tools, modelling of daily snow load series from daily snow depth measurements is possible. Finally, extreme value statistics nowadays offers convincing methods to calculate snow depths and loads with a return period of 50 years, which is the base of sk, and allows reproducible spatial extrapolation. The project introduced here will investigate these issues in order to update the Austrian snow load standard by providing a well-founded and reproducible snow load map for Austria. Not least, we seek for contact with standards bodies of neighboring countries to find intersections as well as to avoid inconsistencies and duplications of effort.

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.

Catchment-scale snow depth monitoring with balloon photogrammetry

NASA Astrophysics Data System (ADS)

Durand, M. T.; Li, D.; Wigmore, O.; Vanderjagt, B. J.; Molotch, N. P.; Bales, R. C.

2016-12-01

Field campaigns and permanent in-situ facilities provide extensive measurements of snowpack properties at catchment (or smaller) scales, and have consistently improved our understanding of snow processes and the estimation of snow water resources. However, snow depth, one of the most important snow states, has been measured almost entirely with discrete point-scale samplings in field measurements; spatiotemporally continuous snow depth measurements are nearly nonexistent, mainly due to the high cost of airborne flights and the ban of Unmanned Aerial Systems in many areas (e.g. in all the national parks). In this study, we estimate spatially continuous snow depth from photogrammetric reconstruction of aerial photos taken from a weather balloon. The study was conducted in a 0.2 km2 watershed in Wolverton, Sequoia National Park, California. We tied a point-and-shoot camera on a helium-inflated weather balloon to take aerial images; the camera was scripted to automatically capture images every 3 seconds and to record the camera position and orientation at the imaging times using a built-in GPS. With the 2D images of the snow-covered ground and the camera position and orientation data, the 3D coordinates of the snow surface were reconstructed at 10 cm resolution using photogrammetry software PhotoScan. Similar measurements were taken for the snow-free ground after snowmelt, and the snow depth was estimated from the difference between the snow-on and snow-off measurements. Comparing the photogrammetric-estimated snow depths with the 32 manually measured depths, taken at the same time as the snow-on balloon flight, we find the RMSE of the photogrammetric snow depth is 7 cm, which is 2% of the long-term peak snow depth in the study area. This study suggests that the balloon photogrammetry is a repeatable, economical, simple, and environmental-friendly method to continuously monitor snow at small-scales. Spatiotemporally continuous snow depth could be regularly measured in future field measurements to supplement traditional snow property observations. In addition, since the process of collecting and processing balloon photogrammetry data is straightforward, the photogrammetric snow depth could be shared with the public in real time using our cloud platform that is currently under development.

Red and near-infrared spectral reflectance of snow

NASA Technical Reports Server (NTRS)

Obrien, H. W.; Munis, R. H.

1975-01-01

The spectral reflectance of snow in the range of 0.60 to 2.50 microns wavelengths was studied in a cold laboratory using natural snow and simulated preparations of snow. A white barium sulfate powder was used as the standard for comparison. The high reflectance (usually nearly 100%) of fresh natural snow in visible wavelengths declines rapidly at wavelengths longer than the visible, as the spectral absorption coefficients of ice increase. Aging snow becomes only somewhat less reflective than fresh snow in the visible region and usually retains a reflectance greater than 80%. In the near infrared, aging snow tends to become considerably less reflective than fresh snow.

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.

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.

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

NASA Technical Reports Server (NTRS)

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

Snow Water Equivalent Pressure Sensor Performance in a Deep Snow Cover

NASA Astrophysics Data System (ADS)

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

2006-12-01

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

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.

Continuity of MODIS and VIIRS Snow-Cover Maps during Snowmelt in the Catskill Mountains in New York

NASA Astrophysics Data System (ADS)

Hall, D. K.; Riggs, G. A., Jr.; Roman, M. O.; DiGirolamo, N. E.

2015-12-01

We investigate the local and regional differences and possible biases between the Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible-Infrared Imager Radiometer Suite (VIIRS) snow-cover maps in the winter of 2012 during snowmelt conditions in the Catskill Mountains in New York using a time series of cloud-gap filled daily snow-cover maps. The MODIS Terra instrument has been providing daily global snow-cover maps since February 2000 (Riggs and Hall, 2015). Using the VIIRS instrument, launched in 2011, NASA snow products are being developed based on the heritage MODIS snow-mapping algorithms, and will soon be available to the science community. Continuity of the standard NASA MODIS and VIIRS snow-cover maps is essential to enable environmental-data records (EDR) to be developed for analysis of snow-cover trends using a consistent data record. For this work, we compare daily MODIS and VIIRS snow-cover maps of the Catskill Mountains from 29 February through 14 March 2012. The entire region was snow covered on 29 February and by 14 March the snow had melted; we therefore have a daily time series available to compare normalized difference snow index (NDSI), as an indicator of snow-cover fraction. The MODIS and VIIRS snow-cover maps have different spatial resolutions (500 m for MODIS and 375 m for VIIRS) and different nominal overpass times (10:30 AM for MODIS Terra and 2:30 PM for VIIRS) as well as different cloud masks. The results of this work will provide a quantitative assessment of the continuity of the snow-cover data records for use in development of an EDR of snow cover.http://modis-snow-ice.gsfc.nasa.gov/Riggs, G.A. and D.K. Hall, 2015: MODIS Snow Products User Guide to Collection 6, http://modis-snow-ice.gsfc.nasa.gov/?c=userguides

The assessment of EUMETSAT HSAF Snow Products for mountainuos areas in the eastern part of Turkey

NASA Astrophysics Data System (ADS)

Akyurek, Z.; Surer, S.; Beser, O.; Bolat, K.; Erturk, A. G.

2012-04-01

Monitoring the snow parameters (e.g. snow cover area, snow water equivalent) is a challenging work. Because of its natural physical properties, snow highly affects the evolution of weather from daily basis to climate on a longer time scale. The derivation of snow products over mountainous regions has been considered very challenging. This can be done by periodic and precise mapping of the snow cover. However inaccessibility and scarcity of the ground observations limit the snow cover mapping in the mountainous areas. Today, it is carried out operationally by means of optical satellite imagery and microwave radiometry. In retrieving the snow cover area from satellite images bring the problem of topographical variations within the footprint of satellite sensors and spatial and temporal variation of snow characteristics in the mountainous areas. Most of the global and regional operational snow products use generic algorithms for flat and mountainous areas. However the non-uniformity of the snow characteristics can only be modeled with different algorithms for mountain and flat areas. In this study the early findings of Satellite Application Facilities on Hydrology (H-SAF) project, which is financially supported by EUMETSAT, will be presented. Turkey is a part of the H-SAF project, both in product generation (eg. snow recognition, fractional snow cover and snow water equivalent) for mountainous regions for whole Europe, cal/val of satellite-derived snow products with ground observations and cal/val studies with hydrological modeling in the mountainous terrain of Europe. All the snow products are operational on a daily basis. For the snow recognition product (H10) for mountainous areas, spectral thresholding methods were applied on sub pixel scale of MSG-SEVIRI images. The different spectral characteristics of cloud, snow and land determined the structure of the algorithm and these characteristics were obtained from subjective classification of known snow cover features in the MSG/SEVIRI images. The fractional snow cover area (H12) algorithm is based on a sub-pixel reflectance model applied on METOP-AVHRR data. Knowing the effects of topography on satellite-measured radiances for rough terrain, the sun zenith and azimuth angles, as well as direction of observation relative to these are taken into account in estimating the target reflectances from the satellite images. The values of SWE products (H13) were obtained using an assimilation process based on the Helsinki University of Technology model using Advanced Microwave Scanning Radiometer for EOS (AMSR-E) daily brightness-temperature values. The validation studies for three products have been performed for the water years 2010 and 2011. Average values of 70% of probability of detection for snow recognition product, 60% of overall accuracy for the fractional snow cover product and 45 mm RMSE for the snow water equivalent product have been obtained from the validation studies. Final versions of these three products will be presented and discussed. Key words: snow, satellite images, mountain, HSAF, snow cover, snow water equivalent

COSMO-SkyMed Image Investigation of Snow Features in Alpine Environment

PubMed Central

Paloscia, Simonetta; Pettinato, Simone; Santi, Emanuele; Valt, Mauro

2017-01-01

In this work, X band images acquired by COSMO-SkyMed (CSK) on alpine environment have been analyzed for investigating snow characteristics and their effect on backscattering variations. Preliminary results confirmed the capability of simultaneous optical and Synthetic Aperture Radar (SAR) images (Landsat-8 and CSK) in separating snow/no-snow areas and in detecting wet snow. The sensitivity of backscattering to snow depth has not always been confirmed, depending on snow characteristics related to the season. A model based on Dense Media Radiative Transfer theory (DMRT-QMS) was applied for simulating the backscattering response on the X band from snow cover in different conditions of grain size, snow density and depth. By using DMRT-QMS and snow in-situ data collected on Cordevole basin in Italian Alps, the effect of grain size and snow density, beside snow depth and snow water equivalent, was pointed out, showing that the snow features affect the backscatter in different and sometimes opposite ways. Experimental values of backscattering were correctly simulated by using this model and selected intervals of ground parameters. The relationship between simulated and measured backscattering for the entire dataset shows slope >0.9, determination coefficient, R2 = 0.77, and root mean square error, RMSE = 1.1 dB, with p-value <0.05. PMID:28054962

Mesoscale variability of the Upper Colorado River snowpack

USGS Publications Warehouse

Ling, C.-H.; Josberger, E.G.; Thorndike, A.S.

1996-01-01

In the mountainous regions of the Upper Colorado River Basin, snow course observations give local measurements of snow water equivalent, which can be used to estimate regional averages of snow conditions. We develop a statistical technique to estimate the mesoscale average snow accumulation, using 8 years of snow course observations. For each of three major snow accumulation regions in the Upper Colorado River Basin - the Colorado Rocky Mountains, Colorado, the Uinta Mountains, Utah, and the Wind River Range, Wyoming - the snow course observations yield a correlation length scale of 38 km, 46 km, and 116 km respectively. This is the scale for which the snow course data at different sites are correlated with 70 per cent correlation. This correlation of snow accumulation over large distances allows for the estimation of the snow water equivalent on a mesoscale basis. With the snow course data binned into 1/4?? latitude by 1/4?? longitude pixels, an error analysis shows the following: for no snow course data in a given pixel, the uncertainty in the water equivalent estimate reaches 50 cm; that is, the climatological variability. However, as the number of snow courses in a pixel increases the uncertainty decreases, and approaches 5-10 cm when there are five snow courses in a pixel.

From the clouds to the ground - snow precipitation patterns vs. snow accumulation patterns

NASA Astrophysics Data System (ADS)

Gerber, Franziska; Besic, Nikola; Mott, Rebecca; Gabella, Marco; Germann, Urs; Bühler, Yves; Marty, Mauro; Berne, Alexis; Lehning, Michael

2017-04-01

Knowledge about snow distribution and snow accumulation patterns is important and valuable for different applications such as the prediction of seasonal water resources or avalanche forecasting. Furthermore, accumulated snow on the ground is an important ground truth for validating meteorological and climatological model predictions of precipitation in high mountains and polar regions. Snow accumulation patterns are determined by many different processes from ice crystal nucleation in clouds to snow redistribution by wind and avalanches. In between, snow precipitation undergoes different dynamical and microphysical processes, such as ice crystal growth, aggregation and riming, which determine the growth of individual particles and thereby influence the intensity and structure of the snowfall event. In alpine terrain the interaction of different processes and the topography (e.g. lifting condensation and low level cloud formation, which may result in a seeder-feeder effect) may lead to orographic enhancement of precipitation. Furthermore, the redistribution of snow particles in the air by wind results in preferential deposition of precipitation. Even though orographic enhancement is addressed in numerous studies, the relative importance of micro-physical and dynamically induced mechanisms on local snowfall amounts and especially snow accumulation patterns is hardly known. To better understand the relative importance of different processes on snow precipitation and accumulation we analyze snowfall and snow accumulation between January and March 2016 in Davos (Switzerland). We compare MeteoSwiss operational weather radar measurements on Weissfluhgipfel to a spatially continuous snow accumulation map derived from airborne digital sensing (ADS) snow height for the area of Dischma valley in the vicinity of the weather radar. Additionally, we include snow height measurements from automatic snow stations close to the weather radar. Large-scale radar snow accumulation patterns show a snowfall gradient consistent with the prevailing wind direction. Deriving snow accumulation based on radar data is challenging as the close-ground precipitation patters cannot be resolved by the radar due to shielding and ground clutter in highly complex terrain. Nonetheless, radar measurements show distinct patterns of snowfall and accumulation, which may be the result of orographic enhancement. Station-based snow accumulation measurements are in reasonable agreement with the estimated large-scale radar snow accumulation. The ADS-based snow accumulation maps feature much smaller scale snow accumulation patterns likely due to close-ground wind effects and snow redistribution on top of an altitudinal gradient. To evaluate microphysical processes and patterns influenced by the topography we run a hydrometeor classification on the radar data. The relative importance of topographically induced effects on snow accumulation patterns is investigated based on vertical cross sections of hydrometeor data and corresponding snow accumulation.

