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All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Lunar and Planetary Science XXXV: Lunar Geophysics: Rockin' and a-Reelin'

This document contained the following topics: The Influence of Tidal, Despinning, and Magma Ocean Cooling Stresses on the Magnitude and Orientation of the Moon#s Early Global Stress Field; New Approach to Development of Moon Rotation Theory; Lunar Core and Tides; Lunar Interior Studies Using Lunar Prospector Line-of-Sight Acceleration Data; A First Crustal Thickness Map of the Moon with Apollo Seismic Data; New Events Discovered in the Apollo Lunar Seismic Data; More Far-Side Deep Moonquake Nests Discovered; and Manifestation of Gas-Dust Streams from Double Stars on Lunar Seismicity.

Source record↗
DOE OSTI2024

Lie–Poisson Neural Networks (LPNets): Data-based computing of Hamiltonian systems with symmetries

An accurate data-based prediction of the long-term evolution of Hamiltonian systems requires a network that preserves the appropriate structure under each time step. Every Hamiltonian system contains two essential ingredients: the Poisson bracket and the Hamiltonian. Hamiltonian systems with symmetries, whose paradigm examples are the Lie–Poisson systems, have been shown to describe a broad category of physical phenomena, from satellite motion to underwater vehicles, fluids, geophysical applications, complex fluids, and plasma physics. The Poisson bracket in these systems comes from the symmetries, while the Hamiltonian comes from the underlying physics. We view the symmetry of the system as primary, hence the Lie–Poisson bracket is known exactly, whereas the Hamiltonian is regarded as coming from physics and is considered not known, or known approximately. Using this approach, we develop a network based on transformations that exactly preserve the Poisson bracket and the special functions of the Lie–Poisson systems (Casimirs) to machine precision. We present two flavors of such systems: one, where the parameters of transformations are computed from data using a dense neural network (LPNets), and another, where the composition of transformations is used as building blocks (G-LPNets). We also show how to adapt these methods to a larger class of Poisson brackets. We apply the resulting methods to several examples, such as rigid body (satellite) motion, underwater vehicles, a particle in a magnetic field, and others. The methods developed in this paper are important for the construction of accurate data-based methods for simulating the long-term dynamics of physical systems.

Data-based modeling↗
NASA NTRS1981

Seasat data utilization project

During the three months of orbital operations, the satellite returned data from the world's oceans. Dozens of tropical storms, hurricanes and typhoons were observed, and two planned major intensive surface truth experiments were conducted. The utility of the Seasat-A microwave sensors as oceanographic tools was determined. Sensor and geophysical evaluations are discussed, including surface observations, and evaluation summaries of an altimeter, a scatterometer, a scanning multichannel microwave radiometer, a synthetic aperture radar, and a visible and infrared radiometer.

Born, G. H.↗
NASA NTRS1982

Analyzing the Broken Ridge area of the Indian Ocean using magnetic and gravity anomaly maps and geoid undulation and bathymetry data

A higher resolution anomaly map of the Broken Ridge area (2 degree dipole spacing) was produced and reduced to the pole using quiet time data for this area. The map was compared with equally scaled maps of gravity anomaly, geoid undulation, and bathymetry. The ESMAP results were compared with a NASA MAGSAT map derived by averaging data in two-degree bins. A survey simulation was developed to model the accuracy of MAGSAT anomaly maps as a function of satellite altitude, instrument noise level, external noise model, and crustal anomaly field model. A preliminary analysis of the geophysical structure of Broken Ridge is presented and unresolved questions are listed.

