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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 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Assessing Climate Change-Induced Variability in Generation Potential and Droughts of Renewable Energy Systems in India

Solar photovoltaic (PV) and wind energy systems are crucial for decarbonizing the electricity sector and achieving climate goals. However, these systems are weather-dependent, and ignoring the potential changes in their generation levels due to climate change could compromise achieving climate targets and meeting future electricity demand. This study evaluates the impact of climate change on the generation potential of wind and solar PV systems in India for three future periods, 2030 (2021-2040), 2050 (2041-2060), and 2070 (2061-2080) compared to the baseline year 2000 (1991-2010), under three emission scenarios: SSP245, SSP370, and SSP585. Solar PV generation levels consistently decline (up to 10 %) across all regions and scenarios. Wind energy shows more pronounced variability (-20 % to 30 %). The South and Southeastern regions of India show improvements in wind potential across all scenarios and time periods. This study also investigated the projected changes in the generation droughts of both energy systems. For solar PV, drought days increase across most regions (exceeding 500 days under SSP370 across the 20-year period). In contrast, wind energy sees a reduction in drought days, especially in parts of South and Southeast India (declines exceeding 50 days across different scenarios). For both energy systems, the patterns of generation drought and generation potential are similar, and indicate that Western and Northern India may be less favorable for the future expansion of solar PV and wind energy, respectively. These results highlight the need to account for the potential impacts in future capacity planning.

14 SOLAR ENERGY↗
DOE OSTI2016

SU-F-R-42: Association of Radiomic and Metabolic Tumor Volumes in Radiation Treatment of Glioblastoma Multiforme

Purpose: High-throughput extraction of imaging and metabolomic quantitative features from MRI and MR Spectroscopy Imaging (MRSI) of Glioblastoma Multiforme (GBM) results in tens of variables per patient. In radiotherapy (RT) of GBM, the relevant metabolic tumor volumes (MTVs) are related to aberrant levels of N-acetyl Aspartate (NAA) and Choline (Cho). Corresponding Clinical Target Volumes (CTVs) for RT planning are based on Contrast Enhancing T1-weighted MRI (CE-T1w) and T2-weighted/Fluid Attenuated Inversion Recovery (FLAIR) MRI. The objective is to build a framework for investigation of associations between imaging, CTV, and MTV features better understanding of the underlying information in the CTVs and dependencies between these volumes. Methods: Necrotic portions, enhancing lesion and edema were manually contoured on T1w/T2w images for 17 GBM patients. CTVs and MTVs for NAA (MTV{sub NAA}) and Cho (MTV{sub Cho}) were constructed. Tumors were scored categorically for ten semantic imaging traits by neuroradiologist. All features were investigated for redundancy. Two-way correlations between imaging and RT/MTV features were visualized as heat maps. Associations between MTV{sub NAA}, MTV{sub Cho} and imaging features were studied using Spearman correlation. Results: 39 imaging features were computed per patient. Half of the imaging traits were replaced with automatically extracted continuous variables. 21 features were extracted from MTVs/CTVs. There were a high number (43) of significant correlations of imaging with CTVs/MTV{sub NAA} while very few (10) significant correlations were with CTVs/MTV{sub Cho}. MTV{sub NAA} was found to be closely associated with MRI volumes, MTV{sub Cho} remains elusive for characterization with imaging. Conclusion: A framework for investigation of co-dependency between MRI and RT/metabolic features is established. A series of semantic imaging traits were replaced with automatically extracted continuous variables. The approach will allow for exploration of relationships between sizes and intersection of imaging features of tumors, RT volumes, metabolite concentrations and comparing those to therapy outcome, quality of life evaluation and overall survival rate. This publication was supported by Grant 10BN03 from Bankhead Coley Cancer Research Program, R01EB000822, R01EB016064, and R01CA172210 from the National Institutes of Health, and Indo-US Science & Technology Forum award #20-2009. Bhaswati Roy received financial assistance from University Grant Commission, New Delhi, India.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Train Like a (Var)Pro: Efficient Training of Neural Networks with Variable Projection

