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At least 1,081 records · Page 60

Porosity and the ecology of icy satellites

The case for a significant role for porosity in the structure and evolution of icy bodies in the Solar System has been difficult to establish. We present a relevant new data set and a series of structure models including a mechanical compression, not thermal creep, model for porosity that accounts satisfactorily for observed densities, moments of inertia, geologic activity, and sizes of tectonic features on icy satellites. Several types of observational data sets have been used to infer significant porosity, but until recently, alternative explanations have been preferred. Our first area of concern is the occurrence of cryovolcanism as a function of satellite radius; simple radiogenic heating models of icy satellites suggest minimum radii for melting and surface cryovolcanism to be 400 to 500 km, yet inferred melt deposits are seen on satellites half that size. One possible explanation is a deep, low conductivity regolith which lowers conductivity and raises internal temperatures, but other possibilities include tidal heating or crustal compositions of low conductivity. Our second area of concern is the occurrence and magnitude of tectonic strain; tectonic structures have been seen on icy satellites as small as Mimas and Proteus. The structures are almost exclusively extensional, with only a few possible compression Al features, and inferred global strains are on the order of 1 percent expansion. Expansions of this order in small bodies like Mimas and prevention of late compressional tectonics due to formation of ice mantles in larger bodies like Rhea are attained only in structure models including low-conductivity, and thus possibly high porosity, crusts. Thirdly, inferred moments of inertia less than 0.4 in Mimas and Tethys can be explained by high-porosity crusts, but also by differentiation of a high density core. Finally, the relatively low densities of smaller satellites like Mimas and Miranda relative to larger neighbors can be explained by deep porosity, but also by bulk compositional differences. Recent work has strengthened the case for significant porosity. Halley's nucleus was found to have a density near 0.6 g/cu cm, Janus and Epimethus were proposed to have densities near 0.7 g/cu cm, densities almost certainly due to high porosity. The irregular-spherical shape transition of icy satellites was quantitatively explained by low conductivity regoliths. A creative structure/thermal history model for Mimas simultaneously accounts quantitatively for Mimas' low density and moment of inertia by invoking initial high-porosity and subsequent compaction in the deep interior by thermal creep. The main problem with this promising model is that approximately 7 percent predicts a reduction in Mimas' radius, implying significant compressional failure and prevention of extensional tectonics, in contradiction to the observed extensional features and inferred 1 percent expansion in radius.

Croft, Steven K.↗

Encoding nonlinear and unsteady aerodynamics of limit cycle oscillations using nonlinear sparse Bayesian learning

This article investigates the applicability of a recently proposed, nonlinear sparse Bayesian learning (NSBL) algorithm to identify and estimate the complex aerodynamics of limit cycle oscillations. NSBL provides a semi-analytical framework for determining the data-optimal sparse model nested within a (potentially) over-parameterized model. This is particularly relevant to nonlinear dynamical systems where modelling approaches involve the use of physics-based and data-driven components. In such cases, the data-driven components, where analytical descriptions of the physical processes are not readily available, are often prone to overfitting, meaning that the empirical aspects of these models will often involve the calibration of an unnecessarily large number of parameters. While an overparameterized model may fit the observed data well, such models may be inadequate for making predictions in regimes that are different from those wherein the data were recorded. In view of this, it is desirable to not only calibrate the model parameters, but also identify the optimal compromise between data fit and model complexity. In this article, we exhibit the optimal model discovery for an aeroelastic system wherein the structural dynamics are well-known and described by a differential equation model, coupled with a semi-empirical aerodynamic model for laminar separation flutter, resulting in low-amplitude limit cycle oscillations (LCO). To illustrate the performance of the algorithm, in this article, we use synthetic data and demonstrate the ability of the algorithm to correctly rediscover the optimal model and model parameters, given a known data-generating model. The synthetic data are generated from a forward simulation of a known differential equation model with parameters selected so as to mimic the dynamics observed in wind-tunnel experiments. Subsequently, we demonstrate the performance of the algorithm for model selection using noisy LCO data from wind tunnel experiments. As there is no ground truth available for the experimental data case, we provide a comparison between NSBL and Bayesian model selection to validate the results, and demonstrate the use of NSBL as an efficient alternative to traditional methods.

