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At least 1,135 records · Page 63

Preliminary OARE absolute acceleration measurements on STS-50

On-orbit Orbital Acceleration Research Experiment (OARE) data on STS-50 was examined in detail during a 2-day time period. Absolute acceleration levels were derived at the OARE location, the orbiter center-of-gravity, and at the STS-50 spacelab Crystal Growth Facility. The tri-axial OARE raw acceleration measurements (i.e., telemetered data) during the interval were filtered using a sliding trimmed mean filter in order to remove large acceleration spikes (e.g., thrusters) and reduce the noise. Twelve OARE measured biases in each acceleration channel during the 2-day interval were analyzed and applied to the filtered data. Similarly, the in situ measured x-axis scale factors in the sensor's most sensitive range were also analyzed and applied to the data. Due to equipment problem(s) on this flight, both y- and z- axis sensitive range scale factors were determined in a separate process (using the OARE maneuver data) and subsequently applied to the data. All known significant low-frequency corrections at the OARE location (i.e., both vertical and horizontal gravity-gradient, and rotational effects) were removed from the filtered data in order to produce the acceleration components at the orbiter's center-of-gravity, which are the aerodynamic signals along each body axes. Results indicate that there is a force of unknown origin being applied to the Orbiter in addition to the aerodynamic forces. The OARE instrument and all known gravitational and electromagnetic forces were reexamined, but none produce the observed effect. Thus, it is tentatively concluded that the Orbiter is creating the environment observed.

Blanchard, Robert C.↗

Sensitivity of Middle Atmospheric Analyses to the Representation of Gravity-Wave Drag in the DAO's Data Assimilation System

The damping of mesoscale gravity waves has important effects on the global circulation, structure, and composition of the atmosphere. A number of assimilation and forecast experiments have been conducted to examine the sensitivity of meteorological analyses and forecasts to the representation of gravity wave impacts in a data assimilation system (DAS). The experiments were conducted with the Finite-Volume (FV) DAS developed at NASA's Data Assimilation Office (DAO), The main purpose of this research is to determine the optimal combination of wave number, phase speed, wavelength, etc. for representing gravity-wave drag (GWD) in FVDAS. The GWD included in FVDAS includes a spectrum of waves, as would be forced by topography and transient motions (e.g., convection) in the troposphere. The sensitivity experiments are performed by modifying several parameters, such as the number of waves allowed, their wavelength, the background stress amplitude, etc. The results show that the assimilated fields are very sensitive to the number of gravity waves represented in the system, especially at high latitudes of the middle and upper stratosphere and mesosphere in winter. The analyzed stratopause temperature varies by up to 10K when the GWD scheme is modified from a multiple-wave scheme (using a stationary wave and waves with phase speeds of 10, 20, 30 and 40 m/s in each direction) to a single, stationary wave. Insight into the reality of the various versions of the GWD can be obtained by examining the "Observation minus Forecast" residuals from the FVDAS.

Li, Shuhua↗

Heterogeneous Multi-Domain Dataset Synthesis to Facilitate Privacy and Risk Assessments in Smart City IoT

The emergence of the Smart Cities paradigm and the rapid expansion and integration of Internet of Things (IoT) technologies within this context have created unprecedented opportunities for high-resolution behavioral analytics, urban optimization, and context-aware services. However, this same proliferation intensifies privacy risks, particularly those arising from cross-modal data linkage across heterogeneous sensing platforms. To address these challenges, this paper introduces a comprehensive, statistically grounded framework for generating synthetic, multimodal IoT datasets tailored to Smart City research. The framework produces behaviorally plausible synthetic data suitable for preliminary privacy risk assessment and as a benchmark for future re-identification studies, as well as for evaluating algorithms in mobility modeling, urban informatics, and privacy-enhancing technologies. As part of our approach, we formalize probabilistic methods for synthesizing three heterogeneous and operationally relevant data streams—cellular mobility traces, payment terminal transaction logs, and Smart Retail nutrition records—capturing the behaviors of a large number of synthetically generated urban residents over a 12-week period. The framework integrates spatially explicit merchant selection using K-Dimensional (KD)-tree nearest-neighbor algorithms, temporally correlated anchor-based mobility simulation reflective of daily urban rhythms, and dietary-constraint filtering to preserve ecological validity in consumption patterns. In total, the system generates approximately 116 million mobility pings, 5.4 million transactions, and 1.9 million itemized purchases, yielding a reproducible benchmark for evaluating multimodal analytics, privacy-preserving computation, and secure IoT data-sharing protocols. To show the validity of this dataset, the underlying distributions of these residents were successfully validated against reported distributions in published research. We present preliminary uniqueness and cross-modal linkage indicators; comprehensive re-identification benchmarking against specific attack algorithms is planned as future work. This framework can be easily adapted to various scenarios of interest in Smart Cities and other IoT applications. By aligning methodological rigor with the operational needs of Smart City ecosystems, this work fills critical gaps in synthetic data generation for privacy-sensitive domains, including intelligent transportation systems, urban health informatics, and next-generation digital commerce infrastructures.

