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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Constraining the Multiscale Structure of Geophysical Fields in Machine Learning: The Case of Precipitation

The use of deep-learning algorithms for estimating the value of geophysical variables from remotely sensed information is rapidly expanding. The typical objective function minimized in such algorithms is the mean square error (MSE), which is known to lead to smooth estimates with compressed dynamical range as compared to the true distribution of the variable of interest. Here, we introduce and evaluate alternative objective functions, focusing on the retrieval of precipitation rates from satellite passive microwave radiometric measurements using a deep convolutional neural network. For this testbed application, the results show that explicitly imposing the preservation of the statistical distribution and spatial wavelet power spectrum of the target variable allows to accurately reproduce extreme values and sharp gradients across multiple scales in this study.

58 GEOSCIENCES↗
DOE OSTI2021

Sensor-based phenology from snowmelt experiment gradient, East River, Colorado, 2017 to 2020

The timing of snowmelt is a critical cue for the initiation of growth in mountain meadow ecosystems and can also impact the duration and magnitude of plant production. High frequency observations of species-level phenology are time consuming and require a high degree of expertise, and publicly available remote sensing products lack the necessary temporal resolution to assess fine-scale growing season dynamics. Near-surface sensing methods provide a middle ground with high temporal frequency and tractable spatial scales (from sub-meter to hillslope scale). This data package includes csv files of Normalized Difference Vegetation Index (NDVI) timeseries (SM_NDVI_dailymax.csv) and phenological thresholds (SM_NDVI_summary.csv) for sub-plots (1m2) and Green Chromatic Coordinate (GCC) phenological thresholds (SM_GCC_summary.csv) at the plot scale (10m x 14m). Location IDs associated with this data package are: ER-LM, WG-UM, WG-LS, ER-US, and XX-AL. Related data packages include: “Microclimate observations associated with snowmelt experiment gradient sites, East River, Colorado, 2017 to 2020” and “Colorado Elevation Gradient Snowmelt Manipulation Plant Phenology 2017-2018”.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1991

Thermal diffusion in metal-sulfide liquids - Early results

Experiments were carried out to evaluate the Soret effect in liquid Fe-Ni-S-P alloys in order to gain a better understanding of the physical and thermodynamic properties of metallic liquids and to assess the possibility of systematic errors in Czochralski growth techniques. The metal-sulfide liquids were found to show a substantial Soret effect and, contrary to previous expectation, can be as large as that seen in the silicate system. The segregation is largely produced by S-Fe interactions. The P redistribution occurs to reduce activity gradients in P consequent upon S gradients, and P segregation can be approximately predicted in Fe-Ni-S liquids using the activity model of Jones and Malvin (1990). It is inferred that the sense of the Soret segregation, with P going to the cold end and S going to the hot end, is in accordance with the prediction of Malvin et al. (1986), who speculated that the crystal-pulling experiments of Sellamuthu and Goldstein (1985) was influenced by the Soret effect.

Jones, J. H.↗
NASA NTRSDate not supplied

Preliminary SnowSAR Results from SnowEx 2017

SnowEx 2017 was the first in a multi-year series of airborne remote sensing campaigns, designed to address gaps in snow retrieval techniques in preparation for a future snow satellite mission. A variety of sensor types were flown to collect multi-sensor airborne data. In combination with detailed ground truth, this multi-sensor dataset enables critical trade studies to determine optimum sensor-plus-model combinations for different snow conditions and confounding factors. Up to half of terrestrial snow-covered areas are forested, and forests are a major confounding factor for global snow retrievals. Therefore, the main focus of SnowEx 2017 was evaluating the performance of the various sensing techniques to retrieve snow water equivalent (SWE) under steadily increasing amounts of forest cover. The primary site of Grand Mesa, Colorado, USA was selected for its natural gradients of forest density and SWE with a minimum of other factors. Radar retrievals of SWE relying on volume scattering have been studied for three decades, using a variety of frequencies, with varying degrees of success. The most recent volume scattering algorithms have focused on using 2 to 3 frequencies and both co- and cross-polarizations in the 9—18 GHz range (X through Ku bands). As such, one of the primary SnowEx 2017 airborne sensors was a dual-band (X & Ku) radar, the SnowSAR. Earlier versions of SnowSAR were used in 2011 and 2012 campaigns in Finland as well as a 2013 campaign in Canada. For SnowEx 2017, SnowSAR was installed on a P-3 aircraft from the US Naval Research Laboratory. Challenges associated with the aircraft, the installation, schedule, and flying weather all contrived to limit the amount of data collected. However, months of painstaking processing has yielded data that should be of value to the original objectives of SnowEx 2017. This paper will describe in detail the SnowSAR data that were collected, and provide quality assessments of the backscatter coefficient in terms of date, time, location, frequency, polarization, snow conditions, overlap with ground truth sites, forest density, etc. The challenges as well as potential remedies/caveats will be described in order to help guide users and maximize exploitation of this valuable data.