97 MATHEMATICS AND COMPUTING↗

Some recent developments in the interpretation of MST radar returns from clear air (keynote paper), part 2

Mesosphere-stratosphere-troposphere (MST) radar returns from clear air come about through the interaction of electromagnetic waves with the inhomogeneous structures of refractive index in the atmosphere. In order to interpret the data correctly to obtain information concerning the dynamics of the atmosphere, one must first know how the various refractive index structures can affect the propagation and scattering of the radio waves. This can be achieved through theoretical and model studies. On the other hand, in order to carry out realistic theoretical studies, realistic models of the inhomogeneous structures of the atmospheric refractive index are needed. These are available only through observational data. Therefore the close interplays between theoretical and observational investigations are essential in making progress in this area. Some results on certain aspects of the problem are presented with emphasis on those aspects that may lead to new developments.

Liu, C. H.↗

Variations of the physical parameters of the blazar Mrk 421 based on analysis of the spectral energy distributions

Abstract We report on the variations of the physical parameters of the jet observed in the blazar Mrk 421, and discuss the origin of X-ray flares in the jet, based on analysis of several spectral energy distributions (SEDs). The SEDs are modeled using the one-zone synchrotron self-Compton model, its parameters determined using a Markov chain Monte Carlo method. The lack of data at TeV energies means many of the parameters cannot be uniquely determined and are correlated. These are studied in detail. We find that the optimal solution can be uniquely determined only when we apply a constraint to one of four parameters: the magnetic field (B), the Doppler factor, the size of the emitting region, and the normalization factor of the electron energy distribution. We used 31 sets of SEDs from 2009 to 2014 with optical–UV data observed with UVOT/Swift and the Kanata telescope, X-ray data with XRT/Swift, and γ-ray data with the Fermi Large Area Telescope. The result of our SED analysis suggests that, in the X-ray faint state, the emission occurs in a relatively small area (∼1016 cm) with a relatively strong magnetic field (B ∼ 10−1 G). The X-ray bright state shows a tendency opposite to that of the faint state, that is, a large emitting area (∼1018 cm), probably downstream of the jet, and a weak magnetic field (B ∼ 10−3 G). The high X-ray flux was due to an increase in the maximum energy of electrons. On the other hand, the presence of two kinds of emitting areas implies that the one-zone model is unsuitable for reproducing at least part of the observed SEDs.

Yamada, Yurika↗

Including the parallel mass flow in calculating the steady-state solutions and stability of the momentum balance equations for a quasisymmetric stellarator

The Helically Symmetric Experiment (HSX) is a quasisymmetric stellarator with minimal parallel viscous damping in a helical direction. The parallel flow (Vǁ) along the magnetic field is similarly weakly damped by viscosity. In this paper, the self-consistent steady-state parallel and poloidal momentum balance equations are used to show that a large Vǁ on the order of the ion thermal velocity can increase the ion resonant radial electric field (Er) beyond the value calculated using the typical approximation that Vǁ is zero. By altering the damping of Vǁ, either by degrading the quasisymmetry or varying the neutral density, the ion resonant Er can shift in a controllable fashion. It is shown explicitly that there exist stable and unstable steady-state solutions in the two-dimensional space of Vǁ and Er. A stability analysis of each solution is performed by calculating the eigenvalues and eigenvectors of the Jacobian. The unstable solution corresponds to a saddle point in which the eigenvalues have opposite signs. The analysis leads to the conclusion that unstable solutions occur when the derivative of the total poloidal damping with respect to Er is positive. A hysteresis in Er and Vǁ is observed when the radial current density is linearly increased to a maximum and then decreased back to zero. Jumps in the radial electric field and the parallel flow are observed as the radial current density drives the evolution from one stable point to the next. This result is similar to experimental data observed on several devices.

