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NASA NTRS1992

The effect of severe storms on the ice cover of the northern Tatarskiy Strait

Passive microwave images from the Special Sensor Microwave Imager are used to study the volume of ice and sea-bottom water in the Japan Sea as affected by winds and severe storms. The data set comprises brightness temperatures gridded on a polar stereographic projection, and the processing is accomplished with a linear algorithm by Cavalieri et al. (1983) based on the vertically polarized 37-GHz channel. The expressions for calculating heat fluxes and downwelling radiation are given, and ice-cover fluctuations are correlated with severe storm events. The storms generate large transient polynya that occur simultaneously with the strongest heat fluxes, and severe storms are found to contribute about 25 percent of the annual introduction of 25 cu km of ice in the region. The ice production could lead to the renewal of enough sea-bottom water to account for the C-14 data provided, and the generation of Japan Sea bottom water is found to vary directly with storm activity.

Martin, Seelye↗

NASA NTRS1992

Convective climatology over the southwest U.S. and Mexico from passive microwave and infrared data

Passive microwave data from the Special Sensor Microwave Imager (SSM/I) were used to estimate the amount of rainfall in the June-August season for the regions of the southwest U.S. and Mexico, and the results are compared to rain-gauge observations and to IR climatologies of Maddox et al. (1992), using both the hourly IR data and IR data sampled at the time of the overpass of the SSM/I. A comparison of the microwave climatology with monthly rainfall measured by the climatological gage network over several states of western Mexico resulted in a 0.63 correlation and a large (482 mm) bias, due to sampling and the incongruity of rain gages and satellite estimates. A comparison between the IR and microwave data showed that the IR tended toward higher percentages along the coast compared to the microwave.

Negri, Andrew J.↗

NASA NTRS1994

Passive microwave structure of severe tornadic storms on 16 November 1987

Passive microwave observations using the Special Sensor Microwave/Imager (SSM/I) are presented for severe tornadic storms in the lower midwestern United States on 16 November 1987. These measurements are compared with Geostationary Operational Environmental Satellite infrared (IR) measurements for the same case. The IR observations had a classic 'V' cold feature commonly associated with severe Midwest thunderstorms. The minimum microwave brightness temperatures at 86 GHz, which primarily respond to ice scattering by larger ice particles, were located in the convective region and the warm interior of the anvil top, between the arms of the IR V feature. The interior warm region was the only portion of the entire anvil region that had high 86-GHz polarization difference temperatures. Microphysical implications of these multispectral observations are discussed. The observations suggest that there are large variations of ice microphysical characteristics spatially and vertically in the anvil region. These observations are discussed in the context of previous dynamical and microphysical hypotheses on the IR V feature.

Heymsfield, Gerald M.↗

NASA NTRS1999

A Prototype MODI- SSM/I Snow Mapping Algorithm

Data in the wavelength range 0.545 - 1.652 microns from the Moderate Resolution Imaging Spectroradiometer (MODIS), to be launched aboard the Earth Observing System (EOS) Terra in the fall of 1999, will be used to map daily global snow cover at 500m resolution. However, during darkness, or when the satellite's view of the surface is obscured by cloud, snow cover cannot be mapped using MODIS data. We show that during these conditions, it is possible to supplement the MODIS product by mapping the snow cover using passive microwave data from the Special Sensor Microwave Imager (SSM/I), albeit with much poorer resolution. For a 7-day time period in March 1999, a prototype MODIS snow-cover product was compared with a prototype MODIS-SSM/I product for the same area in the mid-western United States. The combined MODIS-SSM/I product mapped 9% more snow cover than the MODIS-only product.

