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NASA NTRS2020

Streaming Instability with Multiple Dust Species – I. Favourable Conditions for the Linear Growth

A recent study suggests that the streaming instability, one of the leading mechanisms for driving the formation of planetesimals, may not be as efficient as previously thought. Under some disc conditions, the growth time-scale of the instability can be longer than the disc lifetime when multiple dust species are considered. To further explore this finding, we use both linear analysis and direct numerical simulations with gas fluid and dust particles tomutually validate and study the unstablemodes of the instability in more detail.We extend the previously studied parameter space by one order of magnitude in both the range of the dust-size distribution [Ts, min, Ts, max] and the total solid-to-gas mass ratio ε and introduce a third dimension with the slope q of the size distribution. We find that the fast-growth regime and the slow-growth regime are distinctly separated in the ε–Ts, max space, while this boundary is not appreciably sensitive to q or Ts, min.With a wide range of dust sizes present in the disc (e.g. Ts, min 10−3), the growth rate in the slow-growth regime decreases as more dust species are considered.With a narrow range of dust sizes (e.g. Ts, max/Ts, min = 5), on the other hand, the growth rate in most of the ε–Ts, max space is converged with increasing dust species, but the fast and the slow growth regimes remain clearly separated. Moreover, it is not necessary that the largest dust species dominate the growth of the unstable modes, and the smaller dust species can affect the growth rate in a complicated way. In any case, we find that the fast-growth regime is bounded by ε 1 or Ts, max 1, which may represent the favourable conditions for planetesimal formation.

Zhaohuan Zhu↗

NASA NTRS2021

Machine Learning Models to Predict Cognitive Impairment of Rodents Subjected to Space Radiation

This research uses machine-learned computational analyses to predict the cognitive performance impairment of rats induced by irradiation. The experimental data in the analyses is from a rodent model exposed to ≤ 15 cGy of individual Galactic Cosmic Radiation (GCR) ions: 4He, 16O, 28Si, 48Ti, or 56Fe, expected for a Lunar or Mars mission. This work investigates rats at a subject-based level and uses performance scores taken before irradiation to predict impairment in Attentional Set-shifting (ATSET) data post-irradiation. Here, the worst performing rats of the control group define the impairment thresholds based on population analyses via cumulative distribution functions, leading to the labeling of impairment for each subject. A significant finding is the exhibition of a dose-dependent increasing probability of impairment for 1 to 10 cGy of 28Si or 56Fe in the Simple Discrimination (SD) stage of the ATSET, and for 1 to 10 cGy of 56Fe in the Compound Discrimination (CD) stage. On a subject-based level, implementing Machine Learning (ML) classifiers such as the Gaussian Naïve Bayes, Support Vector Machine, and Artificial Neural Networks identifies rats that have a higher tendency for impairment after GCR exposure. The algorithms employ the experimental prescreenperformance scores as multidimensional input features to predict each rodent’s susceptibility to cognitive impairment due to space radiation exposure. The receiver operating characteristic and the precision-recall curves of the ML models show a better prediction of impairment when 56Feis the ion in question in both SD and CD stages. They, however, do not depict impairment due to 4Hein SD and 28Siin CD, suggesting no dose-dependent impairment response in these cases. One key finding of our study is that prescreen performance scores can be used to predict the ATSET performance impairments. This result is significant to crewed space missions as it supports the potential of predicting an astronaut’s impairment in a specific task before spaceflight through the implementation of appropriately trained ML tools. Future research can focus on constructing ML ensemble methods to integrate the findings from the methodologies implemented in this study for morerobust predictionsof cognitive decrements due to space radiation exposure.

space radiation↗

NASA NTRS2021

Ross 19B: An Extremely Cold Companion Discovered via the Backyard Worlds: Planet 9 Citizen Science Project

Through the Backyard Worlds: Planet 9 citizen science project, we have identified a wide-separation (∼10', ∼9900 au projected) substellar companion to the nearby (∼17.5 pc), mid-M dwarf Ross 19. We have developed a new formalism for determining chance alignment probabilities based on the BANYAN Σ tool, and find a 100% probability that this is a physically associated pair. Through a detailed examination of Ross 19A, we find that the system is metal-poor ([Fe/H] = −0.40 ± 0.12) with an age of 7.2 (+3.8, -3.6) Gyr. Combining new and existing photometry and astrometry, we find that Ross 19B is one of the coldest known wide-separation companions, with a spectral type on the T/Y boundary, an effective temperature of 500 (+115, -100) K, and a mass in the range 15–40 M(Jup). This new, extremely cold benchmark companion is a compelling target for detailed characterization with future spectroscopic observations using facilities such as the Hubble Space Telescope or James Webb Space Telescope.

