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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

(abstract) A Polarimetric Model for Effects of Brine Infiltrated Snow Cover and Frost Flowers on Sea Ice Backscatter

A polarimetric scattering model is developed to study effects of snow cover and frost flowers with brine infiltration on thin sea ice. Leads containing thin sea ice in the Artic icepack are important to heat exchange with the atmosphere and salt flux into the upper ocean. Surface characteristics of thin sea ice in leads are dominated by the formation of frost flowers with high salinity. In many cases, the thin sea ice layer is covered by snow, which wicks up brine from sea ice due to capillary force. Snow and frost flowers have a significant impact on polarimetric signatures of thin ice, which needs to be studied for accessing the retrieval of geophysical parameters such as ice thickness. Frost flowers or snow layer is modeled with a heterogeneous mixture consisting of randomly oriented ellipsoids and brine infiltration in an air background. Ice crystals are characterized with three different axial lengths to depict the nonspherical shape. Under the covering multispecies medium, the columinar sea-ice layer is an inhomogeneous anisotropic medium composed of ellipsoidal brine inclusions preferentially oriented in the vertical direction in an ice background. The underlying medium is homogeneous sea water. This configuration is described with layered inhomogeneous media containing multiple species of scatterers. The species are allowed to have different size, shape, and permittivity. The strong permittivity fluctuation theory is extended to account for the multispecies in the derivation of effective permittivities with distributions of scatterer orientations characterized by Eulerian rotation angles. Polarimetric backscattering coefficients are obtained consistently with the same physical description used in the effective permittivity calculation. The mulitspecies model allows the inclusion of high-permittivity species to study effects of brine infiltrated snow cover and frost flowers on thin ice. The results suggest that the frost cover with a rough interface significantly increases the backscatter from thin saline ice and the polarimetric signature becomes closer to the isotropic characteristics. The snow cover also modifies polarimetric signatures of thin sea ice depending on the snow mixture and the interface condition.

thin sea ice radar backscatter frost flowers snow ↗
NASA NTRS1975

An operational application of satellite snow cover observations, northwest United States

LANDSAT-1 imagery showing extent of snow cover was collected and is examined for the 1973 and 1974 snowmelt seasons for three Columbia River Basins. Snowlines were mapped and the aerial snow cover was determined using satellite data. Satellite snow mapping products were compared products from conventional information sources (computer programming and aerial photography was used). Available satellite data were successfully analyzed by radiance thresholding to determine snowlines and the attendant snow-covered area. Basin outline masks, contour elevation masks, and grid overlays were utilized as satellite data interpretation aids. Verification of the LANDSAT-1 data was generally good although there were exceptions. A major problem was lack of adequate cloud-free satellite imagery of high resolution and determining snowlines in forested areas.

Dillard, J. P.↗
DOE OSTI2025

Ground surface temperature derived Snow Cover Properties, Seward Peninsula, Alaska, 2019-2023

Snow-ground interface temperatures have been collected at the Teller mile marker 27 and Kougarok mile marker 64 field sites on the Seward Peninsula, Alaska from 2019 through 2023 (with data missing from Fall 2020 through Summer 2021 due to COVID). Temperatures were measured using iButton Link DS1921G-F5# Thermochron miniature temperature sensors and Tinytag TGP-4017 internal sensors deployed across the Kougarok 64 and Teller 27 field sites. These sensors are a cost-efficient way to collect snow-ground interface temperatures at a high spatial resolution, and when paired with air temperature data these measurements can provide insight into fine-scale variability in snowpack characteristics across the study sites. From this data, snow process metrics were calculated at each sensor location based on the methods outlined in Staub and Delaloye, 2017. Metrics are calculated daily for each sensor as well as over the entire season. These metrics include ground surface temperature (°C), the number of days under snow cover (number of days), the insulation effect of snow (unitless), the length of the transitional snow periods (number of days), as well as intermediaries such as temperature variability. Calculating these snow processes relies on the assumption that when snow covers a temperature sensor, it is buffered from diurnal fluctuations in air temperature by the insulating snow layer. More information on the calculated metrics can be found in the User Guide of this dataset, as well as in Staub and Delaloye’s 2017 publication Using Near-Surface Ground Temperature Data to Derive Snow Insulation and Melt Indices for Mountain Permafrost Applications. This dataset includes one daily and one seasonal *.csv file of metrics for every year of data, a daily and a seasonal *.csv data dictionary, and one User Guide document (*.pdf) describing data collection and processing.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1999