Lazarewicz, A. R.↗
NASA NTRS1989

Laboratory and theoretical models of planetary-scale instabilities and waves

The continuous low-g environment of the orbiting space shuttle provided a setting for conducting geophysical fluid model experiments with a completely consistent representation of sphericity and the resultant radial gravity found on astrogeophysical objects. This is possible because in zero gravity an experiment can be constructed that has its own radial buoyancy forces. The dielectric forces in a liquid, which are linearly dependent on fluid temperature, give rise to an effectively radial buoyancy force when a radial electrostatic field is applied. The Geophysical Fluid Flow Cell (GFFC) experiment is an implementation of this idea in which fluid is contained between two rotating hemispheres that are differentially heated and stressed with a large ac voltage. The GFFC flew on Spacelab 3 in May 1985. Data in the form of global Schlieren images of convective patterns were obtained for a large variety of configurations. These included situations of rapid rotation (large Taylor numbers), low rotation, large and small thermal forcing, and situations with applied meridional temperature gradients. The analysis and interpretation of the GFFC-85 data are being conducted. Improvements were developed to the GFFC instrument that will allow for real-time (TV) display of convection data and for near-real-time interactive experiments. These experiments, on the transition to global turbulence, the breakdown of rapidly rotating convective planforms and other phenomena, are scheduled to be carried out on the International Microgravity Laboratory (IML-1) aboard the shuttle in June 1990.

Hart, John E.↗
NASA NTRS1989

The GEM-T2 gravitational model

The GEM-T2 is the latest in a series of Goddard Earth Models of the terrestrial field. It was designed to bring modeling capabilities one step closer towards ultimately determining the TOPEX/Poseidon satellite's radial position to an accuracy of 10-cm RMS (root mean square). It also improves models of the long wavelength geoid to support many oceanographic and geophysical applications. The GEM-T2 extends the spherical harmonic field to include more than 600 coefficients above degree 36 (which was the limit for its predecessor, GEM-T1). Like GEM-T1, it was produced entirely from satellite tracking data, but it now uses nearly twice as many satellites (31 vs. 17), contains four times the number of observations (2.4 million), has twice the number of data arcs (1132), and utilizes precise laser tracking from 11 satellites. The estimation technique for the solution has been augmented to include an optimum data weighting procedure with automatic error calibration for the gravitational parameters. Results for the GEM-T2 error calibration indicate significant improvement over previous satellite-only models. The error of commission in determining the geoid has been reduced from 155 cm in GEM-T1 to 105 cm for GEM-T2 for the 36 x 36 portion of the field, and 141 cm for the entire model. The orbital accuracies achieved using GEM-T2 are likewise improved. Also, the projected radial error on the TOPEX satellite orbit indicates 9.4 cm RMS for GEM-T2, compared to 24.1 cm for GEM-T1.

Marsh, J. G.↗
NASA NTRS1990

The GEM-T2 gravitational model

The GEM-T2 is the latest in a series of Goddard Earth Models of the terrestrial field. It was designed to bring modeling capabilities one step closer towards ultimately determining the TOPEX/Poseidon satellite's radial position to an accuracy of 10-cm RMS (root mean square). It also improves models of the long wavelength geoid to support many oceanographic and geophysical applications. The GEM-T2 extends the spherical harmonic field to include more than 600 coefficients above degree 36 (which was the limit for its predecessor, GEM-T1). Like GEM-T1, it was produced entirely from satellite tracking data, but it now uses nearly twice as many satellites (31 vs. 17), contains four times the number of observations (2.4 million), has twice the number of data arcs (1132), and utilizes precise laser tracking from 11 satellites. The estimation technique for the solution has been augmented to include an optimum data weighting procedure with automatic error calibration for the gravitational parameters. Results for the GEM-T2 error calibration indicate significant improvement over previous satellite-only models. The error of commission in determining the geoid has been reduced from 155 cm in GEM-T1 to 105 cm for GEM-T2 for the 36 x 36 portion of the field, and 141 cm for the entire model. The orbital accuracies achieved using GEM-T2 are likewise improved. Also, the projected radial error on the TOPEX satellite orbit indicates 9.4 cm RMS for GEM-T2, compared to 24.1 cm for GEM-T1.