Evaluation of the Snow Simulations from the Community Land Model, Version 4 (CLM4)

NASA Technical Reports Server (NTRS)

Toure, Ally M.; Rodell, Matthew; Yang, Zong-Liang; Beaudoing, Hiroko; Kim, Edward; Zhang, Yongfei; Kwon, Yonghwan

2015-01-01

This paper evaluates the simulation of snow by the Community Land Model, version 4 (CLM4), the land model component of the Community Earth System Model, version 1.0.4 (CESM1.0.4). CLM4 was run in an offline mode forced with the corrected land-only replay of the Modern-Era Retrospective Analysis for Research and Applications (MERRA-Land) and the output was evaluated for the period from January 2001 to January 2011 over the Northern Hemisphere poleward of 30 deg N. Simulated snow-cover fraction (SCF), snow depth, and snow water equivalent (SWE) were compared against a set of observations including the Moderate Resolution Imaging Spectroradiometer (MODIS) SCF, the Interactive Multisensor Snow and Ice Mapping System (IMS) snow cover, the Canadian Meteorological Centre (CMC) daily snow analysis products, snow depth from the National Weather Service Cooperative Observer (COOP) program, and Snowpack Telemetry (SNOTEL) SWE observations. CLM4 SCF was converted into snow-cover extent (SCE) to compare with MODIS SCE. It showed good agreement, with a correlation coefficient of 0.91 and an average bias of -1.54 x 10(exp 2) sq km. Overall, CLM4 agreed well with IMS snow cover, with the percentage of correctly modeled snow-no snow being 94%. CLM4 snow depth and SWE agreed reasonably well with the CMC product, with the average bias (RMSE) of snow depth and SWE being 0.044m (0.19 m) and -0.010m (0.04 m), respectively. CLM4 underestimated SNOTEL SWE and COOP snow depth. This study demonstrates the need to improve the CLM4 snow estimates and constitutes a benchmark against which improvement of the model through data assimilation can be measured.

Impact of the snow cover scheme on snow distribution and energy budget modeling over the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Xie, Zhipeng; Hu, Zeyong; Xie, Zhenghui; Jia, Binghao; Sun, Genhou; Du, Yizhen; Song, Haiqing

2018-02-01

This paper presents the impact of two snow cover schemes (NY07 and SL12) in the Community Land Model version 4.5 (CLM4.5) on the snow distribution and surface energy budget over the Tibetan Plateau. The simulated snow cover fraction (SCF), snow depth, and snow cover days were evaluated against in situ snow depth observations and a satellite-based snow cover product and snow depth dataset. The results show that the SL12 scheme, which considers snow accumulation and snowmelt processes separately, has a higher overall accuracy (81.8%) than the NY07 (75.8%). The newer scheme performs better in the prediction of overall accuracy compared with the NY07; however, SL12 yields a 15.1% underestimation rate while NY07 overestimated the SCF with a 15.2% overestimation rate. Both two schemes capture the distribution of the maximum snow depth well but show large positive biases in the average value through all periods (3.37, 3.15, and 1.48 cm for NY07; 3.91, 3.52, and 1.17 cm for SL12) and overestimate snow cover days compared with the satellite-based product and in situ observations. Higher altitudes show larger root-mean-square errors (RMSEs) in the simulations of snow depth and snow cover days during the snow-free period. Moreover, the surface energy flux estimations from the SL12 scheme are generally superior to the simulation from NY07 when evaluated against ground-based observations, in particular for net radiation and sensible heat flux. This study has great implications for further improvement of the subgrid-scale snow variations over the Tibetan Plateau.

Wet Snow Mapping in Southern Ontario with Sentinel-1A Observations

NASA Astrophysics Data System (ADS)

Chen, H.; Kelly, R. E. J.

2017-12-01

Wet snow is defined as snow with liquid water present in an ice-water mix. It is can be an indicator for the onset of the snowmelt period. Knowledge about the extent of wet snow area can be of great importance for the monitoring of seasonal snowmelt runoff with climate-induced changes in snowmelt duration having implications for operational hydrological and ecological applications. Spaceborne microwave remote sensing has been used to observe seasonal snow under all-weather conditions. Active microwave observations of snow at C-band are sensitive to wet snow due to the high dielectric contrast with non-wet snow surfaces and synthetic aperture radar (SAR) is now openly available to identify and map the wet snow areas globally at relatively fine spatial resolutions ( 100m). In this study, a semi-automated workflow is developed from the change detection method of Nagler et al. (2016) using multi-temporal Sentinel-1A (S1A) dual-polarization observations of Southern Ontario. Weather station data and visible-infrared satellite observations are used to refine the wet snow area estimates. Wet snow information from National Operational Hydrologic Remote Sensing Center (NOHRSC) is used to compare with the S1A estimates. A time series of wet snow maps shows the variations in backscatter from wet snow on a pixel basis. Different land cover types in Southern Ontario are assessed with respect to their impacts on wet snow estimates. While forests and complex land surfaces can impact the ability to map wet snow, the approach taken is robust and illustrates the strong sensitivity of the approach to wet snow backscattering characteristics. The results indicate the feasibility of the change detection method on non-mountainous large areas and address the usefulness of Sentinel-1A data for wet snow mapping.

Investigation of the fracture mechanics of boride composites

NASA Technical Reports Server (NTRS)

Clougherty, E. V.; Pober, R. L.; Kaufman, L.

1972-01-01

Significant results were obtained in fabrication studies of the role of metallic additives of Zr, Ti, Ni, Fe and Cr on the densification of ZrB2. All elemental additions lower the processing temperatures required to effect full densification of ZrB2. Each addition effects enhanced densification by a clearly distinguishable and different mechanism and the resulting fabricated materials are different. A significant improvement in strength and fracture toughness was obtained for the ZrB2/Ti composition. Mechanical characterization studies for the ZrB2/SiC/C composites and the new ZrB2/Metal materials produced data relevant to the effect of impacting load on measured impact energies, a specimen configuration for which controlled fracture could occur in a suitably hard testing apparatus, and fracture strength data. Controlled fracture--indicative of measurable fracture toughness--was obtained for the ZrB2-SiC-C composite, and a ZrB2/Ti composite fabricated from ZrB2 with an addition of 30 weight per cent Ti. The increased strength and toughness of the ZrB2/Ti composite is consistent with the presence of a significantly large amount of a fine grained acicular phase formed by reaction of Ti with ZrB2 during processing.

The AlSi10Mg samples produced by selective laser melting: single track, densification, microstructure and mechanical behavior

NASA Astrophysics Data System (ADS)

Wei, Pei; Wei, Zhengying; Chen, Zhen; Du, Jun; He, Yuyang; Li, Junfeng; Zhou, Yatong

2017-06-01

This densification behavior and attendant microstructural characteristics of the selective laser melting (SLM) processed AlSi10Mg alloy affected by the processing parameters were systematically investigated. The samples with a single track were produced by SLM to study the influences of laser power and scanning speed on the surface morphologies of scan tracks. Additionally, the bulk samples were produced to investigate the influence of the laser power, scanning speed, and hatch spacing on the densification level and the resultant microstructure. The experimental results showed that the level of porosity of the SLM-processed samples was significantly governed by energy density of laser beam and the hatch spacing. The tensile properties of SLM-processed samples and the attendant fracture surface can be enhanced by decreasing the level of porosity. The microstructure of SLM-processed samples consists of supersaturated Al-rich cellular structure along with eutectic Al/Si situated at the cellular boundaries. The Si content in the cellular boundaries increases with increasing the laser power and decreasing the scanning speed. The hardness of SLM-processed samples was significantly improved by this fine microstructure compared with the cast samples. Moreover, the hardness of SLM-processed samples at overlaps was lower than the hardness observed at track cores.

Effects of Thermal and Pressure Histories on the Chemical Strengthening of Sodium Aluminosilicate Glass

NASA Astrophysics Data System (ADS)

Svenson, Mouritz; Thirion, Lynn; Youngman, Randall; Mauro, John; Bauchy, Mathieu; Rzoska, Sylwester; Bockowski, Michal; Smedskjaer, Morten

2016-03-01

Glasses can be chemically strengthened through the ion exchange process, wherein smaller ions in the glass (e.g., Na+) are replaced by larger ions from a salt bath (e.g., K+). This develops a compressive stress (CS) on the glass surface, which, in turn, improves the damage resistance of the glass. The magnitude and depth of the generated CS depends on the thermal and pressure histories of the glass prior to ion exchange. In this study, we investigate the ion exchange-related properties (mutual diffusivity, CS, and hardness) of a sodium aluminosilicate glass, which has been densified through annealing below the initial fictive temperature of the glass or through pressure-quenching from the glass transition temperature at 1 GPa prior to ion exchange. We show that the rate of alkali interdiffusivity depends only on the density of the glass, rather than on the applied densification method. However, we also demonstrate that for a given density, the increase in CS and increase in hardness induced by ion exchange strongly depends on the densification method. Specifically, at constant density, the CS and hardness values achieved through thermal annealing are larger than those achieved through pressure-quenching. These results are discussed in relation to the structural changes in the environment of the network-modifier and the overall network densification.

Nursing management of sensory overload in psychiatry – Theoretical densification and modification of the framework model

PubMed

Scheydt, Stefan; Needham, Ian; Behrens, Johann

2017-01-01

Background: Within the scope of the research project on the subjects of sensory overload and stimulus regulation, a theoretical framework model of the nursing care of patients with sensory overload in psychiatry was developed. In a second step, this theoretical model should now be theoretically compressed and, if necessary, modified. Aim: Empirical verification as well as modification, enhancement and theoretical densification of the framework model of nursing care of patients with sensory overload in psychiatry. Method: Analysis of 8 expert interviews by summarizing and structuring content analysis methods based on Meuser and Nagel (2009) as well as Mayring (2010). Results: The developed framework model (Scheydt et al., 2016b) could be empirically verified, theoretically densificated and extended by one category (perception modulation). Thus, four categories of nursing care of patients with sensory overload can be described in inpatient psychiatry: removal from stimuli, modulation of environmental factors, perceptual modulation as well as help somebody to help him- or herself / coping support. Conclusions: Based on the methodological approach, a relatively well-saturated, credible conceptualization of a theoretical model for the description of the nursing care of patients with sensory overload in stationary psychiatry could be worked out. In further steps, these measures have to be further developed, implemented and evaluated regarding to their efficacy.

