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At least 1,351 records · Page 75

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DOE OSTI2025

Data-Driven Recommendation of Optimal Tuning Scheme for Range-Separated Hybrid Functionals in Solution-Phase UV/Vis Absorption Energy Prediction

Time-dependent density functional theory (TDDFT) combined with range-separated hybrid (RSH) functionals and a tuned range-separation parameter γ offers a computationally economical approach for high-throughput excited- state property predictions. The γ-tuning procedure in the gas phase is well established. However, no agreement on the best γ- tuning procedure has been made when considering the solvent effect with implicit solvent models like the polarizable continuum model (PCM). To answer that question, this study created a diverse dataset with 937 molecules with experimental solutionphase UV/vis absorption spectra. Three γ-tuning methods, the gasphase γ-tuning (GPγT), the partial vertical γ-tuning (PVγT), and the strict vertical γ-tuning (SVγT), were evaluated for the ωPBEh functional over the entire dataset. Additional benchmarks are done for the optimally tuned screened range-separated hybrid combined with the PCM approach (SRSH-PCM) and the solvation-mediated tuning procedure (sol-med-OT). Our findings revealed that the optimal γ-values obtained by the PVγT and the SVγT are significantly smaller than the GPγT. This trend holds consistently across all molecules in our dataset, and we explained the origin of this phenomenon. TDDFT calculations with PVγTand SVγT-tuned γ-values and default global Fock exchange fraction achieve superior performance compared to those using GPγTtuned or default γ and slightly outperform SRSH-PCM and sol-med-OT with similar or lesser computational cost. Furthermore, we found that the smaller γ-values from SVγT captured the expected 1/(εR) asymptotic behavior in the solution phase, resulting in accurate prediction of solution-phase CT excitations, consistent with the screened asymptote behavior encoded in SRSH-PCM. These results show that SVγT is the best scheme for high-throughput UV/vis absorption spectrum calculations using the ωPBEh functional from a data-driven perspective.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Field Performance of R-1234yf Heat Pump Water Heaters

Heat pump water heaters (HPWH) provide a resource for increasing water heating efficiency in U.S. residences. Electric HPWHs have traditionally utilized R-134a as the refrigerant in the vapor-compression cycle; however, this refrigerant is undesirable long-term due to its high global warming potential. For HPWHs, low global warming potential refrigerants such as R-1234yf may offer comparable performance, but the evaluation of these systems has been limited to laboratory settings. This study provides field evaluations of off-the-shelf HPWHs that had their factory R-134a refrigerant replaced with an optimized charge of R-1234yf. The field evaluation consisted of R-1234yf HPWHs at two occupied field sites and two unoccupied, simulated lab homes. At the two residential field sites with occupants, the R-1234yf HPWHs operated issue-free for the 18-month field trial, and the home occupants perceived no change in HPWH performance relative to their prior R-134a HPWHs. At the lab homes, under simulated hot water draws, the average daily operating efficiency of the R-1234yf HPWH was within 2% of the baseline R-134a HPWHs.

42 ENGINEERING↗

DOE OSTI2022

Quantum Local Search with the Quantum Alternating Operator Ansatz

We present a new hybrid, local search algorithm for quantum approximate optimization of constrained combinatorial optimization problems. We focus on the Maximum Independent Set problem and demonstrate the ability of quantum local search to solve large problem instances on quantum devices with few qubits. This hybrid algorithm iteratively finds independent sets over carefully constructed neighborhoods and combines these solutions to obtain a global solution. We study the performance of this algorithm on 3-regular, Community, and Erdős-Rényi graphs with up to 100 nodes.

Tomesh, Teague↗

DOE OSTI2021

Multi-scale assessment of a grassland productivity model

Grasslands provide many important ecosystem services globally, and projecting grassland productivity in the coming decades will provide valuable information to land managers. Productivity models can be well calibrated at local scales but generally have some maximum spatial scale in which they perform well. Here we evaluate a grassland productivity model to find the optimal spatial scale for parameterization and thus for subsequently applying it in future productivity projections for North America. We also evaluated the model on new vegetation types to ascertain its potential generality. We find the model most suitable when incorporating only grasslands, as opposed to also including agriculture and shrublands, and only in the Great Plains and eastern temperate forest ecoregions of North America. The model was not well suited to grasslands in North American deserts or northwest forest ecoregions. It also performed poorly in agriculture vegetation, likely due to management activities, and shrubland vegetation, likely because the model lacks representation of deep water pools. This work allows us to perform long-term projections in areas where model performance has been verified, with gaps filled in by future modeling efforts.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2011

Challenges at Petascale for Pseudo-Spectral Methods on Spheres (A Last Hurrah?)