Using Spaceborne Ku-Band Scatterometer for Global Snow Cover Monitoring

We demonstrate for the first time the utility of spaceborne Ku-band scatterometer for global snow cover monitoring. Satellite radar data were collected over the globe by the NASA Scatterometer (NSCAT) operated at 14 GHz on board the Japanese ADEOS spacecraft from September 1996 to June 1997, spanning the 1997 seasonal snow season. First, we present backscatter signature of dry and wet snow to facilitate the interpretation of NSCAT backscatter evolution over snow cover regions. Surface field experiments indicated that dry snow backscatter at Ku band is approximately 40 times stronger than that at C band. Thus, Ku-band scatterometer measurements are sensitive to snow cover, which is typically transparent to C-band scatterometer returns. Furthermore, Ku-band backscatter does not saturate for most of natural snow depths as compared to radar responses at 19 GHz and 37 GHz or higher frequencies which have more limited penetration depths into snow. Ku-band backscatter is also sensitive to wetness in snow, which is appropriate to detect early snow melt conditions. Using the snow backscatter characteristics, we investigate NSCAT backscatter evolution over global snow cover regions throughout the 1997 snow season. The results reveal detail delineations between different regional snow areas. We show the correlation of these delineations with the boundaries of different global snow classes defined by the U.S. Army Cold Regions Research and Engineering Laboratory snow classification system. Using in-situ snow depth data from the U.S. National Climatic Data Center, we show that Ku-band backscatter corresponds very well to the trend of snow melt while snow mapping products (U.S. Climate Prediction Center gridded snow charts) from visible sensors does not reflect the fast snow melt trend. To illustrate the practical application of global snow monitoring with spaceborne Ku-band scatterometer, we present NSCAT backscatter response corresponding to the snow event leading to the 1997 Flood of the Century over the U.S. Northern plains and the Canadian prarie region, which caused loss of lives and several billion dollars in flood related damages and cleanup costs. Finally, we show that the fixed incidence configuration of Seawinds scatterometers, to be launched on QuickSCAT and on ADEOS-2 in the near future, is better for snow monitoring and then discuss the use of future high-resolution scatterometers for global snow mapping.

Nghiem, S. V.↗
DOE OSTI2022

Estimating snow cover from high-resolution satellite imagery by thresholding blue wavelengths

We report the extent and duration of snow cover, a critical component of the hydrologic cycle and the global climate system, is expected to shift dramatically under climate change. Therefore, developing high-resolution assessments of snow cover change is crucial for estimating the impact of changing snow cover on watershed and ecosystems processes in cold regions. Remote sensing tools provide a powerful method for mapping snow-covered area (SCA) across a landscape. The most common method for estimating SCA utilizes the normalized difference snow index (NDSI), which relies on spectral measurements in the shortwave-infrared wavelengths (SWIR). NDSI can effectively estimate catchment- to regional-scale SCA, but it cannot be used to assess fine-scale SCA because of current limitations on the spatial resolution of satellite-derived SWIR measurements. Here, we map SCA using a threshold of blue wavelengths and high-resolution satellite imagery. The thresholding method, which we call the Blue Snow Threshold algorithm (BST), has previously been used with digital camera imagery. We refine and automate the algorithm for use with cloud-free high-resolution satellite imagery and find that the BST can be used to assess fine-scale SCA. For validation, we compared BST-derived estimates of SCA to a) airborne lidar surveys, b) Landsat fractional SCA, and c) snow disappearance dates from Snow Telemetry (SNOTEL) stations. When compared to airborne lidar surveys of SCA, the BST predicted SCA had a range of F-scores between 0.81 and 0.94 in four study areas in California and Colorado. We also found general agreement between SCA and snow disappearance at multiple SNOTEL sites across the western United States. Given the relatively recent availability of high-resolution satellite imagery with spectral measurements in the visible wavelengths but lacking in SWIR, the BST offers a reliable and easy-to-apply tool for examining fine-scale snow-related processes.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2001

MODIS Snow-Cover Products

On December 18, 1999, the Terra satellite was launched with a complement of five instruments including the Moderate Resolution Imaging Spectroradiometer (MODIS). Many geophysical products are derived from MODIS data including global snow-cover products. These products have been available through the National Snow and Ice Data Center (NSIDC) Distributed Active Archive Center (DAAC) since September 13, 2000. MODIS snow-cover products represent potential improvement to the currently available operation products mainly because the MODIS products are global and 500-m resolution, and have the capability to separate most snow and clouds. Also the snow-mapping algorithms are automated which means that a consistent data set is generated for long-term climates studies that require snow-cover information. Extensive quality assurance (QA) information is stored with the product. The snow product suite starts with a 500-m resolution swath snow-cover map which is gridded to the Integerized Sinusoidal Grid to produce daily and eight-day composite tile products. The sequence then proceeds to a climate-modeling grid product at 5-km spatial resolution, with both daily and eight-day composite products. A case study from March 6, 2000, involving MODIS data and field and aircraft measurements, is presented. Near-term enhancements include daily snow albedo and fractional snow cover.