IoT↗

Attentional sensitivity and asymmetries of vertical saccade generation in monkey

The first goal of this study was to systematically document asymmetries in vertical saccade generation. We found that visually guided upward saccades have not only shorter latencies, but higher peak velocities, shorter durations and smaller errors. The second goal was to identify possible mechanisms underlying the asymmetry in vertical saccade latencies. Based on a recent model of saccade generation, three stages of saccade generation were investigated using specific behavioral paradigms: attention shift to a visual target (CUED paradigm), initiation of saccade generation (GAP paradigm) and release of the motor command to execute the saccade (DELAY paradigm). Our results suggest that initiation of a saccade (or "ocular disengagement") and its motor release contribute little to the asymmetry in vertical saccade latency. However, analysis of saccades made in the CUED paradigm indicated that it took less time to shift attention to a target in the upper visual field than to a target in the lower visual field. These data suggest that higher attentional sensitivity to targets in the upper visual field may contribute to shorter latencies of upward saccades.

NASA Discipline Neuroscience↗

Bias due to neutrinos must not uncorrect'd go

It is a well known fact that galaxies are biased tracers of the distribution of matter in the Universe. The galaxy bias is usually factored as a function of redshift and scale, and approximated as being scale-independent on large, linear scales. In cosmologies with massive neutrinos, the galaxy bias defined with respect to the total matter field (cold dark matter, baryons, and non-relativistic neutrinos) also depends on the sum of the neutrino masses M ν , and becomes scale-dependent even on large scales. This effect has been usually neglected given the sensitivity of current surveys. Yet, it becomes a severe systematic for future surveys aiming to provide the first detection of non-zero M ν . The effect can be corrected for by defining the bias with respect to the density field of cold dark matter and baryons, rather than the total matter field. In this work, we provide a simple prescription for correctly mitigating the neutrino-induced scale-dependent bias effect in a practical way. We clarify a number of subtleties regarding how to properly implement this correction in the presence of redshift-space distortions and non-linear evolution of perturbations. We perform a Markov Chain Monte Carlo analysis on simulated galaxy clustering data that match the expected sensitivity of the Euclid survey. We reveal that the neutrino-induced scale-dependent bias can lead to important shifts in both the inferred mean value of M ν , as well as its uncertainty, and provide an analytical explanation for the magnitude of the shifts. We show how these shifts propagate to the inferred values of other cosmological parameters correlated with M ν , such as the cold dark matter physical density Ω cdm h 2 and the scalar spectral index n s . In the end, we find that correctly accounting for the neutrino-induced scale-dependent bias will be of crucial importance for future galaxy clustering analyses. We encourage the cosmology community to correctly account for this effect using the simple prescription we present in our work. The tools necessary to easily correct for the neutrino-induced scale-dependent bias will be made publicly available in an upcoming release of the Boltzmann solver CLASS.

79 ASTRONOMY AND ASTROPHYSICS↗

Ice Shape Analysis of an eVTOL Propeller in Forward Flight at the NASA Glenn Icing Research Tunnel

Advanced Air Mobility (AAM) introduces many novel electric vertical takeoff and landing (eVTOL) aircraft configurations for which the effect of icing is not well understood. While icing computational tools have often aided in the design and certification of conventional aircraft, experimental data is needed to support the development and validation of such tools for eVTOL applications. To investigate the icing phenomenon relevant to eVTOL aircraft, NASA Glenn Research Center developed a general-purpose propeller test stand for conducting fundamental icing research on electrically driven propellers in the Icing Research Tunnel (IRT). A 10-day test entry in the IRT was completed in March, 2023, with the goal of generating ice accretions on a non-proprietary propeller geometry under well-characterized conditions. Three carbon fiber propellers of diameters 0.610, 0.711, and 0.914 m (24, 28, and 36 in) were used during the test. Various parametric sweeps of cloud and operating conditions were performed to evaluate the sensitivity of the parameters on the resulting ice accretion characteristics such as ice thickness, mass, location (impingement limits), and type (glaze vs rime). Ice shapes were reviewed for their repeatability, correctness of trends, and sensitivity to parameter variations. The data from the test is being used to support the development of the ice accretion solver, GlennICE.