Physics↗

Deep Learning Parameterization of Vertical Wind Velocity Variability via Constrained Adversarial Training

Atmospheric models with typical resolution in the tenths of kilometers cannot resolve the dynamics of air parcel ascent, which varies on scales ranging from tens to hundreds of meters. Small-scale wind fluctuations are thus characterized by a subgrid distribution of vertical wind velocity W with standard deviation σ W . The parameterization of σ W is fundamental to the representation of aerosol–cloud interactions, yet it is poorly constrained. Using a novel deep learning technique, this work develops a new parameterization for σ W merging data from global storm-resolving model simulations, high-frequency retrievals of W , and climate reanalysis products. The parameterization reproduces the observed statistics of σ W and leverages learned physical relations from the model simulations to guide extrapolation beyond the observed domain. Incorporating observational data during the training phase was found to be critical for its performance. The parameterization can be applied online within large-scale atmospheric models, or offline using output from weather forecasting and reanalysis products.

54 ENVIRONMENTAL SCIENCES↗

Models, data, and scripts associated with “Prediction of Distributed River Sediment Respiration Rates using Community-Generated Data and Machine Learning”

This data package is associated with the publication “Prediction of Distributed River Sediment Respiration Rates using Community-Generated Data and Machine Learning’’ submitted to the Journal of Geophysical Research: Machine Learning and Computation (Scheibe et al. 2024). River sediment respiration observations are expensive and labor intensive to obtain and there is no physical model for predicting this quantity. The Worldwide Hydrobiogeochemisty Observation Network for Dynamic River Systems (WHONDRS) observational data set (Goldman et al.; 2020) is used to train machine learning (ML) models to predict respiration rates at unsampled sites. This repository archives training data, ML models, predictions, and model evaluation results for the purposes of reproducibility of the results in the associated manuscript and community reuse of the ML models trained in this project. One of the key challenges in this work was to find an optimum configuration for machine learning models to work with this feature-rich (i.e. 100+ possible input variables) data set. Here, we used a two-tiered approach to managing the analysis of this complex data set: 1) a stacked ensemble of ML models that can automatically optimize hyperparameters to accelerate the process of model selection and tuning and 2) feature permutation importance to iteratively select the most important features (i.e. inputs) to the ML models. The major elements of this ML workflow are modular, portable, open, and cloud-based, thus making this implementation a potential template for other applications. This data package is associated with the GitHub repository found at Please see the file level metadata (flmd; “sl-archive-whondrs_flmd.csv”) for a list of all files contained in this data package and descriptions for each. Please see the data dictionary (dd; “sl-archive-whondrs_dd.csv”) for a list of all column headers contained within comma separated value (csv) files in this data package and descriptions for each. The GitHub repository is organized into five top-level directories: (1) “input_data” holds the training data for the ML models; (2) “ml_models” holds machine learning models trained on the data in “input_data”; (3) “scripts” contains data preprocessing and postprocessing scripts and intermediate results specific to this data set that bookend the ML workflow; (4) “examples” contains the visualization of the results in this repository including plotting scripts for the manuscript (e.g., model evaluation, FPI results) and scripts for running predictions with the ML models (i.e., reusing the trained ML models); (5) “output_data” holds the overall results of the ML model on that branch. Each trained ML model resides on its own branch in the repository; this means that inputs and outputs can be different branch-to-branch. Furthermore, depending on the number of features used to train the ML models, the preprocessing and postprocessing scripts, and their intermediate results, can also be different branch-to-branch. The “main-*” branches are meant to be starting points (i.e. trunks) for each model branch (i.e. sprouts). Please see the Branch Navigation section in the top-level README.md in the GitHub repository for more details. There is also one hidden directory “.github/workflows”. This hidden directory contains information for how to run the ML workflow as an end-to-end automated GitHub Action but it is not needed for reusing the ML models archived here. Please the top-level README.md in the GitHub repository for more details on the automation.

13C↗

Weak Lensing And Cosmology In The Dark Energy Survey

In this PhD Thesis, we present studies which aim at understanding and testing the fundamental assumptions of the $\Lambda$CDM cosmological model. We initially show that weak gravitational lensing can be derived as a consequence of General Relativity, and that it can be applied to astronomical data from the Dark Energy Survey (DES) in order to constrain the amplitude of matter fluctuations in the universe. This constraint can be used as an end-to-end cosmological test when it is compared to inferences from the Cosmic Microwave Background. We further extend the cosmological model to account for non-standard parameters which can point to novel physics, and use DES data to assess their statistical significance. We finally show that the Cold Dark Matter (CDM) paradigm can also be fundamentally tested with observational data using morphological signatures of disk galaxies in cluster environments if CDM is self-interacting.