Hall, Dorothy K.↗
NASA NTRS2001

Assessment of the Relative Accuracy of Hemispheric-Scale Snow-Cover Maps

There are several hemispheric-scale satellite-derived snow-cover maps available, but none has been fully validated. For the period October 23 - December 25, 2000, we compare snow maps of North America derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the National Oceanic and Atmospheric Administration (NOAA) National Operational Hydrologic Remote Sensing Center (NOHRSC), which both rely on satellite data from the visible and near-infrared parts of the spectrum; we also compare MODIS and Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I) passive-microwave snow maps. The maps derived from visible and near-infrared data are more accurate for mapping snow cover than are the passive-microwave-derived maps, however discrepancies exist as to the location and extent of the snow cover among those maps. The large (approx. 30 km) footprint of the SSM/I data and the difficulty in distinguishing wet and shallow snow from wet or snow-free ground, reveal differences up to 5.32 million sq km in the amount of snow mapped using MODIS versus SSM/I data. Algorithms that utilize both visible and passive-microwave data, which would take advantage of the all-weather mapping ability of the passive-microwave data, will be refined following the launch of the Advanced Microwave Scanning Radiometer (AMSR) in the fall of 2001.

Hall, Dorothy K.↗
NASA NTRS1994

Changes of snow cover, temperature, and radiative heat balance over the Northern Hemisphere

Contemporary large-scale changes in satellite-derived snow cover were examined over the Northern Hemisphere extratropical land (NEL) areas. These areas encompass 55% of the land in the Northern Hemisphere. Snow cover (S) transient regions, the 'centers of action' relative to interannual variations of snow cover, were identified for the years 1972-1992. During these years a global retreat in snow cover extent (SE) occurred in the second half of the hydrologic year (April-September). Mean annual SE has decreased by 10% (2.3 x 10(exp 6) sq km). Negative trends account for one-third to one-half of the interannual continental variance of SE. The historical influence of S on the planetary albedo and outgoing longwave radiation (OLR) is investigated. The mean annual response of the S feedback on the radiative balance (RB) is negative and suggests a largescale heat redistribution. During autumn and early winter (up to January), however, the feedback of S on the planetary RB may be positive. Only by February does the cooling effect of S (due to albedo increase) dominate the planetary warming due to reduced OLR over the S. Despite a wintertime maximum in SE, the feedback in spring has the greatest magnitude. The global retreat of spring SE should lead to a positive feedback on temperature. Based on observed records of S, changes in RB are calculated that parallel an observed increase of spring temperature during the past 20 years. The results provide a partial explanation of the significant increase in spring surface air temperature observed over the land areas of the Northern Hemisphere during the past century. The mean SE in years with an El Nino and La Nina were also evaluated. El Nino events are generally accompanied by increased SE over the NEL during the first half of the hydrological year. In the second half of the hydrologic year (spring and summer), the El Nino events are accompanied by a global retreat of SE.

Groisman, Pavel YA.↗
NASA NTRS1980

The seasonal cycle of snow cover, sea ice and surface albedo

The paper examines satellite data used to construct mean snow cover caps for the Northern Hemisphere. The zonally averaged snow cover from these maps is used to calculate the seasonal cycle of zonally averaged surface albedo. The effects of meltwater on the surface, solar zenith angle, and cloudiness are parameterized and included in the calculations of snow and ice albedo. The data allows a calculation of surface albedo for any land or ocean 10 deg latitude band as a function of surface temperature ice and snow cover; the correct determination of the ice boundary is more important than the snow boundary for accurately simulating the ice and snow albedo feedback.