Icing↗

Ice Shape Analysis of an eVTOL Propeller in Forward Flight at the NASA Glenn Icing Research Tunnel

Advanced Air Mobility (AAM) introduces many novel electric vertical takeoff and landing (eVTOL) aircraft configurations for which the effect of icing is not well understood. While icing computational tools have often aided in the design and certification of conventional aircraft, experimental data is needed to support the development and validation of such tools for eVTOL applications. To investigate the icing phenomenon relevant to eVTOL aircraft, NASA Glenn Research Center developed a general-purpose propeller test stand for conducting fundamental icing research on electrically driven propellers in the Icing Research Tunnel (IRT). A 10-day test entry in the IRT was completed in March, 2023, with the goal of generating ice accretions on a non-proprietary propeller geometry under well-characterized conditions. Three carbon fiber propellers of diameters 0.610, 0.711, and 0.914 m (24, 28, and 36 in) were used during the test. Various parametric sweeps of cloud and operating conditions were performed to evaluate the sensitivity of the parameters on the resulting ice accretion characteristics such as ice thickness, mass, location (impingement limits), and type (glaze vs rime). Ice shapes were reviewed for their repeatability, correctness of trends, and sensitivity to parameter variations. The data from the test is being used to support the development of the ice accretion solver, GlennICE.

Icing↗

Modeling the Uncertainties of Solar System Ephemerides for Robust Gravitational-wave Searches with Pular-timing Arrays

The regularity of pulsar emissions becomes apparent once we reference the pulses’ times of arrivals to the inertial rest frame of the solar system. It follows that errors in the determination of Earthʼs position with respect to the solar system barycenter can appear as a time-correlated bias in pulsar-timing residual time series, affecting the searches for low-frequency gravitational waves performed with pulsar-timing arrays. Indeed, recent array data sets yield different gravitational-wave background upper limits and detection statistics when analyzed with different solar system ephemerides. Crucially, the ephemerides do not generally provide usable error representations. In this article, we describe the motivation, construction, and application of a physical model of solar system ephemeris uncertainties, which focuses on the degrees of freedom (Jupiterʼs orbital elements) most relevant to gravitational-wave searches with pulsar-timing arrays. This model, BAYESEPHEM, was used to derive ephemeris-robust results in NANOGravʼs 11 yr stochastic-background search, and it provides a foundation for future searches by NANOGrav and other consortia. The analysis and simulations reported here suggest that ephemeris modeling reduces the gravitational-wave sensitivity of the 11 yr data set and that this degeneracy will vanish with improved ephemerides and with pulsar-timing data sets that extend well beyond a single Jovian orbital period.

M Vallisneri↗

Extension of SCALE/Sampler’s sensitivity index for the assessment of cross section, fission yield, and decay data uncertainties

Accurate prediction of nuclide compositions and neutron and gamma sources and spectra for fresh and spent nuclear fuel through computational modeling and simulations is the basis for safeguards instruments design, optimization, and calibration, and for validation of the measured responses. The accuracy of these simulations can be significantly impacted by uncertainties in input parameters to the applied computer code. Input parameters are, for example, dimensions, material compositions, and temperatures of the model. Additionally, important but sometimes neglected input parameters for simulations of nuclear systems are the nuclear data that include nuclear reaction cross sections, fission product yields, and decay data. It has been shown that uncertainties of calculated results are dominated by uncertainties of these nuclear data.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A bimodal search strategy for SETI

