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At least 649 records · Page 36

Cultivating an Emergent Earth Observation Analytics Ecosystem in the Cloud

A diverse set of data analytics systems for Earth Observations are sprouting up in the Earth Science community, with a wealth of processing algorithms and analysis methods. There is a similar wealth of data resources available via myriad data providers and clearinghouses, including large institutional systems like the Earth Observing System Data and Information System, Comprehensive Large Scale Array-data Stewardship System, and Federated Earth Observation Missions gateway. With Earth system science driving a need to work with more datasets together, and the community developing more analysis tools (some of them dataset-specific), how can we develop analysis workflows that incorporate far-flung datasets and leverage analysis resources from multiple organizations? Cloud computing points the way toward a solution in two different respects. Firstly, the access to and abstraction of virtually unlimited storage and computing power provides an environment that enables more straightforward means of pulling datasets and analysis resources together. Just as importantly, however, cloud computing serves as an example of an "ecosystem" of interoperating services, since the essence of cloud computing is the presentation of all resources as a service, from hardware to infrastructure to platform to software. This enables the combination of off-the-shelf, diverse services to construct entire systems that emerge out of an equally diverse community of architects and developers. This approach can be similarly applied to the data and analysis resources in the Earth Observation community. By exposing these resources via well understood services, and consuming resources in the same way, different organizations can construct bespoke analysis workflows and systems for their own purposes. The key leap the community needs to make is to develop analysis systems in components that interact with other components via services. The result would be a rich ecosystem of analytics components that can be combined to analyze datasets at scale and in conjunction with other datasets from other sources.

chaos↗

Shock-Layer Radiation Insights Available Through Flowfield Property Binning

This paper introduces a method for assessing similarity between available shock-layer radiation measurements and the radiative heating to a vehicle of interest. This method will be referred to as the flowfield property binning (FPB) approach. The challenge in developing this approach is that radiometer measurements from a surface normal line of sight, observed radiation measurements of the entire shock-layer from a distance, or measured shock-tube nonequilibrium profiles are notably different geometrically than the radiative flux to a vehicle surface. Therefore, the relative contributions of various regions of the shock-layer to the measurement, and how these relative contributions compare with the radiative heating to a vehicle of interest, are unclear. By tracking the radiation contribution from each flowfield location, and then grouping this contribution based on two local flowfield properties, these geometric differences are removed. This provide a two dimensional group, or bin, distribution that represents the radiation environment in the same format for various types of radiation simulations, such as observed radiation or radiative flux to a vehicle surface. In the limits of optically-thin radiation transport and thermochemical equilibrium flow, the choice of pressure and temperature as the binning flowfield properties is shown to provide a bin distribution that uniquely defines the radiation simulation. This concept is found to be sufficient for establishing similarity between two cases even when the optically-thin radiation transport and thermochemical equilibrium assumptions are not satisfied. A simple metric of comparison between bin distributions from different cases is provided by the histogram intersection algorithm. This algorithm results in a histogram intersection factor (H) between 0 and 1, which represents the fraction of the radiation that is similar between the two cases. Therefore, if H evaluated between bin distributions for two completely different radiation problems is near 1, then they represent essentially the same radiation problem. This means that they depend on the same weighting of various radiation modeling parameters evaluated at the same pressure and temperature. If one of these cases agrees well with a radiation measurement, then the matching bin distributions provide justification for applying this experimental validation to the other case. Even for H values as low as 0.2, the measurement case could be considered relevant if there are no other useful measurements. This approach allows observed radiation measurements to directly inform radiative heating simulations, which allows NASA’s past and future investments in observed radiation measurements to directly inform the radiative heating uncertainty or margins for future vehicle design. This FPB approach is also used to determine shock-tube conditions for informing backshell radiative heating simulations, where the normal shock velocity and Lagrangian time from the shock is used for the binning variables instead of pressure and temperature.

Shock Layer Radiation↗

An AI-Enabled MODEX Framework for Improving Predictability of Subsurface Water Storage across Local and Continental Scales

Focal Area: (2) Predictive modeling through the use of AI techniques and AI-derived model components. (3) Insight gleaned from complex data using AI, big data analytics, and other advanced methods. We propose an AI-enabled model-experiment (MODEX) framework to improve the predictability of subsurface water storage (SWS) from local to conus scales in a changing environment by taking advantage of DOE’s observation and simulation capabilities, as well as to inform the model and the observation development.

