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NASA NTRS1986

On uniformly valid high-frequency far-field asymptotic solutions of the Helmholtz equation

An asymptotic, large wave number approximation for the Helmholtz equation is derived. The theory is an extension of the geometric acoustic theory, and provides corrections to that theory in the form of multiplicative functions which satisfy parabolic equations. A simple example is used both to illustrate failure of the geometric theory for large propagation distances, and to show the improvement obtained by use of the new theory.

Mcaninch, G. L.↗

NASA NTRS1990

Propeller-wing interaction using a frequency domain panel method

The unsteady aerodynamic coupling between a propeller and a wing is analyzed using linear compressible aerodynamic theory. The periodic loads are decomposed into harmonics, and the harmonic amplitudes are found iteratively. Each stage of the iteration involves the solution of an isolated propeller or wing problem; the interaction is done through the Fourier transform of the induced velocity field. The method was validated by comparing the predicted velocity field about an isolated propeller with detailed laser Doppler velocimeter measurements and by comparison with mean loads measured in a wing-propeller experiment. Comparisons have also been made between the fluctuating loads predicted by the present method and a quasisteady vortex lattice scheme.

Williams, Marc H.↗

NASA NTRS2003

National Combustion Code Validated Against Lean Direct Injection Flow Field Data

Most combustion processes have, in some way or another, a recirculating flow field. This recirculation stabilizes the reaction zone, or flame, but an unnecessarily large recirculation zone can result in high nitrogen oxide (NOx) values for combustion systems. The size of this recirculation zone is crucial to the performance of state-of-the-art, low-emissions hardware. If this is a large-scale combustion process, the flow field will probably be turbulent and, therefore, three-dimensional. This research dealt primarily with flow fields resulting from lean direct injection (LDI) concepts, as described in Research & Technology 2001. LDI is a concept that depends heavily on the design of the swirler. The LDI concept has the potential to reduce NOx values from 50 to 70 percent of current values, with good flame stability characteristics. It is cost effective and (hopefully) beneficial to do most of the design work for an LDI swirler using computer-aided design (CAD) and computer-aided engineering (CAE) tools. Computational fluid dynamics (CFD) codes are CAE tools that can calculate three-dimensional flows in complex geometries. However, CFD codes are only beginning to correctly calculate the flow fields for complex devices, and the related combustion models usually remove a large portion of the flow physics.

Iannetti, Anthony C.↗

NASA NTRS2015

Construction of Polarimetric Radar-Based Reference Rain Maps for the Iowa Flood Studies Campaign

The Global Precipitation Measurement (GPM) Mission Iowa Flood Studies (IFloodS) campaign was conducted in central and northeastern Iowa during the months of April-June, 2013. Specific science objectives for IFloodS included quantification of uncertainties in satellite and ground-based estimates of precipitation, 4-D characterization of precipitation physical processes and associated parameters (e.g., size distributions, water contents, types, structure etc.), assessment of the impact of precipitation estimation uncertainty and physical processes on hydrologic predictive skill, and refinement of field observations and data analysis approaches as they pertain to future GPM integrated hydrologic validation and related field studies. In addition to field campaign archival of raw and processed satellite data (including precipitation products), key ground-based platforms such as the NASA NPOL S-band and D3R Ka/Ku-band dual-polarimetric radars, University of Iowa X-band dual-polarimetric radars, a large network of paired rain gauge platforms, and a large network of 2D Video and Parsivel disdrometers were deployed. In something of a canonical approach, the radar (NPOL in particular), gauge and disdrometer observational assets were deployed to create a consistent high-quality distributed (time and space sampling) radar-based ground "reference" rainfall dataset, with known uncertainties, that could be used for assessing the satellite-based precipitation products at a range of space/time scales. Subsequently, the impact of uncertainties in the satellite products could be evaluated relative to the ground-benchmark in coupled weather, land-surface and distributed hydrologic modeling frameworks as related to flood prediction. Relative to establishing the ground-based "benchmark", numerous avenues were pursued in the making and verification of IFloodS "reference" dual-polarimetric radar-based rain maps, and this study documents the process and results as they pertain specifically to efforts using the NPOL radar dataset. The initial portions of the "process" involved dual-polarimetric quality control procedures which employed standard phase and correlation-based approaches to removal of clutter and non-meteorological echo. Calculation of a scale-adaptive KDP was accomplished using the method of Wang and Chandrasekar (2009; J. Atmos. Oceanic Tech.). A dual-polarimetric blockage algorithm based on Lang et al. (2009; J. Atmos. Oceanic Tech.) was then implemented to correct radar reflectivity and differential reflectivity at low elevation angles. Next, hydrometeor identification algorithms were run to identify liquid and ice hydrometeors. After the quality control and data preparation steps were completed several different dual-polarimetric rain estimation algorithms were employed to estimate rainfall rates using rainfall scans collected approximately every two to three minutes throughout the campaign. These algorithms included a polarimetrically-tuned Z-R algorithm that adjusts for drop oscillations (via Bringi et al., 2004, J. Atmos. Oceanic Tech.), and several different hybrid polarimetric variable approaches, including one that made use of parameters tuned to IFloodS 2D Video Disdrometer measurements. Finally, a hybrid scan algorithm was designed to merge the rain rate estimates from multiple low level elevation angle scans (where blockages could not be appropriately corrected) in order to create individual low-level rain maps. Individual rain maps at each time step were subsequently accumulated over multiple time scales for comparison to gauge network data. The comparison results and overall error character depended strongly on rain event type, polarimetric estimator applied, and range from the radar. We will present the outcome of these comparisons and their impact on constructing composited "reference" rainfall maps at select time and space scales.