A SETI plan has been developed jointly by the NASA Ames Research Center and the Jet Propulsion Laboratory with the objective of both observing all potential sites to some limiting equivalent isotropic radiated power and surveying with greater sensitivity a set of especially promising sites. The bimodal search strategy assumes that existing radio telescopes with state-of-the-art receivers and data processing devices will have the sensitivity to explore the vicinity of nearby stars for similar transmitters and the entire galaxy for more powerful signals. The discrete source observational mode is designed to observe 773 F, G and K-type stars within 25 pc of the sun at frequencies from 1.2 to 3 GHz and spot bands between 3 and 25 GHz with sensitivities from 10 to the -25th to 10 to the -27th W/sq m. The sky survey is intended to search the entire celestial sphere between 1.2 and 10 GHz and spot bands between 10 and 25 GHz at a sensitivity limit of approximately 10 to the -23rd times the square root of the frequency. Instrumentation for the surveys includes a large multichannel spectrum analyzer. Immediate goals of the program are the investigation of the RF background at high resolution and the development of signal detection algorithms, with operation to begin in 1984.

Gulkis, S.↗

Automatic terrain elevation mapping and registration

Optimum radar illumination geometries for stereoscopic analysis of surface topography are determined. Correlation and image processing experiments on synthetic aperture radar (SAR) data for improved information extraction are conducted. Model of the geometry of the multiple SIR-B views of the Earth are developed the sensitivity of the derived terrain altitude data to the various system parameters is established. The limits of accuracy of terrain data achievable with shuttle imaging radar (SIR-B) are derived. Algorithms for matching multiple SIR-B images to generate digital terrain maps are developed. Finally, the use of such terrain maps in geometric correction and registration of SIR-B and LANDSAT Thematic Mapper data is demonstrated.

Ramapriyan, H. K.↗

Fertilization of sea urchin eggs and sperm motility are negatively impacted under low hypergravitational forces significant to space flight

Sperm and other flagellates swim faster in microgravity (microG) than in 1 G, raising the question of whether fertilization is altered under conditions of space travel. Such alterations have implications for reproduction of plant and animal food and for long-term space habitation by man. We previously demonstrated that microG accelerates protein phosphorylation during initiation of sperm motility but delays the sperm response to the egg chemotactic factor, speract. Thus sperm are sensitive to changes in gravitational force. New experiments using the NiZeMi centrifugal microscope examined whether low hypergravity (hyperG) causes effects opposite to microG on sperm motility, signal transduction, and fertilization. Sperm % motility and straight-line velocity were significantly inhibited by as little as 1.3 G. The phosphorylation states of FP130, an axonemal phosphoprotein, and FP160, a cAMP-dependent salt-extractable flagellar protein, both coupled to motility activation, showed a more rapid decline in hyperG. Most critically, hyperG caused an approximately 50% reduction in both the rate of sperm-egg binding and fertilization. The similar extent of inhibition of both fertilization parameters in hyperG suggests that the primary effect is on sperm rather than eggs. These results not only support our earlier microG data demonstrating that sperm are sensitive to small changes in gravitational forces but more importantly now show that this sensitivity affects the ability of sperm to fertilize eggs. Thus, more detailed studies on the impact of space flight on development should include studies of sperm function and fertilization.

NASA Discipline Developmental Biology↗

Data and Scripts associated with “Lambda-PFLOTRAN: Workflow for Incorporating Organic Matter Chemistry Informed by Ultra High Resolution Mass Spectrometry into Biogeochemical Modeling.”