airborne sensors↗
NASA NTRS2019

The 1997 Mars Pathfinder Spacecraft Landing Site: Spillover Deposits from an Early Mars Inland Sea

The Martian outflow channels comprise some of the largest known channels in the Solar System. Remote-sensing investigations indicate that cataclysmic floods likely excavated the channels ~3.4 Ga. Previous studies show that, in the southern circum-Chryse region, their flooding pathways include hundreds of kilometers of channel floors with upward gradients. However, the impact of the reversed channel-floor topography on the cataclysmic floods remains uncertain. Here, we show that these channel floors occur within a vast basin, which separates the downstream reaches of numerous outflow channels from the northern plains. Consequently, floods propagating through these channels must have ponded, producing an inland sea, before reaching the northern plains as enormous spillover discharges. The resulting paleohydrological reconstruction reinterprets the 1997 Pathfinder landing site as part of a marine spillway, which connected the inland sea to a hypothesized northern plains ocean. Our flood simulation shows that the presence of the sea would have permitted the propagation of low-depth floods beyond the areas of reversed channel-floor topography. These results explain the formation at the landing site of possible fluvial features indicative of flow depths at least an order of magnitude lower than those apparent from the analyses of orbital remote-sensing observations.

J. A. P. Rodriguez↗
NASA NTRS2022

Remote Sensing of Coronal Forces During a Solar Prominence Eruption

We present a new methodology—the Keplerian Optical Dynamics Analysis (KODA)—for quantifying the dynamics of erupting magnetic structures in the solar corona. The technique involves adaptive spatiotemporal tracking of propagating intensity gradients and their characterization in terms of time-evolving Keplerian areas swept out by the position vectors of moving plasma blobs. Whereas gravity induces purely ballistic motions consistent with Kepler's second law, noncentral forces such as the Lorentz force introduce nonzero torques resulting in more complex motions. KODA algorithms enable direct evaluation of the line-of-sight component of the net torque density from the image-plane projection of the areal acceleration. The method is applied to the prominence eruption of 2011 June 7, observed by the Solar Dynamics Observatory's Atmospheric Imaging Assembly. Results obtained include quantitative estimates of the magnetic forces, field intensities, and blob masses and energies across a vast region impacted by the postreconnection redistribution of the prominence material. The magnetic pressure and energy are strongly dominant during the early, rising phase of the eruption, while the dynamic pressure and kinetic energy become significant contributors during the subsequent falling phases. Measured intensive properties of the prominence blobs are consistent with those of typical active-region prominences; measured extensive properties are compared with those of the whole pre-eruption prominence and the post-eruption coronal mass ejection of 2011 June 7, all derived by other investigators and techniques. We show that KODA provides valuable information on spatially and temporally dependent characteristics of coronal eruptions that is not readily available via alternative means, thereby shedding new light on the environment and evolution of these solar events.

V M Uritskiy↗
NASA NTRS2019

Holocene Ecohydrological Variability on the East Coast of Kamchatka

The Late Glacial and Holocene climate of the western North Pacific is less studied than that of the eastern North Pacific. While it is well known that strong east-west gradients in the tropical Pacific Ocean influence terrestrial climate, we seek to better understand how these gradients are expressed in the northern extratropics. Toward this aim, we present an organic and stable isotope geochemical and macrofossil record from a peatland on the east coast of the Kamchatka peninsula. We find that both the early and late Holocene were wetter, with a different assemblage of plants from the middle Holocene, which was drier, with more episodic precipitation. The large ecohydrological changes at several points during the Holocene are contemporaneous with and of the same sense as those we find at places to the east, such as south-central Alaska and to the south, in northern Japan. We also find that the middle Holocene period of warmth, dryness and low carbon accumulation occur contemporaneously with an enhanced east-west gradient in tropical Pacific sea surface temperature. This suggests that hydroclimatic conditions in the subarctic can be influenced by tropical dynamics.

