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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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At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
NASA NTRS2023

Optimizing the Resolution of Hydrodynamic Simulations for MCRaT Radiative Transfer Calculations

Despite their discovery about half a century ago, the Gamma-ray burst (GRB) prompt emission mechanism is still not well understood. Theoretical modeling of the prompt emission has advanced considerably due to new computational tools and techniques. One such tool is the PLUTO hydro dynamics code, which is used to numerically simulate GRB outflows. PLUTO uses Adaptive Mesh Refinement to focus computational efforts on the portion of the grid that contains the simulated jet. Another tool is the Monte Carlo Radiation Transfer (MCRaT) code, which predicts electromagnetic signatures of GRBs by conducting photon scatterings within a jet using PLUTO. The effects of the underlying resolution of a PLUTO simulation with respect to MCRaT post-processing radiative transfer results have not yet been quantified. We analyze an analytic spherical outflow and a hydrodynamically simulated GRB jet with MCRaT at varying spatial and temporal resolutions and quantify how decreasing both resolutions affect the resulting mock observations. We find that changing the spatial resolution changes the hydrodynamic properties of the jet, which directly affect the MCRaT mock observable peak energies. We also find that decreasing the temporal resolution artificially decreases the high energy slope of the mock observed spectrum, which increases both the spectral peak energy and the luminosity. We show that the effects are additive when both spatial and temporal resolutions are modified. Our results allow us to understand how decreased hydrodynamic temporal and spatial resolutions affect the results of post-processing radiative transfer calculations, allowing for the optimization of hydrodynamic simulations for radiative transfer codes.

Jose Arita-Escalante↗
NASA NTRS2006

Progress and Plans in Support of the Polar Community

Feedback provided by the Antarctic community has proven instrumental in positively influencing the direction of the GCMD's development. For example, in response to requests for a stand alone metadata authoring tool, a new shareable software package called docBUILDER solo will be released to the public in March 2006. This tool permits researchers to document their data during experiments and observational periods in the field. The international polar community has also played a key role in encouraging support for the foreign language character set in the metadata display and tools (10% of the records in the AMD hold foreign characters). In the upcoming release, the full ISO character set, which also includes mathematical symbols, will be supported. Additional upgrades include the ability for users to search for data sets based on pre-selected temporal and spatial resolution ranges. Data providers are strongly encouraged to populate the resolution fields for their data sets, although these fields are not currently required. In prior versions, browser incompatibilities often resulted in unreliable performance for users attempting to initiate a spatial search using a map based on Java applet technology. The GCMD will offer an integrated Google map and date search, replacing the applet technology and enhancing the geospatial and temporal searches. It is estimated that 30% of the records in the AMD have direct access to data. A growing number of these records can be accessed through data service links. Related data services are therefore becoming valuable assets in facilitating the use and visualization of data. Users will gain the ability to refine services using the same options as those available for data set searches. Data providers are encouraged to describe available data-related services through the directory. Future plans include offering web services through a SOAP interface and extending semantic queries for the polar regions through the use of ontologies. The Open Archives Initiative's (OAI) Protocol for Metadata Harvesting (PMH) has been successfully tested with several organizations and appears to be a prime candidate for sharing metadata within the community. The GCMD anticipates contributing to the design of the data management system for the International Polar Year and to the ongoing efforts in the years to come. Further enhancements will be discussed at the meeting.

Olsen, Lola M.↗
DOE OSTI2023

The June 2012 North American Derecho: A Testbed for Evaluating Regional and Global Climate Modeling Systems at Cloud‐Resolving Scales

Abstract In this paper, we introduce a testbed for evaluating and comparing climate modeling systems at cloud resolving scales using hindcasts of the June 2012 North American derecho. To demonstrate its utility for model intercomparison, the testbed is applied to two models: the regionally‐refined Simple Cloud‐Resolving E3SM Atmosphere Model (SCREAM) at 6.5, 3.25 and 1.625 km grid spacing and the Weather Research and Forecasting (WRF) model with 3.2 and 1.6 km grid spacing. We find the simulation results to be highly sensitive to the initial conditions (ICs), initialization time, and model configurations, with ICs from the Rapid Refresh producing the best simulation. Significant improvement is identified in both models as horizontal grid spacing is refined. While a propagation delay of approximately 2 hr is found in both models, SCREAM at 1.625 km simulates the observed bow echo structure of the derecho well and predicts strong surface gusts that exceed 30 m/s. In comparison, WRF has difficulty producing surface wind over 25 m/s, with wind gusts in WRF 42%–46% lower than in SCREAM. However, WRF has a lower bias in simulating cloud top temperature and extent, but overestimates precipitation intensity. Both models reproduce the observed outgoing longwave radiation spatial patterns well (Pearson correlation >0.88), but, compared with NEXRAD observations, simulate generally larger areas of composite radar reflectivity >40 dBZ and underestimate the precipitating area by ∼47%.