Adam C. Schneider↗

NASA NTRSDate not supplied

Tours of High-containment and Pristine Facilities in Support of Mars Sample Return (MSR) Sample Receiving Facility (SRF) Definition Studies

During 2019 and 2020, the NASA Tiger Team RAMA (acronym of the authors) toured several high-containment biosafety laboratories and pristine space-mission facilities worldwide to better understand their practices, capabilities, and lessons-learned to aid in planning a Sample Receiving Facility (SRF) in support of Mars Sample Return (MSR). The team also included tours of a manufacturer of mobile and modular high-containment facilities as well as manufacturers of isolators and gloveboxes. In addition, the team visited the European Space Agency (ESA)ultraclean and sterile ISO 3 / airborne molecular contamination -9 (AMC-9) isolator line to clean and assemble the most critical hardware for ESA’s ExoMars Mars Lander System, and researchers developing a novel double-walled isolator (DWI) and robotic handling techniques in support of an MSR SRF. The RAMA team visits covered several construction modalities for an MSR SRF: (1) a new traditional fixed facility; (2) use of an existing fixed Biosafety Level 4(BSL-4) facility; (3) a novel modular BSL-4 approach; and (4) a hybrid combination of fixed, modular, and existing facilities. A new fixed facility approach can be tailored to MSR’s needs and is the approach used by all U.S. BSL-4 laboratories constructed to date. However, this approach could be the most expensive modality, take the longest to implement (8-12 years), and have significant programmatic risk of delay. The utilization of an existing BSL-4 facility may be possible depending on the final contamination control and science requirements for the MSR SRF. Due to the internal dimensions of the labs visited and facility structural requirements, it is unlikely that any modification can be made to the facility to meet cleanliness requirements. Furthermore, due to possible construction delays, possible capacity issues, and potential cross contamination vectors from in-house select agents, there may also be significant programmatic risks for sharing an existing facility. Another approach is building a contemporary modular facility. This is a novel approach that has recently been used for a BSL-3/3Ag facilities. The modular elements would be installed in a traditional building or shell structure. A modular facility has many advantages over a traditional fixed facility with lower costs, shorter design/construction/ commissioning schedule, and flexibility for easier retrofits and future expansion. Lastly, a hybrid approach of combining the use of either: (1) a modular facility inside a new fixed facility or (2) a modular and/or fixed BSL-4 annex in conjunction with an existing BSL-4 space should be considered. The advantage of a hybrid approach is that the facility could leverage the strengths of other approaches. Beyond facility construction approaches, the RAMA team investigated technologies and techniques for isolating and handling Martian samples in pristine environments. For example, ESA has been studying and developing a DWI breadboard along with other sample-handling technologies. The research and development investment for clean, remote manipulation and robotics at the start of the facility design phase would be beneficial to the SRF. Additionally, under-standing the lessons learned from Thales Alenia Space during the construction and operation of the most advanced state-of-the-art precision cleaning, sterilization, and assembly glovebox isolators ever developed for spacecraft hardware are also critical for the SRF. The RAMA team lays out a summary of the 18 facilities toured, and includes 43 observations,18 findings, and 22 areas of possible follow-up that the RAMA team and others could pursue to enable further findings. The observations and findings illustrate that constructing an MSR SRF would combine the complexity of both high-containment and pristine facilities, and merging these technologies would be challenging, but achievable.

Mars Sample Return↗

NASA NTRS2022

Identifying Chemical Aerosol Signatures Using Optical Suborbital Observations: How Much Can Optical Properties Tell us about Aerosol Composition?

