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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 NTRS2012

NASA Tech Briefs, November 2012

The topics include: Visual System for Browsing, Analysis, and Retrieval of Data (ViSBARD); Time-Domain Terahertz Computed Axial Tomography NDE System; Adaptive Sampling of Time Series During Remote Exploration; A Tracking Sun Photometer Without Moving Parts; Surface Temperature Data Analysis; Modular, Autonomous Command and Data Handling Software with Built-In Simulation and Test; In-Situ Wire Damage Detection System; Amplifier Module for 260-GHz Band Using Quartz Waveguide Transitions; Wideband Agile Digital Microwave Radiometer; Buckyball Nucleation of HiPco Tubes; FACT, Mega-ROSA, SOLAROSA; An Integrated, Layered-Spinel Composite Cathode for Energy Storage Applications; Engineered Multifunctional Surfaces for Fluid Handling; Polyolefin-Based Aerogels; Adjusting Permittivity by Blending Varying Ratios of SWNTs; Gravity-Assist Mechanical Simulator for Outreach; Concept for Hydrogen-Impregnated Nanofiber/Photovoltaic Cargo Stowage System; DROP: Durable Reconnaissance and Observation Platform; Developing Physiologic Models for Emergency Medical Procedures Under Microgravity; Spectroscopic Chemical Analysis Methods and Apparatus; Low Average Sidelobe Slot Array Antennas for Radiometer Applications; Motion-Corrected 3D Sonic Anemometer for Tethersondes and Other Moving Platforms; Water Treatment Systems for Long Spaceflights; Microchip Non-Aqueous Capillary Electrophoresis (MicronNACE) Method to Analyze Long-Chain Primary Amines; Low-Cost Phased Array Antenna for Sounding Rockets, Missiles, and Expendable Launch Vehicles; Mars Science Laboratory Engineering Cameras; Seismic Imager Space Telescope; Estimating Sea Surface Salinity and Wind Using Combined Passive and Active L-Band Microwave Observations; A Posteriori Study of a DNS Database Describing Super critical Binary-Species Mixing; Scalable SCPPM Decoder; QuakeSim 2.0; HURON (HUman and Robotic Optimization Network) Multi-Agent Temporal Activity Planner/Scheduler; MPST Software: MoonKommand

Source record↗
NASA NTRS2013

Characterization and Correction of Aquarius Long Term Calibration Drift Using On-Earth Brightness Temperature Refernces

The Aquarius/SAC-D mission was launched on June 10, 2011 from Vandenberg Air Force Base. Aquarius consists of an L-band radiometer and scatterometer intended to provide global maps of sea surface salinity. One of the main mission objectives is to provide monthly global salinity maps for climate studies of ocean circulation, surface evaporation and precipitation, air/sea interactions and other processes. Therefore, it is critical that any spatial or temporal systematic biases be characterized and corrected. One of the main mission requirements is to measure salinity with an accuracy of 0.2 psu on montly time scales which requires a brightness temperature stability of about 0.1K, which is a challenging requirement for the radiometer. A secondary use of the Aquarius data is for soil moisture applications, which requires brightness temperature stability at the warmer end of the brightness temperature dynamic range. Soon after launch, time variable drifts were observed in the Aquarius data compared to in-situ data from ARGO and models for the ocean surface salinity. These drifts could arise from a number of sources, including the various components of the retrieval algorithm, such as the correction for direct and reflected galactic emission, or from the instrument brightness temperature calibration. If arising from the brightness temperature calibration, they could have gain and offset components. It is critical that the nature of the drifts be understood before a suitable correction can be implemented. This paper describes the approach that was used to detect and characterize the components of the drift that were in the brightness temperature calibration using on-Earth reference targets that were independent of the ocean model.