Deep neural networks (DNNs) have achieved state-of-the-art performance across a variety of traditional machine learning tasks, e.g., speech recognition, image classification, and segmentation. The ability of DNNs to efficiently approximate high-dimensional functions has also motivated their use in scientific applications, e.g., to solve partial differential equations and to generate surrogate models. In this paper, we consider the supervised training of DNNs, which arises in many of the above applications. We focus on the central problem of optimizing the weights of the given DNN such that it accurately approximates the relation between observed input and target data. Devising effective solvers for this optimization problem is notoriously challenging due to the large number of weights, nonconvexity, data sparsity, and nontrivial choice of hyperparameters. To solve the optimization problem more efficiently, we propose the use of variable projection (VarPro), a method originally designed for separable nonlinear least-squares problems. Our main contribution is the Gauss--Newton VarPro method (GNvpro) that extends the reach of the VarPro idea to nonquadratic objective functions, most notably cross-entropy loss functions arising in classification. These extensions make GNvpro applicable to all training problems that involve a DNN whose last layer is an affine mapping, which is common in many state-of-the-art architectures. In our four numerical experiments from surrogate modeling, segmentation, and classification, GNvpro solves the optimization problem more efficiently than commonly used stochastic gradient descent (SGD) schemes. Finally, GNvpro finds solutions that generalize well, and in all but one example better than well-tuned SGD methods, to unseen data points.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Magellan/M2FS and MMT/Hectochelle Spectroscopy of Dwarf Galaxies and Faint Star Clusters within the Galactic Halo*

We present spectroscopic data for 16,369 stellar targets within and/or toward 38 dwarf spheroidal galaxies and faint star clusters within the Milky Way halo environment. All spectra come from observations with the multiobject, fiber-fed echelle spectrographs M2FS at the Magellan/Clay telescope or Hectochelle at the MMT, reaching a typical limiting magnitude G ≲ 21. Data products include processed spectra from all observations and catalogs listing estimates—derived from template model fitting—of line-of-sight velocity (median uncertainty 1.4 km s –1 ) effective temperature (255 K), (base-10 logarithm of) surface gravity (0.59 dex in cgs units), [Fe/H] (0.4 dex) and [Mg/Fe] (0.27 dex) abundance ratios. The sample contains multiepoch measurements for 3720 sources, with up to 15 epochs per source, enabling studies of intrinsic spectroscopic variability. The sample contains 6087 likely red giant stars (based on surface gravity), and 4492 likely members (based on line-of-sight velocity and Gaia-measured proper motion) of the target systems. The number of member stars per individual target system ranges from a few, for the faintest systems, to ~850 for the most luminous. For most systems, our new samples extend over wider fields than have previously been observed; of the likely members in our samples, 820 lie beyond 2 times the projected half-light radius of their host system, and 42 lie beyond 5 R half .

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Advancing global change biology through experimental manipulations: Where have we been and where might we go?

Abstract This commentary summarizes the publication history of Global Change Biology for works on experimental manipulations over the past 25 years and highlights a number of key publications. The retrospective summary is then followed by some thoughts on the future of experimental work as it relates to mechanistic understanding and methodological needs. Experiments for elevated CO 2 atmospheres and anticipated warming scenarios which take us beyond historical analogs are suggested as future priorities. Disturbance is also highlighted as a key agent of global change. Because experiments are demanding of both personnel effort and limited fiscal resources, the allocation of experimental investments across Earth's biomes should be done in ecosystems of key importance. Uncertainty analysis and broad community consultation should be used to identify research questions and target biomes that will yield substantial gains in predictive confidence and societal relevance. A full range of methodological approaches covering small to large spatial scales will continue to be justified as a source of mechanistic understanding. Nevertheless, experiments operating at larger spatial scales encompassing organismal, edaphic, and environmental diversity of target ecosystems are favored, as they allow for the assessment of long‐term biogeochemical feedbacks enabling a full range of questions to be addressed. Such studies must also include adequate investment in measurements of key interacting variables (e.g., water and nutrient availability and budgets) to enable mechanistic understanding of responses and to interpret context dependency. Integration of ecosystem‐scale manipulations with focused process‐based manipulations, networks, and large‐scale observations will aid more complete understanding of ecosystem responses, context dependence, and the extrapolation of results. From the outset, these studies must be informed by and integrated with ecosystem models that provide quantitative predictions from their embedded mechanistic hypotheses. A true two‐way interaction between experiments and models will simultaneously increase the rate and robustness of Global Change research.