Improving the Terrain-Based Parameter for the Assessment of Snow Redistribution in the Col du Lac Blanc Area and Comparisons with TLS Snow Depth Data

NASA Astrophysics Data System (ADS)

Schön, Peter; Prokop, Alexander; Naaim-Bouvet, Florence; Nishimura, Kouichi; Vionnet, Vincent; Guyomarc'h, Gilbert

2014-05-01

Wind and the associated snow drift are dominating factors determining the snow distribution and accumulation in alpine areas, resulting in a high spatial variability of snow depth that is difficult to evaluate and quantify. The terrain-based parameter Sx characterizes the degree of shelter or exposure of a grid point provided by the upwind terrain, without the computational complexity of numerical wind field models. The parameter has shown to qualitatively predict snow redistribution with good reproduction of spatial patterns, but has failed to quantitatively describe the snow redistribution, and correlations with measured snow heights were poor. The objective of our research was to a) identify the sources of poor correlations between predicted and measured snow re-distribution and b) improve the parameters ability to qualitatively and quantitatively describe snow redistribution in our research area, the Col du Lac Blanc in the French Alps. The area is at an elevation of 2700 m and particularly suited for our study due to its constant wind direction and the availability of data from a meteorological station. Our work focused on areas with terrain edges of approximately 10 m height, and we worked with 1-2 m resolution digital terrain and snow surface data. We first compared the results of the terrain-based parameter calculations to measured snow-depths, obtained by high-accuracy terrestrial laser scan measurements. The results were similar to previous studies: The parameter was able to reproduce observed patterns in snow distribution, but regression analyses showed poor correlations between terrain-based parameter and measured snow-depths. We demonstrate how the correlations between measured and calculated snow heights improve if the parameter is calculated based on a snow surface model instead of a digital terrain model. We show how changing the parameter's search distance and how raster re-sampling and raster smoothing improve the results. To improve the parameter's quantitative abilities, we modified the parameter, based on the comparisons with TLS data and the terrain and wind conditions specific to the research site. The modification is in a linear form f(x) = a * Sx, where a is a newly introduced parameter; f(x) yields the estimates for the snow height. We found that the parameter depends on the time period between the compared snow surfaces and the intensity of drifting snow events, which are linked to wind velocities. At the Col du Lac Blanc test side, blowing snow flux is recorded with snow particle counters (SPC). Snow flux is the number of drifting snow particles per time and area. Hence, the SPC provide data about the duration and intensity of drifting snow events, two important factors not accounted for by the terrain parameter Sx. We analyse how the SPC snow flux data can be used to estimate the magnitude of the new variable parameter a. We could improve the parameters' correlations with measured snow heights and its ability to quantitatively describe snow distribution in the Col du Lac Blanc area. We believe that our work is also a prerequisite to further improve the parameter's ability to describe snow redistribution.

Calculation of new snow densities from sub-daily automated snow measurements

NASA Astrophysics Data System (ADS)

Helfricht, Kay; Hartl, Lea; Koch, Roland; Marty, Christoph; Lehning, Michael; Olefs, Marc

2017-04-01

In mountain regions there is an increasing demand for high-quality analysis, nowcasting and short-range forecasts of the spatial distribution of snowfall. Operational services, such as for avalanche warning, road maintenance and hydrology, as well as hydropower companies and ski resorts need reliable information on the depth of new snow (HN) and the corresponding water equivalent (HNW). However, the ratio of HNW to HN can vary from 1:3 to 1:30 because of the high variability of new snow density with respect to meteorological conditions. In the past, attempts were made to calculate new snow densities from meteorological parameters mainly using daily values of temperature and wind. Further complex statistical relationships have been used to calculate new snow densities on hourly to sub-hourly time intervals to drive multi-layer snow cover models. However, only a few long-term in-situ measurements of new snow density exist for sub-daily time intervals. Settling processes within the new snow due to loading and metamorphism need to be considered when computing new snow density. As the effect of these processes is more pronounced for long time intervals, a high temporal resolution of measurements is desirable. Within the pluSnow project data of several automatic weather stations with simultaneous measurements of precipitation (pluviometers), snow water equivalent (SWE) using snow pillows and snow depth (HS) measurements using ultrasonic rangers were analysed. New snow densities were calculated for a set of data filtered on the basis of meteorological thresholds. The calculated new snow densities were compared to results from existing new snow density parameterizations. To account for effects of settling of the snow cover, a case study based on a multi-year data set using the snow cover model SNOWPACK at Weissfluhjoch was performed. Measured median values of hourly new snow densities at the different stations range from 54 to 83 kgm-3. This is considerably lower than a 1:10 approximation (i.e. 100 kgm-3), which is mainly based on daily values in the Alps. Variations in new snow density could not be explained in a satisfactory manner using meteorological data measured at the same location. Likewise, some of the tested parametrizations of new snow density, which primarily use air temperature as a proxy, result in median new snow densities close to the ones from automated measurements, but show only a low correlation between calculated and measured new snow densities. The case study on the influence of snow settling on HN resulted on average in an underestimation of HN by 17%, which corresponds to 2-3% of the cumulated HN from the previous 24 hours. Therefore, the mean hourly new snow densities may be overestimated by 14%. The analysis in this study is especially limited with respect to the meteorological influence on the HS measurement using ultra-sonic rangers. Nevertheless, the reasonable mean values encourage calculating new snow densities from standard hydro-meteorological measurements using more precise observation devices such as optical snow depth sensors and more sensitive scales for SWE measurements also on sub-daily time-scales.

Estimation of Snow Particle Model Suitable for a Complex and Forested Terrain: Lessons from SnowEx

NASA Astrophysics Data System (ADS)

Gatebe, C. K.; Li, W.; Stamnes, K. H.; Poudyal, R.; Fan, Y.; Chen, N.

2017-12-01

SnowEx 2017 obtained consistent and coordinated ground and airborne remote sensing measurements over Grand Mesa in Colorado, which feature sufficient forested stands to have a range of density and height (and other forest conditions); a range of snow depth/snow water equivalent (SWE) conditions; sufficiently flat snow-covered terrain of a size comparable to airborne instrument swath widths. The Cloud Absorption Radiometer (CAR) data from SnowEx are unique and can be used to assess the accuracy of Bidirectional Reflectance-Distribution Functions (BRDFs) calculated by different snow models. These measurements provide multiple angle and multiple wavelength data needed for accurate surface BRDF characterization. Such data cannot easily be obtained by current satellite remote sensors. Compared to ground-based snow field measurements, CAR measurements minimize the effect of self-shading, and are adaptable to a wide variety of field conditions. We plan to use the CAR measurements as the validation data source for our snow modeling effort. By comparing calculated BRDF results from different snow models to CAR measurements, we can determine which model best explains the snow BRDFs, and is therefore most suitable for application to satellite remote sensing of snow parameters and surface energy budget calculations.

Satellite Snow-Cover Mapping: A Brief Review

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.

1995-01-01

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

Snow-Cover Variability in North America in the 2000-2001 Winter as Determined from MODIS Snow Products

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Salomonson, Vincent V.; Riggs, George A.; Chien, Janet Y. L.; Houser, Paul R. (Technical Monitor)

2001-01-01

Moderate Resolution Imaging Spectroradiometer (MODIS) snow-cover maps have been available since September 13, 2000. These products, at 500 m spatial resolution, are available through the National Snow and Ice Data Center Distributed Active Archive Center in Boulder, Colorado. By the 2001-02 winter, 5 km climate-modeling grid (CMG) products will be available for presentation of global views of snow cover and for use in climate models. All MODIS snow-cover products are produced from automated algorithms that map snow in an objective manner. In this paper, we describe the MODIS snow products, and show snow maps from the fall of 2000 in North America.

Snow-Cover Variability in North America in the 2000-2001 Winter as Determined from MODIS Snow Products

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Salomonson, Vincent V.; Riggs, George A.; Chien, Y. L.; Houser, Paul R. (Technical Monitor)

2001-01-01

Moderate Resolution Imaging Spectroradiometer (MODIS) snow-cover maps have been available since September 13, 2000. These products, at 500-m spatial resolution, are available through the National Snow and Ice Data Center Distributed Active Archive Center in Boulder, Colorado. By the 2001-02 winter, 5-km climate-modeling grid (CMG) products will be available for presentation of global views of snow cover and for use in climate models. All MODIS snow-cover products are produced from automated algorithms that map snow in an objective manner. In this paper, we describe the MODIS snow products, and show snow maps from the fall of 2000 in North America.

Unexpected Patterns in Snow and Dirt

NASA Astrophysics Data System (ADS)

Ackerson, Bruce J.

2018-01-01

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

When Models and Observations Collide: Journeying towards an Integrated Snow Depth Product

NASA Astrophysics Data System (ADS)

Webster, M.; Petty, A.; Boisvert, L.; Markus, T.; Kurtz, N. T.; Kwok, R.; Perovich, D. K.

2017-12-01

Knowledge of snow depth is essential for assessing changes in sea ice mass balance due to snow's insulating and reflective properties. In remote sensing applications, the accuracy of sea ice thickness retrievals from altimetry crucially depends on snow depth. Despite the need for snow depth data, we currently lack continuous observations that capture the basin-scale snow depth distribution and its seasonal evolution. Recent in situ and remote sensing observations are sparse in space and time, and contain uncertainties, caveats, and/or biases that often require careful interpretation. Likewise, using model output for remote sensing applications is limited due to uncertainties in atmospheric forcing and different treatments of snow processes. Here, we summarize our efforts in bringing observational and model data together to develop an approach for an integrated snow depth product. We start with a snow budget model and incrementally incorporate snow processes to determine the effects on snow depth and to assess model sensitivity. We discuss lessons learned in model-observation integration and ideas for potential improvements to the treatment of snow in models.

A Comprehensive Snow Density Model for Integrating Lidar-Derived Snow Depth Data into Spatial Snow Modeling

NASA Astrophysics Data System (ADS)

Marks, D. G.; Kormos, P.; Johnson, M.; Bormann, K. J.; Hedrick, A. R.; Havens, S.; Robertson, M.; Painter, T. H.

2017-12-01

Lidar-derived snow depths when combined with modeled or estimated snow density can provide reliable estimates of the distribution of SWE over large mountain areas. Application of this approach is transforming western snow hydrology. We present a comprehensive approach toward modeling bulk snow density that is reliable over a vast range of weather and snow conditions. The method is applied and evaluated over mountainous regions of California, Idaho, Oregon and Colorado in the western US. Simulated and measured snow density are compared at fourteen validation sites across the western US where measurements of snow mass (SWE) and depth are co-located. Fitting statistics for ten sites from three mountain catchments (two in Idaho, one in California) show an average Nash-Sutcliff model efficiency coefficient of 0.83, and mean bias of 4 kg m-3. Results illustrate issues associated with monitoring snow depth and SWE and show the effectiveness of the model, with a small mean bias across a range of snow and climate conditions in the west.

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

NASA Technical Reports Server (NTRS)

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

2015-01-01

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

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.

Seasonal Snow Extent and Snow Mass in South America Using SMMR and SSM/I Passive Microwave Data (1979-2003)

NASA Technical Reports Server (NTRS)

Foster, J. L.; Hall, D. K.; Chiu, L.; Kelly, R. E.; Powell, H.; Chiu, L.

2007-01-01

Seasonal snow cover in South America was examined in this study using passive microwave satellite data from the Scanning Multichannel Microwave Radiometer (SMMR) on board the Nimbus-satellite and the Special Sensor Microwave Imagers (SSM/I) on board Defense Meteorological Satellite Program (DMSP) satellites. For the period from 1979-2003, both snow cover extent and snow depth (snow mass) were investigated during coldest months (May-September), primarily in the Patagonia area of Argentina and in Chile. Most of the seasonal snow in South America is in the Patagonia region of Argentina. Since winter temperatures in this region are often above freezing, the coldest winter month was found to be the month having the most extensive snow cover and also usually the month having the deepest snow cover as well. Sharp year-to-year differences were recorded using the passive microwave observations. The average snow cover extent for July, the month with the greatest average snow extent during the 25-year period of record, is 320,700 km(exp 2). In July of 1984, the average monthly snow cover was 701,250 km(exp 2) - the most extensive coverage observed between 1979 and 2003. However, in July of 1989, snow cover extent was only 120 km(exp 2). The 25-year period of record shows a sinusoidal like pattern, though there appears to be no obvious trend in either increasing or decreasing snow extent or snow mass between 1979 and 2003.

Improvement of mechanical strength of sintered Mo alloyed steel by optimization of sintering and cold-forging processes with densification

NASA Astrophysics Data System (ADS)

Kamakoshi, Y.; Shohji, I.; Inoue, Y.; Fukuda, S.