Aquarius↗
NASA NTRS2013

Aquarius' Object-Oriented, Plug and Play Component-Based Flight Software

The Aquarius mission involves a combined radiometer and radar instrument in low-Earth orbit, providing monthly global maps of Sea Surface Salinity. Operating successfully in orbit since June, 2011, the spacecraft bus was furnished by the Argentine space agency, Comision Nacional de Actividades Espaciales (CONAE). The instrument, built jointly by NASA's Caltech/JPL and Goddard Space Flight Center, has been successfully producing expectation-exceeding data since it was powered on in August of 2011. In addition to the radiometer and scatterometer, the instrument contains an command & data-handling subsystem with a computer and flight software (FSW) that is responsible for managing the instrument, its operation, and its data. Aquarius' FSW is conceived and architected as a Component-based system, in which the running software consists of a set of Components, each playing a distinctive role in the subsystem, instantiated and connected together at runtime. Component architectures feature a well-defined set of interfaces between the Components, visible and analyzable at the architectural level (see [1]). As we will describe, this kind of an architecture offers significant advantages over more traditional FSW architectures, which often feature a monolithic runtime structure. Component-based software is enabled by Object-Oriented (OO) techniques and languages, the use of which again is not typical in space mission FSW. We will argue in this paper that the use of OO design methods and tools (especially the Unified Modeling Language), as well as the judicious usage of C++, are very well suited to FSW applications, and we will present Aquarius FSW, describing our methods, processes, and design, as a successful case in point.

Component Architecture↗
NASA NTRS2014

Aquarius Radiometer Status

Aquarius was launched on June 10, 2011 as part of the Aquarius/SAC-D observatory and the instrument has been operating continuously since being turned on in August of the same year. The initial map of sea surface salinity was released one month later (September) and the quality of the retrieval has continuously improved since then. The Aquarius radiometers include several special features such as measurement of the third Stokes parameter, fast sampling, and careful thermal control, and a combined passive/active instrument. Aquarius is working well and in addition to helping measure salinity, the radiometer special features are generating new results.

Mircrowave Remote Sensing↗
NASA NTRS2014

Aquarius Whole Range Calibration: Celestial Sky, Ocean, and Land Targets

Aquarius is a spaceborne instrument that uses L-band radiometers to monitor sea surface salinity globally. Other applications of its data over land and the cryosphere are being developed. Combining its measurements with existing and upcoming L-band sensors will allow for long term studies. For that purpose, the radiometers calibration is critical. Aquarius measurements are currently calibrated over the oceans. They have been found too cold at the low end (celestial sky) of the brightness temperature scale, and too warm at the warm end (land and ice). We assess the impact of the antenna pattern model on the biases and propose a correction. We re-calibrate Aquarius measurements using the corrected antenna pattern and measurements over the Sky and oceans. The performances of the new calibration are evaluated using measurements over well instrument land sites.

L-band↗
NASA NTRS2013

Aquarius RFI Detection and Mitigation Algorithm: Assessment and Examples

Aquarius is an L-band radiometer system designed to map sea surface salinity from space. This is a sensitive measurement, and protection from radio frequency interference (RFI) is important for success. An initial look at the performance of the Aquarius RFI detection and mitigation algorithm is reported together with examples of the global distribution of RFI at the L-band. To protect against RFI, Aquarius employs rapid sampling (10 ms) and a "glitch" detection algorithm that looks for outliers among the samples. Samples identified as RFI are removed, and the remainder is averaged to produce an RFI-free signal for the salinity retrieval algorithm. The RFI detection algorithm appears to work well over the ocean with modest rates for false alarms (5%) and missed detection. The global distribution of RFI coincides well with population centers and is consistent with observations reported by the Soil Moisture and Ocean Salinity mission.

remote sensing↗
NASA NTRS2015

Watching the Blue Planet from Space over Recent Decades: What's up for Science and Society?

Since the first photographs of “Earth Rise” taken by the Apollo astronauts in the 1960s galvanized the environmental movement, imaging of our planet from low Earth orbit has grown more sophisticated and diverse. Satellite and astronaut observations and imagery of the changing ocean still have the power to galvanize oceanographers and society. So what are some of the key ideas for oceanography and society that come out of out recent decades of ocean observation from space? Satellite oceanography has made fundamental contributions to our understanding and estimation of changing sea level, winds and storminess over the oceans, primary productivity of the seas, the role of the ocean in the water cycle, and the changes in the ocean known as ocean acidification. Some of these phenomena interact in complex ways and Mother Nature hides the future well. However, some things are clear. Sea level rise has been monitored from space for more than 20 years and now we have a more nuanced understanding of regional variation in sea level rise and the contributions of ocean thermal expansion and the melting of glaciers and ice sheets. Wind vectors at the ocean surface have been measured for more than 2 decades and provide evidence for shifts in wind patterns that help, for example, explain some of the regional variations in sea level rise. Chlorophyll-a has been estimated in a multi-decadal record of observations and is being used to describe the shifts and trends in ocean primary productivity. Sea surface temperature estimation from space has records going back to the 1970s and provides critical information for the interaction of the ocean with the atmosphere. Sea surface salinity has been measured from space only within the last decade and provides a novel new view of regional, seasonal, and inter-annual changes in the ocean related to precipitation, river run-off, and eddy transport. Potential changes in the Earth’s water cycle have a huge societal impact.

