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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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At least 397 records · Page 22
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NASA NTRS2019

Applicability of Spectral Decomposition by Varimax-Rotated, Principal Component Analysis to the Surface Biology and Geology (SBG) VNIR Mission Concept

Cyanobacterial and Harmful Algal Blooms (CyanoHABs) are a growing concern in coastal and inland waters. But, spectral interference from multiple constituents in optically complex waters can hamper application of remote sensing using traditional image processing methods. The Kent State University (KSU) spectral decomposition method can be applied to multispectral and hyperspectral remote sensing images (e.g. HICO and the NASA Glenn HSI2) to partition and identify signals related to cyanobacteria, algae, pigment degradation products and suspended sediment in each pixel. Fundamental to the use of remote sensing data is the ability to extract independent signals from correlated hyperspectral VNIR data cubes. The Kent State University varimax-rotated, principal component analysis method (VPCA) is important to integrate into the SBG VNIR mission concept because it provides greater specificity, a software-based SNR boost relative to hardware performance, and can assist with Cal/Val, Modeling and Applications. We present examples of the hyperspectral application of the KSU VPCA method with relevance to SBG. The information extracted by VPCA can be validated spectrally or spatially with laboratory and/or in situ sensors, which capture spatial or time series of information at discrete points within remote sensing images. Comparisons show hyperspectral sensors extract more components than multispectral ones, but more independent information can be extracted from multispectral sensors by VPCA than traditional band ratio approaches. The spectral decomposition method is capable of enhancing the signal to noise ratio (SNR) of the NASA Glenn, second-generation hyperspectral imager by a factor of 7x to 20x, with a spectral reproducibility of ±3%. The spectral decomposition method, when compared against existing remote sensing monitoring methods exhibits both greater specificity and a lower detection limit. The method has been validated with multispectral images in Lake Erie to quantify the Microcystis CyanoHAB and from the Indian River Lagoon, Florida to quantify the Brown Tide resulting from A. lagunesnsis. Field operations in the Western Basin of Lake Erie were conducted using a bbe Fluoroprobe to collect vertical profiles and horizontal tows along a transect from the Toledo to the Detroit Lighthouse during coincident satellite overpasses. Extraction of pixel values from the MODIS Aqua sensor yields agreement between in situ field and lab-based measures of cyanobacterial, cryptophyte, diatoms and green algae, suspended sediment and pigment degradation products with R2>0.8.

hyperspectral↗
NASA NTRSDate not supplied

The International Space Station Lightning Imaging Sensor: Performance, Applications, and Cross-Platform Science

The Lightning Imaging Sensor (LIS), an optically based lightning detector developed at NASA Marshall Space Flight Center, was launched to the International Space Station (ISS) in February 2017, detecting optical signatures of lightning with storm-scale horizontal resolution (4-km) during both day and night. ISS LIS data are available 1 March 2017 to present. Millisecond timing allows detailed intercalibration and validation with other spaceborne and ground-based lightning sensors. Initial comparisons with those other sensors suggest flash detection efficiency around 60% (diurnal variability of 51-75%), false alarm rate under 5%, timing accuracy better than 2 ms, and horizontal location accuracy around 3 km. The spatially uniform flash detection capability of ISS LIS from low-Earth orbit allows assessment of spatially varying flash detection efficiency for other sensors and networks, particularly the Geostationary Lightning Mappers (GLMs). ISS LIS provides research data suitable for investigations of lightning physics, climatology, thunderstorm processes, and atmospheric composition, as well as realtime lightning data for operational forecasting and aviation weather interests. ISS LIS enables enrichment and extension of the long-term global climatology of lightning from space, and is the only recent platform that extends the global record to higher latitudes (± 55°). The global spatial distribution of lightning from ISS LIS is broadly similar to previous datasets, with globally averaged seasonal/annual flash rates (3-year average: ~44 s) about 5-10% lower. This difference is likely due to reduced flash detection efficiency that will be mitigated in future ISS LIS data processing, as well as the shorter ISS LIS period of record. The expected land/ocean contrast in the diurnal variability of global lightning is also observed. The near-realtime ISS LIS data make the instrument important to operational weather forecasting and related applications, including public safety. Finally, ISS LIS is demonstrating utility as part (or potential part) of cross-platform studies examining a diverse array of topics, including lightning physics, thunderstorm processes, convective precipitation, and atmospheric composition.

