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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 NTRS2019

Evaluating the Operational Application of SMAP for Global Agricultural Drought Monitoring

Over the past two decades, remote sensing has made possible the routine global monitoring of surface soil moisture. Regionalagricultural drought monitoring is one of the most logicalapplication areas for such monitoring. However, remote sensing alone provides soil moisture information for only the top few centimetersof the soil profile, while agricultural drought monitoring requires knowledge of the amount of water present in the entireroot zone. The assimilation of remotely sensed soil moisture productsinto continuous soil water balance models provides a way ofaddressing this shortcoming. Here, we describe the assimilationof NASA's soil moisture active passive (SMAP) surface soil moisture data into the United States Department of Agriculture Foreign Agricultural Service (USDA FAS) Palmer model and assess the impactof SMAP on USDA FAS drought monitoring capabilities. Theassimilation of SMAP is specifically designed to enhance the model skill and the USDA FAS drought capabilities by correcting for randomerrors inherent in its rainfall forcing data. The performanceof this SMAP-based assimilation system is evaluated using two approaches.At global scale, the accuracy of the system is assessed by examining the lagged correlation agreement between soil moistureand the normalized difference vegetation index (NDVI). Additional regional-scale evaluation using in situ-based soil moisture estimatesis carried out at seven of the SMAP core Cal/Val sites located in theUSA. Both types of analysis demonstrate the value of assimilating SMAP into the USDA FAS Palmer model and its potential to enhance operational USDA FAS root-zone soil moisture information.

Mladenova, Iliana E.↗
NASA NTRS2021

Scaling photosynthetic function and CO2 dynamics from leaf to canopy level for maize – dataset combining diurnal and seasonal measurements of vegetation fluorescence, reflectance and vegetation indices with canopy gross ecosystem productivity

Recent advances in leaf fluorescence measurements and canopy proximal remote sensing currently enable the non-destructive collection of rich diurnal and seasonal time series, which are required for monitoring vegetation function at the temporal and spatial scales relevant to the natural dynamics of photosynthesis. Remote sensing assessments of vegetation function have traditionally used actively excited foliar chlorophyll fluorescence measurements, canopy optical reflectance data and vegetation indices (VIs), and only recently passive solar induced chlorophyll fluorescence (SIF) measurements. In general, reflectance data are more sensitive to the seasonal variations in canopy chlorophyll content and foliar biomass, while fluorescence observations more closely relate to the dynamic changes in plant photosynthetic function. With this dataset we link leaf level actively excited chlorophyll fluorescence, canopy proximal reflectance and SIF, with eddy covariance measurements of gross ecosystem productivity (GEP). The dataset was collected during the 2017 growing season on maize, using three automated systems (i.e., Monitoring Pulse-Amplitude-Modulation fluorimeter, Moni-PAM; Fluorescence Box, FloX; and from eddy covariance tower). The data were quality checked, filtered and collated to a common 30 minutes timestep. We derived vegetation indices related to canopy functioning (e.g., Photochemical Reflectance Index, PRI; Normalized Difference Vegetation Index, NDVI; Chlorophyll Red-edge, Clre) to investigate how SIF and VIs can be coupled for monitoring vegetation photosynthesis. The raw datasets and the filtered and collated data are provided to enable new processing and analyses.

Petya Campbell↗
NASA NTRS2018

Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS): Final Report of the ASCENDS Ad Hoc Science Definition Team

Improved remote sensing observations of atmospheric carbon dioxide (CO2) are critically needed to quantify, monitor, and understand the Earth's carbon cycle and its evolution in a changing climate. The processes governing ocean and terrestrial carbon uptake remain poorly understood,especially in dynamic regions with large carbon stocks and strong vulnerability to climate change,for example, the tropical land biosphere, the northern hemisphere high latitudes, and the Southern Ocean. Because the passive spectrometers used by GOSAT (Greenhouse gases Observing SATellite) and OCO-2 (Orbiting Carbon Observatory-2) require sunlit and cloud-free conditions,current observations over these regions remain infrequent and are subject to biases. These short comings limit our ability to understand and predict the processes controlling the carbon cycle on regional to global scales.In contrast, active CO2 remote-sensing techniques allow accurate measurements to be taken day and night, over ocean and land surfaces, in the presence of thin or scattered clouds, and at all times of year. Because of these benefits, the National Research Council recommended the National Aeronautics and Space Administration (NASA) Active Sensing of CO2 Emissions over Nights,Days, and Seasons (ASCENDS) mission in the 2007 report Earth Science and Applications from Space: National Imperatives for the Next Decade and Beyond. The ability of ASCENDS to collect low-bias observations in these key regions is expected to address important gaps in our knowledge of the contemporary carbon cycle.The ASCENDS ad hoc Science Definition Team (SDT), comprised of carbon cycle modeling and active remote sensing instrument teams throughout the United States (US), worked to develop the mission's requirements and advance its readiness from 2008 through 2018. Numerous scientific investigations were carried out to identify the benefit and feasibility of active CO2 remote sensing measurements for improving our understanding of CO2 sources and sinks. This report summarizes their findings and recommendations based on mission modeling studies, analysis of ancillary meteorological data products, development and demonstration of candidate technologies, anddesign studies of the ASCENDS mission concept.