2012 North American derecho↗
DOE OSTI2025

Determining the nanostructure of polymer foams using 3D ptycho-tomography for inertial fusion energy applications

Polymer foams play a critical role in contemporary inertial fusion energy (IFE) target designs by enhancing energy yield and optimizing implosion dynamics. However, the lack of high-resolution characterization of the nanostructure of these foams restricts progress in fusion science. In this work, we demonstrate the first high-resolution three-dimensional (3D) reconstruction of a low-density, Si-doped polymer foam fabricated via two-photon polymerization, using ptychographic x-ray computed tomography (PXCT) at an x-ray free electron laser (XFEL). This imaging method reconstructs two-dimensional (2D) attenuation and phase information at multiple sample angles that are combined into a 3D density map used to extract local mass density and determine structural dimensions. We achieve a 2D spatial resolution of 19 ± 3 nm on a high-contrast Ronchi pattern target and 78.7 ± 3 nm for low-contrast polymer foams, marking a significant advancement for XFEL-based ptychography of low-density materials. Furthermore, our experimental results reveal an average foam strut thickness of 1.17 ± 0.4 μm, consistent with fabrication expectations, and a reconstructed average mass density of 0.35 g/cc, aligning closely with the predicted density of 0.29 g/cc. These findings provide important insights for improving foam design and refining radiation hydrodynamics modeling in future IFE experiments. Our study establishes PXCT at an XFEL as a powerful tool for high-resolution characterization of fusion-relevant materials, paving the way for enhanced target performance in IFE research.

Hancock, Levi [Colorado State Univ., Fort Collins,↗
DOE OSTI2023

Density limits as disruption forecasters for spherical tokamaks

Fusion power output from spherical tokamaks would benefit from increased confined plasma density, but there exists a limit on the density before confinement is lost and the plasma current is disrupted. This density limit has long been characterized by a simple, global Greenwald limit proportional to the plasma current and inversely proportional to the cross sectional area of the plasma. It is shown that in the database of discharges from the National Spherical Tokamak Experiment (NSTX) and Mega Ampere Spherical Tokamak (MAST) spherical tokamaks, the likelihood of disruption does increase above the Greenwald limit, and especially in the plasma current rampdown phase. The physics of the density limit has been recently theoretically explored through local criteria. Several of these are tested using the disruption event characterization and forecasting (DECAF TM ) code for their potential effectiveness as disruption warning signals. For a limited set of NSTX discharges, a local island power balance criteria was found to be less reliable, presently, than the Greenwald limit. For this work, an empirical critical edge line density and a boundary turbulent transport limit were both tested for MAST-U, which has an electron density profile measurement with high spatial resolution in the outer part of the plasma. Both were found to have similar dependencies on key plasma parameters. In a limited set of MAST-U discharges that appear to disrupt due to rising density at values under the Greenwald limit, crossing of the boundary turbulent transport limit occurred close to the time of disruption. Finally, these limits were evaluated for their potential use in real-time, and it was found that with the necessary real-time inputs and with refinement through further testing, these limits could be implemented in a real-time disruption forecasting system.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Seismic Characterization of the Blue Mountain Geothermal Field