Marsh, J. G.↗
NASA NTRS1997

Sounding of the Cleft Ion Fountain Energization Region

The objectives of the ground-based observations in support of the SCIFER are: Acquire and display ionospheric conditions prior to launch to aid in the establishment of launch criteria in real time. Observers at both stations participated in real-time visual interpretation. Solar wind data from IMP-8 and WIND were acquired and interpreted in real time. Telephonic and data links were established at the observatory for the launch window period. Ground-based observatory countdown and launch criteria were developed. 2) Relate optical and magnetic ionospheric signatures observed from the ground to magnetospheric boundaries in the energetic particle flux measured at the payload. The energetic electron trapping boundary was found to correspond to the equatorward edge of the discrete auroral arcs forming the dayside aurora. The energetic electron trapping boundary was found to correspond to the poleward edge of pulsating aurora. The pulsating aurora was found to correspond to one second bursts of energy-dispersed electrons originating in the equatorial plane. Pulsations at larger intervals corresponded to travel times to the conjugate region and return. The pulsating aurora was also directly linked to the geomagnetic pulsations and traveling magnetic vortices, all occurring equatorward of the trapping boundary. 630 nm emission corresponding to less than 10 eV electron precipitation was observed equatorward of the trapping boundary (L=15) and ascribed to photoelectrons from the sunlit conjugate region. 3) Aid in the interpretation of time/space incongruities in the rocket data. The motion of the payload conjugate across the aurora showed that the payload passed over three distinct arc systems on the poleward side of the trapping boundary. These results were reported in a series of articles to be printed in Geophysical Research Letters on June 15, l996.

Kintner, P.↗
NASA NTRS2008

Spatial and Temporal Inter-Relationships between Anomalies and Trends of Temperature, Moisture, Cloud Cover, and OLR as Observed by AIRS/AMSU on Aqua

AIRS/AMSU is the advanced IR/MW atmospheric sounding system launched on EOS Aqua in May 2002. Products derived from AIRS/AMSU by the AIRS Science Team include surface skin temperature and atmospheric temperature profiles; atmospheric humidity profiles, fractional cloud cover and cloud top pressure, and OLR. Products covering the period September 2002 through the present have been derived from AIRS/AMSU using the AIRS Science Team Version 5 retrieval algorithm. In this paper, we will show results covering the time period September 2006 - November 2008. This time period is marked by a substantial warming trend of Northern Hemisphere Extratropical land surface skin temperatures, as well as pronounced El Nino - La Nina episodes. These both influence the spatial and temporal anomaly patterns of atmospheric temperature and moisture profiles, as well as of cloud cover and Clear sky and All Sky OLR. The relationships between temporal and spatial anomalies of these parameters over this time period, as determined from AIRS/AMSU observations, will be shown, with particular emphasis on which contribute significantly to OLR anomalies in each of the tropics and extra-tropics. Results will also be shown to validate the anomalies and trends of temperature profiles and OLR as determined from analysis of AIRS/AMSU data. Global and regional trends during the 6 1/3 year period are not necessarily indicative of what has happened in the past, or what may happen in the future. Nevertheless, the inter-relationships of spatial and temporal anomalies of atmospheric geophysical parameters with those of surface skin temperature are indicative of climate processes, and can be used to test the performance of climate models when driven by changes in surface temperatures.

Susskind, Joel↗
NASA NTRS2010

Recent Spatial and Temporal Anomalies and Trends of OLR as Observed by CERES and Computed Based on AIRS Retrievals

We show that a recent CERES-observed negative trend in OLR of approx.-0.1 W/sq m/yr averaged over the globe, for the time period of September 2002 through February 2010 used in this study, is found in the AIRS OLR data as well. Most importantly, even minute details (down to 1 x 1 Degree GCM-scale resolution) of spatial and temporal anomalies and trends of OLR as observed by CERES and computed based on AIRS-retrieved surface and atmospheric geophysical parameters over this time period are essentially the same. We see this correspondence even in the very large spatial variations of these trends with local values ranging from -2.6 W/sq m/yr to +3.0 W/sq m/yr in the tropics. This essentially perfect agreement of OLR anomalies and even local trends derived from observations by two different instruments, in totally independent and different manners, implies that both sets of results must be highly accurate; and indirectly validates the anomalies and trends of other AIRS derived products as well. These products show that global and regional anomalies and trends of OLR, water vapor and cloud cover over the last 7+ years are strongly influenced by El-Nino-La Nina cycles . We use the anomalies and trends of AIRS derived products to explain why the global OLR has a large negative trend over this time period; Global and tropical OLR began to decrease significantly at the onset of a strong La Nina in mid-2007. AIRS products show that cloudiness and mid-tropospheric water vapor began to increase in the tropics at roughly the same time, especially in the region 5degN - 20degS latitude extending eastward from 150degW to 30degE longitude, with a corresponding very large drop in OLR in this region. Late 2009 is characterized by a strong El-Nino, with a corresponding change in sign of observed tropical water vapor, cloud cover, and OLR anomalies. If one excludes the area 5degN - 20degS, 150degW - 30degE from the statistics, area mean OLR trends over the rest of the globe are substantially reduced over the time period under study.

