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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

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.

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.

On the Impact of Snow Salinity on CryoSat-2 First-Year Sea Ice Thickness Retrievals

NASA Astrophysics Data System (ADS)

Nandan, V.; Yackel, J.; Geldsetzer, T.; Mahmud, M.

2017-12-01

European Space Agency's Ku-band altimeter CryoSat-2 (CS-2) has demonstrated its potential to provide extensive basin-scale spatial and temporal measurements of Arctic sea ice freeboard. It is assumed that CS-2 altimetric returns originate from the snow/sea ice interface (assumed to be the main scattering horizon). However, in newly formed thin ice ( 0.6 m) through to thick first-year sea ice (FYI) ( 2 m), upward wicking of brine into the snow cover from the underlying sea ice surface produces saline snow layers, especially in the bottom 6-8 cm of a snow cover. This in turn modifies the brine volume at/or near the snow/sea ice interface, altering the dielectric and scattering properties of the snow cover, leading to strong Ku-band microwave attenuation within the upper snow volume. Such significant reductions in Ku-band penetration may substantially affect CS-2 FYI freeboard retrievals. Therefore, the goal of this study is to evaluate a theoretical approach to estimate snow salinity induced uncertainty on CS-2 Arctic FYI freeboard measurements. Using the freeboard-to-thickness hydrostatic equilibrium equation, we quantify the error differences between the CS-2 FYI thickness, (assuming complete penetration of CS-2 radar signals to the snow/FYI interface), and the FYI thickness based on the modeled Ku-band main scattering horizon for different snow cover cases. We utilized naturally occurring saline and non-saline snow cover cases ranging between 6 cm to 32 cm from the Canadian Arctic, observed during late-winter from 1993 to 2017, on newly-formed ice ( 0.6 m), medium ( 1.5 m) and thick FYI ( 2 m). Our results suggest that irrespective of the thickness of the snow cover overlaying FYI, the thickness of brine-wetted snow layers and actual FYI freeboard strongly influence the amount with which CS-2 FYI freeboard estimates and thus thickness calculations are overestimated. This effect is accentuated for increasingly thicker saline snow covers overlaying newly-formed ice, which accounted to an overestimated FYI thickness by 250%, when compared to 80% overestimations on thinner saline snow covers, and the error reduces with increase in FYI thickness. Our study recommends the CS-2 sea ice community to add snow salinity as a potential error source, affecting CS-2 Arctic FYI freeboard and thickness retrievals.

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

Light scattering measurement of sodium polyacrylate products

NASA Astrophysics Data System (ADS)

Lama, Nisha; Norwood, David; Boone, Steven; Massie-Boyer, Valerie

2015-03-01

In the presentation, we will describe the use of a multi-detector HPLC incorporating the DAWN EOS multi-angle laser light scattering (MALLS) detector to measure the properties such as molecular weight, RMS radius, contour and persistence length and polydispersity of sodium polyacrylate products. The samples of sodium polyacrylate are used in various industries as thickening agents, coating dispersants, artificial snow, laundry detergent and disposable diapers. Data and results obtained from the experiment will be presented.

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 R.; Lambert, Kevin M.; Miranda, Felix A.

2015-01-01

This poster describes the implementation of a 6x6 element, dual linear polarized array with beamformer that operates from about 8-40 GHz. It is implemented using a relatively new multi-layer microfabrication process. The beamformer includes baluns that feed dual-polarized differential antenna elements and reactive splitters that cover the full frequency range of operation. This fixed beam array (FBA) serves as the feed for a multi-band instrument designed to measure snow water equivalent (SWE) from an airborne platform known as the Wideband Instrument for Snow Measurements (WISM).

The effects of layers in dry snow on its passive microwave emissions using dense media radiative transfer theory based on the quasicrystalline approximation (QCA/DMRT)

USGS Publications Warehouse

Liang, D.; Xu, X.; Tsang, L.; Andreadis, K.M.; Josberger, E.G.

2008-01-01

A model for the microwave emissions of multilayer dry snowpacks, based on dense media radiative transfer (DMRT) theory with the quasicrystalline approximation (QCA), provides more accurate results when compared to emissions determined by a homogeneous snowpack and other scattering models. The DMRT model accounts for adhesive aggregate effects, which leads to dense media Mie scattering by using a sticky particle model. With the multilayer model, we examined both the frequency and polarization dependence of brightness temperatures (Tb's) from representative snowpacks and compared them to results from a single-layer model and found that the multilayer model predicts higher polarization differences, twice as much, and weaker frequency dependence. We also studied the temporal evolution of Tb from multilayer snowpacks. The difference between Tb's at 18.7 and 36.5 GHz can be S K lower than the single-layer model prediction in this paper. By using the snowpack observations from the Cold Land Processes Field Experiment as input for both multi- and single-layer models, it shows that the multilayer Tb's are in better agreement with the data than the single-layer model. With one set of physical parameters, the multilayer QCA/DMRT model matched all four channels of Tb observations simultaneously, whereas the single-layer model could only reproduce vertically polarized Tb's. Also, the polarization difference and frequency dependence were accurately matched by the multilayer model using the same set of physical parameters. Hence, algorithms for the retrieval of snowpack depth or water equivalent should be based on multilayer scattering models to achieve greater accuracy. ?? 2008 IEEE.

The DMRT-ML Model: Numerical Simulations of the Microwave Emission of Snowpacks Based on the Dense Media Radiative Transfer Theory

NASA Technical Reports Server (NTRS)

Picard, Ghislain; Brucker, Ludovic; Roy, Alexandre; DuPont, FLorent; Champollion, Nicolas; Morin, Samuel

2014-01-01

Microwave radiometer observations have been used to retrieve snow depth and snow water equivalent on both land and sea ice, snow accumulation on ice sheets, melt events, snow temperature, and snow grain size. Modeling the microwave emission from snow and ice physical properties is crucial to improve the quality of these retrievals. It also is crucial to improve our understanding of the radiative transfer processes within the snow cover, and the snow properties most relevant in microwave remote sensing. Our objective is to present a recent microwave emission model and its validation. The model is named DMRT-ML (DMRT Multi-Layer).

Unusual radar echoes from the Greenland ice sheet

NASA Technical Reports Server (NTRS)

Rignot, E. J.; Vanzyl, J. J.; Ostro, S. J.; Jezek, K. C.

1993-01-01

In June 1991, the NASA/Jet Propulsion Laboratory airborne synthetic-aperture radar (AIRSAR) instrument collected the first calibrated data set of multifrequency, polarimetric, radar observations of the Greenland ice sheet. At the time of the AIRSAR overflight, ground teams recorded the snow and firn (old snow) stratigraphy, grain size, density, and temperature at ice camps in three of the four snow zones identified by glaciologists to characterize four different degrees of summer melting of the Greenland ice sheet. The four snow zones are: (1) the dry-snow zone, at high elevation, where melting rarely occurs; (2) the percolation zone, where summer melting generates water that percolates down through the cold, porous, dry snow and then refreezes in place to form massive layers and pipes of solid ice; (3) the soaked-snow zone where melting saturates the snow with liquid water and forms standing lakes; and (4) the ablation zone, at the lowest elevations, where melting is vigorous enough to remove the seasonal snow cover and ablate the glacier ice. There is interest in mapping the spatial extent and temporal variability of these different snow zones repeatedly by using remote sensing techniques. The objectives of the 1991 experiment were to study changes in radar scattering properties across the different melting zones of the Greenland ice sheet, and relate the radar properties of the ice sheet to the snow and firn physical properties via relevant scattering mechanisms. Here, we present an analysis of the unusual radar echoes measured from the percolation zone.

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

USGS Publications Warehouse

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

2008-01-01

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

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.

Snow Radar Derived Surface Elevations and Snow Depths Multi-Year Time Series over Greenland Sea-Ice During IceBridge Campaigns

NASA Astrophysics Data System (ADS)

Perkovic-Martin, D.; Johnson, M. P.; Holt, B.; Panzer, B.; Leuschen, C.

2012-12-01

This paper presents estimates of snow depth over sea ice from the 2009 through 2011 NASA Operation IceBridge [1] spring campaigns over Greenland and the Arctic Ocean, derived from Kansas University's wideband Snow Radar [2] over annually repeated sea-ice transects. We compare the estimates of the top surface interface heights between NASA's Atmospheric Topographic Mapper (ATM) [3] and the Snow Radar. We follow this by comparison of multi-year snow depth records over repeated sea-ice transects to derive snow depth changes over the area. For the purpose of this paper our analysis will concentrate on flights over North/South basin transects off Greenland, which are the closest overlapping tracks over this time period. The Snow Radar backscatter returns allow for surface and interface layer types to be differentiated between snow, ice, land and water using a tracking and classification algorithm developed and discussed in the paper. The classification is possible due to different scattering properties of surfaces and volumes at the radar's operating frequencies (2-6.5 GHz), as well as the geometries in which they are viewed by the radar. These properties allow the returns to be classified by a set of features that can be used to identify the type of the surface or interfaces preset in each vertical profile. We applied a Support Vector Machine (SVM) learning algorithm [4] to the Snow Radar data to classify each detected interface into one of four types. The SVM algorithm was trained on radar echograms whose interfaces were visually classified and verified against coincident aircraft data obtained by CAMBOT [5] and DMS [6] imaging sensors as well as the scanning ATM lidar. Once the interface locations were detected for each vertical profile we derived a range to each interface that was used to estimate the heights above the WGS84 ellipsoid for direct comparisons with ATM. Snow Radar measurements were calibrated against ATM data over areas free of snow cover and over GPS land surveyed areas of Thule and Sondrestrom air bases. The radar measurements were compared against the ATM and the GPS measurements that were located in the estimated radar footprints, which resulted in an overall error of ~ 0.3 m between the radar and ATM. The agreement between ATM and GPS survey is within +/- 0.1 m. References: [1] http://www.nasa.gov/mission_pages/icebridge/ [2] Panzer, B. et. al, "An ultra-wideband, microwave radar for measuring snow thickness on sea ice and mapping near-surface internal layers in polar firn," Submitted to J. of Glaciology Instr. and Tech., July 23, 2012. [3] Krabill, William B. 2009 and 2011, updated current year. IceBridge ATM L1B Qfit Elevation and Return Strength. Boulder, Colorado USA: National Snow and Ice Data Center. Digital media. [4] Chih-Chung Chang and Chih-Jen Lin. "Libsvm: a library for support vector machines", ACM Transactions on Intelligent Systems and Technology, 2:2:27:1-27:27, 2011. [5] Krabill, William B. 2009 and 2011, updated current year. IceBridge CAMBOT L1B Geolocated Images, [2009-04-25, 2011-04-15]. Boulder, Colorado USA: National Snow and Ice Data Center. Digital media. [6] Dominguez, Roseanne. 2011, updated current year. IceBridge DMS L1B Geolocated and Orthorectified Images. Boulder, Colorado USA: National Snow and Ice Data Center. Digital media

Simulation of Seasonal Snow Microwave TB Using Coupled Multi-Layered Snow Evolution and Microwave Emission Models

NASA Technical Reports Server (NTRS)

Brucker, Ludovic; Royer, Alain; Picard, Ghislain; Langlois, Alex; Fily, Michel

2014-01-01

The accurate quantification of SWE has important societal benefits, including improving domestic and agricultural water planning, flood forecasting and electric power generation. However, passive-microwave SWE algorithms suffer from variations in TB due to snow metamorphism, difficult to distinguish from those due to SWE variations. Coupled snow evolution-emission models are able to predict snow metamorphism, allowing us to account for emissivity changes. They can also be used to identify weaknesses in the snow evolution model. Moreover, thoroughly evaluating coupled models is a contribution toward the assimilation of TB, which leads to a significant increase in the accuracy of SWE estimates.

Laboratory-based observations of capillary barriers and preferential flow in layered snow

NASA Astrophysics Data System (ADS)

Avanzi, F.; Hirashima, H.; Yamaguchi, S.; Katsushima, T.; De Michele, C.

2015-12-01

Several evidences are nowadays available that show how the effects of capillary gradients and preferential flow on water transmission in snow may play a more important role than expected. To observe these processes and to contribute in their characterization, we performed observations on the development of capillary barriers and preferential flow patterns in layered snow during cold laboratory experiments. We considered three different layering (all characterized by a finer-over-coarser texture in grain size) and three different water input rates. Nine samples of layered snow were sieved in a cold laboratory, and subjected to a constant supply of dyed tracer. By means of visual inspection, horizontal sectioning and liquid water content measurements, the processes of ponding and preferential flow were characterized as a function of texture and water input rate. The dynamics of each sample were replicated using the multi-layer physically-based SNOWPACK model. Results show that capillary barriers and preferential flow are relevant processes ruling the speed of liquid water in stratified snow. Ponding is associated with peaks in LWC at the boundary between the two layers equal to ~ 33-36 vol. % when the upper layer is composed by fine snow (grain size smaller than 0.5 mm). The thickness of the ponding layer at the textural boundary is between 0 and 3 cm, depending on sample stratigraphy. Heterogeneity in water transmission increases with grain size, while we do not observe any clear dependency on water input rate. The extensive comparison between observed and simulated LWC profiles by SNOWPACK (using an approximation of Richards Equation) shows high performances by the model in estimating the LWC peak over the boundary, while water speed in snow is underestimated by the chosen water transport scheme.

The DMRT-ML Model: Numerical Simulations of the Microwave Emission of Snowpacks Based on the Dense Media Radiative Transfer Theory

NASA Technical Reports Server (NTRS)

Brucker, Ludovic; Picard, Ghislain; Roy, Alexandre; Dupont, Florent; Fily, Michel; Royer, Alain

2014-01-01

Microwave radiometer observations have been used to retrieve snow depth and snow water equivalent on both land and sea ice, snow accumulation on ice sheets, melt events, snow temperature, and snow grain size. Modeling the microwave emission from snow and ice physical properties is crucial to improve the quality of these retrievals. It also is crucial to improve our understanding of the radiative transfer processes within the snow cover, and the snow properties most relevant in microwave remote sensing. Our objective is to present a recent microwave emission model and its validation. The model is named DMRT-ML (DMRT Multi-Layer), and is available at http:lgge.osug.frpicarddmrtml.

A novel linear physical model for remote sensing of snow wetness and snow density using the visible and infrared bands

NASA Astrophysics Data System (ADS)

Varade, D. M.; Dikshit, O.

2017-12-01

Modeling and forecasting of snowmelt runoff are significant for understanding the hydrological processes in the cryosphere which requires timely information regarding snow physical properties such as liquid water content and density of snow in the topmost layer of the snowpack. Both the seasonal runoffs and avalanche forecasting are vastly dependent on the inherent physical characteristics of the snowpack which are conventionally measured by field surveys in difficult terrains at larger impending costs and manpower. With advances in remote sensing technology and the increase in the availability of satellite data, the frequency and extent of these surveys could see a declining trend in future. In this study, we present a novel approach for estimating snow wetness and snow density using visible and infrared bands that are available with most multi-spectral sensors. We define a trapezoidal feature space based on the spectral reflectance in the near infrared band and the Normalized Differenced Snow Index (NDSI), referred to as NIR-NDSI space, where dry snow and wet snow are observed in the left diagonal upper and lower right corners, respectively. The corresponding pixels are extracted by approximating the dry and wet edges which are used to develop a linear physical model to estimate snow wetness. Snow density is then estimated using the modeled snow wetness. Although the proposed approach has used Sentinel-2 data, it can be extended to incorporate data from other multi-spectral sensors. The estimated values for snow wetness and snow density show a high correlation with respect to in-situ measurements. The proposed model opens a new avenue for remote sensing of snow physical properties using multi-spectral data, which were limited in the literature.

Snow particles extracted from X-ray computed microtomography imagery and their single-scattering properties

NASA Astrophysics Data System (ADS)

Ishimoto, Hiroshi; Adachi, Satoru; Yamaguchi, Satoru; Tanikawa, Tomonori; Aoki, Teruo; Masuda, Kazuhiko

2018-04-01

Sizes and shapes of snow particles were determined from X-ray computed microtomography (micro-CT) images, and their single-scattering properties were calculated at visible and near-infrared wavelengths using a Geometrical Optics Method (GOM). We analyzed seven snow samples including fresh and aged artificial snow and natural snow obtained from field samples. Individual snow particles were numerically extracted, and the shape of each snow particle was defined by applying a rendering method. The size distribution and specific surface area distribution were estimated from the geometrical properties of the snow particles, and an effective particle radius was derived for each snow sample. The GOM calculations at wavelengths of 0.532 and 1.242 μm revealed that the realistic snow particles had similar scattering phase functions as those of previously modeled irregular shaped particles. Furthermore, distinct dendritic particles had a characteristic scattering phase function and asymmetry factor. The single-scattering properties of particles of effective radius reff were compared with the size-averaged single-scattering properties. We found that the particles of reff could be used as representative particles for calculating the average single-scattering properties of the snow. Furthermore, the single-scattering properties of the micro-CT particles were compared to those of particle shape models using our current snow retrieval algorithm. For the single-scattering phase function, the results of the micro-CT particles were consistent with those of a conceptual two-shape model. However, the particle size dependence differed for the single-scattering albedo and asymmetry factor.

35 GHz Measurements of CO2 Crystals for Simulating Observations of the Martian Polar Caps

NASA Technical Reports Server (NTRS)

Foster, J. L.; Chang, A. T. C.; Hall, D. K.; Tait, A. B.; Barton, J. S.

1998-01-01

In order to learn more about the Martian polar caps, it is important to compare and contrast the behavior of both frozen H2O and CO2 in different parts of the electromagnetic spectrum. Relatively little attention has been given, thus far, to observing the thermal microwave part of the spectrum. In this experiment, passive microwave radiation emanating from within a 33 cm snowpack was measured with a 35 GHz hand-held radiometer, and in addition to the natural snow measurements, the radiometer was used to measure the microwave emission and scattering from layers of manufactured CO2 (dry ice). A 1 m x 2 m plate of aluminum sheet metal was positioned beneath the natural snow so that microwave emissions from the underlying soil layers would be minimized. Compared to the natural snow crystals, results for the dry ice layers exhibit lower' microwave brightness temperatures for similar thicknesses, regardless of the incidence angle of the radiometer. For example, at 50 degree H (horizontal polarization) and with a covering of 21 cm of snow and 18 cm of dry ice, the brightness temperatures were 150 K and 76 K, respectively. When the snow depth was 33 cm, the brightness temperature was 144 K, and when the total thickness of the dry ice was 27 cm, the brightness temperature was 86 K. The lower brightness temperatures are due to a combination of the lower physical temperature and the larger crystal sizes of the commercial CO2 Crystals compared to the snow crystals. As the crystal size approaches the size of the microwave wavelength, it scatters microwave radiation more effectively, thus lowering the brightness temperature. The dry ice crystals in this experiment were about an order of magnitude larger than the snow crystals and three orders of magnitude larger than the CO2 Crystals produced in the cold stage of a scanning electron microscope. Spreading soil, approximately 2 mm in thickness, on the dry ice appeared to have no effect on the brightness temperatures.

Multi-RTM-based Radiance Assimilation to Improve Snow Estimates

NASA Astrophysics Data System (ADS)

Kwon, Y.; Zhao, L.; Hoar, T. J.; Yang, Z. L.; Toure, A. M.

2015-12-01

Data assimilation of microwave brightness temperature (TB) observations (i.e., radiance assimilation (RA)) has been proven to improve snowpack characterization at relatively small scales. However, large-scale applications of RA require a considerable amount of further efforts. Our objective in this study is to explore global-scale snow RA. In a RA scheme, a radiative transfer model (RTM) is an observational operator predicting TB; therefore, the quality of the assimilation results may strongly depend upon the RTM used as well as the land surface model (LSM). Several existing RTMs show different sensitivities to snowpack properties and thus they simulate significantly different TB. At the global scale, snow physical properties vary widely with local climate conditions. No single RTM has been shown to be able to accurately reproduce the observed TB for such a wide range of snow conditions. In this study, therefore, we hypothesize that snow estimates using a microwave RA scheme can be improved through the use of multiple RTMs (i.e., multi-RTM-based approaches). As a first step, here we use two snowpack RTMs, i.e., the Dense Media Radiative Transfer-Multi Layers model (DMRT-ML) and the Microwave Emission Model for Layered Snowpacks (MEMLS). The Community Land Model version 4 (CLM4) is used to simulate snow dynamics. The assimilation process is conducted by the Data Assimilation Research Testbed (DART), which is a community facility developed by the National Center for Atmospheric Research (NCAR) for ensemble-based data assimilation studies. In the RA experiments, the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) TB at 18.7 and 36.5 GHz vertical polarization channels are assimilated into the RA system using the ensemble adjustment Kalman filter. The results are evaluated using the Canadian Meteorological Centre (CMC) daily snow depth, the Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover fraction, and in-situ snowpack and river discharge observations.

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.

Multi-scale responses of scattering layers to environmental variability in Monterey Bay, California

NASA Astrophysics Data System (ADS)

Urmy, Samuel S.; Horne, John K.

2016-07-01

A 38 kHz upward-facing echosounder was deployed on the seafloor at a depth of 875 m in Monterey Bay, CA, USA (36° 42.748‧N, 122° 11.214‧W) from 27 February 2009 to 18 August 2010. This 18-month record of acoustic backscatter was compared to oceanographic time series from a nearby data buoy to investigate the responses of animals in sound-scattering layers to oceanic variability at seasonal and sub-seasonal time scales. Pelagic animals, as measured by acoustic backscatter, moved higher in the water column and decreased in abundance during spring upwelling, attributed to avoidance of a shoaling oxycline and advection offshore. Seasonal changes were most evident in a non-migrating scattering layer near 500 m depth that disappeared in spring and reappeared in summer, building to a seasonal maximum in fall. At sub-seasonal time scales, similar responses were observed after individual upwelling events, though they were much weaker than the seasonal relationship. Correlations of acoustic backscatter with oceanographic variability also differed with depth. Backscatter in the upper water column decreased immediately following upwelling, then increased approximately 20 days later. Similar correlations existed deeper in the water column, but at increasing lags, suggesting that near-surface productivity propagated down the water column at 10-15 m d-1, consistent with sinking speeds of marine snow measured in Monterey Bay. Sub-seasonal variability in backscatter was best correlated with sea-surface height, suggesting that passive physical transport was most important at these time scales.

Relative influence upon microwave emissivity of fine-scale stratigraphy, internal scattering, and dielectric properties

USGS Publications Warehouse

England, A.W.

1976-01-01

The microwave emissivity of relatively low-loss media such as snow, ice, frozen ground, and lunar soil is strongly influenced by fine-scale layering and by internal scattering. Radiometric data, however, are commonly interpreted using a model of emission from a homogeneous, dielectric halfspace whose emissivity derives exclusively from dielectric properties. Conclusions based upon these simple interpretations can be erroneous. Examples are presented showing that the emission from fresh or hardpacked snow over either frozen or moist soil is governed dominantly by the size distribution of ice grains in the snowpack. Similarly, the thickness of seasonally frozen soil and the concentration of rock clasts in lunar soil noticeably affect, respectively, the emissivities of northern latitude soils in winter and of the lunar regolith. Petrophysical data accumulated in support of the geophysical interpretation of microwave data must include measurements of not only dielectric properties, but also of geometric factors such as finescale layering and size distributions of grains, inclusions, and voids. ?? 1976 Birkha??user Verlag.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

The hydrological balance of an Alpine catchment is strongly affected by snowpack dynamics. Melt-water supplies a significant component of the annual water budget, both in terms of soil moisture and runoff, which play a critical role in floods generation and impact water resource management in snow-dominated basins. Several snow models have been developed with variable degrees of complexity, mainly depending on their target application and the availability of computational resources and data. According to the level of detail, snow models range from statistical snowmelt-runoff and degree-day methods using composite snow-soil or explicit snow layer(s), to physically-based and energy balance snow models, consisting of detailed internal snow-process schemes. Intermediate-complexity approaches have been widely developed resulting in simplified versions of the physical parameterization schemes with a reduced snowpack layering. Nevertheless, an increasing model complexity does not necessarily entail improved model simulations. This study presents a comparison analysis between two snow models designed for hydrological purposes. The snow module developed at UPMC and IRSTEA is a mono-layer energy balance model analytically resolving heat and phase change equations into the snowpack. Vertical mass exchange into the snowpack is also analytically resolved. The model is intended to be used for hydrological studies but also to give a realistic estimation of the snowpack state at watershed scale (SWE and snow depth). The structure of the model allows it to be easily calibrated using snow observation. This model is further presented in EGU2017-7492. The snow module of SMASH (Snow Multidata Assimilation System for Hydrology) consists in a multi-layer snow dynamic scheme. It is physically based on mass and energy balances and it reproduces the main physical processes occurring within the snowpack: accumulation, density dynamics, melting, sublimation, radiative balance, heat and mass exchanges. The model is driven by observed forcing meteorological data (air temperature, wind velocity, relative air humidity, precipitation and incident solar radiation) to provide an estimation of the snowpack state. In this study, no DA is used. For more details on the DA scheme, please see EGU2017-7777. Observed data supplied by meteorological stations located in three experimental Alpine sites are used: Col de Porte (1325 m, France); Torgnon (2160 m, Italy); Weissfluhjoch (2540 m, Switzerland). Performances of the two models are compared through evaluations of snow mass, snow depth, albedo and surface temperature simulations in order to better understand and pinpoint limits and potentialities of the analyzed schemes and the impact of different parameterizations on models simulations.

Multiple Volume Scattering in Random Media and Periodic Structures with Applications in Microwave Remote Sensing and Wave Functional Materials

NASA Astrophysics Data System (ADS)

Tan, Shurun

The objective of my research is two-fold: to study wave scattering phenomena in dense volumetric random media and in periodic wave functional materials. For the first part, the goal is to use the microwave remote sensing technique to monitor water resources and global climate change. Towards this goal, I study the microwave scattering behavior of snow and ice sheet. For snowpack scattering, I have extended the traditional dense media radiative transfer (DMRT) approach to include cyclical corrections that give rise to backscattering enhancements, enabling the theory to model combined active and passive observations of snowpack using the same set of physical parameters. Besides DMRT, a fully coherent approach is also developed by solving Maxwell's equations directly over the entire snowpack including a bottom half space. This revolutionary new approach produces consistent scattering and emission results, and demonstrates backscattering enhancements and coherent layer effects. The birefringence in anisotropic snow layers is also analyzed by numerically solving Maxwell's equation directly. The effects of rapid density fluctuations in polar ice sheet emission in the 0.5˜2.0 GHz spectrum are examined using both fully coherent and partially coherent layered media emission theories that agree with each other and distinct from incoherent approaches. For the second part, the goal is to develop integral equation based methods to solve wave scattering in periodic structures such as photonic crystals and metamaterials that can be used for broadband simulations. Set upon the concept of modal expansion of the periodic Green's function, we have developed the method of broadband Green's function with low wavenumber extraction (BBGFL), where a low wavenumber component is extracted and results a non-singular and fast-converging remaining part with simple wavenumber dependence. We've applied the technique to simulate band diagrams and modal solutions of periodic structures, and to construct broadband Green's functions including periodic scatterers.

Triple-frequency radar retrievals of snowfall properties from the OLYMPEX field campaign

NASA Astrophysics Data System (ADS)

Leinonen, J. S.; Lebsock, M. D.; Sy, O. O.; Tanelli, S.

2017-12-01

Retrieval of snowfall properties with radar is subject to significant errors arising from the uncertainties in the size and structure of snowflakes. Recent modeling and theoretical studies have shown that multi-frequency radars can potentially constrain the microphysical properties and thus reduce the uncertainties in the retrieved snow water content. So far, there have only been limited efforts to leverage the theoretical advances in actual snowfall retrievals. In this study, we have implemented an algorithm that retrieves the snowfall properties from triple-frequency radar data using the radar scattering properties from a combination of snowflake scattering databases, which were derived using numerical scattering methods. Snowflake number concentration, characteristic size and density are derived using a combination of optimal estimation and Kalman smoothing; the snow water content and other bulk properties are then derived from these. The retrieval framework is probabilistic and thus naturally provides error estimates for the retrieved quantities. We tested the retrieval algorithm using data from the APR3 airborne radar flown onboard the NASA DC-8 aircraft during the Olympic Mountain Experiment (OLYMPEX) in late 2015. We demonstrated consistent retrieval of snow properties and smooth transition from single- and dual-frequency retrievals to using all three frequencies simultaneously. The error analysis shows that the retrieval accuracy is improved when additional frequencies are introduced. We also compare the findings to in situ measurements of snow properties as well as measurements by polarimetric ground-based radar.

A Microfabricated 8-40 GHz Dual-Polarized Reflector Feed

NASA Technical Reports Server (NTRS)

Vanhille, Kenneth; Durham, Tim; Stacy, William; Karasiewicz, David; Caba, Aaron; Trent, Christopher; Lambert, Kevin; Miranda, Felix

2014-01-01

Planar antennas based on tightly coupled dipole arrays (also known as a current sheet antenna or CSA) are amenable for use as electronically scanned phased arrays. They are capable of performance nearing a decade of bandwidth. These antennas have been demonstrated in many implementations at frequencies below 18 GHz. This paper describes the implementation using a relatively new multi-layer microfabrication process resulting in a small, 6x6 element, dual-linear polarized array with beamformer that operates from 8 to 40 GHz. The beamformer includes baluns that feed the dual-polarized differential antenna elements and reactive splitter networks that also cover the full frequency range of operation. This antenna array serves as a reflector feed for a multi-band instrument designed to measure snow water equivalent (SWE) from airborne platforms. The instrument has both radar and radiome try capability at multiple frequencies. Scattering-parameter and time-domain measurements have been used to characterize the array feed. Radiation patterns of the antenna have been measured and are compared to simulation. To the best of the authors' knowledge, this work represents the most integrated multi-octave millimeter-wave antenna feed fabricated to date.

Influence of cloud fraction and snow cover to the variation of surface UV radiation at King Sejong station, Antarctica

NASA Astrophysics Data System (ADS)

Lee, Yun Gon; Koo, Ja-Ho; Kim, Jhoon

2015-10-01

This study investigated how cloud fraction and snow cover affect the variation of surface ultraviolet (UV) radiation by using surface Erythemal UV (EUV) and Near UV (NUV) observed at the King Sejong Station, Antarctica. First the Radiative Amplification Factor (RAF), the relative change of surface EUV according to the total-column ozone amount, is compared for different cloud fractions and solar zenith angles (SZAs). Generally, all cloudy conditions show that the increase of RAF as SZA becomes larger, showing the larger effects of vertical columnar ozone. For given SZA cases, the EUV transmission through mean cloud layer gradually decreases as cloud fraction increases, but sometimes the maximum of surface EUV appears under partly cloudy conditions. The high surface EUV transmittance under broken cloud conditions seems due to the re-radiation of scattered EUV by cloud particles. NUV transmission through mean cloud layer also decreases as cloud amount increases but the sensitivity to the cloud fraction is larger than EUV. Both EUV and NUV radiations at the surface are also enhanced by the snow cover, and their enhancement becomes higher as SZA increases implying the diurnal variation of surface albedo. This effect of snow cover seems large under the overcast sky because of the stronger interaction between snow surface and cloudy sky.

Multi-Frequency Radar/Passive Microwave retrievals of Cold Season Precipitation from OLYMPEX data

NASA Astrophysics Data System (ADS)

Tridon, Frederic; Battaglia, Alessandro; Turk, Joe; Tanelli, Simone; Kneifel, Stefan; Leinonen, Jussi; Kollias, Pavlos

2017-04-01

Due to the large natural variability of its microphysical properties, the characterization of solid precipitation over the variety of Earth surface conditions remain a longstanding open issue for space-based radar and passive microwave (MW) observing systems, such those on board the current NASA-JAXA Global Precipitation measurement (GPM) core and constellation satellites. Observations from the NASA DC-8 including radar profiles from the triple frequency Advanced Precipitation Radar (APR-3) and brightness temperatures from PMW radiometers with frequencies ranging from 89 to 183 GHz were collected during November-December 2015 as part of the OLYMPEX-RADEX campaign in western Washington state. Observations cover orographically-driven precipitation events with flight transects over ocean, coastal areas, vegetated and snow-covered surfaces. This study presents results obtained by a retrieval optimal estimation technique capable of combining the various radar and radiometer measurements in order to retrieve the snow properties such as equivalent water mass and characteristic size. The retrieval is constrained by microphysical a-priori defined by in situ measurements whilst the most recent ice scattering models are used in the forward modelling. The vast dataset collected during OLYMPEX is particular valuable because it can provide very strong tests for the fidelity of ice scattering models deep in the non-Rayleigh regime. In addition, the various scattering tables of snow aggregates with different degrees of riming can be exploited to assess the potential of multi-wavelength active and passive microwave systems in identifying the primary ice growth process (i.e. aggregation vs riming vs deposition). First comparisons with in-situ observations from the coordinated flights of the Citation aircraft will also be presented.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Retrieval of Snow Properties for Ku- and Ka-band Dual-Frequency Radar

NASA Technical Reports Server (NTRS)

Liao, Liang; Meneghini, Robert; Tokay, Ali; Bliven, Larry F.

2016-01-01

The focus of this study is on the estimation of snow microphysical properties and the associated bulk parameters such as snow water content and water equivalent snowfall rate for Ku- and Ka-band dual-frequency radar. This is done by exploring a suitable scattering model and the proper particle size distribution (PSD) assumption that accurately represent, in the electromagnetic domain, the micro/macro-physical properties of snow. The scattering databases computed from simulated aggregates for small-to-moderate particle sizes are combined with a simple scattering model for large particle sizes to characterize snow scattering properties over the full range of particle sizes. With use of the single-scattering results, the snow retrieval lookup tables can be formed in a way that directly links the Ku- and Ka-band radar reflectivities to snow water content and equivalent snowfall rate without use of the derived PSD parameters. A sensitivity study of the retrieval results to the PSD and scattering models is performed to better understand the dual-wavelength retrieval uncertainties. To aid in the development of the Ku- and Ka-band dual-wavelength radar technique and to further evaluate its performance, self-consistency tests are conducted using measurements of the snow PSD and fall velocity acquired from the Snow Video Imager Particle Image Probe (SVIPIP) duringthe winter of 2014 at the NASA Wallops Flight Facility site in Wallops Island, Virginia.

Retrieval of Snow Properties for Ku- and Ka-Band Dual-Frequency Radar

NASA Technical Reports Server (NTRS)

Liao, Liang; Meneghini, Robert; Tokay, Ali; Bliven, Larry F.

2016-01-01

The focus of this study is on the estimation of snow microphysical properties and the associated bulk parameters such as snow water content and water equivalent snowfall rate for Ku- and Ka-band dual-frequency radar. This is done by exploring a suitable scattering model and the proper particle size distribution (PSD) assumption that accurately represent, in the electromagnetic domain, the micro-macrophysical properties of snow. The scattering databases computed from simulated aggregates for small-to-moderate particle sizes are combined with a simple scattering model for large particle sizes to characterize snow-scattering properties over the full range of particle sizes. With use of the single-scattering results, the snow retrieval lookup tables can be formed in a way that directly links the Ku- and Ka-band radar reflectivities to snow water content and equivalent snowfall rate without use of the derived PSD parameters. A sensitivity study of the retrieval results to the PSD and scattering models is performed to better understand the dual-wavelength retrieval uncertainties. To aid in the development of the Ku- and Ka-band dual-wavelength radar technique and to further evaluate its performance, self-consistency tests are conducted using measurements of the snow PSD and fall velocity acquired from the Snow Video Imager Particle Image Probe (SVIPIP) during the winter of 2014 at the NASA Wallops Flight Facility site in Wallops Island, Virginia.

Scattering of electromagnetic waves from a half-space of randomly distributed discrete scatterers and polarized backscattering ratio law

NASA Technical Reports Server (NTRS)

Zhu, P. Y.

1991-01-01

The effective-medium approximation is applied to investigate scattering from a half-space of randomly and densely distributed discrete scatterers. Starting from vector wave equations, an approximation, called effective-medium Born approximation, a particular way, treating Green's functions, and special coordinates, of which the origin is set at the field point, are used to calculate the bistatic- and back-scatterings. An analytic solution of backscattering with closed form is obtained and it shows a depolarization effect. The theoretical results are in good agreement with the experimental measurements in the cases of snow, multi- and first-year sea-ice. The root product ratio of polarization to depolarization in backscattering is equal to 8; this result constitutes a law about polarized scattering phenomena in the nature.

Polarimetric scattering from layered media with multiple species of scatterers

NASA Technical Reports Server (NTRS)

Nghiem, S. V.; Kwok, R.; Yueh, S. H.; Kong, J. A.; Hsu, C. C.; Tassoudji, M. A.; Shin, R. T.

1995-01-01

Geophysical media are usually heterogeneous and contain multiple species of scatterers. In this paper a model is presented to calculate effective permittivities and polarimetric backscattering coefficients of multispecies-layered media. The same physical description is consistently used in the derivation of both permittivities and scattering coefficients. The strong permittivity fluctuation theory is extended to account for the multiple species of scatterers with a general ellipsoidal shape whose orientations are randomly distributed. Under the distorted Born approximation, polarimetric scattering coefficients are obtained. These calculations are applicable to the special cases of spheroidal and spherical scatterers. The model is used to study effects of scatterer shapes and multispecies mixtures on polarimetric signatures of heterogeneous media. The multispecies model accounts for moisture content in scattering media such as snowpack in an ice sheet. The results indicate a high sensitivity of backscatter to moisture with a stronger dependence for drier snow and ice grain size is important to the backscatter. For frost-covered saline ice, model results for bare ice are compared with measured data at C band and then the frost flower formation is simulated with a layer of fanlike ice crystals including brine infiltration over a rough interface. The results with the frost cover suggest a significant increase in scattering coefficients and a polarimetric signature closer to isotropic characteristics compared to the thin saline ice case.

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

NASA Astrophysics Data System (ADS)

Xiong, Chuan; Shi, Jiancheng

2014-01-01

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

LANDSAT-D investigations in snow hydrology

NASA Technical Reports Server (NTRS)

Dozier, J. (Principal Investigator)

1984-01-01

Two stream methods provide rapid approximate calculations of radiative transfer in scattering and absorbing media. Although they provide information on fluxes only, and not on intensities, their speed makes them attractive to more precise methods. The methods provide a comprehensive, unified review for a homogeneous layer, and solve the equations for reflectance and transmittance for a homogeneous layer over a non reflecting surface. Any of the basic kernels for a single layer can be extended to a vertically inhomogeneous medium over a surface whose reflectance properties vary with illumination angle, as long as the medium can be subdivided into homogeneous layers.

Bidirectional Reflectance of Flat, Optically Thick Particulate Layers: An Efficient Radiative Transfer Solution and Applications to Snow and Soil Surfaces

NASA Technical Reports Server (NTRS)

Mishchenko, Michael I.; Dlugach, Janna M.; Yanovitsku, Edgard G.; Zakharova, Nadia T.

1999-01-01

We describe a simple and highly efficient and accurate radiative transfer technique for computing bidirectional reflectance of a macroscopically flat scattering layer composed of nonabsorbing or weakly absorbing, arbitrarily shaped, randomly oriented and randomly distributed particles. The layer is assumed to be homogeneous and optically semi-infinite, and the bidirectional reflection function (BRF) is found by a simple iterative solution of the Ambartsumian's nonlinear integral equation. As an exact Solution of the radiative transfer equation, the reflection function thus obtained fully obeys the fundamental physical laws of energy conservation and reciprocity. Since this technique bypasses the computation of the internal radiation field, it is by far the fastest numerical approach available and can be used as an ideal input for Monte Carlo procedures calculating BRFs of scattering layers with macroscopically rough surfaces. Although the effects of packing density and coherent backscattering are currently neglected, they can also be incorporated. The FORTRAN implementation of the technique is available on the World Wide Web at http://ww,,v.giss.nasa.gov/-crmim/brf.html and can be applied to a wide range of remote sensing, engineering, and biophysical problems. We also examine the potential effect of ice crystal shape on the bidirectional reflectance of flat snow surfaces and the applicability of the Henyey-Greenstein phase function and the 6-Eddington approximation in calculations for soil surfaces.

Studies of snowpack properties by passive microwave radiometry

NASA Technical Reports Server (NTRS)

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

1979-01-01

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

Climate Sensitivity to Realistic Solar Heating of Snow and Ice

NASA Astrophysics Data System (ADS)

Flanner, M.; Zender, C. S.

2004-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Snow Microwave Radiative Transfer (SMRT): A new model framework to simulate snow-microwave interactions for active and passive remote sensing applications

NASA Astrophysics Data System (ADS)

Loewe, H.; Picard, G.; Sandells, M. J.; Mätzler, C.; Kontu, A.; Dumont, M.; Maslanka, W.; Morin, S.; Essery, R.; Lemmetyinen, J.; Wiesmann, A.; Floury, N.; Kern, M.

2016-12-01

Forward modeling of snow-microwave interactions is widely used to interpret microwave remote sensing data from active and passive sensors. Though different models are yet available for that purpose, a joint effort has been undertaken in the past two years within the ESA Project "Microstructural origin of electromagnetic signatures in microwave remote sensing of snow". The new Snow Microwave Radiative Transfer (SMRT) model primarily facilitates a flexible treatment of snow microstructure as seen by X-ray tomography and seeks to unite respective advantages of existing models. In its main setting, SMRT considers radiation transfer in a plane-parallel snowpack consisting of homogeneous layers with a layer microstructure represented by an autocorrelation function. The electromagnetic model, which underlies permittivity, absorption and scattering calculations within a layer, is based on the improved Born approximation. The resulting vector-radiative transfer equation in the snowpack is solved using spectral decomposition of the discrete ordinates discretization. SMRT is implemented in Python and employs an object-oriented, modular design which intends to i) provide an intuitive and fail-safe API for basic users ii) enable efficient community developments for extensions (e.g. for improvements of sub-models for microstructure, permittivity, soil or interface reflectivity) from advanced users and iii) encapsulate the numerical core which is maintained by the developers. For cross-validation and inter-model comparison, SMRT implements various ingredients of existing models as selectable options (e.g. Rayleigh or DMRT-QCA phase functions) and shallow wrappers to invoke legacy model code directly (MEMLS, DMRT-QMS, HUT). In this paper we give an overview of the model components and show examples and results from different validation schemes.

Studies of snowpack properties by passive microwave radiometry

NASA Technical Reports Server (NTRS)

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

1978-01-01

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

Report on Research

DTIC Science & Technology

1989-06-01

Force systems require a resolved information on the optical thorough understanding of the propaga- extinction coefficient. Measurements of tion path , the...Depolarization as Function of Snow Density. Measurement System ). (It correlated well with the ( Multi -scatter scale length information is usable to extinction ...data on the effect of optically thin cirrus clouds on long - path infrared transmit- tance. Future system designers will have access to this new

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.

Scattering from randomly oriented scatterers of arbitrary shape in the low-frequency limit with application to vegetation

NASA Technical Reports Server (NTRS)

Karam, M. A.; Fung, A. K.

1983-01-01

A general theory of intensity scattering from small particles of arbitrary shape has been developed based on the radiative transfer theory. Upon permitting the particles to orient in accordance with any prescribed distribution, scattering models can be derived. By making an appropriate choice of the particle size, the scattering model may be used to estimate scattering from media such as snow, vegetation and sea ice. For the purpose of illustration only comparisons with measurements from a vegetated medium are shown. The difference in scattering between elliptic- and circular-shaped leaves is demonstrated. In the low-frequency limit, the major factors on backscattering from vegetation are found to be the depth of the vegetation layer and the orientation distribution of the leaves. The shape of the leaf is of secondary importance.

Scattering from randomly oriented scatterers of arbitrary shape in the low-frequency limit with application to vegetation

NASA Technical Reports Server (NTRS)

Karam, M. A.; Fung, A. K.

1984-01-01

A general theory of intensity scattering from small particles of arbitrary shape was developed based on the radiative transfer theory. Upon permitting the particles to orient in accordance with any prescribed distribution, scattering models can be derived. By making an appropriate choice of the particle size, the scattering model may be used to estimate scattering from media such as snow, vegetation and sea ice. For the purpose of illustration only comparisons with measurements from a vegetated medium are shown. The difference in scattering between elliptic and circular shaped leaves is demonstrated. In the low frequency limit, the major factors on backscattering from vegetation are found to be the depth of the vegetation layer and the orientation distribution of the leaves. The shape of the leaf is of secondary importance.

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

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

Snowstorm Along the China-Mongolia-Russia Borders

NASA Technical Reports Server (NTRS)

2004-01-01

Heavy snowfall on March 12, 2004, across north China's Inner Mongolia Autonomous Region, Mongolia and Russia, caused train and highway traffic to stop for several days along the Russia-China border. This pair of images from the Multi-angle Imaging SpectroRadiometer (MISR) highlights the snow and surface properties across the region on March 13. The left-hand image is a multi-spectral false-color view made from the near-infrared, red, and green bands of MISR's vertical-viewing (nadir) camera. The right-hand image is a multi-angle false-color view made from the red band data of the 46-degree aftward camera, the nadir camera, and the 46-degree forward camera.

About midway between the frozen expanse of China's Hulun Nur Lake (along the right-hand edge of the images) and Russia's Torey Lakes (above image center) is a dark linear feature that corresponds with the China-Mongolia border. In the upper portion of the images, many small plumes of black smoke rise from coal and wood fires and blow toward the southeast over the frozen lakes and snow-covered grasslands. Along the upper left-hand portion of the images, in Russia's Yablonovyy mountain range and the Onon River Valley, the terrain becomes more hilly and forested. In the nadir image, vegetation appears in shades of red, owing to its high near-infrared reflectivity. In the multi-angle composite, open-canopy forested areas are indicated by green hues. Since this is a multi-angle composite, the green color arises not from the color of the leaves but from the architecture of the surface cover. The green areas appear brighter at the nadir angle than at the oblique angles because more of the snow-covered surface in the gaps between the trees is visible. Color variations in the multi-angle composite also indicate angular reflectance properties for areas covered by snow and ice. The light blue color of the frozen lakes is due to the increased forward scattering of smooth ice, and light orange colors indicate rougher ice or snow, which scatters more light in the backward direction.

The Multi-angle Imaging SpectroRadiometer observes the daylit Earth continuously and every 9 days views the entire Earth between 82 degrees north and 82 degrees south latitude. These data products were generated from a portion of the imagery acquired during Terra orbit 22525. The panels cover an area of about 355 kilometers x 380 kilometers, and utilize data from blocks 50 to 52 within World Reference System-2 path 126.

MISR was built and is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Office of Earth Science, Washington, DC. The Terra satellite is managed by NASA's Goddard Space Flight Center, Greenbelt, MD. JPL is a division of the California Institute of Technology.

Subsurface Scattered Photons: Friend or Foe? Improving visible light laser altimeter elevation estimates, and measuring surface properties using subsurface scattered photons

NASA Astrophysics Data System (ADS)

Greeley, A.; Kurtz, N. T.; Neumann, T.; Cook, W. B.; Markus, T.

2016-12-01

Photon counting laser altimeters such as MABEL (Multiple Altimeter Beam Experimental Lidar) - a single photon counting simulator for ATLAS (Advanced Topographical Laser Altimeter System) - use individual photons with visible wavelengths to measure their range to target surfaces. ATLAS, the sole instrument on NASA's upcoming ICESat-2 mission, will provide scientists a view of Earth's ice sheets, glaciers, and sea ice with unprecedented detail. Precise calibration of these instruments is needed to understand rapidly changing parameters such as sea ice freeboard, and to measure optical properties of surfaces like snow covered ice sheets using subsurface scattered photons. Photons that travel through snow, ice, or water before scattering back to an altimeter receiving system travel farther than photons taking the shortest path between the observatory and the target of interest. These delayed photons produce a negative elevation bias relative to photons scattered directly off these surfaces. We use laboratory measurements of snow surfaces using a flight-tested laser altimeter (MABEL), and Monte Carlo simulations of backscattered photons from snow to estimate elevation biases from subsurface scattered photons. We also use these techniques to demonstrate the ability to retrieve snow surface properties like snow grain size.

Numerical Model of Multiple Scattering and Emission from Layering Snowpack for Microwave Remote Sensing

NASA Astrophysics Data System (ADS)

Jin, Y.; Liang, Z.

2002-12-01

The vector radiative transfer (VRT) equation is an integral-deferential equation to describe multiple scattering, absorption and transmission of four Stokes parameters in random scatter media. From the integral formal solution of VRT equation, the lower order solutions, such as the first-order scattering for a layer medium or the second order scattering for a half space, can be obtained. The lower order solutions are usually good at low frequency when high-order scattering is negligible. It won't be feasible to continue iteration for obtaining high order scattering solution because too many folds integration would be involved. In the space-borne microwave remote sensing, for example, the DMSP (Defense Meterological Satellite Program) SSM/I (Special Sensor Microwave/Imager) employed seven channels of 19, 22, 37 and 85GHz. Multiple scattering from the terrain surfaces such as snowpack cannot be neglected at these channels. The discrete ordinate and eigen-analysis method has been studied to take into account for multiple scattering and applied to remote sensing of atmospheric precipitation, snowpack etc. Snowpack was modeled as a layer of dense spherical particles, and the VRT for a layer of uniformly dense spherical particles has been numerically studied by the discrete ordinate method. However, due to surface melting and refrozen crusts, the snowpack undergoes stratifying to form inhomegeneous profiles of the ice grain size, fractional volume and physical temperature etc. It becomes necessary to study multiple scattering and emission from stratified snowpack of dense ice grains. But, the discrete ordinate and eigen-analysis method cannot be simply applied to multi-layers model, because numerically solving a set of multi-equations of VRT is difficult. Stratifying the inhomogeneous media into multi-slabs and employing the first order Mueller matrix of each thin slab, this paper developed an iterative method to derive high orders scattering solutions of whole scatter media. High order scattering and emission from inhomogeneous stratifying media of dense spherical particles are numerically obtained. The brightness temperature at low frequency such as 5.3 GHz without high order scattering and at SSM/I channels with high order scattering are obtained. This approach is also compared with the conventional discrete ordinate method for an uniform layer model. Numerical simulation for inhomogeneous snowpack is also compared with the measurements of microwave remote sensing.

Estimation of global snow cover using passive microwave data

NASA Astrophysics Data System (ADS)

Chang, Alfred T. C.; Kelly, Richard E.; Foster, James L.; Hall, Dorothy K.

2003-04-01

This paper describes an approach to estimate global snow cover using satellite passive microwave data. Snow cover is detected using the high frequency scattering signal from natural microwave radiation, which is observed by passive microwave instruments. Developed for the retrieval of global snow depth and snow water equivalent using Advanced Microwave Scanning Radiometer EOS (AMSR-E), the algorithm uses passive microwave radiation along with a microwave emission model and a snow grain growth model to estimate snow depth. The microwave emission model is based on the Dense Media Radiative Transfer (DMRT) model that uses the quasi-crystalline approach and sticky particle theory to predict the brightness temperature from a single layered snowpack. The grain growth model is a generic single layer model based on an empirical approach to predict snow grain size evolution with time. Gridding to the 25 km EASE-grid projection, a daily record of Special Sensor Microwave Imager (SSM/I) snow depth estimates was generated for December 2000 to March 2001. The estimates are tested using ground measurements from two continental-scale river catchments (Nelson River and the Ob River in Russia). This regional-scale testing of the algorithm shows that for passive microwave estimates, the average daily snow depth retrieval standard error between estimated and measured snow depths ranges from 0 cm to 40 cm of point observations. Bias characteristics are different for each basin. A fraction of the error is related to uncertainties about the grain growth initialization states and uncertainties about grain size changes through the winter season that directly affect the parameterization of the snow depth estimation in the DMRT model. Also, the algorithm does not include a correction for forest cover and this effect is clearly observed in the retrieval. Finally, error is also related to scale differences between in situ ground measurements and area-integrated satellite estimates. With AMSR-E data, improvements to snow depth and water equivalent estimates are expected since AMSR-E will have twice the spatial resolution of the SSM/I and will be able to characterize better the subnivean snow environment from an expanded range of microwave frequencies.

Perturbation Theory for Scattering from Multilayers with Randomly Rough Fractal Interfaces: Remote Sensing Applications.

PubMed

Imperatore, Pasquale; Iodice, Antonio; Riccio, Daniele

2017-12-27

A general, approximate perturbation method, able to provide closed-form expressions of scattering from a layered structure with an arbitrary number of rough interfaces, has been recently developed. Such a method provides a unique tool for the characterization of radar response patterns of natural rough multilayers. In order to show that, here, for the first time in a journal paper, we describe the application of the developed perturbation theory to fractal interfaces; we then employ the perturbative method solution to analyze the scattering from real-world layered structures of practical interest in remote sensing applications. We focus on the dependence of normalized radar cross section on geometrical and physical properties of the considered scenarios, and we choose two classes of natural stratifications: wet paleosoil covered by a low-loss dry sand layer and a sea-ice layer above water with dry snow cover. Results are in accordance with the experimental evidence available in the literature for the low-loss dry sand layer, and they may provide useful indications about the actual ability of remote sensing instruments to perform sub-surface sensing for different sensor and scene parameters.

Perturbation Theory for Scattering from Multilayers with Randomly Rough Fractal Interfaces: Remote Sensing Applications

PubMed Central

2017-01-01

A general, approximate perturbation method, able to provide closed-form expressions of scattering from a layered structure with an arbitrary number of rough interfaces, has been recently developed. Such a method provides a unique tool for the characterization of radar response patterns of natural rough multilayers. In order to show that, here, for the first time in a journal paper, we describe the application of the developed perturbation theory to fractal interfaces; we then employ the perturbative method solution to analyze the scattering from real-world layered structures of practical interest in remote sensing applications. We focus on the dependence of normalized radar cross section on geometrical and physical properties of the considered scenarios, and we choose two classes of natural stratifications: wet paleosoil covered by a low-loss dry sand layer and a sea-ice layer above water with dry snow cover. Results are in accordance with the experimental evidence available in the literature for the low-loss dry sand layer, and they may provide useful indications about the actual ability of remote sensing instruments to perform sub-surface sensing for different sensor and scene parameters. PMID:29280979

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Quantitative, depth-resolved determination of particle motion using multi-exposure, spatial frequency domain laser speckle imaging.

PubMed

Rice, Tyler B; Kwan, Elliott; Hayakawa, Carole K; Durkin, Anthony J; Choi, Bernard; Tromberg, Bruce J

2013-01-01

Laser Speckle Imaging (LSI) is a simple, noninvasive technique for rapid imaging of particle motion in scattering media such as biological tissue. LSI is generally used to derive a qualitative index of relative blood flow due to unknown impact from several variables that affect speckle contrast. These variables may include optical absorption and scattering coefficients, multi-layer dynamics including static, non-ergodic regions, and systematic effects such as laser coherence length. In order to account for these effects and move toward quantitative, depth-resolved LSI, we have developed a method that combines Monte Carlo modeling, multi-exposure speckle imaging (MESI), spatial frequency domain imaging (SFDI), and careful instrument calibration. Monte Carlo models were used to generate total and layer-specific fractional momentum transfer distributions. This information was used to predict speckle contrast as a function of exposure time, spatial frequency, layer thickness, and layer dynamics. To verify with experimental data, controlled phantom experiments with characteristic tissue optical properties were performed using a structured light speckle imaging system. Three main geometries were explored: 1) diffusive dynamic layer beneath a static layer, 2) static layer beneath a diffuse dynamic layer, and 3) directed flow (tube) submerged in a dynamic scattering layer. Data fits were performed using the Monte Carlo model, which accurately reconstructed the type of particle flow (diffusive or directed) in each layer, the layer thickness, and absolute flow speeds to within 15% or better.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Parameterization of single-scattering properties of snow

NASA Astrophysics Data System (ADS)

Räisänen, Petri; Kokhanovsky, Alexander; Guyot, Gwennole; Jourdan, Olivier; Nousiainen, Timo

2015-04-01

Snow consists of non-spherical ice grains of various shapes and sizes, which are surrounded by air and sometimes covered by films of liquid water. Still, in many studies, homogeneous spherical snow grains have been assumed in radiative transfer calculations, due to the convenience of using Mie theory. More recently, second-generation Koch fractals have been employed. While they produce a relatively flat scattering phase function typical of deformed non-spherical particles, this is still a rather ad-hoc choice. Here, angular scattering measurements for blowing snow conducted during the CLimate IMpacts of Short-Lived pollutants In the Polar region (CLIMSLIP) campaign at Ny Ålesund, Svalbard, are used to construct a reference phase function for snow. Based on this phase function, an optimized habit combination (OHC) consisting of severely rough (SR) droxtals, aggregates of SR plates and strongly distorted Koch fractals is selected. The single-scattering properties of snow are then computed for the OHC as a function of wavelength λ and snow grain volume-to-projected area equivalent radius rvp. Parameterization equations are developed for λ=0.199-2.7 μm and rvp = 10-2000 μm, which express the single-scattering co-albedo β, the asymmetry parameter g and the phase function as functions of the size parameter and the real and imaginary parts of the refractive index. Compared to the reference values computed for the OHC, the accuracy of the parameterization is very high for β and g. This is also true for the phase function parameterization, except for strongly absorbing cases (β > 0.3). Finally, we consider snow albedo and reflected radiances for the suggested snow optics parameterization, making comparisons with spheres and distorted Koch fractals. Further evaluation and validation of the proposed approach against (e.g.) bidirectional reflectance and polarization measurements for snow is planned. At any rate, it seems safe to assume that the OHC selected here provides a substantially better basis for representing the single-scattering properties of snow than spheres do. Moreover, the parameterizations developed here are analytic and simple to use, and they can also be applied to the treatment of dirty snow following (e.g.) the approach of Kokhanovsky (The Cryosphere, 7, 1325-1331, doi:10.5194/tc-7-1325-2013, 2013). This should make them an attractive option for use in radiative transfer applications involving snow.

Detection of Heterogeneous Small Inclusions by a Multi-Step MUSIC Method

NASA Astrophysics Data System (ADS)

Solimene, Raffaele; Dell'Aversano, Angela; Leone, Giovanni

2014-05-01

In this contribution the problem of detecting and localizing scatterers with small (in terms of wavelength) cross sections by collecting their scattered field is addressed. The problem is dealt with for a two-dimensional and scalar configuration where the background is given as a two-layered cylindrical medium. More in detail, while scattered field data are taken in the outermost layer, inclusions are embedded within the inner layer. Moreover, the case of heterogeneous inclusions (i.e., having different scattering coefficients) is addressed. As a pertinent applicative context we identify the problem of diagnose concrete pillars in order to detect and locate rebars, ducts and other small in-homogeneities that can populate the interior of the pillar. The nature of inclusions influences the scattering coefficients. For example, the field scattered by rebars is stronger than the one due to ducts. Accordingly, it is expected that the more weakly scattering inclusions can be difficult to be detected as their scattered fields tend to be overwhelmed by those of strong scatterers. In order to circumvent this problem, in this contribution a multi-step MUltiple SIgnal Classification (MUSIC) detection algorithm is adopted [1]. In particular, the first stage aims at detecting rebars. Once rebars have been detected, their positions are exploited to update the Green's function and to subtract the scattered field due to their presence. The procedure is repeated until all the inclusions are detected. The analysis is conducted by numerical experiments for a multi-view/multi-static single-frequency configuration and the synthetic data are generated by a FDTD forward solver. Acknowledgement This work benefited from networking activities carried out within the EU funded COST Action TU1208 "Civil Engineering Applications of Ground Penetrating Radar." [1] R. Solimene, A. Dell'Aversano and G. Leone, "MUSIC algorithms for rebar detection," J. of Geophysics and Engineering, vol. 10, pp. 1-8, 2013

Radiative transfer in falling snow: A two-stream approximation

NASA Astrophysics Data System (ADS)

Koh, Gary

1989-04-01

Light transmission measurements through falling snow have produced results unexplainable by single scattering arguments. A two-stream approximation to radiative transfer is used to derive an analytical expression that describes the effects of multiple scattering as a function of the snow optical depth and the snow asymmetry parameter. The approximate solution is simple and it may be as accurate as the exact solution for describing the transmission measurements within the limits of experimental uncertainties.

Comparison of radar backscatter from Antarctic and Arctic sea ice

NASA Technical Reports Server (NTRS)

Hosseinmostafa, R.; Lytle, V.

1992-01-01

Two ship-based step-frequency radars, one at C-band (5.3 GHz) and one at Ku-band (13.9 GHz), measured backscatter from ice in the Weddell Sea. Most of the backscatter data were from first-year (FY) and second-year (SY) ice at the ice stations where the ship was stationary and detailed snow and ice characterizations were performed. The presence of a slush layer at the snow-ice interface masks the distinction between FY and SY ice in the Weddell Sea, whereas in the Arctic the separation is quite distinct. The effect of snow-covered ice on backscattering coefficients (sigma0) from the Weddell Sea region indicates that surface scattering is the dominant factor. Measured sigma0 values were compared with Kirchhoff and regression-analysis models. The Weibull power-density function was used to fit the measured backscattering coefficients at 45 deg.

Advanced Multi-frequency Inversion Methods for Classifying Acoustic Scatterers

DTIC Science & Technology

2002-09-30

layers and the presence of individual zooplankton taxa. For example, physonect siphonophore larvae with small gas­ filled pneumatophores (~0.20 mm...over an approximately 2h period. The white circles indicate the presence of physonect siphonophore larvae detected by the VPR. Note the coincidence...of the distributions of these organisms and layers of elevated scattering. The high scattering in the vicinity of siphonophore larvae at 43 kHz is

Parameterization of single-scattering properties of snow

NASA Astrophysics Data System (ADS)

Räisänen, P.; Kokhanovsky, A.; Guyot, G.; Jourdan, O.; Nousiainen, T.

2015-02-01

Snow consists of non-spherical grains of various shapes and sizes. Still, in many radiative transfer applications, single-scattering properties of snow have been based on the assumption of spherical grains. More recently, second-generation Koch fractals have been employed. While they produce a relatively flat phase function typical of deformed non-spherical particles, this is still a rather ad-hoc choice. Here, angular scattering measurements for blowing snow conducted during the CLimate IMpacts of Short-Lived pollutants In the Polar region (CLIMSLIP) campaign at Ny Ålesund, Svalbard, are used to construct a reference phase function for snow. Based on this phase function, an optimized habit combination (OHC) consisting of severely rough (SR) droxtals, aggregates of SR plates and strongly distorted Koch fractals is selected. The single-scattering properties of snow are then computed for the OHC as a function of wavelength λ and snow grain volume-to-projected area equivalent radius rvp. Parameterization equations are developed for λ = 0.199-2.7 μm and rvp = 10-2000 μm, which express the single-scattering co-albedo β, the asymmetry parameter g and the phase function P11 as functions of the size parameter and the real and imaginary parts of the refractive index. The parameterizations are analytic and simple to use in radiative transfer models. Compared to the reference values computed for the OHC, the accuracy of the parameterization is very high for β and g. This is also true for the phase function parameterization, except for strongly absorbing cases (β > 0.3). Finally, we consider snow albedo and reflected radiances for the suggested snow optics parameterization, making comparisons to spheres and distorted Koch fractals.

Parameterization of single-scattering properties of snow

NASA Astrophysics Data System (ADS)

Räisänen, P.; Kokhanovsky, A.; Guyot, G.; Jourdan, O.; Nousiainen, T.

2015-06-01

Snow consists of non-spherical grains of various shapes and sizes. Still, in many radiative transfer applications, single-scattering properties of snow have been based on the assumption of spherical grains. More recently, second-generation Koch fractals have been employed. While they produce a relatively flat phase function typical of deformed non-spherical particles, this is still a rather ad hoc choice. Here, angular scattering measurements for blowing snow conducted during the CLimate IMpacts of Short-Lived pollutants In the Polar region (CLIMSLIP) campaign at Ny Ålesund, Svalbard, are used to construct a reference phase function for snow. Based on this phase function, an optimized habit combination (OHC) consisting of severely rough (SR) droxtals, aggregates of SR plates and strongly distorted Koch fractals is selected. The single-scattering properties of snow are then computed for the OHC as a function of wavelength λ and snow grain volume-to-projected area equivalent radius rvp. Parameterization equations are developed for λ = 0.199-2.7 μm and rvp = 10-2000 μm, which express the single-scattering co-albedo β, the asymmetry parameter g and the phase function P11 as functions of the size parameter and the real and imaginary parts of the refractive index. The parameterizations are analytic and simple to use in radiative transfer models. Compared to the reference values computed for the OHC, the accuracy of the parameterization is very high for β and g. This is also true for the phase function parameterization, except for strongly absorbing cases (β > 0.3). Finally, we consider snow albedo and reflected radiances for the suggested snow optics parameterization, making comparisons to spheres and distorted Koch fractals.

Chemical and morphological characterization of III-V strained layered heterostructures

NASA Astrophysics Data System (ADS)

Gray, Allen Lindsay

This dissertation describes investigations into the chemical and morphological characterization of III-V strained layered heterostructures by high-resolution x-ray diffraction. The purpose of this work is two-fold. The first was to use high-resolution x-ray diffraction coupled with transmission electron microscopy to characterize structurally a quaternary AlGaAsSb/InGaAsSb multiple quantum well heterostructure laser device. A method for uniquely determining the chemical composition of the strain quaternary quantum well, information previously thought to be unattainable using high resolution x-ray diffraction is thoroughly described. The misconception that high-resolution x-ray diffraction can separately find the well and barrier thickness of a multi-quantum well from the pendellosung fringe spacing is corrected, and thus the need for transmission electron microscopy is motivated. Computer simulations show that the key in finding the well composition is the intensity of the -3rd order satellite peaks in the diffraction pattern. The second part of this work addresses the evolution of strain relief in metastable multi-period InGaAs/GaAs multi-layered structures by high-resolution x-ray reciprocal space maps. Results are accompanied by transmission electron and differential contrast microscopy. The evolution of strain relief is tracked from a coherent "pseudomorphic" growth to a dislocated state as a function of period number by examining the x-ray diffuse scatter emanating from the average composition (zeroth-order) of the multi-layer. Relaxation is determined from the relative positions of the substrate with respect to the zeroth-order peak. For the low period number, the diffuse scatter from the multi-layer structure region arises from periodic, coherent crystallites. For the intermediate period number, the displacement fields around the multi-layer structure region transition to random coherent crystallites. At the higher period number, displacement fields of overlapping dislocations from relaxation of the random crystallites cause the initial stages of relaxation of the multi-layer structure. At the highest period number studied, relaxation of the multi-layer structure becomes bi-modal characterized by overlapping dislocations caused by mosaic block relaxation and periodically spaced misfit dislocations formed by 60°-type dislocations. The relaxation of the multi-layer structure has an exponential dependence on the diffuse scatter length-scale, which is shown to be a sensitive measure of the onset of relaxation.

