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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Fluid-Dynamic Mechanisms Underlying Wind Turbine Wake Control with Strouhal-Timed Actuation

A reduction in wake effects in large wind farms through wake-aware control has considerable potential to improve farm efficiency. This work examines the success of several emerging, empirically derived control methods that modify wind turbine wakes (i.e., the pulse method, helix method, and related methods) based on Strouhal numbers on the O(0.3). Drawing on previous work in the literature for jet and bluff-body flows, the analyses leverage the normal-mode representation of wake instabilities to characterize the large-scale wake meandering observed in actuated wakes. Idealized large-eddy simulations (LES) using an actuator-line representation of the turbine blades indicate that the n=0 and ±1 modes, which correspond to the pulse and helix forcing strategies, respectively, have faster initial growth rates than higher-order modes, suggesting these lower-order modes are more appropriate for wake control. Exciting these lower-order modes with periodic pitching of the blades produces increased modal growth, higher entrainment into the wake, and faster wake recovery. Modal energy gain and the entrainment rate both increase with streamwise distance from the rotor until the intermediate wake. This suggests that the wake meandering dynamics, which share close ties with the relatively well-characterized meandering dynamics in jet and bluff-body flows, are an essential component of the success of wind turbine wake control methods. A spatial linear stability analysis is also performed on the wake flows and yields insights on the modal evolution. In the context of the normal-mode representation of wake instabilities, these findings represent the first literature examining the characteristics of the wake meandering stemming from intentional Strouhal-timed wake actuation, and they help guide the ongoing work to understand the fluid-dynamic origins of the success of the pulse, helix, and related methods.

17 WIND ENERGY↗
DOE OSTI2017

DEEP CHANDRA OBSERVATIONS OF NGC 1404: CLUSTER PLASMA PHYSICS REVEALED BY AN INFALLING EARLY-TYPE GALAXY

The intracluster medium (ICM), as a magnetized and highly ionized fluid, provides an ideal laboratory to study plasma physics under extreme conditions that cannot be achieved on Earth. NGC 1404 is a bright elliptical galaxy that is being gas stripped as it falls through the ICM of the Fornax Cluster. We use the new Chandra X-ray observations of NGC 1404 to study ICM microphysics. The interstellar medium of NGC 1404 is characterized by a sharp leading edge, 8 kpc from the Galaxy center, and a short downstream gaseous tail. Contact discontinuities are resolved on unprecedented spatial scales (0.″5 = 45 pc) due to the combination of the proximity of NGC 1404, the superb spatial resolution of Chandra , and the very deep (670 ks) exposure. At the leading edge, we observe sub-kiloparsec-scale eddies generated by Kelvin–Helmholtz instability (KHI) and put an upper limit of 5% Spitzer on the isotropic viscosity of the hot cluster plasma. We also observe mixing between the hot cluster gas and the cooler galaxy gas in the downstream stripped tail, which provides further evidence of a low viscosity plasma. The assumed ordered magnetic fields in the ICM ought to be smaller than 5 μ G to allow KHI to develop. The lack of an evident magnetic draping layer just outside the contact edge is consistent with such an upper limit.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Active Longitude and Coronal Mass Ejection Occurrences

The spatial inhomogeneity of the distribution of coronal mass ejection (CME) occurrences in the solar atmosphere could provide a tool to estimate the longitudinal position of the most probable CME-capable active regions in the Sun. The anomaly in the longitudinal distribution of active regions themselves is often referred to as active longitude (AL). In order to reveal the connection between the AL and CME spatial occurrences, here we investigate the morphological properties of active regions. The first morphological property studied is the separateness parameter, which is able to characterize the probability of the occurrence of an energetic event, such as a solar flare or CME. The second morphological property is the sunspot tilt angle. The tilt angle of sunspot groups allows us to estimate the helicity of active regions. The increased helicity leads to a more complex buildup of the magnetic structure and also can cause CME eruption. We found that the most complex active regions appear near the AL and that the AL itself is associated with the most tilted active regions. Therefore, the number of CME occurrences is higher within the AL. The origin of the fast CMEs is also found to be associated with this region. We concluded that the source of the most probably CME-capable active regions is at the AL. By applying this method, we can potentially forecast a flare and/or CME source several Carrington rotations in advance. This finding also provides new information for solar dynamo modeling.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Anisotropic conducting films for electromagnetic radiation applications

Electronic devices for the generation of electromagnetic radiation are provided. Also provided are methods for using the devices to generate electromagnetic radiation. The radiation sources include an anisotropic electrically conducting thin film that is characterized by a periodically varying charge carrier mobility in the plane of the film. The periodic variation in carrier mobility gives rise to a spatially varying electric field, which produces electromagnetic radiation as charged particles pass through the film.