Timothy Lang↗
NASA NTRS2016

Vibrating-Wire, Supercooled Liquid Water Content Sensor Calibration and Characterization Progress

NASA conducted a winter 2015 field campaign at the NASA Glenn Research Center intended to generate a validation database for the NASA Icing Remote Sensing System. The weather balloons carried a specialized, disposable sensor designed to determine supercooled liquid water content aloft. Significant progress has been made to calibrate and characterize these specialized sensors. Calibration testing of these sensors was carried out in a specially developed, low-speed, icing wind tunnel. The sensor icing behavior was documented and analyzed. Finally, post-campaign evaluation of the balloon soundings revealed a gradual drift in the sensor data with increasing altitude. The behavior was analyzed and a method to account for the drift was developed.

Icing↗
NASA NTRSDate not supplied

On the use of DSCOVR EPIC to monitor the visible calibration stability of polar orbiting imagers to improve the next edition of the CERES climate data record.

The NASA CERES project has provided the climate quality observed TOA and computed surface fluxes to the scientific community. CERES instruments are onboard the Terra, Aqua, NPP, and NOAA-20 spacecraft. CERES uses MODIS and VIIRS imagers to retrieve cloud properties needed to convert CERES footprint radiance observations into fluxes using empirically derived angular directional models obtained during early CERES record. CERES utilizes geostationary sensors to infer the regional diurnal fluxes in between Terra and Aqua CERES observations. The imagers are also used to radiometrically scale the geostationary sensors (GEO) radiances to the imager calibration reference to ensure that the GEO derived cloud properties and broadband TOA fluxes are consistent in both space and time. Both the imager and GEO retrieved cloud properties are used to compute the surface fluxes. The Aqua-MODIS, SNPP-VIIRS, and NOAA-20 VIIRS afternoon imagers will also need to be radiometrically scaled to the same common calibration reference. Although all three imagers employ onboard solar diffusers, the calibration is not consistent over time due to instrument anomalies and ageing of the onboard calibrators. The CERES imager and GEO calibration group (IGCG) has been tasked to remove the imager channel calibration drifts for the next CERES reprocessing effort. The team will rely primarily on deep convective clouds, desert, and polar ice invariant targets to monitor the imager channel stability. The team uses ray-matched radiance pairs to radiometrically scale the SNPP and NOAA-20 VIIRS sensors to Aqua-MODIS. The radiometric scaling is further validated using geostationary imagers as transfer radiometers. The DSCOVR satellite was launched on February 25, 2015 and orbits around the L1 Lagrange point directly between the Earth and the sun. The EPIC instrument onboard DSCOVR employs a CCD array to image the Earth approximately every 2-hours. The EPIC sensor contains no onboard calibration systems. However, multiple inter-calibration studies have shown that the EPIC imager is very stable in time. This is likely due to the DSCOVR satellite being located about a 1.5M km from the Earth, where very little Earth reflected solar radiation degrades the optics. The excellent radiometric stability of EPIC allows the CERES IGCG to utilize the EPIC observations as a stable reference for monitoring the calibration stability of the three afternoon imagers, as well as to validate the radiometric scaling factors between them. Examples of the imager relative calibration using EPIC before and after radiometric scaling will be shown along with the results from the use of invariant targets to remove imager calibration drifts.

DSCOVR-EPIC↗
NASA NTRS1979

SAGE ground truth plan: Correlative measurements for the Stratospheric Aerosol and Gas Experiment (SAGE) on the AEM-B satellite

The ground truth plan is outlined for correlative measurements to validate the Stratospheric Aerosol and Gas Experiment (SAGE) sensor data. SAGE will fly aboard the Applications Explorer Mission-B satellite scheduled for launch in early 1979 and measure stratospheric vertical profiles of aerosol, ozone, nitrogen dioxide, and molecular extinction between 79 N and 79 S. latitude. The plan gives details of the location and times for the simultaneous satellite/correlative measurements for the nominal launch time, the rationale and choice of the correlative sensors, their characteristics and expected accuracies, and the conversion of their data to extinction profiles. In addition, an overview of the SAGE expected instrument performance and data inversion results are presented. Various atmospheric models representative of stratospheric aerosols and ozone are used in the SAGE and correlative sensor analyses.

