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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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NASA NTRS2000

The Influence of Microphysical Cloud Parameterization on Microwave Brightness Temperatures

The microphysical parameterization of clouds and rain-cells plays a central role in atmospheric forward radiative transfer models used in calculating passive microwave brightness temperatures. The absorption and scattering properties of a hydrometeor-laden atmosphere are governed by particle phase, size distribution, aggregate density., shape, and dielectric constant. This study identifies the sensitivity of brightness temperatures with respect to the microphysical cloud parameterization. Cloud parameterizations for wideband (6-410 GHz observations of baseline brightness temperatures were studied for four evolutionary stages of an oceanic convective storm using a five-phase hydrometeor model in a planar-stratified scattering-based radiative transfer model. Five other microphysical cloud parameterizations were compared to the baseline calculations to evaluate brightness temperature sensitivity to gross changes in the hydrometeor size distributions and the ice-air-water ratios in the frozen or partly frozen phase. The comparison shows that, enlarging the rain drop size or adding water to the partly Frozen hydrometeor mix warms brightness temperatures by up to .55 K at 6 GHz. The cooling signature caused by ice scattering intensifies with increasing ice concentrations and at higher frequencies. An additional comparison to measured Convection and Moisture LA Experiment (CAMEX 3) brightness temperatures shows that in general all but, two parameterizations produce calculated T(sub B)'s that fall within the observed clear-air minima and maxima. The exceptions are for parameterizations that, enhance the scattering characteristics of frozen hydrometeors.

Skofronick-Jackson, Gail M.↗
NASA NTRS2019

Exploring the Utility of Machine Learning-Based Passive Microwave Brightness Temperature Data Assimilation over Terrestrial Snow in High Mountain Asia

This study explores the use of a support vector machine (SVM) as the observation operator within a passive microwave brightness temperature data assimilation framework (herein SVM-DA) to enhance the characterization of snow water equivalent (SWE) over High Mountain Asia (HMA). A series of synthetic twin experiments were conducted with the NASA Land Information System (LIS) at a number of locations across HMA. Overall, the SVM-DA framework is effective at improving SWE estimates (~70% reduction in RMSE relative to the Open Loop) for SWE depths less than 200 mm during dry snowpack conditions. The SVM-DA framework also improves SWE estimates in deep, wet snow (~45% reduction in RMSE) when snow liquid water is well estimated by the land surface model, but can lead to model degradation when snow liquid water estimates diverge from values used during SVM training. In particular, two key challenges of using the SVM-DA framework were observed over deep, wet snowpacks. First, variations in snow liquid water content dominate the brightness temperature spectral difference (TB) signal associated with emission from a wet snowpack, which can lead to abrupt changes in SWE during the analysis update. Second, the ensemble of SVM-based predictions can collapse (i.e., yield a near-zero standard deviation across the ensemble) when prior estimates of snow are outside the range of snow inputs used during the SVM training procedure. Such a scenario can lead to the presence of spurious error correlations between SWE and TB, and as a consequence, can result in degraded SWE estimates from the analysis update. These degraded analysis updates can be largely mitigated by applying rule-based approaches. For example, restricting the SWE update when the standard deviation of the predicted TB is greater than 0.05 K helps prevent the occurrence of filter divergence. Similarly, adding a thin layer (i.e., 5 mm) of SWE when the synthetic TB is larger than 5 K can improve SVM-DA performance in the presence of a precipitation dry bias. The study demonstrates that a carefully constructed SVM-DA framework cognizant of the inherent limitations of passive microwave-based SWE estimation holds promise for snow mass data assimilation.