Hanson, Paul J.↗
DOE OSTI2020

Final Technical Report for project entitled Highly Active, Durable, and Ultra-Low PGM NSTF Thin Film ORR Catalysts and Support

In this project, the objective was to develop new oxygen reduction reaction (ORR) electrocatalysts for proton exchange membrane fuel cells (PEMFCs) which could exceed all of the Department of Energy (DOE) 2020 targets listed in DE-FOA-0001224, Subtopic 1b, Table I. The expected outcome was development of one or more electrocatalysts which are substantially improved over the current state-of-the-art in terms of overall activity, durability, and cost, and are suitable for automotive traction and stationary fuel cell applications. This report summarizes this project’s progress towards meeting the stated objectives and includes a summary of key findings and conclusions. The development activities towards new highly active and durable thin film electrocatalysts has led to the discovery of several electrocatalysts which approached or exceeded several DOE 2020 targets for activity, durability, and performance in proton exchange membrane fuel cell (membrane electrode assemblies (MEAs). In this project, electrocatalyst development focused on systematic physical and electrochemical characterization of electrocatalyst activity, durability, and performance in MEAs as a function of electrocatalyst fabrication, compositional and structural variables. The project approach was to develop relationships between the catalyst functional responses (activity, durability and performance) with catalyst physical properties and catalyst fabrication methods. Additionally, the thin film catalysts were integrated onto the unique and durable 3M Nanostructured Thin Film (NSTF) support, consisting of arrays of self-assembled organic crystalline whiskers. The catalysts were evaluated against the project targets via extensive electrochemical characterization in MEA format at 3M, advanced structural and compositional microscopy at Oak Ridge National Laboratory (ORNL), and atomic structure analysis via XAFS at Argonne National Laboratory (ANL). The extensive electrochemical and physical characterization resulted in development of several trends which correlate the catalysts’ electrochemical properties to their physical properties, including composition, structure, and method of fabrication. The development was guided by density functional theory (DFT) modeling at Purdue University and kinetic Monte Carlo (kMC) modeling at Johns Hopkins University. The catalyst simulations provided key insights into the observed experimental activity and durability trends, and additionally were utilized to assess new electrocatalyst concepts prior to or coincident with physical catalyst development. This development has led to several electrocatalyst candidates with activity and durability which approach or exceed DOE targets. One class of catalysts, based on nm-scale thin layers of Pt on Ir, met or exceeded 6 of the 6 DOE targets the project addressed.

08 HYDROGEN↗
DOE OSTI2018

Universal protection against influenza infection by a multidomain antibody to influenza hemagglutinin

Broadly neutralizing antibodies against highly variable pathogens have stimulated the design of vaccines and therapeutics. We report the use of diverse camelid single-domain antibodies to influenza virus hemagglutinin to generate multidomain antibodies with impressive breadth and potency. Multidomain antibody MD3606 protects mice against influenza A and B infection when administered intravenously or expressed locally from a recombinant adeno-associated virus vector. Crystal and single-particle electron microscopy structures of these antibodies with hemagglutinins from influenza A and B viruses reveal binding to highly conserved epitopes. Collectively, our findings demonstrate that multidomain antibodies targeting multiple epitopes exhibit enhanced virus cross-reactivity and potency. In combination with adeno-associated virus–mediated gene delivery, they may provide an effective strategy to prevent infection with influenza virus and other highly variable pathogens.

Laursen, Nick S. (ORCID:0000000275122649)↗
NASA NTRS1976

Variability of wetland reflectance and its effect on automatic catergorization of satellite imagery

The author has identified the following significant results. A technique for training automated analysis of satellite multispectral data based on in situ measurements of target reflectance was tested and applied in delineating cover communities in Delaware's tidal wetlands. Land cover categorization of data from the same overpass in four test wetland areas was carried out using a four category classification system. The tests indicate that training data based on in situ reflectance measurements and atmospheric correction of LANDSAT data can produce comparable accuracy of categorization to that achieved using more conventional relative radiance training. Analysis of the four wetlands cover categories (salt marsh cordgrass, salt hay, water, and unvegetated tidal flat) produced average categorization accuracies of 82.1% by conventional relative radiance training and 81.4% by use of in situ reflectance measurements.