Russell, P. B.↗
NASA NTRS1986

Chlorophyll pigment concentration using spectral curvature algorithms - An evaluation of present and proposed satellite ocean color sensor bands

During the past several years symmetric three-band (460-, 490-, 520-nm) spectral curvature algorithm (SCA) has demonstrated rather accurate determination of chlorophyll pigment concentration using low-altitude airborne ocean color data. It is shown herein that the in-water asymmetric SCA, when applied to certain recently proposed OCI (NOAA-K and SPOT-3) and OCM (ERS-1) satellite ocean color bands, can adequately recover chlorophyll-like pigments. These airborne findings suggest that the proposed new ocean color sensor bands are in general satisfactorily, but not necessarily optimally, positioned to allow space evaluation of the SCA using high-precision atmospherically corrected satellite radiances. The pigment concentration recovery is not as good when existing Coastal Zone Color Scanner bands are used in the SCA. The in-water asymmetric SCA chlorophyll pigment recovery evaluations were performed using (1) airborne laser-induced chlorophyll fluorescence and (2) concurrent passive upwelled radiances. Data from a separate ocean color sensor aboard the aircraft were further used to validate the findings.

Hoge, Frank E.↗
NASA NTRS1995

Orbital Acceleration Research Experiment: Calibration Measurements

The Orbital Acceleration Research Experiment (OARE), which has flown on STS-40, STS-50, and STS-58, contains a three-axis accelerometer with a single, nonpendulous, electrostatically suspended proofmass, which can resolve accelerations to the 10(sub -9) g level. The experiment also contains a full calibration station to permit in situ bias and scale-factor calibration. This on-orbit calibration capability eliminates the large uncertainty of ground-based calibrations encountered with accelerometers flown in the past on the Orbiter, and thus provides absolute acceleration measurement accuracy heretofore unachievable. This is the first time accelerometer scale-factor measurements have been performed on orbit. A detailed analysis of the calibration process is given, along with results of the calibration factors from the on-orbit OARE flight measurements on STS-58. In addition, the analysis of OARE flight-maneuver data used to validate the scale-factor measurements in the sensor's most sensitive range are also presented. Estimates on calibration uncertainties are discussed. These uncertainty estimates provides bounds on the STS-58 absolute acceleration measurements for future applications.

Blanchard, Robert C.↗
NASA NTRS2001

AVHRR-Based Polar Pathfinder Products: Evaluation, Enhancement, and Transition to MODIS

The AVHRR-Based Polar Pathfinder (APP) products include calibrated AVHRR channel data, surface temperatures, albedo, satellite scan and solar geometries, and a cloud mask composited into twice- per-day images, and daily averaged fields of sea ice motion, for regions poleward of 50 deg. latitude. Our goals under this grant, in general, are four-fold: 1. To quantify the APP accuracy and sources of error by comparing Pathfinder products with field measurements. 2. To determine the consistency of mean fields and trends in comparison with longer time series of available station data and forecast model output. 3. To investigate the consistency of the products between the different AVHRR instruments over the 1982-present period of the NOAA program. 4. To compare an annual cycle of the AVHRR Pathfinder products with MODIS to establish a baseline for extending Pathfinder-type products into the new ESE period. Year One tasks include intercomparisons of the Pathfinder products with field measurements, testing of algorithm assumptions, collection of field data, and further validation and possible improvement of the multi-sensor ice motion fields. Achievements for these tasks are summarized below.