79 ASTRONOMY AND ASTROPHYSICS↗

Recurrent brief X-ray bursts from the globular cluster NGC 6624

Observational data are presented on ten brief X-ray bursts, recurrent at nearly equal time intervals, recorded during a two-day observation of 3U 1820-30 in the globular cluster NGC 6624 with the wide-field modulation collimator detectors on the SAS-3 X-ray observatory. The occurrence times were fitted by least squares to a linear sequence with an rms deviation of 621 sec, corresponding to a phase jitter of 3.9%. The bursts were observed in two energy channels. For a sequence of five of the most clearly observed bursts, the 2-6 keV rate rose to its peak value in about 1 sec and then decayed to preburst level in about 10 sec. The 6-11 keV rate rose more slowly and decayed similarly. The smooth decay of their averaged light curve suggests the temporal evolution may have a geometrical origin, where Compton scattering in a surrounding cloud of hot plasma stretches the pulse out and causes a progressive hardening of the spectrum.

Clark, G. W.↗

Transfer of solar radiation in the atmosphere

Current needs in the field of atmospheric radiative transfer include the development and validation of fast but accurate calculation techniques for use in climate modeling. Progress toward meeting these needs can be made by application of existing computational techniques and use of observational data for radiation transfer across the earth-atmosphere system boundaries. In this study radiative transfer model simulations are compared to satellite observations of reflected solar radiation. Calculations are presented from both detailed and approximate transfer models for the solar radiation reflected from the earth-atmosphere system. These calculations are compared with the measurements made by the Earth Radiation Budget (ERB) experiment on Nimbus 6 in August 1975. Results show good agreement between simulations and observations.

Suttles, J. T.↗

Scale covariance and G-varying cosmology. III - The /m, z/, /theta sub m, z/, /theta sub i, z/, and /N/m/, m/ tests

The Einstein gravitational equations in atomic units are fully solved for a matter-dominated universe in the context of a recently proposed scale-covariant cosmology. The magnitude-redshift relation for elliptical galaxies is studied, the evolutionary parameter used in such a study is derived, and the relation between isophotal angular diameters and redshifts is investigated, along with the relation between metric angular diameters and redshifts, the N(m)-magnitude relation for QSOs, and the magnitude-redshift relation for QSOs. Results are presented for four gauges (i.e., relations between G and the scale function beta (t)), and no contradictions are found between the proposed theory and the observational data. It is shown that only an open universe can fit the data if certain gauges suggested by a recent analysis of the time variation of the moon's period are selected and that observations made with atomic instruments do not necessarily yield geometrical parameters unless specific assumptions are made regarding the relation between atomic and gravitational dynamics.

Canuto, V. M.↗

Observations of the reappearance of polar coronal holes and the reversal of the polar magnetic field

Observational data relating to the evolution of the polar magnetic field around sunspot maximum is examined. Particular emphasis is given to coronal hole observations performed during the last two solar maxima. Long-term averages of the latitudinal dependence of the photospheric magnetic field and the evolutionary pattern of the polar crown filaments are used to trace the poleward motion of the reversal of the large-scale field and are compared to the redevelopment of polar holes. Within the context of phenomenological models of the solar cycle, it is concluded that: (1) the process of polarity reversal and redevelopment of polar holes is discontinuous, with surges of flux of old-cycle polarity interrupting the poleward migration of new-cycle flux; (2) contrary to the Babcock (1961) hypothesis, the polar crown disappears months after the magnetic pole reversal; and (3) the observations support suggestions of a poleward meridional flow around solar maximum that cannot be accounted for by Leighton-type (1964) diffusion.