2017-10-01

Powder metallurgy (P/M) materials have been expected to be spread in automotive industry. Generally, since sintered materials using P/M ones contain many pores and voids, mechanical properties of them are inferior to those of conventional wrought materials. To improve mechanical properties of the sintered materials, densification is effective. The aim of this study is to improve mechanical strength of sintered Mo-alloyed steel by optimizing conditions in sintering and cold-forging processes. Mo-alloyed steel powder was compacted. Then, pre-sintering (PS) using a vacuum sintering furnace was conducted. Subsequently, coldforging (CF) by a backward extrusion method was conducted to the pre-sintered specimen. Moreover, the cold-forged specimen was heat treated by carburizing, tempering and quenching (CQT). Afterwards, mechanical properties were investigated. As a result, it was found that the density of the PS specimen is required to be more than 7.4 Mg/m3 to strengthen the specimen by heat treatment after CF. Furthermore, density and the microstructure of the PS specimen are most important factors to make the high density and strength material by CF. At the CF load of 1200 kN, the maximum density ratio reached approximately 99% by the use of the PS specimen with proper density and microstructure. At the CF load of 900 kN, although density ratio was high like more than 97.8%, transverse rupture strength decreased sharply. Since densification caused high shear stress and stress concentration in the surface layer, microcracks occurred by the damages of inter-particle sintered connection of the surface layer. On the contrary, in case of the CF load of 1200 kN, ultra-densification of the surface layer occurred by a sufficient plastic flow. Such sufficient compressed specimens regenerated the sintered connections by high temperature heat treatment and thus the high strength densified material was obtained. These processes can be applicable to near net shape manufacturing without surface machining.

Net mass balance calculations for the Shirase Drainage Basin, east Antarctica, using the mass budget method

NASA Astrophysics Data System (ADS)

Nakamura, Kazuki; Yamanokuchi, Tsutomu; Doi, Koichiro; Shibuya, Kazuo

2016-06-01

We quantify the mass budget of the Shirase drainage basin (SHI), Antarctica, by separately estimating snow accumulation (surface mass balance; SMB) and glacier ice mass discharge (IMD). We estimated the SMB in the SHI, using a regional atmospheric climate model (RACMO2.1). The SMB of the mainstream A flow region was 12.1 ± 1.5 Gt a-1 for an area of 1.985 × 105 km2. Obvious overestimation of the model round the coast, ∼0.5 Gt a-1, was corrected for. For calculating the IMD, we employed a 15-m resolution Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) with a digital elevation model (DEM) to determine the heights at the grounding line (GL), after comparison with the interpolated Bamber DEM grid heights; the results of this are referred to as the measured heights. Ice thickness data at the GL were inferred by using a free-board relationship between the measured height and the ice thickness, and considering the measured firn depth correction (4.2 m with the reference ice density of 910 kg m-3) for the nearby blue-ice area. The total IMD was estimated to be 14.0 ± 1.8 Gt a-1. Semi-empirical firn densification model gives the estimate within 0.1-0.2 Gt a-1 difference. The estimated net mass balance, -1.9 Gt a-1, has a two-σ uncertainty of ±3.3 Gt a-1, and probable melt water discharge strongly suggests negative NMB, although the associated uncertainty is large.

Anomalously-dense firn in an ice-shelf channel revealed by wide-angle radar

NASA Astrophysics Data System (ADS)

Drews, R.; Brown, J.; Matsuoka, K.; Witrant, E.; Philippe, M.; Hubbard, B.; Pattyn, F.

2015-10-01

The thickness of ice shelves, a basic parameter for mass balance estimates, is typically inferred using hydrostatic equilibrium for which knowledge of the depth-averaged density is essential. The densification from snow to ice depends on a number of local factors (e.g. temperature and surface mass balance) causing spatial and temporal variations in density-depth profiles. However, direct measurements of firn density are sparse, requiring substantial logistical effort. Here, we infer density from radio-wave propagation speed using ground-based wide-angle radar datasets (10 MHz) collected at five sites on Roi Baudouin Ice Shelf (RBIS), Dronning Maud Land, Antarctica. Using a novel algorithm including traveltime inversion and raytracing with a prescribed shape of the depth-density relationship, we show that the depth to internal reflectors, the local ice thickness and depth-averaged densities can reliably be reconstructed. For the particular case of an ice-shelf channel, where ice thickness and surface slope change substantially over a few kilometers, the radar data suggests that firn inside the channel is about 5 % denser than outside the channel. Although this density difference is at the detection limit of the radar, it is consistent with a similar density anomaly reconstructed from optical televiewing, which reveals 10 % denser firn inside compared to outside the channel. The denser firn in the ice-shelf channel should be accounted for when using the hydrostatic ice thickness for determining basal melt rates. The radar method presented here is robust and can easily be adapted to different radar frequencies and data-acquisition geometries.

Constraining variable density of ice shelves using wide-angle radar measurements

NASA Astrophysics Data System (ADS)

Drews, Reinhard; Brown, Joel; Matsuoka, Kenichi; Witrant, Emmanuel; Philippe, Morgane; Hubbard, Bryn; Pattyn, Frank

2016-04-01

The thickness of ice shelves, a basic parameter for mass balance estimates, is typically inferred using hydrostatic equilibrium, for which knowledge of the depth-averaged density is essential. The densification from snow to ice depends on a number of local factors (e.g., temperature and surface mass balance) causing spatial and temporal variations in density-depth profiles. However, direct measurements of firn density are sparse, requiring substantial logistical effort. Here, we infer density from radio-wave propagation speed using ground-based wide-angle radar data sets (10 MHz) collected at five sites on Roi Baudouin Ice Shelf (RBIS), Dronning Maud Land, Antarctica. We reconstruct depth to internal reflectors, local ice thickness, and firn-air content using a novel algorithm that includes traveltime inversion and ray tracing with a prescribed shape of the depth-density relationship. For the particular case of an ice-shelf channel, where ice thickness and surface slope change substantially over a few kilometers, the radar data suggest that firn inside the channel is about 5 % denser than outside the channel. Although this density difference is at the detection limit of the radar, it is consistent with a similar density anomaly reconstructed from optical televiewing, which reveals that the firn inside the channel is 4.7 % denser than that outside the channel. Hydrostatic ice thickness calculations used for determining basal melt rates should account for the denser firn in ice-shelf channels. The radar method presented here is robust and can easily be adapted to different radar frequencies and data-acquisition geometries.

Towards a realistic simulation of boreal summer tropical rainfall climatology in state-of-the-art coupled models: role of the background snow-free land albedo

NASA Astrophysics Data System (ADS)

Terray, P.; Sooraj, K. P.; Masson, S.; Krishna, R. P. M.; Samson, G.; Prajeesh, A. G.

2017-07-01

State-of-the-art global coupled models used in seasonal prediction systems and climate projections still have important deficiencies in representing the boreal summer tropical rainfall climatology. These errors include prominently a severe dry bias over all the Northern Hemisphere monsoon regions, excessive rainfall over the ocean and an unrealistic double inter-tropical convergence zone (ITCZ) structure in the tropical Pacific. While these systematic errors can be partly reduced by increasing the horizontal atmospheric resolution of the models, they also illustrate our incomplete understanding of the key mechanisms controlling the position of the ITCZ during boreal summer. Using a large collection of coupled models and dedicated coupled experiments, we show that these tropical rainfall errors are partly associated with insufficient surface thermal forcing and incorrect representation of the surface albedo over the Northern Hemisphere continents. Improving the parameterization of the land albedo in two global coupled models leads to a large reduction of these systematic errors and further demonstrates that the Northern Hemisphere subtropical deserts play a seminal role in these improvements through a heat low mechanism.

Gas chromatography--inductively coupled plasma--time-of-flight mass spectrometry for the speciation analysis of organolead compounds in environmental water samples.

PubMed

Heisterkamp, M; Adams, F C

2001-07-01

The application of inductively coupled plasma--time-of-flight mass spectrometry for the speciation analysis of organolead compounds in environmental waters is described. Construction of the transfer line was achieved by means of a relatively simple and rapid coupling procedure. Derivatization of the ionic lead species was achieved by in-situ propylation with sodium tetrapropylborate; simultaneous extraction of the derivatized compounds in hexane was followed by separation and detection by capillary gas chromatography hyphenated to inductively coupled plasma-time-of-flight mass spectrometry. Detection limits for the different organolead species ranged from 10 to 15 fg (as Pb), corresponding to procedural detection limits between 50 and 75 ng L(-1), on the basis of a 50 mL snow sample, extraction with 200 microL hexane, and subsequent injection of 1 microL of the organic extract on to the column. The accuracy of the system was confirmed by additional analysis of the water samples by capillary gas chromatography coupled with microwave-induced plasma-atomic-emission spectrometry and the analysis of a standard reference material CRM 605 (road dust) with a certified content of trimethyllead.

Improving snow fraction spatio-temporal continuity using a combination of MODIS and Fengyun-2 satellites over China

NASA Astrophysics Data System (ADS)

Jiang, L.; Wang, G.

2017-12-01

Snow cover is one of key elements in the investigations of weather, climatic change, water resource, and snow hazard. Satellites observations from on-board optical sensors provides the ability to snow cover mapping through the discrimination of snow from other surface features and cloud. MODIS provides maximum of snow cover data using 8-day composition data in order to reduce the cloud obscuration impacts. However, snow cover mapping is often required to obtain at the temporal scale of less than one day, especially in the case of disasters. Geostationary satellites provide much higher temporal resolution measurements (typically at 15 min or half or one hour), which has a great potential to reduce cloud cover problem and observe ground surface for identifying snow. The proposed method in this work is that how to take the advantages of polar-orbiting and geostationary optical sensors to accurately map snow cover without data gaps due to cloud. FY-2 geostationary satellites have high temporal resolution observations, however, they are lacking enough spectral bands essential for snow cover monitoring, such as the 1.6 μm band. Based on our recent work (Wang et al., 2017), we improved FY-2/VISSR fractional snow cover estimation with a linear spectral unmixing analysis method. The linear approach is applied then using the reflectance observed at the certain hourly image of FY-2 to calculate pixel-wise snow cover fraction. The composition of daily factional snow cover employs the sun zenith angle, where the snow fraction under lowest sun zenith angle is considered as the most confident result. FY-2/VISSR fractional snow cover map has less cloud due to the composition of multi-temporal snow maps in a single day. In order to get an accurate and cloud-reduced fractional snow cover map, both of MODIS and FY-2/VISSR daily snow fraction maps are blended together. With the combination of FY-2E/VISSR and MODIS, there are still some cloud existing in the daily snow fraction map. Then the combination snow fraction map is temporally reconstructed using MATLAB Piecewise Cubic Hermite Interpolating Polynomial (PCHIP) function to derive a completely daily cloud-free snow cover map under all the sky conditions.

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.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Neutral Poly-/perfluoroalkyl Substances in Air and Snow from the Arctic

PubMed Central

Xie, Zhiyong; Wang, Zhen; Mi, Wenying; Möller, Axel; Wolschke, Hendrik; Ebinghaus, Ralf

2015-01-01

Levels of neutral poly-/perfluoroalkyl substances (nPFASs) in air and snow collected from Ny-Ålesund were measured and their air-snow exchange was determined to investigate whether they could re-volatilize into the atmosphere driven by means of air-snow exchange. The total concentration of 12 neutral PFASs ranged from 6.7 to 39 pg m−3 in air and from 330 to 690 pg L−1 in snow. A significant log-linear relationship was observed between the gas/particle partition coefficient and vapor pressure of the neutral PFASs. For fluorotelomer alcohol (FTOHs) and fluorotelomer acrylates (FTAs), the air-snow exchange fluxes were positive, indicating net evaporative from snow into air, while net deposition into snow was observed for perfluorooctane sulfonamidoethanols (Me/EtFOSEs) in winter and spring of 2012. The air-snow exchange was snow-phase controlled for FTOHs and FTAs, and controlled by the air-phase for FOSEs. Air-snow exchange may significantly interfere with atmospheric concentrations of neutral PFASs in the Arctic. PMID:25746440

Catchment-scale evaluation of pollution potential of urban snow at two residential catchments in southern Finland.