Molnar, Gyula↗
NASA NTRS2009

A Decade of Satellite Ocean Color Observations

After the successful Coastal Zone Color Scanner (CZCS, 1978-1986), demonstration that quantitative estimations of geophysical variables such as chlorophyll a and diffuse attenuation coefficient could be derived from top of the atmosphere radiances, a number of international missions with ocean color capabilities were launched beginning in the late 1990s. Most notable were those with global data acquisition capabilities, i.e., the Ocean Color and Temperature Sensor (OCTS 1996-1997), the Sea-viewing Wide Field-of-view Sensor (SeaWiFS, United States, 1997-present), two Moderate Resolution Imaging Spectroradiometers, (MODIS, United States, Terra/2000-present and Aqua/2002-present), the Global Imager (GLI, Japan, 2002-2003), and the Medium Resolution Imaging Spectrometer (MERIS, European Space Agency, 2002-present). These missions have provided data of exceptional quality and continuity, allowing for scientific inquiries into a wide variety of marine research topics not possible with the CZCS. This review focuses on the scientific advances made over the past decade using these data sets.

McClain, Charles R.↗
NASA NTRS2019

Analyzing Machine Learning Predictions of Passive Microwave Brightness Temperature Spectral Difference Over Snow-Covered Terrain in High Mountain Asia

Snow is an important component of the terrestrial freshwater budget in high mountainAsia (HMA) and contributes to the runoff in Himalayan rivers through snowmelt. Despitethe importance of snow in HMA, considerable spatiotemporal uncertainty exists across the different estimates of snow water equivalent for this region. In order to better estimate snow water equivalent, radiative transfer models are often used in conjunction with microwave brightness temperature measurements. In this study, the efficacy of support vector machines (SVMs), a machine learning technique, to predict passive microwave brightness temperature spectral difference (1Tb) as a function of geophysical variables (snow water equivalent, snow depth, snow temperature, and snow density) is explored through a sensitivity analysis. The use of machine learning (as opposed to radiative transfer models) is a relatively new and novel approach for improving snow water equivalent estimates. The Noah-MP land surface model within the NASALand Information System framework is used to simulate the hydrologic cycle over HMA and model geophysical variables that are then used for SVM training. The SVMsserve as a nonlinear map between the geophysical space (modeled in Noah-MP) andthe observation space (1Tb as measured by the radiometer). Advanced MicrowaveScanning Radiometer-Earth Observing System measured passive microwave brightness temperatures over snow-covered locations in the HMA region are used as training data during the SVM training phase. Sensitivity of well-trained SVMs to each Noah-MP modeled state variable is assessed by computing normalized sensitivity coefficients. Sensitivity analysis results generally conform with the known first-order physics. Input states that increase volume scattering of microwave radiation, such as snow density and snow water equivalent, exhibit a plurality of positive normalized sensitivity coefficients. In general, snow temperature was the most sensitive input to the SVM predictions. The sensitivity of each state is location and time dependent. The signs of normalized sensitivity coefficients that indicate physical irrationality are ascribed to significant cross-correlation between Noah-MP simulated states and decreased SVM prediction capability at specific locations due to insufficient training data. SVM prediction pitfalls do exist that serve to highlight the limitations of this particular machine learning algorithm.