36 MATERIALS SCIENCE↗
DOE OSTI2025

An Optothermal Raman Model Accounting for Convection, Radiation, and Substrate Effects for Evaluation of the Thermal Conductivity of Two‐Dimensional Coatings

Thermal conductivity of two‐dimensional (2D) materials is important to characterize as this will govern thermal transport physics in the various thermal and energy applications benefitting from the unique properties of these materials. Here, analytical and numerical techniques are presented to determine the thermal conductivity and interfacial conductance of a 2D material coating using confocal micro‐Raman spectroscopy as a noncontact diagnostic. While several methods have been proposed for calculating the values of thermal conductivity, interfacial conductance, and spatial temperature profile, these models often do not consider effects of radiation, convection, and substrate resistance on the temperature and heat flux profiles. We present a model to calculate the thermal conductivity and interfacial conductance which accounts for convection, radiation, and substrate effects to characterize a variety of 2D material coatings, which is demonstrated using large area graphene transferred onto copper and nickel substrates. Convection and radiation effects are found to have a negligible effect on the temperature profile of supported coatings, while the substrate effects have a considerable effect and therefore impact the quantification of thermal conductivity and interfacial conductance in addition to limiting the spatial resolution of the technique. These findings will allow for more accurate and reproducible extraction of the thermal conductivity of graphene and other 2D material coatings when employing noncontact optothermal Raman spectroscopy methods.

2D coatings↗
DOE OSTI2018

Hydrogeologic Setting and Groundwater Contaminant Conceptual Model, Los Alamos National Laboratory - 18681

Our understanding of the complex hydrogeologic setting at Los Alamos National Laboratory (LANL) has evolved significantly over the previous decade. The semi-arid, high-desert setting consists of generally dry drainages in canyons that head either in uplands to the west of the Laboratory or on the high mountain-front plateau where the Laboratory is spread across approximately 40 square miles. Some canyon drainages have spatially limited reaches with perennial surface water from natural runoff and spring sources and/or from permitted effluent sources. The Rio Grande rift basin-fill stratigraphy includes primary volcanic deposits from pyroclastic eruptions and intermediate composition lava flows, and fluvial and alluvial fan deposits. Highly complex and spatially variable stratigraphy governs the occurrences of three groundwater zones: shallow 'alluvial groundwater', deep perched groundwater, and a thick 'regional' aquifer that is the water supply for the community of Los Alamos and the Laboratory. The current understanding of the hydrogeologic framework was greatly expanded as part of a site hydrogeologic characterization program completed in 2005. Higher resolution information exists in area where more detailed groundwater characterization has been conducted to support specific project objectives. A conceptual model for occurrences of contaminants in each of the three groundwater zones is governed by four factors: contaminant solubility/mobility, the mass of historical release, presence of a continuous hydraulic driver, and 'breakthrough' geology, defined as geology conducive to infiltration of shallow groundwater to deeper groundwater zones. The Laboratory's operations were historically somewhat spatially partitioned. Most of the radionuclide work (and historical releases) was conducted in the northern portion of the Laboratory, high explosives work has taken place exclusively in the southwestern portion, and treated sanitary effluent was released at a limited number of outfalls. Historical material disposal areas (MDAs) are dispersed throughout the Laboratory, and active MDAs are all located on a single dry mesa at the eastern part of the Laboratory. Evidence exists of transport of anthropogenic constituents to the regional aquifer. However, years of groundwater characterization have identified only two cases for which all the key factors were present and a complete contaminant pathway to the regional aquifer has resulted in contamination at levels above an applicable standard. Hexavalent chromium contamination associated with historical use as a corrosion inhibitor in a power plant is present beneath Mortandad Canyon, and RDX contamination associated with high-explosives machining is present beneath Canon de Valle. Each of those project areas have refined conceptual and numerical models that address contaminant migration pathways, spatial extent of perched-intermediate groundwater, mass balance, and fate and transport within the regional aquifer. No known contamination is present in the regional aquifer associated with MDAs, and interestingly, much of the Laboratory's groundwater background dataset is from wells located beneath active MDAs. A comprehensive groundwater monitoring program is in place to track the evolution of chromium and RDX contamination, and to identify any other constituents that may be attributable to historical LANL operations. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Prognostic Power of Extreme Rainfall Scaling Formulas Across Space and Time Scales

