Analytical Lunar Ephemeris - Progress report
Gravitational lunar theory high order solution for geophysical relevance, discussing perturbation methods and computer analyzed ephemeris time
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Gravitational lunar theory high order solution for geophysical relevance, discussing perturbation methods and computer analyzed ephemeris time
The visual and infrared radiometer (VIRR) system on Seasat is described, and methods used in the geophysical evaluation of digital data from this system are discussed. The main function of the radiometer system is to provide images of visual reflection and thermal infrared emission from ocean, coastal and atmospheric features to facilitate interpretation of data from other Seasat sensors; in addition, it is expected to provide some derived quantitative measurements of such factors as sea-surface temperature and cloud-top height. Some results of a statistical comparison of Seasat VIRR-derived sea-surface temperatures in a cloud-free region with a National Oceanic and Atmospheric Administration (NOAA) analysis based on surface measurements made in the same region are presented. The data sets were in agreement of plus or minus 1.7 deg K root-mean-square. The means of the two sets of temperatures were 293.9 deg K (VIRR) and 293.1 deg K (NOAA), and the standard deviations were 3.21 deg and 3.2 deg K, respectively.
A pilot project to establish an operational phase stable very long baseline interferometer (VLBI) for geophysical studies is described. Methods for implementation as well as practical applications are presented.
A simple method of deriving an F-region index that can warn the prediction users at low latitudes as to the specific months when they have to be more careful in using the long term predictions is described.
Earth models consistent with geophysical data using Monte Carlo method
The test site selected for the investigation covers nearly all the regions of active and quiescent volcanism in southern Italy, i.e. the eastern part of the island of Sicily, the Aeolian Islands and the area of Naples. The three active European volcanoes (Etna, Stromboli and Vesuvius) are included. The investigation is in the frame of a program for the surveillance of active volcanoes by geophysical (including remote sensing thermal methods) and geochemical methods. By the multispectral analysis of ERTS-1 data it is intended to study the spectral behavior of the volcanic materials as well as the major geological lineaments with special reference to those associated with the volcanic region. Secondary objectives are also the determination of the hydrographic network seasonal behavior and the relationship between the vegetation cover and the different type of soils and rocks.
The relationships of a variety of general computational methods (and variances) for treating illposed problems such as geophysical inverse problems are considered. Differences in approach and interpretation based on varying assumptions as to, e.g., the nature of measurement uncertainties are discussed along with the factors to be considered in selecting an approach. The reliability of the results of such computation is addressed.
Causal discovery tools enable scientists to infer meaningful relationships from observational data, spurring advances in fields as diverse as biology, economics, and climate science. Despite these successes, the application of causal discovery to space-time systems remains immensely challenging due to the high-dimensional nature of the data. For example, in climate sciences, modern observational temperature records over the past few decades regularly measure thousands of locations around the globe. To address these challenges, we introduce Causal Space-Time Stencil Learning (CaStLe), a novel meta-algorithm for discovering causal structures in complex space-time systems. CaStLe leverages regularities in local space-time dependencies to learn governing global dynamics. This local perspective eliminates spurious confounding and drastically reduces sample complexity, making space-time causal discovery practical and effective. For causal discovery, CaStLe flexibly accepts any appropriately adapted time series causal discovery algorithm to recover local causal structures. These advances enable causal discovery of geophysical phenomena that were previously unapproachable, including non-periodic, transient phenomena such as volcanic eruption plumes. Regularities in local space-time dependencies are transformed into informative spatial replicates, which actually improve CaStLe's performance when applied to ever-larger spatial grids. We successfully apply CaStLe to discover the atmospheric dynamics governing the climate response to the 1991 Mount Pinatubo volcanic eruption. We provide validation experiments to demonstrate the effectiveness of CaStLe over existing causal-discovery frameworks on a range of geophysics-inspired benchmarks while identifying the method's limitations and domains where its assumptions may not hold.
Efforts are made to identify methods of decreasing magnetic interpretation ambiguity by combined gravity and magnetic analysis, to evaluate these techniques in a preliminary manner, to consider the geologic and geophysical implications of correlation, and to recommend a course of action to evaluate methods of correlating gravity and magnetic anomalies. The major thrust of the study was a search and review of the literature. The literature of geophysics, geology, geography, and statistics was searched for articles dealing with spatial correlation of independent variables. An annotated bibliography referencing the Germane articles and books is presented. The methods of combined gravity and magnetic analysis techniques are identified and reviewed. A more comprehensive evaluation of two types of techniques is presented. Internal correspondence of anomaly amplitudes is examined and a combined analysis is done utilizing Poisson's theorem. The geologic and geophysical implications of gravity and magnetic correlation based on both theoretical and empirical relationships are discussed.
A computational scheme and a standard program is proposed for solving systems of nonstationary spatially one-dimensional nonlinear differential equations using Newton's method. The proposed scheme is universal in its applicability and its reduces to a minimum the work of programming. The program is written in the FORTRAN language and can be used without change on electronic computers of type YeS and BESM-6. The standard program described permits the identification of nonstationary (or stationary) solutions to systems of spatially one-dimensional nonlinear (or linear) partial differential equations. The proposed method may be used to solve a series of geophysical problems which take chemical reactions, diffusion, and heat conductivity into account, to evaluate nonstationary thermal fields in two-dimensional structures when in one of the geometrical directions it can take a small number of discrete levels, and to solve problems in nonstationary gas dynamics.