This data package is associated with the publication “Lambda-PFLOTRAN: Workflow for Incorporating Organic Matter Chemistry Informed by Ultra High Resolution Mass Spectrometry into Biogeochemical Modeling” submitted to Geoscientific Model Development (Muller et al., 2024). In this manuscript, organic matter chemistry and thermodynamics are directly connected to reactive transport simulators through the newly developed Lambda-PFLOTRAN (Parallel Reactive Flow and Transport model) workflow tool that succinctly incorporates organic matter chemistry data generated from Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) into reaction networks to simulate aerobic respiration of the organic matter and the resulting biogeochemistry. Lambda-PFLOTRAN is a python-based workflow, executed through a Jupyter Notebook interface, that digests raw FTICR-MS data, develops a representative reaction network based on substrate-explicit thermodynamic modeling (also termed lambda modeling due to its key thermodynamic parameter λ used therein), and completes a biogeochemical simulation with the open source, reactive flow, and transport code PFLOTRAN. This data package contains Jupyter Notebook based workflows for two test cases for running biogeochemical simulations of organic matter oxidation identified by FTICR-MS. It contains four primary folders (workflow, data, src, and analysis), a file-level metadata file (Muller_2024_Lambda_PFLOTRAN_Manuscript_Data_Package_flmd.csv) that lists all the files contained in this data package with a short description of each, and a data dictionary (Muller_2024_Lambda_PFLOTRAN_Manuscript_Data_Package_dd.csv) file that describes the tabular column headers. The ‘workflow’ folder contains the Jupyter Notebook based workflows for running the lambda analysis, PFLOTRAN simulation, sensitivity analysis and parameter estimation. The ‘data’ folder contains the FTICR-MS data, initial conditions, and incubation data for test cases 1 and 2 in folders titled ‘WHONDRS’ and ‘Colloids’, respectively. The data folder also has a ‘Database’ folder containing a reaction network for bulk organic matter (assumed to be CH2O) and a general database for PFLOTRAN (hanford_rxn_network). The CH2O reaction network defines bulk organic matter oxidation. Biogeochemical simulations are completed for both the lambda binned organic matter and bulk organic matter reaction networks. The ‘hanford_rxn_network’ database includes information required for PFLTORAN simulations including ion size, molar mass, and charge of the aqueous species, gases, and minerals phases. The ‘src’ folder contains python source codes for performing lambda analysis, PFLOTRAN simulation, sensitivity analysis and parameter estimation. The ‘analysis’ folder contains outputs from the test cases 1 and 2 including lambda analysis, PFLOTRAN runs and the calibration results.

54 ENVIRONMENTAL SCIENCES↗

A Global Map of Mars' Crustal Magnetic Field Based on Electron Reflectometry

One of the great surprises of the Mars Global Surveyor mission was the discovery of intensely magnetized crust. Magnetic sources on Mars are at least ten times stronger than their terrestrial counterparts, probably requiring large volumes of coherently magnetized material, very strong remanence, or both. Although much of the attention so far has been placed on the strong crustal fields in the southern highlands, magnetic sources do exist in the younger low-lying plains. The strength and morphology of these sources could yield clues to the thermal and magnetic history of the northern plains. Low altitude (approx. 100 km) Magnetometer (MAG) data obtained during aerobraking have the greatest spatial resolution and sensitivity for identifying crustal magnetic sources from orbit, but those data are sparse and therefore limit the ability to discern morphology. Fully sampled MAG data obtained in the 400-km altitude mapping orbit have been differenced with respect to latitude (Br/Lat) to minimize the influence of induced fields from the solar wind interaction and thus enhance the sensitivity to weak crustal sources. Here we describe independent results from the Electron Reflectometer (ER), which remotely measures the magnetic field intensity at approx. 170 km altitude, and is roughly seven times more sensitive to crustal magnetic sources than measurements of Br from the mapping orbit.

Mitchell, D. L.↗

Standardising the “Gregory method” for calculating equilibrium climate sensitivity

The equilibrium climate sensitivity (ECS) – the equilibrium global mean temperature response to a doubling of atmospheric CO 2 – is a high-profile metric for quantifying the Earth system's response to human-induced climate change. A widely applied approach to estimating the ECS is the “Gregory method” (Gregory et al., 2004), which uses an ordinary least squares (OLS) regression between the net radiative flux, N, and surface air temperature anomalies, ΔT, from a 150 year experiment in which atmospheric CO 2 concentrations are quadrupled. The ECS is determined by extrapolating the linear fit to N=0, i.e. the ΔT-intercept, indicating the point at which the system is back in equilibrium. This method has been used to compare ECS estimates across the CMIP5 and CMIP6 ensembles and will likely be a key diagnostic for CMIP7. Despite its widespread application, there is little consistency or transparency between studies in how the climate model data is processed prior to the regression, leading to potential discrepancies in ECS estimates. We identify 32 alternative data processing pathways, varying by differences in global mean weighting, net radiative flux variable, anomaly calculation method, and linear regression fit. Using 44 CMIP6 models, we systematically assess the impact of these choices on ECS estimates and calculate uncertainty ranges using two bootstrap approaches. While the inter-model ECS range is insensitive to the data processing pathway, individual outlier models exhibit notable differences. Approximating a model's native grid cell area (if irregular) with cosine of the latitude can decrease the ECS by 11 %, the choice of N-variable can change the ECS by 6 %, and some anomaly calculation methods can introduce spurious temporal correlations in the processed data. Beyond data processing choices, we also evaluate an alternative linear regression method – total least squares (TLS) – which has a more statistically robust basis than OLS. However, for consistency with previous literature, and given TLS may reduce the ECS compared to OLS (by up to 24 %), thereby making a known bias in the Gregory method worse, we do not feel there is sufficient clarity to recommend a transition to TLS in all cases. To improve reproducibility and comparability in future studies, we recommend a standardised Gregory method: weighting the global mean by cell area, using the top of the atmosphere (as opposed to the top of model) N-variable, and calculating anomalies by first applying a rolling average to the preindustrial control timeseries then subtracting from the raw CO 2 quadrupling experiment. This approach accounts for model drift while reducing noise in the data to best meet the pre-conditions of the linear regression. While CMIP6 results of the multi-model mean ECS appear insensitive to these processing choices, similar assumptions may not hold for CMIP7, underscoring the need for standardised data preparation in future climate sensitivity assessments.