Robock, A.↗
NASA NTRS1999

Intercomparison of Satellite-Derived Snow-Cover Maps

In anticipation of the launch of the Earth Observing System (EOS) Terra, and the PM-1 spacecraft in 1999 and 2000, respectively, efforts are ongoing to determine errors of satellite-derived snow-cover maps. EOS Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer-E (AMSR-E) snow-cover products will be produced. For this study we compare snow maps covering the same study area acquired from different sensors using different snow- mapping algorithms. Four locations are studied: 1) southern Saskatchewan; 2) a part of New England (New Hampshire, Vermont and Massachusetts) and eastern New York; 3) central Idaho and western Montana; and 4) parts of North and South Dakota. Snow maps were produced using a prototype MODIS snow-mapping algorithm used on Landsat Thematic Mapper (TM) scenes of each study area at 30-m and when the TM data were degraded to 1 -km resolution. National Operational Hydrologic Remote Sensing Center (NOHRSC) 1 -km resolution snow maps were also used, as were snow maps derived from 1/2 deg. x 1/2 deg. resolution Special Sensor Microwave Imager (SSM/1) data. A land-cover map derived from the International Geosphere-Biosphere Program (IGBP) land-cover map of North America was also registered to the scenes. The TM, NOHRSC and SSM/I snow maps, and land-cover maps were compared digitally. In most cases, TM-derived maps show less snow cover than the NOHRSC and SSM/I maps because areas of incomplete snow cover in forests (e.g., tree canopies, branches and trunks) are seen in the TM data, but not in the coarser-resolution maps. The snow maps generally agree with respect to the spatial variability of the snow cover. The 30-m resolution TM data provide the most accurate snow maps, and are thus used as the baseline for comparison with the other maps. Comparisons show that the percent change in amount of snow cover relative to the 3 0-m resolution TM maps is lowest using the TM I -km resolution maps, ranging from 0 to 40%. The highest percent change (less than 100%) is found in the New England study area, probably due to the presence of patchy snow cover. A scene with patchy snow cover is more difficult to map accurately than is a scene with a well-defined snowline such as is found on the North and South Dakota scene where the percent change ranged from 0 to 40%. There are also some important differences in the amount of snow mapped using the two different SSM/I algorithms because they utilize different channels.

Hall, Dorothy K.↗
NASA NTRS1985

Evaluation of the satellite derived snow cover area - Runoff forecasting models for the inaccessible basins of western Himalayas

In this study, the existing seasonal snow cover area runoff forecasting models of the Indus, Kabul, Sutlej and Chenab basins were evaluated with the concurrent flow correlation model for the period 1975-79. In all the basins under study, correlation of concurrent flow model explained the variability in flow better than by the snow cover area runoff models. Actually, the concurrent flow correlation model explained more than 90 percent of the variability in the flow of these rivers. Compared to this model, the snow cover area runoff models explained less of the variability in flow. In the Himalayan river basins under study and at least for the period under observation, the concurrent flow correlation model provided a set of results with which to compare the estimates from the snow cover area runoff models.

Dey, B.↗
NASA NTRS1988

Modelling changes in the dielectric and scattering properties of young snow-covered sea ice at GHz frequencies

Observations of the physical properties of the snow cover and underlying young fast ice in Resolute Passage, Canada, were made during the winter of 1982. Detailed measurements of snow density and ice and snow temperatures, salinities, and brine volumes were made over a period of 46 d, beginning when the ice was 0.4 m thick and about 9 d old. The recorded values are used in a theoretical mixture model to predict the dielectric properties of the snow cover over the microwave frequency range. The results of this analysis are then used to investigate the effects of the snow properties on the radar backscatter signatures of young sea ice. The results show that backscatter is a function of the incidence angle and can change significantly over short periods of time during the early evolutionary phase of ice and snow-cover development. This has important consequences for the identification of young ice forms from SAR or SLAR images.

Drinkwater, Mark R.↗
NASA NTRS2011

Snow Cover, Snowmelt Timing and Stream Power in the Wind River Range, Wyoming

Earlier onset of springtime weather, including earlier snowmelt, has been documented in the western United States over at least the last 50 years. Because the majority (is greater than 70%) of the water supply in the western U.S. comes from snowmelt, analysis of the declining spring snowpack (and shrinking glaciers) has important implications for the management of streamflow. The amount of water in a snowpack influences stream discharge which can also influence erosion and sediment transport by changing stream power, or the rate at which a stream can do work, such as move sediment and erode the stream bed. The focus of this work is the Wind River Range (WRR) in west-central Wyoming. Ten years of Moderate-Resolution Imaging Spectroradiometer (MODIS) snow-cover, cloud-gap-filled (CGF) map products and 30 years of discharge and meteorological station data are studied. Streamflow data from streams in WRR drainage basins show lower annual discharge and earlier snowmelt in the decade of the 2000s than in the previous three decades, though no trend of either lower streamflow or earlier snowmelt was observed within the decade of the 2000s. Results show a statistically-significant trend at the 95% confidence level (or higher) of increasing weekly maximum air temperature (for three out of the five meteorological stations studied) in the decade of the 1970s, and also for the 40-year study period as a whole. The extent of snow-cover (percent of basin covered) derived from the lowest elevation zone (2500-3000 m) of the WRR, using MODIS CGF snow-cover maps, is strongly correlated with maximum monthly discharge on 30 April, where Spearman's Rank correlation, rs,=0.89 for the decade of the 2000s. We also investigated stream power for Bull Lake Creek above Bull Lake; and found a trend (significant at the 90% confidence level) toward reduced stream power from 1970 to 2009. Observed changes in streamflow and stream power may be related to increasing weekly maximum air temperature measured during the 40-year study period, possibly contributing to a reduction in snow cover. In addition, the strong relationship between percent of basin that was snow covered, and maximum monthly streamflow indicates that MODIS snow-cover maps are useful for predicting streamflow, and can be used to improve management of water resources in the drought-prone western United States.