PubMed

Sillanpää, Nora; Koivusalo, Harri

2013-01-01

Despite the crucial role of snow in the hydrological cycle in cold climate conditions, monitoring studies of urban snow quality often lack discussions about the relevance of snow in the catchment-scale runoff management. In this study, measurements of snow quality were conducted at two residential catchments in Espoo, Finland, simultaneously with continuous runoff measurements. The results of the snow quality were used to produce catchment-scale estimates of areal snow mass loads (SML). Based on the results, urbanization reduced areal snow water equivalent but increased pollutant accumulation in snow: SMLs in a medium-density residential catchment were two- to four-fold higher in comparison with a low-density residential catchment. The main sources of pollutants were related to vehicular traffic and road maintenance, but also pet excrement increased concentrations to a high level. Ploughed snow can contain 50% of the areal pollutant mass stored in snow despite its small surface area within a catchment.

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

USGS Publications Warehouse

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

2003-01-01

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

Testing a blowing snow model against distributed snow measurements at Upper Sheep Creek, Idaho, United States of America

Treesearch

Rajiv Prasad; David G. Tarboton; Glen E. Liston; Charles H. Luce; Mark S. Seyfried

2001-01-01

In this paper a physically based snow transport model (SnowTran-3D) was used to simulate snow drifting over a 30 m grid and was compared to detailed snow water equivalence (SWE) surveys on three dates within a small 0.25 km2 subwatershed, Upper Sheep Creek. Two precipitation scenarios and two vegetation scenarios were used to carry out four snow transport model runs in...

Spatiotemporal Variability and in Snow Phenology over Eurasian Continent druing 1966-2012

NASA Astrophysics Data System (ADS)

Zhong, X.; Zhang, T.; Wang, K.; Zheng, L.; Wang, H.

2016-12-01

Snow cover is a key part of the cryosphere, which is a critical component of the global climate system. Snow cover phenology critically effects on the surface energy budget, the surface albedo and hydrological processes. In this study, the climatology and spatiotemporal variability of snow cover phenology were investigated using the long-term (1966-2012) ground-based measurements of daily snow depth from 1103 stations across the Eurasian Continent. The results showed that the distributions of the first date, last date, snow cover duration and number of snow cover days generally represented the latitudinal zonality over the Eurasian Continent, and there were significant elevation gradient patterns in the Tibetan Plateau. The first date of snow cover delayed by about 1.2 day decade-1, the last date of snow cover advanced with the rate of -1.2 day decade-1, snow cover duration and number of snow cover days shortened by about 2.7and 0.6 day decade-1, respectively, from 1966 through 2012. Compared with precipitation, the correlation between snow cover phenology and air temperature was more significant. The changes in snow cover duration were mainly controlled by the changes of air temperature in autumn and spring. The shortened number of snow cover days was affected by rising temperature during the cold season except for the air temperature in autumn and spring.

Mesocell study area snow distributions for the Cold Land Processes Experiment (CLPX)

Treesearch

Glen E. Liston; Christopher A. Hiemstra; Kelly Elder; Donald W. Cline

2008-01-01

The Cold Land Processes Experiment (CLPX) had a goal of describing snow-related features over a wide range of spatial and temporal scales. This required linking disparate snow tools and datasets into one coherent, integrated package. Simulating realistic high-resolution snow distributions and features requires a snow-evolution modeling system (SnowModel) that can...

Application of LANDSAT imagery for snow mapping in Norway

NASA Technical Reports Server (NTRS)

Odegaard, H. (Principal Investigator); Ostrem, G.

1977-01-01

The author has identified the following significant results. It was shown that if the snow cover extent was determined from all four LANDSAT bands, there were significant differences in results. The MSS 4 gave the largest snow cover, but only slightly more than MSS 5, whereas MSS 6 and 7 gave the smallest snow area. A study was made to show that there was a relationship between the last date of snow fall and the area covered with snow, as determined from different bands. Imagery obtained shortly after a snow fall showed no significant difference in the snow-covered area when the four bans were compared, whereas, pronounced differences in the snow-covered area were found in images taken after a long period without precipitation.

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

NASA Astrophysics Data System (ADS)

Dong, Wenquan; Meng, Jihua

2015-10-01

The distribution and change of snow coverage are sensitive factors of climate change. In northeast part of China, farmlands are still covered with snow in spring. Since sowing activity can only be done when the snow melted, fields snow coverage monitoring provides reference for the determination of sowing date. Because of the restriction of the sensors and application requirements, current researches on remote sensing of snow focus more on the study of musicale and large scale, rather than the study of small scale, and especially research on snow melting period is rarely reported.HJ-1A/B satellites are parts of little satellite constellation, focusing on environment and disaster monitoring and meteorological forecast. Compared to other data sources, HJ-1A/B satellites both have comparatively higher temporal and spatial resolution and are more conducive to monitor the variations of melting snow coverage at small watershed. This paper was based on HJ-1A/1B data, taking Hongxing farm of Bei'an, Heilongjiang Province, China as the study area. In this paper, we exploited the methods for extraction of snow cover information on farmland in two cases, both HJ-1A/1B CCD with HJ-1B IRS data and just HJ-1A/1B CCD data. The reason we chose the two cases is that, the two optical satellites HJ-1A/B are capable of providing a whole territory coverage period in visible light spectrum in two days, infrared spectrum in four days. So sometimes we can only obtain CCD image. In this case, the method of normalized snow index cannot be used to extract snow coverage information. Using HJ-1A/1B CCD with HJ-1B IRS data, combined with the theory of snow remote sensing monitoring, this paper analyzed spectral response characteristics of HJ-1A/1B satellites data, then the widely used Normalized Difference Snow Index(NDSI) and S3 Index were quoted to the HJ-1A/1B satellites data. The NDSI uses reflectance values of Red and SWIR spectral bands of HJ-1B, and S3 index uses reflectance values of NIR, Red and SWIR spectral bands. With multi-temporal HJ satellite data, the optimal threshold of normalized snow index was determined to divide the farmland into snow covering area, melting snow area and non-snow area. The results are quite similar to each other and of high accuracy, and the melting snow coverage can be well extracted by two types of normalized snow index. When we can only obtain CCD image, we use supervised classification method to extract melting snow coverage. With this method, the accuracy of fields snow coverage extraction is slightly lower than that using normalized snow index methods mentioned above. And in mountain area, the snow coverage area is slightly larger than that is extracted by normalized snow index methods, because the shadows make the color of snow in the valley darker, the supervised classification method divides it into non-snow coverage area, while the normalized snow index method well weakened the effect of shadow. This study shows that extraction accuracy in both cases is assessed, and both of them can meet the needs of practical applications. HJ-1A/1B satellites are conducive to monitor the variations of melting snow coverage over farmland, and they can provide reference for the determination of sowing date.

Under-canopy snow accumulation and ablation measured with airborne scanning LiDAR altimetry and in-situ instrumental measurements, southern Sierra Nevada, California

NASA Astrophysics Data System (ADS)

Kirchner, P. B.; Bales, R. C.; Musselman, K. N.; Molotch, N. P.

2012-12-01

We investigated the influence of canopy on snow accumulation and melt in a mountain forest using paired snow on and snow off scanning LiDAR altimetry, synoptic measurement campaigns and in-situ time series data of snow depth, SWE, and radiation collected from the Kaweah River watershed, Sierra Nevada, California. Our analysis of forest cover classified by dominant species and 1 m2 grided mean under canopy snow accumulation calculated from airborne scanning LiDAR, demonstrate distinct relationships between forest class and under-canopy snow depth. The five forest types were selected from carefully prepared 1 m vegetation classifications and named for their dominant tree species, Giant Sequoia, Jeffrey Pine, White Fir, Red Fir, Sierra Lodgepole, Western White Pine, and Foxtail Pine. Sufficient LiDAR returns for calculating mean snow depth per m2 were available for 31 - 44% of the canopy covered area and demonstrate a reduction in snow depth of 12 - 24% from adjacent open areas. The coefficient of variation in snow depth under canopies ranged from 0.2 - 0.42 and generally decreased as elevation increased. Our analysis of snow density snows no statistical significance between snow under canopies and in the open at higher elevations with a weak significance for snow under canopies at lower elevations. Incident radiation measurements made at 15 minute intervals under forest canopies show an input of up to 150 w/m2 of thermal radiation from vegetation to the snow surface on forest plots. Snow accumulated on the mid to high elevation forested slopes of the Sierra Nevada represents the majority of winter snow storage. However snow estimates in forested environments demonstrate a high level of uncertainty due to the limited number of in-situ observations and the inability of most remote sensing platforms to retrieve reflectance under dense vegetation. Snow under forest canopies is strongly mediated by forest cover and decoupled from the processes that dictate accumulation and ablation of snow in open locations, where almost all precipitation and meteorlogic measurements concerning snow are made. Snow accumulation is intercepted by vegetation until it accumulates to a depth equal to or greater than the height of the vegetation, is reduced by the amount of sublimation or evaporation occurring while on the canopy and is redistributed beneath the canopy at a different density or as liquid water. Ablation processes are dictated by the energy environment surrounding vegetation where sensible heat is mediated by shading of short wave radiation.

Field observations of the electrostatic charges of blowing snow in Hokkaido, Japan

NASA Astrophysics Data System (ADS)

Omiya, S.; Sato, A.

2011-12-01

An electrostatic charge of blowing snow may be a contributing factor in the formation of a snow drift and a snow cornice, and changing of the trajectory of own motion. However, detailed electrification characteristics of blowing snow are not known as there are few reports of charge measurements. We carried out field observations of the electrostatic charges of blowing snow in Tobetsu, Hokkaido, Japan in the mid winter of 2011. An anemovane and a thermohygrometer were used for the meteorological observation. Charge-to-mass ratios of blowing snow were obtained by a Faraday-cage, an electrometer and an electric balance. In this observation period, the air temperature during the blowing snow event was -6.5 to -0.5 degree Celsius. The measured charges in this observation were consistent with the previous studies in sign, which is negative, but they were smaller than the previous one. In most cases, the measured values increased with the temperature decrease, which corresponds with previous studies. However, some results contradicted the tendency, and the maximum value was obtained on the day of the highest air temperature of -0.5 degree Celsius. This discrepancy may be explained from the difference of the snow surface condition on observation day. The day when the maximum value was obtained, the snow surface was covered with old snow, and hard. On the other hand, in many other cases, the snow surface was covered with the fresh snow, and soft. Blowing snow particles on the hard surface can travel longer distance than on the soft one. Therefore, it can be surmised that the hard surface makes the blowing snow particles accumulate a lot of negative charges due to a large number of collisions to the surface. This can be supported by the results of the wind tunnel experiments by Omiya and Sato (2011). By this field observation, it was newly suggested that the electrostatic charge of blowing snow are influenced greatly by the difference of the snow surface condition. REFERENCE: Omiya and Sato,(2010):An electrostatic charge measurement of blowing snow particles focusing on collision frequency to the snow surface. AGU Abstract Database, 2010 Fall Meeting.

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.

Subpixel Snow-covered Area Including Differentiated Grain Size from AVIRIS Data Over the Sierra Nevada Mountain Range

NASA Astrophysics Data System (ADS)

Hill, R.; Calvin, W. M.; Harpold, A. A.

2016-12-01

Mountain snow storage is the dominant source of water for humans and ecosystems in western North America. Consequently, the spatial distribution of snow-covered area is fundamental to both hydrological, ecological, and climate models. Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data were collected along the entire Sierra Nevada mountain range extending from north of Lake Tahoe to south of Mt. Whitney during the 2015 and 2016 snow-covered season. The AVIRIS dataset used in this experiment consists of 224 contiguous spectral channels with wavelengths ranging 400-2500 nanometers at a 15-meter spatial pixel size. Data from the Sierras were acquired on four days: 2/24/15 during a very low snow year, 3/24/16 near maximum snow accumulation, and 5/12/16 and 5/18/16 during snow ablation and snow loss. Previous retrieval of subpixel snow-covered area in alpine regions used multiple snow endmembers due to the sensitivity of snow spectral reflectance to grain size. We will present a model that analyzes multiple endmembers of varying snow grain size, vegetation, rock, and soil in segmented regions along the Sierra Nevada to determine snow-cover spatial extent, snow sub-pixel fraction and approximate grain size or melt state. The root mean squared error will provide a spectrum-wide assessment of the mixture model's goodness-of-fit. Analysis will compare snow-covered area and snow-cover depletion in the 2016 year, and annual variation from the 2015 year. Field data were also acquired on three days concurrent with the 2016 flights in the Sagehen Experimental Forest and will support ground validation of the airborne data set.