Webb, D. F.↗

Line emission from H II blister models

Numerical techniques to calculate the thermal and geometric properties of line emission from H II 'blister' regions are presented. It is assumed that the density distributions of the H II regions are a function of two dimensions, with rotational symmetry specifying the shape in three-dimensions. The thermal and ionization equilibrium equations of the problem are solved by spherical modeling, and a spherical sector approximation is used to simplify the three-dimensional treatment of diffuse ionizing radiation. The global properties of H II 'blister' regions near the edges of a molecular cloud are simulated by means of the geometry/density distribution, and the results are compared with observational data. It is shown that there is a monotonic increase of peak surface brightness from the i = 0 deg (pole-on) observational position to the i = 90 deg (edge-on) position. The enhancement of the line peak intensity from the edge-on to the pole-on positions is found to depend on the density, stratification, ionization, and electron temperature weighting. It is found that as i increases, the position of peak line brightness of the lower excitation species is displaced to the high-density side of the high excitation species.

Rubin, R. H.↗

Numerical simulations of the subsynoptic features associated with the AVE-SESAME I case. I - The preconvective environment

The extensive diagnostic calculations made possible by the AVE-SESAME I database are used in combination with numerical simulations from the Mesoscale Atmospheric Simulation System (MASS) model to examine the dynamics of the meso-alpha-scale features during the preconvective period from 1130 to 2030 UTC on April 10, 1979. The version of the MASS model used in this investigation is presented, and an overview of the general synoptic conditions present at the time of model initialization is presented along with the data used to initialize the model. The dynamical processes present in the numerical simulations are presented and compared with analyses of the observational data from this and other investigations of this case. The relative importance of the adiabatic and diabatic processes in creating and then initiating the release of the convective instability is discussed.

Zack, John W.↗

Lidar observations of the fine-scale variability of marine stratocumulus clouds

An Nd:YAG lidar system was flown aboard NASA's ER-2 high altitude aircraft. Observations of cloud top height were made with 70 m along-track and 7.5 m vertical-height resolution. The lidar data observed from an East Pacific stratocumulus cloud height deck revealed large cloud variability on 1-5 km scales. The cloud deck sloped upward from 700 to 1000 m in a northeast-southwest direction over a distance of 120 km. Vertical cloud top distributions were negatively skewed indicating flat-topped clouds. The dominant spectral peak of the cloud top variations was found at 4.5 km, which is 5 to 7 times the depth of the local boundary layer. No other peaks were significant in the average spectrum. The cloud layer was stable with respect to cloud top entrainment instability. The southwestern region of the study area was more prone to shear instability at cloud top than the northeastern region. The results of this study show that a lidar system is ideal to provide the topography of clouds and local boundary layer depth. This information is useful in the study of cloud top radiation and parameterization of clouds in numerical models.

Boers, Reinout↗

An Integrated Data Analytics Platform

An Integrated Science Data Analytics Platform is an environment that enables the confluence of resources for scientific investigation. It harmonizes data, tools and computational resources which subsequently enable the research community to focus on the investigation rather than spending time on security, data preparation, management, etc. OceanWorks is a NASA technology integration project to establish a cloud-based Integrated Ocean Science Data Analytics Platform at NASA’s Physical Oceanography Distributed Active Archive Center (PO.DAAC) for big ocean science. It focuses on advancement and maturity by bringing together several NASA open-source, big data projects for parallel analytics, anomaly detection, in-situ to satellite data matchup, quality-screened data subsetting, search relevancy, and data discovery. Our communities are relying on data distributed through data centers such as the PO.DAAC, COAPS, NCAR, and many others to conduct their research. In typical investigations, scientists would engage in: search for data, evaluate the relevance of that data, download it, and then apply algorithms to identify trends. Such workflow cannot scale if the research involves a massive amount of data or multi-variate measurements. NASA’s Surface Water and Ocean Topography (SWOT) mission is expected to produce massive amount of observational data during its 3-year nominal mission. Collections like SWOT challenges all existing Earth Science data archival, distribution and analysis paradigms. In this paper, we will discuss how OceanWorks enhances the analysis of physical ocean data where the computation is done on an elastic cloud platform next to the archive to deliver fast, web-accessible services for working with oceanographic measurements.