Ten Years of Cloud Optical and Microphysical Retrievals from MODIS

NASA Technical Reports Server (NTRS)

Platnick, Steven; King, Michael D.; Wind, Galina; Hubanks, Paul; Arnold, G. Thomas; Amarasinghe, Nandana

2010-01-01

The MODIS cloud optical properties algorithm (MOD06/MYD06 for Terra and Aqua MODIS, respectively) has undergone extensive improvements and enhancements since the launch of Terra. These changes have included: improvements in the cloud thermodynamic phase algorithm; substantial changes in the ice cloud light scattering look up tables (LUTs); a clear-sky restoral algorithm for flagging heavy aerosol and sunglint; greatly improved spectral surface albedo maps, including the spectral albedo of snow by ecosystem; inclusion of pixel-level uncertainty estimates for cloud optical thickness, effective radius, and water path derived for three error sources that includes the sensitivity of the retrievals to solar and viewing geometries. To improve overall retrieval quality, we have also implemented cloud edge removal and partly cloudy detection (using MOD35 cloud mask 250m tests), added a supplementary cloud optical thickness and effective radius algorithm over snow and sea ice surfaces and over the ocean, which enables comparison with the "standard" 2.1 11m effective radius retrieval, and added a multi-layer cloud detection algorithm. We will discuss the status of the MOD06 algorithm and show examples of pixellevel (Level-2) cloud retrievals for selected data granules, as well as gridded (Level-3) statistics, notably monthly means and histograms (lD and 2D, with the latter giving correlations between cloud optical thickness and effective radius, and other cloud product pairs).

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.

Potential Elevation Biases for Laser Altimeters from Subsurface Scattered Photons: Laboratory and Model Exploration of Green Light Scattering in Snow

NASA Astrophysics Data System (ADS)

Greeley, A.; Neumann, T.; Markus, T.; Kurtz, N. T.; Cook, W. B.

2015-12-01

Existing visible light laser altimeters such as MABEL (Multiple Altimeter Beam Experimental Lidar) - a single photon counting simulator for ATLAS (Advanced Topographic Laser Altimeter System) on NASA's upcoming ICESat-2 mission - and ATM (Airborne Topographic Mapper) on NASA's Operation IceBridge mission provide scientists a view of Earth's ice sheets, glaciers, and sea ice with unprecedented detail. Precise calibration of these instruments is needed to understand rapidly changing parameters like sea ice freeboard and to measure optical properties of surfaces like snow covered ice sheets using subsurface scattered photons. Photons travelling into snow, ice, or water before scattering back to the altimeter receiving system (subsurface photons) travel farther and longer than photons scattering off the surface only, causing a bias in the measured elevation. We seek to identify subsurface photons in a laboratory setting using a flight-tested laser altimeter (MABEL) and to quantify their effect on surface elevation estimates for laser altimeter systems. We also compare these estimates with previous laboratory measurements of green laser light transmission through snow, as well as Monte Carlo simulations of backscattered photons from snow.

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.

Non-destructive evaluation of nano-sized structure of thin film devices by using small angle neutron scattering.

PubMed

Shin, E J; Seong, B S; Choi, Y; Lee, J K

2011-01-01

Nano-sized multi-layers copper-doped SrZrO3, platinum (Pt) and silicon oxide (SiO2) on silicon substrates were prepared by dense plasma focus (DPF) device with the high purity copper anode tip and analyzed by using small angle neutron scattering (SANS) to establish a reliable method for the non-destructive evaluation of the under-layer structure. Thin film was well formed at the time-to-dip of 5 microsec with stable plasma of DPF. Several smooth intensity peaks were periodically observed when neutron beam penetrates the thin film with multi-layers perpendicularly. The platinum layer is dominant to intensity peaks, where the copper-doped SrZnO3 layer next to the platinum layer causes peak broadening. The silicon oxide layer has less effect on the SANS spectra due to its relative thick thickness. The SANS spectra shows thicknesses of platinum and copper-doped SrZnO3 layers as 53 and 25 nm, respectively, which are well agreement with microstructure observation.

Resolving Size Distribution of Black Carbon Internally Mixed With Snow: Impact on Snow Optical Properties and Albedo

NASA Astrophysics Data System (ADS)

He, Cenlin; Liou, Kuo-Nan; Takano, Yoshi

2018-03-01

We develop a stochastic aerosol-snow albedo model that explicitly resolves size distribution of aerosols internally mixed with various snow grains. We use the model to quantify black carbon (BC) size effects on snow albedo and optical properties for BC-snow internal mixing. Results show that BC-induced snow single-scattering coalbedo enhancement and albedo reduction decrease by a factor of 2-3 with increasing BC effective radii from 0.05 to 0.25 μm, while polydisperse BC results in up to 40% smaller visible single-scattering coalbedo enhancement and albedo reduction compared to monodisperse BC with equivalent effective radii. We further develop parameterizations for BC size effects for application to climate models. Compared with a realistic polydisperse assumption and observed shifts to larger BC sizes in snow, respectively, assuming monodisperse BC and typical atmospheric BC effective radii could lead to overestimates of 24% and 40% in BC-snow albedo forcing averaged over different BC and snow conditions.

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.

Comparisons Between Ground Measurements of Broadband UV Irradiance (300-380 nm) and TOMS UV Estimates at Moscow for 1979-2000

NASA Technical Reports Server (NTRS)

Yurova, Alla Y.; Krotkov, Nicholay A.; Herman, Jay R.; Bhartia, P. K. (Technical Monitor)

2002-01-01

We show the comparisons between ground-based measurements of spectrally integrated (300 nm to 380 nm) ultraviolet (UV) irradiance with satellite estimates from the Total Ozone Mapping Spectrometer (TOMS) total ozone and reflectivity data for the whole period of TOMS measurements (1979-2000) over the Meteorological Observatory of Moscow State University (MO MSU), Moscow, Russia. Several aspects of the comparisons are analyzed, including effects of cloudiness, aerosol, and snow cover. Special emphasis is given to the effect of different spatial and temporal averaging of ground-based data when comparing with low-resolution satellite measurements (TOMS footprint area 50-200 sq km). The comparisons in cloudless scenes with different aerosol loading have revealed TOMS irradiance overestimates from +5% to +20%. A-posteriori correction of the TOMS data accounting for boundary layer aerosol absorption (single scattering albedo of 0.92) eliminates the bias for cloud-free conditions. The single scattering albedo was independently verified using CIMEL sun and sky-radiance measurements at MO MSU in September 2001. The mean relative difference between TOMS UV estimates and ground UV measurements mainly lies within 1 10% for both snow-free and snow period with a tendency to TOMS overestimation in snow-free period especially at overcast conditions when the positive bias reaches 15-17%. The analysis of interannual UV variations shows quite similar behavior for both TOMS and ground measurements (correlation coefficient r=0.8). No long-term trend in the annual mean bias was found for both clear-sky and all-sky conditions with snow and without snow. Both TOMS and ground data show positive trend in UV irradiance between 1979 and 2000. The UV trend is attributed to decreases in both cloudiness and aerosol optical thickness during the late 1990's over Moscow region. However, if the analyzed period is extended to include pre-TOMS era (1968-2000 period), no trend in ground UV irradiance is detected.

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

NASA Astrophysics Data System (ADS)

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

2003-12-01

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

Remote sensing of Earth terrain

NASA Technical Reports Server (NTRS)

Kong, J. A.

1993-01-01

Progress report on remote sensing of Earth terrain covering the period from Jan. to June 1993 is presented. Areas of research include: radiative transfer model for active and passive remote sensing of vegetation canopy; polarimetric thermal emission from rough ocean surfaces; polarimetric passive remote sensing of ocean wind vectors; polarimetric thermal emission from periodic water surfaces; layer model with tandom spheriodal scatterers for remote sensing of vegetation canopy; application of theoretical models to active and passive remote sensing of saline ice; radiative transfer theory for polarimetric remote sensing of pine forest; scattering of electromagnetic waves from a dense medium consisting of correlated mie scatterers with size distributions and applications to dry snow; variance of phase fluctuations of waves propagating through a random medium; polarimetric signatures of a canopy of dielectric cylinders based on first and second order vector radiative transfer theory; branching model for vegetation; polarimetric passive remote sensing of periodic surfaces; composite volume and surface scattering model; and radar image classification.

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

NASA Technical Reports Server (NTRS)

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

1976-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2007-12-01

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

The Scattering Properties of Natural Terrestrial Snows versus Icy Satellite Surfaces

NASA Technical Reports Server (NTRS)

Domingue, Deborah; Hartman, Beth; Verbiscer, Anne

1997-01-01

Our comparisons of the single particle scattering behavior of terrestrial snows and icy satellite regoliths to the laboratory particle scattering measurements of McGuire and Hapke demonstrate that the differences between icy satellite regoliths and their terrestrial counterparts are due to particle structures and textures. Terrestrial snow particle structures define a region in the single particle scattering function parameter space separate from the regions defined by the McGuire and Hapke artificial laboratory particles. The particle structures and textures of the grains composing icy satellites regoliths are not simple or uniform but consist of a variety of particle structure and texture types, some of which may be a combination of the particle types investigated by McGuire and Hapke.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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.

Heat transfer and phase transitions of water in multi-layer cryolithozone-surface systems

NASA Astrophysics Data System (ADS)

Khabibullin, I. L.; Nigametyanova, G. A.; Nazmutdinov, F. F.

2018-01-01

A mathematical model for calculating the distribution of temperature and the dynamics of the phase transfor-mations of water in multilayer systems on permafrost-zone surface is proposed. The model allows one to perform calculations in the annual cycle, taking into account the distribution of temperature on the surface in warm and cold seasons. A system involving four layers, a snow or land cover, a top layer of soil, a layer of thermal-insulation materi-al, and a mineral soil, is analyzed. The calculations by the model allow one to choose the optimal thickness and com-position of the layers which would ensure the stability of structures built on the permafrost-zone surface.

Insights into seasonal active layer dynamics by monitoring relative velocity changes using ambient seismic noise

NASA Astrophysics Data System (ADS)

James, S. R.; Knox, H. A.; Cole, C. J.; Abbott, R. E.; Screaton, E.

2016-12-01

Seasonal freeze and thaw of the active layer above permafrost results in dramatic changes in seismic velocity. We used daily cross correlations of ambient seismic noise recorded at Poker Flat Research Range in central Alaska to create a nearly continuous 2-year record of relative velocity changes. This analysis required that we modify the Moving Window Cross-spectral Analysis technique used in the Python package MSNoise to reduce the occurrence of cycle skipping. Results show relative velocity variations follow a seasonal pattern, where velocities decrease in late spring through the summer months and increase through the fall and winter months. This timing is consistent with active layer freeze and thaw in this region. These results were compared to a suite of ground- and satellite-based measurements to identify relationships. A decrease in relative velocities in late spring closely follows the timing of snow melt recorded in nearby ground temperatures and snow-depth logs. This transition also aligns with a decrease in the Normalized Difference Snow Index (NDSI) derived from multi-temporal Landsat 8 satellite imagery collected over the study site. A gradual increase in relative velocity through the fall months occurs when temperatures below ground surface remain near zero. We suggest this is due to latent heat feedbacks that keep temperatures constant while active layer velocities increase from continued ice formation. This highlights the value in velocity variations for capturing details on the freezing process. In addition, spatial variations in the magnitude of velocity changes are consistent with thaw probe surveys. Exploring relationships with remote sensing may allow indirect measurements of thaw over larger areas and further surface wave analysis may allow for thickness evolution measurements. 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.

A microwave backscattering model for precipitation

NASA Astrophysics Data System (ADS)

Ermis, Seda

A geophysical microwave backscattering model for space borne and ground-based remote sensing of precipitation is developed and used to analyze backscattering measurements from rain and snow type precipitation. Vector Radiative Transfer (VRT) equations for a multilayered inhomogeneous medium are applied to the precipitation region for calculation of backscattered intensity. Numerical solution of the VRT equation for multiple layers is provided by the matrix doubling method to take into account close range interactions between particles. In previous studies, the VRT model was used to calculate backscattering from a rain column on a sea surface. In the model, Mie scattering theory for closely spaced scatterers was used to determine the phase matrix for each sublayer characterized by a set of parameters. The scatterers i.e. rain drops within the sublayers were modelled as spheres with complex permittivities. The rain layer was bounded by rough boundaries; the interface between the cloud and the rain column as well as the interface between the sea surface and the rain were all analyzed by using the integral equation model (IEM). Therefore, the phase matrix for the entire rain column was generated by the combination of surface and volume scattering. Besides Mie scattering, in this study, we use T-matrix approach to examine the effect of the shape to the backscattered intensities since larger raindrops are most likely oblique in shape. Analyses show that the effect of obliquity of raindrops to the backscattered wave is related with size of the scatterers and operated frequency. For the ground-based measurement system, the VRT model is applied to simulate the precipitation column on horizontal direction. Therefore, the backscattered reflectivities for each unit range of volume are calculated from the backscattering radar cross sections by considering radar range and effective illuminated area of the radar beam. The volume scattering phase matrices for each range interval are calculated by Mie scattering theory. VRT equations are solved by matrix doubling method to compute phase matrix for entire radar beam. Model results are validated with measured data by X-band dual polarization Phase Tilt Weather Radar (PTWR) for snow, rain, wet hail type precipitation. The geophysical parameters given the best fit with measured reflectivities are used in previous models i.e. Rayleigh Approximation and Mie scattering and compared with the VRT model. Results show that reflectivities calculated by VRT models are differed up to 10 dB from the Rayleigh approximation model and up to 5 dB from the Mie Scattering theory due to both multiple scattering and attenuation losses for the rain rates as high as 80 mm/h.

Snow Crystal Orientation Effects on the Scattering of Passive Microwave Radiation

NASA Technical Reports Server (NTRS)

Foster, J. L.; Barton, J. S.; Chang, A. T. C.; Hall, D. K.

1999-01-01

For this study, consideration is given to the role crystal orientation plays in scattering and absorbing microwave radiation. A discrete dipole scattering model is used to measure the passive microwave radiation, at two polarizations (horizontal and vertical), scattered by snow crystals oriented in random and non random positions, having various sizes (ranging between 1 micrometers to 10,000 micrometers in radius), and shapes (including spheroids, cylinders, hexagons). The model results demonstrate that for the crystal sizes typically found in a snowpack, crystal orientation is insignificant compared to crystal size in terms of scattering microwave energy in the 8,100 gm (37 GHz) region of the spectrum. Therefore, the assumption used in radiative transfer approaches, where snow crystals are modeled as randomly oriented spheres, is adequate to account for the transfer of microwave energy emanating from the ground and passing through a snowpack.

Modelling Ground Based X- and Ku-Band Observations of Tundra Snow

NASA Astrophysics Data System (ADS)

Kasurak, A.; King, J. M.; Kelly, R. E.

2012-12-01

As part of a radar-based remote sensing field experiment in Churchill, Manitoba ground based Ku- and X-band scatterometers were deployed to observe changing tundra snowpack conditions from November 2010 to March 2011. The research is part of the validation effort for the Cold Regions Hydrology High-resolution Observatory (CoReH2O) mission, a candidate in the European Space Agency's Earth Explorer program. This paper focuses on the local validation of the semi-empirical radiative transfer (sRT) model proposed for use in snow property retrievals as part of the CoReH2O mission. In this validation experiment, sRT was executed in the forward mode, simulating backscatter to assess the ability of the model. This is a necessary precursor to any inversion attempt. Two experiments are considered, both conducted in a hummocky tundra environment with shallow snow cover. In both cases, scatterometer observations were acquired over a field of view of approximately 10 by 20 meters. In the first experiment, radar observations were made of a snow field and then repeated after the snow had been removed. A ground-based scanning LiDAR system was used to characterize the spatial variability of snow depth through measurements of the snow and ground surface. Snow properties were determined in the field of view from two snow pits, 12 density core measurements, and Magnaprobe snow depth measurements. In the second experiment, a site was non-destructively observed from November through March, with snow properties measured out-of-scene, to characterize the snow evolution response. The model results from sRT fit the form of the observations from the two scatterometer field experiments but do not capture the backscatter magnitude. A constant offset for the season of 5 dB for X-band co- and cross-polarization response was required to match observations, in addition to a 3 dB X- and Ku-band co-polarization offset after the 6th of December. To explain these offsets, it is recognized that the two main physical processes represented by the model are snow volume scattering and ground surface reflectance. With a larger correction needed for X-band, where the ground portion of backscatter is expected to be larger, the contribution from the underlying soil is explored first. The ground contribution in sRT is computed using the semi-empirical Oh et al. (1992) model using permittivity from a temperate mineral soil based model. The ground response is tested against two observations of snow-removed tundra, and one observation of snow free tundra. A secondary analysis is completed using a modified sRT ground model, incorporating recent work on frozen organic permittivity by Mironov et al. (2010). Multi-scale surface roughness resulting from superimposed microtopography on regularly distributed hummocks is also addressed. These results demonstrate the applicability of microwave scattering models to tundra snowpacks underlain with peat, and demonstrate the applicability of the CoReH2O sRT model.

Early results from NASA's SnowEx campaign

NASA Astrophysics Data System (ADS)

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

2017-04-01

SnowEx is a multi-year airborne snow campaign with the primary goal of addressing the question: How much water is stored in Earth's terrestrial snow-covered regions? Year 1 (2016-17) focuses on the distribution of snow-water equivalent (SWE) and the snow energy balance in a forested environment. The year 1 primary site is Grand Mesa and the secondary site is the Senator Beck Basin, both in western, Colorado, USA. Ten core sensors on four core aircraft will make observations using a broad suite of airborne sensors including active and passive microwave, and active and passive optical/infrared sensing techniques to determine the sensitivity and accuracy of these potential satellite remote sensing techniques, along with models, to measure snow under a range of forest conditions. SnowEx also includes an extensive range of ground truth measurements—in-situ samples, snow pits, ground based remote sensing measurements, and sophisticated new techniques. A detailed description of the data collected will be given and some early results will be presented. Seasonal snow cover is the largest single component of the cryosphere in areal extent (covering an average of 46M km2 of Earth's surface (31 % of land areas) each year). This seasonal snow has major societal impacts in the areas of water resources, natural hazards (floods and droughts), water security, and weather and climate. The only practical way to estimate the quantity of snow on a consistent global basis is through satellites. Yet, current space-based techniques underestimate storage of snow water equivalent (SWE) by as much as 50%, and model-based estimates can differ greatly vs. estimates based on remotely-sensed observations. At peak coverage, as much as half of snow-covered terrestrial areas involve forested areas, so quantifying the challenge represented by forests is important to plan any future snow mission. Single-sensor approaches may work for certain snow types and certain conditions, but not for others. Snow simply varies too much. Thus, the snow community consensus is that a multi-sensor approach is needed to adequately address global snow, combined with modeling and data assimilation. What remains at issue, then, is how best to combine and use the various sensors in an optimal way. That requires field measurements. NASA's SnowEx airborne campaign is designed to do exactly that. A list of core sensors is as follows. All are from NASA unless otherwise noted. • Radar (volume scattering): European Space Agency's SnowSAR, operated by MetaSensing • Lidar & hyperspectral imager: Airborne Snow Observatory (ASO) • Passive microwave: Airborne Earth Science Microwave Imaging Radiometer (AESMIR) • Bi-directional Reflectance Function (BRDF): the Cloud Absorption Radiometer (CAR) • Thermal Infrared imager • Thermal infrared non-imager from U. Washington • Video camera The ASO suite flew on a King Air, and the other sensors flew on a Navy P-3. In addition, two NASA radars flew on G-III aircraft to test more experimental retrieval techniques: • InSAR altimetry: Glacier and Ice Surface Topography Interferometer (GLISTIN-A) • Radar phase delay: Uninhabited Aerial Vehicle Synthetic Aperture Radar, (UAVSAR)

Snow in Earth System Models: Recent Progress and Future Challenges

NASA Astrophysics Data System (ADS)

Clark, M. P.; Slater, A. G.

2016-12-01

Snow is the most variable of terrestrial boundary conditions. Some 50 million km^2 of the Northern Hemisphere typically sees periods of accumulation and ablation in the annual cycle. The wonderous properties of snow, such as high albedo, thermal insulation and its ability to act as a water store make it an integral part of the global climate system. Earliest inclusions of snow within climate models were simple adjustments to albedo and a moisture store. Modern Earth Syetem Models now represent snow through a myriad of model architectures and parameterizations that span a broad range of complexity. Understanding the impacts of modeling decisions upon simulation of snow and other Earth System components (either directly or via feedbacks) is an ongoing area of research. Snow models are progressing with multi-layer representations and capabilities such as complex albedo schemes that include contaminants. While considerable advances have been made, numerous challenges also remain. Simply getting a grasp on the mass of snow (seasonal or permanent) has proved more difficult than expected over the past 30 years. Snow interactions with vegetation has improved but the details of vegetation masking and emergence are still limited. Inclusion of blowing snow processes, in terms of transport and sublimation, is typically rare and sublimation remains a difficult quantity to measure. Contemplation of snow crystal form within models and integration with radiative transfer schemes for better understanding of full spectrum interations (from UV to long microwave) may simultaneously advance simulation and remote sensing. A series of international modeling experiments and directed field campaigns are planned in the near future with the aim of pushing our knowledge forward.

SWEAT: Snow Water Equivalent with AlTimetry

NASA Astrophysics Data System (ADS)

Agten, Dries; Benninga, Harm-Jan; Diaz Schümmer, Carlos; Donnerer, Julia; Fischer, Georg; Henriksen, Marie; Hippert Ferrer, Alexandre; Jamali, Maryam; Marinaci, Stefano; Mould, Toby JD; Phelan, Liam; Rosker, Stephanie; Schrenker, Caroline; Schulze, Kerstin; Emanuel Telo Bordalo Monteiro, Jorge

2017-04-01

To study how the water cycle changes over time, satellite and airborne remote sensing missions are typically employed. Over the last 40 years of satellite missions, the measurement of true water inventories stored in sea and land ice within the cryosphere have been significantly hindered by uncertainties introduced by snow cover. Being able to determine the thickness of this snow cover would act to reduce such error, improving current estimations of hydrological and climate models, Earth's energy balance (albedo) calculations and flood predictions. Therefore, the target of the SWEAT (Snow Water Equivalent with AlTimetry) mission is to directly measure the surface Snow Water Equivalent (SWE) on sea and land ice within the polar regions above 60°and below -60° latitude. There are no other satellite missions currently capable of directly measuring SWE. In order to achieve this, the proposed mission will implement a novel combination of Ka- and Ku-band radioaltimeters (active microwave sensors), capable of penetrating into the snow microstructure. The Ka-band altimeter (λ ≈ 0.8 cm) provides a low maximum snow pack penetration depth of up to 20 cm for dry snow at 37 GHz, since the volume scattering of snow dominates over the scattering caused by the underlying ice surface. In contrast, the Ku-band altimeter (λ ≈ 2 cm) provides a high maximum snowpack penetration depth of up to 15 m in high latitudes regions with dry snow, as volume scattering is decreased by a factor of 55. The combined difference in Ka- and Ku-band signal penetration results will provide more accurate and direct determination of SWE. Therefore, the SWEAT mission aims to improve estimations of global SWE interpreted from passive microwave products, and improve the reliability of numerical snow and climate models.

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.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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.

Global land-atmosphere coupling associated with cold climate processes

NASA Astrophysics Data System (ADS)

Dutra, Emanuel

This dissertation constitutes an assessment of the role of cold processes, associated with snow cover, in controlling the land-atmosphere coupling. The work was based on model simulations, including offline simulations with the land surface model HTESSEL, and coupled atmosphere simulations with the EC-EARTH climate model. A revised snow scheme was developed and tested in HTESSEL and EC-EARTH. The snow scheme is currently operational at the European Centre for Medium-Range Weather Forecasts integrated forecast system, and in the default configuration of EC-EARTH. The improved representation of the snowpack dynamics in HTESSEL resulted in improvements in the near surface temperature simulations of EC-EARTH. The new snow scheme development was complemented with the option of multi-layer version that showed its potential in modeling thick snowpacks. A key process was the snow thermal insulation that led to significant improvements of the surface water and energy balance components. Similar findings were observed when coupling the snow scheme to lake ice, where lake ice duration was significantly improved. An assessment on the snow cover sensitivity to horizontal resolution, parameterizations and atmospheric forcing within HTESSEL highlighted the role of the atmospheric forcing accuracy and snowpack parameterizations in detriment of horizontal resolution over flat regions. A set of experiments with and without free snow evolution was carried out with EC-EARTH to assess the impact of the interannual variability of snow cover on near surface and soil temperatures. It was found that snow cover interannual variability explained up to 60% of the total interannual variability of near surface temperature over snow covered regions. Although these findings are model dependent, the results showed consistency with previously published work. Furthermore, the detailed validation of the snow dynamics simulations in HTESSEL and EC-EARTH guarantees consistency of the results.

Light source distribution and scattering phase function influence light transport in diffuse multi-layered media

NASA Astrophysics Data System (ADS)

Vaudelle, Fabrice; L'Huillier, Jean-Pierre; Askoura, Mohamed Lamine

2017-06-01

Red and near-Infrared light is often used as a useful diagnostic and imaging probe for highly scattering media such as biological tissues, fruits and vegetables. Part of diffusively reflected light gives interesting information related to the tissue subsurface, whereas light recorded at further distances may probe deeper into the interrogated turbid tissues. However, modelling diffusive events occurring at short source-detector distances requires to consider both the distribution of the light sources and the scattering phase functions. In this report, a modified Monte Carlo model is used to compute light transport in curved and multi-layered tissue samples which are covered with a thin and highly diffusing tissue layer. Different light source distributions (ballistic, diffuse or Lambertian) are tested with specific scattering phase functions (modified or not modified Henyey-Greenstein, Gegenbauer and Mie) to compute the amount of backscattered and transmitted light in apple and human skin structures. Comparisons between simulation results and experiments carried out with a multispectral imaging setup confirm the soundness of the theoretical strategy and may explain the role of the skin on light transport in whole and half-cut apples. Other computational results show that a Lambertian source distribution combined with a Henyey-Greenstein phase function provides a higher photon density in the stratum corneum than in the upper dermis layer. Furthermore, it is also shown that the scattering phase function may affect the shape and the magnitude of the Bidirectional Reflectance Distribution (BRDF) exhibited at the skin surface.

Carbon dioxide crystals: An examination of their size, shape, and scattering properties at 37 GHz and comparisons with water ice (snow) measurements

NASA Astrophysics Data System (ADS)

Foster, J. L.; Chang, A. T. C.; Hall, D. K.; Wergin, W. P.; Erbe, E. F.; Barton, J.

1998-11-01

On Earth, the temperature regime is such that water is generally fairly close to its freezing point, and thus relatively small differences in climate affect how much snow and ice are present and whether or not the snow covering will be seasonal or last from one year to the next. On Mars, as on Earth, the presence of ice also plays a role in large-scale climate processes and it is important in controlling the abundance of atmospheric carbon dioxide (CO2) and water vapor. Passive microwave radiometry has been used to derive snow extent and snow depth on Earth, where scattering by snow (H2O) crystals is the dominant effect on the microwave radiation emanating from the ground and emerging from the snowpack. Microwave remote sensing may also prove to be useful for assessing the coverage and thickness of the frozen H2O and CO2 on Mars, but more exact information is needed on how both H2O crystals and frozen CO2 crystals scatter and absorb passive microwave radiation. In this study, CO2 crystals have been produced in a laboratory cold chamber with temperature conditions similar to those found on the polar caps of Mars, and detailed three-dimensional images of their size and shape have been made with a low-temperature scanning electron microscope. Unlike the much larger H2O snow crystals found on Earth, which typically range in size between 0.1 mm and 1.0 mm (radius), CO2 crystals are differently shaped and considerably smaller. Bipyramid crystals (base to base four-sided pyramids) are commonly observed, some as small as 1.0 μm. A discrete dipole model was employed to calculate the passive microwave radiation scattered and absorbed by crystals of various sizes and shapes. Modeling results indicate that the shape of the crystal, whether for frozen CO2 or H2O, is of little consequence in affecting extinction efficiency. However, owing to their smaller size, frozen CO2 crystals are more emissive than the H2O crystals in the 37 GHz region of the microwave spectrum. For the larger sizes of the modeled crystals, scattering dominates over absorption since the particles approach the size of the wavelength. The scattering values are 2 orders of magnitude larger than absorption for the 900 μm size snow particles. For CO2 crystals of 3.0 μm in size, absorption is 7 orders of magnitude greater than scattering.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Snow micro-structure at Kongsvegen glacier, Svalbard

NASA Astrophysics Data System (ADS)

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

2012-04-01

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

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.

Implementation of a physically based water percolation routine in the Crocus/SURFEX (V7.3) snowpack model

NASA Astrophysics Data System (ADS)

D'Amboise, Christopher J. L.; Müller, Karsten; Oxarango, Laurent; Morin, Samuel; Schuler, Thomas V.

2017-09-01

We present a new water percolation routine added to the one-dimensional snowpack model Crocus as an alternative to the empirical bucket routine. This routine solves the Richards equation, which describes flow of water through unsaturated porous snow governed by capillary suction, gravity and hydraulic conductivity of the snow layers. We tested the Richards routine on two data sets, one recorded from an automatic weather station over the winter of 2013-2014 at Filefjell, Norway, and the other an idealized synthetic data set. Model results using the Richards routine generally lead to higher water contents in the snow layers. Snow layers often reached a point at which the ice crystals' surface area is completely covered by a thin film of water (the transition between pendular and funicular regimes), at which feedback from the snow metamorphism and compaction routines are expected to be nonlinear. With the synthetic simulation 18 % of snow layers obtained a saturation of > 10 % and 0.57 % of layers reached saturation of > 15 %. The Richards routine had a maximum liquid water content of 173.6 kg m-3 whereas the bucket routine had a maximum of 42.1 kg m-3. We found that wet-snow processes, such as wet-snow metamorphism and wet-snow compaction rates, are not accurately represented at higher water contents. These routines feed back on the Richards routines, which rely heavily on grain size and snow density. The parameter sets for the water retention curve and hydraulic conductivity of snow layers, which are used in the Richards routine, do not represent all the snow types that can be found in a natural snowpack. We show that the new routine has been implemented in the Crocus model, but due to feedback amplification and parameter uncertainties, meaningful applicability is limited. Updating or adapting other routines in Crocus, specifically the snow compaction routine and the grain metamorphism routine, is needed before Crocus can accurately simulate the snowpack using the Richards routine.

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.

Geometrical-optics code for computing the optical properties of large dielectric spheres.

PubMed

Zhou, Xiaobing; Li, Shusun; Stamnes, Knut

2003-07-20

Absorption of electromagnetic radiation by absorptive dielectric spheres such as snow grains in the near-infrared part of the solar spectrum cannot be neglected when radiative properties of snow are computed. Thus a new, to our knowledge, geometrical-optics code is developed to compute scattering and absorption cross sections of large dielectric particles of arbitrary complex refractive index. The number of internal reflections and transmissions are truncated on the basis of the ratio of the irradiance incident at the nth interface to the irradiance incident at the first interface for a specific optical ray. Thus the truncation number is a function of the angle of incidence. Phase functions for both near- and far-field absorption and scattering of electromagnetic radiation are calculated directly at any desired scattering angle by using a hybrid algorithm based on the bisection and Newton-Raphson methods. With these methods a large sphere's absorption and scattering properties of light can be calculated for any wavelength from the ultraviolet to the microwave regions. Assuming that large snow meltclusters (1-cm order), observed ubiquitously in the snow cover during summer, can be characterized as spheres, one may compute absorption and scattering efficiencies and the scattering phase function on the basis of this geometrical-optics method. A geometrical-optics method for sphere (GOMsphere) code is developed and tested against Wiscombe's Mie scattering code (MIE0) and a Monte Carlo code for a range of size parameters. GOMsphere can be combined with MIE0 to calculate the single-scattering properties of dielectric spheres of any size.

Processes that generate and deplete liquid water and snow in thin midlevel mixed-phase clouds

NASA Astrophysics Data System (ADS)

Smith, Adam J.; Larson, Vincent E.; Niu, Jianguo; Kankiewicz, J. Adam; Carey, Lawrence D.

2009-06-01

This paper uses a numerical model to investigate microphysical, radiative, and dynamical processes in mixed-phase altostratocumulus clouds. Three cloud cases are chosen for study, each of which was observed by aircraft during the fifth or ninth Complex Layered Cloud Experiment (CLEX). These three clouds are numerically modeled using large-eddy simulation (LES). The observed and modeled clouds consist of a mixed-phase layer with a quasi-adiabatic profile of liquid, and a virga layer below that consists of snow. A budget of cloud (liquid) water mixing ratio is constructed from the simulations. It shows that large-scale ascent/descent, radiative cooling/heating, turbulent transport, and microphysical processes are all significant. Liquid is depleted indirectly via depositional growth of snow (the Bergeron-Findeisen process). This process is more influential than depletion of liquid via accretional growth of snow. Also constructed is a budget of snow mixing ratio, which turns out to be somewhat simpler. It shows that snow grows by deposition in and below the liquid (mixed-phase) layer, and sublimates in the remainder of the virga region below. The deposition and sublimation are balanced primarily by sedimentation, which transports the snow from the growth region to the sublimation region below. In our three clouds, the vertical extent of the virga layer is influenced more by the profile of saturation ratio below the liquid (mixed-phase) layer than by the mixing ratio of snow at the top of the virga layer.

Microwave signatures of snow, ice and soil at several wavelengths

NASA Technical Reports Server (NTRS)

Gloersen, P.; Schmugge, T. J.; Chang, T. C.

1974-01-01

Analyses of data obtained from aircraft-borne radiometers have shown that the microwave signatures of various parts of the terrain depend on both the volume scattering cross-section and the dielectric loss in the medium. In soil, it has been found that experimental data fit a model in which the scattering cross section is negligible compared to the dielectric loss. On the other hand, the volume scattering cross-section in snow and continental ice was found, from analyzing data obtained with aircraft- and spacecraft-borne radiometers, to be more important than the dielectric loss or surface reflectivity in determining the observed microwave emissivity. A model which assumes Mie scattering of ice particles of various sizes was found to be the dominant volume scattering mechanism in these media. Both spectral variation in the microwave signatures of snow and ice fields, as well as the variation in the emissivity of continental ice sheets such as those covering Greenland and Antarctica appear to be consistent with this model.

A Vision for an International Multi-Sensor Snow Observing Mission

NASA Technical Reports Server (NTRS)

Kim, Edward

2015-01-01

Discussions within the international snow remote sensing community over the past two years have led to encouraging consensus regarding the broad outlines of a dedicated snow observing mission. The primary consensus - that since no single sensor type is satisfactory across all snow types and across all confounding factors, a multi-sensor approach is required - naturally leads to questions about the exact mix of sensors, required accuracies, and so on. In short, the natural next step is to collect such multi-sensor snow observations (with detailed ground truth) to enable trade studies of various possible mission concepts. Such trade studies must assess the strengths and limitations of heritage as well as newer measurement techniques with an eye toward natural sensitivity to desired parameters such as snow depth and/or snow water equivalent (SWE) in spite of confounding factors like clouds, lack of solar illumination, forest cover, and topography, measurement accuracy, temporal and spatial coverage, technological maturity, and cost.

Analysis on the electromagnetic scattering properties of crops at multi-band

NASA Astrophysics Data System (ADS)

Wu, Tao; Wu, Zhensen; Liu, Xiaoyi

2014-12-01

The vector radiative transfer (VRT) theory for active microwave remote sensing and Rayleigh-Gans approximation (GRG) are applied in the study, and an iterative algorithm is used to solve the RT equations, thus we obtain the zeroorder and first-order equation for numerical results. The Michigan Microwave Canopy Scattering (MIMICS) model is simplified to adapt to the crop model, by analyzing body-surface bistatic scattering and backscattering properties between a layer of soybean or wheat consisting of stems and leaves and different underlying soil surface at multi-band (i.e. P, L, S, X, Ku-band), we obtain microwave scattering mechanisms of crop components and the effect of underlying ground on total crop scattering. Stem and leaf are regard as a needle and a circular disk, respectively. The final results are compared with some literature data to verify our calculating method, numerical results show multi-band crop microwave scattering properties differ from scattering angle, azimuth angle and moisture of vegetation and soil, which offer the part needed information for the design of future bistatic radar systems for crop sensing applications.

A stochastic model for density-dependent microwave Snow- and Graupel scattering coefficients of the NOAA JCSDA community radiative transfer model

NASA Astrophysics Data System (ADS)

Stegmann, Patrick G.; Tang, Guanglin; Yang, Ping; Johnson, Benjamin T.

2018-05-01

A structural model is developed for the single-scattering properties of snow and graupel particles with a strongly heterogeneous morphology and an arbitrary variable mass density. This effort is aimed to provide a mechanism to consider particle mass density variation in the microwave scattering coefficients implemented in the Community Radiative Transfer Model (CRTM). The stochastic model applies a bicontinuous random medium algorithm to a simple base shape and uses the Finite-Difference-Time-Domain (FDTD) method to compute the single-scattering properties of the resulting complex morphology.

Acoustic resonance scattering from a multilayered cylindrical shell with imperfect bonding.

PubMed

Rajabi, M; Hasheminejad, Seyyed M

2009-12-01

The method of wave function expansion is adopted to study the three dimensional scattering of a time-harmonic plane progressive sound field obliquely incident upon a multi-layered hollow cylinder with interlaminar bonding imperfection. For the generality of solution, each layer is assumed to be cylindrically orthotropic. An approximate laminate model in the context of the modal state equations with variable coefficients along with the classical T-matrix solution technique is set up for each layer to solve for the unknown modal scattering and transmission coefficients. A linear spring model is used to describe the interlaminar adhesive bonding whose effects are incorporated into the global transfer matrix by introduction of proper interfacial transfer matrices. Following the classic acoustic resonance scattering theory (RST), the scattered field and response to surface waves are determined by constructing the partial waves and obtaining the non-resonance (backgrounds) and resonance components. The solution is first used to investigate the effect of interlayer imperfection of an air-filled and water submerged bilaminate aluminium cylindrical shell on the resonances associated with various modes of wave propagation (i.e., symmetric/asymmetric Lamb waves, fluid-borne A-type waves, Rayleigh and Whispering Gallery waves) appearing in the backscattered spectrum, according to their polarization and state of stress. An illustrative numerical example is also given for a multi-layered (five-layered) cylindrical shell for which the stiffness of the adhesive interlayers is artificially varied. The sensitivity of resonance frequencies associated with higher mode numbers to the stiffness coefficients is demonstrated to be a good measure of the bonding strength. Limiting cases are considered and fair agreements with solutions available in the literature are established.

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.

Monte Carlo model of light transport in multi-layered tubular organs

NASA Astrophysics Data System (ADS)

Zhang, Yunyao; Zhu, Jingping; Zhang, Ning

2017-02-01

We present a Monte Carlo static light migration model (Endo-MCML) to simulate endoscopic optical spectroscopy for tubular organs such as esophagus and colon. The model employs multi-layered hollow cylinder which emitting and receiving light both from the inner boundary to meet the conditions of endoscopy. Inhomogeneous sphere can be added in tissue layers to model cancer or other abnormal changes. The 3D light distribution and exit angle would be recorded as results. The accuracy of the model has been verified by Multi-layered Monte Carlo(MCML) method and NIRFAST. This model can be used for the forward modeling of light transport during endoscopically diffuse optical spectroscopy, light scattering spectroscopy, reflectance spectroscopy and other static optical detection or imaging technologies.

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

NASA Technical Reports Server (NTRS)

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

2000-01-01

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

How Can Polarization States of Reflected Light from Snow Surfaces Inform Us on Surface Normals and Ultimately Snow Grain Size Measurements?

NASA Astrophysics Data System (ADS)

Schneider, A. M.; Flanner, M.; Yang, P.; Yi, B.; Huang, X.; Feldman, D.

2016-12-01

The Snow Grain Size and Pollution (SGSP) algorithm is a method applied to Moderate Resolution Imaging Spectroradiometer data to estimate snow grain size from space-borne measurements. Previous studies validate and quantify potential sources of error in this method, but because it assumes flat snow surfaces, however, large scale variations in surface normals can cause biases in its estimates due to its dependence on solar and observation zenith angles. To address these variations, we apply the Monte Carlo method for photon transport using data containing the single scattering properties of different ice crystals to calculate polarization states of reflected monochromatic light at 1500nm from modeled snow surfaces. We evaluate the dependence of these polarization states on solar and observation geometry at 1500nm because multiple scattering is generally a mechanism for depolarization and the ice crystals are relatively absorptive at this wavelength. Using 1500nm thus results in a higher number of reflected photons undergoing fewer scattering events, increasing the likelihood of reflected light having higher degrees of polarization. In evaluating the validity of the model, we find agreement with previous studies pertaining to near-infrared spectral directional hemispherical reflectance (i.e. black-sky albedo) and similarities in measured bidirectional reflectance factors, but few studies exist modeling polarization states of reflected light from snow surfaces. Here, we present novel results pertaining to calculated polarization states and compare dependences on solar and observation geometry for different idealized snow surfaces. If these dependencies are consistent across different ice particle shapes and sizes, then these findings could inform the SGSP algorithm by providing useful relationships between measurable physical quantities and solar and observation geometry to better understand variations in snow surface normals from remote sensing observations.

Enhance the accuracy of radar snowfall estimation with Multi new Z-S relationships in MRMS system

NASA Astrophysics Data System (ADS)

Qi, Y.

2017-12-01

Snow may have negative affects on roadways and human lives, but the result of the melted snow/ice is good for farm, humans, and animals. For example, in the Southwest and West mountainous area of United States, water shortage is a very big concern. However, snowfall in the winter can provide humans, animals and crops an almost unlimited water supply. So, using radar to accurately estimate the snowfall is very important for human life and economic development in the water lacking area. The current study plans to analyze the characteristics of the horizontal and vertical variations of dry/wet snow using dual polarimetric radar observations, relative humidity and in situ snow water equivalent observations from the National Weather Service All Weather Prediction Accumulation Gauges (AWPAG) across the CONUS, and establish the relationships between the reflectivity (Z) and ground snow water equivalent (S). The new Z-S relationships will be evaluated with independent CoCoRaHS (Community Collaborative Rain, Hail & Snow Network) gauge observations and eventually implemented in the Multi-Radar Multi-Sensor system for improved quantitative precipitation estimation for snow. This study will analyze the characteristics of the horizontal and vertical variations of dry/wet snow using dual polarimetric radar observations, relative humidity and in situ snow water equivalent observations from the National Weather Service All Weather Prediction Accumulation Gauges (AWPAG) across the CONUS, and establish the relationships between the reflectivity (Z) and ground snow water equivalent (S). The new Z-S relationships will be used to reduce the error of snowfall estimation in Multi Radar and Multi Sensors (MRMS) system, and tested in MRMS system and evaluated with the COCORaHS observations. Finally, it will be ingested in MRMS sytem, and running in NWS/NCAR operationally

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.

Iron layer-dependent surface-enhanced raman scattering of hierarchical nanocap arrays

NASA Astrophysics Data System (ADS)

Chen, Lei; Sun, Huanhuan; Zhao, Yue; Gao, Renxian; Wang, Yaxin; Liu, Yang; Zhang, Yongjun; Hua, Zhong; Yang, Jinghai

2017-11-01

In this report, we fabricated the multi-layer Ag/Fe/Ag sandwich cap-shaped films on monolayer non-closed packed (ncp) polystyrene colloidal particle (PSCP) templates through a layer-by-layer (LBL) depositing method. This research focused on the surface-enhanced Raman scattering (SERS) effect of the thickness of the deposited Fe film which was controlled by the sputtering time. The SERS intensities were increased firstly, and then decreased as the thickness of Fe layer grows gradually, which is attributed to the charge transition from the Fermi level of the Ag NPs to Fe layer. The use of multi-layer Ag/Fe/Ag sandwich cap-shaped films enables us to evaluate the contribution of surface plasmon resonance and charge distribution between Ag and Fe to SERS enhancement. Our work introduced a novel system (Ag/Fe/Ag) for high performance SERS and extended the SERS application of Fe. Furthermore, we have designed the Ag/Fe/Ag SERS-active substrate as the immunoassay chip for quantitative determination of AFP-L3 which is the biomarker of hepatocellular carcinoma (HCC). The proposed research demonstrates that the SERS substrates with Ag/Fe/Ag sandwich cap-shaped arrays have a high sensitivity for bioassay.

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.

Light dosimetry for focused and defocused beam irradiation in multi-layered tissue models

NASA Astrophysics Data System (ADS)

Petrova, Kremena S.; Stoykova, Elena V.

2006-09-01

Treatment of acupuncture points, trigger points, joint inflammations in low level laser therapy as well as various applications of lasers for treatment of soft tissues in dental medicine, require irradiation by a narrow converging laser beam. The aim of this study is to compare light delivery produced by focused or defocused narrow beam irradiation in a multi-layered skin tissue model at increasing depth of the target. The task is solved by 3-D Monte-Carlo simulation for matched and mismatched refractive indices at the tissue/ambient medium interface. The modeled light beams have a circular cross-section at the tissue entrance with uniform or Gaussian intensity distribution. Three are the tissue models used in simulation : i) a bloodless skin layer; ii) a bloodless skin layer with embedded scattering object; iii) a skin layer with small blood vessels of varying size, which are modeled as infinite cylinders parallel to the tissue surface located at different depths. Optical properties (absorption coefficient, scattering coefficient, anisotropy factor, g, and index of refraction) of different tissue constituents are chosen from the literature.

Field experiments to determine wave propagation principles and mechanical properties of snow

NASA Astrophysics Data System (ADS)

Simioni, Stephan; Gebhard, Felix; Dual, Jürg; Schweizer, Jürg

2017-04-01

To understand the release of snow avalanches by explosions one needs to know how acoustic waves travel above and within the snowpack. Hitherto, wave propagation was investigated in the laboratory with small samples or in the field in the shock wave region. We developed a measurement system and layout to derive wave attenuation in snow, wave speeds and elastic moduli on small-scale (1-2 m) field experiments to close the gap between the lab scale (0.1 m) and the scale of artificial release (10-100 m). We used solid explosives and hammer blows to create the load and accelerometers to measure the resulting wave within the snowpack. The strong attenuation we observed indicates that we measured the second longitudinal wave which propagates through the pore space. The wave speeds, however, corresponded to the speeds of the first longitudinal wave within the ice skeleton. The elastic moduli were high on the order of several tens of MPa for lower densities (150 kg m-3) and agreed well with earlier lab studies, in particular for the higher densities 250-400 kg m-3). However, the scatter was rather large as expected for in-situ experiments in the layered snow cover. In addition, we measured accelerations during propagation saw test experiments. The propagation of cracks during this type of snow instability test has mainly been studied by analysing the bending of the slab (due to the saw cut) using particle tracking velocimetry. We used the accelerometers to measure crack propagation speeds. The wave speeds were slightly higher for most experiments than reported previously. Furthermore, in some experiments, we encountered to different wave types with one propagating at a higher speed. This finding may be interpreted as the actual crack propagation and the settling of the weak layer (collapse wave). Our results show that field measurements of propagation properties are feasible and that crack propagation as observed during propagation saw tests may involve different processes that need to be further investigated.

The magnitude of the snow-sourced reactive nitrogen flux to the boundary layer in the Uintah Basin, Utah, USA

NASA Astrophysics Data System (ADS)

Zatko, Maria; Erbland, Joseph; Savarino, Joel; Geng, Lei; Easley, Lauren; Schauer, Andrew; Bates, Timothy; Quinn, Patricia K.; Light, Bonnie; Morison, David; Osthoff, Hans D.; Lyman, Seth; Neff, William; Yuan, Bin; Alexander, Becky

2016-11-01

Reactive nitrogen (Nr = NO, NO2, HONO) and volatile organic carbon emissions from oil and gas extraction activities play a major role in wintertime ground-level ozone exceedance events of up to 140 ppb in the Uintah Basin in eastern Utah. Such events occur only when the ground is snow covered, due to the impacts of snow on the stability and depth of the boundary layer and ultraviolet actinic flux at the surface. Recycling of reactive nitrogen from the photolysis of snow nitrate has been observed in polar and mid-latitude snow, but snow-sourced reactive nitrogen fluxes in mid-latitude regions have not yet been quantified in the field. Here we present vertical profiles of snow nitrate concentration and nitrogen isotopes (δ15N) collected during the Uintah Basin Winter Ozone Study 2014 (UBWOS 2014), along with observations of insoluble light-absorbing impurities, radiation equivalent mean ice grain radii, and snow density that determine snow optical properties. We use the snow optical properties and nitrate concentrations to calculate ultraviolet actinic flux in snow and the production of Nr from the photolysis of snow nitrate. The observed δ15N(NO3-) is used to constrain modeled fractional loss of snow nitrate in a snow chemistry column model, and thus the source of Nr to the overlying boundary layer. Snow-surface δ15N(NO3-) measurements range from -5 to 10 ‰ and suggest that the local nitrate burden in the Uintah Basin is dominated by primary emissions from anthropogenic sources, except during fresh snowfall events, where remote NOx sources from beyond the basin are dominant. Modeled daily averaged snow-sourced Nr fluxes range from 5.6 to 71 × 107 molec cm-2 s-1 over the course of the field campaign, with a maximum noontime value of 3.1 × 109 molec cm-2 s-1. The top-down emission estimate of primary, anthropogenic NOx in Uintah and Duchesne counties is at least 300 times higher than the estimated snow NOx emissions presented in this study. Our results suggest that snow-sourced reactive nitrogen fluxes are minor contributors to the Nr boundary layer budget in the highly polluted Uintah Basin boundary layer during winter 2014.

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

PubMed

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

2017-04-01

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

Research on snow cover monitoring of Northeast China using Fengyun Geostationary Satellite

NASA Astrophysics Data System (ADS)

Wu, Tong; Gu, Lingjia; Ren, Ruizhi; Zhou, TIngting

2017-09-01

Snow cover information has great significance for monitoring and preventing snowstorms. With the development of satellite technology, geostationary satellites are playing more important roles in snow monitoring. Currently, cloud interference is a serious problem for obtaining accurate snow cover information. Therefore, the cloud pixels located in the MODIS snow products are usually replaced by cloud-free pixels around the day, which ignores snow cover dynamics. FengYun-2(FY-2) is the first generation of geostationary satellite in our country which complements the polar orbit satellite. The snow cover monitoring of Northeast China using FY-2G data in January and February 2016 is introduced in this paper. First of all, geometric and radiometric corrections are carried out for visible and infrared channels. Secondly, snow cover information is extracted according to its characteristics in different channels. Multi-threshold judgment methods for the different land types and similarity separation techniques are combined to discriminate snow and cloud. Furthermore, multi-temporal data is used to eliminate cloud effect. Finally, the experimental results are compared with the MOD10A1 and MYD10A1 (MODIS daily snow cover) product. The MODIS product can provide higher resolution of the snow cover information in cloudless conditions. Multi-temporal FY-2G data can get more accurate snow cover information in cloudy conditions, which is beneficial for monitoring snowstorms and climate changes.

Advanced Multi-frequency Inversion Methods for Classifying Acoustic Scatterers

DTIC Science & Technology

2001-09-30

individual zooplankton taxa. For example, physonect siphonophore larvae with small gas­ filled pneumatophores (~0.20 mm) detected by the VPR appear...period. The white circles indicate the presence of physonect siphonophore larvae detected by the VPR. Note the coincidence of the distributions of...these organisms and layers of elevated scattering. The high scattering in the vicinity of siphonophore larvae at 43 kHz is believed to be an artifact

Modelling the backscatter from spherical cavities in a solid matrix: Can an effective medium layer model mimic the scattering response?

NASA Astrophysics Data System (ADS)

Pinfield, Valerie J.; Challis, Richard E.

2011-01-01

Industrial applications are increasingly turning to modern composite layered materials to satisfy strength requirements whilst reducing component weight. An important group of such materials are fibre/resin composites in which long fibres are laid down in layers in a resin matrix. Whilst delamination flaws, where layers separate from each other, are detectable using traditional ultrasonic techniques, the presence of porosity in any particular layer is harder to detect. The reflected signal from a layered material can already be modelled successfully by using the acoustic impedance of the layers and summing reflections from layer boundaries. However, it is not yet known how to incorporate porosity into such a model. The aim of the work reported here was to model the backscatter from randomly distributed spherical cavities within one layer, and to establish whether an effective medium, with a derived acoustic impedance, could reproduce the characteristics of that scattering. Since effective medium models are much more readily implemented in simulations of multi-layer structures than scattering per se, it was felt desirable to simplify the scattering response into an effective medium representation. A model was constructed in which spherical cavities were placed randomly in a solid continuous matrix and the system backscattering response was calculated. The scattering from the cavities was determined by using the Rayleigh partial-wave method, and taking the received signal at the transducer to be equivalent to the far field limit. It was concluded that even at relatively low porosity levels, the received signal was still "layer-like" and an effective medium model was a good approximation for the scattering behaviour.

Mesoporous multi-shelled ZnO microspheres for the scattering layer of dye sensitized solar cell with a high efficiency

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

Xia, Weiwei; Mei, Chao; Zeng, Xianghua, E-mail: xhzeng@yzu.edu.cn

2016-03-14

Both light scattering and dye adsorbing are important for the power conversion efficiency PCE performance of dye sensitized solar cell (DSSC). Nanostructured scattering layers with a large specific surface area are regarded as an efficient way to improve the PCE by increasing dye adsorbing, but excess adsorbed dye will hinder light scattering and light penetration. Thus, how to balance the dye adsorbing and light penetration is a key problem to improve the PCE performance. Here, multiple-shelled ZnO microspheres with a mesoporous surface are fabricated by a hydrothermal method and are used as scattering layers on the TiO{sub 2} photoanode ofmore » the DSSC in the presence of N719 dye and iodine–based electrolyte, and the results reveal that the DSSCs based on triple shelled ZnO microsphere with a mesoporous surface exhibit an enhanced PCE of 7.66%, which is 13.0% higher than those without the scattering layers (6.78%), indicating that multiple-shelled microspheres with a mesoporous surface can ensure enough light scattering between the shells, and a favorable concentration of the adsorbed dye can improve the light penetration. These results may provide a promising pathway to obtain the high efficient DSSCs.« less

[Effects of snow pack on soil nitrogen transformation enzyme activities in a subalpine Abies faxioniana forest of western Sichuan, China].

PubMed

Xiong, Li; Xu, Zhen-Feng; Wu, Fu-Zhong; Yang, Wan-Qin; Yin, Rui; Li, Zhi-Ping; Gou, Xiao-Lin; Tang, Shi-Shan

2014-05-01

This study characterized the dynamics of the activities of urease, nitrate reductase and nitrite reductase in both soil organic layer and mineral soil layer under three depths of snow pack (deep snowpack, moderate snowpack and shallow snowpack) over the three critical periods (snow formed period, snow stable period, and snow melt period) in the subalpine Abies faxoniana forest of western Sichuan in the winter of 2012 and 2013. Throughout the winter, soil temperature under deep snowpack increased by 46.2% and 26.2%, respectively in comparison with moderate snowpack and shallow snowpack. In general, the three nitrogen-related soil enzyme activities under shallow snowpack were 0.8 to 3.9 times of those under deep snowpack during the winter. In the beginning and thawing periods of seasonal snow pack, shallow snowpack significantly increased the activities of urease, nitrate and nitrite reductase enzyme in both soil organic layer and mineral soil layer. Although the activities of the studied enzymes in soil organic layer and mineral soil layer were observed to be higher than those under deep- and moderate snowpacks in deep winter, no significant difference was found under the three snow packs. Meanwhile, the effects of snowpack on the activities of the measured enzymes were related with season, soil layer and enzyme type. Significant variations of the activities of nitrogen-related enzymes were found in three critical periods over the winter, and the three measured soil enzymes were significantly higher in organic layer than in mineral layer. In addition, the activities of the three measured soil enzymes were closely related with temperature and moisture in soils. In conclusion, the decrease of snow pack induced by winter warming might increase the activities of soil enzymes related with nitrogen transformation and further stimulate the process of wintertime nitrogen transformation in soils of the subalpine forest.

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

NASA Astrophysics Data System (ADS)

Armstrong, Richard L.; Brodzik, Mary Jo

2003-04-01

Snow cover is an important variable for climate and hydrologic models due to its effects on energy and moisture budgets. Seasonal snow can cover more than 50% of the Northern Hemisphere land surface during the winter resulting in snow cover being the land surface characteristic responsible for the largest annual and interannual differences in albedo. Passive microwave satellite remote sensing can augment measurements based on visible satellite data alone because of the ability to acquire data through most clouds or during darkness as well as to provide a measure of snow depth or water equivalent. It is now possible to monitor the global fluctuation of snow cover over a 24 year period using passive microwave data (Scanning Multichannel Microwave Radiometer (SMMR) 1978-1987 and Special Sensor Microwave/Imager (SSM/I), 1987-present). Evaluation of snow extent derived from passive microwave algorithms is presented through comparison with the NOAA Northern Hemisphere snow extent data. For the period 1978 to 2002, both passive microwave and visible data sets show a smiliar pattern of inter-annual variability, although the maximum snow extents derived from the microwave data are consistently less than those provided by the visible statellite data and the visible data typically show higher monthly variability. During shallow snow conditions of the early winter season microwave data consistently indicate less snow-covered area than the visible data. This underestimate of snow extent results from the fact that shallow snow cover (less than about 5.0 cm) does not provide a scattering signal of sufficient strength to be detected by the algorithms. As the snow cover continues to build during the months of January through March, as well as on into the melt season, agreement between the two data types continually improves. This occurs because as the snow becomes deeper and the layered structure more complex, the negative spectral gradient driving the passive microwave algorithm is enhanced. Trends in annual averages are similar, decreasing at rates of approximately 2% per decade. The only region where the passive microwave data consistently indicate snow and the visible data do not is over the Tibetan Plateau and surrounding mountain areas. In the effort to determine the accuracy of the microwave algorithm over this region we are acquiring surface snow observations through a collaborative study with CAREERI/Lanzhou. In order to provide an optimal snow cover product in the future, we are developing a procedure that blends snow extent maps derived from MODIS data with snow water equivalent maps derived from both SSM/I and AMSR.

Effect of Microstructure on Diffusional Solidification of 4343/3005/4343 Multi-Layer Aluminum Brazing Sheet

NASA Astrophysics Data System (ADS)

Tu, Yiyou; Tong, Zhen; Jiang, Jianqing

2013-04-01

The effect of microstructure on clad/core interactions during the brazing of 4343/3005/4343 multi-layer aluminum brazing sheet was investigated employing differential scanning calorimetry (DSC) and electron back-scattering diffraction (EBSD). The thickness of the melted clad layer gradually decreased during the brazing operation. It could be completely removed isothermally as a result of diffusional solidification at the brazing temperature. During the brazing cycle, the rate of loss of the melt in the brazing sheet, with small equiaxed grains' core layer, was higher than that with the core layer consisting of elongated large grains. The difference in microstructure affected the amount of liquid formed during brazing.

New Perspectives on Blowing Snow Transport, Sublimation, and Layer Thermodynamic Structure over Antarctica

NASA Technical Reports Server (NTRS)

Palm, Steve; Kayetha, Vinay; Yang, Yuekui; Pauly, Rebecca M.

2017-01-01

Blowing snow over Antarctica is a widespread and frequent event. Satellite remote sensing using lidar has shown that blowing snow occurs over 70% of the time over large areas of Antarctica in winter. The transport and sublimation of blowing snow are important terms in the ice sheet mass balance equation and the latter is also an important part of the hydrological cycle. Until now the only way to estimate the magnitude of these processes was through model parameterization. We present a technique that uses direct satellite observations of blowing snow and model (MERRA-2) temperature and humidity fields to compute both transport and sublimation of blowing snow over Antarctica for the period 2006 to 2016. The results show a larger annual continent-wide integrated sublimation than current published estimates and a significant transport of snow from continent to ocean. The talk will also include the lidar backscatter structure of blowing snow layers that often reach heights of 200 to 300 m as well as the first dropsonde measurements of temperature, moisture and wind through blowing snow layers.

Estimation of snow in extratropical cyclones from multiple frequency airborne radar observations. An Expectation-Maximization approach

NASA Astrophysics Data System (ADS)

Grecu, M.; Tian, L.; Heymsfield, G. M.

2017-12-01

A major challenge in deriving accurate estimates of physical properties of falling snow particles from single frequency space- or airborne radar observations is that snow particles exhibit a large variety of shapes and their electromagnetic scattering characteristics are highly dependent on these shapes. Triple frequency (Ku-Ka-W) radar observations are expected to facilitate the derivation of more accurate snow estimates because specific snow particle shapes tend to have specific signatures in the associated two-dimensional dual-reflectivity-ratio (DFR) space. However, the derivation of accurate snow estimates from triple frequency radar observations is by no means a trivial task. This is because the radar observations can be subject to non-negligible attenuation (especially at W-band when super-cooled water is present), which may significantly impact the interpretation of the information in the DFR space. Moreover, the electromagnetic scattering properties of snow particles are computationally expensive to derive, which makes the derivation of reliable parameterizations usable in estimation methodologies challenging. In this study, we formulate an two-step Expectation Maximization (EM) methodology to derive accurate snow estimates in Extratropical Cyclones (ECTs) from triple frequency airborne radar observations. The Expectation (E) step consists of a least-squares triple frequency estimation procedure applied with given assumptions regarding the relationships between the density of snow particles and their sizes, while the Maximization (M) step consists of the optimization of the assumptions used in step E. The electromagnetic scattering properties of snow particles are derived using the Rayleigh-Gans approximation. The methodology is applied to triple frequency radar observations collected during the Olympic Mountains Experiment (OLYMPEX). Results show that snowfall estimates above the freezing level in ETCs consistent with the triple frequency radar observations as well as with independent rainfall estimates below the freezing level may be derived using the EM methodology formulated in the study.

An Inexpensive, Implantable Electronic Sensor for Autonomous Measurement of Snow Pack Parameters

NASA Astrophysics Data System (ADS)

De Roo, R. D.; Haengel, E.; Rogacki, S.

2015-12-01

Snow accumulations on the ground are an important source of water in many parts of the world. Mapping the accumulation, usually represented as the snow water equivalent (SWE), is valuable for water resource management. The longest record of regional and global maps of SWE are from orbiting microwave radiometers, which do not directly measure SWE but rather measure the scatter darkening from the snow pack. Robustly linking the scatter darkening to SWE eludes us to this day, in part because the snow pack is highly variable in both time and space. The data needed is currently collected by hand in "snow pits," and the labor-intensive process limits the size of the data sets that can be obtained. In particular, time series measurements are only a one or two samples per day at best, and come at the expense of spatial sampling. We report on the development of a low-power wireless device that can be embedded within a snow pack to report on some of the critical parameters needed to understand scatter darkening. The device autonomously logs temperature, the microwave dielectric constant and infrared backscatter local to the device. The microwave dielectric constant reveals the snow density and the presence of liquid water, while the infrared backscatter measurement, together with the density measurement, reveals a characteristic grain size of the snow pack. The devices are made to be inexpensive (less than $200 in parts each) and easily replicated, so that many can be deployed to monitor variations vertically and horizontally in the snow pack. The low-power operation is important both for longevity of observations as well as insuring minimal anomalous metamorphism of the snow pack. The hardware required for the microwave measurement is intended for wireless communications, and this feature will soon be implemented for near real-time monitoring of snow conditions. We will report on the design, construction and initial deployment of about 30 of these devices in northern lower Michigan, and, data permitting, on the measurements that these novel devices have acquired.

Snow stratigraphic heterogeneity within ground-based passive microwave radiometer footprints: Implications for emission modeling

NASA Astrophysics Data System (ADS)

Rutter, Nick; Sandells, Mel; Derksen, Chris; Toose, Peter; Royer, Alain; Montpetit, Benoit; Langlois, Alex; Lemmetyinen, Juha; Pulliainen, Jouni

2014-03-01

Two-dimensional measurements of snowpack properties (stratigraphic layering, density, grain size, and temperature) were used as inputs to the multilayer Helsinki University of Technology (HUT) microwave emission model at a centimeter-scale horizontal resolution, across a 4.5 m transect of ground-based passive microwave radiometer footprints near Churchill, Manitoba, Canada. Snowpack stratigraphy was complex (between six and eight layers) with only three layers extending continuously throughout the length of the transect. Distributions of one-dimensional simulations, accurately representing complex stratigraphic layering, were evaluated using measured brightness temperatures. Large biases (36 to 68 K) between simulated and measured brightness temperatures were minimized (-0.5 to 0.6 K), within measurement accuracy, through application of grain scaling factors (2.6 to 5.3) at different combinations of frequencies, polarizations, and model extinction coefficients. Grain scaling factors compensated for uncertainty relating optical specific surface area to HUT effective grain size inputs and quantified relative differences in scattering and absorption properties of various extinction coefficients. The HUT model required accurate representation of ice lenses, particularly at horizontal polarization, and large grain scaling factors highlighted the need to consider microstructure beyond the size of individual grains. As variability of extinction coefficients was strongly influenced by the proportion of large (hoar) grains in a vertical profile, it is important to consider simulations from distributions of one-dimensional profiles rather than single profiles, especially in sub-Arctic snowpacks where stratigraphic variability can be high. Model sensitivity experiments suggested that the level of error in field measurements and the new methodological framework used to apply them in a snow emission model were satisfactory. Layer amalgamation showed that a three-layer representation of snowpack stratigraphy reduced the bias of a one-layer representation by about 50%.

