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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Observing Traveling Ionospheric Disturbances Caused by Tsunamis Using GPS TEC Measurements

Ground-based Global Positioning System (GPS) measurements of ionospheric Total Electron Content (TEC) show variations consistent with atmospheric internal gravity waves caused by ocean tsunamis following two recent seismic events: the American Samoa earthquake of September 29, 2009, and the Chile earthquake of February 27, 2010. Fluctuations in TEC correlated in time, space, and wave properties with these tsunamis were observed in TEC estimates processed using JPL's Global Ionospheric Mapping Software. These TEC estimates were band-pass filtered to remove ionospheric TEC variations with wavelengths and periods outside the typical range of internal gravity waves caused by tsunamis. Observable variations in TEC appear correlated with the tsunamis in certain locations, but not in others. Where variations are observed, the typical amplitude tends to be on the order of 1% of the background TEC value. Variations with amplitudes ~ 0.1 - 0.2 TECU are observable with periods and timing affiliated with the tsunami. These observations are compared to estimates of expected tsunami-driven TEC variations produced by Embry Riddle Aeronautical University's Spectral Full Wave Model, an atmosphere-ionosphere coupling model, and found to be in good agreement in some locations, though there are cases when the model predicts an observable tsunami-driven signature and none is observed. These TEC variations are not always seen when a tsunami is present, but in these two events the regions where a strong ocean tsunami was observed did coincide with clear TEC observations, while a lack of clear TEC observations coincided with smaller tsunami amplitudes. There exists the potential to apply these detection techniques to real-time GPS TEC data, providing estimates of tsunami speed and amplitude that may be useful for early warning systems.

Galvan, David A.↗
NASA NTRS2016

Faraday Rotation for SMOS Retrievals of Ocean Salinity and Soil Moisture

Faraday rotation is a change in polarization as radiation propagates from the surface through the ionosphere to the sensor. At L-band (1.4 GHz) this change can be significant and can be important for the remote sensing of soil moisture and ocean salinity from space. Consequently, modern L-band radiometers (SMOS, Aquarius and SMOS) are polarimetric to measure Faraday rotation in situ so that a correction can be made. This is done using the ratio of the third and second Stokes parameters. In the case of SMOS this procedure has produced very noisy estimates. An alternate procedure is reported here in which the total electron content is estimated and averaged to reduce noise.

Microwave remote sensing↗
NASA NTRS2018

Survey of Localized Solar Flare Signatures in the Ionosphere with GNSS, VLF, and GOES Observations

Global navigation satellite system (GNSS) phase measurements of the total electron content (TEC) and ionospheric delay are sensitive to sudden increases in electron density in the layers of the Earth’s ionosphere. These sudden ionospheric disruptions, or SIDs, are due to enhanced X-ray and extreme ultraviolet radiation from a solar flare that drastically increases the electron density in localized regions. SIDs are solar flare signatures in the Earth’s ionosphere and can be observed with very low frequency (VLF ~ 3-30 kHz) monitors and dual-frequency GNSS (L1 = 1575.42 MHz, L2 = 1227.60 MHz) receivers that probe lower (D-region) to upper (F-region) ionospheric layers, respectively.

Blevins, Sandra↗
NASA NTRS2019

The NANOGrav 11 yr Data Set: Solar Wind Sounding through Pulsar Timing

The North American Nanohertz Observatory for Gravitational Waves (NANOGrav) has observed dozens ofmillisecond pulsars for over a decade. We have accrued a large collection of dispersion measure (DM)measurements sensitive to the total electron content between Earth and the pulsars at each observation. All lines ofsight cross through the solar wind (SW), which produces correlated DM fluctuations in all pulsars. We develop andapply techniques for extracting the imprint of the SW from the full collection of DM measurements in the recentlyreleased NANOGrav 11 yr data set. We filter out long-timescale DM fluctuations attributable to structure in theinterstellar medium and carry out a simultaneous analysis of all pulsars in our sample that can differentiate thecorrelated signature of the wind from signals unique to individual lines of sight. When treating the SW asspherically symmetric and constant in time, we find the electron number density at 1au to be 7.9 ± 0.2 cm(exp -3). Wefind our data to be insensitive to long-term variation in the density of the wind. We argue that our techniques pairedwith a high-cadence, low-radio-frequency observing campaign of near-ecliptic pulsars would be capable ofmapping out large-scale latitudinal structure in the wind.

Madison, D.R.↗
NASA NTRS2000

Ionospheric specification algorithms for precise GPS-based aircraft navigation

We present a technique for converting real-time total electron content (TEC) measurements into gridded vertical delay corrections at the GPS L***sub***1 frequency, which will be broadcast to users every 5 min via geosynchronous satellite. Users will convert these delays to slant corrections for their own particular lines of sight to GPS satellites. To preserve user safety, estimates of the error in the user delay corrections will also be broadcast.