Blue Planet from Space↗
NASA NTRS2016

Accurate Measurements of the Dielectric Constant of Seawater at L Band

This paper describes measurements of the dielectric constant of seawater at a frequency of 1.413 GHz, the center of the protected band (i.e., passive use only) used in the measurement of sea surface salinity from space. The objective of the measurements is to accurately determine the complex dielectric constant of seawater as a function of salinity and temperature. A resonant cylindrical microwave cavity in transmission mode has been employed to make the measurements. The measurements are made using standard seawater at salinities of 30, 33, 35, and 38 practical salinity units over a range of temperatures from 0 degree C to 35 degree C in 5 degree C intervals. Repeated measurements have been made at each temperature and salinity. Mean values and standard deviations are then computed. The total error budget indicates that the real and imaginary parts of the dielectric constant have a combined standard uncertainty of about 0.3 over the range of salinities and temperatures considered. The measurements are compared with the dielectric constants obtained from the model functions of Klein and Swift and those of Meissner and Wentz. The biggest differences occur at low and high temperatures.

Measurements↗
NASA NTRS2016

L-Band RFI in Japan

In recent years, three instruments have been launched into orbit with the aim of producing global maps of sea surface salinity and soil moisture using the 1400-1427 MHz band: SMOS, Aquarius and SMAP. Although this frequency band is allocated to passive measurements only, RFI (Radio-Frequency Interference) is present in the data of all three missions. On a global scale, the three sensors have observed approximately the same distribution of RFI. Japan is an important exception that has implications for the design of RFI detection algorithms. RFI in Japan is caused by a large number of emitters belonging to the same system (TV receivers) and for this reason some traditional RFI detection strategies detect little to no RFI over Japan. The study of this case has led to an improvement of the approach to detect RFI in Aquarius data.

Aquarius↗
NASA NTRS2018

Aquarius Final Release Product and Full Range Calibration of L-band Radiometers

Aquarius final product V5.0 has been released. The dataset includes close to four years of global radiometric measurements at L-band. The mission's objective was to monitor sea surface salinity, but other applications of its data over land and the cryosphere have been developed. For this reason, it is important to have accurate calibration over the full range of antenna temperatures from natural targets. It is also needed in order to combine Aquarius measurements with other L-band sensors. Aquarius calibration is strongly focused on the ocean. We present a research product which is part of the final release and aims at producing an accurate calibration from the low end (celestial sky) to the high end (land and ice) of the brightness temperature scale. We calibrate the Aquarius radiometers using measurements over the Sky and oceans and assess the new calibration using measurements over land.

Radiometry↗
NASA NTRS2018

Impacts of NASA's Earth Observations on Subseasonal and Seasonal Forecasts

NASA's suite of Earth-observing satellites provides a unique view of many processes on Earth, with relevance on timescales ranging from hours to weeks and even years. NASA's observations span all parts of the Earth system: atmospheric, ocean, land and cryosphere, and include physical, chemical and biological components. This presentation explores use of NASA observations in extended-range prediction, from many days to months, using the Goddard Earth Observing System (GEOS) assimilation and predictive modeling capabilities. The skill of a weather forecast is linked to the fidelity of the initialization process (data assimilation) and the realistic representation of "fast" physical processes in the model. At longer time horizons, the slower "feedback" processes in the Earth System begin to take a more prominent role in the accuracy of the forecast. Simultaneously, forecast-skill attribution transitions away from feature-based metrics that emphasize smaller scales (e.g., representations of fronts and vortices) to metrics that emphasize the statistical distributions of large-scale features (e.g., ENSO diagnostics and teleconnections). This presentation will summarize studies performed using the GEOS-S2S (subseasonal to seasonal) system that explore the impacts of NASA observations on the fidelity of the forecasts. The GEOS-S2S system is configured for the atmosphere-ocean-land-ice model and is initialized using in-situ and space-based observations, including atmospheric aerosols and ozone which are not typically analyzed in such systems. The GEOS-S2S model routinely includes aerosol feedbacks, which systematically impact the realism of the forecasts, providing a first example of how suitable NASA observations impact the performance of the GEOS-S2S system. Studies in which a stratospheric chemistry module is activated in the GEOS-S2S system allow the impacts of ozone radiative feedbacks to be isolated. Space-based observations of sea-surface temperature and altimetry are routinely analyzed for the initialization of the GEOS-S2S system; recent advances allow the use of NASA's sea-surface salinity data, which are shown to impact the long-range skill of the forecasts.