Yang, Chaowei↗

The O IV and S IV intercombination lines in solar and stellar ultraviolet spectra

New calculations of O IV electron density diagnostic emission-line ratios involving the 1399.8, 1401.2, 1404.8, and 14076.4 A transitions are presented. A comparison of these calculations with observational data from a quiet solar region, a sunspot, and an active region obtained with the High Resolution Telescope and Spectrograph (HRTS), two flares observed with the SO82B spectrograph on board Skylab, and Hubble Space Telescope (HST) observations by the Goddard High Resolution Spectrograph (GHRS) of Capella, gives good results using the ratio R(sub 1) = I(1407.4 A)/I(1401.2 A). However, the electron density obtained using the ratio R(sub 2) = I(1407.4 A)/I(1404.8 A) is often an order of magnitude smaller. The O IV 1404.8 A line is blended with the S IV 1404.8 A line, and we investigate whether this ratio may still be used as a density diagnostic if the S IV 1406.1 A line intensity is used to correct for the presence of S IV 1404.8 A, using previous S IV calculations by Dufton et al. We still find systematic differences compared to density determinations from line ratios that do not involve the O IV 1404.8 A line, which we suggest are due to errors in earlier theoretical calculations of the S IV atomic data, and also possibly to previously unconsidered fluorescent pumping of the upper level of the S IV 1404.8 A transition.

Cook, J. W.↗

Multi-Scale Hydrometeorological Modeling, Land Data Assimilation and Parameter Estimation with the Land Information System

The Land Information System (LIS; http://lis.gsfc.nasa.gov) is a flexible land surface modeling framework that has been developed with the goal of integrating satellite-and ground-based observational data products and advanced land surface modeling techniques to produce optimal fields of land surface states and fluxes. As such, LIS represents a step towards the next generation land component of an integrated Earth system model. In recognition of LIS object-oriented software design, use and impact in the land surface and hydrometeorological modeling community, the LIS software was selected as a co-winner of NASA?s 2005 Software of the Year award.LIS facilitates the integration of observations from Earth-observing systems and predictions and forecasts from Earth System and Earth science models into the decision-making processes of partnering agency and national organizations. Due to its flexible software design, LIS can serve both as a Problem Solving Environment (PSE) for hydrologic research to enable accurate global water and energy cycle predictions, and as a Decision Support System (DSS) to generate useful information for application areas including disaster management, water resources management, agricultural management, numerical weather prediction, air quality and military mobility assessment. LIS has e volved from two earlier efforts -- North American Land Data Assimilation System (NLDAS) and Global Land Data Assimilation System (GLDAS) that focused primarily on improving numerical weather prediction skills by improving the characterization of the land surface conditions. Both of GLDAS and NLDAS now use specific configurations of the LIS software in their current implementations.In addition, LIS was recently transitioned into operations at the US Air Force Weather Agency (AFWA) to ultimately replace their Agricultural Meteorology (AGRMET) system, and is also used routinely by NOAA's National Centers for Environmental Prediction (NCEP)/Environmental Modeling Center (EMC) for their land data assimilation systems to support weather and climate modeling. LIS not only consolidates the capabilities of these two systems, but also enables a much larger variety of configurations with respect to horizontal spatial resolution, input datasets and choice of land surface model through "plugins". LIS has been coupled to the Weather Research and Forecasting (WRF) model to support studies of land-atmosphere coupling be enabling ensembles of land surface states to be tested against multiple representations of the atmospheric boundary layer. LIS has also been demonstrated for parameter estimation, who showed that the use of sequential remotely sensed soil moisture products can be used to derive soil hydraulic and texture properties given a sufficient dynamic range in the soil moisture retrievals and accurate precipitation inputs.LIS has also recently been demonstrated for multi-model data assimilation using an Ensemble Kalman Filter for sequential assimilation of soil moisture, snow, and temperature.Ongoing work has demonstrated the value of bias correction as part of the filter, and also that of joint calibration and assimilation.Examples and case studies demonstrating the capabilities and impacts of LIS for hydrometeorological modeling, assimilation and parameter estimation will be presented as advancements towards the next generation of integrated observation and modeling systems

Peters-Lidard, Christa D.↗