A 3 Gc/s scale model of a submerged VLF ANTENNA using lossy ceramic powder.
Scale model of submerged VLF antenna using lossy ceramic powder to model ice and snow for submarine communication, geophysics, etc
DIELECTRIC CONSTANT↗
SEARCH · Engineering Papers
Results for “Snow model”
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Recent advances in remote sensing; Proceedings of the First International Geoscience and Remote Sensing Symposium, Washington, DC, June 8-10, 1981
The state of the art in remote sensing of the earth and the planets was discussed in terms of sensor performance, signal processing, and data interpretation. Particular attention was given to lidar for characterizing atmospheric particulates, the modulation of short waves by long ocean gravity waves, and runoff modeling for snow-covered areas. The use of NOAA-6 spacecraft AVHRR data to explore hydrologic land surface features, the effects of soil moisture and vegetation canopies on microwave and thermal microwave emissions, and regional scale evapotranspiration rate determination through satellite IR data are examined. A Shuttle experiment to demonstrate high accuracy global time and frequency transfer is described, along with features of the proposed Gravsat, radar image processing for rock-type discrimination, and passive microwave sensing of temperature and salinity in coastal zones.
Mcintosh, R.↗
Retrieval of Dry Snow Parameters from Radiometric Data Using a Dense Medium Model and Genetic Algorithms
In this paper, GA-based techniques are used to invert the equations of an electromagnetic model based on Dense Medium Radiative Transfer Theory (DMRT) under the Quasi Crystalline Approximation with Coherent Potential to retrieve snow depth, mean grain size and fractional volume from microwave brightness temperatures. The technique is initially tested on both noisy and not-noisy simulated data. During this phase, different configurations of genetic algorithm parameters are considered to quantify how their change can affect the algorithm performance. A configuration of GA parameters is then selected and the algorithm is applied to experimental data acquired during the NASA Cold Land Process Experiment. Snow parameters retrieved with the GA-DMRT technique are then compared with snow parameters measured on field.
Tedesco, Marco↗
Model estimates of dissolved organic carbon, runoff, snowmelt, and snow water equivalent from 1981-2010 across the western Arctic
This dataset contains estimates of dissolved organic carbon (DOC) yield (mg C m-2), runoff (mm day-1), snow water equivalent (SWE, mm day-1), and snowmelt (mm day-1) from a simulation of the Permafrost Water Balance Model (PWBM v4). The simulation effectively quantifies snowpack accumulation and melt, runoff, and DOC leaching, and broadly capture the seasonal cycle in DOC concentration and mass loadings. Daily air temperature, precipitation, and wind speed data from the Modern-Era Retrospective Analysis for Research and Applications (MERRA) were used for meteorological forcings. The model outputs are organized by grid and day of the month in gzipped ASCII text files contained within each archived ZIP file. No special software is required to work with these data. The basin and domain information files are also ASCII text. The gridded estimates are most useful for analyses of the spatial and temporal variations in terrestrial hydrology and leachate DOC concentrations and loadings across parts of the western Arctic. A manuscript describing the data and associated analysis has been accepted for publication in Journal of Geophysical Research - Biogeosciences (Rawlins et al., 2021).
54 ENVIRONMENTAL SCIENCES↗
A Microwave Radiance Assimilation Study for a Tundra Snowpack
Recent studies have begun exploring the assimilation of microwave radiances for the modeling and retrieval of snow properties. At a point scale, and for short durations (i week), radiance assimilation (RA) results are encouraging. However, in order to determine how practical RA might be for snow retrievals when applied over longer durations, larger spatial scales, and/or different snow types, we must expand the scope of the tests. In this paper we use coincident microwave radiance measurements and station data from a tundra site on the North Slope of Alaska. The field data are from the 3rd Radio-brightness Energy Balance Experiment (REBEX-3) carried out in 1994-95 by the University of Michigan. This dataset will provide a test of RA over months instead of one week, and for a very different type of snow than previous snow RA studies. We will address the following questions: flow well can a snowpack physical model (SM), forced with local weather, match measured conditions for a tundra snowpack?; How well can a microwave emission model, driven by the snowpack model, match measured microwave brightnesses for a tundra snowpack?; How well does RA increase or decrease the fidelity of estimates of snow depth and temperatures for a tundra snowpack?
Kim, Edward↗
Microwave scattering models and basic experiments
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.
Fung, Adrian K.↗
Participation in the GISS EOS Proposal
To model the mass balance of the Greenland and Antarctic ice-sheets, Research Assistant Veronique Bugnion developed a snowpack model which embodies a physically based approach to modeling the temperature and density distribution of a snow, firn, and ice mixture. The snowpack model performed satisfactorily in capturing the surface energy balance and melt amounts measured at stations in Greenland and Antarctica. Also a comparison between the predicted extent of the wet snow zone obtained with the model and the same quantity derived from satellite microwave measurements showed excellent agreement. In addition the model's simulated total runoff was close to the best estimates from observations for the Greenland and Antarctic ice caps. Ms. Bugnion and research scientist Andrei Sokolov coupled the snowpack model to the climate submodel of MIT's Integrated Global System Model (IGSM) and integrated forward over the 21st century for a range of climate change scenarios, using forcings from simulations with the IGSM. The changes in mass balance of the ice caps were then translated into changes in sea level. For the scenarios with small to moderate warming, the runoff from Greenland and Antarctica is minimal. For the scenarios with a larger warming, there is a net increase in sea-level of 2-3 cm from Greenland, and a decrease of between 2 and 5 cm from Antarctica. These results show that the net change in sea level which can be expected to follow climatic changes in the Arctic and Antarctic regions, a decrease of 2 to 4 cm or less by the end of the 21st century, is smaller than most previously published estimates.
