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Bonding of MEMs materials is carried out using microwave. High microwave absorbing films are placed within a microwave cavity, and excited to cause selective heating in the skin of the material. This causes heating in one place more than another. Thereby minimizing the effects of the bonding microwave energy.
Seasonal snow cover in South America was examined in this study using passive microwave satellite data from the Scanning Multichannel Microwave Radiometer (SMMR) on board the Nimbus-7 satellite and the Special Sensor Microwave Imagers (SSM/I) onboard Defense Meteorological Satellite Program (DMSP) satellites. For the period from 1979-2006, both snow cover extent and snow water equivalent (snow mass) were investigated during the coldest months (May-September), primarily in the Patagonia area of Argentina and in the Andes of Chile, Argentina and Bolivia, where most of the seasonal snow is found. Since winter temperatures in this region are often above freezing, the coldest winter month was found to be the month having the most extensive snow cover and usually the month having the deepest snow cover as well. Sharp year-to-year differences were recorded using the passive microwave observations. The average snow cover extent for July, the month with the greatest average extent during the 28-year period of record, is 321,674 km(exp 2). In July of 1984, the average monthly snow cover extent was 701,250 km(exp 2) the most extensive coverage observed between 1979 and 2006. However, in July of 1989, snow cover extent was only 120,000 km(exp 2). The 28-year period of record shows a sinusoidal like pattern for both snow cover and snow mass, though neither trend is significant at the 95% level.
Snow fall and snow accumulation are key climate parameters due to the snow's high albedo, its thermal insulation, and its importance to the global water cycle. Satellite passive microwave radiometers currently provide the only means for the retrieval of snow depth and/or snow water equivalent (SWE) over land as well as over sea ice from space. All algorithms make use of the frequency-dependent amount of scattering of snow over a high-emissivity surface. Specifically, the difference between 37- and 19-GHz brightness temperatures is used to determine the depth of the snow or the SWE. With the availability of the Advanced Microwave Scanning Radiometer (AMSR-E) on the National Aeronautics and Space Administration's Earth Observing System Aqua satellite (launched in May 2002), a wider range of frequencies can be utilized. In this study we investigate, using model simulations, how snow depth retrievals are affected by the evolution of the physical properties of the snow (mainly grain size growth and densification), how they are affected by variations in atmospheric conditions and, finally, how the additional channels may help to reduce errors in passive microwave snow retrievals. The sensitivity of snow depth retrievals to atmospheric water vapor is confirmed through the comparison with precipitable water retrievals from the National Oceanic and Atmospheric Administration's Advanced Microwave Sounding Unit (AMSU-B). The results suggest that a combination of the 10-, 19-, 37-, and 89-GHz channels may significantly improve retrieval accuracy. Additionally, the development of a multisensor algorithm utilizing AMSR-E and AMSU-B data may help to obtain weather-corrected snow retrievals.
Accurate estimates of snow water equivalent and other properties play an important role in weather, natural hazard, and hydrological forecasting and climate modeling over a range of scales in space and time. Remote sensing-derived estimates have traditionally been of the "snapshot" type, but techniques involving models with assimilation are also being explored. In both cases, forward emission models are useful to understand the observed passive microwave signatures and developing retrieval algorithms. However, mismatches between passive microwave sensor resolutions and the scales of processes controlling subpixel heterogeneity can affect the accuracy of the estimates. Improving the spatial resolution of new passive microwave satellite sensors is a major desire in order to (literally) resolve such subpixel heterogeneity, but limited spacecraft and mission resources impose severe constraints and tradeoffs. In order to maximize science return while mitigating risk for a satellite concept, it is essential to understand the scaling behavior of snow in terms of what the sensor sees (brightness temperature) as well as in terms of the actual variability of snow. NASA's Cold Land Processes Experiment-1 (CLPX-1: Colorado, 2002 and 2003) was designed to provide data to measure these scaling behaviors for varying snow conditions in areas with forested, alpine, and meadow/pasture land cover. We will use observations from CLPX-1 ground, airborne, and satellite passive microwave sensors to examine and evaluate the scaling behavior of observed and modeled brightness temperatures and observed and retrieved snow parameters across scales from meters to 10's of kilometers. The conclusions will provide direct examples of the appropriate spatial sampling scales of new sensors for snow remote sensing. The analyses will also illustrate the effects and spatial scales of the underlying phenomena (e.g., land cover) that control subpixel heterogeneity.