The radio-frequency interferometry method can be used to probe interiors of celestial bodies and terrestrial areas with low conductivity. In order to interpret the interference patterns, a theoretical study is made of the electromagnetic fields due to a dipole antenna on the surface of a horizontally stratified n-layered medium. Three approaches are used to calculate the interference patterns: direct numerical integration, asymptotic evaluation by the saddle point method, and a residue series approach. The asymptotic approach leads to the geometrical-optics interpretation. The residue approach leads to modal analysis. The validity of the formulation is checked by comparisons with analog model tank experiments and actual field data obtained from glaciers.
The present paper argues for using the information theory approach as an inference technique in solid earth geophysics. A spherically symmetric density distribution is derived as an example of the method. A simple model of the earth plus knowledge of its mass and moment of inertia leads to a density distribution. Future directions for the information theory approach in solid earth geophysics as well as its strengths and weaknesses are discussed.
An argument for using the information theory approach as an inference technique in solid earth geophysics. A spherically symmetric density distribution is derived as an example of the method. A simple model of the earth plus knowledge of its mass and moment of inertia lead to a density distribution which was surprisingly close to the optimum distribution. Future directions for the information theory approach in solid earth geophysics as well as its strengths and weaknesses are discussed.
Hydrological models and geophysical measurements are widely used tools for understanding subsurface hydrological processes relevant to water resource management, yet they typically remain disconnected due to technical barriers. We present PyHydroGeophysX, an open-source Python platform bridging this gap by providing standardized interfaces between hydrological modeling software (MODFLOW, ParFlow) and geophysical simulation tools (PyGIMLi, SimPEG). The platform implements bidirectional workflows: translating hydrological outputs into simulated geophysical responses through petrophysical models, and extracting hydrological information from geophysical inversions. Key features include bidirectional workflow modules, configurable petrophysical models, time-lapse inversion with temporal regularization, parallel computing, and mesh utilities for property transfer between geophysical and hydrological grids. The modular architecture of PyHydroGeophysX enables researchers to incorporate additional models and methods, fostering broader adoption of integrated hydrogeophysical approaches. The software is freely available on GitHub and is intended for researchers and practitioners working at the intersection of hydrology and geophysics.
The design, development, application, and capabilities of a variable frequency microwave radiometer are described. This radiometer demonstrated the versatility, accuracy, and stability required to provide contributions to the geophysical understanding of ocean and ice processes. A closed-loop feedback method was used, whereby noise pulses were added to the received electromagnetic radiation to achieve a null balance in a Dicke switched radiometer. Stability was achieved through the use of a constant temperature enclosure around the low loss microwave front end. The Dicke reference temperature was maintained to an absolute accuracy of 0.1 K using a closed-loop proportional temperature controller. A microprocessor based digital controller operates the radiometer and records the data on computer compatible tapes. This radiometer exhibits an absolute accuracy of better than 0.5 K when the sensitivity is 0.1 K. The sensitivity varies between 0.0125 K and 1.25 K depending upon the bandwidth and integration time selected by the digital controller. Remote sensing experiments were conducted from an aircraft platform and the first radiometeric mapping of an ocean polar front; exploratory experiments to measure the thickness of lake ice; first discrimination between first year and multiyear ice below 10 GHz; and the first known measurements of frequency sensitive characteristics of sea ice.
Methods to analyze the generation, transport, and dissipation of energy to study geophysical fluid flows are discussed. Energetics analyses are pursued in several directions: (1) the longitudinal and time dependence on the energy flow to the stratosphere was examined as a function of geographical sector; (2) strong and weak energy flows were correlated by medium range forecasts; (3) the one dimensional spectral results (Fourier services around latitude circles) were extended to spherical harmonics over a global domain; (4) the validity of vertical velocities derived from mass convergence was examined for their effect on the conversion of eddy available potential energy to eddy kinetic energy.
Procedures for correcting antenna temperature measurements and retrieving the true brightness temperatures are developed for the Scanning Multichannel Microwave Radiometer (SMMR) flown on the Seasat-A and Nimbus-G satellites. These procedures are necessary to meet the measurement accuracies required for deriving sea surface temperatures and wind speeds. It is shown that sidelobe contributions and polarization cross-coupling are major effects to be accounted for, in addition to some unique features of the SMMR instrument such as integration times and antenna scan characteristics. Methods are presented for data averaging and data reformatting, these are to be used with geophysical parameter retrieval algorithms.
The central objective of this project was to address the challenge of modeling and simulating complex multiscale turbulence phenomena by leveraging physics-guided machine learning (PGML) and hybrid modeling approaches. By integrating physics-based methods with data-driven models, the research focused on achieving robust and scalable solutions for geophysical turbulence, enhancing numerical weather prediction and climate research tools. The project resulted in significant advancements in computational modeling paradigms, predictive tools for reduced-order modeling, and innovative algorithms for fluid dynamics.