Building the GPM-GV Column from the GPM Cold season Precipitation Experiment (Invited)

NASA Astrophysics Data System (ADS)

Nesbitt, S. W.; Duffy, G. A.; Gleicher, K.; McFarquhar, G. M.; Kulie, M.; Williams, C. R.; Petersen, W. A.; Munchak, S. J.; Tokay, A.; Skofronick Jackson, G.; Chandrasekar, C. V.; Kollias, P.; Hudak, D. R.; Tanelli, S.

2013-12-01

Within the context of the Drop Size Distribution Working Group (DSDWG) of the Global Precipitation Mission-Ground Validation (GPM-GV) program, a major science and satellite precipitation algorithm validation focus is on quantitatively determining the variability of microphysical properties of precipitation in the vertical column, as well as the radiative properties of those particles at GPM-relevant microwave frequencies. The GPM Cold season Precipitation Experiment, or GCPEx, was conducted to address both of these objectives in mid-latitude winter precipitation. Radar observations at C, X, Ku, Ka, and W band from ground based scanning radars, profiling radars, and aircraft, as well as an aircraft passive microwave imager from GCPEx, conducted in early 2012 near Barrie, Ontario, Canada, can be used to constrain the observed reflectivites and brightness temperatures in snow as well as construct radar dual frequency ratios (DFRs) that can be used to identify regimes of microwave radiative properties in observed hydrometeor columns. These data can be directly matched with aircraft and ground based in situ microphysical probes, such as 2-D and bulk aircraft probes and surface disdrometers, to place the microphysical and microwave scattering and emission properties of the snow in context throughout the column of hydrometeors. In this presentation, particle scattering regimes will be identified in GCPEx hydrometeor columns storm events using a clustering technique in a multi-frequency DFR-near Rayleigh radar reflectivity phase space using matched ground-based and aircraft-based radar and passive microwave data. These data will be interpreted using matched in situ disdrometer and aircraft probe microphysical data (particle size distributions, habit identification, fall speed, mass-diameter relationships) derived during the events analyzed. This database is geared towards evaluating scattering simulations and the choice of integral particle size distributions for snow precipitation retrieval algorithms for ground and spaceborne radars at relevant wavelengths. A comparison of results for different cases with varying synoptic forcing and microphysical evolution will be presented.

Satellite Estimation of Spectral Surface UV Irradiance. 2; Effect of Horizontally Homogeneous Clouds

NASA Technical Reports Server (NTRS)

Krothov, N.; Herman, J. R.; Bhartia, P. K.; Ahmad, Z.a; Fioletov, V.

1998-01-01

The local variability of UV irradiance at the Earth's surface is mostly caused by clouds in addition to the seasonal variability. Parametric representations of radiative transfer RT calculations are presented for the convenient solution of the transmission T of ultraviolet radiation through plane parallel clouds over a surface with reflectivity R(sub s). The calculations are intended for use with the Total Ozone Mapping Spectrometer (TOMS) measured radiances to obtain the calculated Lambert equivalent scene reflectivity R for scenes with and without clouds. The purpose is to extend the theoretical analysis of the estimation of UV irradiance from satellite data for a cloudy atmosphere. Results are presented for a range of cloud optical depths and solar zenith angles for the cases of clouds over a low reflectivity surface R(sub s) less than 0.1, over a snow or ice surface R(sub s) greater than 0.3, and for transmission through a non-conservative scattering cloud with single scattering albedo omega(sub 0) = 0.999. The key finding for conservative scattering is that the cloud-transmission function C(sub T), the ratio of cloudy-to clear-sky transmission, is roughly C(sub T) = 1 - R(sub c) with an error of less than 20% for nearly overhead sun and snow-free surfaces. For TOMS estimates of UV irradiance in the presence of both snow and clouds, independent information about snow albedo is needed for conservative cloud scattering. For non-conservative scattering with R(sub s) greater than 0.5 (snow) the satellite measured scene reflectance cannot be used to estimate surface irradiance. The cloud transmission function has been applied to the calculation of UV irradiance at the Earth's surface and compared with ground-based measurements.

The Microwave Radiative Properties of Falling Snow Derived from Nonspherical Ice Particle Models. Part II: Initial Testing Using Radar, Radiometer and In Situ Observations

NASA Technical Reports Server (NTRS)

Olson, William S.; Tian, Lin; Grecu, Mircea; Kuo, Kwo-Sen; Johnson, Benjamin; Heymsfield, Andrew J.; Bansemer, Aaron; Heymsfield, Gerald M.; Wang, James R.; Meneghini, Robert

2016-01-01

In this study, two different particle models describing the structure and electromagnetic properties of snow are developed and evaluated for potential use in satellite combined radar-radiometer precipitation estimation algorithms. In the first model, snow particles are assumed to be homogeneous ice-air spheres with single-scattering properties derived from Mie theory. In the second model, snow particles are created by simulating the self-collection of pristine ice crystals into aggregate particles of different sizes, using different numbers and habits of the collected component crystals. Single-scattering properties of the resulting nonspherical snow particles are determined using the discrete dipole approximation. The size-distribution-integrated scattering properties of the spherical and nonspherical snow particles are incorporated into a dual-wavelength radar profiling algorithm that is applied to 14- and 34-GHz observations of stratiform precipitation from the ER-2 aircraft-borne High-Altitude Imaging Wind and Rain Airborne Profiler (HIWRAP) radar. The retrieved ice precipitation profiles are then input to a forward radiative transfer calculation in an attempt to simulate coincident radiance observations from the Conical Scanning Millimeter-Wave Imaging Radiometer (CoSMIR). Much greater consistency between the simulated and observed CoSMIR radiances is obtained using estimated profiles that are based upon the nonspherical crystal/aggregate snow particle model. Despite this greater consistency, there remain some discrepancies between the higher moments of the HIWRAP-retrieved precipitation size distributions and in situ distributions derived from microphysics probe observations obtained from Citation aircraft underflights of the ER-2. These discrepancies can only be eliminated if a subset of lower-density crystal/aggregate snow particles is assumed in the radar algorithm and in the interpretation of the in situ data.

Crevasse detection with GPR across the Ross Ice Shelf, Antarctica

NASA Astrophysics Data System (ADS)

Delaney, A.; Arcone, S.

2005-12-01

We have used 400-MHz ground penetrating radar (GPR) to detect crevasses within a shear zone on the Ross Ice Shelf, Antarctica, to support traverse operations. The transducer was attached to a 6.5-m boom and pushed ahead of an enclosed tracked vehicle. Profile speeds of 4.8-11.3 km / hr allowed real-time crevasse image display and a quick, safe stop when required. Thirty-two crevasses were located with radar along the 4.8 km crossing. Generally, crevasse radar images were characterized by dipping reflections above the voids, high-amplitude reflections originating from ice layers at the base of the snow-bridges, and slanting, diffracting reflections from near-vertical crevasse walls. New cracks and narrow crevasses (<50 cm width) show no distinct snow bridge structure, few diffractions, and a distinct band where pulse reflections are absent. Wide (0.5-5.0 m), vertical wall crevasses show distinct dipping snow bridge layering and intense diffractions from ice layers near the base of the snow bridge. Pulse reflections are absent from voids beneath the snow bridges. Old, wide (3.0-8.0 m) and complexly shaped crevasses show well-developed, broad, dipping snow-bridge layers and a high-amplitude, complex, diffraction pattern. The crevasse mitigation process, which included hot-water drilling, destroying the bridges with dynamite, and back-filling with bulldozed snow, afforded an opportunity to ground-truth GPR interpretations by comparing void size and snow-bridge geometry with the radar images. While second and third season radar profiles collected along the identical flagged route confirmed stability of the filled crevasses, those profiles also identified several new cracks opened by ice extension. Our experiments demonstrate capability of high-frequency GPR in a cold-snow environment for both defining snow layers and locating voids.

Measuring Geophysical Parameters of the Greenland Ice Sheet using Airborne Radar Altimetry

NASA Technical Reports Server (NTRS)

Ferraro, Ellen J.; Swift. Calvin T.

1995-01-01

This paper presents radar-altimeter scattering models for each of the diagenetic zones of the Greenland ice sheet. AAFE radar- altimeter waveforms obtained during the 1991 and 1993 NASA multi-sensor airborne altimetry experiments over Greenland reveal that the Ku-band return pulse changes significantly with the different diagenetic zones. These changes are due to varying amounts of surface and volume scattering in the return waveform. In the ablation and soaked zones, where surface scattering dominates the AAFE return, geophysical parameters such as rms surface height and rms surface slope are obtained by fitting the waveforms to a surface-scattering model. Waveforms from the percolation zone show that the sub-surface ice features have a much more significant effect on the return pulse than the surrounding snowpack. Model percolation waveforms, created using a combined surface- and volume-scattering model and an ice-feature distribution obtained during the 1993 field season, agree well with actual AAFE waveforms taken in the same time period. Using a combined surface- and volume-scattering model for the dry-snow-zone return waveforms, the rms surface height and slope and the attenuation coefficient of the snowpack are obtained. These scattering models not only allow geophysical parameters of the ice sheet to be measured but also help in the understanding of satellite radar-altimeter data.

Optical and structural characterization of Ge clusters embedded in ZrO2

NASA Astrophysics Data System (ADS)

Agocs, E.; Zolnai, Z.; Rossall, A. K.; van den Berg, J. A.; Fodor, B.; Lehninger, D.; Khomenkova, L.; Ponomaryov, S.; Gudymenko, O.; Yukhymchuk, V.; Kalas, B.; Heitmann, J.; Petrik, P.

2017-11-01

The change of optical and structural properties of Ge nanoclusters in ZrO2 matrix have been investigated by spectroscopic ellipsometry versus annealing temperatures. Radio-frequency top-down magnetron sputtering approach was used to produce the samples of different types, i.e. single-layers of pure Ge, pure ZrO2 and Ge-rich-ZrO2 as well as multi-layers stacked of 40 periods of 5-nm-Ge-rich-ZrO2 layers alternated by 5-nm-ZrO2 ones. Germanium nanoclusters in ZrO2 host were formed by rapid-thermal annealing at 600-800 °C during 30 s in nitrogen atmosphere. Reference optical properties for pure ZrO2 and pure Ge have been extracted using single-layer samples. As-deposited multi-layer structures can be perfectly modeled using the effective medium theory. However, annealed multi-layers demonstrated a significant diffusion of elements that was confirmed by medium energy ion scattering measurements. This fact prevents fitting of such annealed structure either by homogeneous or by periodic multi-layer models.

Handheld microwave bomb-detecting imaging system

NASA Astrophysics Data System (ADS)

Gorwara, Ashok; Molchanov, Pavlo

2017-05-01

Proposed novel imaging technique will provide all weather high-resolution imaging and recognition capability for RF/Microwave signals with good penetration through highly scattered media: fog, snow, dust, smoke, even foliage, camouflage, walls and ground. Image resolution in proposed imaging system is not limited by diffraction and will be determined by processor and sampling frequency. Proposed imaging system can simultaneously cover wide field of view, detect multiple targets and can be multi-frequency, multi-function. Directional antennas in imaging system can be close positioned and installed in cell phone size handheld device, on small aircraft or distributed around protected border or object. Non-scanning monopulse system allows dramatically decrease in transmitting power and at the same time provides increased imaging range by integrating 2-3 orders more signals than regular scanning imaging systems.

Comparison of Bi-directional Reflectance Distribution Functions of Black Spruce Forest in Snow and No-snow Seasons in Alaska

NASA Astrophysics Data System (ADS)

Suzuki, R.; Nagai, S.; Nakai, T.; Kim, Y.

2011-12-01

The Bidirectional Reflectance Distribution Function (BRDF) of the forest is an important clue for remote sensing to reveal the forest structure such as Leaf Area Index (LAI) and above-ground biomass. The BRDF is required for the robust development of forest radiative transfer model, which is applied to the forest structure analysis based on satellite data. To acquire in-situ BRDF of the forest, we carried out the field survey of BRDFs at a boreal forest in no-snow season (July 2010) and snow season (March 2011) in Alaska, and compared them. A black spruce forest, a typical boreal evergreen forest in Alaska, located in the Poker Flat Research Range of University of Alaska Fairbanks (65 07'24"N, 147 29'15"W, 210 m MSL) was targeted. Since the forest homogeneously extends about 500 m wide and the terrain is relatively even, this forest site is highly suitable for the validation of the remote sensing measurement. The tree stand density was about 4000 tree/ha, and the highest tree was 6.4 m. The forest floor is covered by the green vegetation such as moss and grass in summer, while the vegetation on the floor is completely covered by snow during winter and early spring. The observations of the BRDF taken place around the noon of July 7 and 8, 2010 (no-snow season) and March 16 and 17, 2011 (snow season) from the top of the tower (17 m) constructed in the forest. We measured the reflected irradiance from the forest by the spectroradiometer (MS-720; EKO Instruments) changing the viewing angle from 20 to 70 degrees and -20 to -70 degrees(off-nadir angle; positive and negative angles mean forward and back scatter angles, respectively) with 5 degrees interval in the principal plane. Irradiances in the orthogonal (cross) plane were also measured in the same manner. The global radiation was simultaneously measured by the other spectroradiometer for the calculation of the reflectance. The BRDF in the principal plane in the no-snow season showed a kind of bowl-shape distribution with its minimum and maximum at approximately 30 and -70 degrees in visible and near-infrared bands, respectively, that is, the forward scatter was generally smaller than the back scatter. By contrast, in the snow season, the back scatter was generally smaller than the forward scatter, that is, the reverse of that in the no-snow season. These results will be used for the development of the forest radiative transfer model aimed to evaluate the forest biodiversity and ecosystem functions.

Multi-hybrid method for investigation of EM scattering from inhomogeneous object above a dielectric rough surface

NASA Astrophysics Data System (ADS)

Li, Jie; Guo, LiXin; He, Qiong; Wei, Bing

2012-10-01

An iterative strategy combining Kirchhoff approximation^(KA) with the hybrid finite element-boundary integral (FE-BI) method is presented in this paper to study the interactions between the inhomogeneous object and the underlying rough surface. KA is applied to study scattering from underlying rough surfaces, whereas FE-BI deals with scattering from the above target. Both two methods use updated excitation sources. Huygens equivalence principle and an iterative strategy are employed to consider the multi-scattering effects. This hybrid FE-BI-KA scheme is an improved and generalized version of previous hybrid Kirchhoff approximation-method of moments (KA-MoM). This newly presented hybrid method has the following advantages: (1) the feasibility of modeling multi-scale scattering problems (large scale underlying surface and small scale target); (2) low memory requirement as in hybrid KA-MoM; (3) the ability to deal with scattering from inhomogeneous (including coated or layered) scatterers above rough surfaces. The numerical results are given to evaluate the accuracy of the multi-hybrid technique; the computing time and memory requirements consumed in specific numerical simulation of FE-BI-KA are compared with those of MoM. The convergence performance is analyzed by studying the iteration number variation caused by related parameters. Then bistatic scattering from inhomogeneous object of different configurations above dielectric Gaussian rough surface is calculated and the influences of dielectric compositions and surface roughness on the scattering pattern are discussed.

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

NASA Technical Reports Server (NTRS)

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

2000-01-01

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

Heterogeneous multi-layered IF steel with simultaneous high strength and good ductility

NASA Astrophysics Data System (ADS)

Zhang, Ling; Jiang, Xiaojuan; Wang, Yuhui; Chen, Qiang; Chen, Zhen; Zhang, Yonghong; Huang, Tianlin; Wu, Guilin

2017-07-01

Multi-layered IF steel samples were designed and fabricated by hot compression followed by cold forging of an alternating stack of cold-rolled and annealed IF steel sheets, with an aim to improve the strength of the material without losing much ductility. A very good combination of strength and ductility was achieved by proper annealing after deformation. Microstructural analysis by electron back-scatter diffraction revealed that the good combination of strength and ductility is related to a characteristic hierarchical structure that is characterized by layered and lamella structures with different length scales.

A model of the planetary boundary layer over a snow surface

NASA Technical Reports Server (NTRS)

Halberstam, I.; Melendez, R.

1979-01-01

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

Microwave Observations of Snow-Covered Freshwater Lake Ice obtained during the Great Lakes Winter EXperiment (GLAWEX), 2017

NASA Astrophysics Data System (ADS)

Gunn, G. E.; Hall, D. K.; Nghiem, S. V.

2017-12-01

Studies observing lake ice using active microwave acquisitions suggest that the dominant scattering mechanism in ice is caused by double-bounce of the signal off vertical tubular bubble inclusions. Recent polarimetric SAR observations and target decomposition algorithms indicate single-bounce interactions may be the dominant source of returns, and in the absence of field observations, has been hypothesized to be the result of roughness at the ice-water interface on the order of incident wavelengths. This study presents in-situ physical observations of snow-covered lake ice in western Michigan and Wisconsin acquired during the Great Lakes Winter EXperiment in 2017 (GLAWEX'17). In conjunction with NASA's SnowEx airborne snow campaign in Colorado (http://snow.nasa.gov), C- (Sentinel-1, RADARSAT-2) and X-band (TerraSAR-X) synthetic aperture radar (SAR) observations were acquired coincidently to surface physical snow and ice observations. Small/large scale roughness features at the ice-water interface are quantified through auger transects and used as an input variable in lake ice backscatter models to assess the relative contributions from different scattering mechanisms.

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.

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

NASA Astrophysics Data System (ADS)

Zhou, J.

2017-12-01

Snow and frozen soil are important components in the Tibetan Plateau, and influence the water cycle and energy balances through snowpack accumulation and melt and soil freeze-thaw. In this study, a new cryosphere land surface model (LSM) with coupled snow and frozen soil parameterization was developed based on a hydrologically improved LSM (HydroSiB2). First, an energy-balance-based three-layer snow model was incorporated into HydroSiB2 (hereafter HydroSiB2-S) to provide an improved description of the internal processes of the snow pack. Second, a universal and simplified soil model was coupled with HydroSiB2-S to depict soil water freezing and thawing (hereafter HydroSiB2-SF). In order to avoid the instability caused by the uncertainty in estimating water phase changes, enthalpy was adopted as a prognostic variable instead of snow/soil temperature in the energy balance equation of the snow/frozen soil module. The newly developed models were then carefully evaluated at two typical sites of the Tibetan Plateau (TP) (one snow covered and the other snow free, both with underlying frozen soil). At the snow-covered site in northeastern TP (DY), HydroSiB2-SF demonstrated significant improvements over HydroSiB2-F (same as HydroSiB2-SF but using the original single-layer snow module of HydroSiB2), showing the importance of snow internal processes in three-layer snow parameterization. At the snow-free site in southwestern TP (Ngari), HydroSiB2-SF reasonably simulated soil water phase changes while HydroSiB2-S did not, indicating the crucial role of frozen soil parameterization in depicting the soil thermal and water dynamics. Finally, HydroSiB2-SF proved to be capable of simulating upward moisture fluxes toward the freezing front from the underlying soil layers in winter.

Development of a land surface model with coupled snow and frozen soil physics

NASA Astrophysics Data System (ADS)

Wang, Lei; Zhou, Jing; Qi, Jia; Sun, Litao; Yang, Kun; Tian, Lide; Lin, Yanluan; Liu, Wenbin; Shrestha, Maheswor; Xue, Yongkang; Koike, Toshio; Ma, Yaoming; Li, Xiuping; Chen, Yingying; Chen, Deliang; Piao, Shilong; Lu, Hui

2017-06-01

Snow and frozen soil are important factors that influence terrestrial water and energy balances through snowpack accumulation and melt and soil freeze-thaw. In this study, a new land surface model (LSM) with coupled snow and frozen soil physics was developed based on a hydrologically improved LSM (HydroSiB2). First, an energy-balance-based three-layer snow model was incorporated into HydroSiB2 (hereafter HydroSiB2-S) to provide an improved description of the internal processes of the snow pack. Second, a universal and simplified soil model was coupled with HydroSiB2-S to depict soil water freezing and thawing (hereafter HydroSiB2-SF). In order to avoid the instability caused by the uncertainty in estimating water phase changes, enthalpy was adopted as a prognostic variable instead of snow/soil temperature in the energy balance equation of the snow/frozen soil module. The newly developed models were then carefully evaluated at two typical sites of the Tibetan Plateau (TP) (one snow covered and the other snow free, both with underlying frozen soil). At the snow-covered site in northeastern TP (DY), HydroSiB2-SF demonstrated significant improvements over HydroSiB2-F (same as HydroSiB2-SF but using the original single-layer snow module of HydroSiB2), showing the importance of snow internal processes in three-layer snow parameterization. At the snow-free site in southwestern TP (Ngari), HydroSiB2-SF reasonably simulated soil water phase changes while HydroSiB2-S did not, indicating the crucial role of frozen soil parameterization in depicting the soil thermal and water dynamics. Finally, HydroSiB2-SF proved to be capable of simulating upward moisture fluxes toward the freezing front from the underlying soil layers in winter.

Polarimetric Signatures of Sea Ice. Part 1; Theoretical Model

NASA Technical Reports Server (NTRS)

Nghiem, S. V.; Kwok, R.; Yueh, S. H.; Drinkwater, M. R.

1995-01-01

Physical, structural, and electromagnetic properties and interrelating processes in sea ice are used to develop a composite model for polarimetric backscattering signatures of sea ice. Physical properties of sea ice constituents such as ice, brine, air, and salt are presented in terms of their effects on electromagnetic wave interactions. Sea ice structure and geometry of scatterers are related to wave propagation, attenuation, and scattering. Temperature and salinity, which are determining factors for the thermodynamic phase distribution in sea ice, are consistently used to derive both effective permittivities and polarimetric scattering coefficients. Polarimetric signatures of sea ice depend on crystal sizes and brine volumes, which are affected by ice growth rates. Desalination by brine expulsion, drainage, or other mechanisms modifies wave penetration and scattering. Sea ice signatures are further complicated by surface conditions such as rough interfaces, hummocks, snow cover, brine skim, or slush layer. Based on the same set of geophysical parameters characterizing sea ice, a composite model is developed to calculate effective permittivities and backscattering covariance matrices at microwave frequencies for interpretation of sea ice polarimetric signatures.

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.

Continuous Estimates of Surface Density and Annual Snow Accumulation with Multi-Channel Snow/Firn Penetrating Radar in the Percolation Zone, Western Greenland Ice Sheet

NASA Astrophysics Data System (ADS)

Meehan, T.; Marshall, H. P.; Bradford, J.; Hawley, R. L.; Osterberg, E. C.; McCarthy, F.; Lewis, G.; Graeter, K.

2017-12-01

A priority of ice sheet surface mass balance (SMB) prediction is ascertaining the surface density and annual snow accumulation. These forcing data can be supplied into firn compaction models and used to tune Regional Climate Models (RCM). RCMs do not accurately capture subtle changes in the snow accumulation gradient. Additionally, leading RCMs disagree among each other and with accumulation studies in regions of the Greenland Ice Sheet (GrIS) over large distances and temporal scales. RCMs tend to yield inconsistencies over GrIS because of sparse and outdated validation data in the reanalysis pool. Greenland Traverse for Accumulation and Climate Studies (GreenTrACS) implemented multi-channel 500 MHz Radar in multi-offset configuration throughout two traverse campaigns totaling greater than 3500 km along the western percolation zone of GrIS. The multi-channel radar has the capability of continuously estimating snow depth, average density, and annual snow accumulation, expressed at 95% confidence (+-) 0.15 m, (+-) 17 kgm-3, (+-) 0.04 m w.e. respectively, by examination of the primary reflection return from the previous year's summer surface.

Seabed roughness parameters from joint backscatter and reflection inversion at the Malta Plateau.

PubMed

Steininger, Gavin; Holland, Charles W; Dosso, Stan E; Dettmer, Jan

2013-09-01

This paper presents estimates of seabed roughness and geoacoustic parameters and uncertainties on the Malta Plateau, Mediterranean Sea, by joint Bayesian inversion of mono-static backscatter and spherical wave reflection-coefficient data. The data are modeled using homogeneous fluid sediment layers overlying an elastic basement. The scattering model assumes a randomly rough water-sediment interface with a von Karman roughness power spectrum. Scattering and reflection data are inverted simultaneously using a population of interacting Markov chains to sample roughness and geoacoustic parameters as well as residual error parameters. Trans-dimensional sampling is applied to treat the number of sediment layers and the order (zeroth or first) of an autoregressive error model (to represent potential residual correlation) as unknowns. Results are considered in terms of marginal posterior probability profiles and distributions, which quantify the effective data information content to resolve scattering/geoacoustic structure. Results indicate well-defined scattering (roughness) parameters in good agreement with existing measurements, and a multi-layer sediment profile over a high-speed (elastic) basement, consistent with independent knowledge of sand layers over limestone.

Investigation of radar backscattering from second-year sea ice

NASA Technical Reports Server (NTRS)

Lei, Guang-Tsai; Moore, Richard K.; Gogineni, S. P.

1988-01-01

The scattering properties of second-year ice were studied in an experiment at Mould Bay in April 1983. Radar backscattering measurements were made at frequencies of 5.2, 9.6, 13.6, and 16.6 GHz for vertical polarization, horizontal polarization and cross polarizations, with incidence angles ranging from 15 to 70 deg. The results indicate that the second-year ice scattering characteristics were different from first-year ice and also different from multiyear ice. The fading properties of radar signals were studied and compared with experimental data. The influence of snow cover on sea ice can be evaluated by accounting for the increase in the number of independent samples from snow volume with respect to that for bare ice surface. A technique for calculating the snow depth was established by this principle and a reasonable agreement has been observed. It appears that this is a usable way to measure depth in snow or other snow-like media using radar.

A vector radiative transfer model for coupled atmosphere and ocean systems based on successive order of scattering method.

PubMed

Zhai, Peng-Wang; Hu, Yongxiang; Trepte, Charles R; Lucker, Patricia L

2009-02-16

A vector radiative transfer model has been developed for coupled atmosphere and ocean systems based on the Successive Order of Scattering (SOS) Method. The emphasis of this study is to make the model easy-to-use and computationally efficient. This model provides the full Stokes vector at arbitrary locations which can be conveniently specified by users. The model is capable of tracking and labeling different sources of the photons that are measured, e.g. water leaving radiances and reflected sky lights. This model also has the capability to separate florescence from multi-scattered sunlight. The delta - fit technique has been adopted to reduce computational time associated with the strongly forward-peaked scattering phase matrices. The exponential - linear approximation has been used to reduce the number of discretized vertical layers while maintaining the accuracy. This model is developed to serve the remote sensing community in harvesting physical parameters from multi-platform, multi-sensor measurements that target different components of the atmosphere-oceanic system.

Influence of multiple scattering on CloudSat measurements in snow: A model study

NASA Astrophysics Data System (ADS)

Matrosov, Sergey Y.; Battaglia, Alessandro

2009-06-01

The effects of multiple scattering on larger precipitating hydrometers have an influence on measurements of the spaceborne W-band (94 GHz) CloudSat radar. This study presents initial quantitative estimates of these effects in “dry” snow using radiative transfer calculations for appropriate snowfall models. It is shown that these effects become significant (i.e., greater than approximately 1 dB) when snowfall radar reflectivity factors are greater than about 10-15 dBZ. Reflectivity enhancement due to multiple scattering can reach 4-5 dB in heavier stratiform snowfalls. Multiple scattering effects counteract signal attenuation, so the observed CloudSat reflectivity factors in snowfall could be relatively close to the values that would be observed in the case of single scattering and the absence of attenuation.

Multi-layer coating of SiO2 nanoparticles to enhance light absorption by Si solar cells

NASA Astrophysics Data System (ADS)

Nam, Yoon-Ho; Um, Han-Don; Park, Kwang-Tae; Shin, Sun-Mi; Baek, Jong-Wook; Park, Min-Joon; Jung, Jin-Young; Zhou, Keya; Jee, Sang-Won; Guo, Zhongyi; Lee, Jung-Ho

2012-06-01

We found that multi-layer coating of a Si substrate with SiO2 dielectric nanoparticles (NPs) was an effective method to suppress light reflection by silicon solar cells. To suppress light reflection, two conditions are required for the coating: 1) The difference of refractive indexes between air and Si should be alleviated, and 2) the quarter-wavelength antireflection condition should be satisfied while avoiding intrinsic absorption loss. Light reflection was reduced due to destructive interference at certain wavelengths that depended on the layer thickness. For the same thickness dielectric layer, smaller NPs enhanced antireflectance more than larger NPs due to a decrease in scattering loss by the smaller NPs.

Regional Glacier Mapping by Combination of Dense Optical and SAR Satellite Image Time-Series

NASA Astrophysics Data System (ADS)

Winsvold, S. H.; Kääb, A.; Andreassen, L. M.; Nuth, C.; Schellenberger, T.; van Pelt, W.

2016-12-01

Near-future dense time series from both SAR (Sentinel-1A and B) and optical satellite sensors (Landsat 8, Sentinel-2A and B) will promote new multisensory time series applications for glacier mapping. We assess such combinations of optical and SAR data among others by 1) using SAR data to supplement optical time series that suffer from heavy cloud cover (chronological gap-filling), 2) merging the two data types based on stack statistics (Std.dev, Mean, Max. etc.), or 3) better explaining glacier facies patterns in SAR data using optical satellite images. As one example, summer SAR backscatter time series have been largely unexplored and even neglected in many glaciological studies due to the high content of liquid melt water on the ice surface and its intrusion in the upper part of the snow and firn. This water content causes strong specular scattering and absorption of the radar signal, and little energy is scattered back to the SAR sensor. We find in many scenes of a Sentinel-1 time series a significant temporal backscatter difference between the glacier ice surface and the seasonal snow as it melts up glacier. Even though both surfaces have typically wet conditions, we suggest that the backscatter difference is due to different roughness lengths of the two surfaces. Higher backscatter is found on the ice surface in the ablation area compared to the firn/seasonal snow surface. We find and present also other backscatter patterns in the Sentinel-1 time series related to glacier facies and weather events. For the Ny Ålesund area, Svalbard we use Radarsat-2 time series to explore the glacier backscatter conditions in a > 5 year period, discussing distinct temporal signals from among others refreezing of the firn in late autumn, or temporal lakes. All these examples are analyzed using the above 3 methods. By this multi-temporal and multi-sensor approach we also explore and describe the possible connection between combined SAR/optical time series and surface mass balance.

Temporal evolution of crack propagation propensity in snow in relation to slab and weak layer properties

NASA Astrophysics Data System (ADS)

Schweizer, Jürg; Reuter, Benjamin; van Herwijnen, Alec; Richter, Bettina; Gaume, Johan

2016-11-01

If a weak snow layer below a cohesive slab is present in the snow cover, unstable snow conditions can prevail for days or even weeks. We monitored the temporal evolution of a weak layer of faceted crystals as well as the overlaying slab layers at the location of an automatic weather station in the Steintälli field site above Davos (Eastern Swiss Alps). We focussed on the crack propagation propensity and performed propagation saw tests (PSTs) on 7 sampling days during a 2-month period from early January to early March 2015. Based on video images taken during the tests we determined the mechanical properties of the slab and the weak layer and compared them to the results derived from concurrently performed measurements of penetration resistance using the snow micro-penetrometer (SMP). The critical cut length, observed in PSTs, increased overall during the measurement period. The increase was not steady and the lowest values of critical cut length were observed around the middle of the measurement period. The relevant mechanical properties, the slab effective elastic modulus and the weak layer specific fracture, overall increased as well. However, the changes with time differed, suggesting that the critical cut length cannot be assessed by simply monitoring a single mechanical property such as slab load, slab modulus or weak layer specific fracture energy. Instead, crack propagation propensity is the result of a complex interplay between the mechanical properties of the slab and the weak layer. We then compared our field observations to newly developed metrics of snow instability related to either failure initiation or crack propagation propensity. The metrics were either derived from the SMP signal or calculated from simulated snow stratigraphy (SNOWPACK). They partially reproduced the observed temporal evolution of critical cut length and instability test scores. Whereas our unique dataset of quantitative measures of snow instability provides new insights into the complex slab-weak layer interaction, it also showed some deficiencies of the modelled metrics of instability - calling for an improved representation of the mechanical properties.

Field measurements and modeling of wave propagation and subsequent weak layer failure in snow due to explosive loading

NASA Astrophysics Data System (ADS)

Simioni, Stephan; Sidler, Rolf; Dual, Jürg; Schweizer, Jürg

2015-04-01

Avalanche control by explosives is among the key temporary preventive measures. Yet, little is known about the mechanism involved in releasing avalanches by the effect of an explosion. Here, we test the hypothesis that the stress induced by acoustic waves exceeds the strength of weak snow layers. Consequently the snow fails and the onset of rapid crack propagation might finally lead to the release of a snow slab avalanche. We performed experiments with explosive charges over a snowpack. We installed microphones above the snowpack to measure near-surface air pressure and accelerometers within three snow pits. We also recorded pit walls of each pit with high speed cameras to detect weak layer failure. Empirical relationships and a priori information from ice and air were used to characterize a porous layered model from density measurements of snow profiles in the snow pits. This model was used to perform two-dimensional numerical simulations of wave propagation in Biot-type porous material. Locations of snow failure were identified in the simulation by comparing the axial and deviatoric stress field of the simulation to the corresponding snow strength. The identified snow failure locations corresponded well with the observed failure locations in the experiment. The acceleration measured in the snowpack best correlated with the modeled acceleration of the fluid relative to the ice frame. Even though the near field of the explosion is expected to be governed by non-linear effects as for example the observed supersonic wave propagation in the air above the snow surface, the results of the linear poroelastic simulation fit well with the measured air pressure and snowpack accelerations. The results of this comparison are an important step towards quantifying the effectiveness of avalanche control by explosives.

Effects of nontropical forest cover on climate

NASA Technical Reports Server (NTRS)

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

1984-01-01

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

Snow multivariable data assimilation for hydrological predictions in Alpine sites

NASA Astrophysics Data System (ADS)

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

2017-04-01

Snowpack dynamics (snow accumulation and ablation) strongly impacts on hydrological processes in Alpine areas. During the winter season the presence of snow cover (snow accumulation) reduces the drainage in the basin with a resulting lower watershed time of concentration in case of possible rainfall events. Moreover, the release of the significant water volume stored in winter (snowmelt) considerably contributes to the total discharge during the melting period. Therefore when modeling hydrological processes in snow-dominated catchments the quality of predictions deeply depends on how the model succeeds in catching snowpack dynamics. The integration of a hydrological model with a snow module allows improving predictions of river discharges. Besides the well-known modeling limitations (uncertainty in parameterizations; possible errors affecting both meteorological forcing data and initial conditions; approximations in boundary conditions), there are physical factors that make an exhaustive reconstruction of snow dynamics complicated: snow intermittence in space and time, stratification and slow phenomena like metamorphism processes, uncertainty in snowfall evaluation, wind transportation, etc. Data Assimilation (DA) techniques provide an objective methodology to combine several independent snow-related data sources (model simulations, ground-based measurements and remote sensed observations) in order to obtain the most likely estimate of snowpack state. This study presents SMASH (Snow Multidata Assimilation System for Hydrology), a multi-layer snow dynamic model strengthened by a multivariable DA framework for hydrological purposes. The model is physically based on mass and energy balances and can be used to reproduce the main physical processes occurring within the snowpack: accumulation, density dynamics, melting, sublimation, radiative balance, heat and mass exchanges. The model is driven by observed forcing meteorological data (air temperature, wind velocity, relative air humidity, precipitation and incident solar radiation) to provide a complete estimate of snowpack state. The implementation of a DA scheme enables to assimilate simultaneously ground-based observations of different snow-related variables (snow depth, snow density, surface temperature and albedo). SMASH performances are evaluated by using observed data supplied by meteorological stations located in three experimental Alpine sites: Col de Porte (1325 m, France); Torgnon (2160 m, Italy); Weissfluhjoch (2540 m, Switzerland). A comparison analysis between the resulting performaces of Particle Filter and Ensemble Kalman Filter schemes is shown.

Multi-decadal Arctic sea ice roughness.

NASA Astrophysics Data System (ADS)

Tsamados, M.; Stroeve, J.; Kharbouche, S.; Muller, J. P., , Prof; Nolin, A. W.; Petty, A.; Haas, C.; Girard-Ardhuin, F.; Landy, J.

2017-12-01

The transformation of Arctic sea ice from mainly perennial, multi-year ice to a seasonal, first-year ice is believed to have been accompanied by a reduction of the roughness of the ice cover surface. This smoothening effect has been shown to (i) modify the momentum and heat transfer between the atmosphere and ocean, (ii) to alter the ice thickness distribution which in turn controls the snow and melt pond repartition over the ice cover, and (iii) to bias airborne and satellite remote sensing measurements that depend on the scattering and reflective characteristics over the sea ice surface topography. We will review existing and novel remote sensing methodologies proposed to estimate sea ice roughness, ranging from airborne LIDAR measurement (ie Operation IceBridge), to backscatter coefficients from scatterometers (ASCAT, QUICKSCAT), to multi angle maging spectroradiometer (MISR), and to laser (Icesat) and radar altimeters (Envisat, Cryosat, Altika, Sentinel-3). We will show that by comparing and cross-calibrating these different products we can offer a consistent multi-mission, multi-decadal view of the declining sea ice roughness. Implications for sea ice physics, climate and remote sensing will also be discussed.

Prototyping and Testing a Wireless Sensor Network to Retrieve SWE at High Spatial Resolution

NASA Astrophysics Data System (ADS)

Kang, D.; Barros, A. P.

2007-12-01

A critical challenge in snow research from space is the ability to obtain measurements at the spatial and temporal resolution to characterize the statistical structure of the space-time variability of the physical properties of the snowpack within an area consistent with the pixel resolution in snow hydrology models or that expected from a future NASA mission dedicated to cold region processes. That is, observations of relevant snow dielectric properties are necessary at high spatial and temporal resolution during the accumulation and melt seasons. We present a new wireless sensor network prototype consisting of multiple antennas and buried low-power, multi- channel transmitters operating in L-band that communicate to a central pod equipped with a Vector Signal Analyzer (VSA) that receives, processes and manages the data. Only commercial off-the-shelf hard-ware parts were used to build the sensors. Because the sensors are very low cost and run autonomously, one envisions that self-organizing networks of large numbers of such sensors might be distributed over very large areas, therefore proving much needed data sets for scaling studies. The measurement strategy consists of placing the transmitters the land surface in the beginning of the snow season which are then run autonomously till the end of the spring and waken at pre-determined time-intervals to emit radio frequency signals and thus sample the snowpack. Along with the sensors, an important component of this work entails the development of an estimation algorithm to estimate snow dielectric properties, snow density, and volume fraction of snow (VF) from the time-of-travel, amplitude and phase modification of the multi-channel RF signals as they propagate through the snow-pack. Here, we present results from full system testing and evaluation of the sensors that were conducted at Duke University using ¢®¡Æsynthetic¢®¡¾ limited-area snowpacks (0.5 by 0.5 m2 and 1 by 2 m2) constructed of various combinations of foam layers of different porosities to simulate heterogeneous distributions of water. The existing sensors are currently being primed for field deployment. Discussion is also presented regarding further technology development including power usage, networking, and distribution and operations in remote regions.

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.

Modelling hazardous surface hoar layers in the mountain snowpack over space and time

NASA Astrophysics Data System (ADS)

Horton, Simon Earl

Surface hoar layers are a common failure layer in hazardous snow slab avalanches. Surface hoar crystals (frost) initially form on the surface of the snow, and once buried can remain a persistent weak layer for weeks or months. Avalanche forecasters have difficulty tracking the spatial distribution and mechanical properties of these layers in mountainous terrain. This thesis presents numerical models and remote sensing methods to track the distribution and properties of surface hoar layers over space and time. The formation of surface hoar was modelled with meteorological data by calculating the downward flux of water vapour from the atmospheric boundary layer. The timing of surface hoar formation and the modelled crystal size was verified at snow study sites throughout western Canada. The major surface hoar layers over several winters were predicted with fair success. Surface hoar formation was modelled over various spatial scales using meteorological data from weather forecast models. The largest surface hoar crystals formed in regions and elevation bands with clear skies, warm and humid air, cold snow surfaces, and light winds. Field surveys measured similar regional-scale patterns in surface hoar distribution. Surface hoar formation patterns on different slope aspects were observed, but were not modelled reliably. Mechanical field tests on buried surface hoar layers found layers increased in shear strength over time, but had persistent high propensity for fracture propagation. Layers with large crystals and layers overlying hard melt-freeze crusts showed greater signs of instability. Buried surface hoar layers were simulated with the snow cover model SNOWPACK and verified with avalanche observations, finding most hazardous surface hoar layers were identified with a structural stability index. Finally, the optical properties of surface hoar crystals were measured in the field with spectral instruments. Large plate-shaped crystals were less reflective at shortwave infrared wavelengths than other common surface snow grains. The methods presented in this thesis were developed into operational products that model hazardous surface hoar layers in western Canada. Further research and refinements could improve avalanche forecasts in regions prone to hazardous surface hoar layers.

The ASMEx snow slab experiment: snow microwave radiative transfer (SMRT) model evaluation

NASA Astrophysics Data System (ADS)

Sandells, Melody; Löwe, Henning; Picard, Ghislain; Dumont, Marie; Essery, Richard; Floury, Nicolas; Kontu, Anna; Lemmetyinen, Juha; Maslanka, William; Mätzler, Christian; Morin, Samuel; Wiesmann, Andreas

2017-04-01

A major uncertainty in snow microwave modelling to date has been the treatment of the snow microstructure. Although observations of microstructural parameters such as the optical grain diameter, specific surface area and correlation length have improved drastically over the last few years, scale factors have been used to derive the parameters needed in microwave emission models from these observations. Previous work has shown that a major difference between electromagnetic models of scattering coefficients is due to the specific snow microstructure models used. The snow microwave radiative transfer model (SMRT) is a new model developed to advance understanding of the role of microstructure and isolate different assumptions in existing microwave models that collectively hinder interpretation of model intercomparison studies. SMRT is implemented in Python and is modular, thus allows switching between different representations in its various components. Here, the role of microstructure is examined with the Improved Born Approximation electromagnetic model. The model is evaluated against scattering and absorption coefficients derived from radiometer measurements of snow slabs taken as part of the Arctic Snow Microstructure Experiment (ASMEx), which took place in Sodankylä, Finland over two seasons. Microtomography observations of slab samples were used to determine parameters for five microstructure models: spherical, exponential, sticky hard sphere, Teubner-Strey and Gaussian random field. SMRT brightness temperature simulations are also compared with radiometric observations of the snow slabs over a reflector plate and an absorber substrate. Agreement between simulations and observations is generally good except for slabs that are highly anisotropic.

Remote sensing of earth terrain

NASA Technical Reports Server (NTRS)

Yueh, Herng-Aung; Kong, Jin AU

1991-01-01

In remote sensing, the encountered geophysical media such as agricultural canopy, forest, snow, or ice are inhomogeneous and contain scatters in a random manner. Furthermore, weather conditions such as fog, mist, or snow cover can intervene the electromagnetic observation of the remotely sensed media. In the modelling of such media accounting for the weather effects, a multi-layer random medium model has been developed. The scattering effects of the random media are described by three-dimensional correlation functions with variances and correlation lengths corresponding to the fluctuation strengths and the physical geometry of the inhomogeneities, respectively. With proper consideration of the dyadic Green's function and its singularities, the strong fluctuation theory is used to calculate the effective permittivities which account for the modification of the wave speed and attenuation in the presence of the scatters. The distorted Born approximation is then applied to obtain the correlations of the scattered fields. From the correlation of the scattered field, calculated is the complete set of scattering coefficients for polarimetric radar observation or brightness temperature in passive radiometer applications. In the remote sensing of terrestrial ecosystems, the development of microwave remote sensing technology and the potential of SAR to measure vegetation structure and biomass have increased effort to conduct experimental and theoretical researches on the interactions between microwave and vegetation canopies. The overall objective is to develop inversion algorithms to retrieve biophysical parameters from radar data. In this perspective, theoretical models and experimental data are methodically interconnected in the following manner: Due to the complexity of the interactions involved, all theoretical models have limited domains of validity; the proposed solution is to use theoretical models, which is validated by experiments, to establish the region in which the radar response is most sensitive to the parameters of interest; theoretically simulated data will be used to generate simple invertible models over the region. For applications to the remote sensing of sea ice, the developed theoretical models need to be tested with experimental measurements. With measured ground truth such as ice thickness, temperature, salinity, and structure, input parameters to the theoretical models can be obtained to calculate the polarimetric scattering coefficients for radars or brightness temperature for radiometers and then compare theoretical results with experimental data. Validated models will play an important role in the interpretation and classification of ice in monitoring global ice cover from space borne remote sensors in the future. We present an inversion algorithm based on a recently developed inversion method referred to as the Renormalized Source-Type Integral Equation approach. The objective of this method is to overcome some of the limitations and difficulties of the iterative Born technique. It recasts the inversion, which is nonlinear in nature, in terms of the solution of a set of linear equations; however, the final inversion equation is still nonlinear. The derived inversion equation is an exact equation which sums up the iterative Neuman (or Born) series in a closed form and, thus, is a valid representation even in the case when the Born series diverges; hence, the name Renormalized Source-Type Integral Equation Approach.

A multi-objective approach to improve SWAT model calibration in alpine catchments

NASA Astrophysics Data System (ADS)

Tuo, Ye; Marcolini, Giorgia; Disse, Markus; Chiogna, Gabriele

2018-04-01

Multi-objective hydrological model calibration can represent a valuable solution to reduce model equifinality and parameter uncertainty. The Soil and Water Assessment Tool (SWAT) model is widely applied to investigate water quality and water management issues in alpine catchments. However, the model calibration is generally based on discharge records only, and most of the previous studies have defined a unique set of snow parameters for an entire basin. Only a few studies have considered snow observations to validate model results or have taken into account the possible variability of snow parameters for different subbasins. This work presents and compares three possible calibration approaches. The first two procedures are single-objective calibration procedures, for which all parameters of the SWAT model were calibrated according to river discharge alone. Procedures I and II differ from each other by the assumption used to define snow parameters: The first approach assigned a unique set of snow parameters to the entire basin, whereas the second approach assigned different subbasin-specific sets of snow parameters to each subbasin. The third procedure is a multi-objective calibration, in which we considered snow water equivalent (SWE) information at two different spatial scales (i.e. subbasin and elevation band), in addition to discharge measurements. We tested these approaches in the Upper Adige river basin where a dense network of snow depth measurement stations is available. Only the set of parameters obtained with this multi-objective procedure provided an acceptable prediction of both river discharge and SWE. These findings offer the large community of SWAT users a strategy to improve SWAT modeling in alpine catchments.

Remote focusing for programmable multi-layer differential multiphoton microscopy

PubMed Central

Hoover, Erich E.; Young, Michael D.; Chandler, Eric V.; Luo, Anding; Field, Jeffrey J.; Sheetz, Kraig E.; Sylvester, Anne W.; Squier, Jeff A.

2010-01-01

We present the application of remote focusing to multiphoton laser scanning microscopy and utilize this technology to demonstrate simultaneous, programmable multi-layer imaging. Remote focusing is used to independently control the axial location of multiple focal planes that can be simultaneously imaged with single element detection. This facilitates volumetric multiphoton imaging in scattering specimens and can be practically scaled to a large number of focal planes. Further, it is demonstrated that the remote focusing control can be synchronized with the lateral scan directions, enabling imaging in orthogonal scan planes. PMID:21326641

Polarization signatures and brightness temperatures caused by horizontally oriented snow particles at microwave bands: Effects of atmospheric absorption

NASA Astrophysics Data System (ADS)

Xie, Xinxin; Crewell, Susanne; Löhnert, Ulrich; Simmer, Clemens; Miao, Jungang

2015-06-01

This study analyzes the effects of atmospheric absorption and emission on the polarization difference (PD) and brightness temperature (TB) generated by horizontally oriented snow particles. A three-layer plane-parallel atmosphere model is used in conjunction with a simplified radiative transfer (RT) scheme to illustrate the combined effects of dichroic and nondichroic media on microwave signatures observed by ground-based and spaceborne sensors. Based on idealized scenarios which encompass a dichroic snow layer and adjacent nondichroic layers composed of supercooled liquid water (SCLW) droplets and water vapor, we demonstrate that the presence of atmospheric absorption/emission enhances TB and damps PD when observed from the ground. From a spaceborne perspective, however, TB can be reduced or enhanced by an absorbing/emitting layer above the snow layer, while a strong absorbing/emitting layer below the dichroic snow layer may even enhance PD. The induced PD and TB, which rely on snow microphysical assumptions, can vary up to 2 K and 10 K, respectively, due to the temperature-dependent absorption of SCLW. RT calculations based on 223 snowfall profiles selected from European Centre for Medium-Range Weather Forecasts data sets indicate that the existence of SCLW has a noticeable impact on PD and TB at three window frequencies (150 GHz, 243 GHz, and 664 GHz) during snowfall. Our results imply that while polarimetric channels at the three window channels have the potential for snowfall characterization, accurate information on liquid water is required to correctly interpret the polarimetric observations.

Millimeter Wave Scatter and Attenuation Measurements on Snow Slabs.

DTIC Science & Technology

1981-09-01

2id cos0• II. Rlay, P.S. (1972) Broadband complex refractive indices of ice and water, Appl. Optics ,Il(No. 8):1836-1844. 12. Lammers, U.H.W., and Hayes...portion was not investi- gated separately for its attenuation coefficient. The theory of multiple scattering in optics ’- provides ai reasoning for l...at 35 GHz to cause a strong specular response, equal to or higher than the noncoherent response. No substantial snow depth is required to generate

An Ultra-Wideband, Microwave Radar for Measuring Snow Thickness on Sea Ice and Mapping Near-Surface Internal Layers in Polar Firn

NASA Technical Reports Server (NTRS)

Panzer, Ben; Gomez-Garcia, Daniel; Leuschen, Carl; Paden, John; Rodriguez-Morales, Fernando; Patel, Azsa; Markus, Thorsten; Holt, Benjamin; Gogineni, Prasad

2013-01-01

Sea ice is generally covered with snow, which can vary in thickness from a few centimeters to >1 m. Snow cover acts as a thermal insulator modulating the heat exchange between the ocean and the atmosphere, and it impacts sea-ice growth rates and overall thickness, a key indicator of climate change in polar regions. Snow depth is required to estimate sea-ice thickness using freeboard measurements made with satellite altimeters. The snow cover also acts as a mechanical load that depresses ice freeboard (snow and ice above sea level). Freeboard depression can result in flooding of the snow/ice interface and the formation of a thick slush layer, particularly in the Antarctic sea-ice cover. The Center for Remote Sensing of Ice Sheets (CReSIS) has developed an ultra-wideband, microwave radar capable of operation on long-endurance aircraft to characterize the thickness of snow over sea ice. The low-power, 100mW signal is swept from 2 to 8GHz allowing the air/snow and snow/ ice interfaces to be mapped with 5 c range resolution in snow; this is an improvement over the original system that worked from 2 to 6.5 GHz. From 2009 to 2012, CReSIS successfully operated the radar on the NASA P-3B and DC-8 aircraft to collect data on snow-covered sea ice in the Arctic and Antarctic for NASA Operation IceBridge. The radar was found capable of snow depth retrievals ranging from 10cm to >1 m. We also demonstrated that this radar can be used to map near-surface internal layers in polar firn with fine range resolution. Here we describe the instrument design, characteristics and performance of the radar.

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

DOE PAGES

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

2017-08-18

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

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

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

Huang, Yuanyuan; Jiang, Jiang; Ma, Shuang

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

Multifactor estimation of ecological risks using numerical simulation

NASA Astrophysics Data System (ADS)

Voskoboynikova, G.; Shalamov, K.; Khairetdinov, M.; Kovalevsky, V.

2017-10-01

In this paper, the problem of interaction of acoustic waves falling at a given angle on a snow layer on the ground and seismic waves arising both in this layer and in the ground is considered. A system of differential equations with boundary conditions describing the propagation of incident and reflected acoustic waves in the air refracted and reflected from the boundary of seismic waves in elastic media (snow and ground) is constructed and solved for a three-layer air-snow layer-ground model. The coefficients of reflection and refraction are calculated in the case of an acoustic wave falling onto both the ground and snow on the ground. The ratio of the energy of the refracted waves to the energy of the falling acoustic wave is obtained. It is noted that snow has a strong influence on the energy transfer into the ground, which can decrease by more than an order of magnitude. The numerical results obtained are consistent with the results of field experiments with a vibrational source performed by the Siberian Branch of the Russian Academy of Sciences.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

A Physical Model to Determine Snowfall over Land by Microwave Radiometry

NASA Technical Reports Server (NTRS)

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

2003-01-01

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

Effects of snow grain shape on climate simulations: sensitivity tests with the Norwegian Earth System Model

NASA Astrophysics Data System (ADS)

Räisänen, Petri; Makkonen, Risto; Kirkevåg, Alf; Debernard, Jens B.

2017-12-01

Snow consists of non-spherical grains of various shapes and sizes. Still, in radiative transfer calculations, snow grains are often treated as spherical. This also applies to the computation of snow albedo in the Snow, Ice, and Aerosol Radiation (SNICAR) model and in the Los Alamos sea ice model, version 4 (CICE4), both of which are employed in the Community Earth System Model and in the Norwegian Earth System Model (NorESM). In this study, we evaluate the effect of snow grain shape on climate simulated by NorESM in a slab ocean configuration of the model. An experiment with spherical snow grains (SPH) is compared with another (NONSPH) in which the snow shortwave single-scattering properties are based on a combination of three non-spherical snow grain shapes optimized using measurements of angular scattering by blowing snow. The key difference between these treatments is that the asymmetry parameter is smaller in the non-spherical case (0.77-0.78 in the visible region) than in the spherical case ( ≈ 0.89). Therefore, for the same effective snow grain size (or equivalently, the same specific projected area), the snow broadband albedo is higher when assuming non-spherical rather than spherical snow grains, typically by 0.02-0.03. Considering the spherical case as the baseline, this results in an instantaneous negative change in net shortwave radiation with a global-mean top-of-the-model value of ca. -0.22 W m-2. Although this global-mean radiative effect is rather modest, the impacts on the climate simulated by NorESM are substantial. The global annual-mean 2 m air temperature in NONSPH is 1.17 K lower than in SPH, with substantially larger differences at high latitudes. The climatic response is amplified by strong snow and sea ice feedbacks. It is further demonstrated that the effect of snow grain shape could be largely offset by adjusting the snow grain size. When assuming non-spherical snow grains with the parameterized grain size increased by ca. 70 %, the climatic differences to the SPH experiment become very small. Finally, the impact of assumed snow grain shape on the radiative effects of absorbing aerosols in snow is discussed.

The criterial optics of oceans and glaciers with technogenic pollutions

NASA Astrophysics Data System (ADS)

Merzlikin, V. G.; Ilushin, Ya. A.; Olenin, A. L.; Sidorov, O. V.; Tovstonog, V. A.

2017-02-01

Effective diagnostics of natural and technogenic pollutions of the ocean and forming snow-ice cover is considered on the basis of priority observation and registration of the changing optical characteristics of the seawater and glaciers. The paper discusses Influence of abnormal optical properties on overheating of the seawater subsurface layer and appearance of significant irradiated oceanic deep horizons up to 100 m. Additional heating of atmosphere, strengthening of hurricanes during a storm, tornadogenesis, generation of dehydrated convective air flows at a calm and effect of overcooling deep seawater is analyzed using the scheme of calculated heat budget and temperature distributions under combined solar and atmospheric exposure. The authors propose to use their unique deep hydrological multi-channel probe for synchronous and independent registration of optical, temperature and other standard hydro physical characteristics developed by Shirshov Institute of Oceanology. The paper presents calculation algorithm of real variability of spatial and temporal temperature field due to influence of registered concentration field of foreign substances in the seawater irrespective of its hydrodynamic conditions. Inphase or antiphase changes of fixed temperature gradients and transparency for polluted seawater has been explained as the result of the various contributions of scattering and absorption within attenuation processes of probing radiation for the local volume at a specified depth.

Physical and Optical Properties of Falling Snow

DTIC Science & Technology

1989-07-01

ments with those measured with a transmissometer .................................. 19 24. HSS forward-scatter meter used for measuring extinction in...snowfall conditions, the different ge- ometries of the transmission systems and discrep- | 2• a 2 n(a) da ancies in the snow precipitation rate measure ...J0 ments. Bet = Ms. (27) Table 3. Relationships between measured fn(a) mn(a) da extinction coefficient and snow precipita- ion rate . 091 This

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

NASA Astrophysics Data System (ADS)

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

2003-04-01

Snow cover is an important variable for climate and hydrologic models due to its effects on energy and moisture budgets. Seasonal snow can cover more than 50% of the Northern Hemisphere land surface during the winter resulting in snow cover being the land surface characteristic responsible for the largest annual and interannual differences in albedo. Passive microwave satellite remote sensing can augment measurements based on visible satellite data alone because of the ability to acquire data through most clouds or during darkness as well as to provide a measure of snow depth or water equivalent. Global snow cover fluctuation can now be monitored over a 24 year period using passive microwave data (Scanning Multichannel Microwave Radiometer (SMMR) 1978-1987 and Special Sensor Microwave/Imager (SSM/I), 1987-present). Evaluation of snow extent derived from passive microwave algorithms is presented through comparison with the NOAA Northern Hemisphere weekly snow extent data. For the period 1978 to 2002, both passive microwave and visible data sets show a similar pattern of inter-annual variability, although the maximum snow extents derived from the microwave data are consistently less than those provided by the visible satellite data and the visible data typically show higher monthly variability. Decadal trends and their significance are compared for the two data types. During shallow snow conditions of the early winter season microwave data consistently indicate less snow-covered area than the visible data. This underestimate of snow extent results from the fact that shallow snow cover (less than about 5.0 cm) does not provide a scattering signal of sufficient strength to be detected by the algorithms. As the snow cover continues to build during the months of January through March, as well as throughout the melt season, agreement between the two data types continually improves. This occurs because as the snow becomes deeper and the layered structure more complex, the negative spectral gradient driving the passive microwave algorithm is enhanced. Because the current generation of microwave snow algorithms is unable to consistently detect shallow and intermittent snow, we combine visible satellite data with the microwave data in a single blended product to overcome this problem. For the period 1978 to 2002 we combine data from the NOAA weekly snow charts with passive microwave data from the SMMR and SSM/I brightness temperature record. For the current and future time period we blend MODIS and AMSR-E data sets, both of which have greatly enhanced spatial resolution compared to the earlier data sources. Because it is not possible to determine snow depth or snow water equivalent from visible data, the regions where only the NOAA or MODIS data indicate snow are defined as "shallow snow". However, because our current blended product is being developed in the 25 km EASE-Grid and the MODIS data being used are in the Climate Modelers Grid (CMG) at approximately 5 km (0.05 deg.) the blended product also includes percent snow cover over the larger grid cell. A prototype version of the blended MODIS/AMSR-E product will be available in near real-time from NSIDC during the 2002-2003 winter season.

[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.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Pyroclast/snow interactions and thermally driven slurry formation. Part 1: Theory for monodisperse grain beds

USGS Publications Warehouse

Walder, J.S.

2000-01-01

Lahars are often produced as pyroclastic flows move over snow. This phenomenon involves a complicated interplay of mechanical and thermal processes that need to be separated to get at the fundamental physics. The thermal physics of pyroclast/snow interactions form the focus of this paper. A theoretical model is developed of heat- and mass transfer at the interface between a layer of uniformly sized pyroclasts and an underlying bed of snow, for the case in which there is no relative shear motion between pyroclasts and snow. A microscale view of the interface is required to properly specify boundary conditions. The physical model leads to the prediction that the upward flux of water vapor - which depends upon emplacement temperature, pyroclast grain size, pyroclast-layer thickness, and snow permeability - is sometimes sufficient to fluidize the pyroclasts. Uniform fluidization is usually unstable to bubble formation, which leads to vigorous convection of the pyroclasts themselves. Thus, predicted threshold conditions for fluidization are tantamount to predicted thresholds for particle convection. Such predictions are quantitatively in good agreement with results of experiments described in part 2 of this paper. Because particle convection commonly causes scour of the snow bed and transformation of the pyroclast layer to a slurry, there exists a 'thermal scour' process for generating lahars from pyroclastic flows moving over snow regardless of the possible role of mechanical scour.

A new MRI land surface model HAL

NASA Astrophysics Data System (ADS)

Hosaka, M.

2011-12-01

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

Superscattering of light optimized by a genetic algorithm

NASA Astrophysics Data System (ADS)

Mirzaei, Ali; Miroshnichenko, Andrey E.; Shadrivov, Ilya V.; Kivshar, Yuri S.

2014-07-01

We analyse scattering of light from multi-layer plasmonic nanowires and employ a genetic algorithm for optimizing the scattering cross section. We apply the mode-expansion method using experimental data for material parameters to demonstrate that our genetic algorithm allows designing realistic core-shell nanostructures with the superscattering effect achieved at any desired wavelength. This approach can be employed for optimizing both superscattering and cloaking at different wavelengths in the visible spectral range.

Quantifying small-scale spatio-temporal variability of snow stratigraphy in forests based on high-resolution snow penetrometry

NASA Astrophysics Data System (ADS)

Teich, M.; Hagenmuller, P.; Bebi, P.; Jenkins, M. J.; Giunta, A. D.; Schneebeli, M.

2017-12-01

Snow stratigraphy, the characteristic layering within a seasonal snowpack, has important implications for snow remote sensing, hydrology and avalanches. Forests modify snowpack properties through interception, wind speed reduction, and changes to the energy balance. The lack of snowpack observations in forests limits our ability to understand the evolution of snow stratigraphy and its spatio-temporal variability as a function of forest structure and to observe snowpack response to changes in forest cover. We examined the snowpack under canopies of a spruce forest in the central Rocky Mountains, USA, using the SnowMicroPen (SMP), a high resolution digital penetrometer. Weekly-repeated penetration force measurements were recorded along 10 m transects every 0.3 m in winter 2015 and bi-weekly along 20 m transects every 0.5 m in 2016 in three study plots beneath canopies of undisturbed, bark beetle-disturbed and harvested forest stands, and an open meadow. To disentangle information about layer hardness and depth variabilities, and to quantitatively compare the different SMP profiles, we applied a matching algorithm to our dataset, which combines several profiles by automatically adjusting their layer thicknesses. We linked spatial and temporal variabilities of penetration force and depth, and thus snow stratigraphy to forest and meteorological conditions. Throughout the season, snow stratigraphy was more heterogeneous in undisturbed but also beneath bark beetle-disturbed forests. In contrast, and despite remaining small diameter trees and woody debris, snow stratigraphy was rather homogenous at the harvested plot. As expected, layering at the non-forested plot varied only slightly over the small spatial extent sampled. At the open and harvested plots, persistent crusts and ice lenses were clearly present in the snowpack, while such hard layers barely occurred beneath undisturbed and disturbed canopies. Due to settling, hardness significantly increased with depth at open and harvested plots, which was less distinctive at the other two plots. Our results contribute to the general understanding of forest-snowpack interactions and, if combined with density and specific surface area estimates, can be used to validate snowpack and microwave models for avalanche formation and SWE retrieval in forests.

Hexagonal boron nitride intercalated multi-layer graphene: a possible ultimate solution to ultra-scaled interconnect technology

NASA Astrophysics Data System (ADS)

Li, Yong-Jun; Sun, Qing-Qing; Chen, Lin; Zhou, Peng; Wang, Peng-Fei; Ding, Shi-Jin; Zhang, David Wei

2012-03-01

We proposed intercalation of hexagonal boron nitride (hBN) in multilayer graphene to improve its performance in ultra-scaled interconnects for integrated circuit. The effect of intercalated hBN layer in bilayer graphene is investigated using non-equilibrium Green's functions. We find the hBN intercalated bilayer graphene exhibit enhanced transport properties compared with pristine bilayer ones, and the improvement is attributed to suppression of interlayer scattering and good planar bonding condition of inbetween hBN layer. Based on these results, we proposed a via structure that not only benefits from suppressed interlayer scattering between multilayer graphene, but also sustains the unique electrical properties of graphene when many graphene layers are stacking together. The ideal current density across the structure can be as high as 4.6×109 A/cm2 at 1V, which is very promising for the future high-performance interconnect.

A field study of the hemispherical directional reflectance factor and spectral albedo of dry snow

NASA Astrophysics Data System (ADS)

Bourgeois, C. S.; Calanca, P.; Ohmura, A.

2006-10-01

Hemispherical directional reflectance factors (HDRF) were collected under solar zenith angles from 49° to 85°. The experimental site was the Greenland Summit Environmental Observatory (72°35'N, 34°30'W, 3203 m above sea level) where both the snow and the atmosphere are very clean. The observations were carried out for two prevailing snow surface types: a smooth surface with wind-broken small snow grains and a surface covered with rime causing a higher surface roughness. A specially designed Gonio-Spectrometer (wavelength range 350-1050 nm), was developed at the Institute for Atmospheric and Climate Science and used to collect spectral HDRFs over the hemisphere. The angular step size was 15° in zenith and azimuth. The HDRFs showed strong variations ranging from 0.6 to 13, depending on the solar zenith angle. The HDRF distribution was nearly isotropic at noon. It varied with increasing solar zenith angle, resulting in a strong forward scattering peak. Smooth surfaces exhibited stronger forward scattering than surfaces covered with rime. At a solar zenith of 85°, an HDRF of ˜13 was observed in the forward scattering direction for λ=900 nm. Spectral albedos were calculated by interpolating the HDRF data sets on a 2° grid and integrating individual wavelengths. Spectral albedos showed variations depending on the solar illumination geometry and the snow surface properties. Broadband albedos were calculated by integration of the spectral albedos over all wavelengths. The broadband albedos derived from directional measurements reproduced the diurnal pattern measured with two back-to-back broadband pyranometers.

Development and Applications of Technology for Sensing Zooplankton

DTIC Science & Technology

2003-09-30

zooplankton-like particles. WORK COMPLETED In support of our first objective, in prior years we occupied sites in both East and West Sound at Orcas ...Island in northern Puget Sound , WA. We have also made deployments at four sites on open linear coasts, including one just north of Oceanside, CA (Red...layers. Multi-static, multi-frequency methods Most active bioacoustical methods in oceanography exclusively utilize the sound that is scattered

Modification of Soil Temperature and Moisture Budgets by Snow Processes

NASA Astrophysics Data System (ADS)

Feng, X.; Houser, P.

