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At least 109 records · Page 6

Thermal remote sensing of surface soil water content with partial vegetation cover for incorporation into climate models

This study outlines a method for the estimation of regional patterns of surface moisture availability (M(sub 0)) and fractional vegetation (Fr) in the presence of spatially variable vegetation cover. The method requires relating variations in satellite-derived (NOAA, Advanced Very High Resolution Radiometer (AVHRR)) surface radiant temperature to a vegetation index (computed from satellite visible and near-infrared data) while coupling this association to an inverse modeling scheme. More than merely furnishing surface soil moisture values, the method constitues a new conceptual and practical approach for combining thermal infrared and vegetation index measurements for incorporating the derived values of M(sub 0) into hydrologic and atmospheric prediction models. Application of the technique is demonstrated for a region in and around the city of Newcastle upon Tyne situated in the northeast of England. A regional estimate of M(sub 0) is derived and is probabbly good for fractional vegetation cover up to 80% before errors in the estimated soil water content become unacceptably large. Moreover, a normalization scheme is suggested from which a nomogram, `universal triangle,' is constructed and is seen to fit the observed data well. The universal triangle also simplifies the inclusion of remotely derived M(sub 0) in hydrology and meteorological models and is perhaps a practicable step toward integrating derived data from satellite measurements in weather forecasting.

Gillies, Robert R.↗

Kinematic properties of double-barred galaxies: simulations versus integral-field observations

Using high-resolution N-body simulations, we recently reported that a dynamically cool inner disk embedded in a hotter outer disk can naturally generate a steady double-barred (S2B) structure. Here we study the kinematics of these S2B simulations, and compare them to integral-field observations from ATLAS {sup 3D} and SAURON. We show that S2B galaxies exhibit several distinct kinematic features, namely: (1) significantly distorted isovelocity contours at the transition region between the two bars, (2) peaks in σ {sub LOS} along the minor axis of inner bars, which we term “σ-humps,” that are often accompanied by ring/spiral-like features of increased σ {sub LOS}, (3) h{sub 3}-- v-bar anti-correlations in the region of the inner bar for certain orientations, and (4) rings of positive h {sub 4} when viewed at low inclinations. The most impressive of these features are the σ-humps; these evolve with the inner bar, oscillating in strength just as the inner bar does as it rotates relative to the outer bar. We show that, in cylindrical coordinates, the inner bar has similar streaming motions and velocity dispersion properties as normal large-scale bars, except for σ {sub z}, which exhibits peaks on the minor axis, i.e., humps. These σ {sub z} humps are responsible for producing the σ-humps. For three well-resolved early-type S2Bs (NGC 2859, NGC 2950, and NGC 3941) and a potential S2B candidate (NGC 3384), the S2B model qualitatively matches the integral-field data well, including the “σ-hollows” previously identified. We also discuss the kinematic effect of a nuclear disk in S2Bs.

79 ASTRONOMY AND ASTROPHYSICS↗

Carbon isotope geochemistry of hydrocarbons in the Cerro Prieto geothermal field, Baja California Norte, Mexico

Hydrocarbon abundances and stable-isotopic compositions were measured in wells M5, M26, M35 and M102, which represent a range of depths (1270-2000 m) and temperatures (275-330 degrees C) in the field. In order to simulate the production of the geothermal hydrocarbons, gases were collected from the pyrolysis of lignite in the laboratory. This lignite was obtained from a well which sampled rock strata which are identical to those occurring in the field, but which have experienced much lower subsurface temperatures. In both the well and the laboratory observations, high-temperature environments favored higher relative concentrations of methane, ethane and benzene and generally higher delta 13C-values in the individual hydrocarbons. The best correlation between the laboratory and well data is obtained when laboratory-produced gases from experiments conducted at lower (400 degrees C) and higher (600 degrees C) temperatures are mixed. This improved correlation suggests that the wells are sampling hydrocarbons produced from a spectrum of depths and temperatures in the sediments.