54 ENVIRONMENTAL SCIENCES↗

Space Weather Nowcasting of Atmospheric Ionizing Radiation for Aviation Safety

There is a growing concern for the health and safety of commercial aircrew and passengers due to their exposure to ionizing radiation with high linear energy transfer (LET), particularly at high latitudes. The International Commission of Radiobiological Protection (ICRP), the EPA, and the FAA consider the crews of commercial aircraft as radiation workers. During solar energetic particle (SEP) events, radiation exposure can exceed annual limits, and the number of serious health effects is expected to be quite high if precautions are not taken. There is a need for a capability to monitor the real-time, global background radiations levels, from galactic cosmic rays (GCR), at commercial airline altitudes and to provide analytical input for airline operations decisions for altering flight paths and altitudes for the mitigation and reduction of radiation exposure levels during a SEP event. The Nowcast of Atmospheric Ionizing Radiation for Aviation Safety (NAIRAS) model is new initiative to provide a global, real-time radiation dosimetry package for archiving and assessing the biologically harmful radiation exposure levels at commercial airline altitudes. The NAIRAS model brings to bear the best available suite of Sun-Earth observations and models for simulating the atmospheric ionizing radiation environment. Observations are utilized from ground (neutron monitors), from the atmosphere (the METO analysis), and from space (NASA/ACE and NOAA/GOES). Atmospheric observations provide the overhead shielding information and the ground- and space-based observations provide boundary conditions on the GCR and SEP energy flux distributions for transport and dosimetry simulations. Dose rates are calculated using the parametric AIR (Atmospheric Ionizing Radiation) model and the physics-based HZETRN (High Charge and Energy Transport) code. Empirical models of the near-Earth radiation environment (GCR/SEP energy flux distributions and geomagnetic cut-off rigidity) are benchmarked against the physics-based CMIT (Coupled Magnetosphere- Ionosphere-Thermosphere) and SEP-trajectory models.

Mertens, Christopher J.↗

The information content of jet quenching and machine learning assisted observable design

Jets produced in high-energy heavy-ion collisions are modified compared to those in proton-proton collisions due to their interaction with the deconfined, strongly-coupled quark-gluon plasma (QGP). In this work, we employ machine learning techniques to identify important features that distinguish jets produced in heavy-ion collisions from jets produced in proton-proton collisions. We formulate the problem using binary classification and focus on leveraging machine learning in ways that inform theoretical calculations of jet modification: (i) we quantify the information content in terms of Infrared Collinear (IRC)-safety and in terms of hard vs. soft emissions, (ii) we identify optimally discriminating observables that are in principle calculable in perturbative QCD, and (iii) we assess the information loss due to the heavy-ion underlying event and background subtraction algorithms. We illustrate our methodology using Monte Carlo event generators, where we find that important information about jet quenching is contained not only in hard splittings but also in soft emissions and IRC-unsafe physics inside the jet. This information appears to be significantly reduced by the presence of the underlying event. We discuss the implications of this for the prospect of using jet quenching to extract properties of the QGP. Since the training labels are exactly known, this methodology can be used directly on experimental data without reliance on modeling. We outline a proposal for how such an experimental analysis can be carried out, and how it can guide future measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

From Existing and New Nuclear and Astrophysical Constraints to Stringent Limits on the Equation of State of Neutron-Rich Dense Matter