high mountain Asia↗
NASA NTRS2012

GRAIL Refinements to Lunar Seismic Structure

The present ]day internal structure of the Moon provides insight not only into its own formation and evolution, but also that of all rocky planetary bodies. The most direct way to probe a planet fs interior structure is through seismology. As part of the Apollo lunar missions, four seismometers were deployed on the nearside surface of the Moon between the years 1969 and 1972. These instruments operated continuously until 1977, forming the only substantial extraterrestrial seismic data set in existence. These data have been used to constrain various aspects of the seismic velocity and density structure of the Moon. Typical 1-D models recognize a 30-60 km thick crust overlying a nearly constant ]velocity mantle, and extend to a depth of approximately 1000 km, below which the lack of penetrating moonquake ray ]paths precludes the seismic determination of deeper structure. Previously, the lack of observed moonquakes from the far side of the Moon has been used to infer the presence of a highly attenuating (possibly molten) core. Indirect geophysical measurements such as moment of inertia, magnetic induction, lunar laser ranging, and elemental abundances of mare basalts also place varying constraints on core size and state. In combination with seismic studies, these indirect measurements have been used to arrive at a commonly accepted model of the Moon's deepest interior that includes a solid inner and fluid outer core, overlain by a partial melt boundary layer. We recently applied modern array seismology techniques to the Apollo data and revealed detailed core structure, including the first direct confirmation of the presence of a solid inner core. Our study focused on the identification of core ]reflected phases in deep moonquake seismograms. The resulting model of the Moon fs innermost structure was found to be consistent with the commonly accepted model. However, the modeled layer radii may vary by tens of kilometers, as is expected when accounting for uncertainties such as moonquake location, timing errors, and potential seismic heterogeneities. In addition, the modeled velocities may vary with a 1-to-1 trade ]off with the modeled reflector depth. The GRAIL (Gravity Recovery and Interior Laboratory) mission, launched in Sept. 2011, placed two nearly identical spacecraft in lunar orbit. The two satellites make extremely high-resolution measurements of the lunar gravity field, which can be used to constrain the interior structure of the Moon using a "crust to core" approach. GRAIL fs constraints on crustal thickness, mantle structure, core radius and stratification, and core state (solid vs. molten) will complement seismic investigations in several ways. Here we present a progress report on our efforts to advance our knowledge of the Moon fs internal structure using joint gravity and seismic analyses. We will focus on methodology, including 1) refinements to the seismic core constraint accomplished through array processing of Apollo seismic data, made by applying a set of travel time corrections based on GRAIL structure estimates local to each Apollo seismic station; 2) modeling deep lunar structure through synthetic seismograms, to test whether the seismic core model can reproduce the core reflections observed in the Apollo seismograms; and 3) a joint seismic and gravity inversion in which we attempt to fit a family of seismic structure models with the gravity constraints from GRAIL, resulting in maps of seismic velocities and densities that vary from a nominal model both laterally and with depth.

Weber, Renee↗
NASA NTRS2002

Relationships Between the Bulk-Skin Sea Surface Temperature Difference, Wind, and Net Air-Sea Heat Flux

The primary purpose of this project was to evaluate and improve models for the bulk-skin temperature difference to the point where they could accurately and reliably apply under a wide variety of environmental conditions. To accomplish this goal, work was conducted in three primary areas. These included production of an archive of available data sets containing measurements of the skin and bulk temperatures and associated environmental conditions, evaluation of existing skin layer models using the compiled data archive, and additional theoretical work on the development of an improved model using the data collected under diverse environmental conditions. In this work we set the basis for a new physical model of renewal type, and propose a parameterization for the temperature difference across the cool skin of the ocean in which the effects of thermal buoyancy, wind stress, and microscale breaking are all integrated by means of the appropriate renewal time scales. Ideally, we seek to obtain a model that will accurately apply under a wide variety of environmental conditions. A summary of the work in each of these areas is included in this report. A large amount of work was accomplished under the support of this grant. The grant supported the graduate studies of Sandra Castro and the preparation of her thesis which will be completed later this year. This work led to poster presentations at the 1999 American Geophysical Union Fall Meeting and 2000 IGARSS meeting. Additional work will be presented in a talk at this year's American Meteorological Society Air-Sea Interaction Meeting this May. The grant also supported Sandra Castro during a two week experiment aboard the R/P Flip (led by Dr. Andrew Jessup of the Applied Physics Laboratory) to help obtain additional shared data sets and to provide Sandra with a fundamental understanding of the physical processes needed in the models. In a related area, the funding also partially supported Dr. William Emery and Daniel Baldwin in the preparation of their publication "Accuracy of in situ sea surface temperatures used to calibrate infrared satellite measurements". The remainder of this report is drawn from these publications and presentations.