Kawa, S. Randolph↗
NASA NTRS1977

Interpretation of multispectral and infrared thermal surveys of the Suez Canal Zone, Egypt

Remote sensing airborne surveys were conducted, as part of the plan of rehabilitation, of the Suez Canal Zone using I2S multispectral camera and Bendix LN-3 infrared passive scanner. The multispectral camera gives four separate photographs for the same scene in the blue, green, red, and near infrared bands. The scanner was operated in the microwave bands of 8 to 14 microns and the thermal surveying was carried out both at night and in the day time. The surveys, coupled with intensive ground investigations, were utilized in the construction of new geological, structural lineation and drainage maps for the Suez Canal Zone on a scale of approximately 1:20,000, which are superior to the maps made by normal aerial photography. A considerable number of anomalies belonging to various types were revealed through the interpretation of the executed multispectral and infrared thermal surveys.

Elshazly, E. M.↗
NASA NTRS1985

Application of the Man-computer Interactive Data Access System (McIDAS) to aerospace meteorology

The Man-computer Interactive Data Access System (McIDAS) considered in this paper has been in use at Marshall Space Flight Center (MSFC) since 1981. The MSFC McIDAS system is primarily employed as a research tool, taking into account rainfall estimates as deduced from Scanning Multichannel Microwave Radiometer (SMMR) data, remote sensing sensor development (MAMS), Doppler-lidar derived winds, cloud tracked winds, and analysis of lightning ground strike data. With respect to the SMMR data analysis, passive microwave satellite data are displayed on McIDAS as images. Two major research efforts are concerned with the determination of mesoscale winds. These efforts are based on a utilization of a Doppler-lidar system, and GOES multispectral imagery. It is pointed out that future plans include increased usage of the McIDAS system.

Meyer, P. J.↗
NASA NTRS1992

The use of satellite observations in ice cover simulations

Satellites can furnish observational data on ice cover over greater areas and for longer periods than field observations; a combination of visible or IR fine-resolution satellite imagery and radar altimetry, in conjunction with coarse-resolution data from passive microwave sources, have been used to verify and validate many numerical models of ice cover. Satellite passive microwave data are especially useful in the case of large-scale models used in studies of sea ice interannual variability. A number of remotely-sensed data sources are used by the NOAA's Joint Ice Center to create a qualitative weekly analysis of ice concentrations.

Preller, Ruth H.↗
NASA NTRS2000

Microwave Mixing and if Bandwidth in Sub-Micron Long High -T(sub c) Hot - Electron Bolometers

The hot-electron bolometer (HEB) mixer made from a high-T(sub c) superconductor (HTS) was introduced recently as a competing alternative to a Schottky mixer. The HEB mixer would require 100-times less LO power and thus would be a desirable candidate for long-term observational missions such as atmospheric remote-sensing and planetary science. The required cooling temperatures between 65 K and 75 K can be achieved with available space-qualified coolers or even with passive radiative coolers.

Harnack, Oliver↗
NASA NTRS2018

Global-scale Evaluation of SMAP, SMOS and ASCAT Soil Moisture Products Using Triple Collocation

Global-scale surface soil moisture products are currently available from multiple remote sensing platforms. Footprint-scale assessments of these products are generally restricted to limited number of densely-instrumented validation sites. However, by taking active and passive soil moisture products together with a third independent soil moisture estimates via land surface modeling, triple collocation (TC) can be applied to estimate the correlation metric of satellite soil moisture products (versus an unknown ground truth) over a quasi-global domain. Here, an assessment of Soil Moisture Active Passive (SMAP), Soil Moisture Ocean Salinity (SMOS) and Advanced SCATterometer (ASCAT) surface soil moisture retrievals via TC is presented. Considering the potential violation of TC error assumptions, the impact of active-passive and satellite-model error cross correlations on the TC-derived inter-comparison results is examined at in situ sites using quadruple collocation analysis. In addition, confidence intervals for the TC-estimated correlation metric are constructed from moving-block bootstrap sampling designed to preserve the temporal persistence of the original (unevenly-sampled) soil moisture time-series. This study is the first to apply TC to obtain a robust global-scale cross-assessment of SMAP, SMOS and ASCAT soil moisture retrieval accuracy in terms of anomaly temporal correlation. Our results confirm the overall advantage of SMAP (with a global average anomaly correlation of 0.76) over SMOS (0.66) and ASCAT (0.63) that has been established in several recent regional, ground-based studies. SMAP is also the best-performing product over the majority of applicable land pixels (52%), although SMOS and ASCAT each shows advantage in distinct geographic regions.