Radar↗

DOE OSTI2023

Field performance of switchgrass plants engineered for reduced recalcitrance

Switchgrass ( Panicum virgatum L.) is a promising perennial bioenergy crop that achieves high yields with relatively low nutrient and energy inputs. Modification of cell wall composition for reduced recalcitrance can lower the costs of deconstructing biomass to fermentable sugars and other intermediates. We have engineered overexpression of OsAT10 , encoding a rice BAHD acyltransferase and QsuB , encoding dehydroshikimate dehydratase from Corynebacterium glutamicum , to enhance saccharification efficiency in switchgrass. These engineering strategies demonstrated low lignin content, low ferulic acid esters, and increased saccharification yield during greenhouse studies in switchgrass and other plant species. In this work, transgenic switchgrass plants overexpressing either OsAT10 or QsuB were tested in the field in Davis, California, USA for three growing seasons. No significant differences in the content of lignin and cell wall-bound p -coumaric acid or ferulic acid were detected in transgenic OsAT10 lines compared with the untransformed Alamo control variety. However, the transgenic overexpressing QsuB lines had increased biomass yield and slightly increased biomass saccharification properties compared to the control plants. This work demonstrates good performance of engineered plants in the field, and also shows that the cell wall changes in the greenhouse were not replicated in the field, emphasizing the need to validate engineered plants under relevant field conditions.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2019

Turbulence Measurements on a Wing-Fuselage Junction Model for CFD Validation

Current turbulence models, such as those employed in Reynolds-averaged Navier-Stokes CFD, are unable to reliably predict the onset and extent of the three-dimensional separated flow that typically occurs in wing fuselage junctions. To critically assess, as well as to improve upon, existing turbulence models, experimental validation-quality flow field data in the junction region is needed. To that end, NASA has developed a CFD validation experiment for a generic full-span wing-fuselage junction model at subsonic conditions. In this paper, we present and discuss sample results from this effort, with a focus on turbulence measurements in the separated corner flow of the wing-fuselage junction that were obtained with an internally mounted laser Doppler velocimetry (LDV) system. In addition, sample comparisons between the flow field measurements and representative CFD of our test case are presented and here, we highlight some of the key discrepancies.

Kegerise, Michael↗

DOE OSTI2020

Chlorophyll fluorescence imaging captures photochemical efficiency of grain sorghum (Sorghum bicolor) in a field setting

Abstract Background Photosynthesis is one of the most important biological reactions and forms the basis of crop productivity and yield on which a growing global population relies. However, to develop improved plant cultivars that are capable of increased productivity, methods that can accurately and quickly quantify photosynthetic efficiency in large numbers of genotypes under field conditions are needed. Chlorophyll fluorescence imaging is a rapid, non-destructive measurement that can provide insight into the efficiency of the light-dependent reactions of photosynthesis. Results To test and validate a field-deployed fluorescence imaging system on the TERRA-REF field scanalyzer, leaves of potted sorghum plants were treated with a photosystem II inhibitor, DCMU, to reduce photochemical efficiency (F V /F M ). The ability of the fluorescence imaging system to detect changes in fluorescence was determined by comparing the image-derived values with a handheld fluorometer. This study demonstrated that the imaging system was able to accurately measure photochemical efficiency (F V /F M ) and was highly correlated ( r = 0.92) with the handheld fluorometer values. Additionally, the fluorescence imaging system was able to track the decrease in photochemical efficiency due to treatment of DCMU over a 7 day period. Conclusions The system’s ability to capture the temporal dynamics of the plants’ response to this induced stress, which has comparable dynamics to abiotic and biotic stressors found in field environments, indicates the system is operating correctly. With the validation of the fluorescence imaging system, physiological and genetic studies can be undertaken that leverage the fluorescence imaging capabilities and throughput of the field scanalyzer.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1992