Through continuous progress in nuclear theory and experiment and an increasing number of neutron-star (NS) observations, a multitude of information about the equation of state (EOS) for matter at extreme densities is available. To constrain the EOS across its entire density range, this information needs to be combined consistently. However, the impact and model dependency of individual observations vary. Given their growing number, assessing the various methods is crucial to compare the respective effects on the EOS and discover potential biases. For this purpose, we present a broad compendium of different constraints and apply them individually to a large set of EOS candidates within a Bayesian framework. Specifically, we explore different ways of how chiral effective field theory and perturbative quantum chromodynamics can be used to place a likelihood on EOS candidates. We also investigate the impact of nuclear experimental constraints, as well as different radio and x-ray observations of NS masses and radii. This is augmented by reanalyses of the existing data from binary neutron star coalescences, in particular of GW170817, with improved models for the tidal waveform and kilonova light curves, which we also utilize to construct a tight upper limit of 2.39 M ⊙ on the TOV mass based on GW170817’s remnant. Our diverse set of constraints is eventually combined to obtain stringent limits on NS properties. We organize the combination in a way to distinguish between constraints where the systematic uncertainties are deemed small and those that rely on less conservative assumptions. For the former, we find the radius of the canonical 1.4 M ⊙ neutron star to be R 1.4 = 12.2 6 − 0.91 + 0.80 km and the TOV mass at M TOV = 2.2 5 − 0.22 + 0.42 M ⊙ (95% credibility). Including all the presented constraints yields R 1.4 = 12.2 0 − 0.48 + 0.50 km and M TOV = 2.3 0 − 0.20 + 0.07 M ⊙ . When comparing these limits to individual data points, we find that the quoted radius of HESS J1731-347 displays noticeable tension with other constraints. Constraining microphysical properties of the EOS proves more challenging. For instance, the symmetry energy slope is restricted to L sym = 48 − 25 + 21 MeV , where this constraint is mainly dominated by our reanalysis of the PREX-II and CREX experiment. Published by the American Physical Society 2025

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

The structure and energy balance of cool star atmospheres

The atmospheric structure and energy balance phenomena associated with magnetic fields in the Sun are reviewed and it is shown that similar phenomena occur in cool stars. The evidence for the weakening or disappearance of transition regions and coronae is discussed together with the appearance of extended cool chromospheres with large mass loss, near V-R = 0.80 in the H-R diagram. Like the solar atmosphere, these atmospheres are not homogeneous and there is considerable evidence for plage regions with bright TR emission lines that overlie dark (presumably magnetic) star spots. The IUE observations are providing important information on the energy balance in these atmospheres that should guide theoretical calculations of the nonradiative heating rate. Recent high dispersion spectra are providing unique information concerning which components of close binary systems are the dominant contributors to the observed emission. A recent unanticipated discovery is that the transition lines are redshifted (an antiwind) in DRa (G2 Ib) and perhaps other stars. Finally, the G and K giants and supergiants are classified into three groups depending on whether their atmospheres are dominated by closed magnetic flux tubes, open field geometries, or a predominately open geometry with a few closed flux tubes embedded.

Linsky, J. L.↗

Forecasting disease risk for increased epidemic preparedness in public health

Emerging infectious diseases pose a growing threat to human populations. Many of the world's epidemic diseases (particularly those transmitted by intermediate hosts) are known to be highly sensitive to long-term changes in climate and short-term fluctuations in the weather. The application of environmental data to the study of disease offers the capability to demonstrate vector-environment relationships and potentially forecast the risk of disease outbreaks or epidemics. Accurate disease forecasting models would markedly improve epidemic prevention and control capabilities. This chapter examines the potential for epidemic forecasting and discusses the issues associated with the development of global networks for surveillance and prediction. Existing global systems for epidemic preparedness focus on disease surveillance using either expert knowledge or statistical modelling of disease activity and thresholds to identify times and areas of risk. Predictive health information systems would use monitored environmental variables, linked to a disease system, to be observed and provide prior information of outbreaks. The components and varieties of forecasting systems are discussed with selected examples, along with issues relating to further development.

Disease Outbreaks↗

Infrared Observations of Late Type Stars

Substantive mass loss resulting in appreciable circumstellar dust envelopes is common in late-type stars. The evolutionary history and physical state of a cool star determine the chemistry within the outer stellar atmosphere mirrored by the molecular and particulate material present in the envelope. The observational consequences of this debris determined by moderate spectral resolution infrared spectrophotometry are reviewed. Significant information is provided by observations of the emergent energy flux of both the cool stellar photosphere and of the circumstellar dust envelope. The observation suggests that mass-loss occurs to some degree throughout late stellar evolutionary phases and that occasional periods of high mass loss are not uncommon.