Tait, Andrew B.↗

NASA NTRS2003

Parameters Describing Earth Observing Remote Sensing Systems

The Earth science community needs to generate consistent and standard definitions for spatial, spectral, radiometric, and geometric properties describing passive electro-optical Earth observing sensors and their products. The parameters used to describe sensors and to describe their products are often confused. In some cases, parameters for a sensor and for its products are identical; in other cases, these parameters vary widely. Sensor parameters are bound by the fundamental performance of a system, while product parameters describe what is available to the end user. Products are often resampled, edge sharpened, pan-sharpened, or compressed, and can differ drastically from the intrinsic data acquired by the sensor. Because detailed sensor performance information may not be readily available to an international science community, standardization of product parameters is of primary performance. Spatial product parameters described include Modulation Transfer Function (MTF), point spread function, line spread function, edge response, stray light, edge sharpening, aliasing, ringing, and compression effects. Spectral product parameters discussed include full width half maximum, ripple, slope edge, and out-of-band rejection. Radiometric product properties discussed include relative and absolute radiometry, noise equivalent spectral radiance, noise equivalent temperature diffenence, and signal-to-noise ratio. Geometric product properties discussed include geopositional accuracy expressed as CE90, LE90, and root mean square error. Correlated properties discussed include such parameters as band-to-band registration, which is both a spectral and a spatial property. In addition, the proliferation of staring and pushbroom sensor architectures requires new parameters to describe artifacts that are different from traditional cross-track system artifacts. A better understanding of how various system parameters affect product performance is also needed to better ascertain the utility of existing datasets and products as well as to specify the performance of new sensors and products. Examples of simulations performed for the Landsat Data Continuity Mission illustrate how various parameters affect system and product performance. Specific examples include the effects of ground sample distance, MTF, and band-to-band registration on various products.

Zanoni, Vicki↗

NASA NTRS2016

GN and C Subsystem Concept for Safe Precision Landing of the Proposed Lunar MARE Robotic Science Mission

The Lunar MARE (Moon Age and Regolith Explorer) Discovery Mission concept targets delivery of a science payload to the lunar surface for sample collection and dating. The mission science is within a 100-meter radius region of smooth lunar maria terrain near Aristarchus crater. The location has several small, sharp craters and rocks that present landing hazards to the spacecraft. For successful delivery of the science payload to the surface, the vehicle Guidance, Navigation and Control (GN&C) subsystem requires safe and precise landing capability, so design infuses the NASA Autonomous precision Landing and Hazard Avoidance Technology (ALHAT) and a gimbaled, throttleable LOX/LCH4 main engine. The ALHAT system implemented for Lunar MARE is a specialization of prototype technologies in work within NASA for the past two decades, including a passive optical Terrain Relative Navigation (TRN) sensor, a Navigation Doppler Lidar (NDL) velocity and range sensor, and a Lidar-based Hazard Detection (HD) sensor. The landing descent profile is from a retrograde orbit over lighted terrain with landing near lunar dawn. The GN&C subsystem with ALHAT capabilities will deliver the science payload to the lunar surface within a 20-meter landing ellipse of the target location and at a site having greater than 99% safety probability, which minimizes risk to safe landing and delivery of the MARE science payload to the intended terrain region.

MARE (Moon Age and Regolith Explorer)↗

NASA NTRS2017

SIIOS in Alaska: Testing an "In-Vault" Option for a Europa Lander Seismometer Experiment

The icy moons of Europa and Enceladus are thought to have global subsurface oceans in contact with mineral-rich silicate interiors, likely providing the three ingredients needed for life as we know it: liquid water, essential chemicals, and a source of energy. The possibility of life forming in their subsurface oceans relies in part on transfer of oxidants from the irradiated ice surface to the sheltered ocean below. Constraining the mechanisms and location of material exchange between the ice surface, the ice shell, and the subsurface ocean, however, is not possible without knowledge of ice thickness and liquid water depths. In a future lander-based experiment seismic measurements will be a key geophysical tool for obtaining this critical knowledge. The Seismometer to Investigate Ice and Ocean Structure (SIIOS) field-tests flight-ready technologies and develops the analytical methods necessary to make a seismic study of Europa and Enceladus a reality. We have been performing small-array seismology with a flight-candidate sensor in analog environments that exploit passive sources. Determining the depth to a subsurface ocean and any intermediate bodies of water is a priority for Ocean Worlds missions as it allows assessment of the habitability of these worlds and provides vital information for evaluating the spacecraft technologies required to access their oceans.