Improvements in air quality and Earth’s climate predictions require improvements of the aerosol speciation in chemical transport models, using observational constraints. Aerosol speciation (e.g., organic aerosols, black carbon, sulfate, nitrate, ammonium, dust or sea salt) is typically determined using in situ instrumentation. Continuous, routine surface network aerosol composition measurements are not uniformly widespread over the globe. Satellites, on the other hand, can provide a maximum coverage of the horizontal and vertical atmosphere but observe aerosol optical properties (and not aerosol speciation) based on remote sensing instrumentation. Combinations of satellite-derived aerosol optical properties can inform on air mass aerosol types (AMTs e.g., clean marine, dust, polluted continental). However, these AMTs are subjectively defined, might often be misclassified and are hard to relate to the critical parameters that need to be refined in models. In this paper, we derive AMTs that are more directly related to sources and hence to speciation. They are defined, characterized, and derived using simultaneous in situ gas-phase, chemical and optical instruments on the same aircraft during the Study of Emissions and Atmospheric Composition, Clouds, and Climate Coupling by Regional Surveys (SEAC4RS, US, summer of 2013). First, we prescribe well-informed AMTs that display distinct aerosol chemical and optical signatures to act as a training AMT dataset. These in situ observations reduce the errors and ambiguities in the selection of the AMT training dataset. We also investigate the relative skill of various combinations of aerosol optical properties to define AMTs and how much these optical properties can capture dominant aerosol speciation. We find distinct optical signatures for biomass burning (from agricultural or wildfires), biogenic and dust-influence AMTs. Useful aerosol optical properties to characterize these signatures are the extinction angstrom exponent (EAE), the single scattering albedo, the difference of single scattering albedo in two wavelengths, the absorption coefficient, the absorption angstrom exponent (AAE), and the real part of the refractive index (RRI). We find that all four AMTs studied when prescribed using mostly airborne in situ gas measurements, can be successfully extracted from at least three combinations of airborne in situ aerosol optical properties (e.g., EAE, AAE and RRI) over the US during SEAC4RS. However, we find that the optically based classifications for BB from agricultural fires and polluted dust include a large percentage of misclassifications that limit the usefulness of results relating to those classes. The technique and results presented in this study are suitable to develop a representative, robust and diverse source-based AMT database. This database could then be used for widespread retrievals of AMTs using existing and future remote sensing suborbital instruments/networks. Ultimately, it has the potential to provide a much broader observational aerosol data set to evaluate chemical transport and air quality models than is currently available by direct in situ measurements. This study illustrates how essential it is to explore existing airborne datasets to bridge chemical and optical signatures of different AMTs, before the implementation of future spaceborne missions (e.g., the next generation of Earth Observing System (EOS) satellites addressing Aerosol, Cloud, Convection and Precipitation (ACCP) designated observables).

Meloe S F Kacenelenbogen↗

NASA NTRS2021

Ionization Efficiency in the Dayside Ionosphere of Mars: Structure and Variability

Ionization efficiency, the ratio between photoelectron impact ionization and primary photoionization, is an important quantity from the perspective of ionospheric energy balance and as a quantity to be parameterized for use in global simulations. We investigate ionization efficiency using MAVEN in situ measurements of solar extreme ultraviolet (EUV) flux, suprathermal electron flux, and neutral density. Its behavior with respect to pressure and solar zenith angle (SZA) is explained by ionization cross-sections and photoabsorption, plus photoelectron transport near the terminator. We find similar ionization efficiencies between the species CO 2 , O, N 2 , and CO, with Argon ∼40% higher, explained largely by its higher ionization potential. Efficiency depends positively on solar activity, increasing by ∼50–100% (depending on season) from low to moderate solar EUV levels, before flattening at higher EUV levels. EUV spectral hardening appears to be responsible for only ∼15% of this increase, the remainder best explained by variability in neutral composition. We find a negligible dependence of ionization efficiency on the strength and direction of crustal magnetic fields. Efficiencies agree poorly with the theoretical model of Nicholson et al. (2009), https://doi.org/10.1111/j.1365-2966.2009.15463.x, possibly reflecting differences in model versus measured solar EUV spectrum and neutral densities. We fit the data to the empirical parameterization of Mendillo et al. (2011), https://doi.org/10.1029/2011ja016865 but find that a single fit cannot capture ionization efficiency behavior across all dayside SZA values. We believe that an empirical model of Mars ionization efficiency will require MAVEN data and validated transport modeling to reach to sufficiently high pressures to capture Mars' photochemical peaks M1 and M2