Some studies documenting changes in extreme precipitation use scaling formulas to approximate the large percentiles of the rainfall distribution from average dynamical and thermodynamical variables, called predictors. Here we instead assess the performance of these formulas as approximations to the rain rates in individual events. We evaluate the accuracies of the scaling relationships as functions of spatial and temporal scales by analyzing tropical rainfall in a superparameterized model. Relationships using full vertical profiles of the predictors are more accurate than those using their values at specific vertical levels because they better characterize the specific dynamics of each event. Both types of scaling relationships perform well over a range of length scales from 200 to 2,000 km and time scales from an hour to a week, and their precision is higher in the case of simulations with superparameterization than with parameterized convection. Uncertainties emerging from the local use of the scaling relationships suggest that they may only characterize the intensification of individual extremes for a warming of 4–5 K or larger. Finally, we argue that these formulas can be used to reconstruct the tail of the rainfall distribution directly from its predictors without prior information on P. While scalings have been used as diagnostic equations conditioned on the occurrence of extreme rainfall, they are actually able to mimic the prognostic behavior of climate model parameterizations on a variety of scales when estimating the intensity, frequency, and spatial patterns of extremes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Statistical Methods for Effective Spatial and Temporal Scaling in Support of Probabilistic Performance Assessments - 17340

Performance assessments (PAs) for the disposal of low-level radioactive waste have traditionally been performed in a deterministic manner, with inputs specified as single values as if they carry no uncertainty. Modern PAs, however, explicitly incorporate uncertainty through use of probability distributions for inputs instead of single values. While this is clearly an improvement, challenges remain in specifying appropriate distributions, many of which relate to capturing the appropriate spatial and/or temporal scale given the PA model, and matching the scale(s) of data and information to that specified by the model. More careful attention to scaling will lead to more defensible characterizations of physical variability and uncertainty in model inputs, thus leading to more defensible information regarding outcomes of interest to be used in decision making, and hence more defensible decisions. This work introduces general strategies and considerations for explicitly incorporating considerations of scale into distribution development. The strategies are explained as a series of steps and then presented with an example that starts to illustrate the new statistical concepts. This work frames the problem in terms of hierarchical statistical modeling, providing important connections to current statistical approaches to formally and rigorously account for temporal and spatial scaling. The larger goal is to build a more formal and unified approach to distribution development to help teams of modelers, subject matter experts, and statisticians work together to develop distributions and justify the choices made in the process, ultimately leading to more informed decision-making. Without this rigor, statistical distributions are not specified correctly and can have unexpected consequences for modeling and sensitivity analysis. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Rapid Coal-Ash Characterization using Geophysical Methods & Machine Learning

Coal combustion products (CCP) are challenging to delineate in heterogeneous field settings. Conventional methods (test pits, coring, and laboratory analyses) are labor-intensive, slow, invasive, and provide sparse spatial coverage. This study evaluates whether rapid non-invasive geophysical screening methods—induced polarization (IP), magnetic susceptibility, and nuclear magnetic resonance (NMR) —combined with surface colorimetry (RGB_24), can discriminate CCP-soil mixtures and provide reliable estimates of CCP content. Laboratory measurements were collected on five CCP-soil mixtures (series) and modeled using (i) a linear baseline, (ii) a calibrated non-linear (power-mean) model, and (iii) a machine-learning (ML) Random Forest approach, with validation via leave-one-series-out and site-specific tests. Across the five series, individual signals—particularly IP and magnetic susceptibility—were strongly predictive of ash content but were consistently outperformed by combined models. The pooled calibrated non-linear and ML models captured the observed non-linearity and achieved high accuracy and precision, improving on linear fits. Colorimetry showed the weakest direct relationship with ash content for the tested samples but improved performance when included in multi-signal models. At pre-selected 3.5% decision threshold, calibrated and ML approaches yielded near-perfect classification (Matthews correlation coefficient ˜ 1), suggesting strong practical operability for field screening. Additionally, field-analog tests highlighted the role of endmembers—accuracy declined without access to end-member measurements but was largely recovered by collecting a minimal labeled pair for local recalibration. With end members, accuracy remained high. Globally trained models performed well on three operational unknowns; however, series-specific refits provided the most accurate predictions. Overall, these results highlight the potential of combining rapid geophysics and minimal local calibration for improved coal-ash delineation.