A gravity field to support Magellan navigation and science at Venus

The development and validation of the revised JPL Venus Gravity Model are described with attention given to the incorporation of data regarding the longitudinal coverage. The motivation for the JPL Venus Gravity Model 1B (VGM1B) is related to the determination of orbit-support requirements for the Magellan mission. Existing gravity models for Venus are reviewed, and the present model is based on orbit-prediction data taken from Doppler tracking data from the Pioneer Venus Orbiter (PVO). Revised information arrays are developed incorporating more complete data describing the longitudinal conditions of the gravity field. Improvements are noted in the Doppler residual statistics taken from field-validation fits to the PVO and Magellan tracking data by using the VGM1B harmonic field. The VGM1B gravity field is also shown to reduce the trajectory errors from PVO and Magellan navigation.

Mcnamee, J. B.↗

NASA NTRS1995

Traffic Management Advisor: Iterative Field Development and Assessment at Multiple Sites

Previous studies have demonstrated the necessity of involving users in the development of automation aids, especially for complex domains such as air traffic control (ATC). Traditional development only demanded a single field test to validate a completed system, but a more iterative combination of development and assessment ensures that the technology meets the requirements of its application domain. Exposure across an adequate spectrum of field users is also required during development, and the use of multiple development sites provides an opportunity to consider individual facility cultures as they relate to implementation strategies. The development of the Center/TRACON Automation System (CTAS) Traffic Management Advisor (TMA) at the Denver and Dallas ATC facilities demonstrates successful iterative development and assessment at multiple field sites. The use of field development changes the nature of assessment. As development progresses, periodic assessments are required to validate that system development is progressing along an appropriate track. In the development of the TMA, assessments were performed based on software in the field, and input from traffic managers was analyzed and incorporated into subsequent releases of the TMA, to be reassessed in the field. This has led to a tool with operational suitability and broad user acceptance. Assessment at multiple sites provides a more generalizable perspective that allows the production of a system that is both generic enough to be used at different sites and tailored enough to be of use at any site. In addition to providing a better understanding of specific facility requirements, the use of multiple assessment sites in the development of TMA has provided an opportunity to consider individual facility operations, procedures and cultures as they relate to development and implementation strategies.

Sanford, Beverly D.↗

DOE OSTI2021

Cross Validation of the Network of Ground-Based Radar with GPM during the Remote Sensing of Electrification, Lightning, And Mesoscale/Microscale Processes with Adaptive Ground Observations (RELAMPAGO) Field Campaign

The cross-validation of radars in a network is important in making consistent retrievals across the domain and assuring the product quality. During the RELAMPAGO field campaign, two C-band radars, namely the Colorado State University C-band Hydrological Instrument for Volumetric Observations ( CSU-CHIVO) and the C-band Scanning ARM Precipitation Radar (CSAPR-2), were deployed near the Sierras de Cordoba in Argentina, a region known for having some of the most intense severe weather in the world. In addition to these two radars, the operational radar of the Cordoba City, the Radar Meteorologico Argentino 1 (RMA-1), adds another instrument to the RELAMPAGO network. This study presents an intercomparison between the RELAMPAGO C-band radars using the GPM spaceborne radar as a common reference ..A method to bring ground-based radars into better agreement is also proposed. Moreover, the attenuation correction for the C-band radar is studied in the context of intercomparing two radars. The attenuation coefficients are computed for the RELAMPAGO domain using the local disdrometers deployed. during the campaign. After the attenuation correction, CSU-CHIVO, CSAPR-2, and RMA-1 compare well with GPM-DPR with a high correlation and bias less than 1 dB.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2000

