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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 181 records · Page 10
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NASA NTRS2023

Single-Band VLBI Absolute Astrometry

The ionospheric path delay impacts single-band very long baseline interferometry (VLBI) group delays, which limits their applicability for absolute astrometry. I consider two important cases: when observations are made simultaneously in two bands, but delays in only one band are available for a subset of observations and when observations are made at one band design. I developed optimal procedures of data analysis for both cases using Global Navigation Satellite System (GNSS) ionosphere maps, provided a stochastic model that describes ionospheric errors, and evaluated their impact on source position estimates. I demonstrate that the stochastic model is accurate at a level of 15%. I found that using GNSS ionospheric maps as is introduces serious biases in estimates of declination and I developed a procedure that almost eliminates them. I found serendipitously that GNSS ionospheric maps have multiplicative errors and have to be scaled by 0.85 in order to mitigate the declination bias. A similar scale factor was found in comparison of the vertical total electron content from satellite altimetry against GNSS ionospheric maps. I favor interpretation of this scaling factor as a manifestation of the inadequacy of the thin shell model of the ionosphere. I showed that we are able to model the ionospheric path delay to the extent that no noticeable systematic errors emerge and we are able to assess adequately the contribution of the ionosphere-driven random errors on source positions. This makes single-band absolute astrometry a viable option that can be used for source position determination.

Radio astrometry↗
NASA NTRS2023

The Faraday Effect Tracker of Coronal and Heliospheric Structure (FETCH) Instrument

There continue to be open questions regarding the solar wind and coronal mass ejections (CMEs). For example: how do magnetic fields within CMEs and corotating/stream interaction regions (CIRs/SIRs) evolve in the inner heliosphere? What is the radially distributed magnetic profile of shock-driving CMEs? What is the internal magnetic structure of CMEs that cause magnetic storms? It is clear that these questions involve the magnetic configurations of solar wind and transient interplanetary plasma structures, for which we have limited knowledge. In order to better understand the origin of the magnetic field variability in steady-state structures and transient events, it is necessary to probe the magnetic field in Earth-directed structures/disturbances. This is the goal of the Multiview Observatory for Solar Terrestrial Science (MOST) mission (Gopalswamy et al., 2022). For MOST to answer the aforementioned questions, we propose the instrument concept of the Faraday Effect Tracker of Coronal and Heliospheric structures (FETCH), a simultaneous quad-line-of-sight polarization radio remote-sensing instrument. With FETCH, spacecraft radio beams passing through the Sun–Earth line offer the possibility of obtaining information of plasma conditions via analysis of radio propagation effects such as Faraday rotation and wave dispersion, which provide information of the magnetic field and total electron content (TEC). This is the goal of the FETCH instrument, one of ten instruments proposed to be hosted on the MOST mission. The MOST mission will provide an unprecedented opportunity to achieve NASA’s heliophysics science goal to “explore and characterize the physical processes in the space environment from the Sun” (Gopalswamy et al., 2022).

Solar corona↗
NASA NTRS2021

Applying Machine Learning to Predict Alaskan Ionospheric Irregularities

In this work several machine-learning (ML) techniques for predicting ionospheric irregularities in the northern auroral zone were tested. The techniques include Ridge Regression, Long Short-Term Memory Neural Network (LSTM), Classification Neural Network (CNN), Autoencoder Classification Neural Network (ACNN), and LSTM Autoencoder Classification Neural Network (LACNN). These techniques were tested with the rate of total electron content (TEC) index (ROTI) data collected during 2008 and 2009 from a geodetic station in Fairbanks, Alaska (64.98°N, 147.50°W), which is in the auroral zone. Using ROTI data with the ML techniques, experiments were conducted to reach two goals: (1) examine what space weather measurements present good correlation with ROTI so that they may be helpful in ML-based prediction of ionospheric irregularities in the polar region; (2) predict ROTI hours and days ahead by training the neural network models with historical ROTI data alone. The Ridge Regression experiments indicate that a combination of measurements of local geomagnetic horizontal components, geomagnetic SYM-H index, 3-hour Kp and ap indices, and F10.7 solar flux index appears to be more correlated to the single-site ROTI measurements than other parameters. The neural network (NN) experiments show that although the LACNN model allows for predictions of non-irregularity and irregularity conditions defined by ROTI levels up to 3 hours in advance, with an overall accuracy ≥ 92%, a number of irregularity events can still be missed. Hence, further development is needed to reduce the number of missed events. In this paper, the models, data processing, model performance, prediction results, and potential applications are presented.