Conclusions: a) Proper software abstractions should enable rapid-exploration of platform-specific optimizations/ tradeoffs. b) Pseudo-spectra! methods are marginally viable for at least some classes of petascaie problems. i.e., GPU based machine with good bisection would be best. c) Scalability at exascale is possible, but the necessary resolution will make algorithm prohibitively expensive. Efficient implementations of realistic global transposes are mtricate and tedious in MPI. PS at petascaie requires exploration of a variety of strategies for spreading local and remote communic3tions. PGAS allows far simpler implementation and thus rapid exploration of variants.

Clune, Thomas↗

NASA NTRS2022

The Scientific Importance of Returning Airfall Dust as a Part of Mars Sample Return (MSR)

Dust transported in the martian atmosphere is of intrinsic scientific interest and has relevance for the planning of human missions in the future. The MSR Campaign, as currently designed, presents an important opportunity to return serendipitous, airfall dust. The tubes containing samples collected by the Perseverance rover would be placed in cache depots on the martian surface perhaps as early as 2023–24 for recovery by a subsequent mission no earlier than 2028–29, and possibly as late as 2030–31. Thus, the sample tube surfaces could passively collect dust for multiple years. This dust is deemed to be exceptionally valuable as it would inform our knowledge and understanding of Mars' global mineralogy, surface processes, surface-atmosphere interactions, and atmospheric circulation. Preliminary calculations suggest that the total mass of such dust on a full set of tubes could be as much as 100 mg and, therefore, sufficient for many types of laboratory analyses. Two planning steps would optimize our ability to take advantage of this opportunity: (1) the dust-covered sample tubes should be loaded into the Orbiting Sample container (OS) with minimal cleaning and (2) the capability to recover this dust early in the workflow within an MSR Sample Receiving Facility (SRF) would need to be established. A further opportunity to advance dust/atmospheric science using MSR, depending upon the design of the MSR Campaign elements, may lie with direct sampling and the return of airborne dust.

Monica M. Grady↗

NASA NTRSDate not supplied

PyroCbs from Australia Fires and its Impact Using Satellite Observations from CrIS and TROPOMI and Reanalysis Data

Pyrocumulonimbus (pyroCb) clouds are thunder clouds created by intense heat from the Earth’s surface. They are formed similarly to cumulonimbus clouds, but the intense heat that results in the vigorous updraft comes from fire, either large wildfires or volcanic eruptions. Australia’s unprecedented fire disasters at the end of 2019 to early 2020 emitted huge amounts of carbon monoxide (CO) and fire aerosol particles to the atmosphere, particularly during the pyroCb outbreak that occurred in southeast Australia between 29 December 2019 and 4 January 2020. It was estimated that at least 18 pyroCbs were generated during this episode, and some of them injected ice, smoke, and biomass burning gases above the local tropopause. An unprecedented abundance of H2O and CO in the stratosphere, and the displacement of background ozone (O3) and N2O from rapid ascent of air from the troposphere and lower stratosphere were found from satellite observations. Some other studies also found that the fire emissions and their long-range transport resulted in stratospheric aerosol, temperature, and O3 anomalies after the 2020 Australian bushfires and altered the Antarctic ozone and vortex, posing great impact to local air quality and climate change. Further study on the atmospheric thermodynamic status of atmosphere associated with these pyroCbs, and the change of the cloud properties and trace gases during this unprecedented Australia fires will be made using a new single Field of View (SFOV) Sounder Atmospheric Products (SiFSAP). SiFSAP was developed by NASA using the Cross-track Infrared Sounder (CrIS) and Advanced Technology Microwave Sounder (ATMS) onboard SNPP and JPSS-1, and will soon be available to the public at NASA DAAC. Since this product has a spatial resolution of 15 km at nadir, which is better than most global weather and climate models and other current operational sounding products, a process-oriented analysis of the dynamic transport of CO and fire plumes during this unprecedented fire disasters will be made in this study. Based on a Principal Component Radiative Transfer Model (PCRTM) and an optimized estimation retrieval algorithm, a simultaneously retrieval is made using the whole spectral information measured by CrIS, and the derived SiFSAP include temperature, water vapor, trace gases (such as O3, CO2, CO, CH4 and N2O), cloud properties and surface properties. Use of ATMS together with CrIS allows SiFSAP to get accurate retrieval products under thick pyroCb conditions, and an algorithm to detect pyroCb based on the hyperspectral infrared sounder spectrum from CrIS will be developed and verified. In addition to SiFSAP sounding products, other products like CO, O3, NO2 from TROPOMI, O3 from OMPS will be used for retrospective analysis. The wind fields from the NASA’s Modern-Era Retrospective Analysis for Research and Applications Version-2 (MERRA-2) and ERA5 will be used to characterize the transport, and the SiFSAP temperature and water vapor profiles within and around pyroCbs will be compared with MERRA-2 and ERA5 products.

