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At least 703 records · Page 39

Regional mapping of forest canopy water content and biomass using AIRSAR images over BOREAS study area

In recent years, monitoring vegetation biomass over various climate zones has become the primary focus of several studies interested in assessing the role of the ecosystem responses to climate change and human activities. Airborne and spaceborne Synthetic Aperture Radar (SAR) systems provide a useful tool to directly estimate biomass due to its sensitivity to structural and moisture characteristics of vegetation canopies. Even though the sensitivity of SAR data to total aboveground biomass has been successfully demonstrated in many controlled experiments over boreal forests and forest plantations, so far, no biomass estimation algorithm has been developed. This is mainly due to the fact that the SAR data, even at lowest frequency (P-band) saturates at biomass levels of about 200 tons/ha, and the structure and moisture information in the SAR signal forces the estimation algorithm to be forest type dependent. In this paper, we discuss the development of a hybrid forest biomass algorithm which uses a SAR derived land cover map in conjunction with a forest backscatter model and an inversion algorithm to estimate forest canopy water content. It is shown that unlike the direct biomass estimation from SAR data, the estimation of water content does not depend on the seasonal and/or environmental conditions. The total aboveground biomass can then be derived from canopy water content for each type of forest by incorporating other ecological information. Preliminary results from this technique over several boreal forest stands indicate that (1) the forest biomass can be estimated with reasonable accuracy, and (2) the saturation level of the SAR signal can be enhanced by separating the crown and trunk biomass in the inversion algorithm. We have used the JPL AIRSAR data over BOREAS southern study area to test the algorithm and to generate regional scale water content and biomass maps. The results are compared with ground data and the sources of errors are discussed. Several SAR images in synoptic modes are used to generate the parameter maps. The maps are then combined to generate mosaic maps over the BOREAS modeling grid.

Saatchi, Sasan↗

Improved geophysical monitoring of carbon sequestration through parameter linkage to reservoir modeling

Predictive reservoir modeling, even if present in the form of only basic hydrogeological model assumptions, is expected to accompany the majority of carbon capture and sequestration monitoring activities. It thus represents a source of prior information about the migration of injected fluids that can benefit geophysical survey planning and ensuing monitoring. Constraining the imaging of geophysical monitoring data with reservoir modeling is preferable over standalone geophysical imaging because of additional complementary hydrogeological information. However, fully coupled hydrogeophysical data inversion for flow-modeling parameters that control saturation predictions is an involved process. Within the context of three-dimensional electromagnetic (EM) inversion of data from borehole-to-surface layouts, we employ a "poor people's" alternative. The approach constrains geophysical inversion parameters through saturation predictions. The coupling is realized through spatially variable lower and upper parameter bounds that scale with gas saturation magnitudes, the latter provided by reservoir modeling. In this work, enhancement of three-dimensional time-lapse plume EM imaging is demonstrated for simulated sequestration into a depleted gas reservoir.

58 GEOSCIENCES↗

Joint inversion of shear wave travel time residuals and geoid and depth anomalies for long-wavelength variations in upper mantle temperature and composition along the Mid-Atlantic Ridge

Measurements were carried out for SS-S differential travel time residuals for nearly 500 paths crossing the northern Mid-Atlantic Ridge, assuming that the residuals are dominated by contributions from the upper mantle near the surface bounce point of the reflected phase SS. Results indicate that the SS-S travel time residuals decrease linearly with square root of age, to an age of 80-100 Ma, in general agreement with the plate cooling model. A joint inversion was formulated of travel time residuals and geoid and bathymetric anomalies for lateral variation in the upper mantle temperature and composition. The preferred inversion solutions were found to have variations in upper mantle temperature along the Mid-Atlantic Ridge of about 100 K. It was calculated that, for a constant bulk composition, such a temperature variation would produce about a 7-km variation in crustal thickness, larger than is generally observed.