Peshtani, Klaudio↗
DOE OSTI2019

Quantitative capabilities of STXM to measure spatially resolved organic volume fractions of mixed organic/inorganic particles

Scanning transmission X-ray microscopy coupled with near-edge X-ray absorption and fine structure (STXM-NEXAFS) spectroscopy can be used to characterize the morphology and composition of aerosol particles. Here, two inorganic/organic systems are used to validate the calculation of organic volume fraction (OVF) and determine the level of associated error by using carbon K-edge STXM data at 278, 285.4, 288.6, and 320 eV. Using the mixture of sodium chloride and sucrose as one system and ammonium sulfate and sucrose as another, three solutions were made with 10:1, 1:1, and 1:10 mass ratios (inorganic to organic). The OVFs of the organic-rich aerosols of both systems deviated from the bulk OVF by less than 1%, while the inorganic-rich aerosols deviated by approximately 1 %. Aerosols from the equal mass mixture deviated more (about 4 %) due to thick inorganic regions exceeding the linear range of Beer's law. These calculations were performed after checking the data for poor image alignment, defocusing issues, and particles too thick to be analyzed. The potential for systematic error in the OVF calculation was also tested by assuming the incorrect composition. There is a small (about 0.5 %) OVF difference if the organic is erroneously assumed to be adipic acid rather than the known organic, sucrose. A much larger difference (up to 25 %) is seen if sodium chloride is assumed instead of ammonium sulfate. These results show that the OVF calculations are fairly insensitive to the organic while being much more sensitive to the choice of inorganic.

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

The Search for Spatial Extension in High-latitude Sources Detected by the Fermi Large Area Telescope

Here, we present a search for spatial extension in high-latitude ($| b| \gt 5^\circ $) sources in recent Fermi point source catalogs. The result is the Fermi High-Latitude Extended Sources Catalog, which provides source extensions (or upper limits thereof) and likelihood profiles for a suite of tested source morphologies. We find 24 extended sources, 19 of which were not previously characterized as extended. These include sources that are potentially associated with supernova remnants and star-forming regions. We also found extended γ-ray emission in the vicinity of the Cen A radio lobes and—at GeV energies for the first time—spatially coincident with the radio emission of the SNR CTA 1, as well as from the Crab Nebula. We also searched for halos around active galactic nuclei, which are predicted from electromagnetic cascades induced by the e + e – pairs that are deflected in intergalactic magnetic fields. These pairs are produced when γ-rays interact with background radiation fields. We do not find evidence for extension in individual sources or in stacked source samples. This enables us to place limits on the flux of the extended source components, which are then used to constrain the intergalactic magnetic field to be stronger than 3 × 10 –16 G for a coherence length λ ≳ 10 kpc, even when conservative assumptions on the source duty cycle are made. This improves previous limits by several orders of magnitude.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Acceleration Techniques using ADVANTG for the MDF Design and Optimization