Bray, Veronica J.↗

NASA NTRS2019

Challenges and Solutions for Precision Solar Pointing on the ISS for the TSIS Instrument

The International Space Station offers an attractive platform for external payloads in many regards, but its large, complex structure is challenging for payloads that require precise, unobstructed pointing. As an instrument that measures solar irradiance on a continual basis, the TSIS payload was designed to robustly account for these ISS challenges and is now performing its mission on the ISS with great success.This paper first describes how TSIS was able to measure the ISS background jitter using High-rate Fine Sun Sensor data that was taken during passive solar transits through its field of view. The measurements showed that ISS jitter at the TSIS location on ELC-3 Site 5 is relatively benign with less than 4 arcseconds 1 at frequencies less than 0.5 Hz. This value is lower than previous estimates but agrees well with recent measurements from other external payloads, including OPALS and SAGE III. Because TSIS was designed to be robust to base motion jitter, it has achieved less than 4 arcseconds 1 of pointing error, which provides an extremely precise pointing platform for the solar irradiance measurements. The other challenging ISS characteristic is its large, complex structure that obscures solar viewing at sunrise and sunset from the zenith-facing location of TSIS. Although TSIS was able to predict solar viewing durations during the design phase with relatively high accuracy, the exact timing and causes of obscuration were difficult to predict and understand after TSIS began operating on the ISS. To aid in the understanding of blockage by ISS structure, detailed obscuration maps were created using HFSS measurements that clearly show the exact gimbal angles where blockage occurs and the specific structural features of the ISS that cause the blockage. These maps have helped TSIS to maximize its solar tracking durations each orbit, which has supported the mission in meeting its science objectives.

background jitter↗

NASA NTRS2021

JPSS-1 ATMS Post-launch Active Geolocation Analysis

A NOAA-20 (N20) ATMS active geolocation test was performed around Jan. 2018 with 24 pre-selected coastline crossing scenes. After comprehensive analysis of ATMS stare data and the corresponding VIIRS data, the ATMS pitch, roll and yaw pointing angle errors are found from the nadir perpendicular, the nadir oblique shallow angle, and the off-nadir perpendicular coastline crossing data, respectively. In this study, we first determine the ATMS radiometric coastline crossing time by using the ATMS radiometric count data. Since the coastline can be located anywhere within one ATMS FOV from the passive (regular scanning) geolocation data, depending on the scan starting time, it is not a valid assumption for the inflection point being the same as the coastline location. Consequently, using the passive geolocation data to validate the sensor’s on-orbit pointing angle performance is limited. After finding the ATMS radiometric coastline crossing time from the ATMS data, we compare it with the VIIRS effective time stamp (see main text). Specifically the VIIRS M3, M4 & M5 (true color) & M15 and M16 bands (thermal) data have a much smaller footprint size. Using the differences of the ATMS and VIIRS (effective) coastlines crossing times, the N20 ATMS pitch, roll and yaw pointing angle errors are found to be -0.09o, -0.24o and 0.28o, respectively. To determine ATMS geolocation properly, these on-orbit pointing errors need to be corrected, adding to the ATMS SDR Processing Coefficient Table, and passed on to the operational geolocation processing code.

Active Geolocation↗

NASA NTRS1996

Sea Ice Identification Using Dual-Polarized Ku-Band Scatterometer Data

Maps of sea ice have been based on a combination of observations from aircraft and ships, and infrared and passive microwave data from various spaceborne sensors. Described here is the potential of using dual-polarized scatterometer returns from the polar oceans to identify the edge of the ice cover. This ice edge could be used to compute the ice extent, which may be a useful indicator of climatic changes.

Ocean↗

NASA NTRSDate not supplied

Summary of Technical Interchange Meetings (TIMs) Designed to Enable Earth Independent Medical Operations (EIMO)