NASA Center ARC↗

Jurassic deserts and CO2 sequestration: the Glen Canyon Group in Utah, western USA

The Early Jurassic in the Western Interior of USA consisted of an extensive desert environment, including one of the largest ergs in geologic history. The Navajo erg has been estimated to extend as much as 2.2 million square kilometers, though the preserved extent is somewhat smaller. The Mesozoic was a global greenhouse phase, and during the Jurassic this region experienced fluctuations in climate aridity, reflected in the depositional environment. In addition to extensive dunefields, interdune deposits (lakes and oases) and fluvial systems are also documented within formations of the Glen Canyon Group. The Navajo Sandstone has received much attention as a potential CO2 injection target in recent years. It consists of thick, aeolian sandstones with high porosity and permeability, occurs in both outcrop and subcrop, and has industry data. Mapping of stratigraphic and sedimentologic changes within the Navajo Sandstone has been undertaken in localized areas, however piecing together these studies and developing regional models for CO2 potential has not received as much attention. There is significant industry data across Utah, and utilizing this data to pivot from a focus on hydrocarbon extraction to CO2 injection is an effective way to move forward with green energy, and to meet carbon neutral emission goals. Using legacy well data, we are developing a more comprehensive study of the Navajo Sandstone as a potential CO2 reservoir, in addition to identifying other zones of interest within the Glen Canyon Group, and improving understanding of stratigraphic complexity within one of the most significant aeolian systems in the world.

Mahon, Elizabeth↗

Wilson Corners SWMU 001 2015 Annual Long Term Monitoring Report Kennedy Space Center, Florida

This document presents the findings of the 2015 Long Term Monitoring (LTM) that was completed at the Wilson Corners site, located at the National Aeronautics and Space Administration John F. Kennedy Space Center, Florida. The objectives of the 2015 LTM event were to evaluate the groundwater flow direction and gradient, to monitor the vertical and horizontal extent of the volatile organic compounds (VOCs; including the upgradient and sidegradient extents, which are monitored every five years), and to monitor select locations internal to the dissolved groundwater plume. The 2015 LTM event included several upgradient and sidegradient monitoring wells that are not sampled annually to verify the extent of VOCs in this portion of the site. The December 2015 LTM groundwater sampling event included, depth to groundwater measurements, 40 VOC samples collected using passive diffusion bags, and one VOC sample collected using low-flow techniques. Additionally, monitoring well MW0052DD was overdrilled and abandoned using rotasonic drilling techniques. The following conclusions can be made based on the 2015 LTM results: groundwater flow is generally to the west with northwest and southwest flow components from the water table to approximately 55 feet below land surface (ft BLS); peripheral monitoring wells generally delineate VOCs to groundwater cleanup target levels (GCTLs) except for monitoring wells MW0088, MW0090, MW0095, and NPSHMW0039, which had vinyl chloride (VC) concentrations near the GCTL and MW0062, which had trichloroethene (TCE), cis-1,2-dichloroethenen (cDCE), and VC concentrations above natural attenuation default concentrations (NADCs); VOCs in interior downgradient wells generally fluctuate within historic ranges except for monitoring wells in the north-northwest portion of the site, which have increasing VC concentrations indicating potential plume migration and expansion; Historically, the vertical extents of the VOCs were delineated by monitoring wells screened greater than 60 ft BLS (MW0083 through MW0086, and MW0078). The 2015 LTM results indicate that concentrations of daughter product cDCE is greater than the NADC in MW0078 and that cDCE and VC are greater than NADCs in MW0130. TCE was greater than the GCTL in monitoring well MW130 and not detected above method detection limits (9 micrograms per Liter) in monitoring well MW0078. No GCTL exceedances were identified in monitoring wells MW0083 or MW0086; the dissolved plume footprint appears generally stable, though not fully delineated by monitoring well data in the northeast portion of the site; and 2015 LTM results generally support the existing Conceptual Site Model. Geosyntec recommends modifying the LTM program, collecting a verification sample from monitoring well MW0062, and performing a direct push technology instigation in the northnortheastern portion of the site. A cluster of monitoring wells (MW0132 [2 to 12 ft BLS], MW0133 [15 to 25 ft BLS], and MW0134 [29 to 34 ft BLS]) is proposed to delineate impacts in the northnortheast portion of the site. Geosyntec recommends installation of a vertical extent well in the center of the site (Hot Spot 2 area) post-remediation implementation.

groundwater↗

SU-G-TeP1-02: Analytical Stopping Power and Range Parameterization for Therapeutic Energy Intervals