Subsurface characterization is crucial for geothermal energy exploration and production. Yet hydrothermal reservoirs usually reside in highly fractured and faulted zones where accurate characterization is very challenging because of low signal-to-noise ratios of land seismic data and lack of coherent reflection signals. We perform an active-source seismic characterization for the Blue Mountain geothermal field in Nevada using active seismic data to reveal the elastic medium property complexity and fault distribution at this field. We first employ an unsupervised machine learning method to attenuate groundroll and near-surface guided-wave noise and enhance coherent reflection and scattering signals from noisy seismic data. We then build a smooth initial P-wave velocity model based on an existing magnetotellurics survey result, and use 3D first-arrival traveltime tomography to refine the initial velocity model. We then derive a set of elastic wave velocities and anisotropic parameters using elastic full-waveform inversion, and obtain PP and PS images using elastic reverse-time migration. We identify major faults by analyzing the variations of seismic velocities and anisotropy parameters, and reveal mid- to small-scale faults by applying a supervised machine learning method to the seismic migration images. Our characterization reveals complex velocity heterogeneities and anisotropies, as well as faults, with a high spatial resolution. These results can provide valuable information for optimal placement of future injection and production wells to increase geothermal energy production at the Blue Mountain geothermal power plant.

58 GEOSCIENCES↗
DOE OSTI2024

The Electron Spectro-Microscopy (ESM) Beamline at NSLS-II

Photoelectron spectroscopy is a primary tool for the study of the electronic structure of materials and the chemical composition of surfaces. High-resolution angle-resolved photoemission spectroscopy (ARPES) has the unique ability to map the energy bands in momentum space. Furthermore, going beyond the single particle picture, the self-energy corrections caused by correlations in solids can be extracted from the analysis of the emission line shape. The current level of refinement, in terms of energy and angular resolution (ΔE < 1 meV, Δθ < 0.1°), makes the technique sensitive to the lowest energy excitations and the dynamics of electrons, which in turn virtually determine all the macroscopic properties of any system and govern the chemical, electrical, magnetic, and physical processes. Similarly important, X-ray photoelectron microscopy (XPEEM), combined with the low-energy electron microscopy (LEEM), is indispensable in probing the complexity of chemical, structural, electronic and magnetic properties of surfaces and shallow interfaces, with the spatial resolution of few tens of nanometer (nm). The Electron-Spectro-Microscopy beamline (ESM) has been recently commissioned at NSLS-II and is now in operation. The primary spectroscopic technique is photoemission, performed over a wide energy range with control of light polarization and in a variety of flux/resolution conditions. The beamline has two experimental end stations that allow to perform ARPES and XPEEM/LEEM, separately. The ARPES end station focuses on high energy-resolution work, with spot-size of a few microns. The XPEEM/LEEM end station is a full-field microscope (XPEEM) operating either with the synchrotron generated X-rays (XPEEM), or with an internal electron gun (LEEM). Spatial resolution is crucial in studies of newly synthesized complex materials since they are often initially available only as small specimens (typically micron size). Furthermore, chemical inhomogeneities on surfaces are often an integral part of surface chemical processes. Finally, the ESM beamline with X-ray spots of few microns is optimized to study the electronic structure of novel materials with microscopy capabilities.

47 OTHER INSTRUMENTATION↗
NASA NTRS2003

Studies of Trace Gas Chemical Cycles Using Inverse Methods and Global Chemical Transport Models

We report progress in the first year, and summarize proposed work for the second year of the three-year dynamical-chemical modeling project devoted to: (a) development, testing, and refining of inverse methods for determining regional and global transient source and sink strengths for long lived gases important in ozone depletion and climate forcing, (b) utilization of inverse methods to determine these source/sink strengths using either MATCH (Model for Atmospheric Transport and Chemistry) which is based on analyzed observed wind fields or back-trajectories computed from these wind fields, (c) determination of global (and perhaps regional) average hydroxyl radical concentrations using inverse methods with multiple titrating gases, and (d) computation of the lifetimes and spatially resolved destruction rates of trace gases using 3D models. Important goals include determination of regional source strengths of methane, nitrous oxide, methyl bromide, and other climatically and chemically important biogenic/anthropogenic trace gases and also of halocarbons restricted by the Montreal protocol and its follow-on agreements and hydrohalocarbons now used as alternatives to the restricted halocarbons.