Domain-averaged snow depth over complex terrain from flat field measurements

NASA Astrophysics Data System (ADS)

Helbig, Nora; van Herwijnen, Alec

2017-04-01

Snow depth is an important parameter for a variety of coarse-scale models and applications, such as hydrological forecasting. Since high-resolution snow cover models are computational expensive, simplified snow models are often used. Ground measured snow depth at single stations provide a chance for snow depth data assimilation to improve coarse-scale model forecasts. Snow depth is however commonly recorded at so-called flat fields, often in large measurement networks. While these ground measurement networks provide a wealth of information, various studies questioned the representativity of such flat field snow depth measurements for the surrounding topography. We developed two parameterizations to compute domain-averaged snow depth for coarse model grid cells over complex topography using easy to derive topographic parameters. To derive the two parameterizations we performed a scale dependent analysis for domain sizes ranging from 50m to 3km using highly-resolved snow depth maps at the peak of winter from two distinct climatic regions in Switzerland and in the Spanish Pyrenees. The first, simpler parameterization uses a commonly applied linear lapse rate. For the second parameterization, we first removed the obvious elevation gradient in mean snow depth, which revealed an additional correlation with the subgrid sky view factor. We evaluated domain-averaged snow depth derived with both parameterizations using flat field measurements nearby with the domain-averaged highly-resolved snow depth. This revealed an overall improved performance for the parameterization combining a power law elevation trend scaled with the subgrid parameterized sky view factor. We therefore suggest the parameterization could be used to assimilate flat field snow depth into coarse-scale snow model frameworks in order to improve coarse-scale snow depth estimates over complex topography.

On the extraordinary snow on the sea ice off East Antarctica in late winter, 2012

NASA Astrophysics Data System (ADS)

Toyota, Takenobu; Massom, Robert; Lecomte, Olivier; Nomura, Daiki; Heil, Petra; Tamura, Takeshi; Fraser, Alexander D.

2016-09-01

In late winter-early spring 2012, the second Sea Ice Physics and Ecosystems Experiment (SIPEX II) was conducted off Wilkes Land, East Antarctica, onboard R/V Aurora Australis. The sea-ice conditions were characterized by significantly thick first-year ice and snow, trapping the ship for about 10 days in the near coastal region. The deep snow cover was particularly remarkable, in that its average value of 0.45 m was almost three times that observed between 1992 and 2007 in the region. To reveal factors responsible, we used in situ observations and ERA-Interim reanalysis (1990-2012) to examine the relative contribution of the different components of the local-regional snow mass balance equation i.e., snow accumulation on sea ice, precipitation minus evaporation (P-E), and loss by (i) snow-ice formation and (ii) entering into leads due to drifting snow. Results show no evidence for significantly high P-E in the winter of 2012. Ice core analysis has shown that although the snow-ice layer was relatively thin, indicating less transformation from snow to snow-ice in 2012 as compared to measurements from 2007, the difference was not enough to explain the extraordinarily deep snow. Based on these results, we deduce that lower loss of snow into leads was probably responsible for the extraordinary snow in 2012. Statistical analysis and satellite images suggest that the reduction in loss of snow into leads is attributed to rough ice surface associated with active deformation processes and larger floe size due to sea-ice expansion. This highlights the importance of snow-sea ice interaction in determining the mean snow depth on Antarctic sea ice.

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.

The application of ERTS imagery to mapping snow cover in the western United States. [Salt Verde in Arizona and Sierra Nevada California

NASA Technical Reports Server (NTRS)

Barnes, J. C. (Principal Investigator); Bowley, C. J.; Simmes, D. A.

1974-01-01

The author has identified the following significant results. In much of the western United States a large part of the utilized water comes from accumulated mountain snowpacks; thus, accurate measurements of snow distributions are required for input to streamflow prediction models. The application of ERTS-1 imagery for mapping snow has been evaluated for two geographic areas, the Salt-Verde watershed in central Arizona and the southern Sierra Nevada in California. Techniques have been developed to identify snow and to differentiate between snow and cloud. The snow extent for these two drainage areas has been mapped from the MSS-5 (0.6 - 0.7 microns) imagery and compared with aerial survey snow charts, aircraft photography, and ground-based snow measurements. The results indicate that ERTS imagery has substantial practical applications for snow mapping. Snow extent can be mapped from ERTS-1 imagery in more detail than is depicted on aerial survey snow charts. Moreover, in Arizona and southern California cloud obscuration does not appear to be a serious deterrent to the use of satellite data for snow survey. The costs involved in deriving snow maps from ERTS-1 imagery appear to be very reasonable in comparison with existing data collection methods.

Snow specific surface area simulation using the one-layer snow model in the Canadian LAnd Surface Scheme (CLASS)

NASA Astrophysics Data System (ADS)

Roy, A.; Royer, A.; Montpetit, B.; Bartlett, P. A.; Langlois, A.

2012-12-01

Snow grain size is a key parameter for modeling microwave snow emission properties and the surface energy balance because of its influence on the snow albedo, thermal conductivity and diffusivity. A model of the specific surface area (SSA) of snow was implemented in the one-layer snow model in the Canadian LAnd Surface Scheme (CLASS) version 3.4. This offline multilayer model (CLASS-SSA) simulates the decrease of SSA based on snow age, snow temperature and the temperature gradient under dry snow conditions, whereas it considers the liquid water content for wet snow metamorphism. We compare the model with ground-based measurements from several sites (alpine, Arctic and sub-Arctic) with different types of snow. The model provides simulated SSA in good agreement with measurements with an overall point-to-point comparison RMSE of 8.1 m2 kg-1, and a RMSE of 4.9 m2 kg-1 for the snowpack average SSA. The model, however, is limited under wet conditions due to the single-layer nature of the CLASS model, leading to a single liquid water content value for the whole snowpack. The SSA simulations are of great interest for satellite passive microwave brightness temperature assimilations, snow mass balance retrievals and surface energy balance calculations with associated climate feedbacks.

Long-term snow and weather observations at Weissfluhjoch and its relation to other high-altitude observatories in the Alps

NASA Astrophysics Data System (ADS)

Marty, Christoph; Meister, Roland

2012-12-01

Snow and weather observations at Weissfluhjoch were initiated in 1936, when a research team set a snow stake and started digging snow pits on a plateau located at 2,540 m asl above Davos, Switzerland. This was the beginning of what is now the longest series of daily snow depth, new snow height and bi-monthly snow water equivalent measurements from a high-altitude research station. Our investigations reveal that the snow depth at Weissfluhjoch with regard to the evolution and inter-annual variability represents a good proxy for the entire Swiss Alps. In order to set the snow and weather observations from Weissfluhjoch in a broader context, this paper also shows some comparisons with measurements from five other high-altitude observatories in the European Alps. The results show a surprisingly uniform warming of 0.8°C during the last three decades at the six investigated mountain stations. The long-term snow measurements reveal no change in mid-winter, but decreasing trends (especially since the 1980s) for the solid precipitation ratio, snow fall, snow water equivalent and snow depth during the melt season due to a strong temperature increase of 2.5°C in the spring and summer months of the last three decades.

Black carbon aerosol size in snow.

PubMed

Schwarz, J P; Gao, R S; Perring, A E; Spackman, J R; Fahey, D W

2013-01-01

The effect of anthropogenic black carbon (BC) aerosol on snow is of enduring interest due to its consequences for climate forcing. Until now, too little attention has been focused on BC's size in snow, an important parameter affecting BC light absorption in snow. Here we present first observations of this parameter, revealing that BC can be shifted to larger sizes in snow than are typically seen in the atmosphere, in part due to the processes associated with BC removal from the atmosphere. Mie theory analysis indicates a corresponding reduction in BC absorption in snow of 40%, making BC size in snow the dominant source of uncertainty in BC's absorption properties for calculations of BC's snow albedo climate forcing. The shift reduces estimated BC global mean snow forcing by 30%, and has scientific implications for our understanding of snow albedo and the processing of atmospheric BC aerosol in snowfall.

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.

Advances in Airborne Altimetric Techniques for the Measurement of Snow on Arctic Sea Ice

NASA Astrophysics Data System (ADS)

Newman, T.; Farrell, S. L.; Richter-Menge, J.; Elder, B. C.; Ruth, J.; Connor, L. N.

2014-12-01

Current sea ice observations and models indicate a transition towards a more seasonal Arctic ice pack with a smaller, and geographically more variable, multiyear ice component. To gain a comprehensive understanding of the processes governing this transition it is important to include the impact of the snow cover, determining the mechanisms by which snow is both responding to and forcing changes to the sea ice pack. Data from NASA's Operation IceBridge (OIB) snow radar system, which has been making yearly surveys of the western Arctic since 2009, offers a key resource for investigating the snow cover. In this work, we characterize the OIB snow radar instrument response to ascertain the location of 'side-lobes', aiding the interpretation of snow radar data. We apply novel wavelet-based techniques to identify the primary reflecting interfaces within the snow pack from which snow depth estimates are derived. We apply these techniques to the range of available snow radar data collected over the last 6 years during the NASA OIB mission. Our results are validated through comparison with a range of in-situ data. We discuss the impact of sea ice surface morphology on snow radar returns (with respect to ice type) and the topographic conditions over which accurate snow-radar-derived snow depths may be obtained. Finally we present improvements to in situ survey design that will allow for both an improved sampling of the snow radar footprint and more accurate assessment of the uncertainties in radar-derived snow depths in the future.

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.

White water: Fifty years of snow research in WRR and the outlook for the future

NASA Astrophysics Data System (ADS)

Sturm, Matthew

2015-07-01

Over the past 50 years, 239 papers related to snow have been published in Water Resources Research (WRR). Seminal papers on virtually every facet of snow physics and snow water resources have appeared in the journal. These include papers on drifting snow, the snow surface energy balance, the effect of grain size on albedo, chemical elution, water movement through snow, and canopy interception. In particular, papers in WRR have explored the distribution of snow across different landscapes, providing data, process knowledge, and the basis for virtually all of the distributed snow models in use today. In this paper, I review these key contributions and provide some personal thoughts on what is likely to be the focus and nature of papers published in the next few decades, a period that is likely to see an increasing ability to map snow cover in detail, which should serve as a basis for the further development and improvement of snow models. It will also be an uncertain future, with profound changes in snow climatology predicted. I expect WRR will continue to play a key role in documenting and understanding these important cryospheric changes.

Spring floods prediction with the use of optical satellite data in Québec

NASA Astrophysics Data System (ADS)

Roy, A.; Royer, A.; Turcotte, R.

2009-04-01

The Centre d'expertise hydrique du Québec (CEHQ) operates a distributed hydrological model, which integrates a snow model, for the management of dams in the south of Québec. It appears that the estimation of the water quantity of snowmelt in spring remains a variable with a large uncertainty and induces generally to an important error in stream flow simulation. Therefore, the National snow and ice center (NSIDC) produces, from MODIS (Moderate Resolution Imaging Spectroradiometer) data, continuous and homogeneous spatial snow cover (snow/swow-free) data on the whole territory, but with a cloud contamination. This research aims to improve the prediction of spring floods and the estimation of the rate of discharge by integrating snow cover data in the CEHQ's snow model. The study is done on two watersheds: du Nord river watershed (45,8°N) and Aux Écorces river watershed (47,9°N). The snow model used in the study (SPH-AV) is an implementation developed by the CEHQ of the snowmelt model of HYDROLTEL in is hydrological forecast system to simulate the melted water. The melted water estimated is then used as input in the empirical hydrological model MOHYSE to simulate stream flow. MODIS data are considered valid only when the cloud cover on each pixel of the watersheds is less then 30%. A pixel by pixel correction is applied to the snow pack when there is a difference between satellite snow cover and modeled snow cover. In the case of model shows to much snow, a factor is applied on temperatures by iterative process (starting from the last valid MODIS data) to melt the snow. In the opposite case, the snow quantity added to the last valid MODIS data is found by iterative process so that the pixel's snow water equivalent is equal to the nonzero neighbor minimum value. The study shows, through the simulations done on the two watersheds, the interest of the use of snow/snow-free product for the operational update of snow water equivalent with the objective to improve spring snowmelt stream flow simulations. The binary aspect (snow/snowfree) of the data is however a limit. Alternatives are discussed (passive microwave data). Keywords : satellite snow cover data, MODIS, satellite data integration, snow model, hydrological model, stream flow simulation, flood.