Sheehan, Anne F.↗

The expected high-energy to ultra-high-energy gamma-ray spectrum of the Crab Nebula

The inverse Compton scattering model for the unpulsed TeV emission from the Crab Nebula is reexamined using the magnetic field distribution derived from MHD flow models of the nebula. It is shown that the observed flux can be explained if the average nebular field is indeed about 0.0003, as is predicted by the spectral break between radio and optical. The brightness distribution of the TeV gamma-ray signal is expected to extend out to about 1.5 arcmin from the pulsar. The present estimates predict a steady flux of unpulsed ultrahigh-energy gamma-rays due to the inverse Compton scattering of soft photons by shock-accelerated electrons and/or positrons in the vicinity of the shock.

De Jager, O. C.↗

Constraints on simulated past Arctic amplification and lapse rate feedback from observations

The Arctic has warmed more rapidly than the global mean during the past few decades. The lapse rate feedback (LRF) has been identified as being a large contributor to the Arctic amplification (AA) of climate change. This particular feedback arises from the vertically non-uniform warming of the troposphere, which in the Arctic emerges as strong near-surface and muted free-tropospheric warming. Stable stratification and meridional energy transport are two characteristic processes that are evoked as causes for this vertical warming structure. Our aim is to constrain these governing processes by making use of detailed observations in combination with the large climate model ensemble of the sixth Coupled Model Intercomparison Project (CMIP6). We build on the result that CMIP6 models show a large spread in AA and Arctic LRF, which are positively correlated for the historical period of 1951–2014. Thus, we present process-oriented constraints by linking characteristics of the current climate to historical climate simulations. In particular, we compare a large consortium of present-day observations to co-located model data from subsets that show a weak and strong simulated AA and Arctic LRF in the past. Our analyses suggest that the vertical temperature structure of the Arctic boundary layer is more realistically depicted in climate models with weak (w) AA and Arctic LRF (CMIP6/w) in the past. In particular, CMIP6/w models show stronger inversions in the present climate for boreal autumn and winter and over sea ice, which is more consistent with the observations. These results are based on observations from the year-long Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in the central Arctic, long-term measurements at the Utqiagvik site in Alaska, USA, and dropsonde temperature profiling from aircraft campaigns in the Fram Strait. In addition, the atmospheric energy transport from lower latitudes that can further mediate the warming structure in the free troposphere is more realistically represented by CMIP6/w models. In particular, CMIP6/w models systemically simulate a weaker Arctic atmospheric energy transport convergence in the present climate for boreal autumn and winter, which is more consistent with fifth generation reanalysis of the European Centre for Medium-Range Weather Forecasts (ERA5). We further show a positive relationship between the magnitude of the present-day transport convergence and the strength of past AA. With respect to the Arctic LRF, we find links between the changes in transport pathways that drive vertical warming structures and local differences in the LRF. This highlights the mediating influence of advection on the Arctic LRF and motivates deeper studies to explicitly link spatial patterns of Arctic feedbacks to changes in the large-scale circulation.

54 ENVIRONMENTAL SCIENCES↗

Multiwavelength Observations of 2HWC J1928+177: Dark Accelerator or New TeV Gamma-Ray Binary?

2HWC J1928+177 is a Galactic TeV gamma-ray source detected by the High Altitude Water Cherenkov (HAWC) Observatory up to ~56 TeV. The HAWC source, later confirmed by the High Energy Stereoscopic System, still remains unidentified as a dark accelerator since there is no apparent supernova remnant or pulsar wind nebula detected in the lower-energy bands. The radio pulsar PSR J1928+1746, coinciding with the HAWC source position, has no X-ray counterpart. In this work, our SED modeling shows that inverse Compton scattering in the putative pulsar wind nebula can account for the TeV emission only if the unseen nebula is extended beyond $r\sim 4^{\prime} $. Alternatively, TeV gamma-rays may be produced by hadronic interactions between relativistic protons from an undetected supernova remnant associated with the radio pulsar and a nearby molecular cloud G52.9+0.1. NuSTAR and Chandra observations detected a variable X-ray point source within the HAWC error circle, potentially associated with a bright infrared (IR) source. The X-ray spectra can be fitted with an absorbed power-law model with N H = (9 ± 3) × 10 22 cm –2 and Γ X = 1.6 ± 0.3 and exhibit long-term X-ray flux variability over the last decade. If the X-ray source, possibly associated with the IR source (likely an O star), is the counterpart of the HAWC source, it may be a new TeV gamma-ray binary powered by collisions between the pulsar wind and stellar wind. Follow-up X-ray observations are warranted to search for diffuse X-ray emission and determine the nature of the HAWC source.