MODIS↗
NASA NTRS1985

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

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.

Gurtovaya, Y. Y.↗
NASA NTRS1990

Preliminary analysis of measured sound propagation over various seasonal snow covers

Measurements of acoustic pulse propagation in the 5 to 500-Hz frequency band were conducted under various snow cover conditions during the 1989 to 1990 winter in New Hampshire. The objective was to determine the effect of snow cover thickness and other snow properties on the absorption of acoustic pulses. Blank pistol shots were used as the source of the acoustic waves, and geophones and microphones in an 80 m-long linear array served as receivers. Snow thicknesses ranged from 0.05 to 0.35 m, and densities varied from 100 to 350 kg m(sup -3) during the 10 separate measurement days. Preliminary analysis indicates that the peak pulse amplitude decayed in proportion to approx. gamma (sup -1.7) for most conditions and that the acoustic-to-seismic ratios varied from about 4 to 15 x 10(exp -6) m s(sup -1) Pa(sup -1). Theoretical waveforms were calculated for propagation in a homogeneous atmosphere using Attenborough's model of ground impedance. An automatic fitting procedure for the normalized experimental and theoretical waveforms was used to determine the effective flow resistivity of the snow covers, and gave values of 10 to 35 kN s m(sup -4), in agreement with earlier results.

Albert, Donald G.↗
NASA NTRS1981

Applications systems verification and transfer project. Volume 2: Operational applications of satellite snow-cover observations and data-collection systems in the Arizona test site

Ground surveys and aerial observations were used to monitor rapidly changing moisture conditions in the Salt-Verde watershed. Repetitive satellite snow cover observations greatly reduce the necessity for routine aerial snow reconnaissance flights over the mountains. High resolution, multispectral imagery provided by LANDSAT satellite series enabled rapid and accurate mapping of snow-cover distributions for small- to medium-sized subwatersheds; however, the imagery provided only one observation every 9 days of about a third of the watershed. Low resolution imagery acquired by the ITOSa dn SMS/GOES meteorological satellite series provides the daily synoptic observation necessary to monitor the rapid changes in snow-covered area in the entire watershed. Short term runoff volumes can be predicted from daily sequential snow cover observations.

Schumann, H. H.↗
NASA NTRS1980

Microwave signatures of the natural snow cover at Weissfluhjoch

The natural snow cover on a high altitude alphine test site was monitored with a multi-frequency radiometer for more than three years. Some measurements were also made with a 10.5 GHz scatterometer. The microwave observations are supported by a large set of ground truth data. From year to year a wide variation in the development of the snowpack above and below average was observed. Typical microwave data are presented for the different snow conditions in view of the applicability as signatures for remote sensing.

Hofer, R.↗
NASA NTRS2016

Changing Arctic Snow Cover: A Review of Recent Developments and Assessment of Future Needs for Observations, Modelling, and Impacts

Snow is a critically important and rapidly changing feature of the Arctic. However, snow-cover and snowpack conditions change through time pose challenges for measuring and prediction of snow. Plausible scenarios of how Arctic snow cover will respond to changing Arctic climate are important for impact assessments and adaptation strategies. Although much progress has been made in understanding and predicting snow-cover changes and their multiple consequences, many uncertainties remain. In this paper, we review advances in snow monitoring and modelling, and the impact of snow changes on ecosystems and society in Arctic regions. Interdisciplinary activities are required to resolve the current limitations on measuring and modelling snow characteristics through the cold season and at different spatial scales to assure human well-being, economic stability, and improve the ability to predict manage and adapt to natural hazards in the Arctic region.

climate change↗