Emery, William J.↗
DOE OSTI2025

Development of an ERT‐Based Framework for Bentonite Buffers Monitoring From Laboratory Tests: 1. Characterizing Thermal–Hydrological–Mechanical Processes

Abstract Bentonite clay is widely used in engineered barrier systems for the permanent disposal of high‐level radioactive waste due to its low permeability, high swelling capacity, and thermal stability. However, the complex thermal‐hydrological‐mechanical (THM) processes induced by heating from decaying radioactive waste and hydration from surrounding rock can lead to heterogeneous changes that are difficult to measure and predict. This study develops an Electrical Resistivity Tomography (ERT)‐based framework for monitoring THM processes, progressing from sample‐scale to bench‐scale tests, to inform field‐scale applications. Sample‐scale tests analyzed small bentonite samples under controlled variations in water content, temperature, and porosity to establish fundamental resistivity relationships. Bench‐scale tests involved larger bentonite columns subjected to heating (up to 200°C) and hydration under controlled pressure, simulating repository conditions. ERT measurements, complemented by X‐ray CT imaging, temperature monitoring, and tracing sensors, revealed coupled THM processes, such as hydration‐induced compression, swelling, and thermal gradients, leading to complex resistivity patterns. The results demonstrate the potential of ERT for capturing THM‐induced resistivity changes, though challenges remain in upscaling and quantitative analysis. This study evaluates laboratory test capabilities and proposes future improvements for understanding THM‐induced resistivity responses. A conceptual framework for ERT implementation in field‐scale monitoring is presented, synthesizing findings from both scales and exploring how ERT data can inform long‐term modeling and reduce prediction uncertainties. Overall, this ERT‐based framework offers a robust method for monitoring bentonite buffers, aiding in early issue detection and supporting the safe long‐term disposal of radioactive waste in geological repositories, while highlighting the need for future development. Plain Language Summary Bentonite clay is crucial in engineered barrier systems (EBS) for containing high‐level radioactive waste due to its ability to absorb water, swell, seal and remain stable under high temperatures. When bentonite absorbs water and heats up from radioactive decay, it experiences complex changes in its physical and mechanical properties. Understanding these changes is important for ensuring the long‐term safety and effectiveness of EBS. This study used Electrical Resistivity Tomography (ERT), a non‐invasive method that measures electrical conductivity to monitor these changes during laboratory experiments. The ERT data revealed significant variations in resistivity corresponding to changes in water content, temperature, and density, providing detailed spatial and temporal insights into the behavior of bentonite. These findings enhance our ability to predict the long‐term performance of bentonite barriers, ensuring the safe containment of radioactive waste. By improving our understanding of bentonite's behavior, this research supports the development of more reliable and effective barrier systems for radioactive waste disposal, protecting the environment and public health. Key Points ERT monitoring was employed to capture resistivity changes in bentonite during controlled heating and hydration experiments, providing insights into THM processes ERT data reveal significant resistivity changes correlated with water content, temperature, and mechanical effects, enhancing the understanding of THM dynamics in bentonite This study explores the potential of the framework for application in field‐scale EBS monitoring, emphasizing the need for integrating additional geophysical methods for comprehensive subsurface imaging

Chen, Hang↗
DOE OSTI2020

EGS Collab Experiment 1: 3D Seismic Velocity Model and Updated Microseismic Catalog from Double-Difference Seismic Tomography

This package contains a 3D Seismic velocity model and an updated microseismic catalog obtained for a double-difference seismic tomography study. The 3D_seismic_velocity_model text file contains x (m), y(m), z(m), P-wave velocity (km/s), P-wave velocity quality indicator (1 for well-constrained; 0 for poorly constrained), S-wave velocity (km/s), and S-wave velocity quality indicator (1 for well-constrained; 0 for poorly constrained). The Updated_MEQ_catalog text file contains event origin time, x(m), y(m), z(m), error in x (m), error in y (m), error in z (m), and RMS misfit (millisecond). The 3D_seismic_P-wave_velocity_model animation file shows slices of the 3D P-wave velocity model. The 3D_seismic_S-wave_velocity_model animation file shows slices of the 3D S-wave velocity model. The Interactive_MEQ_location_comparison API file is an interactive visualization of the updated microseismic event locations and the original seismic catalog. The visualization allows users to view and compare the event locations by dragging, rotating, and zooming in. An updated version of 3D_seismic_velocity_model and associated animations were included, which were calculated with a more strict assumption for quality indicators.

15 GEOTHERMAL ENERGY↗