Klemas, V.↗
NASA NTRSDate not supplied

Variability in Mt. Sharp Group Bedrock as Seen By ChemCam Passive and Active Spectra

The Curiosity rover landed in Gale crater in August 2012 and has since been travelling up the central sedimentary mound known as Mt. Sharp. The ChemCam instrument on Curiosity was designed primarily for the use of Laser Induced Breakdown Spectroscopy (LIBS), where a laser ablates a small amount of material from the target and the spectrum of the resulting plasma yields elemental abundance data. ChemCam’s three spectrometers range from 240-905 nm and can also take passive spectra (without the use of the laser). The spectral range ChemCam passive spectra observe is sensitive to charge-transfer and crystal field absorptions related to iron-bearing minerals. In the first 2934 sols of Curiosity’s mission, 9,400 passive spectra were taken of bedrock targets in Mt. Sharp’s Murray and Carolyn Shoemaker formations. We examine these spectra using spectral slope/ratio and band depth calculations as well as Principal Component Analysis (PCA). For the first time, paired passive spectra and LIBS elemental abundances are compared on a large scale. Finally, CheMin data are compared to ChemCam passive observations to understand sources of spectral variability.

H T Manelski↗
DOE OSTI2024

Situational awareness-enhancing community-level load mapping with opportunistic machine learning

Motivated by present and forthcoming challenges in the adoption and integration of distributed renewable energy, we develop a machine learning (ML) approach that builds short-fuse mappings connecting the occasionally-unobservable true load in one target community with information-rich signals collected from relatively more instrumented reference communities. Our setting is inspired by and tailored to target communities with significant unobservable behind-the-meter solar generation, where true load (a relatively well-behaved quantity of interest to grid operators) is hard to discern during daytime due to insufficient instrumentation and/or privacy reasons, but that can be related to reference communities with low unobservable distributed variable generation or with sufficient instrumentation. The developed mapping, herein realized with Support Vector Machine regression, is built using nighttime data from all communities, when their distributed generation is low or zero. Our ML algorithm opportunistically learns to correlate signals of interest and then is operationally used the next day to shed light into target community load evolution. The mapping is subsequently rebuilt, rolling its short-fuse scope perpetually forward in time. Here, we demonstrate the efficacy of our approach on nine synthetically generated topologies and associated timeseries stemming from real-world data, on which we observe cumulative error performance that yields lower than 10% and 15% daily-averaged mean absolute percentage errors in target community load estimation on more than about 75% and 90% of days, respectively, in multiple yearly evaluations that shed light on long-term performance also under seasonal and one-off effects. The proposed ML-powered methodology can offer grid operators much-improved visibility into a previously obscure space and can also serve as an additional source of information in broader, multi-modal solar disaggregation solutions.

14 SOLAR ENERGY↗
DOE OSTI2020

Optimization-based, property-preserving finite element methods for scalar advection equations and their connection to Algebraic Flux Correction

In this paper, we continue our efforts to exploit optimization and control ideas as a common foundation for the development of property-preserving numerical methods. Here we focus on a class of scalar advection equations whose solutions have fixed mass in a given Eulerian region and constant bounds in any Lagrangian volume. Our approach separates discretization of the equations from the preservation of their solution properties by treating the latter as optimization constraints. This relieves the discretization process from having to comply with additional restrictions and makes stability and accuracy the sole considerations in its design. A property-preserving solution is then sought as a state that minimizes the distance to an optimally accurate but not property-preserving target solution computed by the scheme, subject to constraints enforcing discrete proxies of the desired properties. Furthermore, we consider two such formulations in which the optimization variables are given by the nodal solution values and suitably defined nodal fluxes, respectively. A key result of the paper reveals that a standard Algebraic Flux Correction (AFC) scheme is a modified version of the second formulation obtained by shrinking its feasible set to a hypercube. In conclusion, we present numerical studies illustrating the optimization-based formulations and comparing them with AFC

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Nonlinear control of safety factor gradient in tokamaks using spatially variable electron cyclotron current drives