Seasonal snow cover in South America was examined in this study using passive microwave satellite data from the Scanning Multichannel Microwave Radiometer (SMMR) on board the Nimbus-satellite and the Special Sensor Microwave Imagers (SSM/I) on board Defense Meteorological Satellite Program (DMSP) satellites. For the period from 1979-2003, both snow cover extent and snow depth (snow mass) were investigated during coldest months (May-September), primarily in the Patagonia area of Argentina and in Chile. Most of the seasonal snow in South America is in the Patagonia region of Argentina. Since winter temperatures in this region are often above freezing, the coldest winter month was found to be the month having the most extensive snow cover and also usually the month having the deepest snow cover as well. Sharp year-to-year differences were recorded using the passive microwave observations. The average snow cover extent for July, the month with the greatest average snow extent during the 25-year period of record, is 320,700 km(exp 2). In July of 1984, the average monthly snow cover was 701,250 km(exp 2) - the most extensive coverage observed between 1979 and 2003. However, in July of 1989, snow cover extent was only 120 km(exp 2). The 25-year period of record shows a sinusoidal like pattern, though there appears to be no obvious trend in either increasing or decreasing snow extent or snow mass between 1979 and 2003.
A joint U.S. Air Force/NASA blended, global snow product that utilizes Earth Observation System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS), Advanced Microwave Scanning Radiometer for EOS (AMSR-E) and QuikSCAT (Quick Scatterometer) (QSCAT) data has been developed. Existing snow products derived from these sensors have been blended into a single, global, daily, user-friendly product by employing a newly-developed Air Force Weather Agency (AFWA)/National Aeronautics and Space Administration (NASA) Snow Algorithm (ANSA). This initial blended-snow product uses minimal modeling to expeditiously yield improved snow products, which include snow cover extent, fractional snow cover, snow water equivalent (SWE), onset of snowmelt, and identification of actively melting snow cover. The blended snow products are currently 25-km resolution. These products are validated with data from the lower Great Lakes region of the U.S., from Colorado during the Cold Lands Processes Experiment (CLPX), and from Finland. The AMSR-E product is especially useful in detecting snow through clouds; however, passive microwave data miss snow in those regions where the snow cover is thin, along the margins of the continental snowline, and on the lee side of the Rocky Mountains, for instance. In these regions, the MODIS product can map shallow snow cover under cloud-free conditions. The confidence for mapping snow cover extent is greater with the MODIS product than with the microwave product when cloud-free MODIS observations are available. Therefore, the MODIS product is used as the default for detecting snow cover. The passive microwave product is used as the default only in those areas where MODIS data are not applicable due to the presence of clouds and darkness. The AMSR-E snow product is used in association with the difference between ascending and descending satellite passes or Diurnal Amplitude Variations (DAV) to detect the onset of melt, and a QSCAT product will be used to map areas of snow that are actively melting.
Tunable microwave devices based on metal terminals connected by thin ferroelectric films can be made to perform better by patterning the films to include suitably dimensioned, positioned, and oriented constrictions. The patterns can be formed during fabrication by means of selective etching processes. If the width of the ferroelectric film in such a device is reduced at one or more locations, then both the microwave field and any applied DC bias (tuning) electric field become concentrated at those locations. The magnitudes of both the permittivity and the dielectric loss of a ferroelectric material are reduced by application of a DC field. Because the concentration of the DC field in the constriction(s) magnifies the permittivity- and loss-reducing effects of the applied DC voltage, the permittivity and dielectric loss in the constriction(s) are smaller in the constriction(s) than they are in the wider parts of the ferroelectric film. Furthermore, inasmuch as displacement current must flow through either the constriction(s) or the low-loss dielectric substrate, the net effect of the constriction(s) is equivalent to that of incorporating one or more low-loss, low-permittivity region(s) in series with the high-loss, high-permittivity regions. In a series circuit, the properties of the low-capacitance series element (in this case, the constriction) dominate the overall performance. Concomitantly, the capacitance between the metal terminals is reduced. By making the capacitance between the metal terminals small but tunable, a constriction increases the upper limit of the frequency range amenable to ferroelectric tuning. The present patterning concept is expected to be most advantageous for devices and circuits that must operate at frequencies from about 4 to about 60 GHz. A constriction can be designed such that the magnitude of the microwave electric field and the effective width of the region occupied by the microwave electric field become functions of the applied DC electric field, so that tunability is enhanced. It should even be possible to design the constriction to obtain a specific tuning-versus-voltage profile.