The Exploration Medical Capability Element (ExMC) in NASA’s Human Research Program hosted a series of TIMs in 2023-2024 designed to stimulate discussion around specific topics with the goal of enabling EIMO. In context of the thematic constituent elements of EIMO, namely pre-mission planning, acute/emergent/prolonged medical decision making, supply/resource management and task load management, subject matter experts from industry, academia and government (NASA and other Agencies) provided valuable and actionable guidance and recommendations. Earth-based medical experts will remain indispensable for pre-mission planning, however, management of acute/emergent medical contingencies will require a gradual transition of medical care and decision making from terrestrial to space-based assets to enable support of astronaut health and performance and reduce overall mission risk. Key to achieving these enhancements is providing an integrated data system platform capable of utilizing multiple data streams in concert with a variety of on-board databases and passive monitoring of video and wearable sensors to enable a multi-modal, agentic AI-based clinical decision support system (CDSS) to support crew medical officer (CMO) medical decision-making. The EIMO series of TIMs (I-V) have proven to be instructive and portend a significant paradigm shift will be necessary to maintain crew health and performance on exploration class missions. Importantly, since the expected paradigm shift will be significantly different from the methods of operation that have been employed for the majority of missions from the inception of human spaceflight to date, any proposed methods must be deployed in the setting of ongoing operations early and be “tested, reviewed and practiced” while reliable back-up is available to facilitate an Enterprise-wide level of comfort and acceptance. Serious constraints on data transmission coupled with a large and expanding universe of on-board medical informatics data streams will necessitate implementation of a CDSS to supplant the current reliance on support provided by ground-based SMEs. Establishment of trust in the system by CMO/crew and the ground-based medical support team will be essential. Co-development of a CDSS with industry partners will assure that state of the art tools can be employed, and industry efficiencies can be leveraged. Training regimens, materials and tools must evolve to be responsive (just-in-time training) and facilitate autonomous execution of procedures. Proficiency metrics should be established and be based on validated competencies or milestones as opposed to a prescribed number of training hours. Training should be prioritized for broad, translatable skills that have universal application across a variety of medical conditions. Repetition was deemed to be the key to achieving proficiency and emphasis should lie in procedural training which is known to extinguish more rapidly than diagnostic skills. Advanced tools, e.g., extended reality, can provide more realistic and effective training. Use of advanced probabilistic risk assessment tools will be essential to optimize the medical system capability while carefully balancing risk relative to mass/power/volume limitations. Importance of factoring use-life of medical supplies and maintaining awareness of redundancy and opportunity to re-purpose under off nominal situations was emphasized. Consideration of adopting optimized performance standards vs. “good-enough” performance thresholds is warranted. The use of legacy systems as opposed to creating new systems may be preferable. Managing task load and associated cognitive load will be essential to maintain operational safety and behavioral health. ExMC aspires to create a shared EIMO paradigm and strategic vision for advancing medical system design through novel technologies, training, protocols, and support capabilities, built upon the spirit of successful strategies and innovations over the past six decades of space medicine operations.

Jay Lemery↗

NASA NTRS2006

Overview of the Field Phase of the NASA Tropical Cloud Systems and Processes (TCSP)Experiment

The Tropical Cloud Systems and Processes experiment is sponsored by the National Aeronautics and Space Administration (NASA) to investigate characteristics of tropical cyclone genesis, rapid intensification and rainfall using a three-pronged approach that emphasizes satellite information, suborbital observations and numerical model simulations. Research goals include demonstration and assessment of new technology, improvements to numerical model parameterizations, and advancements in data assimilation techniques. The field phase of the experiment was based in Costa Rica during July 2005. A fully instrumented NASA ER-2 high altitude airplane was deployed with Doppler radar, passive microwave instrumentation, lightning and electric field sensors and an airborne simulator of visible and infrared satellite sensors. Other assets brought to TCSP were a low flying uninhabited aerial vehicle, and a surface-based radiosonde network. In partnership with the Intensity Forecasting Experiment of the National Oceanic and Atmospheric Administration (NOAA) Hurricane Research Division, two NOAA P-3 aircraft instrumented with radar, passive microwave, microphysical, and dropsonde instrumentation were also deployed to Costa Rica. The field phase of TCSP was conducted in Costa Rica to take advantage of the geographically compact tropical cyclone genesis region of the Eastern Pacific Ocean near Central America. However, the unusual 2005 hurricane season provided numerous opportunities to sample tropical cyclone development and intensification in the Caribbean Sea and Gulf of Mexico as well. Development of Hurricane Dennis and Tropical Storm Gert were each investigated over several days in addition to Hurricane Emily as it was close to Saffir-Simpson Category 5 intensity. An overview of the characteristics of these storms along with the pregenesis environment of Tropical Storm Eugene in the Eastern Pacific will be presented.