Kwon, Yonghwan↗
NASA NTRS1972

Microwave brightness temperature of a windblown sea

A mathematical model is developed for the apparent temperature of the sea at all microwave frequencies. The model is a numerical model in which both the clear water structure and white water are accounted for as a function of wind speed. The model produces results similar to Stogryn's model at 19.35 GHz for wind speeds less than 8 m/sec; it can use radiosonde data to calculate atmospheric effects and can incorporate an empirically determined antenna gain pattern. The corresponding computer program is of modular design and the logic of the main program is capable of treating a horizontally inhomogeneous surface or atmosphere. It is shown that a variation of microwave brightness temperature with zenith angle is necessary to produce the wind sensitivity of the horizontally polarized brightness temperature; the variation of sky temperature with frequency is sufficient to produce a frequency dependent wind sensitivity.

Hall, F. G.↗
NASA NTRS1981

Satellite-derived ice data sets no. 1: Antarctic monthly average microwave brightness temperatures and sea-ice concentrations, 1973 - 1976

A summary data set concerning 4 years of Antarctic sea-ice conditions was created and is available on magnetic tape. The data were derived from electrically scanning microwave radiometer brightness temperatures and were mapped into a polar stereographic grid enclosing the 50 deg S latitude circle. The grid size varies from about 32 by 32 sq km at the poles to about 28 by 28 sq km at 50 deg S. The microwave brightness temperatures of Antarctic sea ice are predominantly characteristic of first-year ice with an emissivity of 0.92 at 19 GHz frequency. Sea ice concentrations were calculated from the brightness temperature data for each grid element with an algorithm that uses an emissivity value of 0.92 and an ice physical temperature estimate from climatological surface air temperatures. Monthly, multiyear monthly, and yearly maps of brightness temperatures and sea ice concentrations were created for the 4 years, except for 7 months for which useable data were insufficient.

Zwally, H. J.↗
NASA NTRS2011

Surface and Atmospheric Contributions to Passive Microwave Brightness Temperatures for Falling Snow Events

Physically based passive microwave precipitation retrieval algorithms require a set of relationships between satellite -observed brightness temperatures (TBs) and the physical state of the underlying atmosphere and surface. These relationships are nonlinear, such that inversions are ill ]posed especially over variable land surfaces. In order to elucidate these relationships, this work presents a theoretical analysis using TB weighting functions to quantify the percentage influence of the TB resulting from absorption, emission, and/or reflection from the surface, as well as from frozen hydrometeors in clouds, from atmospheric water vapor, and from other contributors. The percentage analysis was also compared to Jacobians. The results are presented for frequencies from 10 to 874 GHz, for individual snow profiles, and for averages over three cloud-resolving model simulations of falling snow. The bulk structure (e.g., ice water path and cloud depth) of the underlying cloud scene was found to affect the resultant TB and percentages, producing different values for blizzard, lake effect, and synoptic snow events. The slant path at a 53 viewing angle increases the hydrometeor contributions relative to nadir viewing channels. Jacobians provide the magnitude and direction of change in the TB values due to a change in the underlying scene; however, the percentage analysis provides detailed information on how that change affected contributions to the TB from the surface, hydrometeors, and water vapor. The TB percentage information presented in this paper provides information about the relative contributions to the TB and supplies key pieces of information required to develop and improve precipitation retrievals over land surfaces.

Skofronick-Jackson, Gail↗
NASA NTRS1982

The effect of monomolecular surface films on the microwave brightness temperature of the sea surface

It is pointed out that monomolecular surface films of biological origin are often encountered on the ocean surface, especially in coastal regions. The thicknesses of the monomolecular films are of the order of 3 x 10 to the -9th m. Huehnerfuss et al. (1978, 1981) have shown that monomolecular surface films damp surface waves quite strongly in the centimeter to decimeter wavelength regime. Other effects caused by films are related to the reduction of the gas exchange at the air-sea interface and the decrease of the wind stress. The present investigation is concerned with experiments which reveal an unexpectedly large response of the microwave brightness temperature to a monomolecular oleyl alcohol slick at 1.43 GHz. Brightness temperature is a function of the complex dielectric constant of thy upper layer of the ocean. During six overflights over an ocean area covered with an artificial monomolecular alcohol film, a large decrease of the brightness temperature at the L-band was measured, while at the S-band almost no decrease was observed.