NASA seeks to transfer the NASA developed microwave ablation technology, designed for the treatment of ventricular tachycardia (irregular heart beat), to industry. After a heart attack, many cells surrounding the resulting scar continue to live but are abnormal electrically; they may conduct impulses unusually slowly or fire when they would typically be silent. These diseased areas might disturb smooth signaling by forming a reentrant circuit in the muscle. The objective of microwave ablation is to heat and kill these diseased cells to restore appropriate electrical activity in the heart. This technology is a method and apparatus that provides for propagating microwave energy into heart tissues to produce a desired temperature profile therein at tissue depths sufficient for thermally ablating arrhythmogenic cardiac tissue while preventing excessive heating of surrounding tissues, organs, and blood. A wide bandwidth double-disk antenna is effective for this purpose over a bandwidth of about six gigahertz. A computer simulation provides initial screening capabilities for an antenna such as antenna, frequency, power level, and power application duration. The simulation also allows optimization of techniques for specific patients or conditions. In comparison with other methods that involve direct-current pulses or radio frequencies below 1 GHz, this method may prove more effective in treating ventricular tachycardia. This is because the present method provides for greater control of the location, cross-sectional area, and depth of a lesion via selection of the location and design of the antenna and the choice of microwave power and frequency.
Seasonal snow cover in extra-tropical areas of South America was examined in this study using passive microwave satellite data from the Scanning Multichannel Microwave Radiometer (SMMR) on board the Nimbus-7 satellite and from the Special Sensor Microwave Imagers (SSM/I) on board the Defense Meteorological Satellite Program (DMSP) satellites. For the period from 1979-2006, both snow cover extent and snow mass were estimated for the months of May-September. Most of the seasonal snow in South America occurs in the Patagonia region of Argentina. The average snow cover extent for July, the month with the greatest average extent during the 28-year period of record, is 321,674 sq km. The seasonal (May-September) 2 average snow cover extent was greatest in 1984 (464,250 sq km) and least in 1990 (69,875 sq km). In terms of snow mass, 1984 was also the biggest year (1.19 x 10(exp 13) kg) and 1990 was the smallest year (0.12 X 10(exp 13) kg). A strong relationship exists between the snow cover area and snow mass, correlated at 0.95, though no significant trend was found over the 28 year record for either snow cover extent or snow mass. For this long term climatology, snow mass and snow cover extent are shown to vary considerably from month to month and season to season. This analysis presents a consistent approach to mapping and measuring snow in South America utilizing an appropriate and readily available long term snow satellite dataset. This is the optimal dataset available, thus far, for deriving seasonal snow cover and snow mass in this region. Nonetheless, shallow snow, wet snow, snow beneath forests, as well as snow along coastal areas all may confound interpretation using passive microwave approaches. More work needs to be done to reduce the uncertainties in the data and hence, increase the confidence of the interpretation
A paper discusses the need to perform accurate dielectric property measurements on larger sized samples, particularly liquids at microwave frequencies. These types of measurements cannot be obtained using conventional cavity perturbation methods, particularly for liquids or powdered or granulated solids that require a surrounding container. To solve this problem, a model has been developed for the resonant frequency and quality factor of a cylindrical microwave cavity containing concentric cylindrical samples. This model can then be inverted to obtain the real and imaginary dielectric constants of the material of interest. This approach is based on using exact solutions to Maxwell s equations for the resonant properties of a cylindrical microwave cavity and also using the effective electrical conductivity of the cavity walls that is estimated from the measured empty cavity quality factor. This new approach calculates the complex resonant frequency and associated electromagnetic fields for a cylindrical microwave cavity with lossy walls that is loaded with concentric, axially aligned, lossy dielectric cylindrical samples. In this approach, the calculated complex resonant frequency, consisting of real and imaginary parts, is related to the experimentally measured quantities. Because this approach uses Maxwell's equations to determine the perturbed electromagnetic fields in the cavity with the material(s) inserted, one can calculate the expected wall losses using the fields for the loaded cavity rather than just depending on the value of the fields obtained from the empty cavity quality factor. These additional calculations provide a more accurate determination of the complex dielectric constant of the material being studied. The improved approach will be particularly important when working with larger samples or samples with larger dielectric constants that will further perturb the cavity electromagnetic fields. Also, this approach enables the ability to have a larger sample of interest, such as a liquid or powdered or granulated solid, inside a cylindrical container.