Xiaozhen (Shawn) Xiong↗

NASA NTRS2024

Global Sensitivity Analysis of Simulated Remote Sensing Polarimetric Observations Over Snow

This study presents a detailed theoretical assessment of the information content of passive polarimetric observations over snow scenes, using a global sensitivity analysis (GSA) method. Conventional sensitivity studies focus on varying a single parameter while keeping all other parameters fixed. In contrast, the GSA correctly addresses the covariance of state parameters across their entire parameter space, hence favoring a more correct interpretation of inversion algorithms and the optimal design of their state vectors. The forward simulations exploit a vector radiative transfer model to obtain the Stokes vector emerging at the top of the atmosphere for different solar zenith angles, when the bottom boundary consists of a vertically resolved snowpack of non-spherical grains. The presence of light-absorbing particulates (LAPs), either embedded in the snow or aloft in the atmosphere above in the form of aerosols, is also considered. The results are presented for a set of wavelengths spanning the visible (VIS), near-infrared (NIR), and shortwave infrared (SWIR) region of the spectrum. The GSA correctly captures the expected, high sensitivity of the reflectance to LAPs in the VIS–NIR and to grain size at different depths in the snowpack in the NIR–SWIR. With adequate viewing geometries, mono-angle measurements of total reflectance in the VIS–SWIR (akin to those of the Moderate Resolution Imaging Spectroradiometer, MODIS) resolve grain size in the top layer of the snowpack sufficiently well. The addition of multi-angle polarimetric observations in the VIS–NIR provides information on grain shape and microscale roughness. The simultaneous sensitivity in the VIS–NIR to both aerosols and snow-embedded impurities can be disentangled by extending the spectral range to the SWIR, which contains information on aerosol optical depth while remaining essentially unaffected when the same particulates are mixed with the snow. Multi-angle polarimetric observations can therefore (i) effectively partition LAPs between the atmosphere and the surface, which represents a notorious challenge for snow remote sensing based on measurements of total reflectance only and (ii) lead to better estimates of grain shape and roughness and, in turn, the asymmetry parameter, which is critical for the determination of albedo. The retrieval uncertainties are minimized when the degree of linear polarization is used in place of the polarized reflectance. The Sobol indices, which are the main metric for the GSA, were used to select the state parameters in retrievals performed on data simulated for multiple instrument configurations. Improvements in retrieval quality with the addition of measurements of polarization, multi-angle views, and different spectral channels reflect the information content, identified by the Sobol indices, relative to each configuration. The results encourage the development of new remote sensing algorithms that fully leverage multi-angle and polarimetric capabilities of modern remote sensors. They can also aid flight planning activities, since the optimal exploitation of the information content of multi-angle measurements depends on the viewing geometry. The better characterization of surface and atmospheric parameters in snow-covered regions advances research opportunities for scientists of the cryosphere and ultimately benefits albedo estimates in climate models.

remote sensing↗

DOE OSTI2026

SENTRA: A Modular Computational Graph Framework for Critical Mineral and Materials Supply Chains: Part I: Network Construction Latent-Quantity Estimation, and Temporal Graph Forecasting