Alpers, W.↗
NASA NTRS2021

Surface Melting Over the Greenland Ice Sheet Derived From Enhanced Resolution Passive Microwave Brightness Temperatures (1979–2019)

Surface melting is a major component of the Greenland ice sheet surface mass balance, and it affects sea level rise through direct runoff and the modulation of ice dynamics and hydrological processes, supraglacially, englacially and subglacially. Passive microwave (PMW) brightness temperature observations are of paramount importance in studying the spatial and temporal evolution of surface melting due to their long temporal coverage (1979–present) and high temporal resolution (daily). However, a major limitation of PMW datasets has been the relatively coarse spatial resolution, which has historically been of the order of tens of kilometers. Here, we use a newly released PMW dataset (37 GHz, horizontal polarization) made available through a NASA “Making Earth System Data Records for Use in Research Environments” (MeASUREs) program to study the spatiotemporal evolution of surface melting over the Greenland ice sheet at an enhanced spatial resolution of 3.125 km. We assess the outputs of different detection algorithms using data collected by automatic weather stations (AWSs) and the outputs of the Modèle Atmosphérique Régional (MAR) regional climate model. We found that sporadic melting is well captured using a dynamic algorithm based on the outputs of the Microwave Emission Model of Layered Snowpack (MEMLS), whereas a fixed threshold of 245 K is capable of detecting persistent melt. Our results indicate that, during the reference period from 1979 to 2019 (from 1988 to 2019), surface melting over the ice sheet increased in terms of both duration, up to 4.5 (2.9) d per decade, and extension, up to 6.9 % (3.6 %) of the entire ice sheet surface extent per decade, according to the MEMLS algorithm. Furthermore, the melting season started up to 4.0 (2.5) d earlier and ended 7.0 (3.9) d later per decade. We also explored the information content of the enhanced-resolution dataset with respect to the one at 25 km and MAR outputs using a semi-variogram approach. We found that the enhanced product is more sensitive to local-scale processes, thereby confirming the potential of this new enhanced product for monitoring surface melting over Greenland at a higher spatial resolution than the historical products and for monitoring its impact on sea level rise. This offers the opportunity to improve our understanding of the processes driving melting, to validate modeled melt extent at high resolution and, potentially, to assimilate these data in climate models.

Surface melting↗
NASA NTRS2020

Surface melting over the Greenland ice sheet from enhanced resolution passive microwave brightness temperatures (1979–2019)

Surface melting is a major component of the Greenland ice sheet (GrIS) surface mass balance, affecting sea level rise through direct runoff and the modulation on ice dynamics and hydrological processes, supraglacially, englacially and subglacially. Passive microwave (PMW) brightness temperature observations are of paramount importance in studying the spatial and temporal evolution of surface melting in view of their long temporal coverage (1979–to date) and high temporal resolution (daily). However, a major limitation of PMW datasets has been the relatively coarse spatial resolution, being historically of the order of tens of kilometres. Here, we use a newly released passive microwave dataset (37 GHz, horizontal polarization) made available through the NASA MeASUREs program to study the spatiotemporal evolution of surface melting over the GrIS at an enhanced spatial resolution of 3.125 Km. We assess the outputs of different detection algorithms through data collected by Automatic Weather Stations (AWS) and the outputs of the MAR regional climate model. We found that surface melting is well captured using a dynamic algorithm based on the outputs of MEMLS model, capable to detect sporadic and persistent melting. Our results indicate that, during the reference period 1979–2019 (1988–2019), surface melting over the GrIS increased in terms of both duration, up to ~4.5 (2.9) days per decade, and extension, up to 6.9 % (3.6 %) of the GrIS surface extent per decade, according to the MEMLS algorithm. Furthermore, the melting season has started up to ~4 (2.5) days earlier and ended ~7 (3.9) days later per decade. We also explored the information content of the enhanced resolution dataset with respect to the one at 25 km and MAR outputs through a semi-variogram approach. We found that the enhanced product is more sensitive to local scale processes, hence confirming the potential interest of this new enhanced product for studying surface melting over Greenland at a higher spatial resolution than the historical products and monitor its impact on sea level rise. This offers the opportunity to improve our understanding of the processes driving melting, to validate modelled melt extent at high resolution and potentially to assimilate this data in climate models.