Robert Lillis↗

NASA NTRSDate not supplied

An Introduction to Data Visualization

Data visualization can be used to present findings, explore data, and use the human eye to find patterns that a computer would struggle to locate. Borrowing tools from art, storytelling, data analytics and software development, data visualization is an indispensable part of the analysis process. While data visualization usage spans across multiple disciplines and sectors, most never receive formal training in the subject. As such, this tutorial will introduce key data visualization building blocks and how to best use those building blocks for different scenarios and audiences. We will also go over tips on accessibility, design and interactive elements. While this will by no means be a complete overview of the data visualization field, by building a foundation and introducing some rules of thumb, attendees will be better equipped for communicating their findings to their audience.

data visualization↗

NASA NTRS2021

Challenges to Aboveground Biomass Prediction from Waveform Lidar

Accurate accounting of aboveground biomass density (AGBD) is crucial for carbon cycle, biodiversity, and climate change science. The Global Ecosystem Dynamics Investigation (GEDI), which maps global AGBD from waveform lidar, is the first of a new generation of Earth observation missions designed to improve carbon accounting. This paper explores the possibility that lidar waveforms may not be unique to AGBD—that forest stands with different AGBD may produce highly similar waveforms—and we hypothesize that non-uniqueness may contribute to the large uncertainties in AGBD predictions. Our analysis integrates simulated GEDI waveforms from 428 in situ stem maps with output from an individual-based forest gap model, which we use to generate a database of potential forest stands and simulate GEDI waveforms from those stands. We use this database to predict the AGBD of the 428 in situ stem maps via two different methods: a linear regression from waveform metrics, and a waveform-matching approach that accounts for waveform-AGBD non-uniqueness. We find that some in situ waveforms are more unique to AGBD than others, which notably impacts AGBD prediction uncertainty (7–411 Mg ha−1, average of 167 Mg ha−1). We also find that forest structure complexity may influence the non-uniqueness effect; stands with low structural complexity are more unique to AGBD than more mature stands with multiple cohorts and canopy layers. These findings suggest that the non-uniqueness phenomena may be introduced by the measuring characteristics of waveform lidar in combination with how forest structure manifests at small scales, and we discuss how this complexity may complicate uncertainty estimation in AGBD prediction. This analysis suggests a limit to the accuracy and precision of AGBD predictions from lidar waveforms seen in empirical studies, and underscores the need for further exploration of the relationships between lidar remote sensing measurements, forest structure, and AGBD.

GEDI↗

NASA NTRS2022

Solar Temperature Variations Computed from SORCE SIM Irradiances Observed During 2003-2020

NASA’s Solar Radiation and Climate Experiment (SORCE) Spectral Irradiance Monitor (SIM) instrument produced about 17 years of daily average Spectral Solar Irradiance ( SSI ) data for wavelengths 240 nm – 2416 nm. We choose a day of minimal solar activity, 2008-08-24, during the 2008 − 2009 minimum between cycles 23 and 24, and compute the brightness temperature (𝑇 o ) from that day’s solar spectral irradiance (𝑆𝑆𝐼 o ). We consider small variations of T and SSI about these reference values, and derive linear and quadratic analytic approximations by Taylor expansion about the reference day values. To determine approximation accuracy, we compare to exact brightness temperatures T computed from the Planck spectrum, by solving analytically for T , or equivalent root-finding in Wolfram Mathematica. We find that the linear analytic approximation overestimates, while the quadratic underestimates the exact result. This motivates search for statistical “fit” models “in between” the two analytic models, with minimum root-mean-square-error RMSE. We make this search using open-source statistical R software, determine coefficients for linear and quadratic fit models, and compare statistical with analytic RMSE’s. When only linear analytic and fit models are compared, the fit model is superior at ultraviolet, visible, and near infrared wavelengths. This again holds true when comparing only quadratic models. Quadratic is superior to linear for both analytic and statistical models, and statistical fits give smallest RMSE’s. Lastly, we use linear analytic and fit models to find an interpolating function in wavelength, useful in case the SIM results need adjustment to another choices of wavelengths, to compare or extend to any other instrument.