Global supply chains for critical minerals and materials are complex, evolving networks of countries, products, production stages, and trade relationships. Existing analytical approaches are limited by fragmented data and static network representations that do not capture the dynamic production dependencies linking raw materials, intermediate products, and final goods across multiple countries. Trade and production statistics provide only a partial view of domestic production, inventories, and material flows, making it difficult to identify indirect sourcing pathways, hidden dependencies, and embedded foreign exposures. This paper introduces the Supply Chain Exposure Network Tracking and Risk Assessment (SENTRA) framework, a modular graph-based computational framework for constructing, analyzing, and forecasting dynamic supply chain networks. As the first paper in a three-part methodological series, it establishes the computational foundation of SENTRA by constructing a temporal attributed multi-relational graph whose nodes represent product–country pairs and whose edges encode observed trade and within-country value-chain relationships. Statistical estimation and constrained optimization recover latent production, final demand, and product input dependency coefficients while enforcing economic accounting constraints. Graph-derived exposure measures quantify direct, transshipment, value-chain, and multi-hop supply chain dependencies independently of the forecasting model. A temporal graph forecasting architecture based on a relational graph neural network then forecasts the evolution of the graph under mass-balance constraints with distribution-free conformal uncertainty quantification. Validation on the global aluminum supply chain shows that the learned graph representations recover economically meaningful supply chain structure, accurately forecast out-of-sample trade relationships, and produce well-calibrated prediction intervals. Subsequent papers apply this computational foundation to exposure assessment, disruption analysis, and scenario-based policy analysis, and extend the framework to multimaterial supply chain modeling and decision support.

36 MATERIALS SCIENCE↗

NASA NTRSDate not supplied

Metadata Entry Optimization for NASA's Biological Institutional Scientific Collection (NBISC)

The NASA Biological Institutional Sample Collection (NBISC) at NASA’s Ames Research Center is a critical resource housing non-human samples collected from spaceflight missions and ground analog studies, primarily consisting of specimens from rats, mice, and select microbes. The primary objective of NBISC is to systematically receive, document, preserve, and facilitate access to these samples for the global scientific community. NBISC promotes international collaboration and maximizes the return on investment for precious tissues from spaceflight and analog experiments. Researchers can request physical samples through an online request form and subsequent written proposal review process. This study addresses two core research objectives: streamlining the NBISC sample lifecycle processes and strategizing for managing an influx of 50,000 tissue samples from a series of cosmic radiation analog experiments carried out at the NASA Space Radiation Laboratory (NSRL) by Drs. Eleanor Chang (Lawrence Berkeley Laboratory) and Polly Blakely (SRI). The Chang/Blakely studies investigated Harderian gland (HG) tumorigenesis in mice exposed to low dose and LET radiation comprising 8 different exposure protocols in over 4000 mice. NBISC sample metadata is stored in a Laboratory Information Management System (SLIMS). To streamline sample data entry, we customize python scripts using information extracted from the individual experimental protocols. The scripts automate entry into multiple SLIMS data fields including protocol name, unique sample barcode, tissue and sub-tissue information, freezer location, sample preservation method, etc. The semi-automated procedure significantly decreases the time spent on data entry by several orders of magnitude. Automation and data organization are essential, as they free up time for curation and promotion of the collection which, in turn, increase the accessibility of samples to the broader research community. NBISC benefits from streamlined data ingestion, and the methodologies developed here are applicable to other projects which use SLIMS including the NASA Biospecimen Sharing Program and GeneLab. As of Fall 2023, plans include transferring sample data from SLIMS to public facing repositories (OSDR and NLSP), expanding the reach of the Chang/Blakely sample collection. The Human Research Program Space Radiation Element plans to transfer non-human tissues from many more investigations to NBISC in the coming year.

Sample Repository↗

NASA NTRSDate not supplied

Metadata Entry Optimization For NASA's Biological Institutional Scientific Collection (NBISC)

Biospecimen↗

DOE OSTI2025

Robust Optimal Control of Inverter-Based Resources Under Grid-Forming Operation

In this paper, we propose and solve a robust control problem for inverter-based resources under grid-forming operation to regulate the voltage and frequency. One major challenge is to mitigate the effect of unmeasurable load current disturbance, grid and load parametric uncertainties. Moreover, strong coupling between the state variables on both the AC and DC sides, as well as between the modulating control input and the frequency impose additional challenges. To address these challenges, first, a robust control problem is solved at the high level via transformation into an equivalent, but more tractable, optimal control problem. Then, in the middle layer a voltage control law is designed on the one side, and a frequency control law on the other side. Finally, an inverter filter current controller is designed to complete the controller design. Theoretical results are derived to provide stability guarantees for the resulting closed-loop system. Specifically, we show that the inverter current injection error is dissipative, the frequency error is semi-globally asymptotically stable, and the inverter terminal voltage error is globally asymptotically stable, all with provided sufficient conditions. Here, numerical simulation experiments are used to validate the theoretical claims. Furthermore, the developed controller is compared with existing work in literature to show the efficacy of the proposed approach.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Benchmarking of Solar Irradiance Nowcast Performance Derived from All-Sky Imagers