Stone, Peter H.↗
Average areal water equivalent of snow in a mountain basin using microwave and visible satellite data
Satellite microwave data were used to evaluate the average areal water equivalent of snow cover in the mountainous Rio Grande basin of Colorado. Areal water equivalent data for the basin were obtained from contoured values of point measurements and from zonal water volume values generated by a snowmelt runoff model. Comparison of these snow water equivalent values shows the model values to consistently exceed the contoured values, probably because of the narrow elevation range in the lower part of the basin where the point measurements are concentrated. A significant relationship between the difference in microwave brightness temperatures at two different wavelengths and a basin-wide average snow water equivalent value is obtained. The average water equivalent of the snow cover in the basin was derived from differences of the microwave brightness temperatures.
Rango, A.↗
Average areal water equivalent of snow in a mountain basin using microwave and visible satellite data
Satellite microwave data were used to evaluate the average areal water equivalent of snow cover in the mountainous Rio Grande basin of Colorado. Areal water equivalent data for the basin were obtained from contoured values of point measurements and from zonal water volume values generated by a snowmelt runoff model. Comparison of these snow water equivalent values shows the model values to consistently exceed the contoured values, probably because of the narrow elevation range in the lower part of the basin where the point measurements are concentrated. A significant relationship between the difference in microwave brightness temperatures at two different wavelengths and a basin-wide average snow water equivalent value is obtained. The average water equivalent of the snow cover in the basin was derived from differences of the microwave brightness temperatures.
Rango, Albert↗
Strategies for using remotely sensed data in hydrologic models
Present and planned remote sensing capabilities were evaluated. The usefulness of six remote sensing capabilities (soil moisture, land cover, impervious area, areal extent of snow cover, areal extent of frozen ground, and water equivalent of the snow cover) with seven hydrologic models (API, CREAMS, NWSRFS, STORM, STANFORD, SSARR, and NWSRFS Snowmelt) were reviewed. The results indicate remote sensing information has only limited value for use with the hydrologic models in their present form. With minor modifications to the models the usefulness would be enhanced. Specific recommendations are made for incorporating snow covered area measurements in the NWSRFS Snowmelt model. Recommendations are also made for incorporating soil moisture measurements in NWSRFS. Suggestions are made for incorporating snow covered area, soil moisture, and others in STORM and SSARR. General characteristics of a hydrologic model needed to make maximum use of remotely sensed data are discussed. Suggested goals for improvements in remote sensing for use in models are also established.
Peck, E. L.↗
Evaluating Multispectral Snowpack Reflectivity With Changing Snow Correlation Lengths
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.
Kang, Do Hyuk↗
Retrieval of Snow Freeboard of Antarctic Sea Ice Using Waveform Fitting of CryoSat-2 Returns
In this paper we develop a CryoSat-2 algorithm to retrieve the surface elevation of the air–snow interface over Antarctic sea ice. This algorithm utilizes a two-layer physical model that accounts for scattering from a snow layer atop sea ice as well as scattering from below the snow surface. The model produces waveforms that are fit to CryoSat-2 level 1B data through a bounded trust region least-squares fitting process. These fit waveforms are then used to track the air–snow interface and retrieve the surface elevation at each point along the CryoSat-2 ground track, from which the snow freeboard is computed. To validate this algorithm, we compare retrieved surface elevation measurements and snow surface radar return power levels with those from Operation IceBridge, which flew along a contemporaneous CryoSat-2 orbit in October 2011 and November 2012. Average elevation differences (standard deviations) along the flight lines (IceBridge Airborne Topographic Mapper, ATM – CryoSat-2) are found to be 0.016 cm (29.24 cm) in 2011 and 2.58 cm (26.65 cm) in 2012. The spatial distribution of monthly average pan-Antarctic snow freeboard found using this method is similar to what was observed from NASA's Ice, Cloud, and land Elevation Satellite (ICESat), where the difference (standard deviation) between October 2011–2017 CryoSat-2 mean snow freeboard and spring 2003–2007 mean freeboard from ICESat is 1.92 cm (9.23 cm). While our results suggest that this physical model and waveform fitting method can be used to retrieve snow freeboard from CryoSat-2, allowing for the potential to join laser and radar altimetry data records in the Antarctic, larger (∼30 cm) regional differences from ICESat and along-track differences from ATM do exist, suggesting the need for future improvements to the method. Snow–ice interface elevation retrieval is also explored as a potential to obtain snow depth measurements. However, it is found that this retrieval method often tracks a strong scattering layer within the snow layer instead of the actual snow–ice interface, leading to an overestimation of ice freeboard and an underestimation of snow depth in much of the Southern Ocean but with promising results in areas such as the East Antarctic sector.