2006-12-01

Snow cover significantly influences the land surface energy and surface moisture budgets. Snow thermally insulates the soil column from large and rapid temperature fluctuations, and snow melting provides an important source for surface runoff and soil moisture. Therefore, it is important to accurately understand and predict the energy and moisture exchange between surface and subsurface associated with snow accumulation and ablation. The objective of this study is to understand the impact of land surface model soil layering treatment on the realistic simulation of soil temperature and soil moisture. We seek to understand how many soil layers are required to fully take into account soil thermodynamic properties and hydrological process while also honoring efficient calculation and inexpensive computation? This work attempts to address this question using field measurements from the Cold Land Processes Field Experiment (CLPX). In addition, to gain a better understanding of surface heat and surface moisture transfer process between land surface and deep soil involved in snow processes, numerical simulations were performed at several Meso-Cell Study Areas (MSAs) of CLPX using the Center for Ocean-Land-Atmosphere (COLA) Simplified Version of the Simple Biosphere Model (SSiB). Measurements of soil temperature and soil moisture were analyzed at several CLPX sites with different vegetation and soil features. The monthly mean vertical profile of soil temperature during October 2002 to July 2003 at North Park Illinois River exhibits a large near surface variation (<5 cm), reveals a significant transition zone from 5 cm to 25 cm, and becomes uniform beyond 25cm. This result shows us that three soil layers are reasonable in solving the vertical variation of soil temperature at these study sites. With 6 soil layers, SSiB also captures the vertical variation of soil temperature during entire winter season, featuring with six soil layers, but the bare soil temperature is underestimated and root-zone soil temperature is overestimated during snow melting; which leads to overestimated temperature variations down to 20 cm. This is caused by extra heat loss from upper soil level and insufficient heat transport from the deep soil. Further work will need to verify if soil temperature displays similar vertical thermal structure for different vegetation and soil types during snow season. This study provides insight to the surface and subsurface thermodynamic and hydrological processes involved in snow modeling which is important for accurate snow simulation.

Material optimization of multi-layered enhanced nanostructures

NASA Astrophysics Data System (ADS)

Strobbia, Pietro

The employment of surface enhanced Raman scattering (SERS)-based sensing in real-world scenarios will offer numerous advantages over current optical sensors. Examples of these advantages are the intrinsic and simultaneous detection of multiple analytes, among many others. To achieve such a goal, SERS substrates with throughput and reproducibility comparable to commonly used fluorescence sensors have to be developed. To this end, our lab has discovered a multi-layer geometry, based on alternating films of a metal and a dielectric, that amplifies the SERS signal (multi-layer enhancement). The advantage of these multi-layered structures is to amplify the SERS signal exploiting layer-to-layer interactions in the volume of the structures, rather than on its surface. This strategy permits an amplification of the signal without modifying the surface characteristics of a substrate, and therefore conserving its reproducibility. Multi-layered structures can therefore be used to amplify the sensitivity and throughput of potentially any previously developed SERS sensor. In this thesis, these multi-layered structures were optimized and applied to different SERS substrates. The role of the dielectric spacer layer in the multi-layer enhancement was elucidated by fabricating spacers with different characteristics and studying their effect on the overall enhancement. Thickness, surface coverage and physical properties of the spacer were studied. Additionally, the multi-layered structures were applied to commercial SERS substrates and to isolated SERS probes. Studies on the dependence of the multi-layer enhancement on the thickness of the spacer demonstrated that the enhancement increases as a function of surface coverage at sub-monolayer thicknesses, due to the increasing multi-layer nature of the substrates. For fully coalescent spacers the enhancement decreases as a function of thickness, due to the loss of interaction between proximal metallic films. The influence of the physical properties of the spacer on the multi-layer enhancement were also studied. The trends in Schottky barrier height, interfacial potential and dielectric constant were isolated by using different materials as spacers (i.e., TiO2, HfO2, Ag 2O and Al2O3). The results show that the bulk dielectric constant of the material can be used to predict the relative magnitude of the multi-layer enhancement, with low dielectric constant materials performing more efficiently as spacers. Optimal spacer layers were found to be ultrathin coalescent films (ideally a monolayer) of low dielectric constant materials. Finally, multi-layered structures were observed to be employable to amplify SERS in drastically different substrate geometries. The multi-layered structures were applied to disposable commercial SERS substrates (i.e., Klarite). This project involved the regeneration of the used substrates, by stripping and redepositing the gold coating layer, and their amplification, by using the multi-layer geometry. The latter was observed to amplify the sensitivity of the substrates. Additionally, the multi-layered structures were applied to probes dispersed in solution. Such probes were observed to yield stronger SERS signal when optically trapped and to reduce the background signal. The application of the multi-layered structures on trapped probes, not only further amplified the SERS signal, but also increased the maximum number of applicable layers for the structures.

How to constrain snow particle scattering models? A novel approach using triple-frequency radar Doppler spectra.

NASA Astrophysics Data System (ADS)

Kneifel, S.; Battaglia, A.; Kollias, P.; Leinonen, J. S.; Maahn, M.; Kalesse, H.; Tridon, F.; Crewell, S.

2016-12-01

During the last years, an increasing number of microwave (MW) scattering databases and novel approximations for single particles, complex aggregates and even rimed and melting aggregates became available. While these developments are in general a great step forward, their evaluation with observations is a very necessary but also challenging task. Recently available multi-frequency radar observations which cover the Rayleigh up to the Mie scattering regime revealed characteristic signatures of rimed and unrimed aggregated particles. However, the observed signatures are still affected by both, the particle size distribution (PSD) and the single scattering properties of the particles which makes a clear evaluation of one or the other challenging. In this contribution we present a new approach which uses the radar Doppler spectra at three frequencies (X, Ka, and W-band) collected during a recent winter field campaign in Finland. We analyzed a snowfall event which includes rimed and unrimed snow aggregates. A large selection of spectra obtained from low-turbulence regions within the cloud reveals distinctly different signatures of the derived Doppler spectral ratios. Due to the third frequency, a characteristic curve can be derived which is almost independent of the underlying particle size distribution and velocity-size relation. The characteristics of the curves obtained for rimed and unrimed are distinctly different. The observed signatures were compared with scattering calculations obtained with discrete dipole approximation (DDA), self-similar Rayleigh-Gans approximation (SSRG), and with the classical soft spheroid (T-Matrix) method. While the DDA calculations of unrimed and rimed aggregates fit the observed signatures well, the T-Matrix results lie far outside the observed range. The SSRG approximations was found to be principally able to recover the main features but a better matching would need an adjustment of the published coefficients. Future campaigns, like the new German Collaborative Research Center Arctic Amplification: Climate Relevant Atmospheric and Surface Processes, and Feedback Mechanisms (AC)³, will provide combined airborne in-situ and remote sensing observations of mixed-phase clouds to further validate the results of the triple-frequency Doppler spectra approach.

Automated Laser-Light Scattering measurements of Impurities, Bubbles, and Imperfections in Ice Cores

NASA Astrophysics Data System (ADS)

Stolz, M. R.; Ram, M.

2004-12-01

Laser- light scattering (LLS) on polar ice, or on polar ice meltwater, is an accepted method for measuring the concentration of water insoluble aerosol deposits (dust) in the ice. LLS on polar ice can also be used to measure water soluble aerosols, as well as imperfections (air bubbles and cavities) in the ice. LLS was originally proposed by Hammer (1977a, b) as a method for measuring the dust concentration in polar ice meltwater. Ram et al. (1995) later advanced the method and applied it to solid ice, measuring the dust concentration profile along the deep, bubble-free sections of the Greenland Ice Sheet Projetct 2 (GISP2) ice core (Ram et al., 1995, 2000) from central Greenland. In this paper, we will put previous empirical findings (Ram et al., 1995, 2000) on a theoretical footing, and extend the usability of LLS on ice into the realm of the non-transparent, bubbly polar ice. For LLS on clear, bubble-free polar ice, we studied numerically the scattering of light by soluble and insoluble (dust) aerosol particles embedded in the ice to complement previous experimental studies (Ram et al., 2000). For air bubbles in polar ice, we calculated the effects of multiple light scattering using Mie theory and Monte Carlo simulations, and found a method for determining the bubble number size and concentration using LLS on bubbly ice. We also demonstrated that LLS can be used on bubbly ice to measure annual layers rapidly in an objective manner. Hammer, C. U. (1977a), Dating of Greenland ice cores by microparticle concentration analyses., in International Symposium on Isotopes and Impurities in Snow and Ice, pp. 297-301, IAHS publ. no. 118. Hammer, C. U. (1977b), Dust studies on Greenland ice cores, in International Symposium on Isotopes and Impurities in Snow and Ice, pp. 365-370, IAHS publ. no. 118. Ram, M., M. Illing, P. Weber, G. Koenig, and M. Kaplan (1995), Polar ice stratigraphy from laser-light scattering: Scattering from ice, Geophys. Res. Lett., 22(24), 3525-3527. Ram, M., J. Donarummo, M. R. Stolz, and G. Koenig (2000), Calibration of laser-light scattering measurements of dust concentration for Wisconsinan GISP2 ice using instrumental neutron activation analysis of aluminum: Results and discussion, J. Geophys. Res., 105(D20), 24,731--24,738.

Modeling thermal infrared (2-14 micrometer) reflectance spectra of frost and snow

NASA Technical Reports Server (NTRS)

Wald, Andrew E.

1994-01-01

Existing theories of radiative transfer in close-packed media assume that each particle scatters independently of its neighbors. For opaque particles, such as are common in the thermal infrared, this assumption is not valid, and these radiative transfer theories will not be accurate. A new method is proposed, called 'diffraction subtraction', which modifies the scattering cross section of close-packed large, opaque spheres to account for the effect of close packing on the diffraction cross section of a scattering particle. This method predicts the thermal infrared reflectance of coarse (greater than 50 micrometers radius), disaggregated granular snow. However, such coarse snow is typically old and metamorphosed, with adjacent grains welded together. The reflectance of such a welded block can be described as partly Fresnel in nature and cannot be predicted using Mie inputs to radiative transfer theory. Owing to the high absorption coefficient of ice in the thermal infrared, a rough surface reflectance model can be used to calculate reflectance from such a block. For very small (less than 50 micrometers), disaggregated particles, it is incorrect in principle to treat diffraction independently of reflection and refraction, and the theory fails. However, for particles larger than 50 micrometers, independent scattering is a valid assumption, and standard radiative transfer theory works.

Detecting ice lenses and melt-refreeze crusts using satellite passive microwaves (Invited)

NASA Astrophysics Data System (ADS)

Montpetit, B.; Royer, A.; Roy, A.

2013-12-01

With recent winter climate warming in high latitude regions, rain-on-snow and melt-refreeze events are more frequent creating ice lenses or ice crusts at the surface or even within the snowpack through drainage. These ice layers create an impermeable ice barrier that reduces vegetation respiration and modifies snow properties due to the weak thermal diffusivity of ice. Winter mean soil temperatures increase due to latent heat being released during the freezing process. When ice layers freeze at the snow-soil interface, they can also affect the feeding habits of the northern wild life. Ice layers also significantly affect satellite passive microwave signals that are widely used to monitor the spatial and temporal evolution of snow. Here we present a method using satellite passive microwave brightness temperatures (Tb) to detect ice lenses and/or ice crusts within a snowpack. First the Microwave Emission Model for Layered Snowpacks (MEMLS) was validated to model Tb at 10.7, 19 and 37 GHz using in situ measurements taken in multiple sub-arctic environments where ice layers where observed. Through validated modeling, the effects of ice layer insertion were studied and an ice layer index was developed using the polarization ratio (PR) at all three frequencies. The developed ice index was then applied to satellite passive microwave signals for reported ice layer events.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Pyroclast/snow interactions and thermally driven slurry formation. Part 2: Experiments and theoretical extension to polydisperse tephra

USGS Publications Warehouse

Walder, J.S.

2000-01-01

Erosion of snow by pyroclastic flows and surges presumably involves mechanical scour, but there may be thermally driven phenomena involved as well. To investigate this possibility, layers of hot (up to 400??C), uniformly sized, fine- to medium-grained sand were emplaced vertically onto finely shaved ice ('snow'); thus there was no relative shear motion between sand and snow and no purely mechanical scour. In some cases large vapor bubbles, commonly more than 10 mm across, rose through the sand layer, burst at the surface, and caused complete convective overturn of the sand, which then scoured and mixed with snow and transformed into a slurry. In other cases no bubbling occurred and the sand passively melted its way downward into the snow as a wetting front moved upward into the sand. A continuum of behaviors between these two cases was observed. Vigorous bubbling and convection were generally favored by high temperature, small grain size, and small layer thickness. A physically based theory of heat- and mass transfer at the pyroclast/snow interface, developed in Part 1 of this paper, does a good job of explaining the observations as a manifestation of unstable vapor-driven fluidization. The theory, when extrapolated to the behavior of actual, poorly sorted pyroclastic flow sediments, leads to the prediction that the observed 'thermal-scour' phenomenon should also occur for many real pyroclastic flows passing over snow. 'Thermal scour' is therefore likely to be involved in the generation of lahars.

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

NASA Astrophysics Data System (ADS)

Mahdavi, Sahel; Maghsoudi, Yasser; Amani, Meisam

2017-07-01

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

Detection of Slope Instabilities Along the National Road 7, Mendoza Province, Argentina, Using Multi-Temporal InSAR

NASA Astrophysics Data System (ADS)

Michoud, Clément; Derron, Marc-Henri; Baumann, Valérie; Jaboyedoff, Michel; Rune Lauknes, Tom

2013-04-01

About 2'230 vehicles per day pass through the National Road 7 that link Buenos Aires to Santiago de Chile, crossing Andes Cordillera. This extremely important corridor, being the most important land pass between Argentina and Chile, is exposed to numerous natural hazards, such as snow avalanches, rockfalls and debris flows and remains closed by natural hazards several days per year. This goal of this study is to perform a regional mapping of geohazard susceptibilities along the Road 7 corridor, as started by Baumann et al. (2005), using modern remote sensing and numerical approaches with field checking. The area of interest is located in the Mendoza Province, between the villages Potrerillos and Las Cuevas near the Chilean border. The diversity of soil and rock conditions, the active geomorphological processes associated to post-glacial decompression, seasonal freeze and thaw and severe storms along the road corridor, increase the risk to natural hazard. With the support of the European Space Agency (ESA Category-1 Project 7154), we have in this study processed a large number of ERS and Envisat ASAR scenes, covering the period from 1995 to 2000. We applied both the small-baseline (SB) and the persistent scatterer (PSI) multi-temporal interferometric SAR (InSAR) techniques. The study area contains sparse vegetation, and the SB InSAR method is therefore well suited to map the area containing mainly distributed scatterers. Furthermore, PSI algorithms are also used for comparison for selected landslides in the inventory. Both approaches show a relatively good coherence within mountain areas, which is a good point for the landslide detections along the road. Indeed, the authors identified several large slope instabilities even active scree deposits. This inventory is finally compared with field observations and with existing susceptibility maps regarding snow avalanches, debris-flows and rockfalls. The final objective of this project is to develop a risk strategy that will help local authorities to manage the risk along this highway and also to provide guidelines.

Microwave scattering models and basic experiments

NASA Technical Reports Server (NTRS)

Fung, Adrian K.

1989-01-01

Progress is summarized which has been made in four areas of study: (1) scattering model development for sparsely populated media, such as a forested area; (2) scattering model development for dense media, such as a sea ice medium or a snow covered terrain; (3) model development for randomly rough surfaces; and (4) design and conduct of basic scattering and attenuation experiments suitable for the verification of theoretical models.

Predicting the distribution and ecological niche of unexploited snow crab (Chionoecetes opilio) populations in Alaskan waters: a first open-access ensemble model.

PubMed

Hardy, Sarah M; Lindgren, Michael; Konakanchi, Hanumantharao; Huettmann, Falk

2011-10-01

Populations of the snow crab (Chionoecetes opilio) are widely distributed on high-latitude continental shelves of the North Pacific and North Atlantic, and represent a valuable resource in both the United States and Canada. In US waters, snow crabs are found throughout the Arctic and sub-Arctic seas surrounding Alaska, north of the Aleutian Islands, yet commercial harvest currently focuses on the more southerly population in the Bering Sea. Population dynamics are well-monitored in exploited areas, but few data exist for populations further north where climate trends in the Arctic appear to be affecting species' distributions and community structure on multiple trophic levels. Moreover, increased shipping traffic, as well as fisheries and petroleum resource development, may add additional pressures in northern portions of the range as seasonal ice cover continues to decline. In the face of these pressures, we examined the ecological niche and population distribution of snow crabs in Alaskan waters using a GIS-based spatial modeling approach. We present the first quantitative open-access model predictions of snow-crab distribution, abundance, and biomass in the Chukchi and Beaufort Seas. Multi-variate analysis of environmental drivers of species' distribution and community structure commonly rely on multiple linear regression methods. The spatial modeling approach employed here improves upon linear regression methods in allowing for exploration of nonlinear relationships and interactions between variables. Three machine-learning algorithms were used to evaluate relationships between snow-crab distribution and environmental parameters, including TreeNet, Random Forests, and MARS. An ensemble model was then generated by combining output from these three models to generate consensus predictions for presence-absence, abundance, and biomass of snow crabs. Each algorithm identified a suite of variables most important in predicting snow-crab distribution, including nutrient and chlorophyll-a concentrations in overlying waters, temperature, salinity, and annual sea-ice cover; this information may be used to develop and test hypotheses regarding the ecology of this species. This is the first such quantitative model for snow crabs, and all GIS-data layers compiled for this project are freely available from the authors, upon request, for public use and improvement.

Estimation of Soil Moisture with L-band Multi-polarization Radar

NASA Technical Reports Server (NTRS)

Shi, J.; Chen, K. S.; Kim, Chung-Li Y.; Van Zyl, J. J.; Njoku, E.; Sun, G.; O'Neill, P.; Jackson, T.; Entekhabi, D.

2004-01-01

Through analyses of the model simulated data-base, we developed a technique to estimate surface soil moisture under HYDROS radar sensor (L-band multi-polarizations and 40deg incidence) configuration. This technique includes two steps. First, it decomposes the total backscattering signals into two components - the surface scattering components (the bare surface backscattering signals attenuated by the overlaying vegetation layer) and the sum of the direct volume scattering components and surface-volume interaction components at different polarizations. From the model simulated data-base, our decomposition technique works quit well in estimation of the surface scattering components with RMSEs of 0.12,0.25, and 0.55 dB for VV, HH, and VH polarizations, respectively. Then, we use the decomposed surface backscattering signals to estimate the soil moisture and the combined surface roughness and vegetation attenuation correction factors with all three polarizations.

Disordered 3 D Multi-layer Graphene Anode Material from CO2 for Sodium-Ion Batteries.

PubMed

Smith, Kassiopeia; Parrish, Riley; Wei, Wei; Liu, Yuzi; Li, Tao; Hu, Yun Hang; Xiong, Hui

2016-06-22

We report the application of disordered 3 D multi-layer graphene, synthesized directly from CO2 gas through a reaction with Li at 550 °C, as an anode for Na-ion batteries (SIBs) toward a sustainable and greener future. The material exhibited a reversible capacity of ∼190 mA h g(-1) with a Coulombic efficiency of 98.5 % at a current density of 15 mA g(-1) . The discharge capacity at higher potentials (>0.2 V vs. Na/Na(+) ) is ascribed to Na-ion adsorption at defect sites, whereas the capacity at low potentials (<0.2 V) is ascribed to intercalation between graphene sheets through electrochemical characterization, Raman spectroscopy, and small-angle X-ray scattering experiments. The disordered multi-layer graphene electrode demonstrated a great rate capability and cyclability. This novel approach to synthesize disordered 3 D multi-layer graphene from CO2 gas makes it attractive not only as an anode material for SIBs but also to mitigate CO2 emission. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Blowing Snow Sublimation at a High Altitude Alpine Site and Effects on the Surface Boundary Layer

NASA Astrophysics Data System (ADS)

Vionnet, V.; Guyomarc'h, G.; Sicart, J. E.; Deliot, Y.; Naaim-Bouvet, F.; Bellot, H.; Merzisen, H.

2017-12-01

In alpine terrain, wind-induced snow transport strongly influences the spatial and temporal variability of the snow cover. During their transport, blown snow particles undergo sublimation with an intensity depending on atmospheric conditions (air temperature and humidity). The mass loss due to blowing snow sublimation is a source of uncertainty for the mass balance of the alpine snowpack. Additionally, blowing snow sublimation modifies humidity and temperature in the surface boundary layer. To better quantify these effects in alpine terrain, a dedicated measurement setup has been deployed at the experimental site of Col du Lac Blanc (2720 m a.s.l., French Alps, Cryobs-Clim network) since winter 2015/2016. It consists in three vertical masts measuring the near-surface vertical profiles (0.2-5 m) of wind speed, air temperature and humidity and blowing snow fluxes and size distribution. Observations collected during blowing snow events without concurrent snowfall show only a slight increase in relative humidity (10-20%) and near-surface saturation is never observed. Estimation of blowing snow sublimation rates are then obtained from these measurements. They range between 0 and 5 mmSWE day-1 for blowing snow events without snowfall in agreement with previous studies in different environments (North American prairies, Antarctica). Finally, an estimation of the mass loss due to blowing snow sublimation at our experimental site is proposed for two consecutive winters. Future use of the database collected in this study includes the evaluation of blowing snow models in alpine terrain.

On the influence of recrystallization on snow fabric and microstructure: study of a snow profile in Central East Antarctica

NASA Astrophysics Data System (ADS)

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

2016-04-01

Temperature gradient metamorphism affects the Antarctic snowpack up to 5 meters depth, which lead to a recrystallization of the ice grains by sublimation of ice and deposition of water vapor. By this way, it is well known that the snow microstructure evolves (geometrical changes). Also, a recent study shows an evolution of the snow fabric, based on a cold laboratory experiment. Both fabric and microstructure are required to better understand mechanical behavior and densification of snow, firn and ice, given polar climatology. The fabric of firn and ice has been extensively investigated, but the publications by Stephenson (1967, 1968) are to our knowledge the only ones describing the snow fabric in Antarctica. In this context, our work focuses on snow microstructure and fabric in the first meters depth of the Antarctic ice sheet, where temperature gradients driven recrystallization occurs. Accurate details of the snow microstructure are observed using micro-computed tomography. Snow fabrics were measured at various depths from thin sections of impregnated snow with an Automatic Ice Texture Analyzer (AITA). A definite relationship between microstructure and fabric is found and highlights the influence of metamorphism on both properties. Our results also show that the metamorphism enhances the differences between the snow layers properties. Our work stresses the significant and complex evolution of snow properties in the upper meters of the ice sheet and opens the question of how these layer properties will evolve at depth and may influence the densification.

C-Band Backscatter Measurements of Winter Sea-Ice in the Weddell Sea, Antarctica

NASA Technical Reports Server (NTRS)

Drinkwater, M. R.; Hosseinmostafa, R.; Gogineni, P.

1995-01-01

During the 1992 Winter Weddell Gyre Study, a C-band scatterometer was used from the German ice-breaker R/V Polarstern to obtain detailed shipborne measurement scans of Antarctic sea-ice. The frequency-modulated continuous-wave (FM-CW) radar operated at 4-3 GHz and acquired like- (VV) and cross polarization (HV) data at a variety of incidence angles (10-75 deg). Calibrated backscatter data were recorded for several ice types as the icebreaker crossed the Weddell Sea and detailed measurements were made of corresponding snow and sea-ice characteristics at each measurement site, together with meteorological information, radiation budget and oceanographic data. The primary scattering contributions under cold winter conditions arise from the air/snow and snow/ice interfaces. Observations indicate so e similarities with Arctic sea-ice scattering signatures, although the main difference is generally lower mean backscattering coefficients in the Weddell Sea. This is due to the younger mean ice age and thickness, and correspondingly higher mean salinities. In particular, smooth white ice found in 1992 in divergent areas within the Weddell Gyre ice pack was generally extremely smooth and undeformed. Comparisons of field scatterometer data with calibrated 20-26 deg incidence ERS-1 radar image data show close correspondence, and indicate that rough Antarctic first-year and older second-year ice forms do not produce as distinctively different scattering signatures as observed in the Arctic. Thick deformed first-year and second-year ice on the other hand are clearly discriminated from younger undeformed ice. thereby allowing successful separation of thick and thin ice. Time-series data also indicate that C-band is sensitive to changes in snow and ice conditions resulting from atmospheric and oceanographic forcing and the local heat flux environment. Variations of several dB in 45 deg incidence backscatter occur in response to a combination of thermally-regulated parameters including sea-ice brine volume, snow and ice complex dielectric properties, and snow physical properties.

Smooth e-beam-deposited tin-doped indium oxide for III-nitride vertical-cavity surface-emitting laser intracavity contacts

NASA Astrophysics Data System (ADS)

Leonard, J. T.; Cohen, D. A.; Yonkee, B. P.; Farrell, R. M.; DenBaars, S. P.; Speck, J. S.; Nakamura, S.

2015-10-01

We carried out a series of simulations analyzing the dependence of mirror reflectance, threshold current density, and differential efficiency on the scattering loss caused by the roughness of tin-doped indium oxide (ITO) intracavity contacts for 405 nm flip-chip III-nitride vertical-cavity surface-emitting lasers (VCSELs). From these results, we determined that the ITO root-mean-square (RMS) roughness should be <1 nm to minimize scattering losses in VCSELs. Motivated by this requirement, we investigated the surface morphology and optoelectronic properties of electron-beam (e-beam) evaporated ITO films, as a function of substrate temperature and oxygen flow and pressure. The transparency and conductivity were seen to increase with increasing temperature. Decreasing the oxygen flow and pressure resulted in an increase in the transparency and resistivity. Neither the temperature, nor oxygen flow and pressure series on single-layer ITO films resulted in highly transparent and conductive films with <1 nm RMS roughness. To achieve <1 nm RMS roughness with good optoelectronic properties, a multi-layer ITO film was developed, utilizing a two-step temperature scheme. The optimized multi-layer ITO films had an RMS roughness of <1 nm, along with a high transparency (˜90% at 405 nm) and low resistivity (˜2 × 10-4 Ω-cm). This multi-layer ITO e-beam deposition technique is expected to prevent p-GaN plasma damage, typically observed in sputtered ITO films on p-GaN, while simultaneously reducing the threshold current density and increasing the differential efficiency of III-nitride VCSELs.

Comparing springtime ice-algal chlorophyll a and physical properties of multi-year and first-year sea ice from the Lincoln Sea.

PubMed

Lange, Benjamin A; Michel, Christine; Beckers, Justin F; Casey, J Alec; Flores, Hauke; Hatam, Ido; Meisterhans, Guillaume; Niemi, Andrea; Haas, Christian

2015-01-01

With near-complete replacement of Arctic multi-year ice (MYI) by first-year ice (FYI) predicted to occur within this century, it remains uncertain how the loss of MYI will impact the abundance and distribution of sea ice associated algae. In this study we compare the chlorophyll a (chl a) concentrations and physical properties of MYI and FYI from the Lincoln Sea during 3 spring seasons (2010-2012). Cores were analysed for texture, salinity, and chl a. We identified annual growth layers for 7 of 11 MYI cores and found no significant differences in chl a concentration between the bottom first-year-ice portions of MYI, upper old-ice portions of MYI, and FYI cores. Overall, the maximum chl a concentrations were observed at the bottom of young FYI. However, there were no significant differences in chl a concentrations between MYI and FYI. This suggests little or no change in algal biomass with a shift from MYI to FYI and that the spatial extent and regional variability of refrozen leads and younger FYI will likely be key factors governing future changes in Arctic sea ice algal biomass. Bottom-integrated chl a concentrations showed negative logistic relationships with snow depth and bulk (snow plus ice) integrated extinction coefficients; indicating a strong influence of snow cover in controlling bottom ice algal biomass. The maximum bottom MYI chl a concentration was observed in a hummock, representing the thickest ice with lowest snow depth of this study. Hence, in this and other studies MYI chl a biomass may be under-estimated due to an under-representation of thick MYI (e.g., hummocks), which typically have a relatively thin snowpack allowing for increased light transmission. Therefore, we suggest the on-going loss of MYI in the Arctic Ocean may have a larger impact on ice-associated production than generally assumed.

Comparing Springtime Ice-Algal Chlorophyll a and Physical Properties of Multi-Year and First-Year Sea Ice from the Lincoln Sea

PubMed Central

Lange, Benjamin A.; Michel, Christine; Beckers, Justin F.; Casey, J. Alec; Flores, Hauke; Hatam, Ido; Meisterhans, Guillaume; Niemi, Andrea; Haas, Christian

2015-01-01

With near-complete replacement of Arctic multi-year ice (MYI) by first-year ice (FYI) predicted to occur within this century, it remains uncertain how the loss of MYI will impact the abundance and distribution of sea ice associated algae. In this study we compare the chlorophyll a (chl a) concentrations and physical properties of MYI and FYI from the Lincoln Sea during 3 spring seasons (2010-2012). Cores were analysed for texture, salinity, and chl a. We identified annual growth layers for 7 of 11 MYI cores and found no significant differences in chl a concentration between the bottom first-year-ice portions of MYI, upper old-ice portions of MYI, and FYI cores. Overall, the maximum chl a concentrations were observed at the bottom of young FYI. However, there were no significant differences in chl a concentrations between MYI and FYI. This suggests little or no change in algal biomass with a shift from MYI to FYI and that the spatial extent and regional variability of refrozen leads and younger FYI will likely be key factors governing future changes in Arctic sea ice algal biomass. Bottom-integrated chl a concentrations showed negative logistic relationships with snow depth and bulk (snow plus ice) integrated extinction coefficients; indicating a strong influence of snow cover in controlling bottom ice algal biomass. The maximum bottom MYI chl a concentration was observed in a hummock, representing the thickest ice with lowest snow depth of this study. Hence, in this and other studies MYI chl a biomass may be under-estimated due to an under-representation of thick MYI (e.g., hummocks), which typically have a relatively thin snowpack allowing for increased light transmission. Therefore, we suggest the on-going loss of MYI in the Arctic Ocean may have a larger impact on ice–associated production than generally assumed. PMID:25901605

Full wave two-dimensional modeling of scattering and inverse scattering for layered rough surfaces with buried objects

NASA Astrophysics Data System (ADS)

Kuo, Chih-Hao

Efficient and accurate modeling of electromagnetic scattering from layered rough surfaces with buried objects finds applications ranging from detection of landmines to remote sensing of subsurface soil moisture. The formulation of a hybrid numerical/analytical solution to electromagnetic scattering from layered rough surfaces is first presented in this dissertation. The solution to scattering from each rough interface is sought independently based on the extended boundary condition method (EBCM), where the scattered fields of each rough interface are expressed as a summation of plane waves and then cast into reflection/transmission matrices. To account for interactions between multiple rough boundaries, the scattering matrix method (SMM) is applied to recursively cascade reflection and transmission matrices of each rough interface and obtain the composite reflection matrix from the overall scattering medium. The validation of this method against the Method of Moments (MoM) and Small Perturbation Method (SPM) is addressed and the numerical results which investigate the potential of low frequency radar systems in estimating deep soil moisture are presented. Computational efficiency of the proposed method is also discussed. In order to demonstrate the capability of this method in modeling coherent multiple scattering phenomena, the proposed method has been employed to analyze backscattering enhancement and satellite peaks due to surface plasmon waves from layered rough surfaces. Numerical results which show the appearance of enhanced backscattered peaks and satellite peaks are presented. Following the development of the EBCM/SMM technique, a technique which incorporates a buried object in layered rough surfaces by employing the T-matrix method and the cylindrical-to-spatial harmonics transformation is proposed. Validation and numerical results are provided. Finally, a multi-frequency polarimetric inversion algorithm for the retrieval of subsurface soil properties using VHF/UHF band radar measurements is devised. The top soil dielectric constant is first determined using an L-band inversion algorithm. For the retrieval of subsurface properties, a time-domain inversion technique is employed together with a parameter optimization for the pulse shape of time delay echoes from VHF/UHF band radar observations. Numerical studies to investigate the accuracy of the proposed inversion technique in presence of errors are addressed.

Effects of snow grain non-sphericity on climate simulations: Sensitivity tests with the NorESM model

NASA Astrophysics Data System (ADS)

Räisänen, Petri; Makkonen, Risto; Kirkevåg, Alf

2017-04-01

Snow grains are non-spherical and generally irregular in shape. Still, in radiative transfer calculations, they are often treated as spheres. This also applies to the computation of snow albedo in the Snow, Ice, and Aerosol Radiation (SNICAR) model and in the Los Alamos sea ice model, version 4 (CICE4), both of which are employed in the Community Earth System Model and in the Norwegian Earth System Model (NorESM). In this work, we evaluate the effect of snow grain shape on climate simulated by NorESM in a slab ocean configuration of the model. An experiment with spherical snow grains (SPH) is compared with another (NONSPH) in which the snow shortwave single-scattering properties are based on a combination of non-spherical snow grain shapes optimized using measurements of angular scattering by blowing snow. The key difference between these treatments is that the asymmetry parameter is smaller in the non-spherical case (≈ 0.78 in the visible region) than in the spherical case (≈ 0.89). Therefore, for a given snow grain size, the use of non-spherical snow grains yields a higher snow broadband albedo, typically by ≈0.03. Consequently, considering the spherical case as the baseline, the use of non-spherical snow grains results in a negative radiative forcing (RF), with a global-mean top-of-the-model value of ≈ -0.22 W m-2. Although this global-mean RF is modest, it has a rather substantial impact on the climate simulated by NoRESM. In particular, the global annual-mean 2-m air temperature in NONSPH is 1.17 K lower than in SPH, with substantially larger differences at high latitudes. The climatic response is amplified by strong snow and sea ice feedbacks. It is further found that the difference between NONSPH and SPH could be largely "tuned away" by adjusting the snow grain size in the NONSPH experiment by ≈ 70%. The impact of snow grain shape on the radiative effect (RE) of absorbing aerosols in snow (black carbon and mineral dust) is also discussed. For an optically thick snowpack with a given snow grain effective size, the absorbing aerosol RE is smaller for non-spherical than for spherical snow grains. The reason for this is that due to the lower asymmetry parameter of the non-spherical snow grains, solar radiation does not penetrate as deep in snow as in the case of spherical snow grains. However, in a climate model simulation, the RE is sensitive to patterns of aerosol deposition and simulated snow cover. In fact, the global land-area mean absorbing aerosol RE is larger in the NONSPH than SPH experiment (0.193 vs. 0.168 W m-2), owing to later snowmelt in spring.

Layer detection and snowpack stratigraphy characterisation from digital penetrometer signals

NASA Astrophysics Data System (ADS)

Floyer, James Antony

Forecasting for slab avalanches benefits from precise measurements of snow stratigraphy. Snow penetrometers offer the possibility of providing detailed information about snowpack structure; however, their use has yet to be adopted by avalanche forecasting operations in Canada. A manually driven, variable rate force-resistance penetrometer is tested for its ability to measure snowpack information suitable for avalanche forecasting and for spatial variability studies on snowpack properties. Subsequent to modifications, weak layers of 5 mm thick are reliably detected from the penetrometer signals. Rate effects are investigated and found to be insignificant for push velocities between 0.5 to 100 cm s-1 for dry snow. An analysis of snow deformation below the penetrometer tip is presented using particle image velocimetry and two zones associated with particle deflection are identified. The compacted zone is a region of densified snow that is pushed ahead of the penetrometer tip; the deformation zone is a broader zone surrounding the compacted zone, where deformation is in compression and in shear. Initial formation of the compacted zone is responsible for pronounced force spikes in the penetrometer signal. A layer tracing algorithm for tracing weak layers, crusts and interfaces across transects or grids of penetrometer profiles is presented. This algorithm uses Wiener spiking deconvolution to detect a portion of the signal manually identified as a layer in one profile across to an adjacent profile. Layer tracing is found to be most effective for tracing crusts and prominent weak layers, although weak layers close to crusts were not well traced. A framework for extending this method for detecting weak layers with no prior knowledge of weak layer existence is also presented. A study relating the fracture character of layers identified in compression tests is presented. A multivariate model is presented that distinguishes between sudden and other fracture characters 80% of the time. Transects of penetrometer profiles are presented over several alpine terrain features commonly associated with spatial variability of snowpack properties. Physical processes relating to the variability of certain snowpack properties revealed in the transects is discussed. The importance of characteristic signatures for training avalanche practitioners to recognise potentially unstable terrain is also discussed.

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.

Comparison with CLPX II airborne data using DMRT model

USGS Publications Warehouse

Xu, X.; Liang, D.; Andreadis, K.M.; Tsang, L.; Josberger, E.G.

2009-01-01

In this paper, we considered a physical-based model which use numerical solution of Maxwell Equations in three-dimensional simulations and apply into Dense Media Radiative Theory (DMRT). The model is validated in two specific dataset from the second Cold Land Processes Experiment (CLPX II) at Alaska and Colorado. The data were all obtain by the Ku-band (13.95GHz) observations using airborne imaging polarimetric scatterometer (POLSCAT). Snow is a densely packed media. To take into account the collective scattering and incoherent scattering, analytical Quasi-Crystalline Approximation (QCA) and Numerical Maxwell Equation Method of 3-D simulation (NMM3D) are used to calculate the extinction coefficient and phase matrix. DMRT equations were solved by iterative solution up to 2nd order for the case of small optical thickness and full multiple scattering solution by decomposing the diffuse intensities into Fourier series was used when optical thickness exceed unity. It was shown that the model predictions agree with the field experiment not only co-polarization but also cross-polarization. For Alaska region, the input snow structure data was obtain by the in situ ground observations, while for Colorado region, we combined the VIC model to get the snow profile. ??2009 IEEE.

Simulation of hole-mobility in doped relaxed and strained Ge layers

NASA Astrophysics Data System (ADS)

Watling, Jeremy R.; Riddet, Craig; Chan, Morgan Kah H.; Asenov, Asen

2010-11-01

As silicon based metal-oxide-semiconductor field-effect transistors (MOSFETs) are reaching the limits of their performance with scaling, alternative channel materials are being considered to maintain performance in future complementary metal-oxide semiconductor technology generations. Thus there is renewed interest in employing Ge as a channel material in p-MOSFETs, due to the significant improvement in hole mobility as compared to Si. Here we employ full-band Monte Carlo to study hole transport properties in Ge. We present mobility and velocity-field characteristics for different transport directions in p-doped relaxed and strained Ge layers. The simulations are based on a method for over-coming the potentially large dynamic range of scattering rates, which results from the long-range nature of the unscreened Coulombic interaction. Our model for ionized impurity scattering includes the affects of dynamic Lindhard screening, coupled with phase-shift, and multi-ion corrections along with plasmon scattering. We show that all these effects play a role in determining the hole carrier transport in doped Ge layers and cannot be neglected.

Remote sensing of Earth terrain

NASA Technical Reports Server (NTRS)

Kong, Jin AU

1987-01-01

Earth terrain covers were modeled as random media characterized by different dielectric constants and correlation functions. In order to model sea ice with brine inclusions and vegetation with row structures, the random medium is assumed to be anisotropic. A three layer model is used to simulate a vegetation field or a snow covered ice field with the top layer being snow or leaves, the middle layer being ice or trunks, and the bottom layer being sea water or ground. The strong fluctuation theory with the distorted Born approximation is applied to the solution of the radar backscattering coefficients.

Towards Snowpack Characterization using C-band Synthetic Aperture Radar (SAR)

NASA Astrophysics Data System (ADS)

Park, J.; Forman, B. A.

2017-12-01

Sentinel 1A and 1B, operated by the European Space Agency (ESA), carries a C-band synthetic aperture radar (SAR) sensor that can be used to monitor terrestrial snow properties. This study explores the relationship between terrestrial snow-covered area, snow depth, and snow water equivalent with Sentinel 1 backscatter observations in order to better characterize snow mass. Ground-based observations collected by the National Oceanic and Atmospheric Administration - Cooperative Remote Sensing Science and Technology Center (NOAA-CREST) in Caribou, Maine in the United States are also used in the comparative analysis. Sentinel 1 Ground Range Detected (GRD) imagery with Interferometric Wide swath (IW) were preprocessed through a series of steps accounting for thermal noise, sensor orbit, radiometric calibration, speckle filtering, and terrain correction using ESA's Sentinel Application Platform (SNAP) software package, which is an open-source module written in Python. Comparisons of dual-polarized backscatter coefficients (i.e., σVV and σVH) with in-situ measurements of snow depth and SWE suggest that cross-polarized backscatter observations exhibit a modest correlation between both snow depth and SWE. In the case of the snow-covered area, a multi-temporal change detection method was used. Results using Sentinel 1 yield similar spatial patterns as when using hyperspectral observations collected by the MODerate Resolution Imaging Spectroradiometer (MODIS). These preliminary results suggest the potential application of Sentinel 1A/1B backscatter coefficients towards improved discrimination of snow cover, snow depth, and SWE. One goal of this research is to eventually merge C-band SAR backscatter observations with other snow information (e.g., passive microwave brightness temperatures) as part of a multi-sensor snow assimilation framework.

Design, Development and Testing of Web Services for Multi-Sensor Snow Cover Mapping

NASA Astrophysics Data System (ADS)

Kadlec, Jiri

This dissertation presents the design, development and validation of new data integration methods for mapping the extent of snow cover based on open access ground station measurements, remote sensing images, volunteer observer snow reports, and cross country ski track recordings from location-enabled mobile devices. The first step of the data integration procedure includes data discovery, data retrieval, and data quality control of snow observations at ground stations. The WaterML R package developed in this work enables hydrologists to retrieve and analyze data from multiple organizations that are listed in the Consortium of Universities for the Advancement of Hydrologic Sciences Inc (CUAHSI) Water Data Center catalog directly within the R statistical software environment. Using the WaterML R package is demonstrated by running an energy balance snowpack model in R with data inputs from CUAHSI, and by automating uploads of real time sensor observations to CUAHSI HydroServer. The second step of the procedure requires efficient access to multi-temporal remote sensing snow images. The Snow Inspector web application developed in this research enables the users to retrieve a time series of fractional snow cover from the Moderate Resolution Imaging Spectroradiometer (MODIS) for any point on Earth. The time series retrieval method is based on automated data extraction from tile images provided by a Web Map Tile Service (WMTS). The average required time for retrieving 100 days of data using this technique is 5.4 seconds, which is significantly faster than other methods that require the download of large satellite image files. The presented data extraction technique and space-time visualization user interface can be used as a model for working with other multi-temporal hydrologic or climate data WMTS services. The third, final step of the data integration procedure is generating continuous daily snow cover maps. A custom inverse distance weighting method has been developed to combine volunteer snow reports, cross-country ski track reports and station measurements to fill cloud gaps in the MODIS snow cover product. The method is demonstrated by producing a continuous daily time step snow presence probability map dataset for the Czech Republic region. The ability of the presented methodology to reconstruct MODIS snow cover under cloud is validated by simulating cloud cover datasets and comparing estimated snow cover to actual MODIS snow cover. The percent correctly classified indicator showed accuracy between 80 and 90% using this method. Using crowdsourcing data (volunteer snow reports and ski tracks) improves the map accuracy by 0.7--1.2%. The output snow probability map data sets are published online using web applications and web services. Keywords: crowdsourcing, image analysis, interpolation, MODIS, R statistical software, snow cover, snowpack probability, Tethys platform, time series, WaterML, web services, winter sports.

Dynamics of active layer in wooded palsas of northern Quebec

NASA Astrophysics Data System (ADS)

Jean, Mélanie; Payette, Serge

2014-02-01

Palsas are organic or mineral soil mounds having a permafrost core. Palsas are widespread in the circumpolar discontinuous permafrost zone. The annual dynamics and evolution of the active layer, which is the uppermost layer over the permafrost table and subjected to the annual freeze-thaw cycle, are influenced by organic layer thickness, snow depth, vegetation type, topography and exposure. This study examines the influence of vegetation types, with an emphasis on forest cover, on active layer dynamics of palsas in the Boniface River watershed (57°45‧ N, 76°00‧ W). In this area, palsas are often colonized by black spruce trees (Picea mariana (Mill.) B.S.P.). Thaw depth and active layer thickness were monitored on 11 wooded or non-wooded mineral and organic palsas in 2009, 2010 and 2011. Snow depth, organic layer thickness, and vegetation types were assessed. The mapping of a palsa covered by various vegetation types and a large range of organic layer thickness were used to identify the factors influencing the spatial patterns of thaw depth and active layer. The active layer was thinner and the thaw rate slower in wooded palsas, whereas it was the opposite in more exposed sites such as forest openings, shrubs and bare ground. Thicker organic layers were associated with thinner active layers and slower thaw rates. Snow depth was not an important factor influencing active layer dynamics. The topography of the mapped palsa was uneven, and the environmental factors such as organic layer, snow depth, and vegetation types were heterogeneously distributed. These factors explain a part of the spatial variation of the active layer. Over the 3-year long study, the area of one studied palsa decreased by 70%. In a context of widespread permafrost decay, increasing our understanding of factors that influence the dynamics of wooded and non-wooded palsas and understanding of the role of vegetation cover will help to define the response of discontinuous permafrost landforms to changing climatic conditions.

Bacterial Composition and Survival on Sahara Dust Particles Transported to the European Alps

PubMed Central

Meola, Marco; Lazzaro, Anna; Zeyer, Josef

2015-01-01

Deposition of Sahara dust (SD) particles is a frequent phenomenon in Europe, but little is known about the viability and composition of the bacterial community transported with SD. The goal of this study was to characterize SD-associated bacteria transported to the European Alps, deposited and entrapped in snow. During two distinct events in February and May 2014, SD particles were deposited and promptly covered by falling snow, thus preserving them in distinct ochre layers within the snowpack. In June 2014, we collected samples at different depths from a snow profile at the Jungfraujoch (Swiss Alps; 3621 m a.s.l.). After filtration, we performed various microbiological and physicochemical analyses of the snow and dust particles therein that originated in Algeria. Our results show that bacteria survive and are metabolically active after the transport to the European Alps. Using high throughput sequencing, we observed distinct differences in bacterial community composition and structure in SD-layers as compared to clean snow layers. Sporulating bacteria were not enriched in the SD-layers; however, phyla with low abundance such as Gemmatimonadetes and Deinococcus-Thermus appeared to be specific bio-indicators for SD. Since many members of these phyla are known to be adapted to arid oligotrophic environments and UV radiation, they are well suited to survive the harsh conditions of long-range airborne transport. PMID:26733988

Local Variability in Firn Layering and Compaction Rates Using GPR Data, Depth-Density Profiles, and In-Situ Reflectors in the Dry Snow Zone Near Summit Station, Greenland

NASA Astrophysics Data System (ADS)

Lines, A.; Elliott, J.; Ray, L.; Albert, M. R.

2017-12-01

Understanding the surface mass balance (SMB) of the Greenland ice sheet is critical to evaluating its response to a changing climate. A key factor in translating satellite and airborne elevation measurements of the ice sheet to SMB is understanding natural variability of firn layer depth and the relative compaction rate of these layers. A site near Summit Station, Greenland was chosen to investigate the variation in layering across a 100m by 100m grid using a 900 MHz and a 2.6 GHz ground penetrating radar (GPR) antenna. These radargrams were ground truthed by taking depth density profiles of five 2m snow pits and five 5m firn cores within the 100m by 100m grid. Combining these measurements with the accumulation data from the nearby ICECAPS weekly bamboo forest measurements, it's possible to see how the snow deposition from individual storm events can vary over a small area. Five metal reflectors were also placed on the surface of the snow in the bounds of the grid to serve as reference reflectors for similar measurements that will be taken in the 2018 field season at Summit Station. This will assist in understanding how one year of accumulation in the dry snow zone impacts compaction and how this rate can vary over a small area.

Ice Versus Rock

ERIC Educational Resources Information Center

Rule, Audrey C.; Olson, Eric A.; Dehm, Janet

2005-01-01

During a snow bank exploration, students noticed "ice caves," or pockets, in some of the larger snow banks, usually below darker layers. Most of these caves had many icicles hanging inside. Students offered reasonable explanations of ice cave formation--squirrels, kids, snow blowers--and a few students came close to the true ice cave-formation…

Structural and magnetic properties of multi-core nanoparticles analysed using a generalised numerical inversion method

PubMed Central

Bender, P.; Bogart, L. K.; Posth, O.; Szczerba, W.; Rogers, S. E.; Castro, A.; Nilsson, L.; Zeng, L. J.; Sugunan, A.; Sommertune, J.; Fornara, A.; González-Alonso, D.; Barquín, L. Fernández; Johansson, C.

2017-01-01

The structural and magnetic properties of magnetic multi-core particles were determined by numerical inversion of small angle scattering and isothermal magnetisation data. The investigated particles consist of iron oxide nanoparticle cores (9 nm) embedded in poly(styrene) spheres (160 nm). A thorough physical characterisation of the particles included transmission electron microscopy, X-ray diffraction and asymmetrical flow field-flow fractionation. Their structure was ultimately disclosed by an indirect Fourier transform of static light scattering, small angle X-ray scattering and small angle neutron scattering data of the colloidal dispersion. The extracted pair distance distribution functions clearly indicated that the cores were mostly accumulated in the outer surface layers of the poly(styrene) spheres. To investigate the magnetic properties, the isothermal magnetisation curves of the multi-core particles (immobilised and dispersed in water) were analysed. The study stands out by applying the same numerical approach to extract the apparent moment distributions of the particles as for the indirect Fourier transform. It could be shown that the main peak of the apparent moment distributions correlated to the expected intrinsic moment distribution of the cores. Additional peaks were observed which signaled deviations of the isothermal magnetisation behavior from the non-interacting case, indicating weak dipolar interactions. PMID:28397851

Identification of mineral dust layers in high alpine snow packs

NASA Astrophysics Data System (ADS)

Greilinger, Marion; Kau, Daniela; Schauer, Gerhard; Kasper-Giebl, Anne

2017-04-01

Deserts serve as a major source for aerosols in the atmosphere with mineral dust as a main contributor to primary aerosol mass. Especially the Sahara, the largest desert in the world, contributes roughly half of the primarily emitted aerosol mass found in the atmosphere [1]. The eroded Saharan dust is episodically transported over thousands of kilometers with synoptic wind patterns towards Europe [2] and reaches Austria about 20 to 30 days per year. Once the Saharan dust is removed from the atmosphere via dry or wet deposition processes, the chemical composition of the precipitation or the affected environment is significantly changed. Saharan dust serves on the one hand as high ionic input leading to an increase of ionic species such as calcium, magnesium or sulfate. On the other hand Saharan dust provides a high alkaline input neutralizing acidic components and causing the pH to increase [3]. Based on these changes in the ion composition, the pH and cross plots of the ion and conductivity balance [4] we tried to develop a method to identify Saharan dust layers in high alpine snow packs. We investigated seasonal snow packs of two high alpine sampling sites situated on the surrounding glaciers of the meteorological Sonnblick observatory serving as a global GAW (Global Atmospheric Watch) station located in the National Park Hohe Tauern in the Austrian Alps. Samples with 10 cm resolution representing the whole winter accumulation period were taken just prior to the start of snow melt at the end of April 2016. In both snow packs two layers with clearly different chemical behavior were observed. In comparison with the aerosol data from the Sonnblick observatory, these layers could be clearly identified as Saharan dust layers. Identified Saharan dust layers in the snow pack allow calculations of the ecological impact of deposited ions, with and without Saharan dust, during snow melt. Furthermore the chemical characteristics for the identification of Saharan dust layers allow a retrospective evaluation of previous snow chemistry data of snow packs of previous years or different locations. Thus the unique time of almost 30 years of snow chemistry data from glaciers surrounding the Sonnblick observatory [5] can be evaluated, focusing on the intensity and frequency of the occurance of Saharan dust layers in high alpine snow packs. Literature: [1] Boucher, O., Randall, D., Artaxo, P., Bretherton, C., Feingold, G., Forster, P., Kerminen, V.M., Kondo, Y., Liao, H., Lohmann, U., Rasch, P., Satheesh, S.K., Sherwood, S., Stevens, B., Zhang, X.Y., 2013. Clouds and aerosols. In: Stocker, T.F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S.K., Boschung, J., Nauels, A., Xia, Y., Bex, V., Midgley, P.M. (Eds.), Climate Change 2013: the Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. [2] Prospero, J.M., 1996. Saharan Dust Transport Over the North Atlantic Ocean and Mediterranean: An Overview, in: Guerzoni, S., Chester, R. (Eds.), The Impact of Desert Dust Across the Mediterranean, Environmental Science and Technology Library. Springer Netherlands, pp. 133-151. [3] Avila, A., Rod_a, F., 1991. Red rains as major contributors of nutrients and alkalinity to terrestrial ecosystems at Montseny (NE Spain). Orsis Org. Sist. 6, 215e229. [4] Miles, L.J., Yost, K.J., 1982. Quality analysis of USGS precipitation chemistry data for New York. Atmos. Environ. 1967 (16), 2889e2898. http://dx.doi.org/10.1016/ 0004-6981(82)90039-7. [5] Greilinger, Marion, et al. "Temporal changes of inorganic ion deposition in the seasonal snow cover for the Austrian Alps (1983-2014)." Atmospheric Environment 132 (2016): 141-152.

A New, Two-layer Canopy Module For The Detailed Snow Model SNOWPACK

NASA Astrophysics Data System (ADS)

Gouttevin, I.; Lehning, M.; Jonas, T.; Gustafsson, D.; Mölder, M.

2014-12-01

A new, two-layer canopy module with thermal inertia for the detailed snow model SNOWPACK is presented. Compared to the old, one-layered canopy formulation with no heat mass, this module now offers a level of physical detail consistent with the detailed snow and soil representation in SNOWPACK. The new canopy model is designed to reproduce the difference in thermal regimes between leafy and woody canopy elements and their impact on the underlying snowpack energy balance. The new model is validated against data from an Alpine and a boreal site. Comparisons of modelled sub-canopy thermal radiations to stand-scale observations at Alptal, Switzerland, demonstrate the improvements induced by our new parameterizations. The main effect is a more realistic simulation of the canopy night-time drop in temperatures. The lower drop is induced by both thermal inertia and the two-layer representation. A specific result is that such a performance cannot be achieved by a single-layered canopy model. The impact of the new parameterizations on the modelled dynamics of the sub-canopy snowpack is analysed and yields consistent results, but the frequent occurrence of mixed-precipitation events at Alptal prevents a conclusive assessment of model performances against snow data.Without specific tuning, the model is also able to reproduce the measured summertime tree trunk temperatures and biomass heat storage at the boreal site of Norunda, Sweden, with an increased accuracy in amplitude and phase. Overall, the SNOWPACK model with its enhanced canopy module constitutes a unique (in its physical process representation) atmosphere-to-soil-through-canopy-and-snow modelling chain.

Snow and frost measurements in a watershed-management research program

Treesearch

Richard S. Sartz

1957-01-01

I am going to tell you about our snow and frost work on the Hubbard Brook Experimental Forest in the White Mountains of New Hampshire. Hubbard Brook is one of several experimental areas scattered throughout the country on which personnel of the United States Forest Service are seeking to learn how different kinds of forests and methods of managing them affect...

Evaluation of Moderate-Resolution Imaging Spectroradiometer (MODIS) Snow Albedo Product (MCD43A) over Tundra

NASA Technical Reports Server (NTRS)

Wang, Zhuosen; Schaaf, Crystal B.; Chopping, Mark J.; Strahler, Alan H.; Wang, Jindi; Roman, Miguel O.; Rocha, Adrian V.; Woodcock, Curtis E.; Shuai, Yanmin

2012-01-01

This study assesses the MODIS standard Bidirectional Reflectance Distribution Function (BRDF)/Albedo product, and the daily Direct Broadcast BRDF/Albedo algorithm at tundra locations under large solar zenith angles and high anisotropic diffuse illumination and multiple scattering conditions. These products generally agree with ground-based albedo measurements during the snow cover period when the Solar Zenith Angle (SZA) is less than 70deg. An integrated validation strategy, including analysis of the representativeness of the surface heterogeneity, is performed to decide whether direct comparisons between field measurements and 500- m satellite products were appropriate or if the scaling of finer spatial resolution airborne or spaceborne data was necessary. Results indicate that the Root Mean Square Errors (RMSEs) are less than 0.047 during the snow covered periods for all MCD43 albedo products at several Alaskan tundra areas. The MCD43 1- day daily albedo product is particularly well suited to capture the rapidly changing surface conditions during the spring snow melt. Results also show that a full expression of the blue sky albedo is necessary at these large SZA snow covered areas because of the effects of anisotropic diffuse illumination and multiple scattering. In tundra locations with dark residue as a result of fire, the MODIS albedo values are lower than those at the unburned site from the start of snowmelt.

Optimization of Al2O3/TiO2/Al 2O3 Multilayer Antireflection Coating With X-Ray Scattering Techniques

NASA Astrophysics Data System (ADS)

Li, Chao

Broadband multilayer antireflection coatings (ARCs) are keys to improving solar cell efficiencies. The goal of this dissertation is to optimize the multilayer Al2O3/TiO2/Al2O 3 ARC designed for a III-V space multi-junction solar cell with understanding influences of post-annealing and varying deposition parameters on the optical properties. Accurately measuring optical properties is important in accessing optical performances of ARCs. The multilayer Al2O3/TiO 2/Al2O3 ARC and individual Al2O 3 and TiO2 layers were characterized by a novel X-ray reflectivity (XRR) method and a combined method of grazing-incidence small angle X-ray scattering (GISAXS), atomic force microscopy (AFM), and XRR developed in this study. The novel XRR method combining an enhanced Fourier analysis with specular XRR simulation effectively determines layer thicknesses and surface and interface roughnesses and/or grading with sub-nanometer precision, and densities less than three percent uncertainty. Also, the combined method of GISAXS, AFM, and XRR characterizes the distribution of pore size with one-nanometer uncertainty. Unique to this method, the diffuse scattering from surface and interface roughnesses is estimated with surface parameters (root mean square roughness sigma, lateral correlation length ξ, and Hurst parameter h) obtained from AFM, and layer densities, surface grading and interface roughness/grading obtained from specular XRR. It is then separated from pore scattering. These X-ray scattering techniques obtained consistent results and were validated by other techniques including optical reflectance, spectroscopic ellipsometry (SE), glancing incidence X-ray diffraction, transmission electron microscopy and energy dispersive X-ray spectroscopy. The ARCs were deposited by atomic layer deposition with standard parameters at 200 °C. The as-deposited individual Al2O3 layer on Si is porous and amorphous as indicated by the combined methods of GISAXS, AFM, and XRR. Both post-annealing at 400 °C for 40 min in air and varying ALD parameters can eliminate pores, and lead to consistent increases in density and refractive index determined by the XRR method, SE, and optical reflectance measurements. After annealing, the layer remains amorphous. On the other hand, the as-deposited TiO 2 layer is non-porous and amorphous. It is densified and crystallized after annealing at 400 °C for 10 min in air. The multilayer Al2O 3/TiO2/Al2O3 ARC deposited on Si has surface and interface roughnesses and/or grading on the order of one nanometer. Annealing at 400 °C for 10 min in air induces densification and crystallization of the amorphous TiO2 layer as well as possible chemical reactions between TiO2 and Si diffusing from the substrate. On the other hand, Al2O3 layers remain amorphous after annealing. The thickness of the top Al2O3 layer decreases - likely due to interdiffusion between the top two layers and loss of hydrogen from hydroxyl groups initially present in the ALD layers. The thickness of the bottom Al2O3 layer increases, probably due to the diffusion of Si atoms into the bottom layer. In addition, the multilayer Al 2O3/TiO2/Al2O3 ARC was deposited on AlInP (30nm) / GaInP (100nm) / GaAs that includes the topmost layers of III-V multi-junction solar cells. Reflectance below 5 % is achieved within nearly the whole wavelength range of the current-limiting sub-cell. Also, internal scattering occurs in the TiO2 layer possibly associated with the initiated crystallization in the TiO2 layer while absent in the amorphous Al2O3 layers.

Sensitivity of multiangle photo-polarimetry to absorbing aerosol vertical layering and properties: Quantifying measurement uncertainties for ACE requirements

NASA Astrophysics Data System (ADS)

Kalashnikova, O. V.; Garay, M. J.; Davis, A. B.; Natraj, V.; Diner, D. J.; Tanelli, S.; Martonchik, J. V.; JPl Team

2011-12-01

The impact of tropospheric aerosols on climate can vary greatly based upon relatively small variations in aerosol properties, such as composition, shape and size distributions, as well as vertical layering. Multi-angle polarimetric measurements have been advocated in recent years as an additional tool to better understand and retrieve the aerosol properties needed for improved predictions of aerosol radiative forcing on climate. The central concern of this work is the assessment of the effects of absorbing aerosol properties under measurement uncertainties achievable for future generation multi-angle, polarimetric imaging instruments under ACE mission requirements. As guidelines, the on-orbit performance of MISR for multi-angle intensity measurements and the reported polarization sensitivities of a MSPI prototype were adopted. In particular, we will focus on sensitivities to absorbing aerosol layering and observation-constrained refractive indices (resulting in various single scattering albedos (SSA)) of both spherical and non-spherical absorbing aerosol types. We conducted modeling experiments to determine how the measured Stokes vector elements are affected in UV-NIR range by the vertical distribution, mixing and layering of smoke and dust aerosols, and aerosol SSA under the assumption of a black and polarizing ocean surfaces. We use a vector successive-orders-of-scattering (SOS) and VLIDORT transfer codes that show excellent agreement. Based on our sensitivity studies we will demonstrate advantages and disadvantages of wavelength selection in UV-NIR range to access absorbing aerosol properties. Polarized UV channels do not show particular advantage for absorbing aerosol property characterization due to dominating molecular signal. Polarimetric SSA sensitivity is small, however needed to be considered in the future polarimetric retrievals under ACE-defined uncertainty.

Accurate Characterization of Winter Precipitation Using In-Situ Instrumentation, CSU-CHILL Radar, and Advanced Scattering Methods

NASA Astrophysics Data System (ADS)

Newman, A. J.; Notaros, B. M.; Bringi, V. N.; Kleinkort, C.; Huang, G. J.; Kennedy, P.; Thurai, M.

2015-12-01

We present a novel approach to remote sensing and characterization of winter precipitation and modeling of radar observables through a synergistic use of advanced in-situ instrumentation for microphysical and geometrical measurements of ice and snow particles, image processing methodology to reconstruct complex particle three-dimensional (3D) shapes, computational electromagnetics to analyze realistic precipitation scattering, and state-of-the-art polarimetric radar. Our in-situ measurement site at the Easton Valley View Airport, La Salle, Colorado, shown in the figure, consists of two advanced optical imaging disdrometers within a 2/3-scaled double fence intercomparison reference wind shield, and also includes PLUVIO snow measuring gauge, VAISALA weather station, and collocated NCAR GPS advanced upper-air system sounding system. Our primary radar is the CSU-CHILL radar, with a dual-offset Gregorian antenna featuring very high polarization purity and excellent side-lobe performance in any plane, and the in-situ instrumentation site being very conveniently located at a range of 12.92 km from the radar. A multi-angle snowflake camera (MASC) is used to capture multiple different high-resolution views of an ice particle in free-fall, along with its fall speed. We apply a visual hull geometrical method for reconstruction of 3D shapes of particles based on the images collected by the MASC, and convert these shapes into models for computational electromagnetic scattering analysis, using a higher order method of moments. A two-dimensional video disdrometer (2DVD), collocated with the MASC, provides 2D contours of a hydrometeor, along with the fall speed and other important parameters. We use the fall speed from the MASC and the 2DVD, along with state parameters measured at the Easton site, to estimate the particle mass (Böhm's method), and then the dielectric constant of particles, based on a Maxwell-Garnet formula. By calculation of the "particle-by-particle" scattering matrices over large time intervals using the in-situ measured data, we obtain, simultaneously, all polarimetric radar observables, which are then compared and analyzed against measurements by the CHILL Radar. We present and discuss results from several interesting events observed during the 2014/2015 winter campaign.

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.

ARGOS: the laser guide star system for the LBT

NASA Astrophysics Data System (ADS)

Rabien, S.; Ageorges, N.; Barl, L.; Beckmann, U.; Blümchen, T.; Bonaglia, M.; Borelli, J. L.; Brynnel, J.; Busoni, L.; Carbonaro, L.; Davies, R.; Deysenroth, M.; Durney, O.; Elberich, M.; Esposito, S.; Gasho, V.; Gässler, W.; Gemperlein, H.; Genzel, R.; Green, R.; Haug, M.; Hart, M. L.; Hubbard, P.; Kanneganti, S.; Masciadri, E.; Noenickx, J.; Orban de Xivry, G.; Peter, D.; Quirrenbach, A.; Rademacher, M.; Rix, H. W.; Salinari, P.; Schwab, C.; Storm, J.; Strüder, L.; Thiel, M.; Weigelt, G.; Ziegleder, J.

2010-07-01

ARGOS is the Laser Guide Star adaptive optics system for the Large Binocular Telescope. Aiming for a wide field adaptive optics correction, ARGOS will equip both sides of LBT with a multi laser beacon system and corresponding wavefront sensors, driving LBT's adaptive secondary mirrors. Utilizing high power pulsed green lasers the artificial beacons are generated via Rayleigh scattering in earth's atmosphere. ARGOS will project a set of three guide stars above each of LBT's mirrors in a wide constellation. The returning scattered light, sensitive particular to the turbulence close to ground, is detected in a gated wavefront sensor system. Measuring and correcting the ground layers of the optical distortions enables ARGOS to achieve a correction over a very wide field of view. Taking advantage of this wide field correction, the science that can be done with the multi object spectrographs LUCIFER will be boosted by higher spatial resolution and strongly enhanced flux for spectroscopy. Apart from the wide field correction ARGOS delivers in its ground layer mode, we foresee a diffraction limited operation with a hybrid Sodium laser Rayleigh beacon combination.

Methane fluxes during the cold season: distribution and mass transfer in the snow cover of bogs

NASA Astrophysics Data System (ADS)

Smagin, A. V.; Shnyrev, N. A.