Surface melting↗
NASA NTRS2021

Passive Microwave Brightness Temperature Assimilation to Improve Snow Mass Estimation across Complex Terrain in Pakistan, Afghanistan, and Tajikistan

An ensemble Kalman filter is used to assimilate Advanced Microwave Scanning Radiometer-2 (AMSR2) observations of passive microwave (PMW) brightness temperatures (spectral differences, ΔT b ) into land surface model estimates of snow mass over northwestern high mountain Asia (HMA). Trained support vector machines serve as the observation operator and map the geophysical modeled variables into ΔT b space within the assimilation framework. Evaluation of the assimilation routine is carried out through comparison of assimilated snow mass estimates with an in situ dataset. The assimilation framework helps improve the land surface model estimates through PMW ΔT b assimilation, particularly in terms of decreasing the domain-wide bias. The assimilation framework proved more effective during the (dry) snow accumulation season and decreased the bias and root-mean-square error (RMSE) in snow mass estimates at 76% and 58% of the comparative pixels, respectively. During the snow ablation season, the PMW brightness temperature signal contained less information related to snow mass due to the presence of other concurrent geophysical features that effectively serve as noise during the snow mass update. The utilization of PMW ΔT b for accurate snow mass estimation in complex terrain such as HMA is dependent on a multitude of factors for optimal results; however, it does add utility to the land surface model if the relevant pitfalls are taken into consideration prior to the state variable update.

Jawairia Ahmad↗
NASA NTRS1998

Microwave Brightness Temperatures of Tilted Convective Systems

Aircraft and ground-based radar data from the Tropical Ocean and Global Atmosphere Coupled-Ocean Atmosphere Response Experiment (TOGA COARE) show that convective systems are not always vertical. Instead, many are tilted from vertical. Satellite passive microwave radiometers observe the atmosphere at a viewing angle. For example, the Special Sensor Microwave/Imager (SSM/I) on Defense Meteorological Satellite Program (DMSP) satellites and the Tropical Rainfall Measurement Mission (TRMM) Microwave Imager (TMI) on the TRMM satellite have an incident angle of about 50deg. Thus, the brightness temperature measured from one direction of tilt may be different than that viewed from the opposite direction due to the different optical depth. This paper presents the investigation of passive microwave brightness temperatures of tilted convective systems. To account for the effect of tilt, a 3-D backward Monte Carlo radiative transfer model has been applied to a simple tilted cloud model and a dynamically evolving cloud model to derive the brightness temperature. The radiative transfer results indicate that brightness temperature varies when the viewing angle changes because of the different optical depth. The tilt increases the displacements between high 19 GHz brightness temperature (Tb(sub 19)) due to liquid emission from lower level of cloud and the low 85 GHz brightness temperature (Tb(sub 85)) due to ice scattering from upper level of cloud. As the resolution degrades, the difference of brightness temperature due to the change of viewing angle decreases dramatically. The dislocation between Tb(sub 19) and Tb(sub 85), however, remains prominent.

Hong, Ye↗
NASA NTRS1988

Determining microwave brightness temperatures from precipitating horizontally finite and vertically structured clouds

Microwave radiances that may be measured from satellite-borne radiometers operating at 37 GHz have been computed as a function of rainfall rates from horizontally finite precipitating clouds that contain both ice and liquid hydrometeors. It is found that precipitating ice at the top of the cloud depresses brightness temperatures significantly. Detailed comparison between finite clouds and the equivalent sections of plane-parallel clouds are made. Footprint averaged brightness temperatures from finite clouds are found to deviate considerably from the sectioned plane-parallel approximation, especially for large rain rates. Better agreement is achieved if a plane-parallel source function is used in the finite cloud model. The effect of shape and orientation of the precipitating cells with respect to the satellite has also been considered. It is found that the largest errors introduced by plane-parallel theory besides the footprint-filling errors are encountered when precipitating cells have large fractions of their surface below the freezing level or contain large amounts of ice.