Prinn, Ronald G.↗
DOE OSTI2025

DeFault: DEep‐Learning‐Based FAULT Delineation Using the IBDP Passive Seismic Data at the Decatur CO2 Storage Site

Abstract The carbon capture, utilization, and storage (CCUS) framework is an essential component in reducing greenhouse gas emissions, with its success hinging on the comprehensive knowledge of subsurface geology and geomechanics. Passive seismic event relocation and fault detection offer vital insights into subsurface structures and the ability to monitor fluid migration pathways. Accurate identification and localization of seismic events, however, face significant challenges, including the necessity for high‐quality seismic data and advanced computational methods. To address these challenges, we introduce a novel deep learning method, , specifically designed for passive seismic source relocation and fault delineating for passive seismic monitoring projects. By leveraging data domain‐adaptation, allows us to train a neural network with labeled synthetic data and apply it directly to field data. Using , the passive seismic sources are automatically clustered based on their recording time and spatial locations, and subsequently, faults and fractures are delineated accordingly. We demonstrate the efficacy of on a field case study involving injection related microseismic data from Decatur, Illinois area. Our approach accurately and efficiently relocated passive seismic events, identified faults and could aid in potential damage induced by seismicity. Our results highlight the potential of as a valuable tool for passive seismic monitoring, emphasizing its role in ensuring CCUS project safety. This research bolsters the understanding of subsurface characterization in CCUS, illustrating machine learning’s capacity to refine these methods. Ultimately, our work has significant implications for CCUS technology deployment, an essential strategy in combating climate change. Plain Language Summary In our quest to tackle climate change, we use a strategy known as carbon capture, utilization, and storage (CCUS) to keep greenhouse gases out of the atmosphere. This strategy relies heavily on our ability to understand what's happening deep under the earth's surface. To make sure we store super critical safely, we need to accurately map out the geological structure, especially faults, but this is tough without high‐quality data and complex computer programs. We've developed a new tool called “DeFault,” which uses advanced machine learning to improve how we find and map these underground features. “DeFault” is smart enough to learn from numerically simulated data and then apply what it’s learned to real‐world situations. It groups together seismic activity—tiny tremors and shifts in the earth—based on when and where they happen, which helps us spot where there might be cracks or faults. We tested “DeFault” in Illinois, where CO 2 is injected underground, and it successfully pinpointed where these tremors occurred and mapped out the faults, helping to prevent accidents accurately in the future. Our study shows that “DeFault” will be a powerful ally in making CCUS safer and more effective, especially for the Illinois Basin Decatur Project. Key Points Faults and fractures introduced by carbon storage can be monitored by passive seismicity DeFault algorithm enables an automatic process for accurate and efficient passive seismic event locating and clustering

58 GEOSCIENCES↗
NASA NTRS1997

Dynamics of Numerics & Spurious Behaviors in CFD Computations

The global nonlinear behavior of finite discretizations for constant time steps and fixed or adaptive grid spacings is studied using tools from dynamical systems theory. Detailed analysis of commonly used temporal and spatial discretizations for simple model problems is presented. The role of dynamics in the understanding of long time behavior of numerical integration and the nonlinear stability, convergence, and reliability of using time-marching approaches for obtaining steady-state numerical solutions in computational fluid dynamics (CFD) is explored. The study is complemented with examples of spurious behavior observed in steady and unsteady CFD computations. The CFD examples were chosen to illustrate non-apparent spurious behavior that was difficult to detect without extensive grid and temporal refinement studies and some knowledge from dynamical systems theory. Studies revealed the various possible dangers of misinterpreting numerical simulation of realistic complex flows that are constrained by available computing power. In large scale computations where the physics of the problem under study is not well understood and numerical simulations are the only viable means of solution, extreme care must be taken in both computation and interpretation of the numerical data. The goal of this paper is to explore the important role that dynamical systems theory can play in the understanding of the global nonlinear behavior of numerical algorithms and to aid the identification of the sources of numerical uncertainties in CFD.

Yee, Helen C.↗
NASA NTRS1996

Algal Accessory Pigment Detection Using AVIRIS Image-Derived Spectral Radiance Data