Nichols, Jonathan↗
DOE OSTI2023

Simulation toolkit for digital material characterization of large image-based microstructures

In this paper, an efficient image-based simulation toolkit for material characterization is presented, which is scalable to work from personal computers to workstations. The effective thermal conductivity, elasticity, and permeability are evaluated employing a computational homogenization framework based on the Finite Element Method (FEM). Two complementary open-source packages are presented: one developed in Python, which can convert digital images into voxel meshes (pyTomoviewer); the other developed in Julia, that can run numerical simulations to compute effective material properties (chpack). Also, a CUDA C version of chpack is provided (chfem_gpu). They were designed to deal with large multi-phase models, so strategies were devised to minimize their memory footprint, while avoiding a high toll on execution time. The voxel-based approach significantly simplifies the FEM meshes and allows efficient matrix-free implementations. In that sense, to handle large linear systems of equations, the element-by-element (EBE) technique is adopted, in conjunction with a low-memory implementation of the Preconditioned Conjugate Gradient (PCG) method. Finally, the code was thoroughly tested on an artificial geometry made of a square array of cylinders, for which analytical solutions exist, as well as on a real micro-tomographic reconstruction of FiberForm TM , a carbon preform commonly used in thermal protection systems.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Carbon–Nutrient Economy of the Rhizosphere: Improving Biogeochemical Prediction and Scaling Feedbacks from Ecosystem to Regional Scales

Our project has advanced the science of plant-soil-microbial dynamics across these areas: i) nutrient cycling and plant uptake; ii) root exudation and priming; and, iii) mycorrhizal dynamics. Our project has accomplished 5 main developments: 1) Incorporation of phosphorus cycling into the Fixation & Uptake of Nutrients (FUN 3.0) model. 2) Coupling of FUN 3.0 into the E3SM Land Model (ELM). 3) Data collection across a large mycorrhizal gradient in the US, as well data in the tropics, to parameterize, test, and validate the model. 4)Scaling up mycorrhizal association measurements across landscapes using airborne hyperspectral remote sensing data. 5) Evaluation of global carbon and nutrient cycle impacts in the Community Land Model (CLM5.0) from a suite of new global mycorrhizal association maps. Over 25 publications resulted from this project, with more continuing past the project funded lifetime. Paper highlights from most of these publications have already been submitted to the DOE paper submission online system. These publications include journals such as Science and PNAS, as well as top disciplinary journals from the Nature journals, Global Change Biology, New Phytologist, and Ecology Letters, for example. Our project also contributed to improving the process representation, capabilities, and accuracy of the DOE ELM. Overall, this project significantly advanced the science of belowground plant-soil-microbial interactions as well as technical capabilities from remote sensing to modeling.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1984

Region one Birkeland currents connecting to sunward convecting flux tubes

On the basis of Birkeland current observations, analytic stability arguments demonstrate that there may be a sector within the plasma sheet in the night side magnetosphere where plasma pressures are reduced relative to the surrounding regions. Physical arguments, in addition to this analysis, imply that a depleted region near the center of the magnetotail would be stable against the interchange instability, thereby generating currents of the same sense as the region-1 currents. The depleted region is presently simulated by means of computer experiments based on the Rice Convection Model. Results indicate that flux tube content gradients across the tailward boundary can cause region-1 currents to flow along sunward-convecting flux tubes, in general agreement with satellite data.

Karty, J. L.↗
NASA NTRS1992

Image masking using polygon fills and morphological transformations

Polygon-fill operations and morphological transformations are effective computational tools for the land-masking and coastline-correction preprocessing operations often applied to AVHRR data prior to oceanographic applications. These masking operations, in conjunction with cloud-screening techniques, can be used on such other oceanographically significant remote-sensing data as those of the Coastal Zone Color Scanner, GOES, and Landsat. The sensitivity of the methods to regional variations in atmospheric conditions and land-ocean temperature gradients is assessed for tropical, midlatitude, and high latitude regions.

Simpson, James J.↗
NASA NTRS1993

Parallel Consensual Neural Networks

A new neural network architecture is proposed and applied in classification of remote sensing/geographic data from multiple sources. The new architecture is called the parallel consensual neural network and its relation to hierarchical and ensemble neural networks is discussed. The parallel consensual neural network architecture is based on statistical consensus theory. The input data are transformed several times and the different transformed data are applied as if they were independent inputs and are classified using stage neural networks. Finally, the outputs from the stage networks are then weighted and combined to make a decision. Experimental results based on remote sensing data and geographic data are given. The performance of the consensual neural network architecture is compared to that of a two-layer (one hidden layer) conjugate-gradient backpropagation neural network. The results with the proposed neural network architecture compare favorably in terms of classification accuracy to the backpropagation method.