global-scale↗
NASA NTRS2014

Hurricane Imaging Radiometer Wind Speed and Rain Rate Retrievals during the 2010 GRIP Flight Experiment

Microwave remote sensing observations of hurricanes, from NOAA and USAF hurricane surveillance aircraft, provide vital data for hurricane research and operations, for forecasting the intensity and track of tropical storms. The current operational standard for hurricane wind speed and rain rate measurements is the Stepped Frequency Microwave Radiometer (SFMR), which is a nadir viewing passive microwave airborne remote sensor. The Hurricane Imaging Radiometer, HIRAD, will extend the nadir viewing SFMR capability to provide wide swath images of wind speed and rain rate, while flying on a high altitude aircraft. HIRAD was first flown in the Genesis and Rapid Intensification Processes, GRIP, NASA hurricane field experiment in 2010. This paper reports on geophysical retrieval results and provides hurricane images from GRIP flights. An overview of the HIRAD instrument and the radiative transfer theory based, wind speed/rain rate retrieval algorithm is included. Results are presented for hurricane wind speed and rain rate for Earl and Karl, with comparison to collocated SFMR retrievals and WP3D Fuselage Radar images for validation purposes.

Sahawneh, Saleem↗
NASA NTRS1993

Sea ice motions in the central arctic ice central arctic pack ice as inferred from AVHRR imagery

Synoptic observations of ice motion in the Arctic Basin are currently limited to those acquired by drifting buoys and, more recently, radar data from ERS-1. Buoys are not uniformly distributed throughout the Arctic, and SAR coverage is limited regionally and temporally due to the data volume, swath width, processing requirements, and power needs of the SAR. Additional ice-motion observations that can map ice responses simultaneously over large portions of the Arctic on daily to weekly time intervals are thus needed to augment the SAR and buoy data and to provide an intermediate-scale measure of ice drift suitable for climatological analyses and ice modeling. Merging the remotely-sensed ice motions with SAR, AVHRR, OLS, and SSM/I imagery permits studies of ice processes over a range of space and time scales. A medium-resolution passive microwave sensor might be ideal for this purpose, but no such satellite will be available in the near future. Combinations of existing data types are thus likely to be our best bet for generating motion fields with a coverage and resolution best suited to climate studies. Principal objectives of this project are to: (1) demonstrate whether sufficient ice features and ice motion existed within the consolidated ice pack to permit motion tracking using AVHRR imagery; (2) determine the limits imposed on AVHRR mapping by cloud cover; and (3) test the applicability of AVHRR-derived motions in studies of ice-atmosphere interactions.

Emery, William↗
NASA NTRS1981

Assessment of Superflux relative to remote sensing

The state-of-the-art advancements in remote sensor technology due to the Superflux program are examined. Three major individual sensor technologies benefitted from the program: laser fluorosensors, optical-range scanners, and passive microwave sensors. Under Superflux, convincing evidence was obtained that the airborne oceanographic lidar fluorosensor can map chlorophyll, i.e., is linear, over a wide range from less than 0.5 to 5.0 mg/cu m. The lidar oceanographic probe dual-excitation concept for addressing phytoplankton color group composition was also demonstrated convincingly. Algorithm development, real time capabilities, and multisensor integration are also addressed.

Campbell, J. W.↗
NASA NTRSDate not supplied

Investigating Convective Gustiness of Winds and Fluxes Using Microwave Remote Sensing

Tropical atmospheric convection is known to be associated with enhanced winds over the oceans that can drive increased rates of mass and energy transfer through turbulent latent and sensible heat fluxes. However, convection and its associated rainfall usually obscures the surface wind signals observed using passive microwave observations. Air-sea flux estimates based on the use of microwave imagers typically mask in areas of rainfall and thus are likely underrepresenting the true turbulent flux transfer. However, both monostatic and bistatic radar scatterometer systems are allowing for more detailed analysis of the convective near-surface environment. While rain still impact C-band scatterometer observations, the L-band observables from the Cyclone Global Navigation Satellite System (CYGNSS) are providing improved observing capabilities in all-weather conditions. In this study, we will present ongoing research to leverage CYGNSS observations in addition to other scatterometer, in situ, and satellite-based precipitation information to provide an improved characterization of surface wind enhancement within tropical oceanic convection. The results will specifically highlight current capabilities and limitations to assess convective wind enhancement and wind gustiness and their relationship to the surface turbulent fluxes of heat and water.