The Spallation Neutron Source (SNS) facility at Oak Ridge National Laboratory (ORNL) is implementing a Moderator Demonstration Facility (MDF) to demonstrate the performance characteristics of advanced moderators central to the Second Target Station (STS) for SNS. The MDF will provide a small, short-pulsed neutron source for slow neutron production in which we intend to easily and quickly change from one moderator concept to another, characterizing the performance of each moderator in a reproducible and consistent fashion. The MDF will be unique and innovative amongst the world's moderator test facilities in that it will be intended to be very prototypic in terms of 'moderator illumination' - the spatial variation of the neutron flux entering the moderator itself - as well as capable of testing so-called high-brightness moderators in a wing configuration. During the design phase of the MDF, the Monte Carlo N-Particle transport code MCNPX v.2.7.0 is being used as the primary tool for the neutronic analysis of the facility and characterization of the moderator performance. The Automated Variance Reduction Generator (ADVANTG) code is being utilized to accelerate the MCNPX calculations. The ADVANTG code generates space- and energy-dependent weight window parameters for a successive MCNP run by calculating the adjoint flux with the Denovo discrete ordinates code based on the user defined MCNP tally. We have tested various strategies using ADVANTG to generate weight window parameters to efficiently calculate detailed moderator performance. Using point detector response functions for weight window parameter optimization with ADVANTG did not work well for improving the efficiency of Monte Carlo calculations of neutron emission into beam lines. However, using cell fluxes of the area of highest contributions to the point detector for the variance reduction parameter analysis worked very well and improved the FOM of the calculation of neutron emission into a beamline by a factor of 50 over the unbiased case. (authors)

42 ENGINEERING↗
DOE OSTI2015

SU-D-303-01: Spatial Distribution of Bone Metastases In Metastatic Castrate-Resistant Prostate Cancer

Purpose: Identification of metastatic bone lesions is critical in prostate cancer, where treatments may be more effective in patients with fewer lesions. This study aims characterize the distribution and spread of bone lesions and create a probability map of metastatic spread in bone. Methods: Fifty-five metastatic castrate-resistant prostate cancer patients received up to 3 whole-body [F-18]NaF PET/CT scans. Lesions were identified by physician on PET/CT and contoured using a threshold of SUV>15. An atlas-based segmentation method was used to create CT regions, which determined skeletal location of lesions. Patients were divided into 3 groups with low (N<40), medium (40 100) numbers of lesions. A combination of articulated and deformable registrations was used to register the skeletal segments and lesions of each patient to a single skeleton. All the lesion data was then combined to make a probability map. Results: A total of 4038 metastatic lesions (mean 74, range 2–304) were identified. Skeletal regions with highest occurrence of lesions included ribs, thoracic spine, and pelvis with 21%, 19%, and 15% of the total number lesions and 8%, 18%, and 31 % of the total lesion volume, respectively. Interestingly, patients with fewer lesions were found to have a lower proportion of lesions in the ribs (9% in low vs. 27% in high number of lesions). Additionally, the probability map showed specific areas in the spine and pelvis where over 75% of patients had metastases, and other areas in the skeleton with a less than 2% of metastases. Conclusion: We identified skeletal regions with higher incidence of metastases and specific sub-regions in the skeleton that had high or low probability of occurrence of metastases. Additionally, we found that metastatic lesions in the ribs and skull occur more commonly in advanced disease. These results may have future applications in computer-aided diagnosis. Funding from the Prostate Cancer Foundation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

The Development of a Generalized Riser Flow Regime Map Based Upon Higher Moment and Chaotic Statistics Using Electrical Capacitance Volume Tomography (ECVT)

Dynamic analyses have been applied to the temporal signals from an Electro Capacitance Volume Tomography instrument located near mid-height on the riser of an industrial-scale cold-flow circulating fluidized bed to characterize gas-solids flow behavior in the riser. Twelve capacitance electrodes surround the cylindrical riser over a height of 1.3 m. The instrument used a neural network deconvolution algorithm to determine the spatially resolved solids fraction recorded at 52 Hz. Experiments were carried out over a range of gas and solids flows in the transport regime using a Geldart Group B bed material, high density polyethylene with mean particle size of 880 μm. The radial solids distribution was found to vary from one-time step to the next between profiles typical of laminar and turbulent flow. The duration of time spent in each of these flow profiles depended upon the operating regime – dilute, core-annular, or fast fluidized bed. The chaotic structure of the temporal data was characterized using the three conventional approaches: the first 4 moments from the distribution of signal in time, system memory parameters from the autocorrelation function and the Hurst exponent, and analysis of the correlationentropy and correlation dimension of the attractor. These signal analysis techniques were used to clearly distinguish differences between different transport operating regimes. Specifically, it was experimentally observed that a riser transitions from core annular flow profile to dilute and dense regimes via increasing the frequency of short term transients to either dilute or dense flow profiles, respectively. A regime map was generated based upon these dynamics using solids flux and gas velocity axes. Fast fluidized, core annular, and dilute each exhibited different degree of dynamic characteristics typical of fluid dominated or particle compromising behavior. It should be noted that the magnitude for the different statistics was in the same range regardless of the regime, it was the radial profile for the statistic that changed and subsequently identified that there was a change in the regime. Finally, a reduced regime map was developed consisting of plotting the gas velocity normalized by the upper transport velocity versus the solids flux normalized by the saturation carrying capacity. The use of this reduced plot allowed the data from widely different conditions to be plotted and compared on the same<p>graph. Note that in many instances, some of the statistics identified the operating point as being in one regime while others indicated that it was in another indicating a transition region between dilute or core annular regimes and between the core annular and fast fluidization regimes. This now provides a tool that can be used to optimize process performance, identify changes in operating states, or replicate process dynamics during process scaling or changing operating parameters. </p>