Purpose: To develop a simple, analytic parameterization of stopping power and range, which covers a wide energy interval and is applicable to many species of projectile ions and target materials, with less than 15% disagreement in linear stopping power and 1 mm in range. Methods: The new parameterization was required to be analytically integrable from stopping power to range, and continuous across the range interval of 1 µm to 50 cm. The model parameters were determined from stopping power and range data for hydrogen, carbon, iron, and uranium ions incident on water, carbon, aluminum, lead and copper. Stopping power and range data was taken from SRIM. A stochastic minimization algorithm was used to find model parameters, with 10 data points per energy decade. Additionally, fitting was performed with 2 and 26 data points per energy decade to test the model’s robustness to sparse Results: 6 free parameters were sufficient to cover the therapeutic energy range for each projectile ion species (e.g. 1 keV – 300 MeV for protons). The model agrees with stopping power and range data well, with less than 9% relative stopping power difference and 0.5 mm difference in range. As few as, 4 bins per decade were required to achieve comparable fitting results to the full data set. Conclusion: This study successfully demonstrated that a simple analytic function can be used to fit the entire energy interval of therapeutic ion beams of hydrogen and heavier elements. Advantages of this model were the small number (6) of free parameters, and that the model calculates both stopping power and range. Applications of this model include GPU-based dose calculation algorithms and Monte Carlo simulations, where available memory is limited. This work was supported in part by a research agreement between United States Naval Academy and Louisiana State University: Contract No N00189-13-P-0786. In addition, this work was accepted for presentation at the American Nuclear Society Annual Meeting 2016.

61 RADIATION PROTECTION AND DOSIMETRY↗

PHYSICS OF ECLIPSING BINARIES. II. TOWARD THE INCREASED MODEL FIDELITY

The precision of photometric and spectroscopic observations has been systematically improved in the last decade, mostly thanks to space-borne photometric missions and ground-based spectrographs dedicated to finding exoplanets. The field of eclipsing binary stars strongly benefited from this development. Eclipsing binaries serve as critical tools for determining fundamental stellar properties (masses, radii, temperatures, and luminosities), yet the models are not capable of reproducing observed data well, either because of the missing physics or because of insufficient precision. This led to a predicament where radiative and dynamical effects, insofar buried in noise, started showing up routinely in the data, but were not accounted for in the models. PHOEBE (PHysics Of Eclipsing BinariEs; http://phoebe-project.org) is an open source modeling code for computing theoretical light and radial velocity curves that addresses both problems by incorporating missing physics and by increasing the computational fidelity. In particular, we discuss triangulation as a superior surface discretization algorithm, meshing of rotating single stars, light travel time effects, advanced phase computation, volume conservation in eccentric orbits, and improved computation of local intensity across the stellar surfaces that includes the photon-weighted mode, the enhanced limb darkening treatment, the better reflection treatment, and Doppler boosting. Here we present the concepts on which PHOEBE is built and proofs of concept that demonstrate the increased model fidelity.

79 ASTRONOMY AND ASTROPHYSICS↗

Lost Circulation Materials in Geothermal Drilling: Thermal Degradation, Viscosity, Compression, and Flow Loop Tests

This dataset provides a set of experimental data on the performance of lost circulation materials (LCMs) used in geothermal drilling operations. It includes results from four distinct tests: thermal degradation, viscosity measurements, compression tests, and high-temperature flow loop experiments. The materials tested, such as cedar fiber, cotton seed hulls, magma fiber, microcellulose, and sawdust, were analyzed under a range of conditions to assess their effectiveness in mitigating fluid losses in geothermal wells. Data on thermal degradation explores mass loss, water loss, and gas release for each material when subjected to temperatures between 90C and 250C. Viscosity measurements capture the behavior of LCM mixtures under different temperatures, while compression tests investigate the structural integrity of both undegraded and thermally degraded materials. The high-temperature flow loop experiments simulate geothermal well conditions, analyzing how different materials and mixtures affect fluid flow and sealing performance in a fractured reservoir environment. In addition to the experimental data, the dataset includes photos documenting the materials, schematics of test setups, and several published manuscripts that provide detailed insights into the experimental methods and findings.