Effects of spatial and temporal resolution on simulated feedbacks from polygonal tundra.

NASA Astrophysics Data System (ADS)

Coon, E.; Atchley, A. L.; Painter, S. L.; Karra, S.; Moulton, J. D.; Wilson, C. J.; Liljedahl, A.

2014-12-01

Earth system land models typically resolve permafrost regions at spatial resolutions grossly larger than the scales of topographic variation. This observation leads to two critical questions: How much error is introduced by this lack of resolution, and what is the effect of this approximation on other coupled components of the Earth system, notably the energy balance and carbon cycle? Here we use the Arctic Terrestrial Simulator (ATS) to run micro-topography resolving simulations of polygonal ground, driven by meteorological data from Barrow, AK, to address these questions. ATS couples surface and subsurface processes, including thermal hydrology, surface energy balance, and a snow model. Comparisons are made between one-dimensional "column model" simulations (similar to, for instance, CLM or other land models typically used in Earth System models) and higher-dimensional simulations which resolve micro-topography, allowing for distributed surface runoff, horizontal flow in the subsurface, and uneven snow distribution. Additionally, we drive models with meteorological data averaged over different time scales from daily to weekly moving windows. In each case, we compare fluxes important to the surface energy balance including albedo, latent and sensible heat fluxes, and land-to-atmosphere long-wave radiation. Results indicate that spatial topography variation and temporal variability are important in several ways. Snow distribution greatly affects the surface energy balance, fundamentally changing the partitioning of incoming solar radiation between the subsurface and the atmosphere. This has significant effects on soil moisture and temperature, with implications for vegetation and decomposition. Resolving temporal variability is especially important in spring, when early warm days can alter the onset of snowmelt by days to weeks. We show that high-resolution simulations are valuable in evaluating current land models, especially in areas of polygonal ground. This work was supported by LANL Laboratory Directed Research and Development Project LDRD201200068DR and by the The Next-Generation Ecosystem Experiments (NGEE Arctic) project. NGEE-Arctic is supported by the Office of Biological and Environmental Research in the DOE Office of Science. LA-UR-14-26227.

Snow mechanics and avalanche formation: field experiments on the dynamic response of the snow cover

NASA Astrophysics Data System (ADS)

Schweizer, Jürg; Schneebeli, Martin; Fierz, Charles; Föhn, Paul M. B.

1995-11-01

Knowledge about snow mechanics and snow avalanche formation forms the basis of any hazard mitigation measures. The crucial point is the snow stability. The most relevant mechanical properties - the compressive, tensile and shear strength of the individual snow layers within the snow cover - vary substantially in space and time. Among other things the strength of the snow layers depends strongly on the state of stress and the strain rate. The evaluation of the stability of the snow cover is hence a difficult task involving many extrapolations. To gain insight in the release mechanism of slab avalanches triggered by skiers, the skier's impact is measured with a load cell at different depths within the snow cover and for different snow conditions. The study focused on the effects of the dynamic loading and of the damping by snow compaction. In accordance with earlier finite-element (FE) calculations the results show the importance of the depth of the weak layer or interface and the snow conditions, especially the sublayering. In order to directly measure the impact force and to study the snow properties in more detail, a new instrument, called rammrutsch was developed. It combines the properties of the rutschblock with the defined impact properties of the rammsonde. The mechanical properties are determined using (i) the impact energy of the rammrutsch and (ii) the deformations of the snow cover measured with accelerometers and digital image processing of video sequences. The new method is well suited to detect and to measure the mechanical processes and properties of the fracturing layers. The duration of one test is around 10 minutes and the method seems appropriate for determining the spatial variability of the snow cover. A series of experiments in a forest opening showed a clear difference in the snow stability between sites below trees and ones in the free field of the opening.

Next Generation Snow Cover Mapping: Can Future Hyperspectral Satellite Spectrometer Systems Improve Subpixel Snow-covered Area and Grain Size in the Sierra Nevada?

NASA Astrophysics Data System (ADS)

Hill, R.; Calvin, W. M.; Harpold, A.

2017-12-01

Mountain snow storage is the dominant source of water for humans and ecosystems in western North America. Consequently, the spatial distribution of snow-covered area is fundamental to both hydrological, ecological, and climate models. Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data were collected along the entire Sierra Nevada mountain range extending from north of Lake Tahoe to south of Mt. Whitney during the 2015 and 2016 snow-covered season. The AVIRIS dataset used in this experiment consists of 224 contiguous spectral channels with wavelengths ranging 400-2500 nanometers at a 15-meter spatial pixel size. Data from the Sierras were acquired on four days: 2/24/15 during a very low snow year, 3/24/16 near maximum snow accumulation, and 5/12/16 and 5/18/16 during snow ablation and snow loss. Building on previous retrieval of subpixel snow-covered area algorithms that take into account varying grain size we present a model that analyzes multiple endmembers of varying snow grain size, vegetation, rock, and soil in segmented regions along the Sierra Nevada to determine snow-cover spatial extent, snow sub-pixel fraction, and approximate grain size. In addition, varying simulated models of the data will compare and contrast the retrieval of current snow products such as MODIS Snow-Covered Area and Grain Size (MODSCAG) and the Airborne Space Observatory (ASO). Specifically, does lower spatial resolution (MODIS), broader resolution bandwidth (MODIS), and limited spectral resolution (ASO) affect snow-cover area and grain size approximations? The implications of our findings will help refine snow mapping products for planned hyperspectral satellite spectrometer systems such as EnMAP (slated to launch in 2019), HISUI (planned for inclusion on the International Space Station in 2018), and HyspIRI (currently under consideration).

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

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

Improving Snow Modeling by Assimilating Observational Data Collected by Citizen Scientists

NASA Astrophysics Data System (ADS)

Crumley, R. L.; Hill, D. F.; Arendt, A. A.; Wikstrom Jones, K.; Wolken, G. J.; Setiawan, L.

2017-12-01

Modeling seasonal snow pack in alpine environments includes a multiplicity of challenges caused by a lack of spatially extensive and temporally continuous observational datasets. This is partially due to the difficulty of collecting measurements in harsh, remote environments where extreme gradients in topography exist, accompanied by large model domains and inclement weather. Engaging snow enthusiasts, snow professionals, and community members to participate in the process of data collection may address some of these challenges. In this study, we use SnowModel to estimate seasonal snow water equivalence (SWE) in the Thompson Pass region of Alaska while incorporating snow depth measurements collected by citizen scientists. We develop a modeling approach to assimilate hundreds of snow depth measurements from participants in the Community Snow Observations (CSO) project (www.communitysnowobs.org). The CSO project includes a mobile application where participants record and submit geo-located snow depth measurements while working and recreating in the study area. These snow depth measurements are randomly located within the model grid at irregular time intervals over the span of four months in the 2017 water year. This snow depth observation dataset is converted into a SWE dataset by employing an empirically-based, bulk density and SWE estimation method. We then assimilate this data using SnowAssim, a sub-model within SnowModel, to constrain the SWE output by the observed data. Multiple model runs are designed to represent an array of output scenarios during the assimilation process. An effort to present model output uncertainties is included, as well as quantification of the pre- and post-assimilation divergence in modeled SWE. Early results reveal pre-assimilation SWE estimations are consistently greater than the post-assimilation estimations, and the magnitude of divergence increases throughout the snow pack evolution period. This research has implications beyond the Alaskan context because it increases our ability to constrain snow modeling outputs by making use of snow measurements collected by non-expert, citizen scientists.

Experimental and model based investigation of the links between snow bidirectional reflectance and snow microstructure

NASA Astrophysics Data System (ADS)

Dumont, M.; Flin, F.; Malinka, A.; Brissaud, O.; Hagenmuller, P.; Dufour, A.; Lapalus, P.; Lesaffre, B.; Calonne, N.; Rolland du Roscoat, S.; Ando, E.

2017-12-01

Snow optical properties are unique among Earth surface and crucial for a wide range of applications. The bi-directional reflectance, hereafter BRDF, of snow is sensible to snow microstructure. However the complex interplays between different parameters of snow microstructure namely size parameters and shape parameters on reflectance are challenging to disentangle both theoretically and experimentally. An accurate understanding and modelling of snow BRDF is required to correctly process satellite data. BRDF measurements might also provide means of characterizing snow morphology. This study presents one of the very few dataset that combined bi-directional reflectance measurements over 500-2500 nm and X-ray tomography of the snow microstructure for three different snow samples and two snow types. The dataset is used to evaluate the approach from Malinka, 2014 that relates snow optical properties to the chord length distribution in the snow microstructure. For low and medium absorption, the model accurately reproduces the measurements but tends to slightly overestimate the anisotropy of the reflectance. The model indicates that the deviation of the ice chord length distribution from an exponential distribution, that can be understood as a characterization of snow types, does not impact the reflectance for such absorptions. The simulations are also impacted by the uncertainties in the ice refractive index values. At high absorption and high viewing/incident zenith angle, the simulations and the measurements disagree indicating that some of the assumptions made in the model are not met anymore. The study also indicates that crystal habits might play a significant role for the reflectance under such geometries and wavelengths. However quantitative relationship between crystal habits and reflectance alongside with potential optical methodologies to classify snow morphology would require an extended dataset over more snow types. This extended dataset can likely be obtained thanks to the use of ray tracing models on tomography images of the snow microstructure.

Bacterial Trapping in Porous Media Flows

NASA Astrophysics Data System (ADS)

Dehkharghani, Amin; Waisbord, Nicolas; Dunkel, Jörn; Guasto, Jeffrey

2016-11-01

Swimming bacteria inhabit heterogeneous, microstructured environments that are often characterized by complex, ambient flows. Understanding the physical mechanisms underlying cell transport in these systems is key to controlling important processes such as bioremediation in porous soils and infections in human tissues. We study the transport of swimming bacteria (Bacillus subtilis) in quasi-two-dimensional porous microfluidic channels with a range of periodic microstructures and flow strengths. Measured cell trajectories and the local cell number density reveal the formation of filamentous cell concentration patterns within the porous structures. The local cell densification is maximized at shear rates in the range 1-10 s-1, but widely varies with pore geometry and flow topology. Experimental observations are complemented by Langevin simulations to demonstrate that the filamentous patterns result from a coupling of bacterial motility to the complex flow fields via Jeffery orbits, which effectively 'trap' the bacteria on streamlines. The resulting microscopic heterogeneity observed here suppresses bacterial transport and likely has implications for both mixing and cell nutrient uptake in porous media flows. NSF CBET-1511340.

Final test results for the ground operations demonstration unit for liquid hydrogen

NASA Astrophysics Data System (ADS)

Notardonato, W. U.; Swanger, A. M.; Fesmire, J. E.; Jumper, K. M.; Johnson, W. L.; Tomsik, T. M.

2017-12-01

Described herein is a comprehensive project-a large-scale test of an integrated refrigeration and storage system called the Ground Operations and Demonstration Unit for Liquid Hydrogen (GODU LH2), sponsored by the Advanced Exploration Systems Program and constructed at Kennedy Space Center. A commercial cryogenic refrigerator interfaced with a 125,000 l liquid hydrogen tank and auxiliary systems in a manner that enabled control of the propellant state by extracting heat via a closed loop Brayton cycle refrigerator coupled to a novel internal heat exchanger. Three primary objectives were demonstrating zero-loss storage and transfer, gaseous liquefaction, and propellant densification. Testing was performed at three different liquid hydrogen fill-levels. Data were collected on tank pressure, internal tank temperature profiles, mass flow in and out of the system, and refrigeration system performance. All test objectives were successfully achieved during approximately two years of testing. A summary of the final results is presented in this paper.