Benediktsson, J. A.↗
NASA NTRS2021

An Operational Overview of the EXport Processes in the Ocean from RemoTe Sensing (EXPORTS) Northeast Pacific Field Deployment

The goal of the EXport Processes in the Ocean from RemoTe Sensing (EXPORTS) field campaign is to develop a predictive understanding of the export, fate, and carbon cycle impacts of global ocean net primary production. To accomplish this goal, observations of export flux pathways, plankton community composition, food web processes, and optical, physical, and biogeochemical (BGC) properties are needed over a range of ecosystem states. Here we introduce the first EXPORTS field deployment to Ocean Station Papa in the Northeast Pacific Ocean during summer of 2018, providing context for other papers in this special collection. The experiment was conducted with two ships: a Process Ship, focused on ecological rates, BGC fluxes, temporal changes in food web, and BGC and optical properties, that followed an instrumented Lagrangian float; and a Survey Ship that sampled BGC and optical properties in spatial patterns around the Process Ship. An array of autonomous underwater assets provided measurements over a range of spatial and temporal scales, and partnering programs and remote sensing observations provided additional observational context. The oceanographic setting was typical of late-summer conditions at Ocean Station Papa: a shallow mixed layer, strong vertical and weak horizontal gradients in hydrographic properties, sluggish sub-inertial currents, elevated macronutrient concentrations and low phytoplankton abundances. Although nutrient concentrations were consistent with previous observations, mixed layer chlorophyll was lower than typically observed, resulting in a deeper euphotic zone. Analyses of surface layer temperature and salinity found three distinct surface water types, allowing for diagnosis of whether observed changes were spatial or temporal.The 2018 EXPORTS field deployment is among the most comprehensive biological pump studies ever conducted. A second deployment to the North Atlantic Ocean occurred in spring 2021, which will be followed by focused work on data synthesis and modeling using the entire EXPORTS data set.

Biological pump↗
NASA NTRSDate not supplied

Towards a Third-Order Accurate, Second-Derivative-Free, Shock-Capturing Finite-Volume Method for Hypersonic Flows on Tetrahedral Grids

In this paper, we report progress in the development of a third-order accurate, second-derivative-free, shock-capturing finite-volume solver for three-dimensional unstructured grids. The method is economical in the sense that the computation and storage of second derivatives are not required for third-order accuracy. It is based on point-valued numerical solutions stored at cells, gradients computed and stored at nodes, and an efficient projected-derivative formula that eliminates the need for second derivatives in a quadratic solution interpolation. The projected-derivative formula is also used to eliminate second derivatives from a high-order flux quadrature formula, so that it can be implemented conveniently in the form of a numerical flux at a face center plus a correction term. Similarly, a high-order source quadrature formula can also be implemented in the form of a cell-center point evaluation plus a similar correction term. These features make it relatively straightforward to extend an existing second-order finite-volume code to third-order. This paper reports progress of implementing the method in the NASA VULCAN-CFD code and discusses the implementation of a high-order accurate limiter for shock capturing.

Weighted Least-Squares↗
NASA NTRS2023

Magnetosonic ULF Waves With Anomalous Plasma–Magnetic Field Correlations: Standing Waves and Inhomogeneous Plasmas

Ultra-low frequency (ULF) wave observations across the heliosphere often rely on the sign of correlations between plasma (density/pressure) and magnetic field perturbations to distinguish between fast and slow magnetosonic modes. However, the assumptions behind this magnetohydrodynamic result are not always valid, particularly within the magnetosphere which is inhomogeneous and supports standing waves along the geomagnetic field. Through theory and a global simulation, we find both effects can result in anomalous plasma–magnetic field correlations. The interference pattern in standing waves can lead both body and surface magnetosonic waves to have different cross-phases than their constituent propagating waves. Furthermore, if the scale of gradients in the background are shorter than the wavelength or the waves are near-incompressible, then advection by the wave of inhomogeneities can overcome the wave's inherent sense of compression. These effects need to be allowed for and taken into account when applying the typical diagnostic to observations.