15 GEOTHERMAL ENERGY↗

Representation of the Geosynchronous Plasma Environment for Spacecraft Charging Calculations

Historically, our ability to predict and postdict surface charging has suffered from both a lack of reliable secondary emission and backscattered electron yields and poor characterization of the plasma environment. One difficulty lies in the common practice of fitting the plasma data to a Maxwellian or Double Maxwellian distribution function, which may not represent the data well for charging purposes. For 13 years Los Alamos National Laboratory (LANL) has been accumulating measurements of electron and proton spectra from Magnetospheric Plasma Analyzer (MPA) instruments aboard a series of geosynchronous satellites. These data provide both a plasma characterization and the potential of the instrument ground. We use electron and ion flux spectra measured by the LANL MPA to examine how the use of different spectral representations of the charged particle environment in computations of spacecraft potentials during magnetospheric substorms affects the accuracy of the results. We calculate the spacecraft potential using both the measured fluxes and several different fits to these fluxes. These flux measurements and fits have been corrected for the difference between the measured and calculated potential. The potentials computed using the measured fluxes, the best available material properties of graphite carbon, and a secondary electron escape fraction of 81%, are within a factor of three of the measured potential for nearly all the data. Using a Kappa fit to the electron distribution function and a Maxwellian fit to the ion distribution function gives agreement similar to the calculations using the actual data. Alternative spectral representations, including Maxwellian and double Maxwellian for both species, lead to less satisfactory agreement between predicted and measured potentials.

Davis, V. A.↗

Sympathetic restraint of respiratory sinus arrhythmia: implications for vagal-cardiac tone assessment in humans

Clinicians and experimentalists routinely estimate vagal-cardiac nerve traffic from respiratory sinus arrhythmia. However, evidence suggests that sympathetic mechanisms may also modulate respiratory sinus arrhythmia. Our study examined modulation of respiratory sinus arrhythmia by sympathetic outflow. We measured R-R interval spectral power in 10 volunteers that breathed sequentially at 13 frequencies, from 15 to 3 breaths/min, before and after beta-adrenergic blockade. We fitted changes of respiratory frequency R-R interval spectral power with a damped oscillator model: frequency-dependent oscillations with a resonant frequency, generated by driving forces and modified by damping influences. beta-Adrenergic blockade enhanced respiratory sinus arrhythmia at all frequencies (at some, fourfold). The damped oscillator model fit experimental data well (39 of 40 ramps; r = 0.86 +/- 0.02). beta-Adrenergic blockade increased respiratory sinus arrhythmia by amplifying respiration-related driving forces (P < 0.05), without altering resonant frequency or damping influences. Both spectral power data and the damped oscillator model indicate that cardiac sympathetic outflow markedly reduces heart period oscillations at all frequencies. This challenges the notion that respiratory sinus arrhythmia is mediated simply by vagal-cardiac nerve activity. These results have important implications for clinical and experimental estimation of human vagal cardiac tone.

NASA Discipline Cardiopulmonary↗

NuSTAR and XMM-Newton Observations of the Hard X- Ray Spectrum of Centaurus A

We present simultaneous XMM-Newton and Nuclear Spectroscopic Telescope Array (NuSTAR) observations spanning 3-78 keV of the nearest radio galaxy, Centaurus A (Cen A). The accretion geometry around the central engine in Cen A is still debated, and we investigate possible configurations using detailed X-ray spectral modeling. NuSTAR imaged the central region of Cen A with subarcminute resolution at X-ray energies above 10 keV for the first time, but found no evidence for an extended source or other off-nuclear point sources. The XMM-Newton and NuSTAR spectra agree well and can be described with an absorbed power law with a photon index Gamma = 1.8150 +/- 0.005 and a fluorescent Fe Kaline in good agreement with literature values. The spectrum is greater than 1 MeV. A thermal Comptonization continuum describes the data well, with parameters that agree with values measured by INTEGRAL, in particular an electron temperature kTe between approximately 100-300 keV and seed photon input temperatures between 5 and 50 eV. We do not find evidence for reflection or a broad iron line and put stringent upper limits of R is less than 0.01 on the reflection fraction and accretion disk illumination. We use archival Chandra data to estimate the contribution from diffuse emission, extra-nuclear point sources, and the outer X-ray jet to the observed NuSTAR and XMM-Newton X-ray spectra and find the contribution to be negligible. We discuss different scenarios for the physical origin of the observed hard X-ray spectrum and conclude that the inner disk is replaced by an advection-dominated accretion flow or that the X-rays are dominated by synchrotron self-Compton emission from the inner regions of the radio jet or a combination thereof.