Global↗
NASA NTRS2019

Modeling the near-field ionospheric disturbances during earthquakes

We present the latest development of the Wave Perturbation-Global Ionosphere-Thermosphere Model (WP-GITM), a threedimensional physics-based numerical model for seismic/tsunami-ionosphere coupling via atmospheric acoustic-gravity waves. WP-GITM was previously applied to simulate the ionospheric perturbations resulted from the epicentral crustal movement by assuming spherical acoustic-gravity waves originated from a point source, which was specified by the seismic measurement at a single location nearby the epicenter. In this work, we extend WP-GITM to include the effects of Rayleigh surface waves and adapt WP-GITM to utilize seismic measurements from more than one location in the attempt to capture the radiation pattern of the seismic source. We apply the new WP-GITM to model the near-field co-seismic ionospheric perturbations during the 16 September 2015 Illapel earthquake. The comparison between the simulated ionospheric total electron content perturbations and the GPS observations shows promising results.

Ravanelli, Michela↗
NASA NTRS2022

Conjugate Effect of the 2011 Tohoku Reflected Tsunami-Driven Gravity Waves in the Ionosphere

This study presents the conjugate ionospheric disturbances triggered by the 2011 Tohoku-Oki reflected tsunami oceanic waves using the ground-based Global Navigation Satellite System (GNSS) total electron content (TEC) observations. We found that the equatorward and westward propagating nighttime medium-scale traveling ionospheric disturbances (MSTIDs) occurred over Japan and Australia simultaneously following the tsunami oceanic waves reflected by the Emperor Seamount Chain in the northern hemisphere. The atmospheric gravity waves driven by reflected tsunami oceanic waves are hypothesized to be the source to trigger the conjugate MSTIDs by transporting the polarization electric fields along the field line to the conjugate hemisphere. Moreover, only the southwestward propagating MSTIDs have this conjugate effect, which could be due to the wavefront orientation. The Perkins instability could also be involved in the interhemispheric coupling process. This study provides the first observational evidence that the reflected tsunami can induce conjugate ionospheric disturbances through electrodynamic forcing.

tsunami, gravity waves, GPS TEC↗
NASA NTRS2022

La Soufriere Volcanic Eruptions Launched Gravity Waves Into Space

Atmospheric gravity waves can be excited by explosive volcanic eruptions and may reach Earth's upper atmosphere. In this study, we report on mesoscale concentric gravity waves observed in the mesopause airglow layer following the La Soufriere volcano eruption in April 2021. A large ash plume observed by the spaceborne Multi-angle Imaging SpectroRadiometer instrument on April 10 reached ∼20 km. Temporal evolution of the volcanic ash plume was provided by the GOES-16 Advanced Baseline Imager. Nightglow gravity waves were observed by the Visible Infrared Imaging Radiometer Suite Day Night Band. These waves had horizontal wavelengths of ∼25–40 km, and took about a half-to-1 hr to travel from the tropopause to the mesopause. Some concentric ionospheric disturbance signatures are also seen in Global Navigation Satellite System-total electron content maps. We found the launch of gravity waves to be highly correlated with the elevated ash plume from explosive eruptions.

gravity waves↗
NASA NTRS2022

Extreme Poleward Expanding Super Plasma Bubbles Over Asia-Pacific Region Triggered By Tonga Volcano Eruption During the Recovery-Phase of Geomagnetic Storm

The Tonga volcano eruption of 15 January 2022 unleashed a variety of atmospheric perturbations, coinciding with the recovery-phase of a geomagnetic storm. The ensuing thermospheric variations created rare display of extreme poleward-expanding conjugate plasma bubbles seen in the rate of total electron content index over 100–150°E, reaching ∼40°N geographic latitude. This is associated with fluctuations in FORMOSAT-7/COSMIC-2 (F7/C2) ion-density measurements and spread-F in ionograms. Preceding to this, an unusually strong pre-reversal enhancement (PRE) occurred in the global ionospheric specification (GIS) electron density profiles derived from F7/C2 observations. The GIS also revealed a decrease of equatorial ionization anomaly (EIA) crest density due to the storm impact. Reduced E-region conductivity by volcano-induced waves and enhanced F-region wind, further accelerated by reduced ion-drag over the EIA, apparently intensified the PRE. Accompanied with the strong PRE, volcano-induced seed perturbations triggered the super plasma bubble activity.

P. K. Rajesh↗
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↗