SORCE↗

NASA NTRS2022

Evidence for a Dense, Inhomogeneous Circumstellar Medium in the Type Ia SNR 0519-69.0

We perform an expansion study of the Balmer dominated outer shock of the SNR0519−69.0 in the LMC by using a combination of newHSTWFC3 imagery obtained in 2020 and archival ACS images from 2010 and 2011. Thanks to the very long time baseline, our proper motion measurements are of unprecedented accuracy. We find a wide range of shock velocities, with the fastest shocks averaging 5280 km s−1and the slowest grouping of shocks averaging just 1670 km s−1. We compare the Hα images from HST with X-ray images from Chandra and mid-IR images from Spitzer, finding a clear anti-correlation between the brightness of the remnant in a particular location and the velocity of the blast wave at that location, supporting the idea that the bright knots of X-ray and IR emission result from an interaction with a dense inhomogeneous circumstellar medium. We find no evidence for X-ray emission, thermal or nonthermal, associated with the fastest shocks, as expected if the fastest velocities are the result of the blast wave encountering the lower density ambient medium of the LMC. We derive an age of the remnant of≤670±70 yr, consistent with results derived from previous investigations.

Brian J Williams↗

NASA NTRS2022

SpaceVPX Interoperability Assessment

The existing VMEbus (VersaModular Eurocard bus) International Trade Association (VITA)-78 industry standard, also known as SpaceVPX, is an avionics board- and chassis-level standard derived from the OpenVPX standard as defined in VITA-65. While VITA-65 defines backplane and board-level profiles from COTS vendors to ensure interoperability of products used in developing systems and subsystems, the VITA-78 standard defines SpaceVPX to incorporate fault tolerance features that are required by many spaceflight systems. However, VITA-78 allows so much flexibility that interoperability between modules cannot be assured. This assessment provides guidelines on the use of, and extensions to, the VITA-78 standard to enable avionics interoperability for future NASA missions. The assessment team was comprised of subject matter experts (SMEs) from Goddard Space Flight Center (GSFC), the Jet Propulsion Laboratory (JPL), Johnson Space Center (JSC), and Langley Research Center (LaRC). The team included valuable external consulting support from a SME who was a key participant in the development of the VITA-78 standard. The team had extensive collaboration with the NASA Space Technology Mission Directorate (STMD) High Performance Spaceflight Computing (HPSC) project, specifically in the development of SpaceVPX interconnect findings, observations, and NESC recommendations. To provide an understanding of the breadth of implementations that SpaceVPX must accommodate, multiple NASA use cases were analyzed to assess the requirements for SpaceVPX implementations across a wide range of NASA missions (Appendix C). Applications included crewed missions, science missions, and orbital and surface robotic systems. Product surveys were conducted to assess the level of industry support for SpaceVPX, applications, and the variations in their implementations (Appendix D). In-depth analysis was conducted in the areas of: (a) power management and distribution, (b) form factors and daughtercards, (c) interconnect, and (d) fault tolerance. Leveraging the use cases, product surveys, and SMEs from multiple NASA Centers, these areas were analyzed to determine the range of implementations permitted by the VITA-78 standard and potential interoperability issues. Applicable findings and NESC recommendations were provided for each area. During this assessment, there were multiple opportunities to engage with other agencies to learn about their interest in SpaceVPX, their strategies for implementing SpaceVPX-based systems, and their internal development efforts. These engagements also generated findings and NESC recommendations. Based on this assessment analysis, NESC recommendations were made regarding the feature set and module profiles to support NASA SpaceVPX implementations. This feature set includes restrictions on features in VITA-78, and extensions to the standard. Key recommendations in this area include the use of 10 Gigabit Ethernet and Peripheral Component Interconnect Express (PCIe) as high bandwidth interconnect on the backplane, the retention of SpaceWire interconnect for control functions, and support for 3U (unit) and 6U, form factors for NASA systems. Restrictions were proposed on the usage of user-defined signals to promote interoperability, and specific power managements and distribution schemes for 3U systems. Beyond the technical implementation of SpaceVPX, recommendations were made on areas that warrant further investigation. Primary among these is the recommendation for NASA to collaborate with other space-going agencies and industry to incorporate recommendations into a future ‘dot spec’ of VITA-78. This would ensure wide adoption and availability of the modules that comply with the specification. The assessment includes appendices with candidate module profiles that can be considered as a starting point for this activity, and example systems based on the recommendations. Follow-on studies are recommended for architectures beyond SpaceVPX to address potential enhancements including condensed set of interconnect, software required to implement protocol layers on the interconnect (and other features), alternative power architectures, and system-level testability.