Breault, Ronald↗
DOE OSTI2024

Leveraging Extremal Dependence to Better Characterize the 2021 Pacific Northwest Heatwave

Abstract In late June, 2021, a devastating heatwave affected the US Pacific Northwest and western Canada, breaking numerous all-time temperature records by large margins and directly causing hundreds of fatalities. The observed 2021 daily maximum temperature across much of the U.S. Pacific Northwest exceeded upper bound estimates obtained from single-station temperature records even after accounting for anthropogenic climate change, meaning that the event could not have been predicted under standard univariate extreme value analysis assumptions. In this work, we utilize a flexible spatial extremes model that considers all stations across the Pacific Northwest domain and accounts for the fact that many stations simultaneously experience extreme temperatures. Our analysis incorporates the effects of anthropogenic forcing and natural climate variability in order to better characterize time-varying changes in the distribution of daily temperature extremes. We show that greenhouse gas forcing, drought conditions and large-scale atmospheric modes of variability all have significant impact on summertime maximum temperatures in this region. Our model represents a significant improvement over corresponding single-station analysis, and our posterior medians of the upper bounds are able to anticipate more than 96% of the observed 2021 high station temperatures after properly accounting for extremal dependence. Supplementary materials accompanying this paper appear online.

Zhang, Likun (ORCID:0000000154584556)↗
DOE OSTI2016

Imaging of electrical response of NiO x under controlled environment with sub-25-nm resolution

The spatially resolved electrical response of rf-sputtered polycrystalline NiO x films composed of 40 nm crystallites was investigated under different relative humidity levels (RH). The topological and electrical properties (surface potential and resistance) were characterized using Kelvin probe force microscopy (KPFM) and conductive scanning probe microscopy at 0%, 50%, and 80% relative humidity with sub 25nm resolution. The surface potential of NiO x decreased by about 180 mV and resistance decreased in a nonlinear fashion by about 2 G when relative humidity was increased from 0% to 80%. The dimensionality of surface features obtained through autocorrelation analysis of topological, surface potential and resistance maps increased linearly with increased relative humidity as water was adsorbed onto the film surface. Spatially resolved surface potential and resistance of the NiO x films were found to be heterogeneous, with distinct features that grew in size from about 60 nm to 175 nm between 0% and 80% RH levels, respectively. Here, we find that the changes in the heterogeneous character of the NiO films are consistent through the topological, surface potential, and resistance measurements, suggesting that the nanoscale surface potential and resistance properties converge with the mesoscale properties as water is adsorbed onto the NiO x film.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

How much information on precipitation is contained in satellite infrared imagery?