Active control of plasma properties may be necessary to achieve stable operation of next-generation tokamaks over large time scales. Such control algorithms can regulate the plasma properties to avoid the onset of magnetohydrodynamic (MHD) instabilities. For instance, the global and local properties of the safety factor profile are linked to the onset of neoclassical tearing modes (NTMs). This work proposes a model-based control approach for deterring/delaying NTMs through active modulation of one of the safety factor properties - the gradient of the safety factor profile at a particular rational safety factor surface. In particular, a novel control-oriented model for the local safety factor gradient is developed. The nonlinear control model is governed by a nonautonomous ordinary differential equation that accounts for a given rational safety factor surface’s spatial variation over time. Further, to improve the controllability of the spatially evolving parameter, the control model treats ECH&CD positions, along with noninductive powers, as controllable variables. A nonlinear control algorithm based on feedback linearization with optimization is synthesized to achieve the objective of regulating the safety factor gradient around a given target. The proposed algorithm allocates optimal ECH&CD positions, in addition to auxiliary powers, at each time instant as the rational safety factor surface drifts to locations with a low control authority. Stability guarantees of the proposed control law are also discussed in this work. The proposed algorithm is tested for a DIII-D tokamak scenario in nonlinear simulations carried out using the Control Oriented Transport SIMulator (COTSIM). Both fixed and moving ECH&CD cases are studied, and their outcomes are compared. Simulation results demonstrate that enthusiastic regulation of the safety factor gradient can be achieved during the ramp-up and flat-top phases of tokamak operation in both fixed and moving ECH&CD cases. However, real-time updates of ECH&CD positions can prevent the saturation of auxiliary powers.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Surrogate modelling the Baryonic Universe II: On forward modelling the colours of individual and populations of galaxies

ABSTRACT Among the properties shaping the light of a galaxy, the star formation history (SFH) is one of the most challenging to model due to the variety of correlated physical processes regulating star formation. In this work, we leverage the stellar population synthesis model fsps, together with SFHs predicted by the hydrodynamical simulation IllustrisTNG and the empirical model universemachine, to study the impact of star formation variability on galaxy colours. We start by introducing a model-independent metric to quantify the burstiness of a galaxy formation model, and we use this metric to demonstrate that universemachine predicts SFHs with more burstiness relative to IllustrisTNG. Using this metric and principal component analysis, we construct families of SFH models with adjustable variability, and we show that the precision of broad-band optical and near-infrared colours degrades as the level of unresolved short-term variability increases. We use the same technique to demonstrate that variability in metallicity and dust attenuation presents a practically negligible impact on colours relative to star formation variability. We additionally provide a model-independent fitting function capturing how the level of unresolved star formation variability translates into imprecision in predictions for galaxy colours; our fitting function can be used to determine the minimal SFH model that reproduces colours with some target precision. Finally, we show that modelling the colours of individual galaxies with per cent-level precision demands resorting to complex SFH models, while producing precise colours for galaxy populations can be achieved using models with just a few degrees of freedom.

Chaves-Montero, Jonás (ORCID:0000000295534261)↗
DOE OSTI2016

Applications of Wireless Sensor Networks for Area Coverage in Microgrids

Area coverage is a critical issue which will have a major impact on the sensing quality over targeted regions in wireless sensor networks. This paper studies the area coverage problem (ACP) with non-penetrable obstacles in microgrids, where a sensor cannot be deployed or sensing signals cannot pass through. The target coverage region is discretized in a deployment map representation of non-penetrable obstacles. A probability detection model is utilized to represent sensors with a variable distance coverage. The ACP is formulated as a mixed integer nonlinear programming problem and an iterative process is developed to solve the problem. The microgrid at Illinois Institute of Technology (IL Tech) is used as a practical example. Both the normal and the N-1 contingency deployments of sensors are simulated for optimizing the ACP at the IL Tech microgrid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

History and Evolution of the Johnson Criteria

The Johnson Criteria metric calculates probability of detection of an object imaged by an optical system, and was created in 1958 by John Johnson. As understanding of target detection has improved, detection models have evolved to better model additional factors such as weather, scene content, and object placement. The initial Johnson Criteria, while sufficient for technology and understanding at the time, does not accurately reflect current research into target acquisition and technology. Even though current research shows a dependence on human factors, there appears to be a lack of testing and modeling of human variability.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2023