Energetic Ion Interactions with the Galilean Satellites

The principal research tasks of this investigation are: (1) specification of the energetic (keV to MeV) ion environments upstream of the four Galilean satellites and (2) data analysis and numerical modeling of observed ion interactions with the satellites. Differential flux spectra are being compiled for the most abundant ions (protons, oxygen, and sulfur) from measurements at 20 keV to 100 MeV total energy by the Energetic Particle Detector (EPD) experiment and at higher ion energies by the Heavy Ion Counter (HIC) experiment. Runge-Kutta and other numerical techniques are used to propagate test particles sampled from the measured upstream spectra to the satellite surface or spacecraft through the local magnetic and corotational electric field environment of each satellite. Modeling of spatial variations in directional flux anisotropies measured during each close flyby provides limits on atomic charge states for heavy (O, S) magnetospheric ions and on internal or induced magnetic fields of the satellites. Validation of models for magnetic and electric field configurations then allows computation of rates for ion implantation, sputtering, and energy deposition into the satellite surfaces for further modeling of observable chemical changes induced by irradiation. Our ongoing work on production of oxidants and other secondary species by ice irradiation on Europa's surface has significant applications, already acknowledged in current literature, to astrobiological evolution. Finally, the work will improve understanding of energetic ion sources and sinks at the satellite orbits for improved modeling of magnetospheric transport processes. The scope of the research effort mainly includes data from the primary Galileo mission (1995-1997) but may also include some later data where directly relevant (e.g., comparison of J0 and I27 data for Io) to the primary mission objectives. Funding for this contract also includes partial support for our related education and public outreach activity, 'Interaction of Magnetospheric Particles Applied to Classroom Teaching (IMPACT).'

Cooper, John F.↗

NASA NTRS2005

Analysis of Raman Lidar and radiosonde measurements from the AWEX-G field campaign and its relation to Aqua validation

Early work within the Aqua validation activity revealed there to be large differences in water vapor measurement accuracy among the various technologies in use for providing validation data. The validation measurements were made at globally distributed sites making it difficult to isolate the sources of the apparent measurement differences among the various sensors, which included both Raman lidar and radiosonde. Because of this, the AIRS Water Vapor Experiment-Ground (AWEX-G) was held in October - November, 2003 with the goal of bringing validation technologies to a common site for intercomparison and resolution of the measurement discrepancies. Using the University of Colorado Cryogenic Frostpoint Hygrometer (CFH) as the water vapor reference, the AWEX-G field campaign resulted in new correction techniques for both Raman lidar, Vaisala RS80-H and RS90/92 measurements that significantly improve the absolute accuracy of those measurement systems particularly in the upper troposphere. Mean comparisons of radiosondes and lidar are performed demonstrating agreement between corrected sensors and the CFH to generally within 5% thereby providing data of sufficient accuracy for Aqua validation purposes. Examples of the use of the correction techniques in radiance and retrieval comparisons are provided and discussed.

Whiteman, D. N.↗

NASA NTRS2018

Physics-Based Retrieval of Surface Roughness Parameters for Bare Soils from Combined Active-Passive Microwave Signatures

In the past the effect of soil roughness was often considered secondary within the determination of soil moisture from remote sensing data. Several studies showed that accurate determination of soil roughness leads to an improved estimation of soil moisture. Two default parameters to describe the surface roughness are the standard deviation of the surface height variation 𝑠 and the surface correlation length 𝑙 with its corresponding autocorrelation function. Both parameters (𝑠,𝑙) affect the emissivity measured by radiometers as well as the backscattering observed by radars. In this study, we develop a physics-based approach to retrieve 𝑠 and 𝑙 by combining both microwave signals based on active-passive microwave covariation. To test the approach, containing a forward model and a retrieval algorithm, we used active/passive microwave data measured with the ComRAD truck-based SMAP simulator at L-band. Results and validations with corresponding field measurements on ground show that 𝑠 and 𝑙 can be estimated simultaneously when using this approach. The physics-based retrieval algorithm works robustly for two investigated test fields having an RMS-Error of 0.68 cm and 0.69 cm between the microwave-based and field-measured 𝑠-values, and of 3.13 cm and 3.04 cm for 𝑙-values. The first validation of the results reveals that the influence of the autocorrelation function, needed within the retrieval, is distinct.

correlation length↗

DOE OSTI2022

Optimization of Water-Alternating-CO2 Injection Field Operations Using a Machine-Learning-Assisted Workflow