SpaceVPX↗

NASA NTRS2022

Coronal Polarimetry: Determining the Magnetic Origins of Coronal Mass Ejections

Synopsis: The mechanism for the release of stored magnetic energy in solar eruptions remains a major unsolved problem of Heliophysics. Choosing between triggers requires knowledge of pre-eruptive magnetic fields (B). Although linear polarization in visible/infrared (VIR) coronal emission lines reveals intriguing clues about coronal mass ejection (CME) precursor topology, small telescope apertures limit current capability for measuring vector field. Current coronal observations are insufficient to diagnose 3D coronal magnetic fields in CME precursors. Coronal cavities are the ideal candidates for CME precursor studies. BLOS in cavities is a direct measure of stored magnetic free energy, and the presence and location of topological X-points (reconnection locations) and O-points (circulation of B about axis) distinguish predictions of the flux rope-torus-instability and sheared-arcade-breakout CME models. - Finding: Coronal cavities are ubiquitous throughout the solar cycle, erupt as CMEs, and have coronal polarimetric signatures that distinguish between model predictions. - Recommendation: Coronal cavities should be targeted in a comprehensive multiwavelength study of CME precursors & associated eruption-driving mechanisms. Large ground-based VIR telescopes can measure both coronal magnetic field topology and strength through a combination of the saturated Hanle and BLOS -sensitive Zeeman effects. - Finding: The 4m Daniel K. Inouye Solar Telescope (DKIST) and proposed 1.5m Coronal Solar Magnetism Observatory Large Coronagraph (COSMO-LC) make a major leap forward in VIR coronal sensitivity, enabling measurement of vector B. - Recommendation: A dedicated coronal synoptic telescope with a large field-of-view (i.e., COSMO-LC) is needed to identify the dominant CME driving mechanisms, by measuring coronal magnetic fields from precursor state into eruption. In the UV, a new opportunity has arisen to make use of the strong H I Lyman-α coronal line, which obtains a measurement of B that is independent of the Zeeman effect. - Finding: Small-telescope spectropolarimetric capability in the unsaturated Hanle regime provides an independent and complementary coronal magnetic diagnostic to large ground-based telescope measurements. - Recommendation: The proposed 12-cm Coronal Lyman-α Resonance Observatory (CLARO) spectropolarimetric coronagraph demonstrates a path forward for space-based observations of the coronal magnetic field that should be incorporated into future missions away from the Sun-Earth line (e.g., COMPLETE).

magnetic energy↗

NASA NTRS2022

The Ozone–Climate Penalty Over South America and Africa By 2100

Climate change has the potential to increase surface ozone (O3) concentrations, known as the “ozone–climate penalty”, through changes to atmospheric chemistry, transport and dry deposition. In the tropics, the response of surface O3 to changing climate is relatively understudied but has important consequences for air pollution and human and ecosystem health. In this study, we evaluate the change in surface O3 due to climate change over South America and Africa using three state-of-the-art Earth system models that follow the Shared Socioeconomic Pathway 3-7.0 emission scenario from CMIP6. In order to quantify changes due to climate change alone, we evaluate the difference between simulations including climate change and simulations with a fixed present-day climate. We find that by 2100, models predict an ozone–climate penalty in areas where O3 is already predicted to be high due to the impacts of precursor emissions, namely urban and biomass burning areas, although on average, models predict a decrease in surface O3 due to climate change. We identify a small but robust positive trend in annual mean surface O3 over polluted areas. Additionally, during biomass burning seasons, seasonal mean O3 concentrations increase by 15 ppb (model range 12 to 18 ppb) in areas with substantial biomass burning such as the arc of deforestation in the Amazon. The ozone–climate penalty in polluted areas is shown to be driven by an increased rate of O3 chemical production, which is strongly influenced by NOx concentrations and is therefore specific to the emission pathway chosen. Multiple linear regression finds the change in NOx concentration to be a strong predictor of the change in O3 production, whereas increased isoprene emission rate is positively correlated with increased O3 destruction, suggesting NOx-limited conditions over the majority of tropical Africa and South America. However, models disagree on the role of climate change in remote, low-NOx regions, partly because of significant differences in NOx concentrations produced by each model. We also find that the magnitude and location of the ozone–climate penalty in the Congo Basin has greater inter-model variation than that in the Amazon, so further model development and validation are needed to constrain the response in central Africa. We conclude that if the climate were to change according to the emission scenario used here, models predict that forested areas in biomass burning locations and urban populations will be at increasing risk of high O3 exposure, irrespective of any direct impacts on O3 via the prescribed emission scenario.