Fluctuations of the incoming solar irradiance impact the power generation from photovoltaic and concentrating solar thermal power plants. Accurate solar nowcasting becomes necessary to detect these sudden changes of generated power and to provide the desired information for optimal exploitation of solar systems. In the framework of the International Energy Agency's Photovoltaic Power Systems Program Task 16, a benchmarking exercise has been conducted relying on a bouquet of solar nowcasting methodologies by all-sky imagers (ASI). In this paper, four ASI systems nowcast the Global Horizontal Irradiance (GHI) with a time forecast ranging from 1 to 20 min during 28 days with variable cloud conditions spanning from September to November 2019 in southern Spain. All ASIs demonstrated their ability to accurately nowcast GHI, with RMSE ranging from 6.9% to 18.1%. Under cloudy conditions, all ASIs' nowcasts outperform the persistence models. Under clear skies, three ASIs are better than persistence. Discrepancies in the observed nowcasting performance become larger at increasing forecast horizons. The findings of this study highlight the feasibility of ASIs to reliably nowcast GHI at different sky conditions, time intervals and horizons. Such nowcasts can be used either to estimate solar power at distant times or detect sudden GHI fluctuations.

all-sky imagers↗

DOE OSTI2021

Observation of fully detached divertor integrated with improved core confinement for tokamak fusion plasmas

Integration of divertor detachment with a high-performance (β N ~ 3, β p > 2, H 98 ~ 1.5) core plasma has been demonstrated in DIII-D high-β p (poloidal beta) plasmas associated with a sustained core internal transport barrier (ITB) and an H-mode edge transport barrier (ETB). Such good core-edge integration has been achieved for both neon and nitrogen seeding, for both favorable and unfavorable B-field directions, independently from the impurity puffing locations, though these variations play important roles on divertor characteristics. Compared to the standard H-mode plasmas, the high-β p plasma exhibits a much wider window of detachment compatible with high confinement core. Fully detached divertor plasmas with low plasma temperature (Te < 5 eV), low particle flux, and low heat flux across the entire divertor target plate were obtained by using nitrogen seeding. This detached high-β p plasma is compatible with a newly developed detachment control system which can help optimize the nitrogen gas flow rate. Several features, i.e., the high edge safety factor in the high-β p scenario, impurity injection, closed divertor and reduced heating power requirement due to the high confinement, facilitate the achievement of full divertor detachment at lower density. Instead of degrading global performance, the divertor detachment facilitates the access to an even stronger ITB at large radius with a relatively weak ETB through self-organized synergy between ITB and ETB, leading to sustained high confinement. The strengthening of the large-radius ITB compensates for the ETB degradation associated with divertor detachment. In addition, a weak ETB naturally has smaller edge localized modes (ELMs). In particular, with neon injection, a long-period no-ELM H-mode phase has been achieved simultaneously with high-performance core and partially detached divertor plasmas. Furthermore, these results demonstrate the possibility of integrating excellent core plasma performance with an effective divertor solution, an essential step toward steady-state operation of reactor-grade plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Quantum process tomography of a Mølmer-Sørensen gate via a global beam

Here, we present a framework for quantum process tomography of two-ion interactions that leverages modulations of the trapping potential and composite pulses from a global laser beam to achieve individual-ion addressing. Tomographic analysis of identity and delay processes reveals dominant error contributions from laser decoherence and slow qubit frequency drift during the tomography experiment. We use this framework on two co-trapped 40 Ca + ions to analyze both an optimized and an overpowered Mølmer–Sørensen gate and to compare the results of this analysis to a less informative Bell-state tomography measurement and to predictions based on a simplified noise model. These results show that the technique is effective for the characterization of two-ion quantum processes and for the extraction of meaningful information about the errors present in the system. The experimental convenience of this method will allow for more widespread use of process tomography for characterizing entangling gates in trapped-ion systems.