2015-08-01

Fluxes and profile distribution of methane in the snow cover and different landscape elements of an oligotrophic West-Siberian bog (Mukhrino Research Station, Khanty-Mansiisk autonomous district) have been studied during a cold season. Simple models have been proposed for the description of methane distribution in the inert snow layer, which combine the transport of the gas and a source of constant intensity on the soil surface. The formation rates of stationary methane profiles in the snow cover have been estimated (characteristic time of 24 h). Theoretical equations have been derived for the calculation of small emission fluxes from bogs to the atmosphere on the basis of the stationary profile distribution parameters, the snow porosity, and the effective methane diffusion coefficient in the snow layer. The calculated values of methane emission significantly (by 2-3 to several tens of times) have exceeded the values measured under field conditions by the closed chamber method (0.008-0.25 mg C/(m2 h)), which indicates the possibility of underestimating the contribution of the cold period to the annual emission cycle of bog methane.

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.

Measuring the global distribution of intense convection over land with passive microwave radiometry

NASA Technical Reports Server (NTRS)

Spencer, R. W.; Santek, D. A.

1985-01-01

The global distribution of intense convective activity over land is shown to be measurable with satellite passive-microwave methods through a comparison of an empirical rain rate algorithm with a climatology of thunderstorm days for the months of June-August. With the 18 and 37 GHz channels of the Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR), the strong volume scattering effects of precipitation can be measured. Even though a single frequency (37 GHz) is responsive to the scattering signature, two frequencies are needed to remove most of the effect that variations in thermometric temperatures and soil moisture have on the brightness temperatures. Because snow cover is also a volume scatterer of microwave energy at these microwavelengths, a discrimination procedure involving four of the SMMR channels is employed to separate the rain and snow classes, based upon their differences in average thermometric temperature.

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

NASA Astrophysics Data System (ADS)

Strack, John E.

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

Empirical conversion of the vertical profile of reflectivity from Ku-band to S-band frequency

NASA Astrophysics Data System (ADS)

Cao, Qing; Hong, Yang; Qi, Youcun; Wen, Yixin; Zhang, Jian; Gourley, Jonathan J.; Liao, Liang

2013-02-01

ABSTRACT This paper presents an empirical method for converting reflectivity from Ku-band (13.8 GHz) to S-band (2.8 GHz) for several hydrometeor species, which facilitates the incorporation of Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) measurements into quantitative precipitation estimation (QPE) products from the U.S. Next-Generation Radar (NEXRAD). The development of empirical dual-frequency relations is based on theoretical simulations, which have assumed appropriate scattering and microphysical models for liquid and solid hydrometeors (raindrops, snow, and ice/hail). Particle phase, shape, orientation, and density (especially for snow particles) have been considered in applying the T-matrix method to compute the scattering amplitudes. Gamma particle size distribution (PSD) is utilized to model the microphysical properties in the ice region, melting layer, and raining region of precipitating clouds. The variability of PSD parameters is considered to study the characteristics of dual-frequency reflectivity, especially the variations in radar dual-frequency ratio (DFR). The empirical relations between DFR and Ku-band reflectivity have been derived for particles in different regions within the vertical structure of precipitating clouds. The reflectivity conversion using the proposed empirical relations has been tested using real data collected by TRMM-PR and a prototype polarimetric WSR-88D (Weather Surveillance Radar 88 Doppler) radar, KOUN. The processing and analysis of collocated data demonstrate the validity of the proposed empirical relations and substantiate their practical significance for reflectivity conversion, which is essential to the TRMM-based vertical profile of reflectivity correction approach in improving NEXRAD-based QPE.

Laws of distribution of the snow cover on the greater Caucasus (Soviet Union)

NASA Technical Reports Server (NTRS)

Gurtovaya, Y. Y.; Sulakvelidze, G. K.; Yashina, A. V.

1985-01-01

The laws of the distribution of the snow cover on the mountains of the greater Caucasus are discussed. It is shown that an extremely unequal distribution of the snow cover is caused by the complex orography of this territory, the diversity of climatic conditions and by the difference in altitude. Regions of constant, variable and unstable snow cover are distinguished because of the clearly marked division into altitude layers, each of which is characterized by climatic differences in the nature of the snow accumulation.

Snowpack ground truth: Radar test site, Steamboat Springs, Colorado, 8-16 April 1976

NASA Technical Reports Server (NTRS)

Howell, S.; Jones, E. B.; Leaf, C. F.

1976-01-01

Ground-truth data taken at Steamboat Springs, Colorado is presented. Data taken during the period April 8, 1976 - April 16, 1976 included the following: (1) snow depths and densities at selected locations (using a Mount Rose snow tube); (2) snow pits for temperature, density, and liquid water determinations using the freezing calorimetry technique and vertical layer classification; (3) snow walls were also constructed of various cross sections and documented with respect to sizes and snow characteristics; (4) soil moisture at selected locations; and (5) appropriate air temperature and weather data.

Optical properties of CO2 ice and CO2 snow from ultraviolet to infrared: Application to frost deposits and clouds on Mars

NASA Technical Reports Server (NTRS)

Hansen, Gary B.; Warren, Stephen G.; Leovy, Conway B.

1991-01-01

Researchers found that it is possible to grow large clear samples of CO2 ice at Mars-like temperatures of 150-170K if a temperature controlled refrigerator is connected to an isolated two-phase pure CO2 system. They designed a chamber for transmission measurements whose optical path between the 13mm diameter window is adjustable from 1.6mm to 107mm. This will allow measurements of linear absorption down to less than 0.01 cm (exp -1). A preliminary transmission spectrum of a thick sample of CO2 ice in the near infrared was obtained. Once revised optical constants have been determined as a function of wavelength and temperature, they can be applied to spectral reflectance/emissivity models for CO2 snow surfaces, both pure and contaminated with dust and water ice, using previously established approaches. It will be useful, also, to develop an infrared scattering-emission cloud radiance model (especially as viewed from near the limb) in order to develop a strategy for the identification of CO2 cloud layers by the atmospheric infrared radiometer instrument on the Mars Observer.

Studying of tritium content in snowpack of Degelen mountain range.

PubMed

Turchenko, D V; Lukashenko, S N; Aidarkhanov, A O; Lyakhova, O N

2014-06-01

The paper presents the results of investigation of tritium content in the layers of snow located in the streambeds of the "Degelen" massif contaminated with tritium. The objects of investigation were selected watercourses Karabulak, Uzynbulak, Aktybai located beyond the "Degelen" site. We studied the spatial distribution of tritium relative to the streambed of watercourses and defined the borders of the snow cover contamination. In the centre of the creek watercourses the snow contamination in the surface layer is as high as 40 000 Bq/L. The values of the background levels of tritium in areas not related to the streambed, which range from 40 to 50 Bq/L. The results of snow cover measurements in different seasonal periods were compared. The main mechanisms causing tritium transfer in snow were examined and identified. The most important mechanism of tritium transfer in the streams is tritium emanation from ice or soil surface. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

The snow line altitude, defined as the line separating snow from ice or firn surfaces, is among the most important parameters in the glacier mass and energy balance of tropical glaciers, since it determines net shortwave radiation via surface albedo. Therefore, hydroglaciological models require estimations of the melting layer during precipitation events, as well as parameterisations of the transient snow line. Typically, the height of the melting layer is implemented by simple air temperature extrapolation techniques, using data from nearby meteorological stations and constant lapse rates. Nonetheless, in the Peruvian mountain ranges, stations at the height of glacier tongues (>5000 m asl.) are scarce and the extrapolation techniques must use data from distant and much lower elevated stations, which need prior careful validation. Thus, reliable snowfall level and snow line altitude estimates from multiple data sets are necessary. Here, we assemble and analyse data from multiple sources (remote sensing, in-situ station data, reanalysis data) in order to assess their applicability in estimating both, the melting layer and snow line altitude. We especially focus on the potential of radar bright band data from TRMM and CloudSat satellite data for its use as a proxy for the snow/rain transition height. As expected for tropical regions, the seasonal and regional variability in the snow line altitude is comparatively low. During the course of the dry season, Landsat satellite as well as webcam images show that the transient snow line is generally increasing, interrupted by light snowfall or graupel events with low precipitation amounts and fast decay rates. We show limitations and possibilities of different data sources as well as their applicability to validate temperature extrapolation methods. Further on, we analyse the implications of the relatively low variability in seasonal snow line altitude on local glacier mass balance gradients. We show that the snow line altitude - ranging within only few hundreds of meters within one year - determines the observed high mass balance gradients. An increase in air temperature by for example 1°C during precipitation events may have even stronger impacts on glacier mass balances of tropical glacier than it would have on those of mid-latitude glaciers. This is an important reason for the high sensitivity of tropical glaciers on past and current climatic changes.

Wideband Interferometric Sensing and Imaging Polarimetry

NASA Technical Reports Server (NTRS)

Verdi, James Salvatore; Kessler, Otto; Boerner, Wolfgang-Martin

1996-01-01

Wideband Interferometric Sensing and Imaging Polarimetry (WISIP) has become an important, indispensible tool in wide area military surveillance and global environmental monitoring of the terrestrial and planetary covers. It enables dynamic, real time optimal feature extraction of significant characteristics of desirable targets and/or target sections with simultaneous suppression of undesirable background clutter and propagation path speckle at hitherto unknown clarity and never before achieved quality. WISIP may be adopted to the detection, recognition, and identification (DRI) of any stationary, moving or vibrating targets or distributed scatterer segments versus arbitrary stationary, dynamical changing and/or moving geo-physical/ecological environments, provided the instantaneous 2x2 phasor and 4x4 power density matrices for forward propagation/backward scattering, respectively, can be measured with sufficient accuracy. For example, the DRI of stealthy, dynamically moving inhomogeneous volumetric scatter environments such as precipitation scatter, the ocean/sea/lake surface boundary layers, the littoral coastal surf zones, pack ice and snow or vegetative canopies, dry sands and soils, etc. can now be successfully realized. A comprehensive overview is presented on how these modern high resolution/precision, complete polarimetric co-registered signature sensing and imaging techniques, complemented by full integration of novel navigational electronic tools, such as DGPS, will advance electromagnetic vector wave sensing and imaging towards the limits of physical realization. Various examples utilizing the most recent image data take sets of airborne, space shuttle, and satellite imaging systems demonstrate the utility of WISIP.

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,

A Forward GPS Multipath Simulator Based on the Vegetation Radiative Transfer Equation Model

PubMed Central

Wu, Xuerui; Jin, Shuanggen; Xia, Junming

2017-01-01

Global Navigation Satellite Systems (GNSS) have been widely used in navigation, positioning and timing. Nowadays, the multipath errors may be re-utilized for the remote sensing of geophysical parameters (soil moisture, vegetation and snow depth), i.e., GPS-Multipath Reflectometry (GPS-MR). However, bistatic scattering properties and the relation between GPS observables and geophysical parameters are not clear, e.g., vegetation. In this paper, a new element on bistatic scattering properties of vegetation is incorporated into the traditional GPS-MR model. This new element is the first-order radiative transfer equation model. The new forward GPS multipath simulator is able to explicitly link the vegetation parameters with GPS multipath observables (signal-to-noise-ratio (SNR), code pseudorange and carrier phase observables). The trunk layer and its corresponding scattering mechanisms are ignored since GPS-MR is not suitable for high forest monitoring due to the coherence of direct and reflected signals. Based on this new model, the developed simulator can present how the GPS signals (L1 and L2 carrier frequencies, C/A, P(Y) and L2C modulations) are transmitted (scattered and absorbed) through vegetation medium and received by GPS receivers. Simulation results show that the wheat will decrease the amplitudes of GPS multipath observables (SNR, phase and code), if we increase the vegetation moisture contents or the scatters sizes (stem or leaf). Although the Specular-Ground component dominates the total specular scattering, vegetation covered ground soil moisture has almost no effects on the final multipath signatures. Our simulated results are consistent with previous results for environmental parameter detections by GPS-MR. PMID:28587255

Seasonal evolution of the effective thermal conductivity of the snow and the soil in high Arctic herb tundra at Bylot Island, Canada

NASA Astrophysics Data System (ADS)

Domine, Florent; Barrere, Mathieu; Sarrazin, Denis

2016-11-01

The values of the snow and soil thermal conductivity, ksnow and ksoil, strongly impact the thermal regime of the ground in the Arctic, but very few data are available to test model predictions for these variables. We have monitored ksnow and ksoil using heated needle probes at Bylot Island in the Canadian High Arctic (73° N, 80° W) between July 2013 and July 2015. Few ksnow data were obtained during the 2013-2014 winter, because little snow was present. During the 2014-2015 winter ksnow monitoring at 2, 12 and 22 cm heights and field observations show that a depth hoar layer with ksnow around 0.02 W m-1 K-1 rapidly formed. At 12 and 22 cm, wind slabs with ksnow around 0.2 to 0.3 W m-1 K-1 formed. The monitoring of ksoil at 10 cm depth shows that in thawed soil ksoil was around 0.7 W m-1 K-1, while in frozen soil it was around 1.9 W m-1 K-1. The transition between both values took place within a few days, with faster thawing than freezing and a hysteresis effect evidenced in the thermal conductivity-liquid water content relationship. The fast transitions suggest that the use of a bimodal distribution of ksoil for modelling may be an interesting option that deserves further testing. Simulations of ksnow using the snow physics model Crocus were performed. Contrary to observations, Crocus predicts high ksnow values at the base of the snowpack (0.12-0.27 W m-1 K-1) and low ones in its upper parts (0.02-0.12 W m-1 K-1). We diagnose that this is because Crocus does not describe the large upward water vapour fluxes caused by the temperature gradient in the snow and soil. These fluxes produce mass transfer between the soil and lower snow layers to the upper snow layers and the atmosphere. Finally, we discuss the importance of the structure and properties of the Arctic snowpack on subnivean life, as species such as lemmings live under the snow most of the year and must travel in the lower snow layer in search of food.

Melting Frozen Droplets Using Photo-Thermal Traps

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

[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.

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.

Albedo and flux extinction coefficient of impure snow for diffuse shortwave radiation

NASA Technical Reports Server (NTRS)

Choudhury, B. J.; Mo, T.; Wang, J. R.; Chang, A. T. C.

1981-01-01

Impurities enter a snowpack as a result of fallout of scavenging by falling snow crystals. Albedo and flux extinction coefficient of soot contaminated snowcovers were studied using a two stream approximation of the radiative transfer equation. The effect of soot was calculated by two methods: independent scattering by ice grains and impurities and average refractive index for ice grains. Both methods predict a qualitatively similar effect of soot; the albedo is decreased and the extinction coefficient is increased compared to that for pure snow in the visible region; the infrared properties are largely unaffected. Quantitatively, however, the effect of soot is more pronounced in the average refractive index method. Soot contamination provides a qualitative explanation for several snow observations.

Multi-slice ptychography with large numerical aperture multilayer Laue lenses

DOE PAGES

Ozturk, Hande; Yan, Hanfei; He, Yan; ...

2018-05-09

Here, the highly convergent x-ray beam focused by multilayer Laue lenses with large numerical apertures is used as a three-dimensional (3D) probe to image layered structures with an axial separation larger than the depth of focus. Instead of collecting weakly scattered high-spatial-frequency signals, the depth-resolving power is provided purely by the intense central cone diverged from the focused beam. Using the multi-slice ptychography method combined with the on-the-fly scan scheme, two layers of nanoparticles separated by 10 μm are successfully reconstructed with 8.1 nm lateral resolution and with a dwell time as low as 0.05 s per scan point. Thismore » approach obtains high-resolution images with extended depth of field, which paves the way for multi-slice ptychography as a high throughput technique for high-resolution 3D imaging of thick samples.« less

Multi-slice ptychography with large numerical aperture multilayer Laue lenses

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

Ozturk, Hande; Yan, Hanfei; He, Yan

Here, the highly convergent x-ray beam focused by multilayer Laue lenses with large numerical apertures is used as a three-dimensional (3D) probe to image layered structures with an axial separation larger than the depth of focus. Instead of collecting weakly scattered high-spatial-frequency signals, the depth-resolving power is provided purely by the intense central cone diverged from the focused beam. Using the multi-slice ptychography method combined with the on-the-fly scan scheme, two layers of nanoparticles separated by 10 μm are successfully reconstructed with 8.1 nm lateral resolution and with a dwell time as low as 0.05 s per scan point. Thismore » approach obtains high-resolution images with extended depth of field, which paves the way for multi-slice ptychography as a high throughput technique for high-resolution 3D imaging of thick samples.« less

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

PubMed

Sun, Henry J

2013-04-03

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

Snowmelt and Infiltration Deficiencies of SSiB and Their Resolution with a New Snow-Physics Scheme

NASA Technical Reports Server (NTRS)

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

1999-01-01

A two-year 1987-1988 integration of SSiB forced with ISLSCP Initiative I surface data (as part of the Global Soil Wetness Project, GSWP, evaluation and intercomparison) produced generally realistic land surface fluxes and hydrology. Nevertheless, the evaluation also helped to identify some of the deficiencies of the current version of the Simplified Simple Biosphere (SSiB) model. The simulated snowmelt was delayed in most regions, along with excessive runoff and lack of an spring soil moisture recharge. The SSIB model had previously been noted to have a problem producing accurate soil moisture as compared to observations in the Russian snowmelt region. Similarly, various GSWP implementations of SSIB found deficiencies in this region of the simulated soil moisture and runoff as compared to other non-SSiB land-surface models (LSMs). The origin of these deficiencies was: 1) excessive cooling of the snow and ground, and 2) deep frozen soil disallowing snowmelt infiltration. The problem was most severe in regions that experience very cold winters. In SSiB, snow was treated as a unified layer with the first soil layer, causing soil and snow to cool together in the winter months, as opposed to snow cover acting as an insulator. In the spring season, a large amount of heat was required to thaw a hard frozen snow plus deep soil layers, delaying snowmelt and causing meltwater to become runoff over the frozen soil rather than infiltrate into it.

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.

Distribution and variability of total mercury in snow cover-a case study from a semi-urban site in Poznań, Poland.

PubMed

Siudek, Patrycja

2016-12-01

In the present paper, the inter-seasonal Hg variability in snow cover was examined based on multivariate statistical analysis of chemical and meteorological data. Samples of freshly fallen snow cover were collected at the semi-urban site in Poznań (central Poland), during 3-month field measurements in winter 2013. It was showed that concentrations of atmospherically deposited Hg were highly variable in snow cover, from 0.43 to 12.5 ng L -1 , with a mean value of 4.62 ng L -1 . The highest Hg concentration in snow cover coincided with local intensification of fossil fuel burning, indicating large contribution from various anthropogenic sources such as commercial and domestic heating, power generation plants, and traffic-related pollution. Moreover, the variability of Hg in collected snow samples was associated with long-range transport of pollutants, nocturnal inversion layer, low boundary layer height, and relatively low air temperature. For three snow episodes, Hg concentration in snow cover was attributed to southerly advection, suggesting significant contribution from the highly polluted region of Poland (Upper Silesia) and major European industrial hotspots. However, the peak Hg concentration was measured in samples collected during predominant N to NE advection of polluted air masses and after a relatively longer period without precipitation. Such significant contribution to the higher Hg accumulation in snow cover was associated with intensive emission from anthropogenic sources (coal combustion) and atmospheric conditions in this area. These results suggest that further measurements are needed to determine how the Hg transformation paths in snow cover change in response to longer/shorter duration of snow cover occurrence and to determine the interactions between mercury and absorbing carbonaceous aerosols in the light of climate change.

High-Albedo Salt Crusts on the Tropical Ocean of Snowball Earth: Measurements and Modeling

NASA Astrophysics Data System (ADS)

Carns, R.; Light, B.; Warren, S. G.

2014-12-01

During a Snowball Earth event, almost all of the ocean surface first freezes as sea ice. As in modern sea ice, trapped inclusions of liquid brine permeate the ice cover. As the ice grows and cools, salt crystals precipitate within the inclusions. At -23C, the most abundant salt in seawater, sodium chloride, begins to precipitate as the dihydrate mineral hydrohalite (NaCl·2H2O). Crystals of hydrohalite within the sea ice scatter light. Measurements of cold, natural sea ice show a broadband albedo increase of 10-20% when salt precipitates. Such snow-free natural sea ice with a surface temperature below -23C is rare on modern Earth, but would have been common in tropical regions of a Snowball Earth where evaporation exceeded precipitation. The persistent cold and lack of summer melt on the Snowball ocean surface, combined with net evaporation, is hypothesized to yield lag deposits of hydrohalite crystals on the ice surface. To investigate this process, we prepared laboratory-grown sea ice in a 1000 liter tank in a walk-in freezer laboratory. The ice was cooled below -23 C and the surface sprayed with a 23% NaCl solution to create a layer of hydrohalite-enriched ice, a proxy for lag deposits that would have formed over long periods of surface sublimation. We have developed a novel technique for measuring the spectral albedo of ice surfaces in the laboratory; this technique was used to monitor the evolution of the surface albedo of our salt crust as the ice matrix sublimated away leaving a layer of fine-grained hydrohalite crystals. Measurements of this hydrohalite surface crust show a very high albedo, comparable to fresh snow at visible wavelengths and significantly larger than fresh snow at near infrared wavelengths. Broadband albedos are 0.55 for bare artificial sea ice at -30C, 0.75 for ice containing 25% hydrohalite by volume, 0.84 after five days of desiccation and 0.93 after 47 days of desiccation. Using our laboratory measurements, along with estimates of grain size and crust optical depth, as inputs to Mie scattering and radiative transfer models allowed us to infer the imaginary refractive index of hydrohalite. The model can calculate albedo for pure hydrohalite crusts of varying thickness and for mixtures of ice and hydrohalite. A parameterization is presented for albedo as a function of the thickness of the hydrohalite crust.

Imaging complex objects using learning tomography

NASA Astrophysics Data System (ADS)

Lim, JooWon; Goy, Alexandre; Shoreh, Morteza Hasani; Unser, Michael; Psaltis, Demetri

2018-02-01

Optical diffraction tomography (ODT) can be described using the scattering process through an inhomogeneous media. An inherent nonlinearity exists relating the scattering medium and the scattered field due to multiple scattering. Multiple scattering is often assumed to be negligible in weakly scattering media. This assumption becomes invalid as the sample gets more complex resulting in distorted image reconstructions. This issue becomes very critical when we image a complex sample. Multiple scattering can be simulated using the beam propagation method (BPM) as the forward model of ODT combined with an iterative reconstruction scheme. The iterative error reduction scheme and the multi-layer structure of BPM are similar to neural networks. Therefore we refer to our imaging method as learning tomography (LT). To fairly assess the performance of LT in imaging complex samples, we compared LT with the conventional iterative linear scheme using Mie theory which provides the ground truth. We also demonstrate the capacity of LT to image complex samples using experimental data of a biological cell.

Operational and LIS-Based North American Land Data Assimilation Systems at National Centers for Environmental Prediction: Capability in Simulating Water and Energy Budget over the Western United States

NASA Astrophysics Data System (ADS)

Mitchell, K.; Xia, Y.; Ek, M. B.; Mocko, D. M.; Kumar, S.; Peters-Lidard, C. D.

2016-12-01

NLDAS is a multi-institutional collaborative project sponsored by NOAA's Climate Program Office and NASA's Terrestrial Hydrological Program. NLDAS has a long successful history of producing soil moisture, snow cover, total runoff and streamflow products via application of surface meteorology and precipitation datasets to drive four land-surface models (i.e., Noah, Mosaic, SAC, VIC). The purpose of the NLDAS system is to support numerous research and operational applications in the land modeling and water resources management communities. Since the operational NLDAS version was successfully implemented at NCEP in August 2014, NLDAS products are being used by over 5000 users annually worldwide, including academia, governmental agencies, and private enterprises. Over 71 million files and 144 Tb of data were downloaded in 2015. As we endeavor to increase the quality and breadth of NLDAS products, a joint effort between NASA and NCEP is underway to enable the assimilation of hydrology-relevant remote sensing datasets within NLDAS through the NASA Land Information System (LIS). The use of LIS will also enable easier transition of newly upgraded land surface models into NCEP NLDAS operations. Cold season processes significantly affect water and energy cycles, and their partitioning. As such, in the evaluation of NLDAS systems it is important to assess water and energy exchanges and/or partitioning processes over high-elevations. The Rocky Mountain region of the western U. S. is chosen as such a region to analyze and compare snow water equivalent (SWE), snow cover, snow melt, snow sublimation, total runoff, and sensible heat and latent heat flux. Reference data sets (observation-based and reanalysis) of monthly SWE, streamflow, evapotranspiration, GRACE-based total water storage change, and energy fluxes are used to evaluate model-simulated results. The results show several key factors that affect model simulations: (1) forcing errors such as precipitation partitioning into snowfall and rainfall, (2) snow albedo, (3) refreezing of melted snow, (4) boundary layer stability, and (5) freezing and thawing of soil. Though the anomaly correlations indicate good agreement with the observations or reanalysis products, large quantitative differences are evident in certain cases.

Application of Satellite SAR Imagery in Mapping the Active Layer of Arctic Permafrost

NASA Technical Reports Server (NTRS)

Zhang, Ting-Jun; Li, Shu-Sun

2003-01-01

The objective of this project is to map the spatial variation of the active layer over the arctic permafrost in terms of two parameters: (i) timing and duration of thaw period and (ii) differential frost heave and thaw settlement of the active layer. To achieve this goal, remote sensing, numerical modeling, and related field measurements are required. Tasks for the University of Colorado team are to: (i) determine the timing of snow disappearance in spring through changes in surface albedo (ii) simulate the freezing and thawing processes of the active layer and (iii) simulate the impact of snow cover on permafrost presence.

Coherent beam control through inhomogeneous media in multi-photon microscopy

NASA Astrophysics Data System (ADS)

Paudel, Hari Prasad

Multi-photon fluorescence microscopy has become a primary tool for high-resolution deep tissue imaging because of its sensitivity to ballistic excitation photons in comparison to scattered excitation photons. The imaging depth of multi-photon microscopes in tissue imaging is limited primarily by background fluorescence that is generated by scattered light due to the random fluctuations in refractive index inside the media, and by reduced intensity in the ballistic focal volume due to aberrations within the tissue and at its interface. We built two multi-photon adaptive optics (AO) correction systems, one for combating scattering and aberration problems, and another for compensating interface aberrations. For scattering correction a MEMS segmented deformable mirror (SDM) was inserted at a plane conjugate to the objective back-pupil plane. The SDM can pre-compensate for light scattering by coherent combination of the scattered light to make an apparent focus even at a depths where negligible ballistic light remains (i.e. ballistic limit). This problem was approached by investigating the spatial and temporal focusing characteristics of a broad-band light source through strongly scattering media. A new model was developed for coherent focus enhancement through or inside the strongly media based on the initial speckle contrast. A layer of fluorescent beads under a mouse skull was imaged using an iterative coherent beam control method in the prototype two-photon microscope to demonstrate the technique. We also adapted an AO correction system to an existing in three-photon microscope in a collaborator lab at Cornell University. In the second AO correction approach a continuous deformable mirror (CDM) is placed at a plane conjugate to the plane of an interface aberration. We demonstrated that this "Conjugate AO" technique yields a large field-of-view (FOV) advantage in comparison to Pupil AO. Further, we showed that the extended FOV in conjugate AO is maintained over a relatively large axial misalignment of the conjugate planes of the CDM and the aberrating interface. This dissertation advances the field of microscopy by providing new models and techniques for imaging deeply within strongly scattering tissue, and by describing new adaptive optics approaches to extending imaging FOV due to sample aberrations.

Characterizing 2-D snow stratigraphy in forests based on high-resolution snow penetrometry

NASA Astrophysics Data System (ADS)

Teich, M.; Loewe, H.; Jenkins, M. J.; Schneebeli, M.

2016-12-01

Snow stratigraphy, the characteristic layering within a seasonal snowpack, has important implications for snow remote sensing, hydrology and avalanches. Forests modify snowpack properties through interception of falling snow by tree crowns, the reduction of near-surface wind speeds, and changes to the energy balance beneath and around trees leading to a highly variable stratigraphy in space and time. The lack of snowpack observations in forests limits our ability to understand the spatio-temporal evolution of snow stratigraphy as a function of forest structure and to observe snowpack response to changes in forest cover. We examined the snowpack in field campaigns using the SnowMicroPen (SMP) under tree canopies in an Engelmann spruce forest in the central Rocky Mountains in Utah, USA. Data were collected in plots beneath canopies of undisturbed, bark beetle-disturbed and salvage logged forest stands, and a non-forested meadow. In 2015 weekly-repeated SMP penetration measurements were taken along 10 m transects at 0.3 m intervals. In the winter of 2016 bi-weekly measurements were collected along 20 m transects every 0.5 m. Using a statistical model, we derived 2-D snow density profiles as a measure of stratigraphy. The small-scale patterns in snow density revealed a more heterogeneous stratigraphy in undisturbed dense stands and also beneath bark beetle-disturbed forest. In contrast, snow stratigraphy was more homogeneous in the harvested plot despite standing small diameter trees and woody debris with effective heights up to 95 cm. As expected, snow depth and layering in non-forested plots varied only slightly over the small spatial extent sampled. Observed patterns changed throughout the snow season dependent upon snow and meteorological conditions. The results contribute to the general understanding of forest-snowpack interactions at high spatial resolution, and can be used to validate snowpack and microwave models for avalanche formation processes and SWE retrieval in forests.

Microwave Remote Sensing of Falling Snow

NASA Technical Reports Server (NTRS)

Kim, Min-Jeong; Wang, J. R.; Meneghini, R.; Johnson, B.; Tanelli, S.; Roman-Nieves, J. I.; Sekelsky, S. M.; Skofronick-Jackson, G.

2005-01-01

This study analyzes passive and active microwave measurements during the 2003 Wakasa Bay field experiment for understanding of the electromagnetic characteristics of frozen hydrometeors at millimeter-wave frequencies. Based on these understandings, parameterizations of the electromagnetic scattering properties of snow at millimeter-wave frequencies are developed and applied to the hydrometeor profiles obtained by airborne radar measurements. Calculated brightness temperatures and radar reflectivity are compared with the millimeter-wave measurements.

Continuous Snow Depth, Intensive Site 1, Barrow, Alaska

DOE Data Explorer

Bob Busey; Larry Hinzman; Vladimir Romanovsky; William Cable

2014-11-06

Continuous Snow depth data are being collected at several points within four intensive study areas in Barrow, Alaska. These data are being collected to better understand the energy dynamics above the active layer and permafrost. They complement in-situ snow and soil measurements at this location. The data could also be used as supporting measurements for other research and modeling activities.

Evidence for propagation of cold-adapted yeast in an ice core from a Siberian Altai glacier

NASA Astrophysics Data System (ADS)

Uetake, Jun; Kohshima, Shiro; Nakazawa, Fumio; Takeuchi, Nozomu; Fujita, Koji; Miyake, Takayuki; Narita, Hideki; Aizen, Vladimir; Nakawo, Masayoshi

2011-03-01

Cold environments, including glacier ice and snow, are known habitats for cold-adapted microorganisms. We investigated the potential for cold-adapted yeast to have propagated in the snow of the high-altitude Belukha glacier. We detected the presence of highly concentrated yeast (over 104 cells mL-1) in samples of both an ice core and firn snow. Increasing yeast cell concentrations in the same snow layer from July 2002 to July 2003 suggests that the yeast cells propagated in the glacier snow. A cold-adapted Rhodotorula sp. was isolated from the snow layer and found to be related to psychrophilic yeast previously found in other glacial environments (based on the D1/D2 26S rRNA domains). 26S rRNA clonal analysis directly amplified from meltwater within the ice core also revealed the presence of genus Rhodotorula. Analyses of the ice core showed that all peaks in yeast concentration corresponded to the peaks in indices of surface melting. These results support the hypothesis that occasional surface melting in an accumulation area is one of the major factors influencing cold-adapted yeast propagation.

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.

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

PubMed Central

Sun, Henry J.

2013-01-01

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

Snow multivariable data assimilation for hydrological predictions in mountain areas

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Snow White Trench After Scraping

NASA Image and Video Library

2008-07-24

This view from the Surface Stereo Imager on NASA Phoenix Mars Lander shows the trench informally named Snow White after a series of scrapings were done in preparation for collecting a sample for analysis from a hard subsurface layer.

Review of levoglucosan in glacier snow and ice studies: Recent progress and future perspectives.

PubMed

You, Chao; Xu, Chao

2018-03-01

Levoglucosan (LEV) in glacier snow and ice layers provides a fingerprint of fire activity, ranging from modern air pollution to ancient fire emissions. In this study, we review recent progress in our understanding and application of LEV in glaciers, including analytical methods, transport and post-depositional processes, and historical records. We firstly summarize progress in analytical methods for determination of LEV in glacier snow and ice. Then, we discuss the processes influencing the records of LEV in snow and ice layers. Finally, we make some recommendations for future work, such as assessing the stability of LEV and obtaining continuous records, to increase reliability of the reconstructed ancient fire activity. This review provides an update for researchers working with LEV and will facilitate the further use of LEV as a biomarker in paleo-fire studies based on ice core records. Copyright © 2017 Elsevier B.V. All rights reserved.

Snow Clouds and the Carbon Dioxide Cycle on Mars

NASA Astrophysics Data System (ADS)

Hayne, P. O.; Paige, D. A.

2009-12-01

The present climate of Mars is strongly influenced by the energy balance at the planet’s poles, with ~30% of the atmospheric mass exchanged seasonally with the polar ice caps. While the spring and summer sublimation process is observable in sunlight, the deposition process occurs in the darkness of polar night. We present direct radiometric observations of carbon dioxide snow clouds from the Mars Climate Sounder (MCS) and estimate the rate of deposition due to snowfall. We also present radiative transfer models capable of reproducing the observations and providing constraints on the radiative and thermal properties of the cap-atmosphere system. Snow clouds display a multi-layered structure with greatest opacity near the surface and extending to typical altitudes of about 20 km, with equivalent normal visible optical depths of ~0.1. Our modeling suggests the observed carbon dioxide snow grains are ~10 μm in radius, implying modest deposition rates, and suggesting the majority of the seasonal cap is deposited in a vertical region within one MCS field of view (or ~1 km) of the surface. Models reproducing the MCS limb observations only reproduce the nadir observations if the surface (or near-surface) is an optically thick layer of small (< 100 μm radius) carbon dioxide grains, which are therefore the primary cause of radiometrically cold areas (“cold spots”) observed since the Viking era. For the extreme polar regions, a persistent, ~500 km diameter snow cloud is strongly coupled to the most active cold spots, and smaller clouds (< 50 km diameter) in the latitude range 60-80°, though unobserved, cannot be ruled out by the MCS data. Based on this correlation, and observations of cold spots recurring near topographic slopes, we conclude that deposition is indeed linked to cloud formation, with the majority of material condensing below ~1 km altitude. Optically thin water ice layers are necessary to accurately model the MCS spectrum, particularly at altitudes above 20 km. This suggests water ice functions as the required condensation nucleus, consistent with earlier laboratory and theoretical studies. Important hemispherical differences are observed in the deposition process: 1) northern clouds are optically thicker at middle altitudes, ~5-15 km; 2) southern clouds are more often “detached”, showing a local maximum opacity near 20-25 km altitude; 3) mode particle radii are larger (~100 μm versus ~10 μm) in the north. Total normal optical depths are typically higher by a factor of ~2 in the north, and water ice content is relatively higher. Energy balance constraints can be placed on the system by MCS observations of outgoing infrared flux, which we map through time as an effective emissivity by taking account of the topography from MOLA and the expected frost point temperature.

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

PubMed

Weiss, Agnes; Weiss, Helmut

2017-11-16

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

Multilayered models for electromagnetic reflection amplitudes

NASA Technical Reports Server (NTRS)

Linlor, W. I.

1976-01-01

The remote sensing of snowpack characteristics with surface installations or with an airborne system could have important applications in water resource management and flood prediction. To derive some insight into such applications, the electromagnetic response of multilayer snow models is analyzed. Normally incident plane waves are assumed at frequencies ranging from 10 to the 6th power to 10 to the 10th power Hz, and amplitude reflection coefficients are calculated for models having various snow-layer combinations, including ice sheets. Layers are defined by a thickness, permittivity, and conductivity; the electrical parameters are constant or prescribed functions of frequency. To illustrate the effect of various layering combinations, results are given in the form of curves of amplitude reflection coefficients, versus frequency for a variety of models. Under simplifying assumptions, the snow thickness and effective dielectric constant can be estimated from the reflection coefficient variations as a function of frequency.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Overview of SnowEx Year 1 Activities

NASA Technical Reports Server (NTRS)

Kim, Edward; Gatebe, Charles; Hall, Dorothy; Newlin, Jerry; Misakonis, Amy; Elder, Kelly; Marshall, Hans Peter; Heimstra, Chris; Brucker, Ludovic; De Marco, Eugenia;

Springtime microwave emissivity changes in the southern Kara Sea

NASA Technical Reports Server (NTRS)

Crane, Robert G.; Anderson, Mark R.

1994-01-01

Springtime microwave brightness temperatures over first-year ice are examined for the southern Kara Sea. Snow emissivity changes are revealed by episodic drops in the 37- to 18-GHz brightness temperature gradient ratio measured by the Nimbus 7 scanning multichannel microwave radiometer. We suggest that the negative gradient ratios in spring 1982 result from increased scatter at 37 GHz due to the formation of a near-surface hoar layer. This interpretation is supported by the results of a surface radiation balance model that shows the melt signature occurring at below freezing temperatures but under clear-sky conditions with increased solar input to the surface. Published observations from the Greenland ice cap show a surface hoar layer forming under similar atmospheric conditions owing to the increased penetration and absorption of solar radiation just below the surface layer. In spring/early summer 1984 similar gradient ratio signatures occur. They appear to be due to several days of freeze-thaw cycling following the movement of a low-pressure system through the region. These changes in surface emissivity represent the transition from winter to summer conditions (as defined by the microwave response) and are shown to be regional in extent and to vary with the synoptic circulations.

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

Muon-Neutrino Electron Elastic Scattering and a Search for the Muon-Neutrino Magnetic Moment in the NOvA Near Detector

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

Wang, Biao

We use the NOvA near detector and the NuMI beam at Fermilab to study the neutrino- electron elastic scattering and the muon neutrino magnetic process beyond the Standard Model physics. The particle identications of neutrino on electron elastic scattering are trained by using the multi-layer neural networks. This thesis provides a general discussion of this technique and shows a good agreement between data and MC for the neutrino-electron elastic weak scattering. So that beneting from the precise cross-section of this channel, we are able to tune the neutrino beam ux simulation in the future. Giving the exposure of 3:62 1020more » POT in the NOvA near detector, we report 1:58 10« less

Boundary Layer Temporal Evolution Observed by Doppler LiDAR Upwind of a Lake-Effect Snow Event

NASA Astrophysics Data System (ADS)

King, D.; Kristovich, D.

2017-12-01

Lake-effect snow (LES) annually affects the Great Lakes region. It can impact communities economically, recreationally and perhaps result in fatalities. Previous studies have shown that the upwind shore of a LES system tends to be a region for mesoscale downdrafts. This study intends to show how the depth of the boundary (BL) on the upwind shore and how it could influence a LES event downstream. From December 7-10, 2016, we deployed a Halo-Photonics Streamline pulsed Doppler LiDAR at Illinois Beach State Park in Zion, Illinois, to observe the evolving BL wind structure and depth upwind of the growing LES over eastern Lake Michigan. The LiDAR scans included vertical stare, velocity-azimuth display (VAD), and range height indicator (RHI) modes to display the BL depth as well as LES cloud band structure. The BL depth was observed by turbulent velocities and backscatter profiles from the LiDAR. The BL was found to be approximately one kilometer during the day, and reduced to near surface at night. The BL depth, overall, increased from the 8th to the 9th, while snowfall rate decreased on the downwind shore. This suggests that local BL dynamics have less influence on downwind convection and snow production than originally anticipated. The larger scale environment appears to play a larger role in the multi-day BL evolution.

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.

Mapping snow cover using multi-source satellite data on big data platforms

NASA Astrophysics Data System (ADS)

Lhermitte, Stef

2017-04-01

Snowmelt is an important and dynamically changing water resource in mountainous regions around the world. In this framework, remote sensing data of snow cover data provides an essential input for hydrological models to model the water contribution from remote mountain areas and to understand how this water resource might alter as a result of climate change. Traditionally, however, many of these remote sensing products show a trade-off between spatial and temporal resolution (e.g., 16-day Landsat at 30m vs. daily MODIS at 500m resolution). With the advent of Sentinel-1 and 2 and the PROBA-V 100m products this trade-off can partially be tackled by having data that corresponds more closely to the spatial and temporal variations in snow cover typically observed over complex mountain areas. This study provides first a quantitative analysis of the trade-offs between the state-of-the-art snow cover mapping methodologies for Landsat, MODIS, PROBA-V, Sentinel-1 and 2 and applies them on big data platforms such as Google Earth Engine (GEE), RSS (ESA Research Service & Support) CloudToolbox, and the PROBA-V Mission Exploitation Platform (MEP). Second, it combines the different sensor data-cubes in one multi-sensor classification approach using newly developed spatio-temporal probability classifiers within the big data platform environments. Analysis of the spatio-temporal differences in derived snow cover areas from the different sensors reveals the importance of understanding the spatial and temporal scales at which variations occur. Moreover, it shows the importance of i) temporal resolution when monitoring highly dynamical properties such as snow cover and of ii) differences in satellite viewing angles over complex mountain areas. Finally, it highlights the potential and drawbacks of big data platforms for combining multi-source satellite data for monitoring dynamical processes such as snow cover.

Building blocks of a multi-layer PET with time sequence photon interaction discrimination and double Compton camera

NASA Astrophysics Data System (ADS)

Ilisie, V.; Giménez-Alventosa, V.; Moliner, L.; Sánchez, F.; González, A. J.; Rodríguez-Álvarez, M. J.; Benlloch, J. M.

2018-07-01

Current PET detectors have a very low sensitivity, of the order of a few percent. One of the reasons is the fact that Compton interactions are rejected. If an event involves multiple Compton scattering and the total deposited energy lays within the photoelectric peak, then an energy-weighted centroid is the given output for the coordinates of the reconstructed interaction point. This introduces distortion in the final reconstructed image. The aim of our work is to prove that Compton events are a very rich source of additional information as one can improve the resolution of the detector and implicitly the final reconstructed image. This could be a real breakthrough for PET detector technology as one should be able to obtain better results with less patient radiation. Using a PET as a double Compton camera, by means of Compton cone matching i.e., Compton cones coming from the same event should be compatible, is applied to discard randoms, patient scattered events and also, to perform a correct matching among events with multiple coincidences. In order to fully benefit experimentally from Compton events using monolithic scintillators a multi-layer configuration is needed and a good time-of-flight resolution.

Snow farming: conserving snow over the summer season

NASA Astrophysics Data System (ADS)

Grünewald, Thomas; Wolfsperger, Fabian; Lehning, Michael

2018-01-01

Summer storage of snow for tourism has seen an increasing interest in the last years. Covering large snow piles with materials such as sawdust enables more than two-thirds of the initial snow volume to be conserved. We present detailed mass balance measurements of two sawdust-covered snow piles obtained by terrestrial laser scanning during summer 2015. Results indicate that 74 and 63 % of the snow volume remained over the summer for piles in Davos, Switzerland and Martell, Italy. If snow mass is considered instead of volume, the values increase to 83 and 72 %. The difference is attributed to settling and densification of the snow. Additionally, we adapted the one-dimensional, physically based snow cover model SNOWPACK to perform simulations of the sawdust-covered snow piles. Model results and measurements agreed extremely well at the point scale. Moreover, we analysed the contribution of the different terms of the surface energy balance to snow ablation for a pile covered with a 40 cm thick sawdust layer and a pile without insulation. Short-wave radiation was the dominant source of energy for both scenarios, but the moist sawdust caused strong cooling by long-wave emission and negative sensible and latent heat fluxes. This cooling effect reduces the energy available for melt by up to a factor of 12. As a result only 9 % of the net short-wave energy remained available for melt. Finally, sensitivity studies of the parameters thickness of the sawdust layer, air temperature, precipitation and wind speed were performed. We show that sawdust thickness has a tremendous effect on snow loss. Higher air temperatures and wind speeds increase snow ablation but less significantly. No significant effect of additional precipitation could be found as the sawdust remained wet during the entire summer with the measured quantity of rain. Setting precipitation amounts to zero, however, strongly increased melt. Overall, the 40 cm sawdust provides sufficient protection for mid-elevation (approx. 1500 m a.s.l.) Alpine climates and can be managed with reasonable effort.

Erosion and entrainment of snow and ice by pyroclastic density currents: some outstanding questions (Invited)

NASA Astrophysics Data System (ADS)

Walder, J. S.

2010-12-01

A pyroclastic density current moving over snow is likely to transform to a lahar if the pyroclasts incorporate enough (melting) snow and meltwater to bring the bulk water content of the mixture to about 35% by volume. However, the processes by which such a mixture forms are still not well understood. Walder (Bull. Volcanol., v. 62, 2000) showed experimentally the existence of an erosion mechanism that functions even in the absence of relative shear motion between pyroclasts and snow substrate: a portion of the snow melted by a blanket of pyroclasts is vaporized; the flux of water vapor upward through the pyroclasts may be enough to fluidize the pyroclasts, which then convect, rapidly scour the snow substrate and transform into a slurry. But these experiments do not tell us how moving pyroclasts would erode snow, and simply releasing a hot grain flow over a snow surface in the lab gives misleading results owing to improper scaling of τ/σ , the ratio of the shear stress τ exerted by the pyroclastic flow to the shear strength σ of snow. There seems to be no way around this problem for experiments with actual snow. However, it may be possible to circumvent the scaling problem by replacing the snow substrate by a gas-fluidized particle bed: by varying the gas flux, the apparent shear strength of the particle bed can be varied. Such an investigation of erosional processes could be done at room temperature. Snow-avalanche studies (for example, Gauer and Issler, Ann. Glaciol. v. 38, 2003) may provide some insight into snow erosion by a pyroclastic density current. Snow is eroded at the base of a dense snow avalanche by abrasion, particle impacts, and—at the avalanche head—by plowing and a “blasting” mechanism associated with compression of the snowpack and expulsion of pore fluid (air). Erosion at the avalanche head seems to be particularly important. Similar processes are likely to occur when the over-riding flow comprises hot grains. The laboratory release of a hot grain flow over snow, although improperly scaled for investigating erosive processes, does demonstrate that snow hydrology and snowpack stability may be critical in the transformation of pyroclastic density currents to lahars. When such an experiment is run in a sloping flume, with meltwater able to drain freely at the base of the snow layer, the hot grain flow spreads over the snow surface and then comes to rest--no slurry is produced. In contrast, if meltwater drainage is blocked, the wet snow layer fails at its bed, mobilizes as a slush flow, and mixes with the hot grains to form a slurry. Ice layers within a natural snowpack would likewise block meltwater drainage and be conducive to the formation of slush flows. Abrasion and particle impacts—processes that have been studied intensively by engineers concerned with the wear of surfaces in machinery—probably play an important role in the erosion of glacier ice by pyroclastic density currents. A prime example may be the summit ice cap of Nevado del Ruiz, Colombia, which was left grooved by the eruption of 1985 (Thouret, J. Volcanol. Geotherm. Res., v. 41, 1990). Erosion of glacier ice is also strongly controlled by the orientation of crevasses, which can “capture” pyroclastic currents. This phenomenon was well displayed at Mount Redoubt, Alaska during the eruptions of 1989-90 and 2009.

Objective Characterization of Snow Microstructure for Microwave Emission Modeling

NASA Technical Reports Server (NTRS)

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

2012-01-01

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

Improving NIR snow pit stratigraphy observations by introducing a controlled NIR light source

NASA Astrophysics Data System (ADS)

Dean, J.; Marshall, H.; Rutter, N.; Karlson, A.

2013-12-01

Near-infrared (NIR) photography in a prepared snow pit measures mm-/grain-scale variations in snow structure, as reflectivity is strongly dependent on microstructure and grain size at the NIR wavelengths. We explore using a controlled NIR light source to maximize signal to noise ratio and provide uniform incident, diffuse light on the snow pit wall. NIR light fired from the flash is diffused across and reflected by an umbrella onto the snow pit; the lens filter transmits NIR light onto the spectrum-modified sensor of the DSLR camera. Lenses are designed to refract visible light properly, not NIR light, so there must be a correction applied for the subsequent NIR bright spot. To avoid interpolation and debayering algorithms automatically performed by programs like Adobe's Photoshop on the images, the raw data are analyzed directly in MATLAB. NIR image data show a doubling of the amount of light collected in the same time for flash over ambient lighting. Transitions across layer boundaries in the flash-lit image are detailed by higher camera intensity values than ambient-lit images. Curves plotted using median intensity at each depth, normalized to the average profile intensity, show a separation between flash- and ambient-lit images in the upper 10-15 cm; the ambient-lit image curve asymptotically approaches the level of the flash-lit image curve below 15cm. We hypothesize that the difference is caused by additional ambient light penetrating the upper 10-15 cm of the snowpack from above and transmitting through the wall of the snow pit. This indicates that combining NIR ambient and flash photography could be a powerful technique for studying penetration depth of radiation as a function of microstructure and grain size. The NIR flash images do not increase the relative contrast at layer boundaries; however, the flash more than doubles the amount of recorded light and controls layer noise as well as layer boundary transition noise.

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).

On the impact of snow cover on daytime pollution dispersion

NASA Astrophysics Data System (ADS)

Segal, M.; Garratt, J. R.; Pielke, R. A.; Hildebrand, P.; Rogers, F. A.; Cramer, J.; Schanot, A.

A preliminary evaluation of the impact of snow cover on daytime pollutant dispersion conditions is made by using conceptual, scaling, and observational analyses. For uniform snow cover and synoptically unperturbed sunny conditions, observations indicate a considerate suppression of the surface sensible heat flux, the turbulence, and the development of the daytime atmospheric boundary layer (ABL) when compared to snow-free conditions. However, under conditions of non-uniform snow cover, as in urban areas, or associated with vegetated areas or bare ground patches, a milder effect on pollutant dispersion conditions would be expected. Observed concentrations of atmospheric particles within the ABL, and surface pollutant concentrations in urban areas, reflect the impact of snow cover on the modification of ABL characteristics.

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

NASA Astrophysics Data System (ADS)

Ebtehaj, A.; Foufoula-Georgiou, E.

2016-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Influence of Sea Ice Crack Formation on the Spatial Distribution of Nutrients and Microalgae in Flooded Antarctic Multiyear Ice

NASA Astrophysics Data System (ADS)

Nomura, Daiki; Aoki, Shigeru; Simizu, Daisuke; Iida, Takahiro

2018-02-01

Cracks are common and natural features of sea ice formed in the polar oceans. In this study, a sea ice crack in flooded, multiyear, land-fast Antarctic sea ice was examined to assess its influence on biological productivity and the transport of nutrients and microalgae into the upper layers of neighboring sea ice. The water inside the crack and the surrounding host ice were characterized by a strong discoloration (brown color), an indicator of a massive algal bloom. Salinity and oxygen isotopic ratio measurements indicated that 64-84% of the crack water consisted of snow meltwater supplied during the melt season. Measurements of nutrient and chlorophyll a concentrations within the slush layer pool (the flooded layer at the snow-ice interface) revealed the intrusion of water from the crack, likely forced by mixing with underlying seawater during the tidal cycle. Our results suggest that sea ice crack formation provides conditions favorable for algal blooms by directly exposing the crack water to sunlight and supplying nutrients from the under-ice water. Subsequently, constituents of the crack water modified by biological activity were transported into the upper layer of the flooded sea ice. They were then preserved in the multiyear ice column formed by upward growth of sea ice caused by snow ice formation in areas of significant snow accumulation.

Improved ocean-color remote sensing in the Arctic using the POLYMER algorithm

NASA Astrophysics Data System (ADS)

Frouin, Robert; Deschamps, Pierre-Yves; Ramon, Didier; Steinmetz, François

2012-10-01

Atmospheric correction of ocean-color imagery in the Arctic brings some specific challenges that the standard atmospheric correction algorithm does not address, namely low solar elevation, high cloud frequency, multi-layered polar clouds, presence of ice in the field-of-view, and adjacency effects from highly reflecting surfaces covered by snow and ice and from clouds. The challenges may be addressed using a flexible atmospheric correction algorithm, referred to as POLYMER (Steinmetz and al., 2011). This algorithm does not use a specific aerosol model, but fits the atmospheric reflectance by a polynomial with a non spectral term that accounts for any non spectral scattering (clouds, coarse aerosol mode) or reflection (glitter, whitecaps, small ice surfaces within the instrument field of view), a spectral term with a law in wavelength to the power -1 (fine aerosol mode), and a spectral term with a law in wavelength to the power -4 (molecular scattering, adjacency effects from clouds and white surfaces). Tests are performed on selected MERIS imagery acquired over Arctic Seas. The derived ocean properties, i.e., marine reflectance and chlorophyll concentration, are compared with those obtained with the standard MEGS algorithm. The POLYMER estimates are more realistic in regions affected by the ice environment, e.g., chlorophyll concentration is higher near the ice edge, and spatial coverage is substantially increased. Good retrievals are obtained in the presence of thin clouds, with ocean-color features exhibiting spatial continuity from clear to cloudy regions. The POLYMER estimates of marine reflectance agree better with in situ measurements than the MEGS estimates. Biases are 0.001 or less in magnitude, except at 412 and 443 nm, where they reach 0.005 and 0.002, respectively, and root-mean-squared difference decreases from 0.006 at 412 nm to less than 0.001 at 620 and 665 nm. A first application to MODIS imagery is presented, revealing that the POLYMER algorithm is robust when pixels are contaminated by sea ice.

Towards Mott design by δ-doping of strongly correlated titanates

NASA Astrophysics Data System (ADS)

Lechermann, Frank; Obermeyer, Michael

2015-04-01

Doping the distorted-perovskite Mott insulators LaTiO3 and GdTiO3 with a single SrO layer along the [001] direction gives rise to a rich correlated electronic structure. A realistic superlattice study by means of the charge self-consistent combination of density functional theory with dynamical mean-field theory reveals layer- and temperature-dependent multi-orbital metal-insulator transitions. An orbital-selective metallic layer at the interface dissolves via an orbital-polarized doped-Mott state into an orbital-ordered insulating regime beyond the two conducting TiO2 layers. We find large differences in the scattering behavior within the latter. Breaking the spin symmetry in δ-doped GdTiO3 results in blocks of ferromagnetic itinerant and ferromagnetic Mott-insulating layers that are coupled antiferromagnetically.

NPP ATMS Snowfall Rate Product

NASA Technical Reports Server (NTRS)

Meng, Huan; Ferraro, Ralph; Kongoli, Cezar; Wang, Nai-Yu; Dong, Jun; Zavodsky, Bradley; Yan, Banghua

2015-01-01

Passive microwave measurements at certain high frequencies are sensitive to the scattering effect of snow particles and can be utilized to retrieve snowfall properties. Some of the microwave sensors with snowfall sensitive channels are Advanced Microwave Sounding Unit (AMSU), Microwave Humidity Sounder (MHS) and Advance Technology Microwave Sounder (ATMS). ATMS is the follow-on sensor to AMSU and MHS. Currently, an AMSU and MHS based land snowfall rate (SFR) product is running operationally at NOAA/NESDIS. Based on the AMSU/MHS SFR, an ATMS SFR algorithm has been developed recently. The algorithm performs retrieval in three steps: snowfall detection, retrieval of cloud properties, and estimation of snow particle terminal velocity and snowfall rate. The snowfall detection component utilizes principal component analysis and a logistic regression model. The model employs a combination of temperature and water vapor sounding channels to detect the scattering signal from falling snow and derive the probability of snowfall (Kongoli et al., 2015). In addition, a set of NWP model based filters is also employed to improve the accuracy of snowfall detection. Cloud properties are retrieved using an inversion method with an iteration algorithm and a two-stream radiative transfer model (Yan et al., 2008). A method developed by Heymsfield and Westbrook (2010) is adopted to calculate snow particle terminal velocity. Finally, snowfall rate is computed by numerically solving a complex integral. NCEP CMORPH analysis has shown that integration of ATMS SFR has improved the performance of CMORPH-Snow. The ATMS SFR product is also being assessed at several NWS Weather Forecast Offices for its usefulness in weather forecast.

Snow water equivalent determination by microwave radiometry

NASA Technical Reports Server (NTRS)

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

1981-01-01

One of the most important parameters for accurate snowmelt runoff prediction is snow water equivalent (SWE) which is contentionally monitored using observations made at widely scattered points in or around specific watersheds. Remote sensors which provide data with better spatial and temporal coverage can be used to improve the SWE estimates. Microwave radiation, which can penetrate through a snowpack, may be used to infer the SWE. Calculations made from a microscopic scattering model were used to simulate the effect of varying SWE on the microwave brightness temperature. Data obtained from truck mounted, airborne and spaceborne systems from various test sites were studied. The simulated SWE compares favorable with the measured SWE. In addition, whether the underlying soil is frozen or thawed can be discriminated successfully on the basis of the polarization of the microwave radiation.

The Impact of Microstructure on an Accurate Snow Scattering Parameterization at Microwave Wavelengths

NASA Astrophysics Data System (ADS)

Honeyager, Ryan

High frequency microwave instruments are increasingly used to observe ice clouds and snow. These instruments are significantly more sensitive than conventional precipitation radar. This is ideal for analyzing ice-bearing clouds, for ice particles are tenuously distributed and have effective densities that are far less than liquid water. However, at shorter wavelengths, the electromagnetic response of ice particles is no longer solely dependent on particle mass. The shape of the ice particles also plays a significant role. Thus, in order to understand the observations of high frequency microwave radars and radiometers, it is essential to model the scattering properties of snowflakes correctly. Several research groups have proposed detailed models of snow aggregation. These particle models are coupled with computer codes that determine the particles' electromagnetic properties. However, there is a discrepancy between the particle model outputs and the requirements of the electromagnetic models. Snowflakes have countless variations in structure, but we also know that physically similar snowflakes scatter light in much the same manner. Structurally exact electromagnetic models, such as the discrete dipole approximation (DDA), require a high degree of structural resolution. Such methods are slow, spending considerable time processing redundant (i.e. useless) information. Conversely, when using techniques that incorporate too little structural information, the resultant radiative properties are not physically realistic. Then, we ask the question, what features are most important in determining scattering? This dissertation develops a general technique that can quickly parameterize the important structural aspects that determine the scattering of many diverse snowflake morphologies. A Voronoi bounding neighbor algorithm is first employed to decompose aggregates into well-defined interior and surface regions. The sensitivity of scattering to interior randomization is then examined. The loss of interior structure is found to have a negligible impact on scattering cross sections, and backscatter is lowered by approximately five percent. This establishes that detailed knowledge of interior structure is not necessary when modeling scattering behavior, and it also provides support for using an effective medium approximation to describe the interiors of snow aggregates. The Voronoi diagram-based technique enables the almost trivial determination of the effective density of this medium. A bounding neighbor algorithm is then used to establish a greatly improved approximation of scattering by equivalent spheroids. This algorithm is then used to posit a Voronoi diagram-based definition of effective density approach, which is used in concert with the T-matrix method to determine single-scattering cross sections. The resulting backscatters are found to reasonably match those of the DDA over frequencies from 10.65 to 183.31 GHz and particle sizes from a few hundred micrometers to nine millimeters in length. Integrated error in backscatter versus DDA is found to be within 25% at 94 GHz. Errors in scattering cross-sections and asymmetry parameters are likewise small. The observed cross-sectional errors are much smaller than the differences observed among different particle models. This represents a significant improvement over established techniques, and it demonstrates that the radiative properties of dense aggregate snowflakes may be adequately represented by equal-mass homogeneous spheroids. The present results can be used to supplement retrieval algorithms used by CloudSat, EarthCARE, Galileo, GPM and SWACR radars. The ability to predict the full range of scattering properties is potentially also useful for other particle regimes where a compact particle approximation is applicable.

Snow depth of the Weddell and Bellingshausen sea ice covers from IceBridge surveys in 2010 and 2011: An examination

NASA Astrophysics Data System (ADS)

Kwok, R.; Maksym, T.

2014-07-01

We examine the snow radar data from the Weddell and Bellingshausen Seas acquired by eight IceBridge (OIB) flightlines in October of 2010 and 2011. In snow depth retrieval, the sidelobes from the stronger scattering snow-ice (s-i) interfaces could be misidentified as returns from the weaker air-snow (a-s) interfaces. In this paper, we first introduce a retrieval procedure that accounts for the structure of the radar system impulse response followed by a survey of the snow depths in the Weddell and Bellingshausen Seas. Limitations and potential biases in our approach are discussed. Differences between snow depth estimates from a repeat survey of one Weddell Sea track separated by 12 days, without accounting for variability due to ice motion, is -0.7 ± 13.6 cm. Average snow depth is thicker in coastal northwestern Weddell and thins toward Cape Norvegia, a decrease of >30 cm. In the Bellingshausen, the thickest snow is found nearshore in both Octobers and is thickest next to the Abbot Ice Shelf. Snow depth is linearly related to freeboard when freeboards are low but diverge as the freeboard increases especially in the thicker/rougher ice of the western Weddell. We find correlations of 0.71-0.84 between snow depth and surface roughness suggesting preferential accumulation over deformed ice. Retrievals also seem to be related to radar backscatter through surface roughness. Snow depths reported here, generally higher than those from in situ records, suggest dissimilarities in sample populations. Implications of these differences on Antarctic sea ice thickness are discussed.

[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.

Reflection and Transmission of Plane Electromagnetic Waves by a Geologic Layer.

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

Aldridge, David F.

Electric field and magnetic field reflection and transmission responses generated by a plane wave normally incident onto a finite - thickness geologic layer are mathematically derived and numerically evaluated. A thin layer with enhanced electric current conductivity and/or magnetic permeability is a reasonable geophysical representation of a hydraulic fracture inject ed with a high - contrast proppant pack. Both theory and numerics indicate that backward - and forward - scattered electromagnetic wavefields are potentially observable in a field experiment, despite the extreme thinness of a fracture compared to a typical low - frequency electromagnetic wavelength. The First Born Approximation (FBA)more » representation of layer scattering, significant for inversion studies, is shown to be accurate for a thin layer with mild medium parameter (i.e., conductivity, permeability, and per mittivity) contrasts with the surrounding homogeneous wholespace. However, FBA scattering theory breaks down for thick layers and strong parameter contrasts. ACKNOWLEDGEMENTS Sandia National Laboratories is a multi - mission laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the US Department of Energy's National Nuclear Security Administration under contract DE - AC04 - 94AL85000. This research is conducted under the auspices of CRADA (Cooperative Research and Development Agreement) SC11/01780.00 between Carbo Ceramics Inc. and Sandia National Laboratories. The author acknowledges former Carbo R&D Vic e - President Mr. Chad Cannan and former SNL Geophysics Department manage r Ms. Amy Halloran for their interest i n and support of this work. Technical discussions with Project Manager and Principal Investigator Dr. Chester J. Weiss of the SNL Geophysics Department greatly benefited this work. Dr. Lewis C. Bartel, formerly with S NL and presently a consultant to Carbo Ceramics, provided many useful and intuitive insights, and is acknowledged as the originator of the concept underpinning a recent patent grant (Aldridge and Bartel, 2016) involving electromagnetic wave scattering.« less

Airborne Spectral Measurements of Surface-Atmosphere Anisotropy for Arctic Sea Ice and Tundra

NASA Technical Reports Server (NTRS)

Arnold, G. Thomas; Tsay, Si-Chee; King, Michael D.; Li, Jason Y.; Soulen, Peter F.

1999-01-01

Angular distributions of spectral reflectance for four common arctic surfaces: snow-covered sea ice, melt-season sea ice, snow-covered tundra, and tundra shortly after snowmelt were measured using an aircraft based, high angular resolution (1-degree) multispectral radiometer. Results indicate bidirectional reflectance is higher for snow-covered sea ice than melt-season sea ice at all wavelengths between 0.47 and 2.3 pm, with the difference increasing with wavelength. Bidirectional reflectance of snow-covered tundra is higher than for snow-free tundra for measurements less than 1.64 pm, with the difference decreasing with wavelength. Bidirectional reflectance patterns of all measured surfaces show maximum reflectance in the forward scattering direction of the principal plane, with identifiable specular reflection for the melt-season sea ice and snow-free tundra cases. The snow-free tundra had the most significant backscatter, and the melt-season sea ice the least. For sea ice, bidirectional reflectance changes due to snowmelt were more significant than differences among the different types of melt-season sea ice. Also the spectral-hemispherical (plane) albedo of each measured arctic surface was computed. Comparing measured nadir reflectance to albedo for sea ice and snow-covered tundra shows albedo underestimated 5-40%, with the largest bias at wavelengths beyond 1 pm. For snow-free tundra, nadir reflectance underestimates plane albedo by about 30-50%.

Coherence-Gated Sensorless Adaptive Optics Multiphoton Retinal Imaging

PubMed Central

Cua, Michelle; Wahl, Daniel J.; Zhao, Yuan; Lee, Sujin; Bonora, Stefano; Zawadzki, Robert J.; Jian, Yifan; Sarunic, Marinko V.

2016-01-01

Multiphoton microscopy enables imaging deep into scattering tissues. The efficient generation of non-linear optical effects is related to both the pulse duration (typically on the order of femtoseconds) and the size of the focused spot. Aberrations introduced by refractive index inhomogeneity in the sample distort the wavefront and enlarge the focal spot, which reduces the multiphoton signal. Traditional approaches to adaptive optics wavefront correction are not effective in thick or multi-layered scattering media. In this report, we present sensorless adaptive optics (SAO) using low-coherence interferometric detection of the excitation light for depth-resolved aberration correction of two-photon excited fluorescence (TPEF) in biological tissue. We demonstrate coherence-gated SAO TPEF using a transmissive multi-actuator adaptive lens for in vivo imaging in a mouse retina. This configuration has significant potential for reducing the laser power required for adaptive optics multiphoton imaging, and for facilitating integration with existing systems. PMID:27599635

Coherence-Gated Sensorless Adaptive Optics Multiphoton Retinal Imaging.