Visual and derivative analyses of AVIRIS spectral data can be used to detect algal accessory pigments in aquatic communities. This capability extends the use of remote sensing for the study of aquatic ecosystems by allowing detection of taxonomically significant pigment signatures which yield information about the type of algae present. Such information allows remote sensing-based assessment of aquatic ecosystem health, as in the detection of nuisance blooms of cyanobacteria or toxic blooms of dinoflagellates. Remote sensing of aquatic systems has traditionally focused on quantification of chlorophyll a, a photoreactive (and light-harvesting) pigment which is common to all algae as well as cyanobacteria (bluegreen algae). Due to the ubiquitousness of this pigment within algae, chl a is routinely measured to estimate algal biomass both during ground-truthing and using various airborne or satellite based sensors, including AVIRIS. Within the remote sensing and aquatic sciences communities, ongoing research has been performed to detect algal accessory pigments for assessment of algal population composition. This research is based on the fact that many algal accessory pigments are taxonomically significant, and all are spectrally unique. Aquatic scientists have been refining pigment analysis techniques, primarily high performance liquid chromatography, or HPLC, to detect specific pigments as a time-saving alternative to individual algal cell identifications and counts. Remote sensing scientists are investigating the use of pigment signatures to construct pigment libraries analogous to mineral spectral libraries used in geological remote sensing applications. The accessory pigment approach has been used successfully in remote sensing using data from the Thematic Mapper, low-altitude, multiple channel scanners, field spectroradiometers and the AVIRIS hyperspectral scanner. Due to spectral and spatial resolution capabilities, AVIRIS is the sensor of choice for such studies. We present here our results on detection of algal accessory pigments using AVIRIS data.

Richardson, Laurie L.↗
NASA NTRS2012

NASA Products to Enhance Energy Utility Load Forecasting

Existing energy load forecasting tools rely upon historical load and forecasted weather to predict load within energy company service areas. The shortcomings of load forecasts are often the result of weather forecasts that are not at a fine enough spatial or temporal resolution to capture local-scale weather events. This project aims to improve the performance of load forecasting tools through the integration of high-resolution, weather-related NASA Earth Science Data, such as temperature, relative humidity, and wind speed. Three companies are participating in operational testing one natural gas company, and two electric providers. Operational results comparing load forecasts with and without NASA weather forecasts have been generated since March 2010. We have worked with end users at the three companies to refine selection of weather forecast information and optimize load forecast model performance. The project will conclude in 2012 with transitioning documented improvements from the inclusion of NASA forecasts for sustained use by energy utilities nationwide in a variety of load forecasting tools. In addition, Battelle has consulted with energy companies nationwide to document their information needs for long-term planning, in light of climate change and regulatory impacts.

Lough, G.↗
DOE OSTI2020

Resolving Nanoscopic and Mesoscopic Heterogeneity of Fluorinated Species in Battery Solid-Electrolyte Interphases by Cryogenic Electron Microscopy

The stability of lithium batteries is tied to the physicochemical properties of the solid-electrolyte interphase (SEI). Owing to the difficulty in characterizing this sensitive interphase, the nanoscale distribution of SEI components is poorly understood. Here, we use cryogenic scanning transmission electron microscopy (cryo-STEM) to map the spatial distribution of SEI components across the metallic Li anode. We reveal that LiF, an SEI component widely believed to play an important role in battery passivation, is absent within the compact SEI film (~15 nm); instead, LiF particles (100–400 nm) precipitate across the electrode surface. We term this larger length scale as the indirect SEI regime. On the basis of these observations, we conclude that LiF cannot be a dominant contribution to anode passivation nor does it influence Li+ transport across the compact SEI film. We refine the traditional SEI structure derived from ensemble-averaged characterizations and nuance the role of SEI components on battery performance.

25 ENERGY STORAGE↗
NASA NTRS2015

Automatic Speech Acquisition and Recognition for Spacesuit Audio Systems

NASA has a widely recognized but unmet need for novel human-machine interface technologies that can facilitate communication during astronaut extravehicular activities (EVAs), when loud noises and strong reverberations inside spacesuits make communication challenging. WeVoice, Inc., has developed a multichannel signal-processing method for speech acquisition in noisy and reverberant environments that enables automatic speech recognition (ASR) technology inside spacesuits. The technology reduces noise by exploiting differences between the statistical nature of signals (i.e., speech) and noise that exists in the spatial and temporal domains. As a result, ASR accuracy can be improved to the level at which crewmembers will find the speech interface useful. System components and features include beam forming/multichannel noise reduction, single-channel noise reduction, speech feature extraction, feature transformation and normalization, feature compression, and ASR decoding. Arithmetic complexity models were developed and will help designers of real-time ASR systems select proper tasks when confronted with constraints in computational resources. In Phase I of the project, WeVoice validated the technology. The company further refined the technology in Phase II and developed a prototype for testing and use by suited astronauts.