Hood, Robbie E.↗

NASA NTRSDate not supplied

Seeking & Evaluating Applications of SAWs (SEASAWs)

Surface Acoustic Wave sensors (SAWs) offer a battery less, wireless, passive, noninvasive, durable means of sensing which might be appealing to many fields in space technology. Developments in many aspects of SAWs including the miniaturization of associated hardware, improvements in interrogation and device fabrication / characterization allow for the use of SAWs in many aerospace settings where traditional sensors may have sufficed but SAWs might enhance. In order to place this technology in relevant environments, an inherent understanding of operation and capabilities must be understood. With the many possibilities of SAWs in their implementation, breaking down their tradeoffs and primary systems allows for their application.

Michael Szostak↗

NASA NTRS2006

Impact of Surface Roughness on AMSR-E Sea Ice Products

This paper examines the sensitivity of Advanced Microwave Scanning Radiometer (AMSR-E) brightness temperatures (Tbs) to surface roughness by a using radiative transfer model to simulate AMSR-E Tbs as a function of incidence angle at which the surface is viewed. The simulated Tbs are then used to examine the influence that surface roughness has on two operational sea ice algorithms, namely: 1) the National Aeronautics and Space Administration Team (NT) algorithm and 2) the enhanced NT algorithm, as well as the impact of roughness on the AMSR-E snow depth algorithm. Surface snow and ice data collected during the AMSR-Ice03 field campaign held in March 2003 near Barrow, AK, were used to force the radiative transfer model, and resultant modeled Tbs are compared with airborne passive microwave observations from the Polarimetric Scanning Radiometer. Results indicate that passive microwave Tbs are very sensitive even to small variations in incidence angle, which can cause either an over or underestimation of the true amount of sea ice in the pixel area viewed. For example, this paper showed that if the sea ice areas modeled in this paper mere assumed to be completely smooth, sea ice concentrations were underestimated by nearly 14% using the NT sea ice algorithm and by 7% using the enhanced NT algorithm. A comparison of polarization ratios (PRs) at 10.7,18.7, and 37 GHz indicates that each channel responds to different degrees of surface roughness and suggests that the PR at 10.7 GHz can be useful for identifying locations of heavily ridged or rubbled ice. Using the PR at 10.7 GHz to derive an "effective" viewing angle, which is used as a proxy for surface roughness, resulted in more accurate retrievals of sea ice concentration for both algorithms. The AMSR-E snow depth algorithm was found to be extremely sensitive to instrument calibration and sensor viewing angle, and it is concluded that more work is needed to investigate the sensitivity of the gradient ratio at 37 and 18.7 GHz to these factors to improve snow depth retrievals from spaceborne passive microwave sensors.

Stroeve, Julienne C.↗

NASA NTRS1972

Experimental active and passive dosimetry systems for the NASA Skylab program

Active and passive dosimetry instrumentation to measure absorbed dose, charged particle spectra, and linear energy transfer spectra inside the command module and orbital workshop on the Skylab program were developed and tested. The active dosimetry system consists of one integral unit employing both a tissue equivalent ionization chamber and silicon solid state detectors. The instrument measures dose rates from 0.2 millirad/hour to 25 rads/hour, linear energy transfer spectra from 2.8 to 42.4 Kev/micron, and the proton and alpha particle energy spectra from 0.5 to 75 Mev. The active dosimeter is equipped with a portable radiation sensor for use in astronaut on-body and spacecraft shielding surveys during passage of the Skylab through significant space radiations. Data are transmitted in real time or are recorded by onboard spacecraft tape recorder for rapid evaluation of the radiation levels. The passive dosimetry systems consist of twelve (12) hard-mounted assemblies, each containing a variety of passive radiation sensors which are recoverable at the end of the mission for analysis.