J Brent Roberts↗
NASA NTRS2009

Concept, Simulation, and Instrumentation for Radiometric Inflight Icing Detection

The multi-agency Flight in Icing Remote Sensing Team (FIRST), a consortium of the National Aeronautics and Space Administration (NASA), the Federal Aviation Administration (FAA), the National Center for Atmospheric Research (NCAR), the National Oceanographic and Atmospheric Administration (NOAA), and the Army Corps of Engineers (USACE), has developed technologies for remotely detecting hazardous inflight icing conditions. The USACE Cold Regions Research and Engineering Laboratory (CRREL) assessed the potential of onboard passive microwave radiometers for remotely detecting icing conditions ahead of aircraft. The dual wavelength system differences the brightness temperature of Space and clouds, with greater differences potentially indicating closer and higher magnitude cloud liquid water content (LWC). The Air Force RADiative TRANsfer model (RADTRAN) was enhanced to assess the flight track sensing concept, and a 'flying' RADTRAN was developed to simulate a radiometer system flying through simulated clouds. Neural network techniques were developed to invert brightness temperatures and obtain integrated cloud liquid water. In addition, a dual wavelength Direct-Detection Polarimeter Radiometer (DDPR) system was built for detecting hazardous drizzle drops. This paper reviews technology development to date and addresses initial polarimeter performance.

Ryerson, Charles↗
NASA NTRS2017

Active and Passive Radiative Transfer Modeling with Preferentially-Aligned Particles

The fluid dynamics of falling hydrometeors often results in preferential orientations that can affect both the intensity and polarization of electromagnetic radiation. In order to properly interpret remote sensing observations of ice and snow, such alignments should be considered when constructing databases of scattering particles; however, the inclusion of aligned particles increases the complexity of the scattering data. To demonstrate the use of scattering properties of preferentially-aligned particles, millimeter-wave brightness temperatures and radar observables, including reflectivity and linear depolarization ratio, are modeled using the Atmospheric Radiative Transfer Simulator (ARTS). The necessary scattering parameters for vector radiative transfer, particularly with respect to ARTS, are reviewed, and the exploitation of particle symmetries, as well as scattering reciprocity relationships, are detailed.

radiative transfer↗
NASA NTRS1985

Shortwave infrared 512 x 2 line sensor for earth resources applications

As part of the NASA remote-sensing Multispectral Linear Array Program, an edge-buttable 512 x 2 IRCCD line image sensor with 30-micron Pd2Si Schottky-barrier detectors is developed for operation with passive cooling at 120 K in the 1.1-2.5 micron short infrared band. On-chip CCD multiplexers provide one video output for each 512 detector band. The monolithic silicon line imager performance at a 4-ms optical integration time includes a signal-to-noise ratio of 241 for irradiance of 7.2 microwatts/sq cm at 1.65 microns wavelength, a 5000 dynamic range, a modulation transfer function, greater than 60 percent at the Nyquist frequency, and an 18-milliwatt imager chip total power dissipation. Blemish-free images with three percent nonuniformity under illumination and nonlinearity of 1.25 percent are obtained. A five SWIR imager hybrid focal plane was constructed, demonstrating the feasibility of arrays with only a two-detector loss at each joint.

Tower, J. R.↗
NASA NTRS1987

Multisensor comparison of ice concentration estimates in the marginal ice zone

Aircraft remote sensing data collected during the 1984 summer Marginal Ice Zone Experiment in the Fram Strait are used to compare ice concentration estimates derived from synthetic aperture radar (SAR) imagery, passive microwave imagery at several frequencies, aerial photography, and spectral photometer data. The comparison is carried out not only to evaluate SAR performance against more established techniques but also to investigate how ice surface conditions, imaging geometry, and choice of algorithm parameters affect estimates made by each sensor.Active and passive microwave sensor estimates of ice concentration derived using similar algorithms show an rms difference of 13 percent. Agreement between each microwave sensor and near-simultaneous aerial photography is approximately the same (14 percent). The availability of high-resolution microwave imagery makes it possible to ascribe the discrepancies in the concentration estimates to variations in ice surface signatures in the scene.

Burns, B. A.↗
NASA NTRS1990

An algorithm to estimate the heating budget from vertical hydrometeor profiles

A simple algorithm to estimate the latent heating of cloud systems from their vertical hydrometeor profiles is proposed. The derivation as well as the validation of the algorithm is based on output generated by a nonhydrostatic cloud model with parameterized microphysical processes. Mature and decaying stages of a GATE squall-type convective system have been tested. The algorithm-derived heating budget is in reasonable agreement with the budget predicted by the cloud model. The input to the proposed algoritm can be obtained from either a rain retrieval technique based on information from multichannel passive microwave signals or a kinematic cloud model based on information from Doppler radar wind fields and radar reflectivity patterns. Such an application would have significant implications for spaceborne remote sensing and the large-scale weather prediction data assimilation problem.

Tao, Wei-Kuo↗