MHD Waves↗
NASA NTRS1993

Analyzing Martian winds and tracer concentrations using Mars Observer data

During the courses of a day, the Mars Observer spacecraft will acquire globally distributed profiles of the martian atmosphere. It is highly desirable that this data be assembled into synoptic weather maps (complete specifications of the atmospheric pressure, temperature, and winds at a given time), which can in turn be used as starting points in the study of many meteorological phenomena. Unfortunately, the special nature of the Mars Observer data presents several challenges above and beyond the usual difficult problem of data initialization. Mars Observer atmospheric data will consist almost exclusively of asynoptic vertical profiles of temperatures (or radiances) and pressures, whereas winds are generally in balance with horizontal gradients of these quantities (which will not be observed). It will therefore be necessary to resort to dynamical models to analyze the wind fields. As a rule, data assimilation into atmospheric models can result in the generation of spurious gravity waves, so special steps must be taken to suppress these. In addition, the asynoptic nature of the data will require a four-dimensional (space and time) data assimilation scheme. The problem is to find a full set of meteorological fields (winds and temperatures) such that, when marched forward in time in the model, they achieve a best fit (in the weighted least-squares sense) to the data. The proposed solution is to develop a model especially for the Mars Observer data assimilation problem. Gravity waves are filtered from the model by eliminating all divergence terms from the prognostic divergence equation. This leaves a diagnostic gradient wind relation between the rotational wind and the temperature field. The divergent wind is diagnosed as the wind required to maintain the gradient wind balance in the presence of the diabatic heating. The primitive equations of atmospheric dynamics (with three principal dependent variables) are thus reduced to a simpler system with a single prognostic equation for temperature - the variable that will be best observed. (This balance system was apparently first derived by Charney as a first-order Rossby number expansion of the equations of motion). Experience with a full primitive equation model of the martian atmosphere indicates that a further simplification is possible: at least for short-term integrations, the model can be linearized about the zonally symmetric basic state.

Houben, Howard C.↗
NASA NTRS1998

Rapid subsidence over oil fields measured by SAR

The Lost Hills and Belridge oil felds are in the San Joaquin Valley, California. The major oil reservoir is high porosity and low permeability diatomite. Extraction of large volumes from shallow depths causes reduction in pore pressure and subsequent compaction, forming a surface subsidence bowl. We measure this subsidence from space using interferometric analysis of SAR (Synthetic Aperture Radar) data collected by the European Space Agency Remote Sensing Satellites (ERS-1 and ERS-2). Maximum subsidence rates are as high as 40 mm in 35 days or > 400 mm/yr, measured from interferograms with time separations ranging from one day to 26 months. The 8- and 26-month interferograms contain areas where the subsidence gradient exceeds the measurement possible with ERS SAR, but shows increased detail in areas of less rapid subsidence. Synoptic mapping of subsidence distribution from satellite data powerfully complements ground-based techniques, permits measurements where access is difficult, and aids identification of underlying causes.

synthetic aperture radar remote sensing oil fields↗
NASA NTRS1993

Observation of pressure ridges in SAR images of sea ice: Scattering theory and comparison with observations

Ridges and keels (hummocks and bummocks) in sea ice flows are important in sea ice research for both scientific and practical reasons. Sea ice movement and deformation is driven by internal and external stresses on the ice. Ridges and keels play important roles in both cases because they determine the external wind and current stresses via drag coefficients. For example, the drag coefficient over sea ice can vary by a factor of several depending on the fluid mechanical roughness length of the surface. This roughness length is thought to be strongly dependent on the ridge structures present. Thus, variations in ridge and keel structure can cause gradients in external stresses which must be balanced by internal stresses and possibly fracture of the ice. Ridging in sea ice is also a sign of fracture. In a practical sense, large ridges form the biggest impediment to surface travel over the ice or penetration through sea ice by ice-strengthened ships. Ridges also play an important role in the damage caused by sea ice to off-shore structures. Hence, observation and measurement of sea ice ridges is an important component of sea ice remote sensing. The research reported here builds on previous work, estimating the characteristics of ridges and leads in sea ice from SAR images. Our objective is to develop methods for quantitative measurement of sea ice ridges from SAR images. To make further progress, in particular, to estimate ridge height, a scattering model for ridges is needed. Our research approach for a ridge scattering model begins with a survey of the geometrical properties of ridges and a comparison with the characteristics of the surrounding ice. For this purpose we have used airborne optical laser (AOL) data collected during the 1987 Greenland Sea Experiment. These data were used to generate a spatial wavenumber spectrum for height variance for a typical ridge - the typical ridge is the average over 10 large ridges. Our first-order model radar scattering includes both the quasi-specular and Bragg resonant scatter mechanisms. This model is extended to include contributions from volume scatter and scatter from discrete objects. Geometrical characteristics from the AOL survey and model calculations imply that for radar wavelengths and observation geometries that are dominated by the quasi-specular scattering mechanism radar backscatter from a ridge is a measure of peak ridge height. We present scattering model results and compare them with ridges observed during the LEADEX experiment of March-April 1992 when both X, C, and L-band aircraft SAR and the ERS-1 satellite SAR observed a region in the Beaufort Sea near 86 deg N, 10 deg W. Data were also collected documenting ridge characteristics on the surface. The surface data are used to generate a SAR signature via the scattering model described above. The predicted SAR signatures compare well with the SAR observations.

Vesecky, J. F.↗