Fowler, Charles↗
NASA NTRS2005

NASA Icing Remote Sensing System Comparisons From AIRS II

NASA has an on-going activity to develop remote sensing technologies for the detection and measurement of icing conditions aloft. A multiple instrument approach is the current emphasis of this activity. Utilizing radar, radiometry, and lidar, a region of supercooled liquid is identified. If the liquid water content (LWC) is sufficiently high, then the region of supercooled liquid cloud is flagged as being an aviation hazard. The instruments utilized for the current effort are an X-band vertical staring radar, a radiometer that measures twelve frequencies between 22 and 59 GHz, and a lidar ceilometer. The radar data determine cloud boundaries, the radiometer determines the sub-freezing temperature heights and total liquid water content, and the ceilometer refines the lower cloud boundary. Data is post-processed with a LabVIEW program with a resultant supercooled LWC profile and aircraft hazard identification. Individual remotely sensed measurements gathered during the 2003-2004 Alliance Icing Research Study (AIRS II) were compared to aircraft in-situ measurements. Comparisons between the remote sensing system s fused icing product and in-situ measurements from the research aircraft are reviewed here. While there are areas where improvement can be made, the cases examined indicate that the fused sensor remote sensing technique appears to be a valid approach.

Reehorst, Andrew L.↗
NASA NTRS2006

Progress in the Development of Practical Remote Detection of Icing Conditions

The NASA Icing Remote Sensing System (NIRSS) has been under definition and development at NASA Glenn Research Center since 1997. The goal of this development activity is to produce and demonstrate the required sensing and data processing technologies required to accurately remotely detect and measure icing conditions aloft. As part of that effort NASA has teamed with NCAR to develop software to fuse data from multiple instruments into a single detected icing condition product. The multiple instrument approach utilizes a X-band vertical staring radar, a multifrequency microwave, and a lidar ceilometer. The radar data determine cloud boundaries, the radiometer determines the sub-freezing temperature heights and total liquid water content, and the ceilometer refines the lower cloud boundary. Data is post-processed with a LabVIEW program with a resultant supercooled liquid water profile and aircraft hazard depiction. Ground-based, remotely-sensed measurements and in-situ measurements from research aircraft were gathered during the international 2003-2004 Alliance Icing Research Study (AIRS II). Comparisons between the remote sensing system s fused icing product and the aircraft measurements are reviewed here. While there are areas where improvement can be made, the cases examined suggest that the fused sensor remote sensing technique appears to be a valid approach.

Reehorst, Andrew↗
NASA NTRS2006

MicroMAPS CO Measurements over North America and Europe during Summer-Fall 2004

The MicroMAPS instrument is a nadir-viewing, gas filter-correlated radiometer which operating in the 4.67 micrometer fundamental band of carbon monoxide. Originally designed and built for a space mission, this CO remote sensor is being flown in support of satellite validation and science instrument demonstrations for potential UAV applications. The MicroMAPS instrument system, as flown on Proteus, was designed by a senior student design project in the Aerospace Engineering Department, Virginia Tech, in Blacksburg, VA. and then revised by Systems Engineers at NASA Langley. The final instrument system was integrated and tested at NASA LaRC, in partnership with Scaled Composites and Virginia Space Grant Consortium (VSGC). VSGC supervised the fabrication of the nacelle that houses the instrument system on the right rear tail boom of Proteus. Full system integration and flight testing was performed at Scaled Composites, in Mojave, in June 2004. Its successful performance enabled participation in four international science missions on Proteus: in 2004, INTEX -NA over eastern North America in July, ADRIEX over the Mediterranean region and EAQUATE over the United Kingdom region in September,and TWP-ICE over Darwin, Australia and the surrounding oceans in Jan-Feb 2006. These flights resulted in nearly 300 hours of data. In parallel with the engineering developments, theoretical radiative transfer models were developed specifically for the MicroMAPS instrument system at the University of Virginia, Mechanical Engineering Department by a combined undergraduate and graduate student team. With technical support from Resonance Ltd. in June 2005, the MicroMAPS instrument was calibrated for the conditions under which the Summer-Fall 2004 flights occurred. The analyses of the calibration data, combined with the theoretical radiative transfer models, provide the first data reduction for the science flights reported here. These early results and comparisons with profile data from the NASA DC-8, the coincident AIRS CO retrievals, and selected CO measurements from the MOZAIC program will be presented.