In this study, a new first-order radiative transfer (RT) model is developed to more accurately account for vegetation canopy scattering by modifying the basic r-co model (the zero-order RT solution). In order to optimally utilize microwave radiometric data in soil moisture (SM) retrievals over moderately to densely vegetated landscapes, a quantitative understanding of the relationship between scattering mechanisms within vegetation canopies and the microwave brightness temperature is desirable. A first-order RT model is used to investigate this relationship and to perform a physical analysis of the scattered and emitted radiation from vegetated terrain. The new model is based on an iterative solution (successive orders of scattering) of the RT equations up to the first order. This formulation adds a new scattering term to the i-w model. The additional term represents emission by particles (vegetation components) in the vegetation layer and emission by the ground that is scattered once by particles in the layer. The new model is tested against 1.4 GHz brightness temperature measurements acquired over deciduous trees by a truck-mounted microwave instrument system called ComRAD in 2007. The model predictions are in good agreement with the data and they give quantitative understanding for the influence of first-order scattering within the canopy on the brightness temperature. The model results show that the scattering term is significant for trees and modifications are necessary to the T-w model when applied to dense vegetation. Numerical simulations also indicate that the scattering term has a negligible dependence on SM and is mainly a function of the angle and polarization of the microwave observation.
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?
Detailed studies of the energy and water cycles require accurate estimation of the turbulent fluxes of moisture and heat across the atmosphere-ocean interface at regional to basin scale. Providing estimates of these latent and sensible heat fluxes over the global ocean necessitates the use of satellite or reanalysis-based estimates of near surface variables. Recent studies have shown that errors in the surface (10 meter)estimates of humidity and temperature are currently the largest sources of uncertainty in the production of turbulent fluxes from satellite observations. Therefore, emphasis has been placed on reducing the systematic errors in the retrieval of these parameters from microwave radiometers. This study discusses recent improvements in the retrieval of air temperature and humidity through improvements in the choice of algorithms (linear vs. nonlinear) and the choice of microwave sensors. Particular focus is placed on improvements using a neural network approach with a single sensor (Special Sensor Microwave/Imager) and the use of combined sensors from the NASA AQUA satellite platform. The latter algorithm utilizes the unique sampling available on AQUA from the Advanced Microwave Scanning Radiometer (AMSR-E) and the Advanced Microwave Sounding Unit (AMSU-A). Current estimates of uncertainty in the near-surface humidity and temperature from single and multi-sensor approaches are discussed and used to estimate errors in the turbulent fluxes.
There has been interest in finding ways to process the lunar regolith since the early analyses of lunar samples returned from the Apollo moon missions. This fact has led to proposals for using microwaves to perform in-situ processing of the lunar soil to support future colonization of the moon. More recently, there has been speculation that the excellent microwave absorption of lunar soil came from the nanophase iron content in the regolith. The motivation for the present study was to begin obtaining a more fundamental understanding of the dielectric and magnetic properties of the regolith at microwave frequencies. A major objective of this study was to obtain information that would help answer the question about whether nanophase iron plays a major role in heating lunar soils. These new measurements over a wide frequency range can also determine the magnitude of the dielectric and magnetic absorption and if there are any resonant features that could be used to enhance processing of the regolith in the future. In addition, these microwave measurements would be useful in confirming that new simulants being developed, particularly those containing nanophase iron, would have the correct composition to simulate the lunar regolith. The results of this study suggest that nanophase iron does not play a major role in heating lunar regolith.