Geosciences↗

Laboratory test data on the stability of the STIS MAMAs

STIS has two MAMA detectors systems with distinctly different tube configurations. The first (designated BAND 1) has an opaque CsI photocathode deposited on the microchannel plate (MCP) providing wavelength coverage from 1150A to 1700A. The other MAMA (designated BAND 2) has a semitransparent CS2Te photocathode deposited on the faceplate in close proximity to the input of the MCP. It covers the 1650A to 3100A bandpass and serves as a backup for the short wavelength detector. Laboratory test data indicate that both of these detectors have good sensitivity, have good uniformity and provide stable response, making each capable of collecting data with a signal-to-noise ratio in excess of 100 per Space Telescope Imaging Spectrograph (STIS) optical resolution element. Over a multiyear development effort, a substantial body of laboratory test data (more than 6 GBytes spanning more than 6 years of collection) has accumulated on more than a dozen fabricated tubes. These tests even included a few destructive evaluations to examine the limitations and operating life. In addition, analyses where conducted regarding impact caused by the specified electronic tolerances and expected changes in the Hubble Space Telescope (HST) thermal environment. Perhaps the simplest test of stability is to collect a sequence of images, each with a uniform illumination, and use these individual "flat fields" to remove the pixel-to-pixel sensitivity in the other flat fields. These sequences typically spanned 3-5 weeks of time. The detectors are very stable, allowing the pixel-to-pixel sensitivity to be removed with good precision. The STIS specification for stability is 1% (sufficient for data with a S/N = 100) over a 1 week period and 2% over 30 days. All Engineering Model Units as well as Flight Detectors tested exceeded this specification.

Joseph, Charles L.↗

Passive Microwave Algorithms for Sea Ice Concentration: A Comparison of Two Techniques

The most comprehensive large-scale characterization of the global sea ice cover so far has been provided by satellite passive microwave data. Accurate retrieval of ice concentrations from these data is important because of the sensitivity of surface flux(e.g. heat, salt, and water) calculations to small change in the amount of open water (leads and polynyas) within the polar ice packs. Two algorithms that have been used for deriving ice concentrations from multichannel data are compared. One is the NASA Team algorithm and the other is the Bootstrap algorithm, both of which were developed at NASA's Goddard Space Flight Center. The two algorithms use different channel combinations, reference brightness temperatures, weather filters, and techniques. Analyses are made to evaluate the sensitivity of algorithm results to variations of emissivity and temperature with space and time. To assess the difference in the performance of the two algorithms, analyses were performed with data from both hemispheres and for all seasons. The results show only small differences in the central Arctic in but larger disagreements in the seasonal regions and in summer. In some ares in the Antarctic, the Bootstrap technique show ice concentrations higher than those of the Team algorithm by as much as 25%; whereas, in other areas, it shows ice concentrations lower by as much as 30%. The The differences in the results are caused by temperature effects, emissivity effects, and tie point differences. The Team and the Bootstrap results were compared with available Landsat, advanced very high resolution radiometer (AVHRR) and synthetic aperture radar (SAR) data. AVHRR, Landsat, and SAR data sets all yield higher concentrations than the passive microwave algorithms. Inconsistencies among results suggest the need for further validation studies.

Comiso, Josefino C.↗