Connors, Vickie S.↗
NASA NTRS2007

Cooperative Collision Avoidance Technology Demonstration Data Analysis Report

This report details the National Aeronautics and Space Administration (NASA) Access 5 Project Office Cooperative Collision Avoidance (CCA) Technology Demonstration for unmanned aircraft systems (UAS) conducted from 21 to 28 September 2005. The test platform chosen for the demonstration was the Proteus Optionally Piloted Vehicle operated by Scaled Composites, LLC, flown out of the Mojave Airport, Mojave, CA. A single intruder aircraft, a NASA Gulf stream III, was used during the demonstration to execute a series of near-collision encounter scenarios. Both aircraft were equipped with Traffic Alert and Collision Avoidance System-II (TCAS-II) and Automatic Dependent Surveillance Broadcast (ADS-B) systems. The objective of this demonstration was to collect flight data to support validation efforts for the Access 5 CCA Work Package Performance Simulation and Systems Integration Laboratory (SIL). Correlation of the flight data with results obtained from the performance simulation serves as the basis for the simulation validation. A similar effort uses the flight data to validate the SIL architecture that contains the same sensor hardware that was used during the flight demonstration.

Source record↗
NASA NTRS2008

In-Situ Polarization Measurements for the Orbiting Carbon Observatory (OCO)

The Jet Propulsion Laboratory (JPL) is developing the Orbiting Carbon Observatory (OCO), a polarization-sensitive sensor that will soon be launched. Calibration and validation for this instrument require the ability to account for polarization properties of various surfaces and atmospheres. In order to validate the OCO assumptions, it is necessary to have instrumentation that can measure atmospheric and surface properties. This paper evaluates several instruments that were on hand. Although these instruments were found to be lacking, this study has allowed us to define requirements for future instruments.

polarization↗
NASA NTRSDate not supplied

Analysis of CO Transport from Australia Fires and Its Impact to Ozone, Water Vapor and Clouds Using CrIS Single-Field-of-View Sounder Products and Other Remote Sensing and MERRA-2 Reanalysis Data

Australia’s unprecedented fire disasters at the end of 2019 to early 2020 emitted huge amounts of carbon monoxide (CO) and fire aerosol particles, and the long-range transport of the smoke plumes poses great impact to climate change, such as altering the Antarctic ozone (O3) hole. Spaceborne observations from satellites have been proven successful in monitoring CO from wildfires in the past decade and can be used to examine the associated CO transport. The primary remote sensing data used in this study is the Single Field of View (SFOV) Sounder Atmospheric Product (SiFSAP) derived from the Cross-track Infrared Sounder (CrIS) on SNPP, a new product that will be generated at NASA and released to the public in a few months. SiFSAP has a high spatial resolution of ~14 km and includes atmospheric profiles of temperature, water vapor, CO, O3, as well as cloud products, and as the SiFSAP algorithm performs both day- and night-time retrievals, it provides an additional observation for night-time in comparison to the day-time-only solar polar satellite instruments such as MOPPIT, OMPS, and TROPOMI. Most recent significant improvements in the quality of this product plus its good spatial resolution (better than most global weather and climate models) enable us to conduct process-oriented analysis of CO transport, and the variation of water vapor, O3 and clouds (optical depth, effective radius and cloud height) within and around the fire plumes. The wind fields from MERRA-2 reanalysis will be used to help characterize the transport. Other remote sensing data, such as CO from AIRS, MOPPIT and TROPOMI, O3 from OMPS and TROPOMI, as well as the UV aerosol index from OMI and OMPS, will be used and compared with SiFSAP sounder products. Cross-validation of CO and O3 from these different sensors with the corresponding MERRA-2 products will also be carried out. Along the plume transport path, some enhancement of O3 and correlation between fire aerosol, cloud optical depth and water vapor have been found but need further investigation. Using the transport of fire plumes over the Southern Pacific Ocean as a unique testbed, this study will demonstrate the trace species monitoring capability of current satellite observations, in particular, for CO and O3, and hopefully, it will provide some insight on the impacts on fire emissions on air quality and climate.