Pawson, Steven↗
NASA NTRS2019

Statistical Analysis of Aquarius Radiometer Radio Frequency Interference (RFI) and Implications on RFI Detection and Mitigation

The Aquarius/SAC-D mission operated between August 2011 and June 2015 with the main goal of providing global estimates of sea surface salinity (SSS). It comprised both active and passive microwave sensors operating at L-band to observe the same surface area almost simultaneously. Measurements from both instruments underwent subsequent filtering to mitigate the effect of Radio Frequency Interference (RFI). This report describes the analysis of statistics of RFI in samples acquired by the Aquarius radiometers, and its results could be used to improve the performance of the interference detection algorithm.

De Matthaeis, Paolo↗
NASA NTRS2020

GEOS S2S Version 3: The New NASA/GMAO High Resolution Seasonal Prediction System

The NASA/Goddard Global Modeling and Assimilation Office (GMAO) released Version 2 of the Subseasonal to Seasonal (GEOS-S2S) forecast system in the fall of 2017, and it has been producing near-real time subseasonal to seasonal forecasts and a weakly coupled atmosphere-ocean data assimilation record since then. A new version of the coupled modeling and analysis system (Version 3) was released by the GMAO at the end of 2019. The new version runs at higher oceanic resolution than the previous (approximately 1/2 degree for the atmosphere, 1/4 degree for the ocean), and includes interactive earth system model components not typically present in seasonal prediction systems (two moment cloud microphysics for aerosol indirect effect and an interactive aerosol model). The weakly coupled atmosphere-ocean data assimilation system now includes assimilation of sea surface salinity, that has been shown to result in improved ocean mixed layer simulation and ENSO prediction skill.

Molod, Andrea↗
NASA NTRS2021

Seawater Dielectric Constant At L-Band: How Consistent Are New Parametrisations Inferred from Smos and Laboratory Measurements?

The accuracy of the Sea Surface Salinity (SSS) retrieved from L-Band radiometer measurements is strongly dependent on the accuracy of the modelling of the dielectric constant (ε). Two new ε parametrizations have recently been developed based on one hand on the Soil Moisture and Ocean Salinity (SMOS) satellite multi-angular brightness temperature measurements and on the other hand on new laboratory measurements. These two approaches are fully independent. These new ε parametrizations are compared with each other and with the ε models previously in use in the SMOS, Soil Moisture Active Passive (SMAP) and Aquarius SSS retrievals. The two new ε parametrizations are found to be in closer agreement than with earlier parametrizations for most common ocean conditions. We will further study to which extent the recent SMOS CCI+SSS v3 reprocessing confirms the above results and could help resolve remaining inconsistencies.