Summary This paper will present a robust workflow to address multiobjective optimization (MOO) of carbon dioxide (CO2)-enhanced oil recovery (EOR)-sequestration projects with a large number of operational control parameters. Farnsworth unit (FWU) field, a mature oil reservoir undergoing CO2 alternating water injection (CO2-WAG) EOR, will be used as a field case to validate the proposed optimization protocol. The expected outcome of this work would be a repository of Pareto-optimal solutions of multiple objective functions, including oil recovery, carbon storage volume, and project economics. FWU’s numerical model is used to demonstrate the proposed optimization workflow. Because using MOO requires computationally intensive procedures, machine-learning-based proxies are introduced to substitute for the high-fidelity model, thus reducing the total computation overhead. The vector machine regression combined with the Gaussian kernel (Gaussian-SVR) is used to construct proxies. An iterative self-adjusting process prepares the training knowledge base to develop robust proxies and minimizes computational time. The proxies’ hyperparameters will be optimally designed using Bayesian optimization to achieve better generalization performance. Trained proxies will be coupled with multiobjective particle swarm Optimization (MOPSO) protocol to construct the Pareto-front solution repository. The outcomes of this workflow will be a repository containing Pareto-optimal solutions of multiple objectives considered in the CO2-WAG project. The proposed optimization workflow will be compared with another established methodology using a multilayer neural network (MLNN) to validate its feasibility in handling MOO with a large number of parameters to control. Optimization parameters used include operational variables that might be used to control the CO2-WAG process, such as the duration of the water/gas injection period, producer bottomhole pressure (BHP) control, and water injection rate of each well included in the numerical model. It is proved that the workflow coupling Gaussian-SVR proxies and the iterative self-adjusting protocol is more computationally efficient. The MOO process is made more rapid by squeezing the size of the required training knowledge base while maintaining the high accuracy of the optimized results. The outcomes of the optimization study show promising results in successfully establishing the solution repository considering multiple objective functions. Results are also verified by validating the Pareto fronts with simulation results using obtained optimized control parameters. The outcome from this work could provide field operators an opportunity to design a CO2-WAG project using as many inputs as possible from the reservoir models. The proposed work introduces a novel concept that couples Gaussian-SVR proxies with a self-adjusting protocol to increase the computational efficiency of the proposed workflow and to guarantee the high accuracy of the obtained optimized results. More importantly, the workflow can optimize a large number of control parameters used in a complex CO2-WAG process, which greatly extends its utility in solving large-scale MOO problems in various projects with similar desired outcomes.

Energy & Fuels↗

DOE OSTI2026

Reactive Transport Modeling with Physics-Informed Machine Learning for Critical Minerals Applications

This study presents a physics-informed neural network (PINN) framework for reactive transport modeling for simulating fast bimolecular reactions in porous media. Accurate characterization of cAhemical interactions and product formation in surface and subsurface environments is essential for advancing critical mineral extraction and related geoscience applications. The proposed methodology sequentially addresses the flow and diffusion–reaction subproblems. The flow field is computed using a mixed formulation, while the diffusion–reaction system is modeled via two uncoupled tensorial diffusion equations reformulated in terms of chemical invariants. PINNs are employed to solve the governing equations, enabling data-efficient, mesh-free prediction of chemical concentration fields. The framework is validated through a series of benchmark problems involving flow in heterogeneous porous media. Initial verification is conducted using patch tests for the flow field, followed by validation of the transport problem with emphasis on preserving non-negativity of concentrations. The complete fast bimolecular reaction scenario is then solved, yielding spatial distributions of reactants and product species. Results demonstrate that the PINNs-based approach effectively captures sharp, mixing-limited reaction fronts and dispersive mixing behavior, offering reliable predictions of reactive plume evolution. These capabilities are crucial for evaluating long-term subsurface behavior in applications such as fluid storage, energy extraction, and efficient extraction of critical minerals.

42 ENGINEERING↗

DOE OSTI2025

Southwest Regional Partnership on Carbon Sequestration: Phase III (Final Scientific/Technical Report)