Merrill, K. M.↗

Late-time spectra and type Ia supernova models: New clues from the Hubble Space Telescope

Calculated late-time spectra of two classical hydrodynamical models for Type Ia supernovae (deflagration model W7 of Nomoto, Thielemann, & Yokoi, and delayed detonation model DD4 of Woosley & Weaver) are compared with observations of SN 1992A and other spectroscopically normal SNe Ia. An important new piece of information is provided by observations done with the Hubble Space Telescope (HST) which cover the ultraviolet range at the nebular phase of a SN Ia: SN 1992A in NGC 1380. For the first time a picture of SN Ia emission from the ultraviolet through the optical is obtained at these phases. Predictions of the classical model (W7 and DD4) are compared with the observed spectrum of SN 1992A and with the optical spectra of SN 1989M in NGC 4579 and SN 1990N in NGC 4639 at similar epochs. The absolute B and V magnitudes of the models are also estimated at these late phases. Taken at face value the nebular spectra of these 'classical' models are more consistent with the long extragalactic distance scale, pointing to distances to NGC 4579 around 21 +/- 3 Mpc and a slightly larger distance, 22 +/- 3 Mpc, to NGC 4639, on the back side of the Virgo Cluster. However, the calculated Fe(+3) luminosity as predicted from the models exceeds the observed limit from the HST data of SN 1992A. Other differences in the ratios of the line intensities between calculated and observed spectra, show some disagreement with the observed spectra at the nebular phases. They may not be the best choice for spectroscopically normal SNe Ia, and their use as an independent calibration of the extragalactic distance scale should be viewed with caution.

Ruiz-Lapuente, P.↗

On the sensitivity of numerical weather prediction to remotely sensed marine surface wind data - A simulation study

The reported investigation has the objective to assess the potential impact on numerical weather prediction (NWP) of remotely sensed surface wind data. Other investigations conducted with similar objectives have not been satisfactory in connection with a use of procedures providing an unrealistic distribution of initial errors. In the current study, care has been taken to duplicate the actual distribution of information in the conventional observing system, thus shifting the emphasis from accuracy of the data to the data coverage. It is pointed out that this is an important consideration in assessing satellite observing systems since experience with sounder data has shown that improvements in forecasts due to satellite-derived information is due less to a general error reduction than to the ability to fill data-sparse regions. The reported study concentrates on the evaluation of the observing system simulation experimental design and on the assessment of the potential of remotely sensed marine surface wind data.

Cane, M. A.↗

Polarimetry of satellite surfaces

Available polarization observations of the satellites are reviewed, and the question of what information about satellite surfaces such observations contain is discussed critically. For satellites with negligible atmospheres, polarization measurements should provide useful information on surface texture and on the opacity of the surface materials. However, they are unlikely to yield specific compositional information. For Titan, the only satellite known to have an extensive atmosphere, polarimetry indicates the presence of optically thick clouds; it should be possible to deduce the cloud particle characteristics from such data, especially if more extensive observations, covering the full range of available phase angles and wavelengths, are obtained.

Veverka, J.↗

Quantum chaos in the Brownian SYK model with large finite N: OTOCs and tripartite information

We consider the Brownian SYK model of N interacting Majorana fermions, with random couplings that are taken to vary independently at each time. We study the out-of-time-ordered correlators (OTOCs) of arbitrary observables and the Rényi-2 tripartite information of the unitary evolution operator, which were proposed as diagnostic tools for quantum chaos and scrambling, respectively. We show that their averaged dynamics can be studied as a quench problem at imaginary times in a model of N qudits, where the Hamiltonian displays site-permutational symmetry. By exploiting a description in terms of bosonic collective modes, we show that for the quantities of interest the dynamics takes place in a subspace of the effective Hilbert space whose dimension grows either linearly or quadratically with N, allowing us to perform numerically exact calculations up to N = 10 6 . We analyze in detail the interesting features of the OTOCs, including their dependence on the chosen observables, and of the tripartite information. We observe explicitly the emergence of a scrambling time t* ~ ln N controlling the onset of both chaotic and scrambling behavior, after which we characterize the exponential decay of the quantities of interest to the corresponding Haar scrambled values.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Constraining neutron-star matter with microscopic and macroscopic collisions

