Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Signature”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,657 records · Page 92
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

Rapid Conjugate Appearance of the Giant Ionospheric Lamb Wave Signatures in the Northern Hemisphere After Hunga-Tonga Volcano Eruptions

The explosive eruption of the Hunga-Tonga volcano in the southwest Pacific at 0415UT on 15 January 2022 triggered gigantic atmospheric disturbances with surface air pressure waves propagating around the globe in Lamb mode. In space, concentric traveling ionosphere disturbances (CTIDs) are also observed as a manifestation of air pressure waves in New Zealand ∼0500UT and Australia ∼0630UT. As soon as the air pressure waves reached central Australia ∼0800UT, conjugate CTIDs appeared almost simultaneously in the northern hemispheres through interhemispheric coupling, much earlier than the arrival of the surface air pressure waves to Japan after 1100UT. Combining observations over Australia and Japan between 0800 and 1000UT, both direct and conjugate CTIDs show similar horizontal phase velocities of 320–390 m/s, matching with the dispersion relation of Lamb mode. The arrival of atmospheric Lamb wave to Japan later created in situ CTIDs showing the same Lamb mode characteristics as the earlier conjugate CTIDs.

Concentric traveling ionospheric disturbances↗
NASA NTRS2022

Systematic Detection of Anomalous Ionospheric Perturbations Above LEOs From GNSS POD Data Including Possible Tsunami Signatures

In this article, we show the capability of a global navigation satellite system (GNSS) precise orbit determination (POD) low Earth orbit (LEO) data to detect anomalous ionospheric disturbances in the spectral range of the signals associated with earthquakes and tsunamis, applied to two of these events in Papua New Guinea (PNG) and the Solomon Islands during 2016. This is achieved thanks to the new PIES approach (POD-GNSS LEO Detrended Ionospheric Electron Content Significant Deviations). The significance of such ionospheric signals above the swarm LEOs is confirmed with different types of independent data: in situ electron density measurements provided by the Langmuir Probe (LP) onboard swarm LEOs, DORIS, and ground-based GNSS colocated measurements, as it is described in this article. In this way, we conclude the possible detection of the tsunami-related ionospheric gravity wave in PNG 2016 event, consistent with the most-recent theory, which shows that a tsunami (which is localized in space and time) excites a spectrum of gravity waves, some of which have faster horizontal phase speeds than the tsunami. We believe that this work shows as well the feasibility of a future potential monitoring system of ionospheric disturbances, to be made possible by hundreds of CubeSats with POD GNSS receivers among other appropriate sensors, and supported for real-time or near real-time confirmation and characterization by thousands of worldwide existing ground GNSS receivers.

Global Navigation Satellite System↗
NASA NTRSDate not supplied

Understanding the Vertical Slope of Mesoscale Snow Band Reflectivity Signatures

Mesoscale snow bands are frequently responsible for dumping large amounts of snow over a relatively small region and pose a considerable forecasting challenge. The ongoing NASA Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign observed several instances of mesoscale snow bands during January and February of 2020 and 2022. These snow bands were sampled by a combination of airborne (NASA ER-2 and P-3) and ground-based remote sensing and in-situ instruments. Along-band cross sections of these snow bands reveal that many of them are vertically sloped. Our preliminary analysis into one of these snow bands suggests that the vertical slope is not maintained by isentropic lift and does not appear to be tied to horizontal deformation. A combined analysis of the reflectivity and wind retrievals from the ER-2 radars raises the possibility that these features could be produced by vertical wind shear layers deforming fall streaks into bands that extend hundreds of kilometers. The present study will focus on extending our preliminary analysis to additional cases and understanding the mechanisms that support these features using a combination of radar data, in-situ aircraft measurements, and numerical modeling.

Charles Helms↗
NASA NTRSDate not supplied

ENSO Tropical Cloud and TOA radiative signatures from the CERES observation

The Clouds and the Earth's Radiant Energy System (CERES) project now has over 15 years accurately observed top-of-the-atmosphere (TOA) flux record for climate monitoring and diagnostic studies. The CERES flux-by-cloud-type dataset, which contains cloud properties and radiative fluxes for 42 cloud types sorted by cloud top pressure and cloud optical depth, is used to investigate the clouds and their associated TOA (top-of-the-atmosphere) fluxes changes over the tropical area during ENSO events during the observed period. Unlike past studies, this study shows the impact of ENSO on cloud properties like optical depth, cloud top effective pressure and temperature and TOA LW and SW fluxes for each sub cloud type. The study reveals the detailed contributions from different cloud types for radiative characteristics during different phases of ENSO. This is especially important for very small net TOA radiative balance due to the cancellation of the fluxes from different cloud types. To further demonstrate the usefulness of this dataset, NCAR Community Atmosphere Model (CAM) is used to simulate the cloud and radiative changes during the period. The model cloud properties are converted to MODIS like cloud properties using modified MODIS simulator. The dataset serves as a more stringent validation of the model for cloud properties and radiative fluxes.