PubMed

Cua, Michelle; Wahl, Daniel J; Zhao, Yuan; Lee, Sujin; Bonora, Stefano; Zawadzki, Robert J; Jian, Yifan; Sarunic, Marinko V

2016-09-07

Multiphoton microscopy enables imaging deep into scattering tissues. The efficient generation of non-linear optical effects is related to both the pulse duration (typically on the order of femtoseconds) and the size of the focused spot. Aberrations introduced by refractive index inhomogeneity in the sample distort the wavefront and enlarge the focal spot, which reduces the multiphoton signal. Traditional approaches to adaptive optics wavefront correction are not effective in thick or multi-layered scattering media. In this report, we present sensorless adaptive optics (SAO) using low-coherence interferometric detection of the excitation light for depth-resolved aberration correction of two-photon excited fluorescence (TPEF) in biological tissue. We demonstrate coherence-gated SAO TPEF using a transmissive multi-actuator adaptive lens for in vivo imaging in a mouse retina. This configuration has significant potential for reducing the laser power required for adaptive optics multiphoton imaging, and for facilitating integration with existing systems.

An Overview of Snow Photochemistry: Evidence, Mechanisms and Impacts

NASA Technical Reports Server (NTRS)

Grannas, A. M.; Jones, A. E.; Dibb, J.; Ammann, M.; Anastasio, C.; Beine, H. J.; Bergin, M.; Bottenheim, J.; Boxe, C. S.; Carver, G.;

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

Snowpack spatial and temporal variability assessment using SMP high-resolution penetrometer

NASA Astrophysics Data System (ADS)

Komarov, Anton; Seliverstov, Yuriy; Sokratov, Sergey; Grebennikov, Pavel

2017-04-01

This research is focused on study of spatial and temporal variability of structure and characteristics of snowpack, quick identification of layers based on hardness and dispersion values received from snow micro penetrometer (SMP). We also discuss the detection of weak layers and definition of their parameters in non-alpine terrain. As long as it is the first SMP tool available in Russia, our intent is to test it in different climate and weather conditions. During two separate snowpack studies in plain and mountain landscapes, we derived density and grain size profiles by comparing snow density and grain size from snowpits and SMP measurements. The first case study was MSU meteorological observatory test site in Moscow. SMP data was obtained by 6 consecutive measurements along 10 m transects with a horizontal resolution of approximately 50 cm. The detailed description of snowpack structure, density, grain size, air and snow temperature was also performed. By comparing this information, the detailed scheme of snowpack evolution was created. The second case study was in Khibiny mountains. One 10-meter-long transect was made. SMP, density, grain size and snow temperature data was obtained with horizontal resolution of approximately 50 cm. The high-definition profile of snowpack density variation was acquired using received data. The analysis of data reveals high spatial and temporal variability in snow density and layer structure in both horizontal and vertical dimensions. It indicates that the spatial variability is exhibiting similar spatial patterns as surface topology. This suggests a strong influence from such factors as wind and liquid water pressure on the temporal and spatial evolution of snow structure. It was also defined, that spatial variation of snowpack characteristics is substantial even within homogeneous plain landscape, while in high-latitude mountain regions it grows significantly.

Dark-field transmission electron microscopy and the Debye-Waller factor of graphene

PubMed Central

Hubbard, William A.; White, E. R.; Dawson, Ben; Lodge, M. S.; Ishigami, Masa; Regan, B. C.

2014-01-01

Graphene's structure bears on both the material's electronic properties and fundamental questions about long range order in two-dimensional crystals. We present an analytic calculation of selected area electron diffraction from multi-layer graphene and compare it with data from samples prepared by chemical vapor deposition and mechanical exfoliation. A single layer scatters only 0.5% of the incident electrons, so this kinematical calculation can be considered reliable for five or fewer layers. Dark-field transmission electron micrographs of multi-layer graphene illustrate how knowledge of the diffraction peak intensities can be applied for rapid mapping of thickness, stacking, and grain boundaries. The diffraction peak intensities also depend on the mean-square displacement of atoms from their ideal lattice locations, which is parameterized by a Debye-Waller factor. We measure the Debye-Waller factor of a suspended monolayer of exfoliated graphene and find a result consistent with an estimate based on the Debye model. For laboratory-scale graphene samples, finite size effects are sufficient to stabilize the graphene lattice against melting, indicating that ripples in the third dimension are not necessary. PMID:25242882

Dark-field transmission electron microscopy and the Debye-Waller factor of graphene.

PubMed

Shevitski, Brian; Mecklenburg, Matthew; Hubbard, William A; White, E R; Dawson, Ben; Lodge, M S; Ishigami, Masa; Regan, B C

2013-01-15

Graphene's structure bears on both the material's electronic properties and fundamental questions about long range order in two-dimensional crystals. We present an analytic calculation of selected area electron diffraction from multi-layer graphene and compare it with data from samples prepared by chemical vapor deposition and mechanical exfoliation. A single layer scatters only 0.5% of the incident electrons, so this kinematical calculation can be considered reliable for five or fewer layers. Dark-field transmission electron micrographs of multi-layer graphene illustrate how knowledge of the diffraction peak intensities can be applied for rapid mapping of thickness, stacking, and grain boundaries. The diffraction peak intensities also depend on the mean-square displacement of atoms from their ideal lattice locations, which is parameterized by a Debye-Waller factor. We measure the Debye-Waller factor of a suspended monolayer of exfoliated graphene and find a result consistent with an estimate based on the Debye model. For laboratory-scale graphene samples, finite size effects are sufficient to stabilize the graphene lattice against melting, indicating that ripples in the third dimension are not necessary.

Discrimination Between Clouds and Snow in Landsat 8 Imagery: an Assessment of Current Methods and a New Approach

NASA Astrophysics Data System (ADS)

Stillinger, T.; Dozier, J.; Phares, N.; Rittger, K.

2015-12-01

Discrimination between snow and clouds poses a serious but tractable challenge to the consistent delivery of high-quality information on mountain snow from remote sensing. Clouds obstruct the surface from the sensor's view, and the similar optical properties of clouds and snow make accurate discrimination difficult. We assess the performance of the current Landsat 8 operational snow and cloud mask products (LDCM CCA and CFmask), along with a new method, using over one million manually identified snow and clouds pixels in Landsat 8 scenes. The new method uses physically based scattering models to generate spectra in each Landsat 8 band, at that scene's solar illumination, for snow and cloud particle sizes that cover the plausible range for each. The modeled spectra are compared to pixels' spectra via several independent ways to identify snow and clouds. The results are synthesized to create a final snow/cloud mask, and the method can be applied to any multispectral imager with bands covering the visible, near-infrared, and shortwave-infrared regions. Each algorithm we tested misidentifies snow and clouds in both directions to varying degrees. We assess performance with measures of Precision, Recall, and the F statistic, which are based on counts of true and false positives and negatives. Tests for significance in differences between spectra in the measured and modeled values among incorrectly identified pixels help ascertain reasons for misidentification. A cloud mask specifically designed to separate snow from clouds is a valuable tool for those interested in remotely sensing snow cover. Given freely available remote sensing datasets and computational tools to feasibly process entire mission histories for an area of interest, enabling researchers to reliably identify and separate snow and clouds increases the usability of the data for hydrological and climatological studies.

Representing Precipitation Ice Species With Both Spherical and Nonspherical Particles for Radiative Transfer Modeling of Microphysics-Consistent Cloud Microwave Scattering Properties

NASA Astrophysics Data System (ADS)

Sieron, Scott B.; Zhang, Fuqing; Clothiaux, Eugene E.; Zhang, Lily N.; Lu, Yinghui

2018-04-01

Cloud microwave scattering properties for the Community Radiative Transfer Model (CRTM) have previously been created to be consistent with the particle size distributions specified by the WSM6 single-moment microphysics scheme. Here substitution of soft sphere scattering properties with nonspherical particle scattering properties is explored in studies of Hurricane Karl (2010). A nonsphere replaces a sphere of the same maximum dimension, and the number of particles of a given size is scaled by the ratio of the sphere to nonsphere mass to keep the total mass of a given particle size unchanged. The replacement of homogeneous soft sphere snow particles is necessary to resolve a highly evident issue in CRTM simulations: precipitation-affected brightness temperatures are generally warmer at 183 GHz than at 91.7 GHz, whereas the reverse is seen in observations. Using sector snowflakes resolve this issue better than using columns/plates, bullet rosettes, or dendrites. With sector snowflakes, both of these high frequencies have low simulated brightness temperatures compared to observations, providing a clear and consistent suggestion that snow is being overproduced in the examined simulation using WSM6 microphysics. Graupel causes cold biases at lower frequencies which can be reduced by either reducing graupel water contents or replacing the microphysics-consistent spherical graupel particles with sector snowflakes. However, soft spheres are likely the better physical representation of graupel particles. The hypotheses that snow and graupel are overproduced in simulations using WSM6 microphysics shall be examined more systematically in future studies through additional cases and ensemble data assimilation of all-sky microwave radiance observations.

Spectral and Polarimetric Imagery Collection Experiment

DTIC Science & Technology

2011-12-01

Also melted snow liquid rate Optical rain gauge Rain rate Possibly snow rate Visibility meter Visibility Smoke, fog, haze Pyranometer Sun and sky...performance of the IR imagery due to thermal effect or possible inversion layer effects. Pyranometers measure total sun and sky radiation. If the direction

Concentrations of Reactive Trace Gases In The Interstitial Air of Surface Snow

NASA Astrophysics Data System (ADS)

Jacobi, H.-W.; Honrath, R. E.; Peterson, M. C.; Lu, Y.; Dibb, J. E.; Arsenault, M. A.; Swanson, A. L.; Blake, N. J.; Bales, R. C.; Schrems, O.

Several measurements at Arctic and Antarctic sites have demonstrated that unexpected photochemical reactions occur in irradiated surface snow influencing the composi- tion of the boundary layer over snow-covered areas. The results of these reactions are probably most obvious in the interstitial air of the surface snow since it constitutes the interface between the surface snow and the boundary layer. Therefore, measurements of concentrations of nitrogen oxide and dioxide, nitrous acid, formaldehyde, hydro- gen peroxide, formic acid, acetic acid, and other organic compounds were performed in the interstitial air of the surface snow of the Greenland ice sheet. Concentrations were measured at variable depths between - 10 cm and - 50 cm during the summer field season in 2000 at the Summit Environmental Observatory. At shallow depths, the system NO-NO2-O3 exhibits large deviations from the calculated photostationary state. Using steady-state analyses applied to OH-HO2-CH3O2 cycling indicated the presence of high concentrations of OH and peroxy radicals in the firn air. Maximum concentrations calculated for a depth of - 10 cm are in the order of 6 105 molecules cm-3 and 1.4 * 107 molecules cm-3 for OH and HO2, respectively, although radia- tion levels at - 10 cm are reduced by approximately 50 % compared to levels above the snow surface. By far the most important OH source is the photolysis of HONO while the photolysis of ozone contributes less than 2 % to the overall production of OH in the firn air.

Scattering properties of natural snow and frost - Comparison with icy satellite photometry

NASA Technical Reports Server (NTRS)

Verbiscer, Anne J.; Veverka, Joseph

1990-01-01

The Hapke (1986) equation is presently fit to ascertain the single-scattering albedo of the icy satellites of Uranus and Neptune and the one-term Henyey-Greenstein particle-phase function g for each of the Middleton and Mungall (1952) goniophotometric data samples. There emerge both very high single-scattering albedos and strongly forward-scattering particle phase functions; while these are in keeping with Mie theory-based theoretical considerations, they contrast with the observed backscattering behavior of icy satellites. It is suggested the icy satellite frost grains are aggregated into particles of complex texture, which produce the unusual backscattering behavior.

Implementation of a physically-based scheme representing light-absorbing impurities deposition, evolution and radiative impacts in the SURFEX/Crocus model

NASA Astrophysics Data System (ADS)

Tuzet, F.; Dumont, M.; Lafaysse, M.; Hagenmuller, P.; Arnaud, L.; Picard, G.; Morin, S.

2017-12-01

Light-absorbing impurities decrease snow albedo, increasing the amount of solar energy absorbed by the snowpack. Its most intuitive impact is to accelerate snow melt. However the presence of a layer highly concentrated in light-absorbing impurities in the snowpack also modify its temperature profile affecting snow metamorphism. New capabilities have been implemented in the detailed snowpack model SURFEX/ISBA-Crocus (referred to as Crocus) to account for impurities deposition and evolution within the snowpack (Tuzet et al., 2017, TCD). Once deposited, the model computes impurities mass evolution until snow melts out. Taking benefits of the recent inclusion of the spectral radiative transfer model TARTES in Crocus, the model explicitly represents the radiative impacts of light-absorbing impurities in snow. In the Pyrenees mountain range, strong sporadic Saharan dust deposition (referred to as dust outbreaks) can occur during the snow season leading some snow layers in the snowpack to contain high concentrations of mineral dust. One of the major events of the past years occurred on February 2014, affecting the whole southern Europe. During the weeks following this dust outbreak a strong avalanche activity was reported in the Aran valley (Pyrenees, Spain). For now, the link between the dust outbreak and the avalanche activity is not demonstrated.We investigate the impact of this dust outbreak on the snowpack stability in the Aran valley using the Crocus model, trying to determine whether the snowpack instability observed after the dust outbreak can be related to the presence of dust. SAFRAN-reanalysis meteorological data are used to drive the model on several altitudes, slopes and aspects. For each slope configuration two different simulations are run; one without dust and one simulating the dust outbreak of February 2014.The two corresponding simulations are then compared to assess the role of impurities on snow metamorphism and stability.On this example, we numerically prove that under specific meteorological conditions the presence of a dusty layer in the snowpack causes an enhanced temperature gradient at the interface, favoring the formation of faceted crystals.These preliminary results need to be evaluated against field measurements and with respect to uncertainties in Crocus model.

The original colours of fossil beetles

PubMed Central

McNamara, Maria E.; Briggs, Derek E. G.; Orr, Patrick J.; Noh, Heeso; Cao, Hui

2012-01-01

Structural colours, the most intense, reflective and pure colours in nature, are generated when light is scattered by complex nanostructures. Metallic structural colours are widespread among modern insects and can be preserved in their fossil counterparts, but it is unclear whether the colours have been altered during fossilization, and whether the absence of colours is always real. To resolve these issues, we investigated fossil beetles from five Cenozoic biotas. Metallic colours in these specimens are generated by an epicuticular multi-layer reflector; the fidelity of its preservation correlates with that of other key cuticular ultrastructures. Where these other ultrastructures are well preserved in non-metallic fossil specimens, we can infer that the original cuticle lacked a multi-layer reflector; its absence in the fossil is not a preservational artefact. Reconstructions of the original colours of the fossils based on the structure of the multi-layer reflector show that the preserved colours are offset systematically to longer wavelengths; this probably reflects alteration of the refractive index of the epicuticle during fossilization. These findings will allow the former presence, and original hue, of metallic structural colours to be identified in diverse fossil insects, thus providing critical evidence of the evolution of structural colour in this group. PMID:21957131

The original colours of fossil beetles.

PubMed

McNamara, Maria E; Briggs, Derek E G; Orr, Patrick J; Noh, Heeso; Cao, Hui

2012-03-22

Structural colours, the most intense, reflective and pure colours in nature, are generated when light is scattered by complex nanostructures. Metallic structural colours are widespread among modern insects and can be preserved in their fossil counterparts, but it is unclear whether the colours have been altered during fossilization, and whether the absence of colours is always real. To resolve these issues, we investigated fossil beetles from five Cenozoic biotas. Metallic colours in these specimens are generated by an epicuticular multi-layer reflector; the fidelity of its preservation correlates with that of other key cuticular ultrastructures. Where these other ultrastructures are well preserved in non-metallic fossil specimens, we can infer that the original cuticle lacked a multi-layer reflector; its absence in the fossil is not a preservational artefact. Reconstructions of the original colours of the fossils based on the structure of the multi-layer reflector show that the preserved colours are offset systematically to longer wavelengths; this probably reflects alteration of the refractive index of the epicuticle during fossilization. These findings will allow the former presence, and original hue, of metallic structural colours to be identified in diverse fossil insects, thus providing critical evidence of the evolution of structural colour in this group.

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

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.

The Potential for Snow to Supply Human Water Demand in the Present and Future

NASA Technical Reports Server (NTRS)

Mankin, Justin S.; Viviroli, Daniel; Singh, Deepti; Hoekstra, Arjen Y.; Diffenbaugh, Noah S.

2015-01-01

Runoff from snowmelt is regarded as a vital water source for people and ecosystems throughout the Northern Hemisphere (NH). Numerous studies point to the threat global warming poses to the timing and magnitude of snow accumulation and melt. But analyses focused on snow supply do not show where changes to snowmelt runoff are likely to present the most pressing adaptation challenges, given sub-annual patterns of human water consumption and water availability from rainfall. We identify the NH basins where present spring and summer snowmelt has the greatest potential to supply the human water demand that would otherwise be unmet by instantaneous rainfall runoff. Using a multi-model ensemble of climate change projections, we find that these basins - which together have a present population of approx. 2 billion people - are exposed to a 67% risk of decreased snow supply this coming century. Further, in the multi-model mean, 68 basins (with a present population of more than 300 million people) transition from having sufficient rainfall runoff to meet all present human water demand to having insufficient rainfall runoff. However, internal climate variability creates irreducible uncertainty in the projected future trends in snow resource potential, with about 90% of snow-sensitive basins showing potential for either increases or decreases over the near-term decades. Our results emphasize the importance of snow for fulfilling human water demand in many NH basins, and highlight the need to account for the full range of internal climate variability in developing robust climate risk management decisions.

An AeroCom Assessment of Black Carbon in Arctic Snow and Sea Ice

NASA Technical Reports Server (NTRS)

Jiao, C.; Flanner, M. G.; Balkanski, Y.; Bauer, S. E.; Bellouin, N.; Bernsten, T. K.; Bian, H.; Carslaw, K. S.; Chin, M.; DeLuca, N.;

Photonic Bandgaps in Photonic Molecules

NASA Technical Reports Server (NTRS)

Smith, David D.; Chang, Hongrok; Gates, Amanda L.; Fuller, Kirk A.; Gregory, Don A.; Witherow, William K.; Paley, Mark S.; Frazier, Donald O.; Curreri, Peter A. (Technical Monitor)

2002-01-01

This talk will focus on photonic bandgaps that arise due to nearly free photon and tight-binding effects in coupled microparticle and ring-resonator systems. The Mie formulation for homogeneous spheres is generalized to handle core/shell systems and multiple concentric layers in a manner that exploits an analogy with stratified planar systems, thereby allowing concentric multi-layered structures to be treated as photonic bandgap (PBG) materials. Representative results from a Mie code employing this analogy demonstrate that photonic bands arising from nearly free photon effects are easily observed in the backscattering, asymmetry parameter, and albedo for periodic quarter-wave concentric layers, though are not readily apparent in extinction spectra. Rather, the periodicity simply alters the scattering profile, enhancing the ratio of backscattering to forward scattering inside the bandgap, in direct analogy with planar quarter-wave multilayers. PBGs arising from tight-binding may also be observed when the layers (or rings) are designed such that the coupling between them is weak. We demonstrate that for a structure consisting of N coupled micro-resonators, the morphology dependent resonances split into N higher-Q modes, in direct analogy with other types of oscillators, and that this splitting ultimately results in PBGs which can lead to enhanced nonlinear optical effects.

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

PubMed

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

2017-11-07

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

On the formation of glide-snow avalanches

NASA Astrophysics Data System (ADS)

Mitterer, C.; Schweizer, J.

2012-12-01

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

Validation of Airborne FMCW Radar Measurements of Snow Thickness Over Sea Ice in Antarctica

NASA Technical Reports Server (NTRS)

Galin, Natalia; Worby, Anthony; Markus, Thorsten; Leuschen, Carl; Gogineni, Prasad

2012-01-01

Antarctic sea ice and its snow cover are integral components of the global climate system, yet many aspects of their vertical dimensions are poorly understood, making their representation in global climate models poor. Remote sensing is the key to monitoring the dynamic nature of sea ice and its snow cover. Reliable and accurate snow thickness data are currently a highly sought after data product. Remotely sensed snow thickness measurements can provide an indication of precipitation levels, predicted to increase with effects of climate change in the polar regions. Airborne techniques provide a means for regional-scale estimation of snow depth and distribution. Accurate regional-scale snow thickness data will also facilitate an increase in the accuracy of sea ice thickness retrieval from satellite altimeter freeboard estimates. The airborne data sets are easier to validate with in situ measurements and are better suited to validating satellite algorithms when compared with in situ techniques. This is primarily due to two factors: better chance of getting coincident in situ and airborne data sets and the tractability of comparison between an in situ data set and the airborne data set averaged over the footprint of the antennas. A 28-GHz frequency modulated continuous wave (FMCW) radar loaned by the Center for Remote Sensing of Ice Sheets to the Australian Antarctic Division is used to measure snow thickness over sea ice in East Antarctica. Provided with the radar design parameters, the expected performance parameters of the radar are summarized. The necessary conditions for unambiguous identification of the airsnow and snowice layers for the radar are presented. Roughnesses of the snow and ice surfaces are found to be dominant determinants in the effectiveness of layer identification for this radar. Finally, this paper presents the first in situ validated snow thickness estimates over sea ice in Antarctica derived from an FMCW radar on a helicopterborne platform.

Snowcover influence on backscattering from terrain

NASA Technical Reports Server (NTRS)

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

1984-01-01

The effects of snowcover on the microwave backscattering from terrain in the 8-35 GHz region are examined through the analysis of experimental data and by application of a semiempirical model. The model accounts for surface backscattering contributions by the snow-air and snow-soil interfaces, and for volume backscattering contributions by the snow layer. Through comparisons of backscattering data for different terrain surfaces measured both with and without snowcover, the masking effects of snow are evaluated as a function of snow water equivalent and liquid water content. The results indicate that with dry snowcover it is not possible to discriminate between different types of ground surface (concrete, asphalt, grass, and bare ground) if the snow water equivalent is greater than about 20 cm (or a depth greater than 60 cm for a snow density of 0.3 g/cu cm). For the same density, however, if the snow is wet, a depth of 10 cm is sufficient to mask the underlying surface.

Coupling the snow thermodynamic model SNOWPACK with the microwave emission model of layered snowpacks for subarctic and arctic snow water equivalent retrievals

NASA Astrophysics Data System (ADS)

Langlois, A.; Royer, A.; Derksen, C.; Montpetit, B.; Dupont, F.; GoïTa, K.

2012-12-01

Satellite-passive microwave remote sensing has been extensively used to estimate snow water equivalent (SWE) in northern regions. Although passive microwave sensors operate independent of solar illumination and the lower frequencies are independent of atmospheric conditions, the coarse spatial resolution introduces uncertainties to SWE retrievals due to the surface heterogeneity within individual pixels. In this article, we investigate the coupling of a thermodynamic multilayered snow model with a passive microwave emission model. Results show that the snow model itself provides poor SWE simulations when compared to field measurements from two major field campaigns. Coupling the snow and microwave emission models with successive iterations to correct the influence of snow grain size and density significantly improves SWE simulations. This method was further validated using an additional independent data set, which also showed significant improvement using the two-step iteration method compared to standalone simulations with the snow model.

An analytical approach for the Propagation Saw Test

NASA Astrophysics Data System (ADS)

Benedetti, Lorenzo; Fischer, Jan-Thomas; Gaume, Johan

2016-04-01

The Propagation Saw Test (PST) [1, 2] is an experimental in-situ technique that has been introduced to assess crack propagation propensity in weak snowpack layers buried below cohesive snow slabs. This test attracted the interest of a large number of practitioners, being relatively easy to perform and providing useful insights for the evaluation of snow instability. The PST procedure requires isolating a snow column of 30 centimeters of width and -at least-1 meter in the downslope direction. Then, once the stratigraphy is known (e.g. from a manual snow profile), a saw is used to cut a weak layer which could fail, potentially leading to the release of a slab avalanche. If the length of the saw cut reaches the so-called critical crack length, the onset of crack propagation occurs. Furthermore, depending on snow properties, the crack in the weak layer can initiate the fracture and detachment of the overlying slab. Statistical studies over a large set of field data confirmed the relevance of the PST, highlighting the positive correlation between test results and the likelihood of avalanche release [3]. Recent works provided key information on the conditions for the onset of crack propagation [4] and on the evolution of slab displacement during the test [5]. In addition, experimental studies [6] and simplified models [7] focused on the qualitative description of snowpack properties leading to different failure types, namely full propagation or fracture arrest (with or without slab fracture). However, beside current numerical studies utilizing discrete elements methods [8], only little attention has been devoted to a detailed analytical description of the PST able to give a comprehensive mechanical framework of the sequence of processes involved in the test. Consequently, this work aims to give a quantitative tool for an exhaustive interpretation of the PST, stressing the attention on important parameters that influence the test outcomes. First, starting from a pure mechanical point of view, a broad phenomenology of the main failure types of the PST is outlined. Then, the Euler-Bernoulli beam theory is applied to the test setup, allowing an easy description of the snowpack stress state in the quasi-static regime. We assume an elastic-perfectly brittle model as constitutive law for the snow slab. Besides, considering the weak layer as a rigid bed of crystals with an a priori inclination, a local instability problem is formulated in order to take into account the combined effect of compressive and shear loading. As a result, the onset of slab and weak layer fracture is described in terms of cut length, slab dimensions and the main mechanical parameters. A condition on the possible propagation of the crack is proposed as well. References [1] C. Sigrist and J. Schweizer, "Critical energy release rates of weak snowpack layers determined in field experiments", Geophysical Research Letters, Volume 34, L03502, 2007. [2] D. Gauthier and B. Jamieson, "Evaluation of a prototype field test for fracture and failure propagation propensity in weak snowpack layers". Cold Regions Science and Technology, Volume 51, Issue 2, Pages 87-97, 2008. [3] R. Simenhois and K.W. Birkeland. "The extended column test: Test effectiveness, spatial variability, and comparison with the propagation saw test." Cold Regions Science and Technology, Volume 59, Issue 23, Pages 210-216, 2009. [4] J. Heierli, P. Gumbsch, M. Zaiser, "Anticrack Nucleation as Triggering Mecchanism for Snow Slab Avalanches", Science, Volume 321, Pages 240-243, 2008. [5] A. van Herwijnen, J. Schweizer, J. Heierli, "Measurement of the deformation field associated with fracture propagation in weak snowpack layers", Journal of Geophysical Research, Volume 115, F03042, 2010. [6] K. W. Birkeland, A. van Herwijnen, E. Knoff, M. Staples, E. Bair, R. Simenhois, "The role of slabs and weak layers in fracture arrest", Proceedings of the International Snow Science Workshop, Banff, 2014. [7] J. Schweizer, B. Reuter, A. van Herwijnen, B. Jamieson, "On how the tensile strength of the slab affects crack propagation propensity", Proceedings of the International Snow Science Workshop, Banff, 2014. [8] J. Gaume, A. van Herwijnen, G. Chambon, K. W. Birkeland, J. Schweizer. "Modeling of crack propagation in weak snowpack layers using the discrete element method", The Cryosphere, Volume 9, Pages 1915-1932, 2015.

Should Promotion to Captain within the United States Army Become Decentralized?

DTIC Science & Technology

1983-06-01

dimen- corder obtained during the SNOW-ONE-B sion) plot in Fig. 1. The time-consuming field experiment are presented. Some labor required for the...into two separate ’.As a means of reducing the scatter, sets; the first spanning 1610 to 2010 _ we applied a five-point-running mean to ESTr and the...the consistancies of the Fv - I relation- ships throughout the period. Because of Because of the time-consuming labor the lesser amount of snow

Magneto-Optic Materials for Biasing Ring Laser Gyros. Report Number 3. (Computer Model for Evaluating Scattering from Multi-Layer Dielectric Thin Film Structures Containing a Magnetic Layer.

DTIC Science & Technology

1980-09-30

16. "Substituted Rare Earth Garnet Substrate Crystals and LPE Films for Magneto-optic Applications," M. Kestigian, W.R. Bekebrede and A.B. Smith, J...transparent garnet magnetic films have been discussed by workers at Sperry [4,5]. The above considerations indicate that it is highly desirable to have...metallic magnetic film , such as a garnet , on top of an MLD stack. C. A partially transparent (very thin) magnetic metal film on top of an MLD stack. We

Mapping snow depth in complex alpine terrain with close range aerial imagery - estimating the spatial uncertainties of repeat autonomous aerial surveys over an active rock glacier

NASA Astrophysics Data System (ADS)

Goetz, Jason; Marcer, Marco; Bodin, Xavier; Brenning, Alexander

2017-04-01

Snow depth mapping in open areas using close range aerial imagery is just one of the many cases where developments in structure-from-motion and multi-view-stereo (SfM-MVS) 3D reconstruction techniques have been applied for geosciences - and with good reason. Our ability to increase the spatial resolution and frequency of observations may allow us to improve our understanding of how snow depth distribution varies through space and time. However, to ensure accurate snow depth observations from close range sensing we must adequately characterize the uncertainty related to our measurement techniques. In this study, we explore the spatial uncertainties of snow elevation models for estimation of snow depth in a complex alpine terrain from close range aerial imagery. We accomplish this by conducting repeat autonomous aerial surveys over a snow-covered active-rock glacier located in the French Alps. The imagery obtained from each flight of an unmanned aerial vehicle (UAV) is used to create an individual digital elevation model (DEM) of the snow surface. As result, we obtain multiple DEMs of the snow surface for the same site. These DEMs are obtained from processing the imagery with the photogrammetry software Agisoft Photoscan. The elevation models are also georeferenced within Photoscan using the geotagged imagery from an onboard GNSS in combination with ground targets placed around the rock glacier, which have been surveyed with highly accurate RTK-GNSS equipment. The random error associated with multi-temporal DEMs of the snow surface is estimated from the repeat aerial survey data. The multiple flights are designed to follow the same flight path and altitude above the ground to simulate the optimal conditions of repeat survey of the site, and thus try to estimate the maximum precision associated with our snow-elevation measurement technique. The bias of the DEMs is assessed with RTK-GNSS survey observations of the snow surface elevation of the area on and surrounding the rock glacier. Additionally, one of the challenges with processing snow cover imagery with SfM-MVS is dealing with the general homogeneity of the surface, which makes is difficult for automated-feature detection algorithms to identify key features for point matching. This challenge depends on the snow cover surface conditions, such as scale, lighting conditions (high vs. low contrast), and availability of snow-free features within a scene, among others. We attempt to explore this aspect by spatial modelling the factors influencing the precision and bias of the DEMs from image, flight, and terrain attributes.

Greenland annual accumulation along the EGIG line, 1959-2004, from ASIRAS airborne radar and neutron-probe density measurements

NASA Astrophysics Data System (ADS)

Overly, Thomas B.; Hawley, Robert L.; Helm, Veit; Morris, Elizabeth M.; Chaudhary, Rohan N.

2016-08-01

We report annual snow accumulation rates from 1959 to 2004 along a 250 km segment of the Expéditions Glaciologiques Internationales au Groenland (EGIG) line across central Greenland using Airborne SAR/Interferometric Radar Altimeter System (ASIRAS) radar layers and high resolution neutron-probe (NP) density profiles. ASIRAS-NP-derived accumulation rates are not statistically different (95 % confidence interval) from in situ EGIG accumulation measurements from 1985 to 2004. ASIRAS-NP-derived accumulation increases by 20 % below 3000 m elevation, and increases by 13 % above 3000 m elevation for the period 1995 to 2004 compared to 1985 to 1994. Three Regional Climate Models (PolarMM5, RACMO2.3, MAR) underestimate snow accumulation below 3000 m by 16-20 % compared to ASIRAS-NP from 1985 to 2004. We test radar-derived accumulation rates sensitivity to density using modeled density profiles in place of NP densities. ASIRAS radar layers combined with Herron and Langway (1980) model density profiles (ASIRAS-HL) produce accumulation rates within 3.5 % of ASIRAS-NP estimates in the dry snow region. We suggest using Herron and Langway (1980) density profiles to calibrate radar layers detected in dry snow regions of ice sheets lacking detailed in situ density measurements, such as those observed by the Operation IceBridge campaign.

MODIS-based Snow Cover Variability of the Upper River Grande Basin

NASA Astrophysics Data System (ADS)

Yu, B.; Wang, X.; Xie, H.

2007-12-01

Snow cover and its spring melting in the Upper Rio Grande Basin provides a major water source for the Upper to Middle Rio Grande valley and Elephant Butte Reservoir. Thus understanding the snowpack and its variability in the context of global climate change is crucial to the sustainable water resources for the region. MODIS instruments (on Terra and Aqua) have provided time series of snow cover products since 2000, but suffering with cloud contaminations. In this study, we evaluated four newly developed cloudless snow cover products (less than 10%) and four standard products: daily (MOD10A1, MYD10A1) and 8-day (MOD10A2, MYD10A2), in comparison with in situ Snowpack Telemetry (SNOTEL) measurements for the hydrological year 2003-2004. The four new products are daily composite of Terra and Aqua (MODMYD10DC), multi-day composites of Terra (MOD10MC), Aqua (MYD10MC), and Terra and Aqua (MODMYD10MC). The standard daily and 8-day products can classify land correctly, but had fairly low accuracy in snow classification due to cloud contamination (a average of 39.4% for Terra and 45% for Aqua in the year 2003-2004). All the new multi-day composite products tended to have high accuracy in classifying both snow and land (over 90%), as the cloud cover has been reduced to less than 10% (~5% for the year) under the new algorithm . This result is consistent with a previous study in the Xinjiang area, China (Wang and Xie, 2007). Therefore, MOD10MC (before the Aqua data available) and MODMYD10MC products are used to get the mean snow cover of the Upper Rio Grande Basin from 2000 to 2007. The snow depletion curve derived from the new cloud-free snow cover map will be used to examine its effect on stream discharge.

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

NASA Astrophysics Data System (ADS)

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

1999-09-01

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

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.

A new test apparatus for studying the failure process during loading experiments of snow

NASA Astrophysics Data System (ADS)

Capelli, Achille; Reiweger, Ingrid; Schweizer, Jürg

2016-04-01

We developed a new apparatus for fully load-controlled snow failure experiments. The deformation and applied load are measured with two displacement and two force sensors, respectively. The loading experiments are recorded with a high speed camera, and the local strain is derived by a particle image velocimetry (PIV) algorithm. To monitor the progressive failure process within the snow sample, our apparatus includes six piezoelectric transducers that record the acoustic emissions in the ultrasonic range. The six sensors allow localizing the sources of the acoustic emissions, i.e. where the failure process starts and how it develops with time towards catastrophic failure. The quadratic snow samples have a side length of 50 cm and a height of 10 to 20 cm. With an area of 0.25 m2 they are clearly larger than samples used in previous experiments. The size of the samples, which is comparable to the critical size for the onset of crack propagation leading to dry-snow slab avalanche release, allows studying the failure nucleation process and its relation to the spatial distribution of the recorded acoustic emissions. Furthermore the occurrence of features in the acoustic emissions typical for imminent failure of the samples can be analysed. We present preliminary results of the acoustic emissions recorded during tests with homogeneous as well as layered snow samples, including a weak layer, for varying loading rates and loading angles.

Possible Quorum Sensing in Marine Snow Bacteria: Production of Acylated Homoserine Lactones by Roseobacter Strains Isolated from Marine Snow

PubMed Central

Gram, Lone; Grossart, Hans-Peter; Schlingloff, Andrea; Kiørboe, Thomas

2002-01-01

We report here, for the first time, that bacteria associated with marine snow produce communication signals involved in quorum sensing in gram-negative bacteria. Four of 43 marine microorganisms isolated from marine snow were found to produce acylated homoserine lactones (AHLs) in well diffusion and thin-layer chromatographic assays based on the Agrobacterium tumefaciens reporter system. Three of the AHL-producing strains were identified by 16S ribosomal DNA gene sequence analysis as Roseobacter spp., and this is the first report of AHL production by these α-Proteobacteria. It is likely that AHLs in Roseobacter species and other marine snow bacteria govern phenotypic traits (biofilm formation, exoenzyme production, and antibiotic production) which are required mainly when the population reaches high densities, e.g., in the marine snow community. PMID:12147515

Limitations of using a thermal imager for snow pit temperatures

NASA Astrophysics Data System (ADS)

Schirmer, M.; Jamieson, B.

2013-10-01

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

Nanotextured thin films for detection of chemicals by surface enhanced Raman scattering

NASA Astrophysics Data System (ADS)

Korivi, Naga; Jiang, Li; Ahmed, Syed; Nujhat, Nabila; Idrees, Mohanad; Rangari, Vijaya

2017-11-01

We report on the development of large area, nanostructured films that function as substrates for surface enhanced Raman scattering (SERS) detection of chemicals. The films are made of polyethylene terephthalate layers partially embedded with multi-walled carbon nanotubes and coated with a thin layer of gold. The films are fabricated by a facile method involving spin-coating, acid dip, and magnetron sputtering. The films perform effectively as SERS substrates when used in the detection of dye pollutants such as Congo red dye, with an enhancement factor of 1.1  ×  106 and a detection limit of 10-7 M which is the lowest reported for CR detection by freestanding SERS film substrates. The films have a long shelf life, and cost US0.20 per cm2 of active area, far less than commercially available SERS substrates. This is the first such work on the use of a polymer layer modified with carbon nanotubes to create a nano-scale texture and arbitrary ‘hot-spots’, contributing to the SERS effect.

Facilitating the exploitation of ERTS-1 imagery utilizing snow enhancement techniques

NASA Technical Reports Server (NTRS)

Wobber, F. J. (Principal Investigator); Martin, K. R.; Amato, R. V.

1973-01-01

The author has identified the following significant results. Snow cover in combination with low angle solar illumination has been found to provide increased tonal contrast of surface feature and is useful in the detection of bedrock fractures. Identical fracture systems were not as readily detectable in the fall due to the lack of a contrasting surface medium (snow) and a relatively high sun angle. Low angle solar illumination emphasizes topographic expressions not as apparent on imagery acquired with a higher sun angle. A strong correlation exists between the major fracture-lineament directions interpreted from multi-sensor imagery (including snow-free and snow cover ERTS) and the strike of bedrock joints recorded in the field indicating the structural origin of interpreted fracture-lineaments. A fracture-annotated ERTS-1 photo base map (1:250,000 scale) is being prepared for western Massachusetts. The map will document the utilization of ERTS-1 imagery for geological analysis in comparative snow-free and snow-covered terrain.

A vertically integrated snow/ice model over land/sea for climate models. I - Development. II - Impact on orbital change experiments

NASA Technical Reports Server (NTRS)

Neeman, Binyamin U.; Ohring, George; Joseph, Joachim H.

1988-01-01

A vertically integrated formulation (VIF) model for sea ice/snow and land snow is discussed which can simulate the nonlinear effects of heat storage and transfer through the layers of snow and ice. The VIF demonstates the accuracy of the multilayer formulation, while benefitting from the computational flexibility of linear formulations. In the second part, the model is implemented in a seasonal dynamic zonally averaged climate model. It is found that, in response to a change between extreme high and low summer insolation orbits, the winter orbital change dominates over the opposite summer change for sea ice. For snow over land the shorter but more pronounced summer orbital change is shown to dominate.

Developing an A Priori Database for Passive Microwave Snow Water Retrievals Over Ocean

NASA Astrophysics Data System (ADS)

Yin, Mengtao; Liu, Guosheng

2017-12-01

A physically optimized a priori database is developed for Global Precipitation Measurement Microwave Imager (GMI) snow water retrievals over ocean. The initial snow water content profiles are derived from CloudSat Cloud Profiling Radar (CPR) measurements. A radiative transfer model in which the single-scattering properties of nonspherical snowflakes are based on the discrete dipole approximate results is employed to simulate brightness temperatures and their gradients. Snow water content profiles are then optimized through a one-dimensional variational (1D-Var) method. The standard deviations of the difference between observed and simulated brightness temperatures are in a similar magnitude to the observation errors defined for observation error covariance matrix after the 1D-Var optimization, indicating that this variational method is successful. This optimized database is applied in a Bayesian retrieval snow water algorithm. The retrieval results indicated that the 1D-Var approach has a positive impact on the GMI retrieved snow water content profiles by improving the physical consistency between snow water content profiles and observed brightness temperatures. Global distribution of snow water contents retrieved from the a priori database is compared with CloudSat CPR estimates. Results showed that the two estimates have a similar pattern of global distribution, and the difference of their global means is small. In addition, we investigate the impact of using physical parameters to subset the database on snow water retrievals. It is shown that using total precipitable water to subset the database with 1D-Var optimization is beneficial for snow water retrievals.

Experimental and computational studies of electromagnetic cloaking at microwaves

NASA Astrophysics Data System (ADS)

Wang, Xiaohui

An invisibility cloak is a device that can hide the target by enclosing it from the incident radiation. This intriguing device has attracted a lot of attention since it was first implemented at a microwave frequency in 2006. However, the problems of existing cloak designs prevent them from being widely applied in practice. In this dissertation, we try to remove or alleviate the three constraints for practical applications imposed by loosy cloaking media, high implementation complexity, and small size of hidden objects compared to the incident wavelength. To facilitate cloaking design and experimental characterization, several devices and relevant techniques for measuring the complex permittivity of dielectric materials at microwave frequencies are developed. In particular, a unique parallel plate waveguide chamber has been set up to automatically map the electromagnetic (EM) field distribution for wave propagation through the resonator arrays and cloaking structures. The total scattering cross section of the cloaking structures was derived based on the measured scattering field by using this apparatus. To overcome the adverse effects of lossy cloaking media, microwave cloaks composed of identical dielectric resonators made of low loss ceramic materials are designed and implemented. The effective permeability dispersion was provided by tailoring dielectric resonator filling fractions. The cloak performances had been verified by full-wave simulation of true multi-resonator structures and experimental measurements of the fabricated prototypes. With the aim to reduce the implementation complexity caused by metamaterials employment for cloaking, we proposed to design 2-D cylindrical cloaks and 3-D spherical cloaks by using multi-layer ordinary dielectric material (epsilon r>1) coating. Genetic algorithm was employed to optimize the dielectric profiles of the cloaking shells to provide the minimum scattering cross sections of the cloaked targets. The designed cloaks can be easily scaled to various operating frequencies. The simulation results show that the multi-layer cylindrical cloak essentially outperforms the similarly sized metamaterials-based cloak designed by using the transformation optics-based reduced parameters. For the designed spherical cloak, the simulated scattering pattern shows that the total scattering cross section is greatly reduced. In addition, the scattering in specific directions could be significantly reduced. It is shown that the cloaking efficiency for larger targets could be improved by employing lossy materials in the shell. At last, we propose to hide a target inside a waveguide structure filled with only epsilon near zero materials, which are easy to implement in practice. The cloaking efficiency of this method, which was found to increase for large targets, has been confirmed both theoretically and by simulations.

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.

Role of nitrite in the photochemical formation of radicals in the snow.

PubMed

Jacobi, Hans-Werner; Kleffmann, Jörg; Villena, Guillermo; Wiesen, Peter; King, Martin; France, James; Anastasio, Cort; Staebler, Ralf

2014-01-01

Photochemical reactions in snow can have an important impact on the composition of the atmosphere over snow-covered areas as well as on the composition of the snow itself. One of the major photochemical processes is the photolysis of nitrate leading to the formation of volatile nitrogen compounds. We report nitrite concentrations determined together with nitrate and hydrogen peroxide in surface snow collected at the coastal site of Barrow, Alaska. The results demonstrate that nitrite likely plays a significant role as a precursor for reactive hydroxyl radicals as well as volatile nitrogen oxides in the snow. Pollution events leading to high concentrations of nitrous acid in the atmosphere contributed to an observed increase in nitrite in the surface snow layer during nighttime. Observed daytime nitrite concentrations are much higher than values predicted from steady-state concentrations based on photolysis of nitrate and nitrite indicating that we do not fully understand the production of nitrite and nitrous acid in snow. The discrepancy between observed and expected nitrite concentrations is probably due to a combination of factors, including an incomplete understanding of the reactive environment and chemical processes in snow, and a lack of consideration of the vertical structure of snow.

Multi-Scale Scattering Transform in Music Similarity Measuring

NASA Astrophysics Data System (ADS)

Wang, Ruobai

Scattering transform is a Mel-frequency spectrum based, time-deformation stable method, which can be used in evaluating music similarity. Compared with Dynamic time warping, it has better performance in detecting similar audio signals under local time-frequency deformation. Multi-scale scattering means to combine scattering transforms of different window lengths. This paper argues that, multi-scale scattering transform is a good alternative of dynamic time warping in music similarity measuring. We tested the performance of multi-scale scattering transform against other popular methods, with data designed to represent different conditions.

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

USGS Publications Warehouse

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

2004-01-01

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

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

NASA Technical Reports Server (NTRS)

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

2010-01-01

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

Snowfall Rate Retrieval using NPP ATMS Passive Microwave Measurements

NASA Technical Reports Server (NTRS)

Meng, Huan; Ferraro, Ralph; Kongoli, Cezar; Wang, Nai-Yu; Dong, Jun; Zavodsky, Bradley; Yan, Banghua; Zhao, Limin

2014-01-01

Passive microwave measurements at certain high frequencies are sensitive to the scattering effect of snow particles and can be utilized to retrieve snowfall properties. Some of the microwave sensors with snowfall sensitive channels are Advanced Microwave Sounding Unit (AMSU), Microwave Humidity Sounder (MHS) and Advance Technology Microwave Sounder (ATMS). ATMS is the follow-on sensor to AMSU and MHS. Currently, an AMSU and MHS based land snowfall rate (SFR) product is running operationally at NOAA/NESDIS. Based on the AMSU/MHS SFR, an ATMS SFR algorithm has been developed recently. The algorithm performs retrieval in three steps: snowfall detection, retrieval of cloud properties, and estimation of snow particle terminal velocity and snowfall rate. The snowfall detection component utilizes principal component analysis and a logistic regression model. The model employs a combination of temperature and water vapor sounding channels to detect the scattering signal from falling snow and derive the probability of snowfall (Kongoli et al., 2014). In addition, a set of NWP model based filters is also employed to improve the accuracy of snowfall detection. Cloud properties are retrieved using an inversion method with an iteration algorithm and a two-stream radiative transfer model (Yan et al., 2008). A method developed by Heymsfield and Westbrook (2010) is adopted to calculate snow particle terminal velocity. Finally, snowfall rate is computed by numerically solving a complex integral. The ATMS SFR product is validated against radar and gauge snowfall data and shows that the ATMS algorithm outperforms the AMSU/MHS SFR.

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

NASA Technical Reports Server (NTRS)

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

1994-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2007-12-01

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

Detection of Rain-on-Snow (ROS) Events Using the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) and Weather Station Observations

NASA Astrophysics Data System (ADS)

Ryan, E. M.; Brucker, L.; Forman, B. A.

2015-12-01

During the winter months, the occurrence of rain-on-snow (ROS) events can impact snow stratigraphy via generation of large scale ice crusts, e.g., on or within the snowpack. The formation of such layers significantly alters the electromagnetic response of the snowpack, which can be witnessed using space-based microwave radiometers. In addition, ROS layers can hinder the ability of wildlife to burrow in the snow for vegetation, which limits their foraging capability. A prime example occurred on 23 October 2003 in Banks Island, Canada, where an ROS event is believed to have caused the deaths of over 20,000 musk oxen. Through the use of passive microwave remote sensing, ROS events can be detected by utilizing observed brightness temperatures (Tb) from AMSR-E. Tb observed at different microwave frequencies and polarizations depends on snow properties. A wet snowpack formed from an ROS event yields a larger Tb than a typical dry snowpack would. This phenomenon makes observed Tb useful when detecting ROS events. With the use of data retrieved from AMSR-E, in conjunction with observations from ground-based weather station networks, a database of estimated ROS events over the past twelve years was generated. Using this database, changes in measured Tb following the ROS events was also observed. This study adds to the growing knowledge of ROS events and has the potential to help inform passive microwave snow water equivalent (SWE) retrievals or snow cover properties in polar regions.

MODIS Snow and Ice Products from the NSIDC DAAC

NASA Technical Reports Server (NTRS)

Scharfen, Greg R.; Hall, Dorothy K.; Riggs, George A.

1997-01-01

The National Snow and Ice Data Center (NSIDC) Distributed Active Archive Center (DAAC) provides data and information on snow and ice processes, especially pertaining to interactions among snow, ice, atmosphere and ocean, in support of research on global change detection and model validation, and provides general data and information services to cryospheric and polar processes research community. The NSIDC DAAC is an integral part of the multi-agency-funded support for snow and ice data management services at NSIDC. The Moderate Resolution Imaging Spectroradiometer (MODIS) will be flown on the first Earth Observation System (EOS) platform (AM-1) in 1998. The MODIS Instrument Science Team is developing geophysical products from data collected by the MODIS instrument, including snow and ice products which will be archived and distributed by NSIDC DAAC. The MODIS snow and ice mapping algorithms will generate global snow, lake ice, and sea ice cover products on a daily basis. These products will augment the existing record of satellite-derived snow cover and sea ice products that began about 30 years ago. The characteristics of these products, their utility, and comparisons to other data set are discussed. Current developments and issues are summarized.

Investigations into the climate of the South Pole

NASA Astrophysics Data System (ADS)

Town, Michael S.

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

Extensive Liquid Meltwater Storage in Firn Within the Greenland Ice Sheet

NASA Technical Reports Server (NTRS)

Forster, Richard R.; Box, Jason E.; vandenBroeke, Michael R.; Miege, Clement; Burgess, Evan W.; vanAngelen, Jan H.; Lenaerts, Jan T. M.; Koenig, Lora S.; Paden, John; Lewis, Cameron;

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.

Saskatchewan and Manitoba

NASA Technical Reports Server (NTRS)

2001-01-01

Surface brightness contrasts accentuated by a thin layer of snow enable a network of rivers, roads, and farmland boundaries to stand out clearly in these MISR images of southeastern Saskatchewan and southwestern Manitoba. The lefthand image is a multi-spectral false-color view made from the near-infrared, red, and green bands of MISR's vertical-viewing (nadir) camera. The righthand image is a multi-angle false-color view made from the red band data of the 60-degree aftward camera, the nadir camera, and the 60-degree forward camera. In each image, the selected channels are displayed as red, green, and blue, respectively. The data were acquired April 17, 2001 during Terra orbit 7083, and cover an area measuring about 285 kilometers x 400 kilometers. North is at the top.

The junction of the Assiniboine and Qu'Apelle Rivers in the bottom part of the images is just east of the Saskatchewan-Manitoba border. During the growing season, the rich, fertile soils in this area support numerous fields of wheat, canola, barley, flaxseed, and rye. Beef cattle are raised in fenced pastures. To the north, the terrain becomes more rocky and forested. Many frozen lakes are visible as white patches in the top right. The narrow linear, north-south trending patterns about a third of the way down from the upper right corner are snow-filled depressions alternating with vegetated ridges, most probably carved by glacial flow.

In the lefthand image, vegetation appears in shades of red, owing to its high near-infrared reflectivity. In the righthand image, several forested regions are clearly visible in green hues. Since this is a multi-angle composite, the green arises not from the color of the leaves but from the architecture of the surface cover. Progressing southeastward along the Manitoba Escarpment, the forested areas include the Pasquia Hills, the Porcupine Hills, Duck Mountain Provincial Park, and Riding Mountain National Park. The forests are brighter in the nadir than at the oblique angles, probably because more of the snow-covered surface is visible in the gaps between the trees. In contrast, the valley between the Pasquia and Porcupine Hills near the top of the images appears bright red in the lefthand image (indicating high vegetation abundance) but shows a mauve color in the multi-angle view. This means that it is darker in the nadir than at the oblique angles. Examination of imagery acquired after the snow has melted should establish whether this difference is related to the amount of snow on the surface or is indicative of a different type of vegetation structure.

Saskatchewan and Manitoba are believed to derive their names from the Cree words for the winding and swift-flowing waters of the Saskatchewan River and for a narrows on Lake Manitoba where the roaring sound of wind and water evoked the voice of the Great Spirit. They are two of Canada's Prairie Provinces; Alberta is the third.

MISR was built and is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Office of Earth Science, Washington, DC. The Terra satellite is managed by NASA's Goddard Space Flight Center, Greenbelt, MD. JPL is a division of the California Institute of Technology.

Design and fabrication of a multi-layered solid dynamic phantom: validation platform on methods for reducing scalp-hemodynamic effect from fNIRS signal

NASA Astrophysics Data System (ADS)

Kawaguchi, Hiroshi; Tanikawa, Yukari; Yamada, Toru

2017-02-01

Scalp hemodynamics contaminates the signals from functional near-infrared spectroscopy (fNIRS). Numerous methods have been proposed to reduce this contamination, but no golden standard has yet been established. Here we constructed a multi-layered solid phantom to experimentally validate such methods. This phantom comprises four layers corresponding to epidermides, dermis/skull (upper dynamic layer), cerebrospinal fluid and brain (lower dynamic layer) and the thicknesses of these layers were 0.3, 10, 1, and 50 mm, respectively. The epidermides and cerebrospinal fluid layers were made of polystyrene and an acrylic board, respectively. Both of these dynamic layers were made of epoxy resin. An infrared dye and titanium dioxide were mixed to match their absorption and reduced scattering coefficients (μa and μs', respectively) with those of biological tissues. The bases of both upper and lower dynamic layers have a slot for laterally sliding a bar that holds an absorber piece. This bar was laterally moved using a programmable stepping motor. The optical properties of dynamic layers were estimated based on the transmittance and reflectance using the Monte Carlo look-up table method. The estimated coefficients for lower and upper dynamic layers approximately coincided with those for biological tissues. We confirmed that the preliminary fNIRS measurement using the fabricated phantom showed that the signals from the brain layer were recovered if those from the dermis layer were completely removed from their mixture, indicating that the phantom is useful for evaluating methods for reducing the contamination of the signals from the scalp.

Long-range-transported bioaerosols captured in snow cover on Mount Tateyama, Japan: impacts of Asian-dust events on airborne bacterial dynamics relating to ice-nucleation activities

NASA Astrophysics Data System (ADS)

Maki, Teruya; Furumoto, Shogo; Asahi, Yuya; Lee, Kevin C.; Watanabe, Koichi; Aoki, Kazuma; Murakami, Masataka; Tajiri, Takuya; Hasegawa, Hiroshi; Mashio, Asami; Iwasaka, Yasunobu

2018-06-01

The westerly wind travelling at high altitudes over eastern Asia transports aerosols from the Asian deserts and urban areas to downwind areas such as Japan. These long-range-transported aerosols include not only mineral particles but also microbial particles (bioaerosols), that impact the ice-cloud formation processes as ice nuclei. However, the detailed relations of airborne bacterial dynamics to ice nucleation in high-elevation aerosols have not been investigated. Here, we used the aerosol particles captured in the snow cover at altitudes of 2450 m on Mt Tateyama to investigate sequential changes in the ice-nucleation activities and bacterial communities in aerosols and elucidate the relationships between the two processes. After stratification of the snow layers formed on the walls of a snow pit on Mt Tateyama, snow samples, including aerosol particles, were collected from 70 layers at the lower (winter accumulation) and upper (spring accumulation) parts of the snow wall. The aerosols recorded in the lower parts mainly came from Siberia (Russia), northern Asia and the Sea of Japan, whereas those in the upper parts showed an increase in Asian dust particles originating from the desert regions and industrial coasts of Asia. The snow samples exhibited high levels of ice nucleation corresponding to the increase in Asian dust particles. Amplicon sequencing analysis using 16S rRNA genes revealed that the bacterial communities in the snow samples predominately included plant associated and marine bacteria (phyla Proteobacteria) during winter, whereas during spring, when dust events arrived frequently, the majority were terrestrial bacteria of phyla Actinobacteria and Firmicutes. The relative abundances of Firmicutes (Bacilli) showed a significant positive relationship with the ice nucleation in snow samples. Presumably, Asian dust events change the airborne bacterial communities over Mt Tateyama and carry terrestrial bacterial populations, which possibly induce ice-nucleation activities, thereby indirectly impacting climate change.

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

NASA Astrophysics Data System (ADS)

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

2018-06-01

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

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

NASA Astrophysics Data System (ADS)

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

2012-06-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Photopolarimetric Retrievals of Snow Properties

NASA Technical Reports Server (NTRS)

Ottaviani, M.; van Diedenhoven, B.; Cairns, B.

2015-01-01

Polarimetric observations of snow surfaces, obtained in the 410-2264 nm range with the Research Scanning Polarimeter onboard the NASA ER-2 high-altitude aircraft, are analyzed and presented. These novel measurements are of interest to the remote sensing community because the overwhelming brightness of snow plagues aerosol and cloud retrievals based on airborne and spaceborne total reflection measurements. The spectral signatures of the polarized reflectance of snow are therefore worthwhile investigating in order to provide guidance for the adaptation of algorithms currently employed for the retrieval of aerosol properties over soil and vegetated surfaces. At the same time, the increased information content of polarimetric measurements allows for a meaningful characterization of the snow medium. In our case, the grains are modeled as hexagonal prisms of variable aspect ratios and microscale roughness, yielding retrievals of the grains' scattering asymmetry parameter, shape and size. The results agree with our previous findings based on a more limited data set, with the majority of retrievals leading to moderately rough crystals of extreme aspect ratios, for each scene corresponding to a single value of the asymmetry parameter.

Snow measurement Using P-Band Signals of Opportunity Reflectometry

NASA Astrophysics Data System (ADS)

Shah, R.; Yueh, S. H.; Xu, X.; Elder, K.

2017-12-01

Snow water storage in land is a critical parameter of the water cycle. In this study, we develop methods for estimating reflectance from bistatic scattering of digital communication Signals of Opportunity (SoOp) across the available microwave spectrum from VHF to Ka band and show results from proof-of-concept experiments at the Fraser Experimental Forest, Colorado to acquire measurements to relate the SoOp phase and reflectivity to a snow-covered soil surface. The forward modeling of this scenario will be presented and multiple sensitivities were conducted. Available SoOp receiver data along with a network of in situ sensor measurements collected since January 2016 will be used to validate theoretical modeling results. In the winter season of 2016 and 2017, we conducted a field experiment using VHF/UHF-band illuminating sources to detect SWE and surface reflectivity. The amplitude of the reflectivity showed sensitivity to the wetness of snow pack and ground reflectivity while the phase showed sensitivity to SWE. This use of this concept can be helpful to measure the snow water storage in land globally.

Numerical simulation of microstructural damage and tensile strength of snow

NASA Astrophysics Data System (ADS)

Hagenmuller, Pascal; Theile, Thiemo C.; Schneebeli, Martin

2014-01-01

This contribution uses finite-element analysis to simulate microstructural failure processes and the tensile strength of snow. The 3-D structure of snow was imaged by microtomography. Modeling procedures used the elastic properties of ice with bond fracture assumptions as inputs. The microstructure experiences combined tensile and compressive stresses in response to macroscopic tensile stress. The simulated nonlocalized failure of ice lattice bonds before or after reaching peak stress creates a pseudo-plastic yield curve. This explains the occurrence of acoustic events observed in advance of global failure. The measured and simulated average tensile strengths differed by 35%, a typical range for strength measurements in snow given its low Weibull modulus. The simulation successfully explains damage, fracture nucleation, and strength according to the geometry of the microstructure of snow and the mechanical properties of ice. This novel method can be applied to more complex snow structures including the weak layers that cause avalanches.

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.

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.

In-plane dynamic Green's functions for inclined and uniformly distributed loads in a multi-layered transversely isotropic half-space

NASA Astrophysics Data System (ADS)

Ba, Zhenning; Kang, Zeqing; Liang, Jianwen

2018-04-01

The dynamic stiffness method combined with the Fourier transform is utilized to derive the in-plane Green's functions for inclined and uniformly distributed loads in a multi-layered transversely isotropic (TI) half-space. The loaded layer is fixed to obtain solutions restricted in it and the corresponding reactions forces, which are then applied to the total system with the opposite sign. By adding solutions restricted in the loaded layer to solutions from the reaction forces, the global solutions in the wavenumber domain are obtained, and the dynamic Green's functions in the space domain are recovered by the inverse Fourier transform. The presented formulations can be reduced to the isotropic case developed by Wolf (1985), and are further verified by comparisons with existing solutions in a uniform isotropic as well as a layered TI half-space subjected to horizontally distributed loads which are special cases of the more general problem addressed. The deduced Green's functions, in conjunction with boundary element methods, will lead to significant advances in the investigation of a variety of wave scattering, wave radiation and soil-structure interaction problems in a layered TI site. Selected numerical results are given to investigate the influence of material anisotropy, frequency of excitation, inclination angle and layered on the responses of displacement and stress, and some conclusions are drawn.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

First results of electron temperature measurements by the use of multi-pass Thomson scattering system in GAMMA 10

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

Yoshikawa, M., E-mail: yosikawa@prc.tsukuba.ac.jp; Nagasu, K.; Shimamura, Y.

2014-11-15

A multi-pass Thomson scattering (TS) has the advantage of enhancing scattered signals. We constructed a multi-pass TS system for a polarisation-based system and an image relaying system modelled on the GAMMA 10 TS system. We undertook Raman scattering experiments both for the multi-pass setting and for checking the optical components. Moreover, we applied the system to the electron temperature measurements in the GAMMA 10 plasma for the first time. The integrated scattering signal was magnified by approximately three times by using the multi-pass TS system with four passes. The electron temperature measurement accuracy is improved by using this multi-pass system.

First results of electron temperature measurements by the use of multi-pass Thomson scattering system in GAMMA 10.

PubMed

Yoshikawa, M; Yasuhara, R; Nagasu, K; Shimamura, Y; Shima, Y; Kohagura, J; Sakamoto, M; Nakashima, Y; Imai, T; Ichimura, M; Yamada, I; Funaba, H; Kawahata, K; Minami, T

2014-11-01

A multi-pass Thomson scattering (TS) has the advantage of enhancing scattered signals. We constructed a multi-pass TS system for a polarisation-based system and an image relaying system modelled on the GAMMA 10 TS system. We undertook Raman scattering experiments both for the multi-pass setting and for checking the optical components. Moreover, we applied the system to the electron temperature measurements in the GAMMA 10 plasma for the first time. The integrated scattering signal was magnified by approximately three times by using the multi-pass TS system with four passes. The electron temperature measurement accuracy is improved by using this multi-pass system.

An AeroCom assessment of black carbon in Arctic snow and sea ice

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

Jiao, C.; Flanner, M. G.; Balkanski, Y.

2014-01-01

Though many global aerosols models prognose surface deposition, only a few models have been used to directly simulate the radiative effect from black carbon (BC) deposition to snow and sea ice. In this paper, we apply aerosol deposition fields from 25 models contributing to two phases of the Aerosol Comparisons between Observations and Models (AeroCom) project to simulate and evaluate within-snow BC concentrations and radiative effect in the Arctic. We accomplish this by driving the offline land and sea ice components of the Community Earth System Model with different deposition fields and meteorological conditions from 2004 to 2009, during whichmore » an extensive field campaign of BC measurements in Arctic snow occurred. We find that models generally underestimate BC concentrations in snow in northern Russia and Norway, while overestimating BC amounts elsewhere in the Arctic. Although simulated BC distributions in snow are poorly correlated with measurements, mean values are reasonable. The multi-model mean (range) bias in BC concentrations, sampled over the same grid cells, snow depths, and months of measurements, are -4.4 (-13.2 to +10.7) ng g -1 for an earlier phase of AeroCom models (phase I), and +4.1 (-13.0 to +21.4) ng g -1 for a more recent phase of AeroCom models (phase II), compared to the observational mean of 19.2 ng g -1. Factors determining model BC concentrations in Arctic snow include Arctic BC emissions, transport of extra-Arctic aerosols, precipitation, deposition efficiency of aerosols within the Arctic, and meltwater removal of particles in snow. Sensitivity studies show that the model–measurement evaluation is only weakly affected by meltwater scavenging efficiency because most measurements were conducted in non-melting snow. The Arctic (60–90° N) atmospheric residence time for BC in phase II models ranges from 3.7 to 23.2 days, implying large inter-model variation in local BC deposition efficiency. Combined with the fact that most Arctic BC deposition originates from extra-Arctic emissions, these results suggest that aerosol removal processes are a leading source of variation in model performance. The multi-model mean (full range) of Arctic radiative effect from BC in snow is 0.15 (0.07–0.25) W m -2 and 0.18 (0.06–0.28) W m -2 in phase I and phase II models, respectively. After correcting for model biases relative to observed BC concentrations in different regions of the Arctic, we obtain a multi-model mean Arctic radiative effect of 0.17 W m -2 for the combined AeroCom ensembles. Finally, there is a high correlation between modeled BC concentrations sampled over the observational sites and the Arctic as a whole, indicating that the field campaign provided a reasonable sample of the Arctic.« less

Long-term deepened snow promotes tundra evergreen shrub growth and summertime ecosystem net CO2 gain but reduces soil carbon and nutrient pools.

PubMed

Christiansen, Casper T; Lafreniére, Melissa J; Henry, Gregory H R; Grogan, Paul

2018-02-07

Arctic climate warming will be primarily during winter, resulting in increased snowfall in many regions. Previous tundra research on the impacts of deepened snow has generally been of short duration. Here, we report relatively long-term (7-9 years) effects of experimentally deepened snow on plant community structure, net ecosystem CO 2 exchange (NEE), and soil biogeochemistry in Canadian Low Arctic mesic shrub tundra. The snowfence treatment enhanced snow depth from 0.3 to ~1 m, increasing winter soil temperatures by ~3°C, but with no effect on summer soil temperature, moisture, or thaw depth. Nevertheless, shoot biomass of the evergreen shrub Rhododendron subarcticum was near-doubled by the snowfences, leading to a 52% increase in aboveground vascular plant biomass. Additionally, summertime NEE rates, measured in collars containing similar plant biomass across treatments, were consistently reduced ~30% in the snowfenced plots due to decreased ecosystem respiration rather than increased gross photosynthesis. Phosphate in the organic soil layer (0-10 cm depth) and nitrate in the mineral soil layer (15-25 cm depth) were substantially reduced within the snowfences (47-70 and 43%-73% reductions, respectively, across sampling times). Finally, the snowfences tended (p = .08) to reduce mineral soil layer C% by 40%, but with considerable within- and among plot variation due to cryoturbation across the landscape. These results indicate that enhanced snow accumulation is likely to further increase dominance of R. subarcticum in its favored locations, and reduce summertime respiration and soil biogeochemical pools. Since evergreens are relatively slow growing and of low stature, their increased dominance may constrain vegetation-related feedbacks to climate change. We found no evidence that deepened snow promoted deciduous shrub growth in mesic tundra, and conclude that the relatively strong R. subarcticum response to snow accumulation may explain the extensive spatial variability in observed circumpolar patterns of evergreen and deciduous shrub growth over the past 30 years. © 2018 John Wiley & Sons Ltd.