Ye, Sherry↗
NASA NTRS1991

Temporally and spatially resolved flow in a two-stage axial compressor. II - Computational assessment

Fluid dynamics of turbomachines are complicated due to aerodynamic interactions between rotors and stators. It is necessary to understand the aerodynamics associated with these interactions in order to design turbomachines that are both light and compact as well as reliable and efficient. The current study uses an unsteady, thin-layer Navier-Stokes zonal approach to investigate the unsteady aerodyamics of a multistage compressor. Relative motion between rotors and stators is made possible by use of systems of patched and overlaid grids. Results have been computed for a 2 1/2-stage compressor configuration. The numerical data compares well with experimental data for surface pressures and wake data. In addition, the effect of grid refinement on the solution is studied.

Gundy-Burlet, K. L.↗
DOE OSTI2024

Overlooked cooling effects of albedo in terrestrial ecosystems

Radiative forcing (RF) resulting from changes in surface albedo is increasingly recognized as a significant driver of global climate change but has not been adequately estimated, including by Intergovernmental Panel on Climate Change (IPCC) assessment reports, compared with other warming agents. Here, we first present the physical foundation for modeling albedo-induced RF and the consequent global warming impact (GWI Δα ). We then highlight the shortcomings of available current databases and methodologies for calculating GWI Δα at multiple temporal scales. There is a clear lack of comprehensive in situ measurements of albedo due to sparse geographic coverage of ground-based stations, whereas estimates from satellites suffer from biases due to the limited frequency of image collection, and estimates from earth system models (ESMs) suffer from very coarse spatial resolution land cover maps and associated albedo values in pre-determined lookup tables. Field measurements of albedo show large differences by ecosystem type and large diurnal and seasonal changes. As indicated from our findings in southwest Michigan, GWI Δα is substantial, exceeding the RF Δα values of IPCC reports. Inclusion of GWI Δα to landowners and carbon credit markets for specific management practices are needed in future policies. We further identify four pressing research priorities: developing a comprehensive albedo database, pinpointing accurate reference sites within managed landscapes, refining algorithms for remote sensing of albedo by integrating geostationary and other orbital satellites, and integrating the GWI Δα component into future ESMs.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1990

Temporally and spatially resolved flow in a two-stage axial compressor. Part 2: Computational assessment

Fluid dynamics of turbomachines are complicated due to aerodynamic interactions between rotors and stators. It is necessary to understand the aerodynamics associated with these interactions in order to design turbomachines that are both light and compact as well as reliable and efficient. The current study uses an unsteady, thin-layer Navier-Stokes zonal approach to investigate the unsteady aerodynamics of a multi-stage compressor. Relative motion between rotors and stators is made possible by use of systems of patched and overlaid grids. Results have been computed for a 2 1/2-stage compressor configuration. The numerical data compares well with experimental data for surface pressures and wake data. In addition, the effect of grid refinement on the solution is studied.

Gundy-Burlet, Karen L.↗
DOE OSTI2020

STAIR 2.0: A Generic and Automatic Algorithm to Fuse Modis, Landsat, and Sentinel-2 to Generate 10 m, Daily, and Cloud-/Gap-Free Surface Reflectance Product

Remote sensing datasets with both high spatial and high temporal resolution are critical for monitoring and modeling the dynamics of land surfaces. However, no current satellite sensor could simultaneously achieve both high spatial resolution and high revisiting frequency. Therefore, the integration of different sources of satellite data to produce a fusion product has become a popular solution to address this challenge. Many methods have been proposed to generate synthetic images with rich spatial details and high temporal frequency by combining two types of satellite datasets—usually frequent coarse-resolution images (e.g., MODIS) and sparse fine-resolution images (e.g., Landsat). In this paper, we introduce STAIR 2.0, a new fusion method that extends the previous STAIR fusion framework, to fuse three types of satellite datasets, including MODIS, Landsat, and Sentinel-2. In STAIR 2.0, input images are first processed to impute missing-value pixels that are due to clouds or sensor mechanical issues using a gap-filling algorithm. The multiple refined time series are then integrated stepwisely, from coarse- to fine- and high-resolution, ultimately providing a synthetic daily, high-resolution surface reflectance observations. We applied STAIR 2.0 to generate a 10-m, daily, cloud-/gap-free time series that covers the 2017 growing season of Saunders County, Nebraska. Moreover, the framework is generic and can be extended to integrate more types of satellite data sources, further improving the quality of the fusion product. View Full-Text

47 OTHER INSTRUMENTATION↗