79 ASTRONOMY AND ASTROPHYSICS↗

Far infrared remote sounding of stratospheric temperature and trace gas distributions

An evaluation is made of the potential usefulness of far-IR thermal emission measurements for simultaneous retrieval of temperature and constituent distributions. Attention is given to the design and performance of a high resolution Michelson interferometer which is currently used in balloon-borne far-IR stratospheric studies. Numerical results based on synthetic limb radiance data for model atmospheres are presented. Formal inversion techniques, together with a radiative transfer model that is based on line-by-line transmittance calculations, are used. Numerical results based on synthetic limb radiance data are given in order to assess the retrieval accuracies of the temperature profiles and the vertical mixing ratio profiles of O3, HCl, and OH.

Abbas, M. M.↗

Controlling topology through targeted composite symmetry manipulation in magnetic systems

The possibility of selecting magnetic space groups by orienting the magnetization direction or tuning magnetic orders offers a vast playground for engineering symmetry-protected topological phases in magnetic materials. In this work, we study how selective tuning of symmetry and magnetism can influence and control the resulting topology in a two-dimensional magnetic system, and we illustrate such a procedure in the ferromagnetic monolayer MnPSe 3 . Density functional theory calculations reveal a symmetry-protected accidental semimetallic (SM) phase for out-of-plane magnetization, which becomes an insulator when the magnetization is tilted in-plane, reaching band-gap values close to 100 meV. We identify an order-2 composite antiunitary symmetry and threefold rotational symmetry that induce the band crossing, and we classify the possible topological phases using symmetry analysis, which we support with tight-binding and k · p models. Breaking of inversion symmetry opens a gap in the SM phase, giving rise to a Chern insulator. We demonstrate this explicitly in the isostructural Janus compound Mn 2 ⁢P 2 ⁢S 3 ⁢Se 3 , which naturally exhibits Rashba spin-orbit coupling that breaks inversion symmetry. Our results map out the phase space of topological properties of ferromagnetic transition-metal phosphorus trichalcogenides, and they demonstrate the potential of the magnetization-dependent metal-to-insulator transition as a spin switch in integrated two-dimensional electronics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Airborne hyperspectral imaging of cover crops through radiative transfer process-guided machine learning

Cover cropping between cash crop growing seasons is a multifunctional conservation practice. Timely and accurate monitoring of cover crop traits, notably aboveground biomass and nutrient content, is beneficial to agricultural stakeholders to improve management and understand outcomes. Currently, there is a scarcity of spatially and temporally resolved information for assessing cover crop growth. Remote sensing has a high potential to fill this need, but conventional empirical regression operated with coarse-resolution multispectral data has large uncertainties. Therefore, this study utilized airborne hyperspectral imaging techniques and developed new process-guided machine learning approaches (PGML) for cover crop monitoring. Specifically, we deployed an airborne hyperspectral system covering visible to shortwave-infrared wavelengths (400–2400 nm) to acquire high spatial (0.5 m) and spectral (3–5 nm) resolution reflectance over 23 cover crop fields across Central Illinois in March and April of 2021. Airborne hyperspectral surface reflectance with high spectral and spatial resolution can be well matched with field data to quantify cover crop traits. Furthermore, the PGML models were pre-trained by synthetic data from soil-vegetation radiative transfer modeling (one million records), and then fine-tuned with field data of cover crop biomass and nutrient content. Results show that airborne hyperspectral data with PGML can achieve high accuracy to predict cover crop aboveground biomass (R 2 = 0.72, relative RMSE = 15.16%) and nitrogen content (R 2 = 0.69, relative RMSE = 16.59%) through leave-one-field-out cross-validation. Unlike the pure data-driven approach (e.g., partial least-squares regression), PGML incorporated radiative transfer knowledge and obtained higher predictive performance with fewer field data. Meanwhile, with field data for model fine-tuning, PGML predicted biomass more accurately than the inversion of radiative transfer models. Here we also found that the red edge has a high contribution in quantifying aboveground biomass and nitrogen content, followed by green and shortwave spectra. This study demonstrated the first attempt of utilizing hyperspectral remote sensing to accurately quantify cover crop traits. We highlight the strength of PGML in exploiting sensing data to quantify ecosystem variables to advance agroecosystem monitoring for sustainable agricultural management.