Fons, Steven W.↗
More Realistic Intermediate Depth Dry Firn Densification in the Energy Exascale Earth System Model (E3SM)
Abstract Earth system models account for seasonal snow cover, but many do not accommodate the deeper snowpack on ice sheets (aka firn) that slowly transforms to ice under accumulating snowfall. To accommodate and resolve firn depths of up to 60 m in the Energy Exascale Earth System Model's land surface model (ELM), we add 11 layers to its snowpack and evaluate three dry snow compaction equations in multi‐century simulations. After comparing results from ELM simulations (forced with atmospheric reanalysis) with empirical data, we find that implementing into ELM a two‐stage firn densification model produces more accurate dry firn densities at intermediate depths of 20–60 m. Compared to modeling firn using the equations in the (12 layer) Community Land Model (version 5), switching to the two‐stage firn densification model (with 16 layers) significantly decreases root‐mean‐square errors in upper 60 m dry firn densities by an average of 41 kg m −3 (31%). Simulations with three different firn density parameterizations show that the two‐stage firn densification model should be used for applications that prioritize accurate upper 60 m firn air content (FAC) in regions where the mean annual surface temperature is greater than roughly −31°C. Because snow metamorphism, firn density, and FAC are major components in modeling ice sheet surface albedo, melt water retention, and climatic mass balance, these developments advance broader efforts to simulate the response of land ice to atmospheric forcing in Earth system models.
58 GEOSCIENCES↗
Modeling Present and Future Permafrost Distribution at Seward Peninsula, Alaska: Modeling Archive
This dataset contains results from two GIPL runs for RCP4.5 and RCP8.5 across the Seward Peninsula. The model was run on 500 m by 500 m resolution for the period 1901-2100. Meteo variables include forcing air temperature and precipitation as well as modeled maxim and average snow height. This dataset also includes ground temperature at 10 different depths for every grid cell, active layer depth and talik thickness. Auxillary variables include ecotype map and projected latitude and longitude. Ground temperature borehole data that is used for model calibration and validation of GIPL2 for Seward Peninsula 500 m resolution model runs for 1901-2100 time period. Dataset also includes calibrated model parameters for future use. The main purpose of this dataset is the reproducibility of research. Data were produced for regional permafrost distribution assessment for present and future, in addition, model parameters can be used for future model runs on adjacent territories. This dataset contains *.pdf, *.txt, *.csv, and *.nc. files. 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↗
Subpixel Snow-Covered-Area and Snow Grain Size from Mixture Analysis with Aviris Data
Snow-covered-area (SCA) and snow grain size are crucial inputs to hydrologic and climatologic modeling of alpine and other seasonally snow-covered regions. SCA is necessary to parameterize energy budget calculations in climate models, to determine in which regions point snowmelt models are to be run for distributed snowmelt modeling efforts and to provide a basis from which estimates of snow water equivalent (SWE) may be made.
hydrologic↗
Remote sensing of snow and ice
This paper reviews remote sensing of snow and ice, techniques for improved monitoring, and incorporation of the new data into forecasting and management systems. The snowcover interpretation of visible and infrared data from satellites, automated digital methods, radiative transfer modeling to calculate the solar reflectance of snow, and models using snowcover input data and elevation zones for calculating snowmelt are discussed. The use of visible and near infrared techniques for inferring snow properties, microwave monitoring of snowpack characteristics, use of Landsat images for collecting glacier data, monitoring of river ice with visible imagery from NOAA satellites, use of sequential imagery for tracking ice flow movement, and microwave studies of sea ice are described. Applications of snow and ice research to commercial use are examined, and it is concluded that a major problem to be solved is characterization of snow and ice in nature, since assigning of the correct properties to a real system to be modeled has been difficult.
Rango, A.↗
Identifying snowfall elevation patterns by assimilating satellite-based snow depth retrievals
Precipitation in mountain regions is highly variable and poorly measured, posing important challenges to water resource management. Traditional methods to estimate precipitation include in-situ gauges, Doppler weather radars, satellite radars and radiometers, numerical modeling and reanalysis products. Each of these methods is unable to adequately capture complex orographic precipitation. Here, we propose a novel approach to characterize orographic snowfall over mountain regions. We use a particle batch smoother to leverage satellite information from Sentinel-1 derived snow depth retrievals and to correct various gridded precipitation products. This novel approach is tested using a simple snow model for an alpine basin located in Trentino Alto Adige, Italy. Here, we quantify the precipitation biases across the basin and found that the assimilation method (i) corrects for snowfall biases and uncertainties, (ii) leads to cumulative snowfall elevation patterns that are consistent across precipitation products, and (iii) results in overall improved basin-wide snow variables (snow depth and snow cover area) and basin streamflow estimates.
54 ENVIRONMENTAL SCIENCES↗
A physical model and inversion approach for remote measurement of snow properties
Explore the source record for details and available documents.
AVIRIS remote measurement imaging spectroscopy↗