In-Situ Resource Utilization will be necessary for sustained exploration of space. Volatiles are present in planetary soils, but water by far has the most potential for effective utilization. The presence of water at the lunar poles, Mars, and possibly on Phobos opens the possibility of producing LOX for propellant. Water is also a useful radiation shielding material , and valuable to replenish expendables (water and oxygen) required for habitation in space. Because of the strong function of water vapor pressure with temperature, heating soil effectively liberates water vapor by sublimation. Microwave energy will penetrate soil and heat from within much more efficiently than heating from the surface with radiant heat. This is especially true under vacuum conditions since the heat transfer rate is very low. The depth of microwave penetration is a strong function of the microwave frequency and to a lesser extent on soil dielectric properties. Methods for complex electric permittivity and magnetic permeability measurement are being developed and used for measurements of lunar soil simulants. A new method for delivery of microwaves deep into a planetary surface is being prototyped with laboratory experiments and modeled with COMSOL MultiPhysics. We are planning to set up a planetary testbed in a large vacuum chamber in the coming year. Recent results are discussed.
In-Situ Resource Utilization will be necessary for sustained exploration of space. Volatiles are present in planetary soils, but water by far has the strongest potential for effective utilization. The presence of water at the lunar poles, Mars, and possibly on Phobos opens the possibility of producing LOX for propellant. Water is also a useful radiation shielding material and water (and oxygen) are expendables that are also required for habitation in space. Because of the strong function of water vapor pressure with temperature, heating soil effectively liberates water vapor by sublimation. Microwave energy will penetrate soil and heat from within much more efficiently than heating from the surface with radiant heat. This is especially true under vacuum conditions since the heat transfer rate is very low. The depth of microwave penetration is a strong function of the microwave frequency and to a lesser extent on soil dielectric properties. Methods for measuring the complex electric permittivity and magnetic permeability are being developed and have been measured for some lunar soil simulants at 0.5, 2.45, and 10 GHz from room temperature down to liquid nitrogen temperature. A new method for delivery of microwaves deep into a planetary surface is being prototyped with laboratory experiments and modeled with COMSOL MultiPhysics. We have plans to set up a planetary testbed in a large vacuum chamber in the coming year. Recent results will be presented.
This study reports on the utilization of microwave modeling, together with ground truth, and L-band (1.4-GHz) brightness temperatures to investigate the passive microwave characteristics of a conifer forest floor. The microwave data were acquired over a natural Virginia Pine forest in Maryland by a ground-based microwave active/passive instrument system in 2008/2009. Ground measurements of the tree biophysical parameters and forest floor characteristics were obtained during the field campaign. The test site consisted of medium-sized evergreen conifers with an average height of 12 m and average diameters at breast height of 12.6 cm. The site is a typical pine forest site in that there is a surface layer of loose debris/needles and an organic transition layer above the mineral soil. In an effort to characterize and model the impact of the surface litter layer, an experiment was conducted on a day with wet soil conditions, which involved removal of the surface litter layer from one half of the test site while keeping the other half undisturbed. The observations showed detectable decrease in emissivity for both polarizations after the surface litter layer was removed. A first-order radiative transfer model of the forest stands including the multilayer nature of the forest floor in conjunction with the ground truth data are used to compute forest emission. The model calculations reproduced the major features of the experimental data over the entire duration, which included the effects of surface litter and ground moisture content on overall emission. Both theory and experimental results confirm that the litter layer increases the observed canopy brightness temperature and obscure the soil emission.
In-Situ Resource Utilization will be Ground Breaking technology for sustained exploration of space. Volatiles are present in planetary regolith, but water by far has the most potential for effective utilization. The presence of water at the lunar poles and Mars opens the possibility of using the hydrogen for propellant on missions beyond Earth orbit. Likewise, the oxygen could be used for in-space propulsion for lunar ascent/descent and for space tugs from low lunar orbit to low Earth orbit. Water is also an effective radiation shielding material as well as a valuable expendable (water and oxygen) required for habitation in space. Because of the strong function of water vapor pressure with temperature, heating regolith effectively liberates water vapor by sublimation. Microwave energy will penetrate soil and heat from within, much more efficiently than heating from the surface with radiant heat. This is especially true under vacuum conditions since the heat transfer rate is very low. The depth of microwave penetration is a strong function of the microwave frequency and to a lesser extent on regolith dielectric properties. New methods for delivery of microwaves into lunar and planetary surfaces is being prototyped with laboratory experiments and modeled with COMSOL MultiPhysics. Recent results are discussed.