SMOS↗
NASA NTRS2022

Earth System Model Parameter Adjustment Using a Green's Functions Approach

We demonstrate the practicality and effectiveness of using a Green's functions estimation approach for adjusting uncertain parameters in an Earth system model (ESM). This estimation approach has previously been applied to an intermediate-complexity climate model and to individual ESM components, e.g., ocean, sea ice, or carbon cycle components. Here, the Green's functions approach is applied to a state-of-the-art ESM that comprises a global atmosphere/land configuration of the Goddard Earth Observing System (GEOS) coupled to an ocean and sea ice configuration of the Massachusetts Institute of Technology general circulation model (MITgcm). Horizontal grid spacing is approximately 110 km for GEOS and 37–110 km for MITgcm. In addition to the reference GEOS-MITgcm simulation, we carried out a series of model sensitivity experiments, in which 20 uncertain parameters are perturbed. These “control” parameters can be used to adjust sea ice, microphysics, turbulence, radiation, and surface schemes in the coupled simulation. We defined eight observational targets: sea ice fraction, net surface shortwave radiation, downward longwave radiation, near-surface temperature, sea surface temperature, sea surface salinity, and ocean temperature and salinity at 300 m. We applied the Green's functions approach to optimize the values of the 20 control parameters so as to minimize a weighted least-squares distance between the model and the eight observational targets. The new experiment with the optimized parameters resulted in a total cost reduction of 9 % relative to a simulation that had already been adjusted using other methods. The optimized experiment attained a balanced cost reduction over most of the observational targets. We also report on results from a set of sensitivity experiments that are not used in the final optimized simulation but helped explore options and guided the optimization process. These experiments include an assessment of sensitivity to the number of control parameters and to the selection of observational targets and weights in the cost function. Based on these sensitivity experiments, we selected a specific definition for the cost function. The sensitivity experiments also revealed a decreasing overall cost as the number of control variables was increased. In summary, we recommend using the Green's functions estimation approach as an additional fine-tuning step in the model development process. The method is not a replacement for modelers' experience in choosing and adjusting sensitive model parameters. Instead, it is an additional practical and effective tool for carrying out final adjustments of uncertain ESM parameters.

Green's Function↗
NASA NTRS2022

The Global L-Band Observatory for Water Cycle Studies (Glows)– SMAP continuity Mission

SMOS and SMAP radiometers have demonstrated the ability to monitor soil moisture and sea surface salinity and continue to provide high quality radiometric measurements to this day in extended mission operations. It is important to maintain data continuity for these science measurements. The proposed instrument concept (Global L-band active/passive Observatory for Water cycle Studies - GLOWS) will enable low-cost L-band data continuity (that includes both L-band radar and radiometer measurements). The objective of this project is to develop key instrument technology to enable L-band observations using an Earth Venture class satellite. Specifically, a new deployable reflectarray lens antenna is being developed that will enable a smaller EELV Secondary Payload Adapter (ESPA) Grande-class satellite mission to continue the L-band observations at SMAP and SMOS resolution and accuracy at substantially lower cost, size, and weight

SMAP↗
NASA NTRS2004

Microwave Remote Sensing Modeling of Ocean Surface Salinity and Winds Using an Empirical Sea Surface Spectrum

Active and passive microwave remote sensing techniques have been investigated for the remote sensing of ocean surface wind and salinity. We revised an ocean surface spectrum using the CMOD-5 geophysical model function (GMF) for the European Remote Sensing (ERS) C-band scatterometer and the Ku-band GMF for the NASA SeaWinds scatterometer. The predictions of microwave brightness temperatures from this model agree well with satellite, aircraft and tower-based microwave radiometer data. This suggests that the impact of surface roughness on microwave brightness temperatures and radar scattering coefficients of sea surfaces can be consistently characterized by a roughness spectrum, providing physical basis for using combined active and passive remote sensing techniques for ocean surface wind and salinity remote sensing.

Sea surface spectrum↗
NASA NTRS2024

Characterizing the California Current System through Sea Surface Temperature and Salinity

Characterizing temperature and salinity (T-S) conditions is a standard framework in oceanography to identify and describe deep water masses and their dynamics. At the surface, this practice is hindered by multiple air–sea–land processes impacting T-S properties at shorter time scales than can easily be monitored. Now, however, the unsurpassed spatial and temporal coverage and resolution achieved with satellite sea surface temperature (SST) and salinity (SSS) allow us to use these variables to investigate the variability of surface processes at climate-relevant scales. In this work, we use SSS and SST data, aggregated into domains using a cluster algorithm over a T-S diagram, to describe the surface characteristics of the California Current System (CCS), validating them with in situ data from uncrewed Saildrone vessels. Despite biases and uncertainties in SSS and SST values in highly dynamic coastal areas, this T-S framework has proven useful in describing CCS regional surface properties and their variability in the past and in real time, at novel scales. This analysis also shows the capacity of remote sensing data for investigating variability in land–air–sea interactions not previously possible due to limited in situ data.

Marisol García-Reyes↗