Satellite infrared (IR) brightness temperature providing information on the characteristics of cloud tops is one of the primary input data used for estimating precipitation from satellites. Thus, the natural questions to ask are: Does IR imagery contain more information about precipitation in some regions more than others? What are the factors that lead to such differences? Should we expect the amount of information provided by IR imagery to change with respect to temporal or spatial aggregation? Comprehensive analysis of the accuracy of satellite-based precipitation estimates obtained from any given algorithm may provide qualitative answers to the above questions. However, such an approach only offers conclusions within the limited context of the algorithm used to obtain precipitation estimates; that is, patterns caused by the inherent information content of IR imagery are inextricable from those induced by assumptions embedded in the precipitation estimation algorithm. Here, we address the abovementioned questions from a different perspective using an information-theoretic measure, free of structural assumptions and general to a wide range of relationships, to characterize the average and seasonal dependence between IR imagery provided by satellite sensors in the spectral range (10.7–11.5 μm) and precipitation rates in the contiguous United States (CONUS) across distinct temporal and spatial scales. We analyze a total of more than 1.3 billion pairs of IR and precipitation observations over CONUS, and we observe interesting patterns. First, we show that there is a strong inverse relationship (ρ = - 0.73) between the information content of IR data and the number of no-rain observations; however, its robustness varies regionally and seasonally with less significant correlation during the warm season. Second, we demonstrate that the intuitive relationship of increasing dependence between IR and precipitation as a result of temporal or spatial aggregation exhibits a diminishing returns behavior. For instance, temporal aggregation from 1 to 3 h increases the dependence approximately 7 times as much as temporal aggregation from 12 to 24 h. Furthermore, we quantitatively examine and re-confirm several statements previously reported in the literature such as the strong association between IR and precipitation in convective storms and the low association in orographic rainfall. Finally, we conclude by illustrating the potential of the analysis in diagnosis of operational algorithms for estimating precipitation from IR brightness temperature. The findings of this study pinpoint spatial domains and time scales at which IR is not an adequate proxy for estimating precipitation. Thus, they can potentially guide the development of operational algorithms that utilize satellite Infrared imagery for estimating, downscaling and data fusion of precipitation. Finally, the analysis presented here opens up the possibility of developing new methodologies for diagnosis of satellite-based precipitation estimation algorithms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Mapping foliar photosynthetic capacity in sub-tropical and tropical forests with UAS-based imaging spectroscopy: Scaling from leaf to canopy

Accurate understanding of the variability in foliar physiological traits across landscapes is critical to improve parameterization and evaluation of terrestrial biosphere models (TBMs) that seek to represent the response of terrestrial ecosystems to a changing climate. Numerous studies suggest imaging spectroscopy can characterize foliar biochemical and morphological traits at the canopy scale, but there is only limited evidence for retrieving canopy photosynthetic capacity (e.g., maximum carboxylation rate, V c,max and maximum electron transport rate, J max ). Moreover, the effect of canopy structure within forest communities on scaling up spectra-trait relationships from leaf to canopy level is not well known. To advance the spectra-trait approach and enable the estimation of key traits using remote sensing, we collected imaging spectroscopy data from an Unoccupied Aerial System (UAS) platform over two forest sites in China (a subtropical forest in Mt. Dinghu and a tropical rainforest in Xishuangbanna). At these sites, we also collected ground measurements of leaf spectra and traits, including biochemical (leaf nitrogen, phosphorus, chlorophyll, and water content), morphological (leaf mass per area, LMA) and physiological (V c,max25 and J max25 ) traits (n=135 tree-crowns from 42 species across two sites). Using a partial least-squares regression (PLSR) approach, we built and tested spectra-trait models with repeated cross-validation. The spectral models developed with leaf spectra were directly transferred to canopy spectra to evaluate the effect of canopy structure. Here we further applied canopy spectral models to map these traits at individual tree-crown scale. The results demonstrate that (1) UAS-based canopy spectra can be used to estimate V c,max (R 2 =0.55, nRMSE=11.79%), Jmax (R 2 =0.54, nRMSE=12.34%), and five additional foliar traits (R 2 =0.38-0.60, nRMSE=10.11-13.56%) at the tree-crown scale with demonstrated generalizability across two sites; (2) canopy structure strongly affects the spectratrait relationships from leaf to canopy level, but the effects vary considerably across foliar traits and cannot be well captured by the 4SAIL canopy radiative transfer model. UAS-based imaging spectroscopy maps large variability in all foliar traits (including physiological traits) with spatially explicit information, reproducing the field-observed inter- and intra-specific variations. These results demonstrate the capability of using UAS-based imaging spectroscopy for characterizing the variability of foliar physiological traits at individual tree-crown scale over forest landscapes and highlight the similar generalizability but different biophysical mechanisms underlying spectra-trait relationships at leaf and canopy levels.

54 ENVIRONMENTAL SCIENCES↗