A multi-layer discrete-ordinate method for vector radiative transfer in a vertically-inhomogeneous, emitting and scattering atmosphere. I - Theory. II - Application

NASA Technical Reports Server (NTRS)

Weng, Fuzhong

1992-01-01

A theory is developed for discretizing the vector integro-differential radiative transfer equation including both solar and thermal radiation. A complete solution and boundary equations are obtained using the discrete-ordinate method. An efficient numerical procedure is presented for calculating the phase matrix and achieving computational stability. With natural light used as a beam source, the Stokes parameters from the model proposed here are compared with the analytical solutions of Chandrasekhar (1960) for a Rayleigh scattering atmosphere. The model is then applied to microwave frequencies with a thermal source, and the brightness temperatures are compared with those from Stamnes'(1988) radiative transfer model.

[Polarization Modeling and Analysis of Light Scattering Properties of Multilayer Films on Slightly Rough Substrate].

PubMed

Gao, Hui; Gao, Jun; Wang, Ling-mei; Wang, Chi

2016-03-01

To satisfy the demand of multilayer films on polarization detection, polarized bidirectional reflectance distribution function of multilayer films on slightly rough substrate is established on the basis of first-order vector perturbation theory and polarization transfer matrix. Due to the function, light scattering polarization properties are studied under multi-factor impacts of two typical targets-monolayer anti-reflection film and multilayer high-reflection films. The result shows that for monolayer anti-reflection film, observing positions have a great influence on the degree of polarization, for the left of the peak increased and right decreased compared with the substrate target. Film target and bare substrate can be distinguished by the degree of polarization in different observation angles. For multilayer high-reflection films, the degree of polarization is significantly associated with the number and optical thickness of layers at different wavelengths of incident light and scattering angles. With the increase of the layer number, the degree of polarization near the mirror reflection area decreases. It reveals that the calculated results coincide with the experimental data, which validates the correctness and rationality of the model. This paper provides a theoretical method for polarization detection of multilayer films target and reflection stealth technology.

Limitations of using a thermal imager for snow pit temperatures

NASA Astrophysics Data System (ADS)

Schirmer, M.; Jamieson, B.

2014-03-01

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

Examining Scattering Mechanisms within Bubbled Freshwater Lake Ice using a Time-Series of RADARSAT-2 (C-band) and UW-Scat (X-, Ku-band) Polarimetric Observations

NASA Astrophysics Data System (ADS)

Gunn, Grant; Duguay, Claude; Atwood, Don

2017-04-01

This study identifies the dominant scattering mechanism for C-, X- and Ku-band for bubbled freshwater lake ice in the Hudson Bay Lowlands near Churchill, Canada, using a winter time series of fully polarimetric ground-based (X- and Ku-band, UW-Scat) scatterometer and spaceborne (C-band) synthetic aperture radar (SAR, Radarsat-2) observations collected coincidentally to in-situ snow and ice measurements. Scatterometer observations identify two dominant backscatter sources from the ice cover: the snow-ice, and ice-water interface. Using in-situ measurements as ground-truth, a winter time series of scatterometer and satellite acquisitions show increases in backscatter from the ice-water interface prior to the timing of tubular bubble development in the ice cover. This timing indicates that scattering in the ice is independent of double-bounce scatter caused by tubular bubble inclusions. Concurrently, the co-polarized phase difference of interactions at the ice-water interface from both scatterometer and SAR observations are centred at 0° throughout the time series, indicating a scattering regime other than double bounce. A Yamaguchi three-component decomposition of SAR observations is presented for C-band acquisitions indicating a dominant single-bounce scattering mechanism regime, which is hypothesized to be a result of an ice-water interface that presents a rough surface or a surface composed of preferentially oriented facets. This study is the first to present a winter time series of coincident ground-based and spaceborne fully polarimetric active microwave observations for bubbled freshwater lake ice.

State of Arctic Sea Ice North of Svalbard during N-ICE2015

NASA Astrophysics Data System (ADS)

Rösel, Anja; King, Jennifer; Gerland, Sebastian

2016-04-01

The N-ICE2015 cruise, led by the Norwegian Polar Institute, was a drift experiment with the research vessel R/V Lance from January to June 2015, where the ship started the drift North of Svalbard at 83°14.45' N, 21°31.41' E. The drift was repeated as soon as the vessel drifted free. Altogether, 4 ice stations where installed and the complex ocean-sea ice-atmosphere system was studied with an interdisciplinary Approach. During the N-ICE2015 cruise, extensive ice thickness and snow depth measurements were performed during both, winter and summer conditions. Total ice and snow thickness was measured with ground-based and airborne electromagnetic instruments; snow depth was measured with a GPS snow depth probe. Additionally, ice mass balance and snow buoys were deployed. Snow and ice thickness measurements were performed on repeated transects to quantify the ice growth or loss as well as the snow accumulation and melt rate. Additionally, we collected independent values on surveys to determine the general ice thickness distribution. Average snow depths of 32 cm on first year ice, and 52 cm on multi-year ice were measured in January, the mean snow depth on all ice types even increased until end of March to 49 cm. The average total ice and snow thickness in winter conditions was 1.92 m. During winter we found a small growth rate on multi-year ice of about 15 cm in 2 months, due to above-average snow depths and some extraordinary storm events that came along with mild temperatures. In contrast thereto, we also were able to study new ice formation and thin ice on newly formed leads. In summer conditions an enormous melt rate, mainly driven by a warm Atlantic water inflow in the marginal ice zone, was observed during two ice stations with melt rates of up to 20 cm per 24 hours. To reinforce the local measurements around the ship and to confirm their significance on a larger scale, we compare them to airborne thickness measurements and classified SAR-satellite scenes. The here presented data set is important for understanding the ocean-ice-atmosphere interactions, for calculating energy fluxes, and biogeochemical processes.

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.

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.

Quantifying Particle Numbers and Mass Flux in Drifting Snow

NASA Astrophysics Data System (ADS)

Crivelli, Philip; Paterna, Enrico; Horender, Stefan; Lehning, Michael

2016-12-01

We compare two of the most common methods of quantifying mass flux, particle numbers and particle-size distribution for drifting snow events, the snow-particle counter (SPC), a laser-diode-based particle detector, and particle tracking velocimetry based on digital shadowgraphic imaging. The two methods were correlated for mass flux and particle number flux. For the SPC measurements, the device was calibrated by the manufacturer beforehand. The shadowgrapic imaging method measures particle size and velocity directly from consecutive images, and before each new test the image pixel length is newly calibrated. A calibration study with artificially scattered sand particles and glass beads provides suitable settings for the shadowgraphical imaging as well as obtaining a first correlation of the two methods in a controlled environment. In addition, using snow collected in trays during snowfall, several experiments were performed to observe drifting snow events in a cold wind tunnel. The results demonstrate a high correlation between the mass flux obtained for the calibration studies (r ≥slant 0.93) and good correlation for the drifting snow experiments (r ≥slant 0.81). The impact of measurement settings is discussed in order to reliably quantify particle numbers and mass flux in drifting snow. The study was designed and performed to optimize the settings of the digital shadowgraphic imaging system for both the acquisition and the processing of particles in a drifting snow event. Our results suggest that these optimal settings can be transferred to different imaging set-ups to investigate sediment transport processes.

Measurement of spectral sea ice albedo at Qaanaaq fjord in northwest Greenland

NASA Astrophysics Data System (ADS)

Tanikawa, T.

2017-12-01

The spectral albedos of sea ice were measured at Qaanaaq fjord in northwest Greenland. Spectral measurements were conducted for sea ice covered with snow and sea ice without snow where snow was artificially removed around measurement point. Thickness of the sea ice was approximately 1.3 m with 5 cm of snow over the sea ice. The measurements show that the spectral albedos of the sea ice with snow were lower than those of natural pure snow especially in the visible regions though the spectral shapes were similar to each other. This is because the spectral albedos in the visible region have information of not only the snow but also the sea ice under the snow. The spectral albedos of the sea ice without the snow were approximately 0.4 - 0.5 in the visible region, 0.05-0.25 in the near-infrared region and almost constant of approximately 0.05 in the region of 1500 - 2500 nm. In the visible region, it would be due to multiple scattering by an air bubble within the sea ice. In contrast, in the near-infrared and shortwave infrared wavelengths, surface reflection at the sea ice surface would be dominant. Since a light absorption by the ice in these regions is relatively strong comparing to the visible region, the light could not be penetrated deeply within the sea ice, resulting that surface reflection based on Fresnel reflection would be dominant. In this presentation we also show the results of comparison between the radiative transfer calculation and spectral measurement data.

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

NASA Technical Reports Server (NTRS)

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

2006-01-01

Ground-based measurements of particle size and fall speed distributions using a Particle Size and Velocity (PARSIVEL) disdrometer are compa red among samples obtained in mixed precipitation (rain and wet snow) and rain in the Oregon Cascade Mountains and in dry snow in the Rock y Mountains of Colorado. Coexisting rain and snow particles are distinguished using a classification method based on their size and fall sp eed properties. The bimodal distribution of the particles' joint fall speed-size characteristics at air temperatures from 0.5 to 0 C suggests that wet-snow particles quickly make a transition to rain once mel ting has progressed sufficiently. As air temperatures increase to 1.5 C, the reduction in the number of very large aggregates with a diame ter > 10 mm coincides with the appearance of rain particles larger than 6 mm. In this setting. very large raindrops appear to be the result of aggregates melting with minimal breakup rather than formation by c oalescence. In contrast to dry snow and rain, the fall speed for wet snow has a much weaker correlation between increasing size and increasing fall speed. Wet snow has a larger standard deviation of fall spee d (120%-230% relative to dry snow) for a given particle size. The ave rage fall speed for observed wet-snow particles with a diameter great er than or equal to 2.4 mm is 2 m/s with a standard deviation of 0.8 m/s. The large standard deviation is likely related to the coexistence of particles of similar physical size with different percentages of melting. These results suggest that different particle sizes are not required for aggregation since wet-snow particles of the same size can have different fall speeds. Given the large standard deviation of fa ll speeds in wet snow, the collision efficiency for wet snow is likely larger than that of dry snow. For particle sizes between 1 and 10 mm in diameter within mixed precipitation, rain constituted I % of the particles by volume within the isothermal layer at 0 C and 4% of the particles by volume for the region just below the isothermal layer where air temperatures rise from 0" to 0.5"C. As air temperatures increa sed above 0.5 C, the relative proportions of rain versus snow particl es shift dramatically and raindrops become dominant. The value of 0.5 C for the sharp transition in volume fraction from snow to rain is sl ightly lower than the range from 1 .l to 1.7 C often used in hydrolog ical models.

Active and Passive Radiative Transfer Modeling with Preferentially-Aligned Particles

NASA Technical Reports Server (NTRS)

Adams, Ian Stuart

2017-01-01

The fluid dynamics of falling hydrometeors often results in preferential orientations that can affect both the intensity and polarization of electromagnetic radiation. In order to properly interpret remote sensing observations of ice and snow, such alignments should be considered when constructing databases of scattering particles; however, the inclusion of aligned particles increases the complexity of the scattering data. To demonstrate the use of scattering properties of preferentially-aligned particles, millimeter-wave brightness temperatures and radar observables, including reflectivity and linear depolarization ratio, are modeled using the Atmospheric Radiative Transfer Simulator (ARTS). The necessary scattering parameters for vector radiative transfer, particularly with respect to ARTS, are reviewed, and the exploitation of particle symmetries, as well as scattering reciprocity relationships, are detailed.

A route for efficient non-resonance cloaking by using multilayer dielectric coating

NASA Astrophysics Data System (ADS)

Wang, Xiaohui; Semouchkina, Elena

2013-03-01

An approach for designing transmission cloaks by using ordinary dielectrics instead of meta- and plasmonic materials is proposed and demonstrated by the development of a multi-layer cloak for hiding cylindrical objects larger than the wavelengths of incident radiation. The parameters of the cloak layers were found by using the Genetic Algorithm-based optimization procedure, which employed the reciprocal of total scattering cross width of the cloaked target, derived from the solution of the Helmholtz equation, as the fitness function. The proposed cloak demonstrated better cloaking efficiency than did a similarly sized metamaterial cloak designed by using the transformation optics relations.

Simultaneous identification of optical constants and PSD of spherical particles by multi-wavelength scattering-transmittance measurement

NASA Astrophysics Data System (ADS)

Zhang, Jun-You; Qi, Hong; Ren, Ya-Tao; Ruan, Li-Ming

2018-04-01

An accurate and stable identification technique is developed to retrieve the optical constants and particle size distributions (PSDs) of particle system simultaneously from the multi-wavelength scattering-transmittance signals by using the improved quantum particle swarm optimization algorithm. The Mie theory are selected to calculate the directional laser intensity scattered by particles and the spectral collimated transmittance. The sensitivity and objective function distribution analysis were conducted to evaluate the mathematical properties (i.e. ill-posedness and multimodality) of the inverse problems under three different optical signals combinations (i.e. the single-wavelength multi-angle light scattering signal, the single-wavelength multi-angle light scattering and spectral transmittance signal, and the multi-angle light scattering and spectral transmittance signal). It was found the best global convergence performance can be obtained by using the multi-wavelength scattering-transmittance signals. Meanwhile, the present technique have been tested under different Gaussian measurement noise to prove its feasibility in a large solution space. All the results show that the inverse technique by using multi-wavelength scattering-transmittance signals is effective and suitable for retrieving the optical complex refractive indices and PSD of particle system simultaneously.

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.

Satellite and Surface Perspectives of Snow Extent in the Southern Appalachian Mountains

NASA Technical Reports Server (NTRS)

Sugg, Johnathan W.; Perry, Baker L.; Hall, Dorothy K.

2012-01-01

Assessing snow cover patterns in mountain regions remains a challenge for a variety of reasons. Topography (e.g., elevation, exposure, aspect, and slope) strongly influences snowfall accumulation and subsequent ablation processes, leading to pronounced spatial variability of snow cover. In-situ observations are typically limited to open areas at lower elevations (<1000 m). In this paper, we use several products from the Moderate Resolution Imaging Spectroradiometer (MODIS) to assess snow cover extent in the Southern Appalachian Mountains (SAM). MODIS daily snow cover maps and true color imagery are analyzed after selected snow events (e.g., Gulf/Atlantic Lows, Alberta Clippers, and Northwest Upslope Flow) from 2006 to 2012 to assess the spatial patterns of snowfall across the SAM. For each event, we calculate snow cover area across the SAM using MODIS data and compare with the Interactive Multi-sensor Snow and ice mapping system (IMS) and available in-situ observations. Results indicate that Gulf/Atlantic Lows are typically responsible for greater snow extent across the entire SAM region due to intensified cyclogenesis associated with these events. Northwest Upslope Flow events result in snow cover extent that is limited to higher elevations (>1000 m) across the SAM, but also more pronounced along NW aspects. Despite some limitations related to the presence of ephemeral snow or cloud cover immediately after each event, we conclude that MODIS products are useful for assessing the spatial variability of snow cover in heavily forested mountain regions such as the SAM.

Alaska North Slope Tundra Travel Model and Validation Study

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

Harry R. Bader; Jacynthe Guimond

2006-03-01

The Alaska Department of Natural Resources (DNR), Division of Mining, Land, and Water manages cross-country travel, typically associated with hydrocarbon exploration and development, on Alaska's arctic North Slope. This project is intended to provide natural resource managers with objective, quantitative data to assist decision making regarding opening of the tundra to cross-country travel. DNR designed standardized, controlled field trials, with baseline data, to investigate the relationships present between winter exploration vehicle treatments and the independent variables of ground hardness, snow depth, and snow slab thickness, as they relate to the dependent variables of active layer depth, soil moisture, and photosyntheticallymore » active radiation (a proxy for plant disturbance). Changes in the dependent variables were used as indicators of tundra disturbance. Two main tundra community types were studied: Coastal Plain (wet graminoid/moist sedge shrub) and Foothills (tussock). DNR constructed four models to address physical soil properties: two models for each main community type, one predicting change in depth of active layer and a second predicting change in soil moisture. DNR also investigated the limited potential management utility in using soil temperature, the amount of photosynthetically active radiation (PAR) absorbed by plants, and changes in microphotography as tools for the identification of disturbance in the field. DNR operated under the assumption that changes in the abiotic factors of active layer depth and soil moisture drive alteration in tundra vegetation structure and composition. Statistically significant differences in depth of active layer, soil moisture at a 15 cm depth, soil temperature at a 15 cm depth, and the absorption of photosynthetically active radiation were found among treatment cells and among treatment types. The models were unable to thoroughly investigate the interacting role between snow depth and disturbance due to a lack of variability in snow depth cover throughout the period of field experimentation. The amount of change in disturbance indicators was greater in the tundra communities of the Foothills than in those of the Coastal Plain. However the overall level of change in both community types was less than expected. In Coastal Plain communities, ground hardness and snow slab thickness were found to play an important role in change in active layer depth and soil moisture as a result of treatment. In the Foothills communities, snow cover had the most influence on active layer depth and soil moisture as a result of treatment. Once certain minimum thresholds for ground hardness, snow slab thickness, and snow depth were attained, it appeared that little or no additive effect was realized regarding increased resistance to disturbance in the tundra communities studied. DNR used the results of this modeling project to set a standard for maximum permissible disturbance of cross-country tundra travel, with the threshold set below the widely accepted standard of Low Disturbance levels (as determined by the U.S. Fish and Wildlife Service). DNR followed the modeling project with a validation study, which seemed to support the field trial conclusions and indicated that the standard set for maximum permissible disturbance exhibits a conservative bias in favor of environmental protection. Finally DNR established a quick and efficient tool for visual estimations of disturbance to determine when investment in field measurements is warranted. This Visual Assessment System (VAS) seemed to support the plot disturbance measurements taking during the modeling and validation phases of this project.« less

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

Modeling snow-crystal growth: a three-dimensional mesoscopic approach.

PubMed

Gravner, Janko; Griffeath, David

2009-01-01

We introduce a three-dimensional, computationally feasible, mesoscopic model for snow-crystal growth, based on diffusion of vapor, anisotropic attachment, and a boundary layer. Several case studies are presented that faithfully replicate most observed snow-crystal morphology, an unusual achievement for a mathematical model. In particular, many of the most striking physical specimens feature both facets and branches, and our model provides an explanation for this phenomenon. We also duplicate many other observed traits, including ridges, ribs, sandwich plates, and hollow columns, as well as various dynamic instabilities. The concordance of observed phenomena suggests that the ingredients in our model are the most important ones in the development of physical snow crystals.

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.

Determining hydrological changes in a small Arctic treeline basin using cold regions hydrological modelling and a pseudo-global warming approach

NASA Astrophysics Data System (ADS)

Krogh, S. A.; Pomeroy, J. W.

2017-12-01

Increasing temperatures are producing higher rainfall ratios, shorter snow-covered periods, permafrost thaw, more shrub coverage, more northerly treelines and greater interaction between groundwater and surface flow in Arctic basins. How these changes will impact the hydrology of the Arctic treeline environment represents a great challenge. To diagnose the future hydrology along the current Arctic treeline, a physically based cold regions model was used to simulate the hydrology of a small basin near Inuvik, Northwest Territories, Canada. The hydrological model includes hydrological processes such as snow redistribution and sublimation by wind, canopy interception of snow/rain and sublimation/evaporation, snowmelt energy balance, active layer freeze/thaw, infiltration into frozen and unfrozen soils, evapotranspiration, horizontal flow through organic terrain and snowpack, subsurface flow and streamflow routing. The model was driven with weather simulated by a high-resolution (4 km) numerical weather prediction model under two scenarios: (1) control run, using ERA-Interim boundary conditions (2001-2013) and (2) future, using a Pseudo-Global Warming (PGW) approach based on the RCP8.5 projections perturbing the control run. Transient changes in vegetation based on recent observations and ecological expectations were then used to re-parameterise the model. Historical hydrological simulations were validated against daily streamflow, snow water equivalent and active layer thickness records, showing the model's suitability in this environment. Strong annual warming ( 6 °C) and more precipitation ( 20%) were simulated by the PGW scenario, with winter precipitation and fall temperature showing the largest seasonal increase. The joint impact of climate and transient vegetation changes on snow accumulation and redistribution, evapotranspiration, active layer development, runoff generation and hydrograph characteristics are analyzed and discussed.

Microbial cell retention in a melting High Arctic snowpack, Svalbard

NASA Astrophysics Data System (ADS)

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

2014-05-01

Introduction The melting snow pack represents a highly dynamic system not only for chemical compounds but also for bacterial cells. Microbial activity was found at subzero temperatures in ice veins when liquid water persists due to high concentration of ions on the surface of snow crystals and brine channels between large ice crystals in ice. Several observations also suggest microbial activity under subzero temperatures in seasonal snow. Even with regard to the spatial and temporal relevance of snow ecosystems, microbial activity in such an extreme habitat represents a relatively small proportion in the carbon flux of the global ecosystem and even of the glacial ecosystems specifically. On the other hand, it represents a remarkable piece of mosaic of the microbial activity in glacial ecosystems because the snow pack represents the first contact between the atmosphere and cryosphere. This topic also embodies vital crossovers to biogeochemistry and ecotoxicology, offering a quantitative view of utilization of various substrates relevant for downstream ecosystems. Here we present our study of the dynamics of both solvents and cells suspended in meltwater of the melting snowpack on a high arctic glacier to demonstrate the spatio-temporal constraint of interaction between solvent and bacterial cells in this environment. Method We used 6 lysimeters inserted into the bottom of the snowpack to collect replicated samples of melt water before it comes into contact with basal ice or slush layer at the base of the snow pack. The sampling site was chosen at Midre Lovénbreen (Svalbard, Kongsfjorden, MLB stake 6) where the snow pack showed melting on the surface but the basal ice was still dry. Sampling was conducted in June 2010 for a period of 10 days once per day and the snow profile was sampled according to distinguished layers in the profile at the beginning of the field mission and as bulk at its end. The height of snow above the lysimeters dropped from the initial 74 cm to the final 38 cm. The major ion composition (IC), pH, conductivity and cell abundances were measured. Results and conlusions The removal of microbial cells from a high arctic snowpack resembles an elution sequence similar to that of hydrophobic compounds a process that helps glaciers retain a microbial biomass upon their surface, even after the demise of the snow cover. The snowpack and the glacier surface therefore act as an accumulator of cells during the melt season. This suggests that wet snowpacks, even on the surface of high arctic glaciers, are likely to be dynamic ecosystems in their own right. In our study, a clear ion elution sequence was observed that resembled earlier reports and caused high concentrations of ions in snowpack runoff at the start of the snow melt, which rapidly decreased as snow melt proceeded. Chloride, sulfate, nitrate, sodium and potassium experienced a 50 % elution before 20 - 25 % of the snowpack water content was lost. By contrast, cell removal only reached the 50 % level after ~70 % snowpack depletion. In contrast to our expectations, the calculated cell budget between the initial and final snowpack (including the cell loss by elution), revealed a significant increase of the total cell numbers, i.e. more than twice the original number. Assuming aeolian deposition processes to be low, this suggests cell proliferation as a contribution to the observed "retention effect". Precipitation was the major cell contributor to the snowpack upon Midtre Lovénbreen. An overall low cell concentration was therefore found within the snowpack stratigraphy, where snow layers frequently showed cell abundances similar to those of cloud water. This was in contrast to the nearby and more wind exposed sites examined in the Kongsfjorden area in 2007. However, layers of higher dust deposition were concomitant with one order of magnitude higher cell abundances, indicating that wind dispersal from locally exposed rocks supplements the atmospheric cell input.

Performance simulation of an x-ray detector for spectral CT with combined Si and Cd[Zn]Te detection layers

NASA Astrophysics Data System (ADS)

Herrmann, Christoph; Engel, Klaus-Jürgen; Wiegert, Jens

2010-12-01

The most obvious problem in obtaining spectral information with energy-resolving photon counting detectors in clinical computed tomography (CT) is the huge x-ray flux present in conventional CT systems. At high tube voltages (e.g. 140 kVp), despite the beam shaper, this flux can be close to 109 Mcps mm-2 in the direct beam or in regions behind the object, which are close to the direct beam. Without accepting the drawbacks of truncated reconstruction, i.e. estimating missing direct-beam projection data, a photon-counting energy-resolving detector has to be able to deal with such high count rates. Sub-structuring pixels into sub-pixels is not enough to reduce the count rate per pixel to values that today's direct converting Cd[Zn]Te material can cope with (<=10 Mcps in an optimistic view). Below 300 µm pixel pitch, x-ray cross-talk (Compton scatter and K-escape) and the effect of charge diffusion between pixels are problematic. By organising the detector in several different layers, the count rate can be further reduced. However this alone does not limit the count rates to the required level, since the high stopping power of the material becomes a disadvantage in the layered approach: a simple absorption calculation for 300 µm pixel pitch shows that the required layer thickness of below 10 Mcps/pixel for the top layers in the direct beam is significantly below 100 µm. In a horizontal multi-layer detector, such thin layers are very difficult to manufacture due to the brittleness of Cd[Zn]Te. In a vertical configuration (also called edge-on illumination (Ludqvist et al 2001 IEEE Trans. Nucl. Sci. 48 1530-6, Roessl et al 2008 IEEE NSS-MIC-RTSD 2008, Conf. Rec. Talk NM2-3)), bonding of the readout electronics (with pixel pitches below 100 µm) is not straightforward although it has already been done successfully (Pellegrini et al 2004 IEEE NSS MIC 2004 pp 2104-9). Obviously, for the top detector layers, materials with lower stopping power would be advantageous. The possible choices are, however, quite limited, since only 'mature' materials, which operate at room temperature and can be manufactured reliably should reasonably be considered. Since GaAs is still known to cause reliability problems, the simplest choice is Si, however with the drawback of strong Compton scatter which can cause considerable inter-pixel cross-talk. To investigate the potential and the problems of Si in a multi-layer detector, in this paper the combination of top detector layers made of Si with lower layers made of Cd[Zn]Te is studied by using Monte Carlo simulated detector responses. It is found that the inter-pixel cross-talk due to Compton scatter is indeed very high; however, with an appropriate cross-talk correction scheme, which is also described, the negative effects of cross-talk are shown to be removed to a very large extent.

Bayesian estimation of optical properties of the human head via 3D structural MRI

NASA Astrophysics Data System (ADS)

Barnett, Alexander H.; Culver, Joseph P.; Sorensen, A. Gregory; Dale, Anders M.; Boas, David A.

2003-10-01

Knowledge of the baseline optical properties of the tissues of the human head is essential for absolute cerebral oximetry, and for quantitative studies of brain activation. In this work we numerically model the utility of signals from a small 6-optode time-resolved diffuse optical tomographic apparatus for inferring baseline scattering and absorption coefficients of the scalp, skull and brain, when complete geometric information is available from magnetic resonance imaging (MRI). We use an optical model where MRI-segmented tissues are assumed homogeneous. We introduce a noise model capturing both photon shot noise and forward model numerical accuracy, and use Bayesian inference to predict errorbars and correlations on the measurments. We also sample from the full posterior distribution using Markov chain Monte Carlo. We conclude that ~ 106 detected photons are sufficient to measure the brain"s scattering and absorption to a few percent. We present preliminary results using a fast multi-layer slab model, comparing the case when layer thicknesses are known versus unknown.

3D printing of tissue-simulating phantoms for calibration of biomedical optical devices

NASA Astrophysics Data System (ADS)

Zhao, Zuhua; Zhou, Ximing; Shen, Shuwei; Liu, Guangli; Yuan, Li; Meng, Yuquan; Lv, Xiang; Shao, Pengfei; Dong, Erbao; Xu, Ronald X.

2016-10-01

Clinical utility of many biomedical optical devices is limited by the lack of effective and traceable calibration methods. Optical phantoms that simulate biological tissues used for optical device calibration have been explored. However, these phantoms can hardly simulate both structural and optical properties of multi-layered biological tissue. To address this limitation, we develop a 3D printing production line that integrates spin coating, light-cured 3D printing and Fused Deposition Modeling (FDM) for freeform fabrication of optical phantoms with mechanical and optical heterogeneities. With the gel wax Polydimethylsiloxane (PDMS), and colorless light-curable ink as matrix materials, titanium dioxide (TiO2) powder as the scattering ingredient, graphite powder and black carbon as the absorption ingredient, a multilayer phantom with high-precision is fabricated. The absorption and scattering coefficients of each layer are measured by a double integrating sphere system. The results demonstrate that the system has the potential to fabricate reliable tissue-simulating phantoms to calibrate optical imaging devices.

Multi-peaks scattering of light in glasses

NASA Astrophysics Data System (ADS)

Smirnov, V. A.; Vostrikova, L. I.

2018-04-01

Investigations of the multi-peaks scattering of the laser light on the micro-scale susceptibility gratings with small periodicities photo-induced in the various glass materials are presented. The observed pictures of the multi-peaks scattering of light in oxide samples show that the efficiencies of the processes of scattering can vary for the different chemical compositions. Experimental results are in agreement with the proposed theory of light scattering.

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

DTIC Science & Technology

1988-01-01

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

The performance of the new enhanced-resolution satellite passive microwave dataset applied for snow water equivalent estimation

NASA Astrophysics Data System (ADS)

Pan, J.; Durand, M. T.; Jiang, L.; Liu, D.

2017-12-01

The newly-processed NASA MEaSures Calibrated Enhanced-Resolution Brightness Temperature (CETB) reconstructed using antenna measurement response function (MRF) is considered to have significantly improved fine-resolution measurements with better georegistration for time-series observations and equivalent field of view (FOV) for frequencies with the same monomial spatial resolution. We are looking forward to its potential for the global snow observing purposes, and therefore aim to test its performance for characterizing snow properties, especially the snow water equivalent (SWE) in large areas. In this research, two candidate SWE algorithms will be tested in China for the years between 2005 to 2010 using the reprocessed TB from the Advanced Microwave Scanning Radiometer for EOS (AMSR-E), with the results to be evaluated using the daily snow depth measurements at over 700 national synoptic stations. One of the algorithms is the SWE retrieval algorithm used for the FengYun (FY) - 3 Microwave Radiation Imager. This algorithm uses the multi-channel TB to calculate SWE for three major snow regions in China, with the coefficients adapted for different land cover types. The second algorithm is the newly-established Bayesian Algorithm for SWE Estimation with Passive Microwave measurements (BASE-PM). This algorithm uses the physically-based snow radiative transfer model to find the histogram of most-likely snow property that matches the multi-frequency TB from 10.65 to 90 GHz. It provides a rough estimation of snow depth and grain size at the same time and showed a 30 mm SWE RMS error using the ground radiometer measurements at Sodankyla. This study will be the first attempt to test it spatially for satellite. The use of this algorithm benefits from the high resolution and the spatial consistency between frequencies embedded in the new dataset. This research will answer three questions. First, to what extent can CETB increase the heterogeneity in the mapped SWE? Second, will the SWE estimation error statistics be improved using this high-resolution dataset? Third, how will the SWE retrieval accuracy be improved using CETB and the new SWE retrieval techniques?

Femtosecond laser fabrication of sub-diffraction nanoripples on wet Al surface in multi-filamentation regime: High optical harmonics effects?

NASA Astrophysics Data System (ADS)

Ionin, A. A.; Kudryashov, S. I.; Makarov, S. V.; Rudenko, A. A.; Saltuganov, P. N.; Seleznev, L. V.; Sinitsyn, D. V.; Sunchugasheva, E. S.

2014-02-01

Relief ripples with sub-diffraction periods (≈λlas/3, λlas/4) were produced on a aluminum surface immersed in water and irradiated in a multi-filamentation regime by focused 744 nm femtosecond laser pulses with highly supercritical, multi-GW peak powers. For the VUV (8.5 eV) surface plasmon resonance on the wet aluminum surface, such small-scale surface nanogratings can be produced by high - second and third - optical harmonics, coming to the surface from the optical filaments in the water layer. Then, the sub-diffraction surface ripples may appear through interference of their transverse electric fields with the longitudinal electric fields of their counterparts, scattered on the surface roughness and appeared as the corresponding high-energy, high-wavenumber surface polaritons.

On the characterization of subpixel effects for passive microwave remote sensing of snow in montane environments

NASA Astrophysics Data System (ADS)

Vander Jagt, Benjamin John

Snow and its water equivalent plays a vital role in global water and energy balances, with particular relevance in mountainous areas with arid and semi-arid climate regimes. Spaceborne passive microwave (PM) remote sensing measurements are attractive for snowpack characterization due to their continuous global coverage and historical record; over 30 years of research has been invested in the development of methods to characterize large-scale snow water resources from PM-based measurements. Historically, use of PM data for snowpack characterization in montane enviroments has been obstructed by the complex subpixel variability of snow properties within the PM measurement footprint. The main subpixel effects can be grouped as: the effect of snow microstructure (e.g. snow grain size) and stratigraphy on snow microwave emission, vegetation attenuation of PM measurements, and the sensitivity PM brightness temperature (Tb) observation to the variability of different subpixel properties at spaceborne measurement scales. This dissertation is focused on a systematic examination of these issues, which thus far have prevented the widespread integration of snow water equivalent (SWE) retrieval methods. It is meant to further our comprehension of the underlying processes at work in these rugged, remote, a hydrologically important areas. The role that snow microstructure plays in the PM retrievals of SWE is examined first. Traditional estimates of grain size are subjective and prone to error. Objective techniques to characterize grain size are described and implemented, including near infrared (NIR), stereology, and autocorrelation based approaches. Results from an intensive Colorado field study in which independent estimates of grain size and their modeled brightness temperature (Tb) emission are evaluated against PM Tb observations are included. The coarse resolution of the passive microwave measurements provides additional challenges when trying to resolve snow states via remote sensing observations. The natural heterogeneity of snowpack (e.g. depth, stratigraphy, etc) and vegetative states within the PM footprint occurs at spatial scales smaller than PM observation scales. The sensitivity to changes in snow depth given sub-pixel variability in snow and vegetation is explored and quantified using the comprehensive dataset acquired during the Cold Land Processes experiment (CLPX). Lastly, vegetation has long been an obstacle in efforts to derive snow depth and mass estimates from passive microwave (PM) measurements of brightness temperature (Tb). We introduce a vegetation transmissivity model that is derived entirely from multi-scale and multi-temporal PM Tb observations and a globally available vegetation dataset, specifically the Leaf Area Index (LAI). This newly constructed model characterizes the attenuation of PM Tb observations at frequencies typically employed for snow retrieval algorithms, as a function of LAI. Additionally, the model is used to predict how much SWE is observable within the major river basins of Colorado and the central Rockies.

Accommodating permafrost in contaminant transport modeling, a preliminary approach to modify the TREECS modeling tools

NASA Astrophysics Data System (ADS)

Ryder, J. L.; Dortch, M. S.; Johnson, B. E.

2017-12-01

Efforts are underway to adapt TREECS (Training Range Environmental Evaluation and Characterization System) for use in arctic or subarctic conditions where the extent and duration of snowpack and frozen ground may influence the development and concentration of contaminant plumes. TREECS is a multi-media model designed to aid facility managers in the long term stewardship of Army properties. TREECS includes sub-models for mass loading, soil, vadose zone, aquifer, and stream transport. Potential changes to the sub-models to improve the ability to model contaminant transport in areas with permafrost include accurately representing the dissolution of contaminants over a wider range of temperatures, estimating snow depth and ablation for both the hydrology and thermal conditions, determining ground freeze/thaw state and an average active layer depth, a more precise method to estimate a vertical transport time to a water table, and a soil interflow routine that adapts for permafrost condition. In this presentation we will show three sub-model comparisons 1) the use of the National Weather Service SNOW-17 model and the current TREECS snowmelt routines for input hydrology, 2) a Continuous Frozen Ground Index (CFGI) model and the Geophysical Institute Permafrost Lab model (GIPL 1.0) for determining active layer depth and summer season length, and 3) the use of HYDRUS-1D and the current TREECS vadose zone model for transport to the water table. The performance vs input needs, assumptions, and limitations of each approach, as well as the physical system uncertainties will also be discussed.

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.

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.

[Spectrum similarities-based analysis of spatial difference of snow cover for multi-scale satellite data-a case study of MODIS and HJ-1B data].

PubMed

Liu, Yan; Li, Yang; Yang, Yun; Jian, Ji

2014-05-01

Vegetation and bare soil were collected in the areas of Miyaluo district in northwest of Sichuan province, the Qilian Mountains in Qinghai province and northern areas of Xinjiang during the years of 2007 and 2013. Then these data were converted to spectral reflectance by applying sensor response function of MODIS and HJ-1B respectively within the range of visible light, near-infrared and shortwave infrared. Comprehensive analysis was made on spectral characteristics and reflectivity similarities and differences of different sensors between old and new snowmelt, under the condition of different snow depth and different snow cover. The conclusions can be drawn That is, there exists high consistency of spectral response between new snow and dirty snow for each sensor in the visible wavelength range, also it is true for bare soil and low vegetation. However, low consistency happens to other types of snow; especially snowmelt and frozen snow. The range of NDSI is relatively stable under the condition of different snow depth for full snow cover and the trend of NDSI shows great consistency for different sensors; NDSI threshold method for monitoring snow by using MODIS and HJ-1B data showed very obvious difference in spatial scales, which is a reasonable explanation of the existence of mixed pixels.

Black carbon in the atmosphere and deposition on snow, last 130 years

NASA Astrophysics Data System (ADS)

Skeie, R. B.; Berntsen, T.; Myhre, G.; Pedersen, C.; Gerland, S.; Ström, J.; Forsström, S.

2009-04-01

The transport of Black Carbon (BC) in the atmosphere and the deposition of BC on snow surfaces for the last 130 years, with special emphasis on the last 8 years, are modeled with the Oslo CTM2 model. In addition regional contribution to BC deposition on snow in the polar region is evaluated for some years. The model results are compared with observations including our own recent measurement of BC in snow. Radiative forcing due to the direct effect as well as the snow-albedo effect is also calculated. Oslo CTM2 is an offline chemical transport model with T42 horizontal resolution using meteorological data from the IFS model at ECMWF. The scheme for BC includes hydrophilic and hydrophobic particles, as well as emissions from fossil fuel, biofuel and open biomass burning. Data on snow fall, melt and evaporation from ECMWF are used to generate and remove snow layers in each grid box. In these snow layers the amounts of deposited BC are stored, and concentration of BC in each snow layer is calculated. For the period 1870-2000 time slice simulations are done every 10th year. The period is simulated with constant meteorological data for the year 2000-2001 and vertical resolution of 40 levels. The emission data used is from Bond [1] for fossil fuel and biofuel, and data from Ito and Penner [2] for open biomass burning. The period 2000 until present are modeled with real time meteorological data and vertical resolution of 60 levels. Fossil fuel emission data used are the year 2000 data from Bond [1] except for the Asian region where REAS emissions [3] are used. For biomass burning BC emission the GFED data set are used [4]. The results are compared with available BC measurements from ice cores, air and snow. The observed time history of the BC concentration in snow over Greenland, US, and Himalaya is compared to the model results. During the years 2006-2008 several measurements of BC concentrations in snow in the Arctic region have been done, showing significant spatial variability. Within the large spread in the observations of BC concentration in snow, the model gives results that are consistent with the observations. In addition to evaluating total effect of BC in snow and its radiative effects, regional contribution to BC deposition on snow in the Arctic region are calculated. Today China is the region with largest BC fossil fuel emissions. Our results using the Olso CTM2 model show however that it is the 4th region in contribution to BC deposition on snow north of 65 degrees. The largest contributor is Russia, followed by Western Europe and North America. In the historical period, the share of emissions between these regions differs from the present situation. The BC emissions from fossil fuel in North America and Western Europe were respectively 3 and 2 times larger in 1920-30 than the present emissions from these regions. Therefore those regions had a higher contribution to BC in snow in the Arctic region 80 years ago than they have today. References: 1. Bond, T.C., et al., Historical emissions of black and organic carbon aerosol from energy-related combustion, 1850-2000. Global Biogeochemical Cycles, 2007. 21(2): p. 16. 2. Ito, A. and J.E. Penner, Historical emissions of carbonaceous aerosols from biomass and fossil fuel burning for the period 1870-2000. Global Biogeochemical Cycles, 2005. 19(2): p. 14. 3. Ohara, T., et al., An Asian emission inventory of anthropogenic emission sources for the period 1980-2020. Atmospheric Chemistry and Physics, 2007. 7(16): p. 4419-4444. 4. van der Werf, G.R., et al., Interannual variability in global biomass burning emissions from 1997 to 2004. Atmos. Chem. Phys., 2006. 6(11): p. 3423-3441.

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.

A novel multi-temporal approach to wet snow retrieval with Sentinel-1 images (Conference Presentation)

NASA Astrophysics Data System (ADS)

Marin, Carlo; Callegari, Mattia; Notarnicola, Claudia

2016-10-01

Snow is one of the most relevant natural water resources present in nature. It stores water in winter and releases it in spring during the melting season. Monitoring snow cover and its variability is thus of great importance for a proactive management of water-resources. Of particular interest is the identification of snowmelt processes, which could significantly support water administration, flood prediction and prevention. In the past years, remote sensing has demonstrated to be an essential tool for providing accurate inputs to hydrological models concerning the spatial and temporal variability of snow. Even though the analysis of snow pack can be conducted in the visible, near-infrared and short-wave infrared spectrum, the presence of clouds during the melting season, which may be pervasive in some parts of the World (e.g., polar regions), renders impossible the regular acquisition of information needed for the operational purposes. Therefore, the use of the microwave sensors, which signal can penetrate the clouds, can be an asset for the detection of snow proprieties. In particular, the SAR images have demonstrated to be effective and robust measurements to identify the wet snow. Among the several methods presented in the literature, the best results in wet snow mapping have been achieved by the bi-temporal change detection approach proposed by Nagler and Rott [1], or its slight improvements presented afterwards (e.g., [2]). Nonetheless, with the introduction of the Sentinel-1 by ESA, which provides free-of-charge SAR images every 6 days over the same geographical area with a resolution of 20m, the scientists have the opportunity to better investigate and improve the state-of-the-art methods for wet snow detection. In this work, we propose a novel method based on a supervised learning approach able to exploit both the experience of the state-of-the-art algorithms and the high multi-temporal information provided by the Sentinel-1 data. In detail, this is done by training the proposed method with examples extracted by [1] and refine this information by deriving additional training for the complex cases where the state-of-the-art algorithm fails. In addition, the multi-temporal information is fully exploited by modelling it as a series of statistical moments. Indeed, with a proper time sampling, statistical moments can describe the shape of the probability density function (pdf) of the backscattering time series ([3-4]). Given the description of the shape of the multi-temporal VV and VH backscattering pdfs, it is not necessary to explicitly identify which time instants in the time series are to be assigned to the reference image as done in the bi-temporal approach. This information is implicit in the shape of the pdf and it is used in the training procedure for solving the wet snow detection problem based on the available training samples. The proposed approach is designed to work in an alpine environment and it is validated considering ground truth measurements provided by automatic weather stations that record snow depth and snow temperature over 10 sites deployed in the South Tyrol region in northern Italy. References: [1] Nagler, T.; Rott, H., "Retrieval of wet snow by means of multitemporal SAR data," in Geoscience and Remote Sensing, IEEE Transactions on , vol.38, no.2, pp.754-765, Mar 2000. [2] Storvold, R., Malnes, E., and Lauknes, I., "Using ENVISAT ASAR wideswath data to retrieve snow covered area in mountainous regions", EARSeL eProceedings 4, 2/2006 [3] Inglada, J and Mercier, G., "A New Statistical Similarity Measure for Change Detection in Multitemporal SAR Images and Its Extension to Multiscale Change Analysis," in IEEE Transactions on Geoscience and Remote Sensing, vol. 45, no. 5, pp. 1432-1445, May 2007. [4] Bujor, F., Trouve, E., Valet, L., Nicolas J. M., and Rudant, J. P., "Application of log-cumulants to the detection of spatiotemporal discontinuities in multitemporal SAR images," in IEEE Transactions on Geoscience and Remote Sensing, vol. 42, no. 10, pp. 2073-2084, Oct. 2004.

Simulating the Dependence of Aspen on Redistributed Snow

NASA Astrophysics Data System (ADS)

Soderquist, B.; Kavanagh, K.; Link, T. E.; Seyfried, M. S.; Winstral, A. H.

2013-12-01

In mountainous regions across the western USA, the distribution of aspen (Populus tremuloides) is often directly related to heterogeneous soil moisture subsidies resulting from redistributed snow. With decades of climate and precipitation data across elevational and precipitation gradients, the Reynolds Creek Experimental Watershed (RCEW) in southwest Idaho provides a unique opportunity to study the relationship between aspen and redistributed snow. Within the RCEW, the total amount of precipitation has not changed in the past 50 years, but there are sharp declines in the percentage of the precipitation falling as snow. As shifts in the distribution of available moisture continue, future trends in aspen net primary productivity (NPP) remain uncertain. In order to assess the importance of snowdrift subsidies, NPP of three aspen stands was simulated at sites spanning elevational and precipitation gradients using the biogeochemical process model BIOME-BGC. At the aspen site experiencing the driest climate and lowest amount of precipitation from snow, approximately 400 mm of total precipitation was measured from November to March of 2008. However, peak measured snow water equivalent (SWE) held in drifts directly upslope of this stand was approximately 2100 mm, 5 times more moisture than the uniform winter precipitation layer initially assumed by BIOME-BGC. BIOME-BGC simulations in dry years forced by adjusted precipitation data resulted in NPP values approximately 30% higher than simulations assuming a uniform precipitation layer. Using BIOME-BGC and climate data from 1985-2011, the relationship between simulated NPP and measured basal area increments (BAI) improved after accounting for redistributed snow, indicating increased simulation representation. In addition to improved simulation capabilities, soil moisture data, diurnal branch water potential, and stomatal conductance observations at each site detail the use of soil moisture in the rooting zone and the onset of drought stress occurring in stands located along a precipitation phase gradient. These results further emphasize the importance of redistributed snow in heterogeneous landscapes along with the need to account for temporal shifts in water resource availability when assessing ecosystem vulnerability to climate change.

Multiple molecular scattering and albedo action on the solar spectral irradiance in the region of the UVB (less than or equal to 320 nm): A preliminary inventory

NASA Astrophysics Data System (ADS)

Nicolet, Marcel

A study comparing, in the spectral UVB region, the various components of the solar radiation field in order to explain the large difference obtained in Apr. 1939 by Goetz in Chur (green meadows), Nicolet in Arosa (adequate location in the snow) and Penndorf on the Weisshorn (above the ski slopes) (Switzerland) is presented. Numerical results from detailed theoretical calculations aimed at evaluating the various absolute effects associated with height, solar zenith angle and surface albedo were obtained for the standard atmosphere. The variations with solar zenith angles from 0 to 90 deg and albedos between 0 and 1 are presented for a spherical terrestrial atmosphere at selected wavelengths between 301 and 325 nm in the UVB region. From simultaneous measurements made at the same solar zenith angles, it was found that the values obtained in Arosa were between 5 and 10 times those obtained in Chur and on the Weisshorn. Such results are explained by a maximum of reflectivity of the snow covering the slope facing the relatively low Sun and its associated multiple scattered radiation in addition to the multiple molecular scattering of the atmosphere.

Influences and interactions of inundation, peat, and snow on active layer thickness

DOE PAGES

Atchley, Adam L.; Coon, Ethan T.; Painter, Scott L.; ...

2016-05-18

Active layer thickness (ALT), the uppermost layer of soil that thaws on an annual basis, is a direct control on the amount of organic carbon potentially available for decomposition and release to the atmosphere as carbon-rich Arctic permafrost soils thaw in a warming climate. Here, we investigate how key site characteristics affect ALT using an integrated surface/subsurface permafrost thermal hydrology model. ALT is most sensitive to organic layer thickness followed by snow depth but is relatively insensitive to the amount of water on the landscape with other conditions held fixed. Furthermore, the weak ALT sensitivity to subsurface saturation suggests thatmore » changes in Arctic landscape hydrology may only have a minor effect on future ALT. But, surface inundation amplifies the sensitivities to the other parameters and under large snowpacks can trigger the formation of near-surface taliks.« less

The life science X-ray scattering beamline at NSLS-II

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

DiFabio, Jonathan; Yang, Lin; Chodankar, Shirish

We report the current development status of the High Brightness X-ray Scattering for Life Sciences (or Life Science X-ray Scattering, LiX) beamline at the NSLS-II facility of Brookhaven National Laboratory. This instrument will operate in the x-ray energy range of 2.1-18 keV, provide variable beam sizes from 1 micron to ~0.5 mm, and support user experiments in three scientific areas: (1) high-throughput solution scattering, in-line size exclusion chromatography and flow mixers-based time-resolved solution scattering of biological macro-molecules, (2) diffraction from single- and multi-layered lipid membranes, and (3) scattering-based scanning probe imaging of biological tissues. In order to satisfy the beammore » stability required for these experiments and to switch rapidly between different types of experiments, we have adopted a secondary source with refractive lenses for secondary focusing, a detector system consisting of three Pilatus detectors, and specialized experimental modules that can be quickly exchanged and each dedicated to a defined set of experiments. The construction of this beamline is on schedule for completion in September 2015. User experiments are expected to start in Spring 2016.« less

The life science X-ray scattering beamline at NSLS-II

DOE PAGES

DiFabio, Jonathan; Yang, Lin; Chodankar, Shirish; ...

2015-09-30

We report the current development status of the High Brightness X-ray Scattering for Life Sciences (or Life Science X-ray Scattering, LiX) beamline at the NSLS-II facility of Brookhaven National Laboratory. This instrument will operate in the x-ray energy range of 2.1-18 keV, provide variable beam sizes from 1 micron to ~0.5 mm, and support user experiments in three scientific areas: (1) high-throughput solution scattering, in-line size exclusion chromatography and flow mixers-based time-resolved solution scattering of biological macro-molecules, (2) diffraction from single- and multi-layered lipid membranes, and (3) scattering-based scanning probe imaging of biological tissues. In order to satisfy the beammore » stability required for these experiments and to switch rapidly between different types of experiments, we have adopted a secondary source with refractive lenses for secondary focusing, a detector system consisting of three Pilatus detectors, and specialized experimental modules that can be quickly exchanged and each dedicated to a defined set of experiments. The construction of this beamline is on schedule for completion in September 2015. User experiments are expected to start in Spring 2016.« less

The life science x-ray scattering beamline at NSLS-II

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

DiFabio, Jonathan; Chodankar, Shirish; Pjerov, Sal

We report the current development status of the High Brightness X-ray Scattering for Life Sciences (or Life Science X-ray Scattering, LiX) beamline at the NSLS-II facility of Brookhaven National Laboratory. This instrument will operate in the x-ray energy range of 2.1-18 keV, provide variable beam sizes from 1 micron to ∼0.5 mm, and support user experiments in three scientific areas: (1) high-throughput solution scattering, in-line size exclusion chromatography and flow mixers-based time-resolved solution scattering of biological macro-molecules, (2) diffraction from single- and multi-layered lipid membranes, and (3) scattering-based scanning probe imaging of biological tissues. In order to satisfy the beammore » stability required for these experiments and to switch rapidly between different types of experiments, we have adopted a secondary source with refractive lenses for secondary focusing, a detector system consisting of three Pilatus detectors, and specialized experimental modules that can be quickly exchanged and each dedicated to a defined set of experiments. The construction of this beamline is on schedule for completion in September 2015. User experiments are expected to start in Spring 2016.« less

A Multi-Step Approach to Assessing LIGO Test Mass Coatings

NASA Astrophysics Data System (ADS)

Glover, Lamar; Goff, Michael; Linker, Seth; Neilson, Joshua; Patel, Jignesh; Pinto, Innocenzo; Principe, Maria; Villarama, Ethan; Arriaga, Eddy; Barragan, Erik; Chao, Shiuh; Daneshgaran, Lara; DeSalvo, Riccardo; Do, Eric; Fajardo, Cameron

2018-02-01

Photographs of the LIGO Gravitational Wave detector mirrors illuminated by the standing beam were analyzed with an astronomical software tool designed to identify stars within images, which extracted hundreds of thousands of point-like scatterers uniformly distributed across the mirror surface, likely distributed through the depth of the coating layers. The sheer number of the observed scatterers implies a fundamental, thermodynamic origin during deposition or processing. If identified as crystallites, these scatterers would be a possible source of the mirror dissipation and thermal noise, which limit the sensitivity of observatories to Gravitational Waves. In order to learn more about the composition and location of the detected scatterers, a feasibility study is underway to develop a method that determines the location of the scatterers by producing a complete mapping of scatterers within test samples, including their depth distribution, optical amplitude distribution, and lateral distribution. Also, research is underway to accurately identify future materials and/or coating methods that possess the largest possible mechanical quality factor (Q). Current efforts propose a new experimental approach that will more precisely measure the Q of coatings by depositing them onto 100 nm Silicon Nitride membranes.

Snow accumulation on Arctic sea ice: is it a matter of how much or when?

NASA Astrophysics Data System (ADS)

Webster, M.; Petty, A.; Boisvert, L.; Markus, T.

2017-12-01

Snow on sea ice plays an important, yet sometimes opposing role in sea ice mass balance depending on the season. In autumn and winter, snow reduces the heat exchange from the ocean to the atmosphere, reducing sea ice growth. In spring and summer, snow shields sea ice from solar radiation, delaying sea ice surface melt. Changes in snow depth and distribution in any season therefore directly affect the mass balance of Arctic sea ice. In the western Arctic, a decreasing trend in spring snow depth distribution has been observed and attributed to the combined effect of peak snowfall rates in autumn and the coincident delay in sea ice freeze-up. Here, we build on this work and present an in-depth analysis on the relationship between snow accumulation and the timing of sea ice freeze-up across all Arctic regions. A newly developed two-layer snow model is forced with eight reanalysis precipitation products to: (1) identify the seasonal distribution of snowfall accumulation for different regions, (2) highlight which regions are most sensitive to the timing of sea ice freeze-up with regard to snow accumulation, and (3) show, if precipitation were to increase, which regions would be most susceptible to thicker snow covers. We also utilize a comprehensive sensitivity study to better understand the factors most important in controlling winter/spring snow depths, and to explore what could happen to snow depth on sea ice in a warming Arctic climate.

Demonstrating the Uneven Importance of Fine-Scale Forest Structure on Snow Distributions using High Resolution Modeling

NASA Astrophysics Data System (ADS)

Broxton, P. D.; Harpold, A. A.; van Leeuwen, W.; Biederman, J. A.

2016-12-01

Quantifying the amount of snow in forested mountainous environments, as well as how it may change due to warming and forest disturbance, is critical given its importance for water supply and ecosystem health. Forest canopies affect snow accumulation and ablation in ways that are difficult to observe and model. Furthermore, fine-scale forest structure can accentuate or diminish the effects of forest-snow interactions. Despite decades of research demonstrating the importance of fine-scale forest structure (e.g. canopy edges and gaps) on snow, we still lack a comprehensive understanding of where and when forest structure has the largest impact on snowpack mass and energy budgets. Here, we use a hyper-resolution (1 meter spatial resolution) mass and energy balance snow model called the Snow Physics and Laser Mapping (SnowPALM) model along with LIDAR-derived forest structure to determine where spatial variability of fine-scale forest structure has the largest influence on large scale mass and energy budgets. SnowPALM was set up and calibrated at sites representing diverse climates in New Mexico, Arizona, and California. Then, we compared simulations at different model resolutions (i.e. 1, 10, and 100 m) to elucidate the effects of including versus not including information about fine scale canopy structure. These experiments were repeated for different prescribed topographies (i.e. flat, 30% slope north, and south-facing) at each site. Higher resolution simulations had more snow at lower canopy cover, with the opposite being true at high canopy cover. Furthermore, there is considerable scatter, indicating that different canopy arrangements can lead to different amounts of snow, even when the overall canopy coverage is the same. This modeling is contributing to the development of a high resolution machine learning algorithm called the Snow Water Artificial Network (SWANN) model to generate predictions of snow distributions over much larger domains, which has implications for improving land surface models that do not currently resolve or parameterize fine-scale canopy structure. In addition, these findings have implications for understanding the potential of different forest management strategies (i.e. thinning) based on local topography and climate to maximize the amount and retention of snow.

[A cloud detection algorithm for MODIS images combining Kmeans clustering and multi-spectral threshold method].

PubMed

Wang, Wei; Song, Wei-Guo; Liu, Shi-Xing; Zhang, Yong-Ming; Zheng, Hong-Yang; Tian, Wei

2011-04-01

An improved method for detecting cloud combining Kmeans clustering and the multi-spectral threshold approach is described. On the basis of landmark spectrum analysis, MODIS data is categorized into two major types initially by Kmeans method. The first class includes clouds, smoke and snow, and the second class includes vegetation, water and land. Then a multi-spectral threshold detection is applied to eliminate interference such as smoke and snow for the first class. The method is tested with MODIS data at different time under different underlying surface conditions. By visual method to test the performance of the algorithm, it was found that the algorithm can effectively detect smaller area of cloud pixels and exclude the interference of underlying surface, which provides a good foundation for the next fire detection approach.

Rain-on-snow and ice layer formation detection using passive microwave radiometry: An arctic perspective

NASA Astrophysics Data System (ADS)

Langlois, A.; Royer, A.; Montpetit, B.; Johnson, C. A.; Brucker, L.; Dolant, C.; Richards, A.; Roy, A.

2015-12-01

With the current changes observed in the Arctic, an increase in occurrence of rain-on-snow (ROS) events has been reported in the Arctic (land) over the past few decades. Several studies have established that strong linkages between surface temperatures and passive microwaves do exist, but the contribution of snow properties under winter extreme events such as rain-on-snow events (ROS) and associated ice layer formation need to be better understood that both have a significant impact on ecosystem processes. In particular, ice layer formation is known to affect the survival of ungulates by blocking their access to food. Given the current pronounced warming in northern regions, more frequent ROS can be expected. However, one of the main challenges in the study of ROS in northern regions is the lack of meteorological information and in-situ measurements. The retrieval of ROS occurrence in the Arctic using satellite remote sensing tools thus represents the most viable approach. Here, we present here results from 1) ROS occurrence formation in the Peary caribou habitat using an empirically developed ROS algorithm by our group based on the gradient ratio, 2) ice layer formation across the same area using a semi-empirical detection approach based on the polarization ratio spanning between 1978 and 2013. A detection threshold was adjusted given the platform used (SMMR, SSM/I and AMSR-E), and initial results suggest high-occurrence years as: 1981-1982, 1992-1993; 1994-1995; 1999-2000; 2001-2002; 2002-2003; 2003-2004; 2006-2007; 2007-2008. A trend in occurrence for Banks Island and NW Victoria Island and linkages to caribou population is presented.

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.

Physics Model-Based Scatter Correction in Multi-Source Interior Computed Tomography.

PubMed

Gong, Hao; Li, Bin; Jia, Xun; Cao, Guohua

2018-02-01

Multi-source interior computed tomography (CT) has a great potential to provide ultra-fast and organ-oriented imaging at low radiation dose. However, X-ray cross scattering from multiple simultaneously activated X-ray imaging chains compromises imaging quality. Previously, we published two hardware-based scatter correction methods for multi-source interior CT. Here, we propose a software-based scatter correction method, with the benefit of no need for hardware modifications. The new method is based on a physics model and an iterative framework. The physics model was derived analytically, and was used to calculate X-ray scattering signals in both forward direction and cross directions in multi-source interior CT. The physics model was integrated to an iterative scatter correction framework to reduce scatter artifacts. The method was applied to phantom data from both Monte Carlo simulations and physical experimentation that were designed to emulate the image acquisition in a multi-source interior CT architecture recently proposed by our team. The proposed scatter correction method reduced scatter artifacts significantly, even with only one iteration. Within a few iterations, the reconstructed images fast converged toward the "scatter-free" reference images. After applying the scatter correction method, the maximum CT number error at the region-of-interests (ROIs) was reduced to 46 HU in numerical phantom dataset and 48 HU in physical phantom dataset respectively, and the contrast-noise-ratio at those ROIs increased by up to 44.3% and up to 19.7%, respectively. The proposed physics model-based iterative scatter correction method could be useful for scatter correction in dual-source or multi-source CT.

Coherent backscattering effect in spectra of icy satellites and its modeling using multi-sphere T-matrix (MSTM) code for layers of particles

NASA Astrophysics Data System (ADS)

Pitman, Karly M.; Kolokolova, Ludmilla; Verbiscer, Anne J.; Mackowski, Daniel W.; Joseph, Emily C. S.

2017-12-01

The coherent backscattering effect (CBE), the constructive interference of light scattering in particulate surfaces (e.g., regolith), manifests as a non-linear increase in reflectance, or opposition surge, and a narrow negative polarization feature at small solar phase angles. Due to a strong dependence of the amplitude and angular width of this opposition surge on the absorptive characteristics of the surface material, CBE also produces phase-angle-dependent variations in the near-infrared spectra. In this paper we present a survey of such variations in the spectra of icy satellites of Saturn obtained by the Cassini spacecraft's Visual and Infrared Mapping Spectrometer (VIMS) and in the ground-based spectra of Oberon, a satellite of Uranus, obtained with TripleSpec, a cross-dispersed near-infrared spectrometer on the Astrophysical Research Consortium 3.5-m telescope located at the Apache Point Observatory near Sunspot, New Mexico. The paper also presents computer modeling of the saturnian satellite spectra and their phase-angle variations using the most recent version of the Multi-Sphere T-Matrix (MSTM) code developed to simulate light scattering by layers of randomly distributed spherical particles. The modeling allowed us not only to reproduce the observed effects but also to estimate characteristics of the icy particles that cover the surfaces of Rhea, Dione, and Tethys.

Role of Marine Snows in Microplastic Fate and Bioavailability.

PubMed

Porter, Adam; Lyons, Brett P; Galloway, Tamara S; Lewis, Ceri

2018-06-19

Microplastics contaminate global oceans and are accumulating in sediments at levels thought sufficient to leave a permanent layer in the fossil record. Despite this, the processes that vertically transport buoyant polymers from surface waters to the benthos are poorly understood. Here we demonstrate that laboratory generated marine snows can transport microplastics of different shapes, sizes, and polymers away from the water surface and enhance their bioavailability to benthic organisms. Sinking rates of all tested microplastics increased when incorporated into snows, with large changes observed for the buoyant polymer polyethylene with an increase in sinking rate of 818 m day -1 and for denser polyamide fragments of 916 m day -1 . Incorporation into snows increased microplastic bioavailability for mussels, where uptake increased from zero to 340 microplastics individual -1 for free microplastics to up to 1.6 × 10 5 microplastics individual -1 when incorporated into snows. We therefore propose that marine snow formation and fate has the potential to play a key role in the biogeochemical processing of microplastic pollution.

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Macroscopic modeling of heat and water vapor transfer with phase change in dry snow based on an upscaling method: Influence of air convection

NASA Astrophysics Data System (ADS)

Calonne, N.; Geindreau, C.; Flin, F.

2015-12-01

At the microscopic scale, i.e., pore scale, dry snow metamorphism is mainly driven by the heat and water vapor transfer and the sublimation-deposition process at the ice-air interface. Up to now, the description of these phenomena at the macroscopic scale, i.e., snow layer scale, in the snowpack models has been proposed in a phenomenological way. Here we used an upscaling method, namely, the homogenization of multiple-scale expansions, to derive theoretically the macroscopic equivalent modeling of heat and vapor transfer through a snow layer from the physics at the pore scale. The physical phenomena under consideration are steady state air flow, heat transfer by conduction and convection, water vapor transfer by diffusion and convection, and phase change (sublimation and deposition). We derived three different macroscopic models depending on the intensity of the air flow considered at the pore scale, i.e., on the order of magnitude of the pore Reynolds number and the Péclet numbers: (A) pure diffusion, (B) diffusion and moderate convection (Darcy's law), and (C) strong convection (nonlinear flow). The formulation of the models includes the exact expression of the macroscopic properties (effective thermal conductivity, effective vapor diffusion coefficient, and intrinsic permeability) and of the macroscopic source terms of heat and vapor arising from the phase change at the pore scale. Such definitions can be used to compute macroscopic snow properties from 3-D descriptions of snow microstructures. Finally, we illustrated the precision and the robustness of the proposed macroscopic models through 2-D numerical simulations.

Estimation of Subpixel Snow-Covered Area by Nonparametric Regression Splines

NASA Astrophysics Data System (ADS)

Kuter, S.; Akyürek, Z.; Weber, G.-W.

2016-10-01

Measurement of the areal extent of snow cover with high accuracy plays an important role in hydrological and climate modeling. Remotely-sensed data acquired by earth-observing satellites offer great advantages for timely monitoring of snow cover. However, the main obstacle is the tradeoff between temporal and spatial resolution of satellite imageries. Soft or subpixel classification of low or moderate resolution satellite images is a preferred technique to overcome this problem. The most frequently employed snow cover fraction methods applied on Moderate Resolution Imaging Spectroradiometer (MODIS) data have evolved from spectral unmixing and empirical Normalized Difference Snow Index (NDSI) methods to latest machine learning-based artificial neural networks (ANNs). This study demonstrates the implementation of subpixel snow-covered area estimation based on the state-of-the-art nonparametric spline regression method, namely, Multivariate Adaptive Regression Splines (MARS). MARS models were trained by using MODIS top of atmospheric reflectance values of bands 1-7 as predictor variables. Reference percentage snow cover maps were generated from higher spatial resolution Landsat ETM+ binary snow cover maps. A multilayer feed-forward ANN with one hidden layer trained with backpropagation was also employed to estimate the percentage snow-covered area on the same data set. The results indicated that the developed MARS model performed better than th

Spherization of the remnants of asymmetrical SN explosions in a uniform medium

NASA Astrophysics Data System (ADS)

Bisnovatyi-Kogan, G. S.; Blinnikov, S. I.