Galaxies: active - galaxies: individual (Centaurus↗

Equation of state and spin crossover of (Mg,Fe)O at high pressure, with implications for explaining topographic relief at the core-mantle boundary

Iron-bearing periclase is thought to represent a significant fraction of Earth’s lower mantle. However, the concentration of iron in (Mg,Fe)O is not well constrained at all mantle depths. Therefore, understanding the effect of iron on the density and elastic properties of this phase plays a major role in interpreting seismically observed complexity in the deep Earth. Here in this paper, we examine the high-pressure behavior of polycrystalline (Mg,Fe)O containing 48 mol% FeO, loaded hydrostatically with neon as a pressure medium. Using X-ray diffraction and synchrotron Mössbauer spectroscopy, we measure the equation of state to about 83 GPa and hyperfine parameters to 107 GPa at 300 K. A gradual volume drop corresponding to a high-spin (HS) to low-spin (LS) crossover is observed between ~45 and 83 GPa with a volume drop of 1.85% at 68.8(2.7) GPa, the calculated spin transition pressure. Using a newly formulated spin crossover equation of state, the resulting zero-pressure isothermal bulk modulus K 0T,HS for the HS state is 160(2) GPa with a K' 0T,HS of 4.12(14) and a V 0,HS of 77.29(0) Å 3 . For the LS state, the K 0T,LS is 173(13) GPa with a K' 0T,LS fixed to 4 and a V 0,LS of 73.64(94) Å 3 . To confirm that the observed volume drop is due to a spin crossover, the quadrupole splitting (QS) and isomer shift (IS) are determined as a function of pressure. At low pressures, the Mössbauer spectra are well explained with two Fe 2+ -like sites. At pressure between 44 and 84, two additional Fe 2+ -like sites with a QS of 0 are required, indicative of low-spin iron. Above 84 GPa, two low-spin Fe 2+ -like sites with increasing weight fraction explain the data well, signifying the completion of the spin crossover. To systematically compare the effect of iron on the equation of state parameters for (Mg,Fe)O, a spin crossover equation of state was fitted to the pressure-volume data of previous measurements. Our results show that K 0,HS is insensitive to iron concentration between 10 to 60 mol% FeO, while the spin transition pressure and width generally increases from about 50–80 and 2–25 GPa, respectively. A key implication is that iron-rich (Mg,Fe)O at the core-mantle boundary would likely contain a significant fraction of high-spin (less dense) iron, contributing a positive buoyancy to promote observable topographic relief in tomographic images of the lowermost mantle.

58 GEOSCIENCES↗

Time-lapse VSP integration and calibration of subsurface stress field utilizing machine learning approaches: A case study of the morrow B formation, FWU

This study aims to develop a methodology for calibrating subsurface stress changes through time-lapse vertical seismic profiling (VSP) integration. The selected study site is a region around the injector well located within Farnsworth field unit (FWU), where there is an ongoing CO 2 -enhanced oil recovery (EOR) operation. In our study, a site-specific rock physics model was created from extensive geological, geophysical, and geomechanical characterization through 3D seismic data, well logs, and core assessed as part of the 1D MEM conducted on the characterization well within the study area. Here, the Biot-Gassmann workflow was utilized to combine the rock physics and reservoir simulation outputs to determine the seismic velocity change due to fluid substitution. Modeled seismic velocities attributed to mean effective stress were determined from the geomechanical simulation outputs, and the stress-velocity relationship developed from ultrasonic seismic velocity measurements. A machine learning-assisted workflow comprised of an artificial neural network and a particle swarm optimizer (PSO) was utilized to minimize a penalty function created between the modeled seismic velocities and the observed time-lapse VSP dataset. The successful execution of this workflow has affirmed the suitability of acoustic time-lapse measurements for 4D-VSP geomechanical stress calibration pending measurable stress sensitivities within the anticipated effective stress changes and the availability of suitable and reliable datasets for petroelastic modeling. © 2023 Society of Chemical Industry and John Wiley & Sons, Ltd.