Kummerow, C.↗
NASA NTRS1982

Some recent results in the interpretation of high brightness temperature microwave spike emission

A review is presented of theoretical work on the interpretation of short duration (1-100 msec), high brightness temperature (approximately 10 to the 15th K) spikes at microwave frequencies during the impulsive phase of some solar flares. Also examined is recent work on the interpretation of the spike emission as gyrosynchrotron masering. Two alternative radiation mechanisms, stimulated plasma emission from the coherent interaction of electrostatic upper hybrid waves and from the interaction of electron plasma waves, are examined.

Holman, G. D.↗
NASA NTRS1987

Satellite-derived ice data sets no. 2: Arctic monthly average microwave brightness temperatures and sea ice concentrations, 1973-1976

A summary data set for four years (mid 70's) of Arctic sea ice conditions is available on magnetic tape. The data include monthly and yearly averaged Nimbus 5 electrically scanning microwave radiometer (ESMR) brightness temperatures, an ice concentration parameter derived from the brightness temperatures, monthly climatological surface air temperatures, and monthly climatological sea level pressures. All data matrices are applied to 293 by 293 grids that cover a polar stereographic map enclosing the 50 deg N latitude circle. The grid size varies from about 32 X 32 km at the poles to about 28 X 28 km at 50 deg N. The ice concentration parameter is calculated assuming that the field of view contains only open water and first-year ice with an ice emissivity of 0.92. To account for the presence of multiyear ice, a nomogram is provided relating the ice concentration parameter, the total ice concentration, and the fraction of the ice cover which is multiyear ice.

Parkinson, C. L.↗
NASA NTRS1989

Interpretation of Nimbus-7 37 GHz microwave brightness temperature data in semi-arid southern Africa

Monthly 37 GHz microwave polarization difference temperatures (MPDT) derived from the Nimbus-7 scanning multichannel microwave radiometer (SMMR) for southern Africa from 1979 to 1985 are compared with rainfall and Advanced Very High Resolution Radiometer (AVHRR) normalized difference vegetation index (NDVI) data. MPDT rose sharply during a drought episode which occurred within the period included in the data. The rise was seen not only in the growing season, but also in the dry season MPDT when no actively photosynthetic, water-containing leaves are present. The results suggest that scattering of the emitted microwave radiation by dead and living vegetation is a more important factor than has previously been recognized.

Prince, S. D.↗
NASA NTRS2006

Antarctic Iceberg Tracking Based on Time Series of Aqua AMSRE Microwave Brightness Temperature Measurements