60 APPLIED LIFE SCIENCES↗

Evaluating the design of an Earth Radiation Budget Instrument with systen simulations. Part 1: Instantaneous estimates

A set of system simulations has been performed to evaluate candidate scanner designs for an Earth Radiation Budget Instrument (ERBI) for the Earth Observing System (EOS) of the late 1990s. Five different instruments are considered: (1) the Active Cavity Array (ACA), (2) the Clouds and Earth's Radiant Energy System-Instrument (CERES-I), (3) the Conically Scanning Radiometer (CSR), (4) the Earth Radiation Budget Experiment Cross-Track Scanner (ERBE), and (5) the Nimbus-7 Biaxial Scanner (N7). Errors in instantaneous, top-of-the-atmosphere (TOA) satellite flux estimates are assumed to arise from two measurement problems: the sampling of space over a given geographic domain, and sampling in angle about a given spatial location. When angular sampling errors vanish due to the application of correct angular dependence models (ADMs) during inversion, the accuracy of each scanner design is determined by the instrument's ability to map the TOA radiance field in a uniform manner. In this regard, the instruments containing a cross-track scanning component (CERES-I and ERBE) do best. As errors in ADMs are encountered, cross-track instruments incur angular sampling errors more rapidly than biaxial instruments (N7, ACA, and CSR) and eventually overtake the biaxial designs in their total error amounts. A latitude bias (north-south error gradient) in the ADM error of cross-track instruments also exists. This would be objectionable when ADM errors are systematic over large areas of the globe. For instantaneous errors, however, cross-track scanners outperform biaxial or conical scanners for 2.5 deg latitude x 2.5 deg longitude target areas, providing that the ADM error is less than or equal to 30%. A key issue is the amount of systematic ADM error (departures from the mean models) that is present at the 2.5 deg resolution of the ERBE target areas. If this error is less than 30%, then the CERES-I, ERBE, and CSR, in order of increasing error, provide the most accurate instantaneous flux estimates, within 2-3 W/sq m of each other in reflected shortwave flux. The magnitude of this error is near the 10 W/sq m accuracy requirement of the user community. Longwave flux errors have been found to have the same space and time characteristics as errors in shortwave radiation, but only about 25% as large.

Stowe, Larry↗

Invertible Neural Networks for Airfoil Design

We report the airfoil design problem, in which an engineer seeks a shape with desired performance characteristics, is fundamental to aerodynamics. Design workflows traditionally rely on iterative optimization methods using low-fidelity integral boundary-layer methods as higher-fidelity adjoint-based computational fluid dynamics methods are computationally expensive. Surrogate-based approaches can accelerate the design process but still rely on some iterative inverse design procedure. In this work, we leverage emerging invertible neural network (INN) tools to enable the rapid inverse design of airfoil shapes for wind turbines. INNs are specialized deep-learning models with well-defined inverse mappings. When trained appropriately, INN surrogate models are capable of forward prediction of aerodynamic and structural quantities for a given airfoil shape as well as inverse recovery of airfoil shapes with specified aerodynamic and structural characteristics. The INN approach offers a roughly 100 times speed-up compared to adjoint-based methods for inverse design. We demonstrate the INN tool for inverse design on three test cases of 100 airfoils each that satisfy the performance characteristics close to those of airfoils used in wind-turbine blades. All generated shapes satisfy the desired aerodynamic characteristics, demonstrating the success of the INN approach for inverse design of airfoils.