Pi, Xiaoqing↗
NASA NTRSDate not supplied

Global Ionospheric Electron Density from GNSS-POD Limb Measurements

GNSS-LEO radio links from Precise Orbital Determination (POD) and Radio Occultation (RO) antennas have been used increasingly in studying and monitoring the global ionospheric electron density (Ne). In this study we developed an optimal estimation (OE) method to retrieve Ne profiles from the slant total electron content (hTEC) measurements acquired by the GNSS-POD links at negative elevation angles. The hmF2 and NmF2 from the OE retrieval are validated against ground-based ionosondes and radar observations, showing generally good agreements in NmF2 from all sites. Nighttime hmF2 measurements tend to agree better than the daytime when the ionosonde heights tend to be slightly lower. The OE algorithm has been applied to all GNSS-POD data acquired from the COSMIC-1 (2006-2019), COSMIC-2 (2019-present), and Spire (2019-present) constellations, showing a consistent ionospheric Ne morphology. A detailed analysis of the frequency-wavenumber spectra is made for the Ne variability at different heights. In the lower ionosphere (~150 km) we found significant spectral power in DE1, DW6, DW4, SW5, and SE4 wave components, in addition to well-known DW1, SW2 and DE3 waves. In the upper ionosphere (~450 km), additional wave components are still present, including DE4, DW4, DW6, SE4 and SW4. The co-exist of eastward and westward propagating WN4 components implies the presence of a stationary planetary wave4 (sPW4), as suggested by other earlier studies.

GNSS-POD↗
NASA NTRSDate not supplied

Improvements to the Simulated CubeSpark Satellite Constellation and Their Effects on Lightning Geolocation Accuracy from Orbit

The CubeSpark mission concept is being developed as a constellation of up to six satellites in low-Earth orbit (LEO) for high resolution 3D lightning mapping using optical and radio frequency (RF) sensors. Individual lightning VHF signals are simulated from Earth’s atmosphere through the ionosphere to each satellite, using their arrival times to reconstruct source locations. Here we present recent updates to these simulations based on improved ionospheric modeling, with a focus on the expected three-dimensional resolution. These studies include testing from the equator up to high latitudes, with varying vertical total electron content (vTEC), and using between one and six orbiting stations. In addition to the more robust ionosphere model, the constellation formation has also been updated to reduce its resulting errors and increase the effective range of VHF geolocation from space. The goals of CubeSpark include mapping thundercloud charge structure as well as lightning channel lengths relevant to climatology, meteorology, and more. These applications require location uncertainty less than 1-2 km in each dimension. This improved algorithm shows sufficient resolution up to high latitudes, including significantly larger areas having 3D resolution less than 1 km. Analysis of the distributions of biases in simulated arrival times has also revealed the unexpected relationship between the shape of those distributions and the resulting uncertainties. This work helps to refine our understanding of the sources of error in lightning geolocation and reinforces the potential for post-processing improvements in this and other similar systems.