quantum computing↗

DOE OSTI2025

PV Degradation Modeling: Applying Geospatial Workflows with "PVDeg"

Accurate degradation modeling is essential for predicting photovoltaic (PV) module performance, estimating longevity and informing design decisions. With degradation rates varying significantly by location, geospatial analysis is critical for PV and broader applications, such as agrivoltaics, weathering and environmental data analysis. This work presents PVDeg, an open-source tool designed for geospatial degradation analysis. PVDeg integrates meteorological data from global sources, including the National Solar Radiation Database (NSRDB) and Photovoltaic Geographical Information System (PVGIS), with degradation models. The toolkit enables users to customize geospatial workflows by integrating weather data, material parameters, and user-defined Python functions. It facilitates accelerated downloads of NSRDB and PVGIS datasets and optimizes geospatial point selection to preserve data density in regions of interest. Additionally, PVDeg provides a local database for storage and spatial queries, supporting large-scale analyses without the need for high-performance computing (HPC) resources. PVDeg provides a foundational workflow that extends its utility beyond PV applications, enabling researchers to analyze geospatial processes across discipline.

14 SOLAR ENERGY↗

NASA NTRS1990

Microspacecraft and Earth observation: Electrical field (ELF) measurement project

The Utah State University space system design project for 1989 to 1990 focuses on the design of a global electrical field sensing system to be deployed in a constellation of microspacecraft. The design includes the selection of the sensor and the design of the spacecraft, the sensor support subsystems, the launch vehicle interface structure, on board data storage and communications subsystems, and associated ground receiving stations. Optimization of satellite orbits and spacecraft attitude are critical to the overall mapping of the electrical field and, thus, are also included in the project. The spacecraft design incorporates a deployable sensor array (5 m booms) into a spinning oblate platform. Data is taken every 0.1 seconds by the electrical field sensors and stored on-board. An omni-directional antenna communicates with a ground station twice per day to down link the stored data. Wrap-around solar cells cover the exterior of the spacecraft to generate power. Nine Pegasus launches may be used to deploy fifty such satellites to orbits with inclinations greater than 45 deg. Piggyback deployment from other launch vehicles such as the DELTA 2 is also examined.

Olsen, Tanya↗

NASA NTRS2016

Construction of a Matched Global Cloud and Radiance Product from LEO/GEO and EPIC Observations to Estimate Daytime Earth Radiation Budget from DSCOVR

With the launch of the Deep Space Climate Observatory (DSCOVR), new estimates of the daytime Earth radiation budget can be computed from a combination of measurements from the two Earth-observing sensors onboard the spacecraft, the Earth Polychromatic Imaging Camera (EPIC) and the National Institute of Standards and Technology Advanced Radiometer (NISTAR). Although these instruments can provide accurate top-of-atmosphere (TOA) radiance measurements, they lack sufficient resolution to provide details on small-scale surface and cloud properties. Previous studies have shown that these properties have a strong influence on the anisotropy of the radiation at the TOA, and ignoring such effects can result in large TOA-flux errors. To overcome these effects, high-resolution scene identification is needed for accurate Earth radiation budget estimation. Selected radiance and cloud property data measured and derived from several low earth orbit (LEO, including NASA Terra and Aqua MODIS, NOAA AVHRR) and geosynchronous (GEO, including GOES (east and west), METEOSAT, INSAT-3D, MTSAT-2, and HIMAWARI-8) satellite imagers were collected to create hourly 5-km resolution global composites of data necessary to compute angular distribution models (ADM) for reflected shortwave (SW) and longwave (LW) radiation. The satellite data provide an independent source of radiance measurements and scene identification information necessary to construct ADMs that are used to determine the daytime Earth radiation budget. To optimize spatial matching between EPIC measurements and the high-resolution composite cloud properties, LEO/GEO retrievals within the EPIC fields of view (FOV) are convolved to the EPIC point spread function (PSF) in a similar manner to the Clouds and the Earth's Radiant Energy System (CERES) Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product. Examples of the merged LEO/GEO/EPIC product will be presented, describing the chosen radiance and cloud properties and details of how data from the multi-satellite measurements are selected.

Duda, David P.↗