Moguo Sun↗
NASA NTRSDate not supplied

Development of Machine Learning-Derived Microbiological and Immune Signatures: Applications in Adaptive Risk Assessment of Infectious Disease During Spaceflight

Infectious diseases represent an urgent risk for spaceflight with consequences ranging from loss in crew performance to crew incapacitation or loss of life should an outbreak occur. The resident environmental microbiome on the International Space Station has been monitored through routine surveillance over almost twenty years, beginning with culture-based microbial detection which has advanced to molecular methods in recent years. This has created a wealth of data that we have begun mining to define the microbial ecology of the ISS. Summarized here is our analysis of data from the historical microbial population defined by culture-based monitoring from the past two decades, organized by their likelihood to cause disease into clinical categories. As expected, many residents of the normal microflora in environments where people work and live were detected. However, some known pathogens were also detected. As the spaceflight environment can predispose humans to infection, crew health records were used to source additional data for the set to uncover clinical relevance. Data mining was performed on crew health records to capture adverse health events that may be related to infectious disease. Machine learning, specifically Random Forest analysis, was used to analyze the microbial and crew health datasets. The symptom categories were not explained by the ranked bacteria, due to lack of sufficient data for some categories and due to poor ranking of the pathogens for others. Poor ranking of the bacteria could be due to the clinical symptoms being linked to other disease-causing factors, such as allergy or viral infection. These findings suggest a lack of relationship between bacteria detected on surfaces in the ISS and historical health events experienced by astronauts.

Kristyn Hoffman↗
NASA NTRSDate not supplied

Discretization Error Estimation and Control for Farfield Acoustic Signatures

We investigate the utility of adjoint-based error estimates for sonic boom farfield simulations governed by solutions of the augmented Burgers’ equation. Solution of this nonlinear system uses operator splitting with a second-order finite volume discretization in space and second-order Runge-Kutta time marching, while the absorption and molecular relaxation are solved using second-order central differencing. The discretization error in selected ground sonic boom cost functionals is estimated using the method of adjoint-weighted residuals. Key elements of the implementation process are emphasized with details provided on the practical aspects as appliedto the sonic boom farfield propagation. We establish the accuracy of the adjoint solutions usingcomplex step and finite difference approaches, and examine the accuracy of the error estimates using analytical N-wave solutions. We then apply it to a pressure waveform corresponding to the X-59 research aircraft. The investigations demonstrate that the method of adjoint-weighted residuals accurately predicts the level of discretization error present in sonic boom farfield simulations while offering insight into which features of the near field signal are the primary drivers of ground noise metrics. The numerical results indicate that at sampling frequencies as low as50kHz, discretization error in the propagation is under 0.01 dB[A] for realistically complex examples.

CST↗
NASA NTRS2026

Isotopic Signature of Organic Molecules from Beyond the Solar System: An Enriched Methane D/H Ratio in the Interstellar Object 3I/ATLAS

Interstellar objects are interlopers from other planetary systems, and their volatile compositions provide a glimpse into planet formation around their host star. We present near-infrared spectra of the coma of interstellar object 3I/ATLAS measured with the James Webb Space Telescope. Our results demonstrate an unexpectedly high D/H = (3.31 ± 0.34)% for methane and represent an exceedingly rare detection of deuterated organic molecules in an interstellar object. This D/H ratio is a factor of 14 ± 2 higher than that measured in comet 67P/Churyumov-Gerasimenko by the Rosetta spacecraft, the only other comet for which CH3D has been detected, yet the ratio of deuteration in methane compared with water is consistent for both comets within 1.2σ. The D/H ratio in methane is observationally unconstrained in extrasolar sources to date, but the enriched ratio in 3I/ATLAS is most similar to those measured in other organic molecules toward primitive environments. The high D/H ratios of water and methane in 3I/ATLAS are a natural consequence of formation in a high D/H elemental ratio environment as a result of locally cold conditions in the protoplanetary disk and prior interstellar cloud. Thus, 3I/ATLAS formed in an environment very different from that in which our Sun and planets originated.

Interstellar Object 3I/ATLAS↗
NASA NTRS2026

Spatially Refined Satellite Gravimetry Captures Human Signatures in Global Terrestrial Water Storage Trends

Human activities have directly altered the water cycle through water management, aquifer pumping, agricultural irrigation, and land use change. Although satellite gravimetry has transformed global hydrological research, its coarse resolution limits attribution of freshwater change to human activities at many management-relevant scales. Here we assessed global terrestrial water storage (TWS) trends from April 2002 to November 2025 using “stacked” regression of Level-1B intersatellite ranging data, which leverages temporal information and variability to dramatically improve effective spatial resolution relative to standard approaches. We combined this refined product with rigorous uncertainty analysis, autocorrelation-robust geostatistical methods, and literature assessment to evaluate TWS trend associations with land and water use, climate variability, and glacial mass loss. We identified TWS trend hotspots exhibiting significant spatial associations with anthropogenic 40 drivers, including groundwater and surface-water irrigation, rainfed agriculture, deforestation, and reservoir impoundment. Across these regions, cumulative TWS losses (3,122 Gt) substantially exceeded gains (2,432 Gt). Compared with traditional regression of monthly mascons, our approach yielded regional trend magnitudes that are on average 33% larger, revealing that global freshwater depletion, particularly from groundwater pumping, is considerably more acute than previously estimated. Multivariate regression models show that humans account for a significant share of the spatial variability in TWS trends on every non-polar continent except Australia. We detected localized TWS gains linked to rainfed agriculture, surface water irrigation, and reservoir filling that were unresolved in earlier gravimetric studies. The methodology provides a foundation for future gravity missions to independently track decadal freshwater change with unprecedented spatial fidelity.

groundwater↗