Schneider, M. F.↗

NASA NTRS2018

Active and Passive Radiative Transfer Modeling of the Olympic Mountains Experiment

Sensor forward models are an important tool for interpreting remote sensing observations of geophysical phenomena. By implementing a three-dimensional framework, we can simulate and analyze observations from various sensors on disparate platforms. To demonstrate our model framework, we simulate observations from the Olympic Mountains Experiment (OLYMPEX). The use of cloud model simulations allows us to understand sensor response to cloud ice, falling snow, and other processes and features, and the application of model tools to observations allows us to quantify precipitation.MIIST 3D Forward ModelThe Multi-Instrument Inverse Solver Testbed(MIIST) uses the Atmospheric Radiative TransferSimulator (ARTS) for solving the vector radiativetransfer (RT) equation in up to three spatialdimensions within a spherical geometry• Gas absorptiono Line-by-line calculationso Fast transmittance tables• Hydrometeor scattering solverso Discrete ordinateo RT4 (Evans, 1D)o Radar Single Scattering (1D or 3D)o Monte Carlo (3D)Scattering TablesHigh-fidelity hydrometeor scatteringtables are necessary for accurateand consistent forward modeling ofmulti-frequency observations• Requires full Stokes matriceso And absorption vector• Randomly oriented particleso Discrete Dipole Approximationo Characteristic Basis Function Method(coming soon)• Horizontally-oriented plateso Invariant Imbedding T-matrix MethodCloud Resolving SimulationsCloud resolving simulations (e.g.,NU-WRF) supply output consistentwith ARTS needs• Atmospheric Informationo Temperatureo Pressure / heighto Water vapor• Hydrometeor Profileso ARTS architecture ripe for explicit binmicrophysics• Examples use Morrison 2M schemeThe Olympic Mountains Experiment (OLYMPEX)Validation for GPM of mid-latitudefrontal systems approaching nearcoastalmountains from the ocean• Large collection of ground-based andairborne sensorso Radarso Radiometerso In situ• Contemporaneous with RADEXo Two sets of radar at same frequenciesRadiometer Simulation (3 km NUWRF, 20151203, 15:00)2018.12.14 7Simulate 166 GHz polarizationdifference• Corresponds to the presence of aligned icecrystals• Look at trends for both simulations andobservations• Simulations can tolerate lower resolutiono Larger domainSimulations from Observations: OLYMPEXSimulate sensor response usinggeophysical retrievals as input• Single frequency radar retrievals• Multiple scattering enhancementapparent at W band• Spatially dependent phenomenonModeling Application: 1D Retrievals03 December 2015• DC-8 and ER-2 flightso Focus on APR-3 (DC-8)• Citationo Stacked microphysics legso Qualitative comparisonso Range of frozen habitso Presence of supercooledliquid cloudsResults• Retrievals match probeso Good qualitative match• Bands of increasedreflectivity correspond tolarge Dm and highaggregate fraction• Significant amounts ofsupercooled liquid water

Adams, Ian S.↗

NASA NTRS1997

Hybrid Damping System for an Electronic Equipment Mounting Shelf

The objective of this study was to design and construct a vibration control system for an electronic equipment shelf to be evaluated in the NASA Dryden FTF-11. The vibration control system was a hybrid system which included passive and active damping techniques. Passive damping was fabricated into the equipment shelf using ScothDamp(trademark) damping film and aluminum constraining layers. Active damping was achieved using a two channel active control circuit employing QuickPack(trademark) sensors and actuators. Preliminary Chirp test results indicated passive damping smoothed the frequency response while active damping reduced amplitudes of the frequency response for most frequencies below 500Hz.

Voracek, David↗

NASA NTRS1997

Hybrid Damping System for an Electronic Equipment Mounting Shelf

The objective of this study was to design and construct a vibration control system for an electronic equipment shelf to be evaluated in the NASA Dryden FTF-II. The vibration control system was a hybrid system which included passive and active damping techniques. Passive damping was fabricated into the equipment shelf using ScothDamp(trademark) damping film and aluminum constraining layers. Active damping was achieved using a two channel active control circuit employing QuickPack(trademark) sensors and actuators. Preliminary Chirp test results indicated passive damping smoothed the frequency response while active damping reduced amplitudes of the frequency response for most frequencies below 500Hz.

Voracek, David↗