A 'snow-plow' approximation is used to project a spherical shape for a supernova remnant (SNR) after a shock wave has traveled through a uniform medium following an asymmetrical SN explosion. The asymmetry arises as magnetorotation causes the explosion. It is assumed that the main part of the mass remains in a thin layer after the explosion and that the layer can be described by 1,5-dimensional hydrodynamics. The cavity pressure inside the shock is assumed much greater than the pressure of the outside medium. The snow-plow model accounts for asymmetrical particle velocities in the expanding layer and the tangential velocity averaged across the shock. The equations are configured to conserve mass and momentum and have specific initial conditions. The calculations are in agreement with observations of Cas A.

On electromagnetic and quantum invisibility

NASA Astrophysics Data System (ADS)

Mundru, Pattabhiraju Chowdary

The principle objective of this dissertation is to investigate the fundamental properties of electromagnetic wave interactions with artificially fabricated materials i.e., metamaterials for application in advanced stealth technology called electromagnetic cloaking. The main goal is to theoretically design a metamaterial shell around an object that completely eliminates the dipolar and higher order multipolar scattering, thus making the object invisible. In this context, we developed a quasi-effective medium theory that determines the optical properties of multi-layered-composites beyond the quasi-static limit. The proposed theory exactly reproduces the far-field scattering/extinction cross sections through an iterative process in which mode-dependent quasi-effective impedances of the composite system are introduced. In the large wavelength limit, our theory is consistent with Maxwell-Garnett formalism. Possible applications in determining the hybridization particle resonances of multi-shell structures and electromagnetic cloaking are identified. This dissertation proposes a multi-shell generic cloaking system. A transparency condition independent of the object's optical and geometrical properties is proposed in the quasi-static regime of operation. The suppression of dipolar scattering is demonstrated in both cylindrically and spherically symmetric systems. A realistic tunable low-loss shell design is proposed based on the composite metal-dielectric shell. The effects due to dissipation and dispersion on the overall scattering cross-section are thoroughly evaluated. It is shown that a strong reduction of scattering by a factor of up to 103 can be achieved across the entire optical spectrum. Full wave numerical simulations for complex shaped particle are performed to validate the analytical theory. The proposed design does not require optical magnetism and is generic in the sense that it is independent of the object's material and geometrical properties. A generic quantum cloak analogous to the optical cloak is also proposed. The transparency conditions required for the shells to cloak an object impinged by a low energy beam of particles are derived. A realistic cloaking system with semiconductor material shells is studied.

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.

Sampling in the Snow: High School Winter Field Experiences Provide Relevant, Real World Connections Between Scientific Practices and Disciplinary Core Ideas

NASA Astrophysics Data System (ADS)

Hanson, E. W.; Burakowski, E. A.

2014-12-01

For much of the northern United States, the months surrounding the winter solstice are times of increased darkness, low temperatures, and frozen landscapes. It's a time when many high school science educators, who otherwise would venture outside with their classes, hunker down and are wary of the outdoors. However, a plethora of learning opportunities lies just beyond the classroom. Working collaboratively, a high school science teacher and a snow scientist have developed multiple activities to engage students in the scientific process of collecting, analyzing and interpreting the winter world using snow data to (1) learn about the insulative properties of snow, and (2) to learn about the role of snow cover on winter climate through its reflective properties while participating in a volunteer network that collects snow depth, albedo (reflectivity), and density data. These outdoor field-based snow investigations incorporate Next Generation Science Standards (NGSS) and disciplinary core ideas, including ESS2.C: The roles of water in Earth's surface processes and ESS2.D: Weather and Climate. Additionally, the lesson plans presented address Common Core State Standards (CCSS) in Mathematics, including the creation and analysis of bar graphs and time series plots (CCSS.Math.HSS-ID.A.1) and xy scatter plots (CCSS.Math.HSS-ID.B.6). High school students participating in the 2013/2014 snow sampling season described their outdoor learning experience as "authentic" and "hands-on" as compared to traditional class indoors. They emphasized that learning outdoors was essential to their understanding of underlying content and concepts because they "learn through actual experience."

Air-snowpack exchange of bromine, ozone and mercury in the springtime Arctic simulated by the 1-D model PHANTAS - Part 2: Mercury and its speciation

NASA Astrophysics Data System (ADS)

Toyota, K.; Dastoor, A. P.; Ryzhkov, A.

2014-04-01

Atmospheric mercury depletion events (AMDEs) refer to a recurring depletion of mercury occurring in the springtime Arctic (and Antarctic) boundary layer, in general, concurrently with ozone depletion events (ODEs). To close some of the knowledge gaps in the physical and chemical mechanisms of AMDEs and ODEs, we have developed a one-dimensional model that simulates multiphase chemistry and transport of trace constituents throughout porous snowpack and in the overlying atmospheric boundary layer (ABL). This paper constitutes Part 2 of the study, describing the mercury component of the model and its application to the simulation of AMDEs. Building on model components reported in Part 1 ("In-snow bromine activation and its impact on ozone"), we have developed a chemical mechanism for the redox reactions of mercury in the gas and aqueous phases with temperature dependent reaction rates and equilibrium constants accounted for wherever possible. Thus the model allows us to study the chemical and physical processes taking place during ODEs and AMDEs within a single framework where two-way interactions between the snowpack and the atmosphere are simulated in a detailed, process-oriented manner. Model runs are conducted for meteorological and chemical conditions that represent the springtime Arctic ABL characterized by the presence of "haze" (sulfate aerosols) and the saline snowpack on sea ice. The oxidation of gaseous elemental mercury (GEM) is initiated via reaction with Br-atom to form HgBr, followed by competitions between its thermal decomposition and further reactions to give thermally stable Hg(II) products. To shed light on uncertain kinetics and mechanisms of this multi-step oxidation process, we have tested different combinations of their rate constants based on published laboratory and quantum mechanical studies. For some combinations of the rate constants, the model simulates roughly linear relationships between the gaseous mercury and ozone concentrations as observed during AMDEs/ODEs by including the reaction HgBr + BrO and assuming its rate constant to be the same as for the reaction HgBr + Br, while for other combinations the results are more realistic by neglecting the reaction HgBr + BrO. Speciation of gaseous oxidized mercury (GOM) changes significantly depending on whether or not BrO is assumed to react with HgBr to form Hg(OBr)Br. Similarly to ozone (reported in Part 1), GEM is depleted via bromine radical chemistry more vigorously in the snowpack interstitial air than in the ambient air. However, the impact of such in-snow sink of GEM is found to be often masked by the re-emissions of GEM from the snow following the photo-reduction of Hg(II) deposited from the atmosphere. GOM formed in the ambient air is found to undergo fast "dry deposition" to the snowpack by being trapped on the snow grains in the top ~1 mm layer. We hypothesize that liquid-like layers on the surface of snow grains are connected to create a network throughout the snowpack, thereby facilitating the vertical diffusion of trace constituents trapped on the snow grains at much greater rates than one would expect inside solid ice crystals. Nonetheless, on the timescale of a week simulated in this study, the signal of atmospheric deposition does not extend notably below the top 1 cm of the snowpack. We propose and show that particulate-bound mercury (PBM) is produced mainly as HgBr42- by taking up GOM into bromide-enriched aerosols after ozone is significantly depleted in the air mass. In the Arctic, "haze" aerosols may thus retain PBM in ozone-depleted air masses, allowing the airborne transport of oxidized mercury from the area of its production farther than in the form of GOM. Temperature dependence of thermodynamic constants calculated in this study for Henry's law and aqueous-phase halide complex formation of Hg(II) species is a critical factor for this proposition, calling for experimental verification. The proposed mechanism may explain observed changes in the GOM-PBM partitioning with seasons, air temperature and the concurrent progress of ozone depletion in the high Arctic. The net deposition of mercury to the surface snow is shown to increase with the thickness of the turbulent ABL and to correspond well with the column amount of BrO in the atmosphere.

Evaluation of Visibility Sensors at the Eglin Air Force Base Climatic Chamber

DOT National Transportation Integrated Search

1983-10-01

Three transmissometers and five forward-scatter meters were evaluated for measuring fog, haze, rain and snow in the large test chamber of the Eglin Air Force Base Climatic Laboratory. Methods were developed for generating moderately uniform and stabl...

Performance Tests of Snow-Related Variables Over the Tibetan Plateau and Himalayas Using a New Version of NASA GEOS-5 Land Surface Model that Includes the Snow Darkening Effect

NASA Technical Reports Server (NTRS)

Yasunari, Tppei J.; Lau, K.-U.; Koster, Randal D.; Suarez, Max; Mahanama, Sarith; Dasilva, Arlindo M.; Colarco, Peter R.

2011-01-01

The snow darkening effect, i.e. the reduction of snow albedo, is caused by absorption of solar radiation by absorbing aerosols (dust, black carbon, and organic carbon) deposited on the snow surface. This process is probably important over Himalayan and Tibetan glaciers due to the transport of highly polluted Atmospheric Brown Cloud (ABC) from the Indo-Gangetic Plain (IGP). This effect has been incorporated into the NASA Goddard Earth Observing System model, version 5 (GEOS-5) atmospheric transport model. The Catchment land surface model (LSM) used in GEOS-5 considers 3 snow layers. Code was developed to track the mass concentration of aerosols in the three layers, taking into account such processes as the flushing of the compounds as liquid water percolates through the snowpack. In GEOS-5, aerosol emissions, transports, and depositions are well simulated in the Goddard Chemistry Aerosol Radiation and Transport (GO CART) module; we recently made the connection between GOCART and the GEOS-5 system fitted with the revised LSM. Preliminary simulations were performed with this new system in "replay" mode (i.e., with atmospheric dynamics guided by reanalysis) at 2x2.5 degree horizontal resolution, covering the period 1 November 2005 - 31 December 2009; we consider the final three years of simulation here. The three simulations used the following variants of the LSM: (1) the original Catchment LSM with a fixed fresh snowfall density of 150 kg m-3 ; (2) the LSM fitted with the new snow albedo code, used here without aerosol deposition but with changes in density formulation and melting water effect on snow specific surface area, (3) the LSM fitted with the new snow albedo code as same as (2) but with fixed aerosol deposition rates (computed from GOCART values averaged over the Tibetan Plateau domain [Ion.: 60-120E; lat.: 20-50N] during March-May 2008) applied to all grid points at every time step. For (2) and (3), the same setting on the fresh snowfall density as in (1) was used.

Impact of model structure on flow simulation and hydrological realism: from a lumped to a semi-distributed approach

NASA Astrophysics Data System (ADS)

Garavaglia, Federico; Le Lay, Matthieu; Gottardi, Fréderic; Garçon, Rémy; Gailhard, Joël; Paquet, Emmanuel; Mathevet, Thibault

2017-08-01

Model intercomparison experiments are widely used to investigate and improve hydrological model performance. However, a study based only on runoff simulation is not sufficient to discriminate between different model structures. Hence, there is a need to improve hydrological models for specific streamflow signatures (e.g., low and high flow) and multi-variable predictions (e.g., soil moisture, snow and groundwater). This study assesses the impact of model structure on flow simulation and hydrological realism using three versions of a hydrological model called MORDOR: the historical lumped structure and a revisited formulation available in both lumped and semi-distributed structures. In particular, the main goal of this paper is to investigate the relative impact of model equations and spatial discretization on flow simulation, snowpack representation and evapotranspiration estimation. Comparison of the models is based on an extensive dataset composed of 50 catchments located in French mountainous regions. The evaluation framework is founded on a multi-criterion split-sample strategy. All models were calibrated using an automatic optimization method based on an efficient genetic algorithm. The evaluation framework is enriched by the assessment of snow and evapotranspiration modeling against in situ and satellite data. The results showed that the new model formulations perform significantly better than the initial one in terms of the various streamflow signatures, snow and evapotranspiration predictions. The semi-distributed approach provides better calibration-validation performance for the snow cover area, snow water equivalent and runoff simulation, especially for nival catchments.

Multi Source Remote Sensing for Monitoring Light-Absorbing Impurities on Snow and Ice in the European Alps

NASA Astrophysics Data System (ADS)

Colombo, R.; Baccolo, G.; Garzonio, R.; Massabò, D.; Julitta, T.; Rossini, M.; Ferrero, L.; Delmonte, B.; Maggi, V.; Mattavelli, M.; Panigada, C.; Cogliati, S.; Cremonese, E.; Di Mauro, B.

2016-12-01

The European Alps are located close to one of the most industrialized areas of the planet and they are 3.000 km from the largest desert of the Earth. Light-absorbing impurities (LAI) emitted from these sources can reach the Alpine chain and deposit on snow covered areas and mountain glaciers. Although several studies show that LAI have important impacts on the optical properties of snow and ice, reducing the albedo and promoting the melt, this impact has been poorly characterized in the Alps. In this contribution, we present the results of a multisource remote sensing approach aimed to study the LAI impact on snow and ice properties in the Alpine area. This process has been observed by means of remote and proximal sensing methods, using satellite (Landsat 8, Hyperion and MODIS data), field spectroscopy (ASD measurements), Automatic Weather Stations, aerial surveys (Unmanned Aerial Vehicle), radiative transfer modeling (SNICAR and TARTES) and laboratory analysis (hyperspectral imaging system). Furthermore, particle size (Coulter Counter), geochemical (Instrumental Neutron Activation Analysis, INAA) and optical (Multi-Wavelength Absorbance Analyzer, MWAA) analyses have been applied to determine the nature and radiative properties of particulate material deposited on snow and ice or aggregated into cryoconite holes. Our results demonstrate that LAI can be monitored from remote sensing at different scale. LAI showed to have a strong impact on the Alpine cryosphere, paving the way for the assessment of their role in melting processes.

Multi Satellites Monitoring of Land Use/Cover Change and Its Driving Forces in Kashgar Region, China

NASA Astrophysics Data System (ADS)

Maimaitiaili, Ayisulitan; Aji, xiaokaiti; Kondoh, Akihiko

2016-04-01

Multi Satellites Monitoring of Land Use/Cover Change and Its Driving Forces in Kashgar Region, China Ayisulitan Maimaitiaili1, Xiaokaiti Aji2 Akihiko Kondoh2 1Graduate School of Science, Chiba University, Japan 2Center for Environmental Remote Sensing, Chiba University The spatio-temporal changes of Land Use/Cover (LUCC) and its driving forces in Kashgar region, Xinjiang Province, China, are investigated by using satellite remote sensing and a geographical information system (GIS). Main goal of this paper is to quantify the drivers of LUCC. First, considering lack of the Land Cover (LC) map in whole study area, we produced LC map by using Landsat images. Land use information from Landsat data was collected using maximum likelihood classification method. Land use change was studied based on the change detection method of land use types. Second, because the snow provides a key water resources for stream flow, agricultural production and drinking water for sustaining large population in Kashgar region, snow cover are estimated by Spot Vegetation data. Normalized Difference Snow Index (NDSI) algorithm are applied to make snow cover map, which is used to screen the LUCC and climate change. The best agreement is found with threshold value of NDSI≥0.2 to generate multi-temporal snow cover and snowmelt maps. Third, driving forces are systematically identified by LC maps and statistical data such as climate and socio-economic data, regarding to i) the climate changes and ii) socioeconomic development that the spatial correlation among LUCC, snow cover change, climate and socioeconomic changes are quantified by using liner regression model and negative / positive trend analysis. Our results showed that water bodies, bare land and grass land have decreasing notably. By contrast, crop land and urban area have continually increasing significantly, which are dominated in study area. The area of snow/ice have fluctuated and has strong seasonal trends, total annual snow cover has two peaks in 2005 and 2009. With increasing population from 2,324,375 in 1984 to 4,228,200 in 2014 and crop land reclamation from 6031.4 km2 in 1972 to 16549km2 in 2014 at the study area. Water resources consumption increased with support to large population and irrigate whole crop land area, caused the water shortages that the surface water bodies decreased from 2531.43km2 in the 1972s to 1067.05km2 in the 2014. The grass land with an acreage larger than 6749km2 in 1972 decreased to 922.6 km2 in 2014. The transformations between water bodies, garss land and bare land are remarkbale. The results also suggested high linearity between the LUCC and socioeconomic changes that specific land cover change be cause of the fact that socioeconomic development. In the recent 42 years, average annual temperature have been increasing significantly, although, precipitation have increased but partly weaken effect of the rising temperature, in addition snow cover more sensitive to precipitation than temperature. Results the change of climate showed a nagitive relationship between the NDSI with decrased of the snow cover and climate with increasing of the tempreature. Morover, the relationship between the LUCC and snow cover recorded higher linearity, because the temperature have increased, consequence influence on snow cover that provides melt water for study area which expanding crop land.

Estimates of free-tropospheric NO2 and HCHO mixing ratios derived from high-altitude mountain MAX-DOAS observations at midlatitudes and in the tropics

NASA Astrophysics Data System (ADS)

Schreier, Stefan F.; Richter, Andreas; Wittrock, Folkard; Burrows, John P.

2016-03-01

In this study, mixing ratios of NO2 (XNO2) and HCHO (XHCHO) in the free troposphere are derived from two multi-axis differential optical absorption spectroscopy (MAX-DOAS) data sets collected at Zugspitze (2650 m a.s.l., Germany) and Pico Espejo (4765 m a.s.l., Venezuela). The estimation of NO2 and HCHO mixing ratios is based on the modified geometrical approach, which assumes a single-scattering geometry and a scattering point altitude close to the instrument altitude. Firstly, the horizontal optical path length (hOPL) is obtained from O4 differential slant column densities (DSCDs) in the horizontal (0°) and vertical (90°) viewing directions. Secondly, XNO2 and XHCHO are estimated from the NO2 and HCHO DSCDs at the 0° and 90° viewing directions and averaged along the obtained hOPLs. As the MAX-DOAS instrument was performing measurements in the ultraviolet region, wavelength ranges of 346-372 and 338-357 nm are selected for the DOAS analysis to retrieve NO2 and HCHO DSCDs, respectively. In order to compare the measured O4 DSCDs and moreover to perform some sensitivity tests, the radiative transfer model SCIATRAN with adapted altitude settings for mountainous terrain is operated to simulate synthetic spectra, on which the DOAS analysis is also applied. The overall agreement between measured and synthetic O4 DSCDs is better for the higher Pico Espejo station than for Zugspitze. Further sensitivity analysis shows that a change in surface albedo (from 0.05 to 0.7) can influence the O4 DSCDs, with a larger absolute difference observed for the horizontal viewing direction. Consequently, the hOPL can vary by about 5 % throughout the season, for example when winter snow cover fully disappears in summer. Typical values of hOPLs during clear-sky conditions are 19 km (14 km) at Zugspitze and 34 km (26.5 km) at Pico Espejo when using the 346-372 (338-357 nm) fitting window. The estimated monthly values of XNO2 (XHCHO), averaged over these hOPLs during clear-sky conditions, are in the range of 60-100 ppt (500-950 ppt) at Zugspitze and 8.5-15.5 ppt (255-385 ppt) at Pico Espejo. Interestingly, multi-year-averaged monthly means of XNO2 and XHCHO increase towards the end of the dry season at the Pico Espejo site, suggesting that both trace gases are frequently lifted above the boundary layer as a result of South American biomass burning.

Estimates of free-tropospheric NO2 and HCHO mixing ratios derived from high-altitude mountain MAX-DOAS observations in the mid-latitudes and tropics

NASA Astrophysics Data System (ADS)

Schreier, S. F.; Richter, A.; Wittrock, F.; Burrows, J. P.

2015-11-01

In this study, mixing ratios of NO2 (XNO2) and HCHO (XHCHO) in the free troposphere are derived from two Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) data sets collected at Zugspitze (2650 m a.s.l., Germany) and Pico Espejo (4765 m a.s.l., Venezuela). The estimation of NO2 and HCHO mixing ratios is based on the modified geometrical approach, which assumes a single-scattering geometry and a scattering point altitude close to the instrument. Firstly, the horizontal optical path length (hOPL) is obtained from O4 differential slant column densities (DSCDs) in the horizontal (0°) and vertical (90°) viewing directions. Secondly, XNO2 and XHCHO are estimated from the NO2 and HCHO DSCDs at the 0 and 90° viewing directions and averaged along the obtained hOPLs. As the MAX-DOAS instrument was performing measurements in the ultraviolet region, wavelength ranges of 346-372 and 338-357 nm are selected for the DOAS analysis to retrieve NO2 and HCHO DSCDs, respectively. In order to compare the measured O4 DSCDs and moreover to perform some sensitivity tests, the radiative transfer model SCIATRAN with adapted altitude settings for mountainous terrain is operated to simulate synthetic spectra, on which the DOAS analysis is also applied. The overall agreement between measured and synthetic O4 DSCDs is better for the higher Pico Espejo station than for Zugspitze. Further sensitivity analysis shows that a change in surface albedo (from 0.05 to 0.7) can influence the O4 DSCDs, with a larger absolute difference observed for the horizontal viewing direction. Consequently, the hOPL can vary by about 5 % throughout the season, for example when winter snow cover fully disappears in summer. Typical values of hOPLs during clear sky conditions are 19 km (14 km) at Zugspitze and 34 km (26.5 km) at Pico Espejo when using the 346-372 nm (338-357 nm) fitting window. The estimated monthly values of XNO2 (XHCHO), averaged over these hOPLs during clear sky conditions, are in the range of 60-100 ppt (500-950 ppt) at Zugspitze and 8.5-15.5 ppt (255-385 ppt) at Pico Espejo. Interestingly, multi-year averaged monthly means of XNO2 and XHCHO increase towards the end of the dry season at the Pico Espejo site, suggesting that both trace gases are frequently lifted above the boundary layer as a result of South American biomass burning.

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

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

NASA Astrophysics Data System (ADS)

Andreadis, K.; Lettenmaier, D.

2008-12-01

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

Surface and basal ice shelf mass balance processes of the Southern McMurdo Ice Shelf determined through radar statistical reconnaissance

NASA Astrophysics Data System (ADS)

Grima, C.; Koch, I.; Greenbaum, J. S.; Soderlund, K. M.; Blankenship, D. D.; Young, D. A.; Fitzsimons, S.

2017-12-01

The McMurdo ice shelves (northern and southern MIS), adjacent to the eponymous station and the Ross Ice Shelf, Antarctica, are known for large gradients in surface snow accumulation and snow/ice impurities. Marine ice accretion and melting are important contributors to MIS's mass balance. Due to erosive winds, the southern MIS (SMIS) shows a locally negative surface mass balance. Thus, marine ice once accreted at the ice shelf base crops out at the surface. However, the exact processes that exert primary control on SMIS mass balance have remained elusive. Radar statistical reconnaissance (RSR) is a recent technique that has been used to characterize the surface properties of the Earth's cryosphere, Mars, and Titan from the stochastic character of energy scattered by the surface. Here, we apply RSR to map the surface density and roughness of the SMIS and extend the technique to derive the basal reflectance and scattering coefficients of the ice-ocean interface. We use an airborne radar survey grid acquired over the SMIS in the 2014-2015 austral summer by the University of Texas Institute for Geophysics with the High Capability Radar Sounder (HiCARS2; 60-MHz center frequency and 15-MHz bandwidth). The RSR-derived snow density values and patterns agree with directly -measured ice shelf surface accumulation rates. We also compare the composition of SMIS ice surface samples to test the ability of RSR to discriminate ices with varying dielectric properties (e.g., marine versus meteoric ice) and hypothesize relationships between the RSR-derived basal reflectance/scattered coefficients and accretion or melting at the ice-ocean interface. This improved knowledge of air-ice and ice-ocean boundaries provides a new perspective on the processes governing SMIS surface and basal mass balance.

Evaluation of an improved intermediate complexity snow scheme in the ORCHIDEE land surface model

NASA Astrophysics Data System (ADS)

Wang, Tao; Ottlé, Catherine; Boone, Aaron; Ciais, Philippe; Brun, Eric; Morin, Samuel; Krinner, Gerhard; Piao, Shilong; Peng, Shushi

2013-06-01

Snow plays an important role in land surface models (LSM) for climate and model applied over Fran studies, but its current treatment as a single layer of constant density and thermal conductivity in ORCHIDEE (Organizing Carbon and Hydrology in Dynamic Ecosystems) induces significant deficiencies. The intermediate complexity snow scheme ISBA-ES (Interaction between Soil, Biosphere and Atmosphere-Explicit Snow) that includes key snow processes has been adapted and implemented into ORCHIDEE, referred to here as ORCHIDEE-ES. In this study, the adapted scheme is evaluated against the observations from the alpine site Col de Porte (CDP) with a continuous 18 year data set and from sites distributed in northern Eurasia. At CDP, the comparisons of snow depth, snow water equivalent, surface temperature, snow albedo, and snowmelt runoff reveal that the improved scheme in ORCHIDEE is capable of simulating the internal snow processes better than the original one. Preliminary sensitivity tests indicate that snow albedo parameterization is the main cause for the large difference in snow-related variables but not for soil temperature simulated by the two models. The ability of the ORCHIDEE-ES to better simulate snow thermal conductivity mainly results in differences in soil temperatures. These are confirmed by performing sensitivity analysis of ORCHIDEE-ES parameters using the Morris method. These features can enable us to more realistically investigate interactions between snow and soil thermal regimes (and related soil carbon decomposition). When the two models are compared over sites located in northern Eurasia from 1979 to 1993, snow-related variables and 20 cm soil temperature are better reproduced by ORCHIDEE-ES than ORCHIDEE, revealing a more accurate representation of spatio-temporal variability.

Wind tunnel experiments: influence of erosion and deposition on wind-packing of new snow

NASA Astrophysics Data System (ADS)

Sommer, Christian G.; Lehning, Michael; Fierz, Charles

2018-01-01

Wind sometimes creates a hard, wind-packed layer at the surface of a snowpack. The formation of such wind crusts was observed during wind tunnel experiments with combined SnowMicroPen and Microsoft Kinect sensors. The former provides the hardness of new and wind-packed snow and the latter spatial snow depth data in the test section. Previous experiments showed that saltation is necessary but not sufficient for wind-packing. The combination of hardness and snow depth data now allows to study the case with saltation in more detail. The Kinect data requires complex processing but with the appropriate corrections, snow depth changes can be measured with an accuracy of about 1 mm. The Kinect is therefore well suited to quantify erosion and deposition. We found that no hardening occurred during erosion and that a wind crust may or may not form when snow is deposited. Deposition is more efficient at hardening snow in wind-exposed than in wind-sheltered areas. The snow hardness increased more on the windward side of artificial obstacles placed in the wind tunnel. Similarly, the snow was harder in positions with a low Sx parameter. Sx describes how wind-sheltered (high Sx) or wind-exposed (low Sx) a position is and was calculated based on the Kinect data. The correlation between Sx and snow hardness was -0.63. We also found a negative correlation of -0.4 between the snow hardness and the deposition rate. Slowly deposited snow is harder than a rapidly growing accumulation. Sx and the deposition rate together explain about half of the observed variability of snow hardness.

Using multi-source satellite data to assess snow-cover change in Qinghai-Tibetan Plateau in last decade

NASA Astrophysics Data System (ADS)

Jiang, Y.; Chen, F.; Gao, Y.; Barlage, M. J.

2017-12-01

Snow cover in Qinghai-Tibetan Plateau (QTP) is a critical component of water cycle and affects regional climate of East Asia. Satellite data from three different sources (i.e., FY3A/B/C, MODIS and IMS) were used to analyze the QTP fractional-snow-cover (FSC) change and associated uncertainties in the last decade. To reduce the high percentage of cloud in FY3A/B/C and MODIS, a four-step cloud removal procedure was applied and effectively reduced the cloud percentage from 40.8-56.1% to 2.2­-­3.3%. The averaged error introduced by the cloud removal procedure was about 2% estimated by a random sampling method. Results show that the snow cover in QTP significantly decreased in recent 5 years. Three data sets (FY3B, MODIS and IMS) showed significant decreased annual FSC at all elevation bands from 2012-2016, and a significant shorter snow season with delayed snow onset and earlier melting. Both IMS and MODIS had a slightly decline annual FSC from 2000 to 3000 m, while MODIS FSC slightly decreased in 2002-2016 and IMS FSC slightly increased from 2006-2016 in the region with elevation higher than 3000 m. Results also show significant uncertainties among the five data sets (FY3A/B/C, MODIS, IMS), although they showed similar fluctuations of daily FSC. IMS had largest snow-cover extent and highest daily FSC due to its multi data sources. FY3A/C and MODIS (observed in the morning) had around 5% higher mean FSC than FY3B (observed in the afternoon) due to the 3 hours detection time gap. The relative error of daily FSC (taking MODIS as `truth') between FY3A/B/C, IMS and MODIS is 23%, -35%, 8% and 63%, respectively, averaged in five elevation bands in 2015-2017.

Spatiotemporal dynamics of snow cover based on multi-source remote sensing data in China

NASA Astrophysics Data System (ADS)

Huang, Xiaodong; Deng, Jie; Ma, Xiaofang; Wang, Yunlong; Feng, Qisheng; Hao, Xiaohua; Liang, Tiangang

2016-10-01

By combining optical remote sensing snow cover products with passive microwave remote sensing snow depth (SD) data, we produced a MODIS (Moderate Resolution Imaging Spectroradiometer) cloudless binary snow cover product and a 500 m snow depth product. The temporal and spatial variations of snow cover from December 2000 to November 2014 in China were analyzed. The results indicate that, over the past 14 years, (1) the mean snow-covered area (SCA) in China was 11.3 % annually and 27 % in the winter season, with the mean SCA decreasing in summer and winter seasons, increasing in spring and fall seasons, and not much change annually; (2) the snow-covered days (SCDs) showed an increase in winter, spring, and fall, and annually, whereas they showed a decrease in summer; (3) the average SD decreased in winter, summer, and fall, while it increased in spring and annually; (4) the spatial distributions of SD and SCD were highly correlated seasonally and annually; and (5) the regional differences in the variation of snow cover in China were significant. Overall, the SCD and SD increased significantly in south and northeast China, and decreased significantly in the north of Xinjiang province. The SCD and SD increased on the southwest edge and in the southeast part of the Tibetan Plateau, whereas it decreased in the north and northwest regions.

Improved Passive Microwave Algorithms for North America and Eurasia

NASA Technical Reports Server (NTRS)

Foster, James; Chang, Alfred; Hall, Dorothy

1997-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Meltwater-induced changes in the structure and behavior of Greenland's firn

NASA Astrophysics Data System (ADS)

MacFerrin, M. J.; Machguth, H.; van As, D.; Charalampidis, C.; Heilig, A.; Vandecrux, B.; Stevens, C.; Abdalati, W.

2017-12-01

As surface melt increases across the Greenland ice sheet in a warming climate, Greenland's accumulation zone has absorbed a progressively greater volume of water. In low-accumulation regions lacking perennial aquifers, this meltwater has refrozen into subsurface ice, which is now fundamentally altering the structure of near-surface firn layers. Here we present an extensive collection of firn cores, in situ radar, NASA IceBridge radar, thermistor string measurements, in situ FirnCover compaction data and regional climate model results to illustrate several distinct ways that Greenland's percolation zone is being fundamentally altered by increasing surface melt. The bulk density of the top 20 meters' firn in the wet-snow facies has increased by up to 40% in the past 50 years, due primarily to an up to six-fold increase in firn ice content. Firn compaction rates have changed both in their annual magnitude and have been delayed in their seasonal phase by up to three months, driven primarily by an increased release of latent heat as water refreezes at depth. When firn exceeds a threshold of excess melt in which seasonal snow can no longer accommodate summer melt, individual refrozen ice layers at depth have annealed together to form low-permeability ice slabs (LPISs). These multi-meter thick layers of ice perched over porous firn block percolation to depth and increase the size of the runoff zone. LPISs are a type of "hybrid facies" capable both of running water off the surface, while continuing to slowly compact porous firn at depth. Currently LPISs cover approximately 5% of Greenland's current accumulation zone, but we project them to extend across 15-50% of the accumulation zone by 2100 under different forcing scenarios. These observed changes in the structure and behavior of Greenland's firn have serious implications for future runoff of the ice sheet. Additionally, they challenge modern assumptions which we use to quantify the mass balance of the Greenland ice sheet from airborne and space-borne measurements.

On the Angular Variation of Solar Reflectance of Snow

NASA Technical Reports Server (NTRS)

Chang, A. T. C.; Choudhury, B. J.

1979-01-01

Spectral and integrated solar reflectance of nonhomogeneous snowpacks were derived assuming surface reflection of direct radiation and subsurface multiple scattering. For surface reflection, a bidirectional reflectance distribution function derived for an isotropic Gaussian faceted surface was considered and for subsurface multiple scattering, an approximate solution of the radiative transfer equation was studied. Solar radiation incident on the snowpack was decomposed into direct and atmospherically scattered radiation. Spectral attenuation coefficients of ozone, carbon dioxide, water vapor, aerosol and molecular scattering were included in the calculation of incident solar radiation. Illustrative numerical results were given for a case of North American winter atmospheric conditions. The calculated dependence of spectrally integrated directional reflectance (or albedo) on solar elevation was in qualitative agreement with available observations.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Remote sensing of Earth terrain

NASA Technical Reports Server (NTRS)

Kong, J. A.

1992-01-01

Research findings are summarized for projects dealing with the following: application of theoretical models to active and passive remote sensing of saline ice; radiative transfer theory for polarimetric remote sensing of pine forest; scattering of electromagnetic waves from a dense medium consisting of correlated Mie scatterers with size distribution and applications to dry snow; variance of phase fluctuations of waves propagating through a random medium; theoretical modeling for passive microwave remote sensing of earth terrain; polarimetric signatures of a canopy of dielectric cylinders based on first and second order vector radiative transfer theory; branching model for vegetation; polarimetric passive remote sensing of periodic surfaces; composite volume and surface scattering model; and radar image classification.

Computer simulation of ion beam analysis of laterally inhomogeneous materials

NASA Astrophysics Data System (ADS)

Mayer, M.

2016-03-01

The program STRUCTNRA for the simulation of ion beam analysis charged particle spectra from arbitrary two-dimensional distributions of materials is described. The code is validated by comparison to experimental backscattering data from a silicon grating on tantalum at different orientations and incident angles. Simulated spectra for several types of rough thin layers and a chessboard-like arrangement of materials as example for a multi-phase agglomerate material are presented. Ambiguities between back-scattering spectra from two-dimensional and one-dimensional sample structures are discussed.

MUSIC imaging method for electromagnetic inspection of composite multi-layers

NASA Astrophysics Data System (ADS)

Rodeghiero, Giacomo; Ding, Ping-Ping; Zhong, Yu; Lambert, Marc; Lesselier, Dominique

2015-03-01

A first-order asymptotic formulation of the electric field scattered by a small inclusion (with respect to the wavelength in dielectric regime or to the skin depth in conductive regime) embedded in composite material is given. It is validated by comparison with results obtained using a Method of Moments (MoM). A non-iterative MUltiple SIgnal Classification (MUSIC) imaging method is utilized in the same configuration to locate the position of small defects. The effectiveness of the imaging algorithm is illustrated through some numerical examples.

Raman Monte Carlo simulation for light propagation for tissue with embedded objects

NASA Astrophysics Data System (ADS)

Periyasamy, Vijitha; Jaafar, Humaira Bte; Pramanik, Manojit

2018-02-01

Monte Carlo (MC) stimulation is one of the prominent simulation technique and is rapidly becoming the model of choice to study light-tissue interaction. Monte Carlo simulation for light transport in multi-layered tissue (MCML) is adapted and modelled with different geometry by integrating embedded objects of various shapes (i.e., sphere, cylinder, cuboid and ellipsoid) into the multi-layered structure. These geometries would be useful in providing a realistic tissue structure such as modelling for lymph nodes, tumors, blood vessels, head and other simulation medium. MC simulations were performed on various geometric medium. Simulation of MCML with embedded object (MCML-EO) was improvised for propagation of the photon in the defined medium with Raman scattering. The location of Raman photon generation is recorded. Simulations were experimented on a modelled breast tissue with tumor (spherical and ellipsoidal) and blood vessels (cylindrical). Results were presented in both A-line and B-line scans for embedded objects to determine spatial location where Raman photons were generated. Studies were done for different Raman probabilities.

Southern Quebec in Late Winter

NASA Technical Reports Server (NTRS)

2002-01-01

These images of Canada's Quebec province were acquired by the Multi-angle Imaging SpectroRadiometer on March 4, 2001. The region's forests are a mixture of coniferous and hardwood trees, and 'sugar-shack' festivities are held at this time of year to celebrate the beginning of maple syrup production. The large river visible in the images is the northeast-flowing St. Lawrence. The city of Montreal is located near the lower left corner, and Quebec City, at the upper right, is near the mouth of the partially ice-covered St. Lawrence Seaway.

Both spectral and angular information are retrieved for every scene observed by MISR. The left-hand image was acquired by the instrument's vertical-viewing (nadir) camera, and is a false-color spectral composite from the near-infrared, red, and blue bands. The right-hand image is a false-color angular composite using red band data from the 60-degree backward-viewing, nadir, and 60-degree forward-viewing cameras. In each case, the individual channels of data are displayed as red, green, and blue, respectively.

Much of the ground remains covered or partially covered with snow. Vegetation appears red in the left-hand image because of its high near-infrared brightness. In the multi-angle composite, vegetated areas appear in shades of green because they are brighter at nadir, possibly as a result of an underlying blanket of snow which is more visible from this direction. Enhanced forward scatter from the smooth water surface results in bluer hues, whereas urban areas look somewhat orange, possibly due to the effect of vertical structures which preferentially backscatter sunlight.

The data were acquired during Terra orbit 6441, and cover an area measuring 275 kilometers x 310 kilometers.

MISR was built and is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Office of Earth Science, Washington, DC. The Terra satellite is managed by NASA's Goddard Space Flight Center, Greenbelt, MD. JPL is a division of the California Institute of Technology.

First-principles many-body investigation of δ-doped titanates

NASA Astrophysics Data System (ADS)

Lechermann, Frank; Obermeyer, Michael

2015-03-01

Studying oxide heterostructures provides the possibility for exploring novel composite materials beyond nature's original conception. In this respect, the doping of Mott-insulating distorted-perovskite titanates such as LaTiO3 and GdTiO3 with a single SrO layer gives rise to a very rich correlated electronic structure. A realistic superlattice survey by means of the charge self-consistent combination of density functional theory (DFT) with dynamical mean-field theory (DMFT) reveals layer- and temperature-dependent multi-orbital metal-insulator transitions. In [001] stacking, an orbital-selective metallic layer at the interface dissolves via an orbital-polarized doped-Mott state into an orbital-ordered insulating regime beyond the two conducting TiO2 layers. We find large differences in the scattering behavior within the latter. Breaking the spin symmetry in δ-doped GdTiO3 results in blocks of ferromagnetic itinerant and ferromagnetic Mott-insulating layers which are coupled antiferromagnetically. Support from the DFG-FOR1346 is acknowledged.

Biochemical component identification by plasmonic improved whispering gallery mode optical resonance based sensor

NASA Astrophysics Data System (ADS)

Saetchnikov, Vladimir A.; Tcherniavskaia, Elina A.; Saetchnikov, Anton V.; Schweiger, Gustav; Ostendorf, Andreas

2014-05-01

Experimental data on detection and identification of variety of biochemical agents, such as proteins, microelements, antibiotic of different generation etc. in both single and multi component solutions under varied in wide range concentration analyzed on the light scattering parameters of whispering gallery mode optical resonance based sensor are represented. Multiplexing on parameters and components has been realized using developed fluidic sensor cell with fixed in adhesive layer dielectric microspheres and data processing. Biochemical component identification has been performed by developed network analysis techniques. Developed approach is demonstrated to be applicable both for single agent and for multi component biochemical analysis. Novel technique based on optical resonance on microring structures, plasmon resonance and identification tools has been developed. To improve a sensitivity of microring structures microspheres fixed by adhesive had been treated previously by gold nanoparticle solution. Another technique used thin film gold layers deposited on the substrate below adhesive. Both biomolecule and nanoparticle injections caused considerable changes of optical resonance spectra. Plasmonic gold layers under optimized thickness also improve parameters of optical resonance spectra. Biochemical component identification has been also performed by developed network analysis techniques both for single and for multi component solution. So advantages of plasmon enhancing optical microcavity resonance with multiparameter identification tools is used for development of a new platform for ultra sensitive label-free biomedical sensor.

Snow hydrology in a general circulation model

NASA Technical Reports Server (NTRS)

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

1994-01-01

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

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.

X-ray solution scattering combined with computation characterizing protein folds and multiple conformational states : computation and application.

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

Yang, S.; Park, S.; Makowski, L.

Small angle X-ray scattering (SAXS) is an increasingly powerful technique to characterize the structure of biomolecules in solution. We present a computational method for accurately and efficiently computing the solution scattering curve from a protein with dynamical fluctuations. The method is built upon a coarse-grained (CG) representation of the protein. This CG approach takes advantage of the low-resolution character of solution scattering. It allows rapid determination of the scattering pattern from conformations extracted from CG simulations to obtain scattering characterization of the protein conformational landscapes. Important elements incorporated in the method include an effective residue-based structure factor for each aminomore » acid, an explicit treatment of the hydration layer at the surface of the protein, and an ensemble average of scattering from all accessible conformations to account for macromolecular flexibility. The CG model is calibrated and illustrated to accurately reproduce the experimental scattering curve of Hen egg white lysozyme. We then illustrate the computational method by calculating the solution scattering pattern of several representative protein folds and multiple conformational states. The results suggest that solution scattering data, when combined with a reliable computational method, have great potential for a better structural description of multi-domain complexes in different functional states, and for recognizing structural folds when sequence similarity to a protein of known structure is low. Possible applications of the method are discussed.« less

Analysis of Airborne Radar Altimetry Measurements of the Greenland Ice Sheet

NASA Technical Reports Server (NTRS)

Ferraro, Ellen J.

1994-01-01

This dissertation presents an analysis of airborne altimetry measurements taken over the Greenland ice sheet with the 13.9 GHz Advanced Application Flight Experiment (AAFE) pulse compression radar altimeter. This Ku-band instrument was refurbished in 1990 by the Microwave Remote Sensing Laboratory at the University of Massachusetts to obtain high-resolution altitude measurements and to improve the tracking, speed, storage and display capabilities of the radar. In 1991 and 1993, the AAFE altimeter took part in the NASA Multisensor Airborne Altimetry Experiments over Greenland, along with two NASA laser altimeters. Altitude results from both experiments are presented along with comparisons to the laser altimeter and calibration passes over the Sondrestroem runway in Greenland. Although it is too early to make a conclusion about the growth or decay of the ice sheet, these results show that the instrument is capable of measuring small-scale surface changes to within 14 centimeters. In addition, results from these experiments reveal that the radar is sensitive to the different diagenetic regions of the ice sheet. Return waveforms from the wet- snow, percolation and dry-snow zones show varying effects of both surface scattering and sub-surface or volume scattering. Models of each of the diagenetic regions of Greenland are presented along with parameters such as rms surface roughness, rms surface slope and attenuation coefficient of the snow pack obtained by fitting the models to actual return waveforms.

Analysis of human tissue optical scattering spectra for the purpose of breast cancer diagnostics using multi-layer perceptron

NASA Astrophysics Data System (ADS)

Nuzhny, Anton S.; Shumsky, Sergey A.; Korzhov, Alexey G.; Lyubynskaya, Tatiana E.

2008-02-01

Optical scattering spectra obtained in the clinical trials of breast cancer diagnostic system were analyzed for the purpose to detect in the dataflow the segments corresponding to malignant tissues. Minimal invasive probe with optical fibers inside delivers white light from the source and collects the scattering light while being moved through the tissue. The sampling rate is 100 Hz and each record contains the results of measurements of scattered light intensity at 184 fixed wavelength points. Large amount of information acquired in each procedure, fuzziness in criteria of 'cancer' family membership and data noisiness make neural networks to be an attractive tool for analysis of these data. To define the dividing rule between 'cancer' and 'non-cancer' spectral families a three-layer perceptron was applied. In the process of perceptron learning back propagation method was used to minimize the learning error. Regularization was done using the Bayesian approach. The learning sample was formed by the experts. End-to-end probability calculation throughout the procedure dataset showed reliable detection of the 'cancer' segments. Much attention was paid on the spectra of the tissues with high blood content. Often the reason is vessel injury caused by the penetrating optical probe. But also it can be a dense vessel net surrounding the malignant tumor. To make the division into 'cancer' and 'non-cancer' families for the tissues with high blood content a special perceptron was learnt exceptionally on such spectra.

Performance simulation of an x-ray detector for spectral CT with combined Si and Cd[Zn]Te detection layers.

PubMed

Herrmann, Christoph; Engel, Klaus-Jürgen; Wiegert, Jens

2010-12-21

The most obvious problem in obtaining spectral information with energy-resolving photon counting detectors in clinical computed tomography (CT) is the huge x-ray flux present in conventional CT systems. At high tube voltages (e.g. 140 kVp), despite the beam shaper, this flux can be close to 10⁹ Mcps mm⁻² in the direct beam or in regions behind the object, which are close to the direct beam. Without accepting the drawbacks of truncated reconstruction, i.e. estimating missing direct-beam projection data, a photon-counting energy-resolving detector has to be able to deal with such high count rates. Sub-structuring pixels into sub-pixels is not enough to reduce the count rate per pixel to values that today's direct converting Cd[Zn]Te material can cope with (≤ 10 Mcps in an optimistic view). Below 300 µm pixel pitch, x-ray cross-talk (Compton scatter and K-escape) and the effect of charge diffusion between pixels are problematic. By organising the detector in several different layers, the count rate can be further reduced. However this alone does not limit the count rates to the required level, since the high stopping power of the material becomes a disadvantage in the layered approach: a simple absorption calculation for 300 µm pixel pitch shows that the required layer thickness of below 10 Mcps/pixel for the top layers in the direct beam is significantly below 100 µm. In a horizontal multi-layer detector, such thin layers are very difficult to manufacture due to the brittleness of Cd[Zn]Te. In a vertical configuration (also called edge-on illumination (Ludqvist et al 2001 IEEE Trans. Nucl. Sci. 48 1530-6, Roessl et al 2008 IEEE NSS-MIC-RTSD 2008, Conf. Rec. Talk NM2-3)), bonding of the readout electronics (with pixel pitches below 100 µm) is not straightforward although it has already been done successfully (Pellegrini et al 2004 IEEE NSS MIC 2004 pp 2104-9). Obviously, for the top detector layers, materials with lower stopping power would be advantageous. The possible choices are, however, quite limited, since only 'mature' materials, which operate at room temperature and can be manufactured reliably should reasonably be considered. Since GaAs is still known to cause reliability problems, the simplest choice is Si, however with the drawback of strong Compton scatter which can cause considerable inter-pixel cross-talk. To investigate the potential and the problems of Si in a multi-layer detector, in this paper the combination of top detector layers made of Si with lower layers made of Cd[Zn]Te is studied by using Monte Carlo simulated detector responses. It is found that the inter-pixel cross-talk due to Compton scatter is indeed very high; however, with an appropriate cross-talk correction scheme, which is also described, the negative effects of cross-talk are shown to be removed to a very large extent.

SMRT: A new, modular snow microwave radiative transfer model

NASA Astrophysics Data System (ADS)

Picard, Ghislain; Sandells, Melody; Löwe, Henning; Dumont, Marie; Essery, Richard; Floury, Nicolas; Kontu, Anna; Lemmetyinen, Juha; Maslanka, William; Mätzler, Christian; Morin, Samuel; Wiesmann, Andreas

2017-04-01

Forward models of radiative transfer processes are needed to interpret remote sensing data and derive measurements of snow properties such as snow mass. A key requirement and challenge for microwave emission and scattering models is an accurate description of the snow microstructure. The snow microwave radiative transfer model (SMRT) was designed to cater for potential future active and/or passive satellite missions and developed to improve understanding of how to parameterize snow microstructure. SMRT is implemented in Python and is modular to allow easy intercomparison of different theoretical approaches. Separate modules are included for the snow microstructure model, electromagnetic module, radiative transfer solver, substrate, interface reflectivities, atmosphere and permittivities. An object-oriented approach is used with carefully specified exchanges between modules to allow future extensibility i.e. without constraining the parameter list requirements. This presentation illustrates the capabilities of SMRT. At present, five different snow microstructure models have been implemented, and direct insertion of the autocorrelation function from microtomography data is also foreseen with SMRT. Three electromagnetic modules are currently available. While DMRT-QCA and Rayleigh models need specific microstructure models, the Improved Born Approximation may be used with any microstructure representation. A discrete ordinates approach with stream connection is used to solve the radiative transfer equations, although future inclusion of 6-flux and 2-flux solvers are envisioned. Wrappers have been included to allow existing microwave emission models (MEMLS, HUT, DMRT-QMS) to be run with the same inputs and minimal extra code (2 lines). Comparisons between theoretical approaches will be shown, and evaluation against field experiments in the frequency range 5-150 GHz. SMRT is simple and elegant to use whilst providing a framework for future development within the community.

Estimation of net accumulation rate at a Patagonian glacier by ice core analyses using snow algae

NASA Astrophysics Data System (ADS)

Kohshima, Shiro; Takeuchi, Nozomu; Uetake, Jun; Shiraiwa, Takayuki; Uemura, Ryu; Yoshida, Naohiro; Matoba, Sumito; Godoi, Maria Angelica

2007-10-01

Snow algae in a 45.97-m-long ice core from the Tyndall Glacier (50°59'05″S, 73°31'12″W, 1756 m a.s.l.) in the Southern Patagonian Icefield were examined for potential use in ice core dating and estimation of the net accumulation rate. The core was subjected to visual stratigraphic observation and bulk density measurements in the field, and later to analyses of snow algal biomass, water isotopes ( 18O, D), and major dissolved ions. The ice core contained many algal cells that belonged to two species of snow algae growing in the snow near the surface: Chloromonas sp. and an unknown green algal species. Algal biomass and major dissolved ions (Na +, K +, Mg 2+, Ca 2+, Cl -, SO 42-) exhibited rapid decreases in the upper 3 m, probably owing to melt water elution and/or decomposition of algal cells. However, seasonal cycles were still found for the snow algal biomass, 18O, D-excess, and major ions, although the amplitudes of the cycles decreased with depth. Supposing that the layers with almost no snow algae were the winter layers without the melt water essential to algal growth, we estimated that the net accumulation rate at this location was 12.9 m a - 1 from winter 1998 to winter 1999, and 5.1 m from the beginning of winter to December 1999. These estimates are similar to the values estimated from the peaks of 18O (17.8 m a - 1 from summer 1998 to summer 1999 and 11.0 m from summer to December 1999) and those of D-excess (14.7 m a - 1 from fall 1998 to fall 1999 and 8.6 m a - 1 from fall to December 1999). These values are much higher than those obtained by past ice core studies in Patagonia, but are of the same order of magnitude as those predicted from various observations at ablation areas of Patagonian glaciers.

Quantifying the accuracy of snow water equivalent estimates using broadband radar signal phase

NASA Astrophysics Data System (ADS)

Deeb, E. J.; Marshall, H. P.; Lamie, N. J.; Arcone, S. A.

2014-12-01

Radar wave velocity in dry snow depends solely on density. Consequently, ground-based pulsed systems can be used to accurately measure snow depth and snow water equivalent (SWE) using signal travel-time, along with manual depth-probing for signal velocity calibration. Travel-time measurements require a large bandwidth pulse not possible in airborne/space-borne platforms. In addition, radar backscatter from snow cover is sensitive to grain size and to a lesser extent roughness of layers at current/proposed satellite-based frequencies (~ 8 - 18 GHz), complicating inversion for SWE. Therefore, accurate retrievals of SWE still require local calibration due to this sensitivity to microstructure and layering. Conversely, satellite radar interferometry, which senses the difference in signal phase between acquisitions, has shown a potential relationship with SWE at lower frequencies (~ 1 - 5 GHz) because the phase of the snow-refracted signal is sensitive to depth and dielectric properties of the snowpack, as opposed to its microstructure and stratigraphy. We have constructed a lab-based, experimental test bed to quantify the change in radar phase over a wide range of frequencies for varying depths of dry quartz sand, a material dielectrically similar to dry snow. We use a laboratory grade Vector Network Analyzer (0.01 - 25.6 GHz) and a pair of antennae mounted on a trolley over the test bed to measure amplitude and phase repeatedly/accurately at many frequencies. Using ground-based LiDAR instrumentation, we collect a coordinated high-resolution digital surface model (DSM) of the test bed and subsequent depth surfaces with which to compare the radar record of changes in phase. Our plans to transition this methodology to a field deployment during winter 2014-2015 using precision pan/tilt instrumentation will also be presented, as well as applications to airborne and space-borne platforms toward the estimation of SWE at high spatial resolution (on the order of meters) over large regions (> 100 square kilometers).

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.

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.

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

NASA Astrophysics Data System (ADS)

Zheng, J.; Yackel, J.

2015-12-01

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

A Mass Diffusion Model for Dry Snow Utilizing a Fabric Tensor to Characterize Anisotropy

NASA Astrophysics Data System (ADS)

Shertzer, Richard H.; Adams, Edward E.

2018-03-01

A homogenization algorithm for randomly distributed microstructures is applied to develop a mass diffusion model for dry snow. Homogenization is a multiscale approach linking constituent behavior at the microscopic level—among ice and air—to the macroscopic material—snow. Principles of continuum mechanics at the microscopic scale describe water vapor diffusion across an ice grain's surface to the air-filled pore space. Volume averaging and a localization assumption scale up and down, respectively, between microscopic and macroscopic scales. The model yields a mass diffusivity expression at the macroscopic scale that is, in general, a second-order tensor parameterized by both bulk and microstructural variables. The model predicts a mass diffusivity of water vapor through snow that is less than that through air. Mass diffusivity is expected to decrease linearly with ice volume fraction. Potential anisotropy in snow's mass diffusivity is captured due to the tensor representation. The tensor is built from directional data assigned to specific, idealized microstructural features. Such anisotropy has been observed in the field and laboratories in snow morphologies of interest such as weak layers of depth hoar and near-surface facets.

Fractional Snow Cover Mapping by Artificial Neural Networks and Support Vector Machines

NASA Astrophysics Data System (ADS)

Çiftçi, B. B.; Kuter, S.; Akyürek, Z.; Weber, G.-W.

2017-11-01

Snow is an important land cover whose distribution over space and time plays a significant role in various environmental processes. Hence, snow cover mapping with high accuracy is necessary to have a real understanding for present and future climate, water cycle, and ecological changes. This study aims to investigate and compare the design and use of artificial neural networks (ANNs) and support vector machines (SVMs) algorithms for fractional snow cover (FSC) mapping from satellite data. ANN and SVM models with different model building settings are trained by using Moderate Resolution Imaging Spectroradiometer surface reflectance values of bands 1-7, normalized difference snow index and normalized difference vegetation index as predictor variables. Reference FSC maps are generated from higher spatial resolution Landsat ETM+ binary snow cover maps. Results on the independent test data set indicate that the developed ANN model with hyperbolic tangent transfer function in the output layer and the SVM model with radial basis function kernel produce high FSC mapping accuracies with the corresponding values of R = 0.93 and R = 0.92, respectively.

Polar boundary layer bromine explosion and ozone depletion events in the chemistry-climate model EMAC v2.52: implementation and evaluation of AirSnow algorithm

NASA Astrophysics Data System (ADS)

Falk, Stefanie; Sinnhuber, Björn-Martin

2018-03-01

Ozone depletion events (ODEs) in the polar boundary layer have been observed frequently during springtime. They are related to events of boundary layer enhancement of bromine. Consequently, increased amounts of boundary layer volume mixing ratio (VMR) and vertical column densities (VCDs) of BrO have been observed by in situ observation, ground-based as well as airborne remote sensing, and from satellites. These so-called bromine explosion (BE) events have been discussed serving as a source of tropospheric BrO at high latitudes, which has been underestimated in global models so far. We have implemented a treatment of bromine release and recycling on sea-ice- and snow-covered surfaces in the global chemistry-climate model EMAC (ECHAM/MESSy Atmospheric Chemistry) based on the scheme of Toyota et al. (2011). In this scheme, dry deposition fluxes of HBr, HOBr, and BrNO3 over ice- and snow-covered surfaces are recycled into Br2 fluxes. In addition, dry deposition of O3, dependent on temperature and sunlight, triggers a Br2 release from surfaces associated with first-year sea ice. Many aspects of observed bromine enhancements and associated episodes of near-complete depletion of boundary layer ozone, both in the Arctic and in the Antarctic, are reproduced by this relatively simple approach. We present first results from our global model studies extending over a full annual cycle, including comparisons with Global Ozone Monitoring Experiment (GOME) satellite BrO VCDs and surface ozone observations.

Layer-dependent second-order Raman intensity of Mo S2 and WS e2 : Influence of intervalley scattering

NASA Astrophysics Data System (ADS)

Qian, Qingkai; Zhang, Zhaofu; Chen, Kevin J.

2018-04-01

Acoustic-phonon Raman scattering, as a defect-induced second-order Raman scattering process (with incident photon scattered by one acoustic phonon at the Brillouin-zone edge and the momentum conservation fulfilled by defect scattering), is used as a sensitive tool to study the defects of transition-metal dichalcogenides (TMDs). Moreover, second-order Raman scattering processes are closely related to the valley depolarization of single-layer TMDs in potential valleytronic applications. Here, the layer dependence of second-order Raman intensity of Mo S2 and WS e2 is studied. The electronic band structures of Mo S2 and WS e2 are modified by the layer thicknesses; hence, the resonance conditions for both first-order and second-order Raman scattering processes are tuned. In contrast to the first-order Raman scattering, second-order Raman scattering of Mo S2 and WS e2 involves additional intervalley scattering of electrons by phonons with large momenta. As a result, the electron states that contribute most to the second-order Raman intensity are different from that to first-order process. A weaker layer-tuned resonance enhancement of second-order Raman intensity is observed for both Mo S2 and WS e2 . Specifically, when the incident laser has photon energy close to the optical band gap and the Raman spectra are normalized by the first-order Raman peaks, single-layer Mo S2 or WS e2 has the strongest second-order Raman intensity. This layer-dependent second-order Raman intensity can be further utilized as an indicator to identify the layer number of Mo S2 and WS e2 .

Brittle Fracture Mechanics of Snow : In Situ Testing and Distinct Element Modeling

NASA Astrophysics Data System (ADS)

Faillettaz, J.; Daudon, D.; Louchet, F.

A snow slab avalanche release usually results from the rupture of the snow cover at the interface between an upper layer (slab) and an underlying substrate. Amazingly, the models proposed so far to predict this kind of rupture were only based on continuum mechanics, as they did not take into account the existing cracks or cohesion defects at the interface between the two layers, and their possible unstable propagation that eventually triggers the avalanche. This is why the present work, essentially devoted to human triggered avalanches, is based instead on Griffith's fracture approach, widely used in modelling brittle fracture of materials. The possible rupture scenario involves a propagation in a shear mode of a "basal crack" nucleated and gradually grown at the interface by the skier's weight, followed by a mode I opening and propagation of a "crown crack" at the top of the sheared zone. Different avalanche sizes are predicted according whether the basal crack propagation reaches or not the Griffith's instabil- ity size before crown crack opening (Louchet 2000). Accurate predictions therefore require a precise knowledge of snow toughness values in both modes. A theoretical estimation of toughness considering snow as an ice foam was proposed by Kirchner and Michot (2000), but the question of whether these results may be extended to an assembly of sintered grains is still open. A mode I toughness measurement of snow was also published for the first time by Kirchner and Michot on samples gathered in the Vosges range. In the present work, we developed an experimental set similar to Michot's, in order to measure mode I toughness: a vertical crack of increasing size is gradually machined from the top surface in an horizontal snow beam until failure takes place under its own weight. The toughness value is computed from the snow weight and the crack length at the onset of rapid crack propagation. A similar device was designed for mode II testing, but is still under development. The experimental cam- paign carried out in the Alps during the 2000-2001 winter on homogeneous sintered snow with a density of 200 kg/m3 (typical of a snow slab) gave results of the same or- der of magnitude as Michot's. A numerical modeling of these toughness experiments was performed using a distinct element code, considering snow as a cohesive granu- lar material. Both crack propagation and rupture patterns are in close agreement with experiments. References: Kirchner, Michot, Suzuki 2000 Fracture thoughness of snow in tension 1 Philisophical Magazine A, vol 80,N5, p1265-1272. Louchet 2001,A transition in dry snow slab avalanche triggering modes, Annales de glaciologie, vol 32,Symphosium on Snow, Avalanches and Impact of the Frest Cover, Innsbruck,Austria,22-26 may 2000, p2285-289 2

ATMOSPHERIC DISPERSION IN THE ARCTIC: WINTERTIME BOUNDARY-LAYER MEASUREMENTS

EPA Science Inventory

The wintertime arctic atmospheric boundary layer was investigated with micro-meteorological and SF6 tracer measurements collected in Prudhoe Bay, AK. he flat, snow-covered tundra surface at this site generates a very small (0.03 cm) surface roughness. he relatively warm maritime ...

Application of SNODAS and hydrologic models to enhance entropy-based snow monitoring network design

NASA Astrophysics Data System (ADS)

Keum, Jongho; Coulibaly, Paulin; Razavi, Tara; Tapsoba, Dominique; Gobena, Adam; Weber, Frank; Pietroniro, Alain

2018-06-01

Snow has a unique characteristic in the water cycle, that is, snow falls during the entire winter season, but the discharge from snowmelt is typically delayed until the melting period and occurs in a relatively short period. Therefore, reliable observations from an optimal snow monitoring network are necessary for an efficient management of snowmelt water for flood prevention and hydropower generation. The Dual Entropy and Multiobjective Optimization is applied to design snow monitoring networks in La Grande River Basin in Québec and Columbia River Basin in British Columbia. While the networks are optimized to have the maximum amount of information with minimum redundancy based on entropy concepts, this study extends the traditional entropy applications to the hydrometric network design by introducing several improvements. First, several data quantization cases and their effects on the snow network design problems were explored. Second, the applicability the Snow Data Assimilation System (SNODAS) products as synthetic datasets of potential stations was demonstrated in the design of the snow monitoring network of the Columbia River Basin. Third, beyond finding the Pareto-optimal networks from the entropy with multi-objective optimization, the networks obtained for La Grande River Basin were further evaluated by applying three hydrologic models. The calibrated hydrologic models simulated discharges using the updated snow water equivalent data from the Pareto-optimal networks. Then, the model performances for high flows were compared to determine the best optimal network for enhanced spring runoff forecasting.

Contamination of agricultural lands by polycyclic aromatic hydrocarbons (Tver region, Russia)

NASA Astrophysics Data System (ADS)

Zhidkin, Andrey; Koshovskii, Timur; Gennadiev, Alexander

2016-04-01

It is important to study sources and concentrations of polycyclic aromatic hydrocarbons (PAHs) in the agriculture soils within areas without intensive contaminations. Our studied object was soil and snow cover in the taiga zone (Tver region, Russia). A total of 52 surface (0-30 cm) and 31 subsurface (30-50 cm) soil samples, and 13 snow samples were collected in 35 soil pits, located in forest, crop and layland soils. Studied concentrations of the following 11 individual compounds: two-ring compounds (diphenyl and naphthalene homologues); three-ring compounds (fluorene, phenanthrene, anthracene); four-ring compounds (chrysene, pyrene, tetraphene); five-ring compounds (perylene, benzo[a]pyrene); and six-ring compounds (benzo[ghi]perylene). Analyses made by specrtofluorometry method at the temperature of liquid nitrogen. The total concentrations of all PAHs in soil samples ranged from 9 to 770 ng*g-1 with a median of 96 ng*g-1. The sum of high molecular weight PAHs was significantly lower than the sum of low molecular weight PAHs in the studied soils. The phenanthrene concentration was highest and ranged from 1.2 to 720 ng*g-1 (medium 72 ng*g-1). Compared PAHs reserves in snow cover (μg*m-2) with the reserves in topsoil layer (μg*m-2 in the upper 30 cm). Low molecular weight PAHs (fluorene, phenanthrene, diphenyl, naphthalene) reserves in snow was less than 20% from the reserves in the soil surface layer. High molecular weight PAHs (benzo[a]pyrene, chrysene, perylene, pyrene and tetraphene) reserves in snow was about 50-70% from the reserves in soil surface layer. High molecular weight PAHs (benzo[ghi]perylene and anthracene) reserves in snow was more than in topsoil. PAHs vertical distribution in soil profiles was statistically examined. The total concentration of all PAHs decreased with depth in all studied forest soils. In the arable soils was no significant trend in domination of PAHs total concentrations in the plowing and subsoil layers. The ratio of topsoil to subsoil concentrations of PAHs is different for differ congeners. Contents of phenanthrene and fluorene predominantly increase with the depth. Content of high molecular weight PAHs (benzo[a]pyrene, anthracene, tetraphene, perylene and pyrene) predominantly decreased with the depth. Other PAHs congeners have indistinct profile distributions in studied pits. Based on studied results PAHs divided to associations with different concentrations, sources and vertical distribution in soils: a) phenanthrene and fluorine; b) naphthalene, diphenyl; c) pyrene, benzo(a)pyrene, tetraphene, perylene, chrysene; d) anthracene and benzo(ghi)perylene. Research is funded by Russian Science Foundation (Project 14-27-00083).

Improving scattering layer through mixture of nanoporous spheres and nanoparticles in ZnO-based dye-sensitized solar cells.

PubMed

Kim, Chohui; Choi, Hongsik; Kim, Jae Ik; Lee, Sangheon; Kim, Jinhyun; Lee, Woojin; Hwang, Taehyun; Kang, Suji; Moon, Taeho; Park, Byungwoo

2014-01-01

A scattering layer is utilized by mixing nanoporous spheres and nanoparticles in ZnO-based dye-sensitized solar cells. Hundred-nanometer-sized ZnO spheres consisting of approximately 35-nm-sized nanoparticles provide not only effective light scattering but also a large surface area. Furthermore, ZnO nanoparticles are added to the scattering layer to facilitate charge transport and increase the surface area as filling up large voids. The mixed scattering layer of nanoparticles and nanoporous spheres on top of the nanoparticle-based electrode (bilayer geometry) improves solar cell efficiency by enhancing both the short-circuit current (J sc) and fill factor (FF), compared to the layer consisting of only nanoparticles or nanoporous spheres.

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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