Lightning↗
NASA NTRS2023

Optimal Estimation Inversion of Ionospheric Electron Density from GNSS-POD Limb Measurements: Part I-Algorithm and Morphology

GNSS-LEO radio links from Precise Orbital Determination (POD) and Radio Occultation (RO) antennas have been used increasingly in characterizing the global 3D distribution and variability of ionospheric electron density (N e ). In this study, we developed an optimal estimation (OE) method to retrieve N e profiles from the slant total electron content (hTEC) measurements acquired by the GNSS-POD links at negative elevation angles (ε < 0°). Although both OE and onion-peeling (OP) methods use the Abel weighting function in the N e inversion, they are significantly different in terms of performance in the lower ionosphere. The new OE results can overcome the large N e oscillations, sometimes negative values, seen in the OP retrievals in the E-region ionosphere. In the companion paper in this Special Issue, the HmF2 and NmF2 from the OE retrieval are validated against ground-based ionosondes and radar observations, showing generally good agreements in NmF2 from all sites. Nighttime hmF2 measurements tend to agree better than the daytime when the ionosonde heights tend to be slightly lower. The OE algorithm has been applied to all GNSS-POD data acquired from the COSMIC-1 (2006–2019), COSMIC-2 (2019–present), and Spire (2019–present) constellations, showing a consistent ionospheric N e morphology. The unprecedented spatiotemporal sampling of the ionosphere from these constellations now allows a detailed analysis of the frequency–wavenumber spectra for the N e variability at different heights. In the lower ionosphere (~150 km), we found significant spectral power in DE1, DW6, DW4, SW5, and SE4 wave components, in addition to well-known DW1, SW2, and DE3 waves. In the upper ionosphere (~450 km), additional wave components are still present, including DE4, DW4, DW6, SE4, and SW4. The co-existence of eastward- and westward-propagating wave4 components implies the presence of a stationary wave4 (SPW4), as suggested by other earlier studies. Further improvements to the OE method are proposed, including a tomographic inversion technique that leverages the asymmetric sampling about the tangent point associated with GNSS-LEO links.

GNSS constellation↗
NASA NTRS2023

Optimal Estimation Inversion of Ionospheric Electron Density from GNSS-POD Limb Measurements: Part II-Validation and Comparison Using NmF2 and hmF2

A growing number of SmallSat/CubeSat constellations with high-rate (50–100 Hz) global navigation satellite system radio occultations (GNSS-RO) as well as low-rate (1 Hz) precise orbit determination (GNSS-POD) limb-viewing capabilities provide unprecedented spatial and temporal sampling rates for ionospheric studies. In the F-region electron density (N 𝑒 ) retrieval process, instead of the conventional onion-peeling (OP) inversion, an optimal estimation (OE) inversion technique was recently developed using total electron content measurements acquired by GNSS-POD link. The new technique is applied to data acquired from the COSMIC-1, COSMIC-2, and Spire constellations. Although both OE and OP techniques use the Abel weighting function in N 𝑒 inversion, OE significantly differs in its performance, especially in the lower F- and E-regions. In this work, we evaluate and compare newly derived data sets using F2 peak properties with other space-based and ground-based observations. We determine the F2 peak N 𝑒 (NmF2) and its altitude (hmF2), and compare them with the OP-retrieved values. Good agreement is observed between the two techniques for both NmF2 and hmF2. In addition, we also utilize autoscaled F2 peak measurements from a number of worldwide Digisonde stations (∼30). The diurnal sensitivity and latitudinal variability of the F2 peak between the two techniques are carefully studied at these locations. Good agreement is observed between OE-retrieved NmF2 and Digisonde-measured NmF2. However, significant differences appear between OE-retrieved hmF2 and Digisonde-measured hmF2. During the daytime, Digisonde-measured hmF2 remains ∼25–45 km below the OE-retrieved hmF2, especially at mid and high latitudes. We also incorporate F-region N 𝑒 measurements from two incoherent scatter radar observations at high latitudes, located in the North American (Millstone Hill) and European (EISCAT at Tromso) sectors. The radar measurements show good agreement with OE-retrieved values. Although there are several possible sources of error in the ionogram-derived N 𝑒 profiles, our further analysis on F1 and F2 layers indicates that the low Digisonde hmF2 is caused by the autoscaled method, which tends to detect a height systematically below the F2 peak when the F1 layer is present.