Time-dependent crashworthiness of polyurethane foam

NASA Astrophysics Data System (ADS)

Basit, Munshi Mahbubul; Cheon, Seong Sik

2018-05-01

Time-dependent stress-strain relationship as well as crashworthiness of polyurethane foam was investigated under constant impact energy with different velocities, considering inertia and strain-rate effects simultaneously during the impact testing. Even though the impact energies were same, the percentage in increase in densification strain due to higher impact velocities was found, which yielded the wider plateau region, i.e. growth in crashworthiness. This phenomenon is analyzed by the microstructure of polyurethane foam obtained from scanning electron microscopy. The equations, coupled with the Sherwood-Frost model and the impulse-momentum theory, were employed to build the constitutive equation of the polyurethane foam and calculate energy absorption capacity of the foam. The nominal stress-strain curves obtained from the constitutive equation were compared with results from impact tests and were found to be in good agreement. This study is dedicated to guiding designer use polyurethane foam in crashworthiness structures such as an automotive bumper system by providing crashworthiness data, determining the crush mode, and addressing a mathematical model of the crashworthiness.

BISON Theory Manual The Equations behind Nuclear Fuel Analysis

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

Hales, J. D.; Williamson, R. L.; Novascone, S. R.

2016-09-01

BISON is a finite element-based nuclear fuel performance code applicable to a variety of fuel forms including light water reactor fuel rods, TRISO particle fuel, and metallic rod and plate fuel. It solves the fully-coupled equations of thermomechanics and species diffusion, for either 2D axisymmetric or 3D geometries. Fuel models are included to describe temperature and burnup dependent thermal properties, fission product swelling, densification, thermal and irradiation creep, fracture, and fission gas production and release. Plasticity, irradiation growth, and thermal and irradiation creep models are implemented for clad materials. Models are also available to simulate gap heat transfer, mechanical contact,more » and the evolution of the gap/plenum pressure with plenum volume, gas temperature, and fission gas addition. BISON is based on the MOOSE framework and can therefore efficiently solve problems using standard workstations or very large high-performance computers. This document describes the theoretical and numerical foundations of BISON.« less

Measurement of snow depth distribution in the Kamikochi-Azusa river basin using an airborne laser scanning

NASA Astrophysics Data System (ADS)

Suzuki, K.; Sasaki, A.

2013-12-01

In the Japanese Alps region, large amounts of precipitation in the form of snow constitute a more important water resource than rain. During the winter, precipitation that is deposited as snowfall accumulates in the river basins, and it forms natural dams known as 'white dams.' A quantitative understanding of snow depth distribution in these mountainous areas is important not only for evaluating water resource volume, but also for understanding the effects of snow in terms of its impact on landforms and its effect on the distribution of vegetation. However, it is not easy to perform a quantitative evaluation of snow depth distribution in mountainous areas. Several methods have been proposed for clarifying snow depth distribution. The most widely used of these is a method of inserting a sounding rod into the snow to measure its depth at each geographic position. Another method is to dig a trench in the snow and then perform an observational measurement of the side of the trench. These methods enable accurate measurement of the snow depth; however, when the snow is several meters deep, the methods may be limited by the measuring capacity of the equipment, or by the time restrictions of the survey. For these reasons, wide area measurement of the spatial distribution of snow is very difficult, and it is not suitable for investigating snow depth distribution in river basins. There is a method of using ultrasonics or radar to measure the depth of snow and to make observations of snow depth at certain positions. This method offers high measurement precision and high time resolution at the observation points. However, for observations in areas of very deep snow, it becomes technically difficult to install the equipment, and it is difficult to make a large number of installations to cover a wide area. There are also methods of indirectly measuring snow depth. One of these is to use aerial photographs taken when there is no snow cover and when there is snow cover, draw contour lines, and then use the difference between them to clarify the snow depth. This method allows researchers to grasp the snow depth over a wide area, but it needs to be made more precise if it is to incorporate high-precision information on equivalent elevation points on the snow surface. In recent years, a measurement technology has been developed that uses laser scanners mounted on aircraft. This method enables researchers to obtain ground surface coordinate data with high precision over a wide area from the air. Using such a scanner to measure the ground surface during snow coverage and during no snow coverage, and then finding the differences between the surface elevations, has made it possible to ascertain snow depth with high precision. Airborne laser measurement enables high-precision measurements over a wide area and in a short amount of time, and measurements can be made regardless of geographical factors such as sloping ground. As such, it enables measurement of snow depth distribution over a wide area without having to worry about the undulations of the land. In this study, airborne laser scanning was carried out on the snow surface in the upstream region of the Kamikochi-Azusa River in Japan on March 29, 2012, in order to clarify the snow depth distribution.

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.

Seasonal Snow Extent and Snow Mass in South America using SMMR and SSM/I Passive Microwave Data (1979-2006)

NASA Technical Reports Server (NTRS)

Foster, J. L.; Hall, D. K.; Kelly, R. E. J.; Chiu, L.

2008-01-01

Seasonal snow cover in South America was examined in this study using passive microwave satellite data from the Scanning Multichannel Microwave Radiometer (SMMR) on board the Nimbus-7 satellite and the Special Sensor Microwave Imagers (SSM/I) onboard Defense Meteorological Satellite Program (DMSP) satellites. For the period from 1979-2006, both snow cover extent and snow water equivalent (snow mass) were investigated during the coldest months (May-September), primarily in the Patagonia area of Argentina and in the Andes of Chile, Argentina and Bolivia, where most of the seasonal snow is found. Since winter temperatures in this region are often above freezing, the coldest winter month was found to be the month having the most extensive snow cover and usually the month having the deepest snow cover as well. Sharp year-to-year differences were recorded using the passive microwave observations. The average snow cover extent for July, the month with the greatest average extent during the 28-year period of record, is 321,674 km(exp 2). In July of 1984, the average monthly snow cover extent was 701,250 km(exp 2) the most extensive coverage observed between 1979 and 2006. However, in July of 1989, snow cover extent was only 120,000 km(exp 2). The 28-year period of record shows a sinusoidal like pattern for both snow cover and snow mass, though neither trend is significant at the 95% level.

Fabrication of Titanium-Niobium-Zirconium-Tantalium Alloy (TNZT) Bioimplant Components with Controllable Porosity by Spark Plasma Sintering

PubMed Central

Rechtin, Jack; Torresani, Elisa; Ivanov, Eugene; Olevsky, Eugene

2018-01-01

Spark Plasma Sintering (SPS) is used to fabricate Titanium-Niobium-Zirconium-Tantalum alloy (TNZT) powder—based bioimplant components with controllable porosity. The developed densification maps show the effects of final SPS temperature, pressure, holding time, and initial particle size on final sample relative density. Correlations between the final sample density and mechanical properties of the fabricated TNZT components are also investigated and microstructural analysis of the processed material is conducted. A densification model is proposed and used to calculate the TNZT alloy creep activation energy. The obtained experimental data can be utilized for the optimized fabrication of TNZT components with specific microstructural and mechanical properties suitable for biomedical applications. PMID:29364165

Realization of ETRF2000 as a New Terrestrial Reference Frame in Republic of Serbia

NASA Astrophysics Data System (ADS)

Blagojevic, D.; Vasilic, V.

2012-12-01

The International Earth Rotation and Reference Systems Service (IERS) is a joint service of the International Association of Geodesy (IAG) and the International Astronomical Union (IAU), which provides the scientific community with the means for computing the transformation from the International Celestial Reference System (ICRS) to the International Terrestrial Reference System (ITRS). It further maintains the realizations of these systems by appropriate coordinate sets called "frames". The densification of terrestrial frame usually serves as official frame for positioning and navigation tasks within the territory of particular country. One of these densifications was recently performed in order to establish new reference frame for Republic of Serbia. The paper describes related activities resulting in ETRF2000 as a new Serbian terrestrial reference frame.

Consolidation of Si3N4 without additives (by hot isostatic pressing)

NASA Technical Reports Server (NTRS)

Yeh, H. C.

1983-01-01

The potential of using hot isostatic pressing (HIP'ing) technique to produce dense silicon nitride materials without or with a reduced amount of additives (much less than 5 w/o) was investigated. Hot isostatic pressing technique can provide higher pressure and temperature than hot pressing can, thus has the potential of requiring less densification aids to consolidate Si3N4 materials. It was anticipated that if such dense materials could be fabricated, the high temperature strength of the material should be improved significantly. Observations on the phase transformation, densification behavior, and microstructures of the samples are also documented. Density, microhardness, four point bend strength (room temperature and 1370 C) were measured on selected densified materials.

Controllable film densification and interface flatness for high-performance amorphous indium oxide based thin film transistors

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

Ou-Yang, Wei, E-mail: OUYANG.Wei@nims.go.jp, E-mail: TSUKAGOSHI.Kazuhito@nims.go.jp; Mitoma, Nobuhiko; Kizu, Takio

2014-10-20

To avoid the problem of air sensitive and wet-etched Zn and/or Ga contained amorphous oxide transistors, we propose an alternative amorphous semiconductor of indium silicon tungsten oxide as the channel material for thin film transistors. In this study, we employ the material to reveal the relation between the active thin film and the transistor performance with aid of x-ray reflectivity study. By adjusting the pre-annealing temperature, we find that the film densification and interface flatness between the film and gate insulator are crucial for achieving controllable high-performance transistors. The material and findings in the study are believed helpful for realizingmore » controllable high-performance stable transistors.« less

Snow Water Equivalent estimation based on satellite observation

NASA Astrophysics Data System (ADS)

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

2009-09-01

The availability of remotely sensed images and them analysis is a powerful tool for monitoring the extension and typology of snow cover over territory where the in situ measurements are often difficult. Information on snow are fundamental for monitoring and forecasting the available water above all in regions at mid latitudes as Mediterranean where snowmelt may cause floods. The hydrological model requirements and the daily acquisitions of MODIS (Moderate Resolution Imaging Spectroradiometer), drove, in previous research activities, to the development of a method to automatically map the snow cover from multi-spectral images. But, the major hydrological parameter related to the snow pack is the Snow Water Equivalent (SWE). This represents a direct measure of stored water in the basin. Because of it, the work was focused to the daily estimation of SWE from MODIS images. But, the complexity of this aim, based only on optical data, doesn’t find any information in literature. Since, from the spectral range of MODIS data it is not possible to extract a direct relation between spectral information and the SWE. Then a new method, respectful of the physic of the snow, was defined and developed. Reminding that the snow water equivalent is the product of the three factors as snow density, snow depth and the snow covered areas, the proposed approach works separately on each of these physical behaviors. Referring to the physical characteristic of snow, the snow density is function of the snow age, then it was studied a new method to evaluate this. Where, a module for snow age simulation from albedo information was developed. It activates an age counter updated by new snow information set to estimate snow age from zero accumulation status to the end of melting season. The height of the snow pack, can be retrieved by adopting relation between vegetation and snow depth distributions. This computes snow height distribution by the relation between snow cover fraction and the forest canopy density. Finally, the SWE has to be calculated for the snow covered areas, detected by means of a previously developed decision tree classifier able to classify snow cover by self selecting rules in a statistically optimum way. The advantages introduced from this work are many. Firstly, applying a suitable method with data features, it is possible to automatically obtain snow cover description with high frequency. Moreover, the advantages of the modularity in the proposed approach allows to improve the three factors estimation in an independent way. Limitations lie into clouds problem that affects results by obscuring the observed territory, that is bounded by fusing temporal and spatial information. Then the spatial resolution of data, satisfactory with the scale of hydrological models, mismatch with the available in situ point information, causing difficulties for a method validation or calibration. However this working flow results computationally cost-effectiveness, robust to the radiometric noise of the original data, provides spatially extended and frequent information.