Xiaozhen (Shawn) Xiong↗
NASA NTRS2026

Incremental Learning for Passive Microwave Precipitation Retrievals using Advanced Technology Microwave Sounder

Spaceborne passive microwave (PMW) radiometry is central to global precipitation monitoring, yet retrieval uncertainties remain substantial, particularly for cross-track sounders whose variable footprints and channel configurations are optimized for atmospheric temperature and moisture profiling rather than precipitation. Consequently, existing operational products often exhibit angular-dependent biases, limited effective swath utilization, unrealistic rainfall probability distributions, and systematic misclassification of precipitation phase. These limitations are further compounded by the scarcity of globally accurate and representative precipitation observations, as training data from the Dual-frequency Precipitation Radar (DPR) and the Cloud Profiling Radar (CPR) are spatially sparse, lack uniform global coverage, and exhibit heterogeneous error characteristics across precipitation regimes. To address these challenges, this study presents a supervised retrieval algorithm that incrementally trains an ensemble of extreme gradient-boosted decision trees by augmenting base learners with pre-training on reanalysis data and post-training on coincident DPR and CPR observations matched with the Advanced Technology Microwave Sounder (ATMS). By transferring prior information from reanalysis to posterior constraints from radar observations and adopting a sequential detection–estimation strategy for precipitation phase and rate retrieval, the proposed approach yields retrievals across the full ATMS swath that are largely free from persistent deficiencies in current Global Precipitation Measurement (GPM) passive microwave operational products. In particular, the method resolves bimodal artifacts in rainfall retrievals and mitigates systematic high-latitude snowfall biases, including overestimation across the Arctic and underestimation across the Antarctic. Validation against independent Multi-Radar Multi-Sensor (MRMS) data over the Contiguous United States (CONUS) further demonstrates improved performance in precipitation phase detection and rate estimation relative to both reanalysis and current GPM PMW products.

Mahyar Garshasbi↗
NASA NTRS1988

NASA Sea Ice and Snow Validation Program for the DMSP SSM/I: NASA DC-8 flight report

In June 1987 a new microwave sensor called the Special Sensor Microwave Imager (SSM/I) was launched as part of the Defense Meteorological Satellite Program (DMSP). In recognition of the importance of this sensor to the polar research community, NASA developed a program to acquire the data, to convert the data into sea ice parameters, and finally to validate and archive both the SSM/I radiances and the derived sea ice parameters. Central to NASA's sea ice validation program was a series of SSM/I aircraft underflights with the NASA DC-8 airborne Laboratory. The mission (the Arctic '88 Sea Ice Mission) was completed in March 1988. This report summarizes the mission and includes a summary of aircraft instrumentation, coordination with participating Navy aircraft, flight objectives, flight plans, data collected, SSM/I orbits for each day during the mission, and lists several piggyback experiments supported during this mission.

Cavalieri, D. J.↗
NASA NTRS2024

Absolute Intercalibration of Spaceborne Microwave Radiometers

Absolute calibration of spaceborne microwave radiometer observations consists of accurate determination of antenna cold space spillover, cross-polarization contamination, and nonlinearity coefficients of the receivers. We deem the GMI sensor to be the most accurate calibrated spaceborne microwave radiometer due to its unique calibration design features and its carefully planned orbit maneuvers. We demonstrate how to transfer the GMI calibration to other spaceborne radiometers, whose operations have sufficient time overlap with GMI. Specifically, we show results for WindSat and AMSR2. The sensor intercalibration is based on brightness temperature matchups between GMI and the other instruments over both open ocean and rainforest scenes. To assess the calibration accuracy, we compare the intercalibrated brightness temperatures with radiative transfer model calculations. In addition, we provide in situ validation results for wind speed and water vapor retrievals from the intercalibrated sensors. The intercalibration methodology allows for the creation of a multidecadal climate data record from passive microwave satellite observations. Significance Statement Creating a long-term climate data record of satellite observations of ocean winds, water vapor, and other variables requires careful and accurate calibration of the various sensors that are used. In particular, it is important to achieve the best possible consistency between the measurements from all the different instruments. This is a challenging task as the configuration and accuracy of these instruments can differ widely. The purpose of our paper is to demonstrate and validate the basic methodology for performing this intercalibration. The backbone of our method is data observed by a well-calibrated sensor that measures the passive microwave emission from Earth’s surface and atmosphere. We show how to transfer its calibration standard to other sensors.

Katherine Wentz↗