Surface ozone↗

NASA NTRSDate not supplied

Polarimeter + Lidar Derived Aerosol Particle Number Concentration

In this study, we propose a simple method to derive vertically resolved aerosol particle number concentration (Na) using combined polarimetric and lidar remote sensing observations. This method relies on accurate polarimeter retrievals of the fine-mode column-averaged aerosol particle extinction cross section and accurate lidar measurements of vertically resolved aerosol particle extinction coefficient such as those provided by multiwavelength high spectral resolution lidar. We compare the resulting lidar + polarimeter vertically resolved Na product to in situ Na data collected by airborne instruments during the NASA aerosol cloud meteorology interactions over the western Atlantic experiment (ACTIVATE). Based on all 35 joint ACTIVATE flights in 2020, we find a total of 32 collocated in situ and remote sensing profiles that occur on 11 separate days, which contain a total of 322 cloud-free vertically resolved altitude bins of 150 m resolution. We demonstrate that the lidar + polarimeter Na agrees to within 106% for 90% of the 322 vertically resolved points. We also demonstrate similar agreement to within 121% for the polarimeter-derived column-averaged Na. We find that the range-normalized mean absolute deviation (NMAD) for the polarimeter-derived column-averaged Na is 21%, and the NMAD for the lidar + polarimeter-derived vertically resolved Na is 16%. Taken together, these findings suggest that the error in the polarimeter-only column-averaged Na and the lidar + polarimeter vertically resolved Na are of similar magnitude and represent a significant improvement upon current remote sensing estimates of Na.

Aerosol number concentration↗

NASA NTRS2022

On the paragenetic modes of minerals: A mineral evolution perspective

A systematic survey of 57 different paragenetic modes distributed among 5659 mineral species reveals patterns in the diversity and distribution of minerals related to their evolving formational environments. The earliest minerals in stellar, nebular, asteroid, and primitive Earth contexts were dominated by relatively abundant chemical elements, notably H, C, O, Mg, Al, Si, S, Ca, Ti, Cr, and Fe. Significant mineral diversification subsequently occurred via two main processes, first through gradual selection and concentration of rarer elements by fluid-rock interactions (for example, in hydrothermal metal deposits, complex granite pegmatites, and agpaitic rocks), and then through near-surface biologically mediated oxidation and weathering. We find that 3349 mineral species (59.2%) are known from only one paragenetic context, whereas another 1372 species (24.2%) are associated with two paragenetic modes. Among the most genetically varied minerals are pyrite, albite, hornblende, corundum, magnetite, calcite, hematite, rutile, and baryte, each with 15 or more known modes of formation. Among the most common paragenetic modes of minerals are near-surface weathering/oxidation (1998 species), subsurface hydrothermal deposition (859 species), and condensation at volcanic fumaroles (459 species). In addition, many species are associated with compositionally extreme environments of highly differentiated igneous lithologies, including agpaitic rocks (726 species), complex granite pegmatites (564 species), and carbonatites and related carbonate-bearing magmas (291 species). Biological processes lead to at least 2707 mineral species, primarily as a consequence of oxidative weathering but also through coal-related and other taphonomic minerals (597 species), as well as anthropogenic minerals, for example as byproducts of mining (603 minerals). However, contrary to previous estimates, we find that only ~34% of mineral species form exclusively as a consequence of biological processes. By far the most significant factor in enhancing Earth’s mineral diversity has been its dynamic hydrological cycle. At least 4583 minerals—81% of all species—arise through water-rock interactions. A timeline for mineral-forming events suggests that much of Earth’s mineral diversity was established within the first 250 million years. If life is rare in the universe, then this view of a mineralogically diverse early Earth provides many more plausible reactive pathways over a longer timespan than previous models. If, however, life is a cosmic imperative that emerges on any mineral- and water-rich world, then these findings support the hypothesis that life on Earth developed rapidly in the early stages of planetary evolution