GNSS radio occultation↗
NASA NTRS1974

Protonospheric columnar electron content determination. II - Observations

The results of over 300 hours of measurements of the quantity I sub w - the difference between total columnar electron content, derived from the differential phase-path data, and Faraday electron content - is presented. The interpretation of the measurements in terms of protonospheric content is discussed in the light of a previous analysis which demonstrates that good protonospheric content measurements can only be obtained under certain geometries of observations unless information on the shape and height of the ionospheric layer is available. A strong correlation between I sub w and the ionospheric content is observed in most of the Arecibo data, because they were collected under unfavorable conditions. The Stanford data, on the other hand, yield good measurements of the protonospheric content. The May 1969 observations show a strong depletion of protonospheric content during a magnetic storm and its subsequent recovery. This is in general agreement with flux tube content behavior observed by the whistler technique during similar conditions.

Almeida, O. G.↗
NASA NTRS1973

Protonospheric columnar electron content determination. I - Analysis.

A combination of phase-path length difference and Faraday rotation angle data obtained from geostationary satellite transmissions is used to determine the integration constant necessary to convert phase-path length difference information into absolute values of total slant columnar electron content. The total content thus determined, which is the sum of the ionospheric and protonospheric contents, is measured with uncertainties about one order of magnitude smaller than the value of the protonospheric content. It is thus, in principle, possible to determine the latter by subtracting from the measurement the so-called 'Faraday content.' This idea, proposed by several authors in the past, is critically examined in the present paper. It is impossible to totally eliminate the ionospheric contribution to the measurements; however, it is shown that the degree of elimination depends on the type of distribution of the longitudinal component of the geomagnetic field along the path of observation. Satisfactory minimization of the ionospheric contribution can be accomplished only under certain geometries of observation.

Almeida, O. G.↗
NASA NTRS1974

Plasmaspheric effects on one way satellite timing signals

The effects of the ionospheric retardation of satellite-emitted timing signals was presented. The retardation at the navigation frequencies, which is proportional to the total ionospheric electron content (TEC), was determined by Faraday polarization measurements of VHF emissions of a geostationary satellite. The polarization data yielded TEC up to approximately 1200 km only, since the measurement technique is based on the Faraday effect which is weighted by the terrestrial magnetic field.

Gorman, F. J., Jr.↗
NASA NTRS1976

Doppler noise considered as a function of the signal path integration of electron density

The hypothesis is advanced that observed Doppler noise during solar conjunctions is proportional to total columnar electron content along the signal path. This assumption leads directly to a geometrical model (ISED) for observed Doppler noise which is shown to be in very good agreement with Doppler noise data accumulated during the 1975 Pioneer 10, Pioneer 11 and Helios 1 solar conjunctions. An augmented model is constructed which quantitatively indicates correlation between earth observed sunspot activity and systematic, cyclical deviations from the ISED model.

Berman, A. L.↗
NASA NTRS1979

ATS-6 satellite radio beacon measurements at Ootacamund, India

ATS-6 radio beacon measurements of modulation phase and Faraday rotation made at Ootacamund, India in 1975-1976 are discussed with emphasis on the measurement and analysis errors. The modulation-phase errors are insensitive to the geomagnetic field and provide an accurate determination of the total columnar electron content. Comparison of modulation-phase measurements at different frequencies shows a minor sensitivity to the ATS-6 pitch angle. For the low geomagnetic latitude and nearly transverse propagation conditions of Ootacamund, the use of a fixed conversion coefficient gives an unreliable Faraday content. However, the Faraday rotation measurements may be used to determine the shape factor F, which provides information about the electron density height profile.

Davies, K.↗
NASA NTRS2002

An assessment of the current WAAS algorithm in the South American region

In this paper, we use a network of 230 GPS receivers worldwide, each equipped with dual-frequency GPS receivers. We assessed the WAAS's planar fit algorithm in the equatorial region where the spatial gradients and the absolute slant TEC are known to be the highest in the world.

GPS total electron content ionosphere validation m↗