17 WIND ENERGY↗

Model Calibration for Cancer Risk Projections According to Uncertain Data

This paper presents forward and inverse formulations for the calibration of computational models according to uncertain data. Uncertainty in the data might be caused by a poor metrology system, measurement noise, missing or uncontrollable input variables, or by the inability to directly measure the inputs and/or outputs of interest. The forward approach performs the calibration in the space of the model’s output thereby requiring repeated model simulations. Conversely, the inverse approach leverages an ensemble of solutions to an inverse problem in order to perform the calibration in the space of the model’s parameters. As such, the computational demands of the inverse approach are considerably lower. These strategies are applied to the calibration of a radiation model that in-forms cancer risk projections for future deep space missions.

uncertainty quantification↗

Approximation methods for the solution of inverse problems in lake and sea sediment core analysis

A theoretical model employing one-dimensional (depth) transport equations to describe vertical redistribution of ocean-floor and lake-floor sediment (particulates, volcanic ash, microtektites, or radioactive tracers) by episodic and nonepisodic events including bioturbation is developed analytically and demonstrated. The principles underlying the model are explained; the model equations are derived; the inverse problem of identifying the depth-dependent bioturbation coefficient is addressed; two approximation theorems are presented; and numerical results for two sample problems are presented graphically. It is suggested that compatification, porosity effects, and depth-dependent sedimentation be taken into account when formulating future models.

Banks, H. T.↗

Drought-induced changes in groundwater-surface water exchange at Lake Mead area

This study focuses on the Lake Mead region in the southwestern United States, a key water reservoir serving over 25 million people and agricultural lands across several states. The area has experienced recurring anthropogenic droughts since the early 2000s. We investigate the hydrological response of the coupled surface-groundwater system to the 2020–2022 drought, one of the most severe on record. To this end, we use Sentinel-1 Interferometric Synthetic Aperture Radar (InSAR) data to quantify vertical land motion caused by the elastic response of the crust to water-mass loss in the lake vicinity. Next, we apply an inverse elastic load modeling framework to quantify water loss. We further assess possible hydraulic connectivity between Lake Mead and adjacent groundwater reservoirs. We detect ground uplift of up to 8 mm/yr near the lake center, likely due to crustal rebound from reduced water-mass loading. We estimated the total water storage loss at 3.03 ± 0.25 km 3 /yr across a 3150 km 2 area surrounding Lake Mead. Groundwater accounts for approximately a third of that, being 0.94 ± 0.32 km 3 /yr. In addition, observed time lags of 6–98 days between lake and groundwater level responses, corresponding to a lateral diffusivity of 3.2–86 m 2 /s, suggest spatially variable connectivity between the lake and aquifers. These findings highlight that drought impacts propagate through the subsurface within interconnected systems, resulting in reduced buffering capacity of groundwater resources following droughts, and emphasizing the need for more integrated surface and groundwater management strategies to enhance resilience under climate and anthropogenic stressors.

58 GEOSCIENCES↗

Microstructural characterization of cold-worked 316 stainless steel flux thimble tubes irradiated up to 100 dpa in a commercial Pressurized Water Reactor