58 GEOSCIENCES↗

Low-Level Jets and the Convergence of Mars Data Assimilation Algorithms

Data assimilation is an increasingly popular technique in Mars atmospheric science, but its effect on the mean states of the underlying atmosphere models has not been thoroughly examined. The robustness of results to the choice of model and assimilation algorithm also warrants further study. We investigate these issues using two Mars general circulation models (MGCMs), with particular emphasis on zonal wind and temperature fields. When temperature retrievals from the Mars Global Surveyor Thermal Emission Spectrometer (TES) are assimilated into the U.K.-Laboratoire de M ́et ́eorologie Dynamique (UK-LMD) MGCM to create the Mars Analysis Correction Data Assimilation (MACDA) reanalysis, low-level zonal jets in the winter northern hemisphere shift equatorward and weaken relative to a free-running control simulation from the same MGCM. The Ensemble Mars Atmosphere Reanalysis System (EMARS) reanalysis, which is also based on TES temperature retrievals, also shows jet weakening (but less if any shifting) relative to a control simulation performed with the underlying Geophysical Fluid Dynamics Laboratory (GFDL) MGCM. Examining higher levels of the atmosphere, monthly mean three-dimensional temperature and zonal wind fields are in generally better agreement between the two reanalyses than between the two control simulations. In conjunction with information about the MGCMs’ physical parametrizations, intercomparisons between the various reanalyses and control simulations suggest that overall the EMARS control run is plausibly less biased (relative to the true state of the Martian atmosphere) than the MACDA control run. Implications for future observational studies are discussed. Plain Language Summary An increasingly popular way to study Martian weather and climate is to combine atmospheric temperature observations with a computer model (specifically, a global climate model). The process of combining model and observations is called “data assimilation”, and the resulting merged data set is called a “reanalysis”. One advantage of reanalyses is that they include variables (such as wind) that are not directly observed. For scientific and practical applications we want these variables to be reasonably accurate— however, it is not clear how well data assimilation algorithms compute them. Our study investigates this issue using two Mars reanalyses and two model simulations that do not assimilate temperature data. We focus on slowly-varying atmospheric phenomena (timescales from 10 Mars days to a season). Assimilating temperature data into two different global climate models changes the strength and/or spatial pattern of east-west winds at low altitudes. Furthermore, monthly mean three-dimensional temperature and east-west wind fields agree better between reanalyses than between non-assimilating model simulations. This suggests that the data assimilation process is basically successful. One non-assimilating model simulation has less realistic representations of atmospheric physical processes than the other—we argue that this plausibly gives it larger biases relative to the true state of the atmosphere.

Todd A Mooring↗

A comparison of model validation approaches for echo state networks using climate model replicates

As global temperatures continue to rise, climate mitigation strategies such as stratospheric aerosol injections (SAI) are increasingly discussed, but the downstream effects of these strategies are not well understood. As such, there is interest in developing statistical methods to quantify the evolution of climate variable relationships during the time period surrounding an SAI. Feature importance applied to echo state network (ESN) models has been proposed as a way to understand the effects of SAI using a data-driven model. This approach depends on the ESN fitting the data well. If not, the feature importance may place importance on features that are not representative of the underlying relationships. Typically, time series prediction models such as ESNs are assessed using out-of-sample performance metrics that divide the times series into separate training and testing sets. However, this model assessment approach is geared towards forecasting applications and not scenarios such as the motivating SAI example where the objective is using a data driven model to capture variable relationships. Here, in this paper, we demonstrate a novel use of climate model replicates to investigate the applicability of the commonly used repeated hold-out model assessment approach for the SAI application. Simulations of an SAI are generated using a simplified climate model, and different initialization conditions are used to provide independent training and testing sets containing the same SAI event. The climate model replicates enable out-of-sample measures of model performance, which are compared to the single time series hold-out validation approach. For our case study, it is found that the repeated hold-out sample performance is comparable, but conservative, to the replicate out-of-sample performance when the training set contains enough time after the aerosol injection.