The Southwest Regional Partnership on Carbon Sequestration (SWP) is one of 7 regional partnerships formed in 2003 under the U.S. Department of Energy’s (DOE) Regional Carbon Sequestration Partnerships (RCSPs) initiative. The overall purpose of the initiative was to help determine and implement the technology, infrastructure, and regulations most appropriate to promote carbon storage in different regions of the country. Covering Arizona, Colorado, New Mexico, Oklahoma, Utah, and parts of Texas, Wyoming, and Kansas, the SWP evaluated regional carbon storage and utilization potential and focused on technologies and sites that could complement the region’s strong position in energy production. The project progressed through three phases: • Phase I (2003–2005): Characterized regional geologic formations and CO 2 sources, assessed sequestration potential, and identified pilot test sites. • Phase II (2005–2013): Conducted small-scale field tests to validate sequestration methods, including geologic and terrestrial projects. • Phase III (2008–2022): Demonstrated large-scale CO 2 injection at a commercial oil field to test monitoring, verification, and long-term storage strategies. This report covers Phase III. The final project site, the Farnsworth Unit (FWU) in Texas, provided real-world testing of reservoir characterization, monitoring, and risk evaluation tools and processes that could be used in any commercial scale carbon capture, utilization, and storage (CCUS) project. Extensive data collection and analysis helped refine best practices for reservoir characterization, injection monitoring, and storage verification. The SWP contributed to national databases, DOE best practice manuals, and regional geological assessments to support future sequestration efforts. Key lessons learned include the importance of robust data management, strategic site selection, regulatory navigation, and effective industry collaboration. The project’s findings will inform ongoing and future carbon storage initiatives. Task 1 (Regional Characterization) • The SWP continued to participate in national outreach efforts and NATCARB. • The SWP evaluated multiple potential sites before selecting the FWU as the primary field test location. Task 2 (Public Outreach and Education) • The SWP contributed to national databases, DOE best practice manuals, and regional geological assessments to support future sequestration efforts. Task 3 (Permitting and Regulatory Compliance) • The SWP ensured compliance with federal and state regulations, including National Environmental Policy Act (NEPA) requirements. • The SWP obtained all necessary permits for drilling, injection, and monitoring activities. Task 4 (Site Characterization and Planning) • The SWP developed work plans for four key activities: characterization, simulation, monitoring and verification, and risk evaluation. • The SWP collected and synthesized legacy data from multiple sources to build initial static geological models and dynamic reservoir models demonstrating project feasibility. • The SWP conducted an initial risk evaluation and developed mitigation plans. Task 5 (Field Operations and Data Collection) • The SWP drilled, logged, and cored three characterization wells to gather critical subsurface data. • The SWP conducted multiple geophysical surveys, including 3D seismic, crosswell seismic, and vertical seismic profiling, to improve reservoir characterization. Task 6 (Monitoring and Verification) • The SWP performed extensive geological characterization using data from characterization wells and seismic surveys. • The SWP established a surface monitoring network to track CO 2 flux in soil gas, groundwater chemistry, and near-surface atmospheric CO 2 levels. • The SWP built and refined reservoir models to study the effects of relative permeability on simulation behavior and improve calibration with experimental data. Task 7 (Risk Assessment and Model Refinement) • The SWP conducted multiple studies to evaluate reservoir integrity, predict CO 2 plume behavior and improve predictive modeling capabilities. • The SWP refined geological models and used them to enhance the accuracy of simulation models. • The SWP continued quantitative risk assessment of top-ranked risks and strengthened the link between qualitative and quantitative risk methodologies.

02 PETROLEUM↗

NASA NTRS1986

The water vapour budget of the stratosphere studied using LIMS and SAMS satellite data

Monthly zonal mean observations of H2O and CH4 made by the limb infrared monitor of the stratosphere and the stratospheric and mesospheric sounder instruments on Nimbus 7 have been used to investigate whether the H2O mixing ratios in the stratosphere are consistent with a source via the oxidation of CH4. While both sets of data show considerable seasonally varying structure, total hydrogen (neglecting molecular hydrogen) is relatively featureless with a mean value over the stratosphere of 6.0 + or - 0.35 ppmm(1sigma) for the five-month period studied. The uniformity of the total hydrogen fields points to the validity of the CH4 oxidation hypothesis. The derived fields of total hydrogen are used to deduce a mean H2O mixing ratio for air as it enters the stratosphere of 2.7 + or - 0.35 ppmv (1sigma) from which a desiccation temperature may be deduced.

Jones, R. L.↗

NASA NTRS1993

Passive millimeter-wave imaging

Millimeter-wave hardware systems are being developed. Our approach begins with identifying and defining the applications. System requirements are then specified based on mission needs using our end-to-end performance model. The model was benchmarked against existing data bases and, where data is deficient, it is acquired via field measurements. The derived system requirements are then validated with the appropriate field measurements using our imaging testbeds and hardware breadboards. The result is a final system that satisfies all the requirements of the target mission.

Young, Stephen K.↗