Robert M. Hazen↗

NASA NTRS2019

A Large Source of Cloud Condensation Nuclei from New Particle Formation in the Tropics

Cloud condensation nuclei (CCN) can affect cloud properties and therefore the Earth’s radiative balance. New particle formation (NPF) from condensable vapours in the free troposphere has been suggested to contribute to CCN, especially in remote, pristine atmospheric regions, but direct evidence is sparse, and the magnitude of this contribution is uncertain. Here we use in-situ aircraft measurements of vertical profiles of aerosol size distributions to present a global-scale survey of NPF occurrence. We observed intense NPF occurring at high altitude in tropical convective regions over both the Pacific and Atlantic Oceans. Together with the results of chemical-transport models, our findings indicate that NPF persists at all longitudes as a global-scale band in the tropical upper troposphere, covering about 40% of the Earth’s surface. Furthermore, we find that this NPF in the tropical upper troposphere is a globally important source of CCN in the lower troposphere, where they can affect cloud properties. Our findings suggest that the production of CCN, as these new particles descend towards the surface, is currently not adequately captured in global models, because they tend to underestimate both the magnitude of tropical upper tropospheric NPF and the subsequent growth to CCN sizes. This has potential implications for cloud albedo and the global radiative balance.

Atmospheric chemistry↗

NASA NTRSDate not supplied

Discovery and Analysis of Rare High-Impact Failure Modes using Adversarial RL-Informed Sampling

Adaptive learning agents have tremendous potential to handle critical tasks currently performed by humans. Unfortunately, due to their complexity, it can be difficult to verify that these learning agents do not have critical failure modes. Standard verification and validation methods often do not apply directly to learning agents and Monte Carlo methods have difficulty covering even a small fraction of the state space, especially in multiagent systems or over long time horizons. To overcome this difficulty, we demonstrate an adaptive stress-testing method based on reinforcement learning of correlations that raise the probability of failure. This approach has three key properties: (1) it is able to find rare failure modes with far greater sample efficiency than Monte Carlo methods, (2) it can estimate the true probability of a failure mode despite the inherent bias in the learning method, and (3) it is capable of learning and resampling compact representations of multimodal failure spaces. These properties are important in practice as we need to find disparate failure modes while accounting for their actual relevance. This is a significant advantage over traditional adaptive stress testing methods that give abstract likelihoods of particular failure instances, but cannot estimate the probability of a broader failure mode. We test our algorithm on a simple problem from the aviation domain where an autonomous aircraft lands in gusty wind conditions. The results suggest that we can find failure modes with far fewer samples than the Monte Carlo approach and simultaneously estimate the probability of failure.

reinforcement learning↗

NASA NTRS2022

Polarimeter + Lidar–Derived Aerosol Particle Number Concentration

In this study, we propose a simple method to derive vertically resolved aerosol particle number concentration (Na) using combined polarimetric and lidar remote sensing observations. This method relies on accurate polarimeter retrievals of the fine-mode column-averaged aerosol particle extinction cross section and accurate lidar measurements of vertically resolved aerosol particle extinction coefficient such as those provided by multiwavelength high spectral resolution lidar. We compare the resulting lidar + polarimeter vertically resolved N(a) product to in situ N(a) data collected by airborne instruments during the NASA aerosol cloud meteorology interactions over the western Atlantic experiment (ACTIVATE). Based on all 35 joint ACTIVATE flights in 2020, we find a total of 32 collocated in situ and remote sensing profiles that occur on 11separate days, which contain a total of 322 cloud-free vertically resolved altitude bins of 150 m resolution. We demonstrate that the lidar + polarimeter N(a) agrees to within 106% for 90% of the 322 vertically resolved points. We also demonstrate similar agreement to within 121% for the polarimeter-derived column-averaged N(a). We find that the range-normalized mean absolute deviation (NMAD) for the polarimeter-derived column-averaged Na is 21%, and the NMAD for the lidar + polarimeter-derived vertically resolved Na is 16%. Taken together, these findings suggest that the error in the polarimeter-only column-averaged N(a) and the lidar + polarimeter vertically resolved N(a) are of similar magnitude and represent a significant improvement upon current remote sensing estimates of N(a).

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