54 ENVIRONMENTAL SCIENCES↗

InSAR Scientific Computing Environment

This computing environment is the next generation of geodetic image processing technology for repeat-pass Interferometric Synthetic Aperture (InSAR) sensors, identified by the community as a needed capability to provide flexibility and extensibility in reducing measurements from radar satellites and aircraft to new geophysical products. This software allows users of interferometric radar data the flexibility to process from Level 0 to Level 4 products using a variety of algorithms and for a range of available sensors. There are many radar satellites in orbit today delivering to the science community data of unprecedented quantity and quality, making possible large-scale studies in climate research, natural hazards, and the Earth's ecosystem. The proposed DESDynI mission, now under consideration by NASA for launch later in this decade, would provide time series and multiimage measurements that permit 4D models of Earth surface processes so that, for example, climate-induced changes over time would become apparent and quantifiable. This advanced data processing technology, applied to a global data set such as from the proposed DESDynI mission, enables a new class of analyses at time and spatial scales unavailable using current approaches. This software implements an accurate, extensible, and modular processing system designed to realize the full potential of InSAR data from future missions such as the proposed DESDynI, existing radar satellite data, as well as data from the NASA UAVSAR (Uninhabited Aerial Vehicle Synthetic Aperture Radar), and other airborne platforms. The processing approach has been re-thought in order to enable multi-scene analysis by adding new algorithms and data interfaces, to permit user-reconfigurable operation and extensibility, and to capitalize on codes already developed by NASA and the science community. The framework incorporates modern programming methods based on recent research, including object-oriented scripts controlling legacy and new codes, abstraction and generalization of the data model for efficient manipulation of objects among modules, and well-designed module interfaces suitable for command- line execution or GUI-programming. The framework is designed to allow users contributions to promote maximum utility and sophistication of the code, creating an open-source community that could extend the framework into the indefinite future.

Rosen, Paul A.↗

Fallon FORGE: Lithology Logs and Well 21-31 Drilling Data

This submission includes lithology logs for all Fallon FORGE area wells; determined from core, cuttings, and thin section. Wells included are 84-31, 21-31, 82-36, FOH-3D, 62-36, 18-5, 88-24, 86-25, FOH-2, 14-36, 17-16, 34-33, 35A-11, 51A-20, 62-15, 72-7, 86-15, Carson_Strat_1_36-32, and several others. Lithology logs last updated 3/13/2018 with confirmation well 21-31 data, and revisited existing wells. Also included is well logging data for Fallon FORGE 21-31. Well logging data includes daily reports, well logs (drill rate, lithology, fractures, mud losses, minerals, temperature, gases, and descriptions), mud reports, drilling parameter plots, daily mud loss summaries, survey reports, progress reports, plan view maps (easting, northing), and wireline logs (caliper [with GR], triple combo [GR, caliper, SP, resistivity, array induction, density, photoelectric factor, and neutron porosity], array induction with linear correlation [GR, SP, Array Induction, caliper, conductivity], and monopole compression dipole shear [GR, SP, Caliper, sonic porosity, delta-T compressional, and delta-T shear])

15 GEOTHERMAL ENERGY↗

Adjoint-Based Inversion of Geodetic Data for Sources of Deformation and Strain

An adjoint-based formulation leads to a particularly efficient approach for inverting geodetic measurements for the source of the deformation. Specifically, the quantities necessary to iteratively improve the fit to the observations can be computed with just three forward calculations, one to obtain the current residuals, another to solve the adjoint problem, and a third to compute the step length. An inversion algorithm utilizing the adjoint-based gradient is applied to a set of Interferometric Synthetic Aperture Radar (InSAR) data gathered between 2016 and 2018 over the Tulare Basin in California's Central Valley. Because the measured deformation is due to groundwater withdrawal, a penalty function is included in the inversion to avoid placing aquifer volume change in locations that are far from any documented wells. The solution of the inverse problem provides estimates of aquifer compaction that provide a match to the observed range changes while honoring the well data. The solution indicates an average aquifer volume loss of 2.17 km 3 /year over the two year period from January 2016 to January 2018, encompassing one drought year (2016) and one wet year (2017). Finally, this magnitude of lost volume is compatible with the 3.1 km 3 /year decrease in water volume for the entire Central Valley, estimated from GRACE satellite gravity data.

58 GEOSCIENCES↗