CSAPR2 Optimized Convective Cell Tracking Data during TRACER

One of the challenges in analyzing convective cell properties is to observe the quick evolution of individual convective cells. While the operational radar data provide a volumetric data set to analyze radar observables of convective precipitation clouds, previous studies also suggested the quick evolution of cell life cycle that might not be captured by conventional radar volume scan strategies that take ~5-7 minutes. Aiming at enhancing our understanding of the links between convective cloud kinematic and microphysical processes as well as life cycles, the Tracking Aerosol Convection Interactions ExpeRiment (TRACER; Jensen et al. 2019) was conducted at Houston, Texas, in 2022. The TRACER campaign deployed the 2nd generation C-band Scanning ARM Precipitation Radar (CSAPR2), which performed frequent updates of range height indicator (RHI) and sector plan position indicator (PPI) scans to track individual convective cells every < 2 minutes, guided by a new cell tracking framework, Multisensor Agile Adaptive Sampling (MAAS; Kollias et al. 2020). This allows for capturing fast-evolving radar observables. We provide the processed CSAPR2 cell tracking data in CfRadial format collected during the TRACER field campaign from June to September 2022. The data files include processed radar variables: noise-masked reflectivity and differential reflectivity corrected for rain attenuation and systematic biases, noise-masked dealiased radial velocity, specific differential phase, locations of target cells (latitude, longitude, radar range), and radar-echo classification. Figure 1 provides an example of a 3D image of CSAPR2 reflectivity from the lowest PPI scan and an RHI scan after data processing.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1976

Observational and theoretical temperatures for a total lunar eclipse

Temperature profiles from seven regions of the moon were recorded during a total eclipse using an infrared radiometer and telescope. The eclipse was visible from beginning to end. Target areas chosen range from mare areas to mountainous highlands. Theoretical temperature curves were calculated using a thermophysical model in which the lunar material properties are variable. These curves are compared with the experimental data. A description of the instrumentation, observations, calibration, signal reduction, and the theoretical model is given. The results show excellent agreement between the observational and theoretical temperatures during the eclipse. The apparent differences between the observed and calculated temperatures during pre- and post-eclipse are minimal after directional radiation is taken into account.

Fountain, W. F.↗
NASA NTRS2003

Environmental Snapshots for Satellite Multi-Angle Aerosol Retrieval Validation During the ACE-Asia Field Campaign

On five occasions spanning the ACE-Asia field experiment in spring 2001, the multi-angle imaging MISR instrument, flying aboard the NASA Earth Observing System s Terra satellite, took quarter-kilometer data over a 400-km-wide swath, coincident with high-quality observations by multiple instruments on two or more participating surface and airborne platforms. The cases capture a range of clean, polluted, and dusty aerosol conditions. They represent some of the best opportunities during ACE- Asia for comparative studies among intensive and extensive aerosol observations in their environmental context. We inter-compare related measurements and discuss the implications of apparent discrepancies for each case, at a level of detail appropriate to the analysis of satellite observations. With a three-stage optical modeling process, we synthesize data from multiple sources into layer-by-layer snapshots that summarize what we know about the state of the atmosphere and surface at key locations during each event, to be used for satellite vicarious calibration and aerosol retrieval validation. Aerosols within a few kilometers of the surface were composed primarily of pollution and Asian dust mixtures, as expected. Accumulation and coarse-mode particle size distributions varied little among the events studied, but column aerosol optical depth changed by more than a factor of four, and the near-surface proportion of dust ranged from about 25% to 50%. The amount of absorbing material in the sub-micron fraction was highest when near-surface winds crossed Beijing and the Korean Peninsula, and was considerably lower for all other cases. Ambiguities remain in segregating size distributions by composition; having simultaneous single scattering albedo measurements at more than a single wavelength would significantly reduce the resulting optical model uncertainties, as would integral constraints from surface and atmospheric radiative flux observations. The consistency of component particle micro-physical properties among the five events, even in this relatively complex aerosol environment, suggests that global, satellite-derived maps of aerosol-air-mass-type extent, combined with targeted in situ measurements, can provide a detailed global picture of aerosol behavior. Further joint satellite and in situ analysis is needed to assess the spatial variability of both intensive and extensive aerosol properties within aerosol air masses in two spatial dimensions.

Kahn, Ralph↗