Interpreting high-energy, astrophysical phenomena, such as supernova explosions or neutron-star collisions, requires a robust understanding of matter at supranuclear densities. However, our knowledge about dense matter explored in the cores of neutron stars remains limited. Fortunately, dense matter is not probed only in astrophysical observations, but also in terrestrial heavy-ion collision experiments. Here we use Bayesian inference to combine data from astrophysical multi-messenger observations of neutron stars and from heavy-ion collisions of gold nuclei at relativistic energies with microscopic nuclear theory calculations to improve our understanding of dense matter. We find that the inclusion of heavy-ion collision data indicates an increase in the pressure in dense matter relative to previous analyses, shifting neutron-star radii towards larger values, consistent with recent observations by the Neutron Star Interior Composition Explorer mission. Our findings show that constraints from heavy-ion collision experiments show a remarkable consistency with multi-messenger observations and provide complementary information on nuclear matter at intermediate densities. This work combines nuclear theory, nuclear experiment and astrophysical observations, and shows how joint analyses can shed light on the properties of neutron-rich supranuclear matter over the density range probed in neutron stars.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Analysis of star pair latitudes

Star pair latitude observations forming the basis for the pole positions reported by the International Polar Motion Service (IPMS) are processed to produce a mean pole position. However, the time series of raw observations contains high frequency information which is lost in the calculation of the mean pole. Analysis of 2931 star pair observations reveals a possible large excitation at one cycle per solar day. The average power level in the frequency band of the tesseral tides is seen to be high, although the peaks do not occur at the expected tidal frequencies.

Graber, M. A.↗

BOREAS Hardcopy Maps

Boreal Ecosystem-Atmospheric Study (BOREAS) hardcopy maps are a collection of approximately 1,000 hardcopy maps representing the physical, climatological, and historical attributes of areas covering primarily the Manitoba and Saskatchewan provinces of Canada. These maps were collected by BOREAS Information System (BORIS) and Canada for Remote Sensing (CCRS) staff to provide basic information about site positions, manmade features, topography, geology, hydrology, land cover types, fire history, climate, and soils of the BOREAS study region. These maps are not available for distribution through the BOREAS project but may be used as an on-site resource. Information is provided within this document for individuals who want to order copies of these maps from the original map source. Note that the maps are not contained on the BOREAS CD-ROM set. An inventory listing file is supplied on the CD-ROM to inform users of the maps that are available. This inventory listing is available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). For hardcopies of the individual maps, contact the sources provided.

Hall, Forrest G.↗

Challenges in Development of Online Visualization and Analysis Tools for Satellite Data

Over the years, various online visualization and analysis tools have been developed to facilitate satellite data access and help scientific users around the world to conduct research and develop applications (e.g., data product evaluation, what-if questions, etc.). For those who are new to satellite data products, using them can be a daunting task due to many obstacles in data processing such as data formats, complex data structures, special software packages, unfamiliar terminology, etc., especially when one is not sure whether a dataset is suitable for his/er research project. Even for experienced users, developing software for data processing and analysis can be a costly and time-consuming task. Online visualization tools can overcome many of these difficulties and allow users to focus on scientific questions. For example, Giovanni (the Geospatial Interactive Online Visualization and Analysis Infrastructure, https://giovanni.gsfc.nasa.gov), developed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), allows access over 1900 satellite and model variables in 82 measurement groups of 8 disciplines without downloading data and software. Main features include basic functions for data analysis and visualization, data provenance, output data in different formats (ASCII, NetCDF, GeoTIFF), and more. Over the years, ~1700 peer-reviewed publications in different disciplines have been benefited from Giovanni in research activities (e.g. initial investigation, what-if questions, product evaluation). Despite the success of online visualization and analysis tools, challenges and new opportunities still exist and more can be done with new requirements and technology. Examples are: a) how to increase the efficiency of dataset search by enhancing intuitive aspects; b) how to facilitate interdisciplinary research; c) how to provide data quality information; d) how to engage users to participate in data quality assessment; and more. NASA Earth Observing System Data and Information System (EOSDIS) satellite-based data products are processed at various levels ranging from Level 0 to Level 4. While most users use data products at higher levels (Level-3 and 4), products at lower levels are still important for case studies, algorithm development, ground validation, etc. In this presentation, we will use Giovanni as an example to present and discuss challenges and near-future opportunities for satellite data online visualization and analysis tools.

Liu, Zhong↗