Two flux thimble tubes (FTT) made of 15% cold-worked 316 stainless steel (SS) were harvested from Ringhals Pressurized Water Reactor (PWR) Unit 2, with peak damages of 76 and 100 displacements per atom (dpa) after 29 and 34 years’ service, respectively. Specimens sectioned from parent tubes were comprehensively characterized with nominal damage levels of ~0, ~41, ~74, 76, and 100 dpa at a nominal temperature range of 285-323 °C. Both FTTs contained helium and hydrogen gases as transmutation products. The helium follows a production rate of ~9.8 appm/dpa, while environmental factors complicate hydrogen production obscuring an exact H/dpa ratio. Irradiation-induced dislocation loops, nano-cavities, solute clusters, and microsegregation were all observed. The dislocation loops and nano-cavities indicated saturation at 41 dpa. The solute clusters continued to evolve with Ni-Si clusters formed at 41 dpa, and Ni-Si-Mn-P clusters formed at 74 and 100 dpa, but neither clusters exhibited distinct diffraction patterns at any damage levels. Solute clusters were observed to frequently be co-located with dislocation loops, but fully decorated loops were rarely detected. Significant radiation-induced segregation (RIS) was observed around grain boundaries at all damage levels. The modified inverse Kirkendall (MIK) model captured the RIS behavior of major elements. Large cavities within or around an Mn-S rich region were observed for the first time. Through all the damage levels, void swelling is always below 0.05%, making significant dimensional change unlikely in core internals when used at similar conditions. Meanwhile, the role of overwhelming nanocavities, presumably helium bubbles, should be considered in other potential degradation mechanisms, including irradiation-assisted stress corrosion cracking, embrittlement, and loss of fracture toughness, which remain the concerns for extended operation of nuclear power plants.

Post Irradiation Examination, Isotope Dilution Mas↗

A Spectrochemical Series for Electron Spin Relaxation

Controlling the rate of electron spin relaxation in paramagnetic molecules is essential for contemporary applications in molecular magnetism and quantum information science. However, the physical mechanisms of spin relaxation remain incompletely understood, and new spectroscopic observables play an important role in evaluating spin dynamics mechanisms and structure–property relationships. Here, we use cryogenic magnetic circular dichroism (MCD) spectroscopy and pulse electron paramagnetic resonance (EPR) in tandem to examine the impact of ligand field (d–d) excited states on spin relaxation rates. We employ a broad scope of square-planar Cu(II) compounds with varying ligand field strength, including CuS 4 , CuN 4 , CuN 2 O 2 , and CuO 4 first coordination spheres. An unexpectedly strong correlation exists between spin relaxation rates and the average d–d excitation energy (R 2 = 0.97). The relaxation rate trends as the inverse 11th power of the excited-state energies, whereas simplified theoretical models predict only an inverse second power dependence. These experimental results directly implicate ligand field excited states as playing a critical role in the ground-state spin relaxation mechanism. Furthermore, ligand field strength is revealed to be a particularly powerful design principle for spin dynamics, enabling formation of a spectrochemical series for spin relaxation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Hydraulically‐vulnerable trees survive on deep‐water access during droughts in a tropical forest

Summary Deep‐water access is arguably the most effective, but under‐studied, mechanism that plants employ to survive during drought. Vulnerability to embolism and hydraulic safety margins can predict mortality risk at given levels of dehydration, but deep‐water access may delay plant dehydration. Here, we tested the role of deep‐water access in enabling survival within a diverse tropical forest community in Panama using a novel data‐model approach. We inversely estimated the effective rooting depth (ERD, as the average depth of water extraction), for 29 canopy species by linking diameter growth dynamics (1990–2015) to vapor pressure deficit, water potentials in the whole‐soil column, and leaf hydraulic vulnerability curves. We validated ERD estimates against existing isotopic data of potential water‐access depths. Across species, deeper ERD was associated with higher maximum stem hydraulic conductivity, greater vulnerability to xylem embolism, narrower safety margins, and lower mortality rates during extreme droughts over 35 years (1981–2015) among evergreen species. Species exposure to water stress declined with deeper ERD indicating that trees compensate for water stress‐related mortality risk through deep‐water access. The role of deep‐water access in mitigating mortality of hydraulically‐vulnerable trees has important implications for our predictive understanding of forest dynamics under current and future climates.

54 ENVIRONMENTAL SCIENCES↗

pnnl/MCRASTA

McRasta (Markov Chain Rate and State Analysis) was developed to estimate parameter uncertainty in constitutive friction models via Bayesian inverse and Markov Chain Monte Carlo (MCMC) methods.

Fichera, Marissa [Pacific Northwest National Labor↗