Observations of icebergs are identified as one of the requirements for the GEOSS (Global Earth Observation System of Systems) in the area of reducing loss of life and property from natural and human-induced disasters. However, iceberg observations are not included among targets in the GEOSS 10-Year Implementation Plan, and thus there is an unfulfilled need for iceberg detection and tracking in the near future. Large Antarctic icebergs have been tracked by the National Ice Center and by the academic community using a variety of satellite sensors including both passive and active microwave imagers, such as SSM/I (Special Sensor Microwave/Imager) deployed on the DMSP (Defense Meteorological Satellite Program) spacecraft. Improvements provided in recent years by NASA and non-NASA satellite radars, scatterometers, and radiometers resulted in an increased number of observed icebergs and even prompted a question: Is The Number of Antarctic Icebergs Really Increasing? [D.G. Long, J. Ballantyne, and C. Bertoia, Eos, Transactions of the American Geophysical Union 83 (42): 469 & 474, 15 October 2002]. AMSR-E (Advanced Microwave Scanning Radiometer for the Earth Observing System) represents an improvement over SSM/I, its predecessor. AMSR-E has more measurement channels and higher spatial resolution than SSM/I. For example, the instantaneous field of view of the AMSR-E s 89-GHz channels is 6 km by 4 km versus 16 km by 14 km for SSM/I s comparable 85-GHz channels. AMSR-E, deployed on the Aqua satellite, scans across a 1450-km swath and provides brightness temperature measurements with nearglobal coverage every one or two days. In polar regions, overlapping swaths generate coverage up to multiple times per day and allow for creation of image time series with high temporal resolution. Despite these advantages, only incidental usage of AMSR-E data for iceberg tracking has been reported so far, none in an operational environment. Therefore, an experiment was undertaken in the RPC (Rapid Prototyping Capability) of NASA s (National Aeronautics and Space Administration) Applied Science Program to demonstrate that passive microwave brightness temperature measurements acquired by AMSR-E can be effectively used to track iceberg movement around Antarctica. The RPC s robust computation environment enabled processing of terabytes of data products available from the NASA Distributed Active Archive Center at the National Snow and Ice Data Center. Iceberg tracking based on the AMSR-E Level 2A data product was compared with records from the National Ice Center for currently existing icebergs. Some icebergs as small as roughly 10 km in size were easily observed, but tracking of many others, even larger ones, was obscured by presence of sea ice surrounding the icebergs. The best results, such as for the large iceberg A22A, were achieved when an iceberg was in open ocean.

Blonski, Slawomir↗
NASA NTRS1986

Zonal wave number variance spectra of stratospheric microwave brightness temperatures

Well-known theoretical predictions suggest that variances of large-scale atmospheric fluctuations, for scales somewhat shorter than those of the forcing mechanisms, should obey a power law, k exp -b, where k is the horizontal wave number. The invariance of the exponent b with season, hemisphere, and latitude is tested using satellite-measured brightness temperatures. Global grids of Tiros-N Microwave Sounding Unit channel 4 measurements, which closely approximate the 30- to 150-mbar layer mean temperature, are constructed for January, March, and August 1979. These grids are zonally Fourier-transformed, and the resulting spectra are averaged over four 18 deg-wide latitude bands. Fits of a power law to these spectra over wave numbers 10-36 and 10-26 give values of b which are independent of season, hemisphere, and latitude band, to within statistical uncertainties. The observed values of b are about 3.6, as compared to theoretical predictions of 3.

Martin, Russell L.↗
NASA NTRS1984

Interpretation of the lunar microwave brightness temperature spectrum - Feasibility of orbital heat flow mapping

The feasibility of an orbital mapping of heat flow by means of microwave radiometers is examined on the basis of a detailed model of the lunar regolith. The results obtained are discussed in terms of contributions of physical properties and regolith structure to the spectral signature of lunation-averaged brightness temperatures. Even for regions for which remote heat flow detection is not feasible, detailed interpretations of remote measurements in terms of physical properties and regolith structure could be made by means of the model presented. Surface and subsurface scattering effects are considered in evaluating possible wavelength dependencies of the microwave emissivity.

Keihm, S. J.↗
NASA NTRS2014

In-situ Microwave Brightness Temperature Variability from Ground-based Radiometer Measurements at Dome C in Antarctica Induced by Wind-formed Features

Space-borne microwave radiometers are among the most useful tools to study snow and to collect information on the Antarctic climate. They have several advantages over other remote sensing techniques: high sensitivity to snow properties of interest (temperature, grain size, density), subdaily coverage in the polar regions, and their observations are independent of cloud conditions and solar illumination. Thus, microwave radiometers are widely used to retrieve information over snow-covered regions. For the Antarctic Plateau, many studies presenting retrieval algorithms or numerical simulations have assumed, explicitly or not, that the subpixel-scale heterogeneity is negligible and that the retrieved properties were representative of whole pixels. In this presentation, we investigate the spatial variations of brightness temperature over arange of a few kilometers in the Dome C area (Antarctic Plateau).

Antarctica↗