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At least 73 records · Page 4

Hypervelocity impact in stellar media: heat shielding, shock fronts and ablation clouds

The Frontier Plasma Science experiments proposed by our team will model the processes occurring during spacecraft atmospheric entries and meteorite planetary collisions by inserting material targets into the Scrape off Layer (SOL) and edge plasma of a tokamak. This project will investigate important plasma-material processes during high-enthalpy atmospheric entries, including heat flux generation and material ablation. Of particular interest is to explore heat and particle flux detachment in front of the sample using concepts and techniques developed in the latest studies of divertor detachment. Exploration missions to the Solar System’s gaseous giants and hyperbolic re-entries into the Earth’s atmosphere require spacecraft that can withstand high velocity (>10 km/s), high heat fluxes (>10 MW/m2), and corresponding enthalpies. Ablative materials have been used as thermal shields to protect the spacecraft from severe heating during entry. However, developing high enthalpy ablating materials is challenging due to the lack of adequate ground testing facilities. Our team stated that the performance of candidate shielding materials could be assessed in a laboratory environment with multiple in-situ diagnostics, which was enabled by the progress in the tokamak research. Modern machines feature relatively long discharges (~10 s) with well-controlled stable plasma conditions at the edge where the heat flux and the flow speed are similar to those experienced during atmospheric entries. The experiments were carried out at the DIII-D National Fusion Facility in San Diego, CA, operated by General Atomics (GA) for the DoE.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

An Open Benchmark of One Million High-Fidelity Cislunar Trajectories

Cislunar space spans from geosynchronous altitudes to beyond the Moon and will underpin future exploration, science, and security operations. We describe and release an open dataset of one million numerically propagated cislunar trajectories generated with the open-source Space Situational Awareness Python package (SSAPy). The model includes high-degree Earth/Moon gravity, solar gravity, and Earth/Sun radiation pressure; other planetary gravities are omitted by design for computational efficiency. Initial conditions uniformly sample commonly used osculating-element ranges, and each trajectory is propagated for up to six years under a single, fixed start epoch. The dataset is intended as a reusable benchmark for method development (e.g., space domain awareness, navigation, and machine-learning pipelines), a reference library for statistical studies of orbit families, and a starting point for community-driven extensions (e.g., alternative epochs). We report empirically observed stability trends (e.g., a band near ~5 GEO and persistence of some co-orbital classes including L4/L5 librators) as dataset descriptors rather than new dynamical results. The chief contribution is the scale, fidelity, organization (CSV/HDF5 with full state time series and metadata), and open availability, which together lower the barrier to comparative and data-driven studies in the cislunar regime.

79 ASTRONOMY AND ASTROPHYSICS↗

Spectroscopic Investigation of the High-Pressure Behavior of Aliphatic Hydrocarbon: Implications for Planetary Processes

Octadecane (C 18 H 38 ) is an aliphatic hydrocarbon that is abundant in carbonaceous chondritic meteorites. It is debated whether these hydrocarbons found in the meteorite are pristine or are a result of subsequent modifications as these meteorites are delivered to the Earth. It is well-known that meteorites are often subjected to extreme pressures and temperatures upon entering the Earth’s atmosphere. To explore the behavior of octadecane at high pressures, that is, how its molecular structure responds to compression, we use a diamond anvil cell in conjunction with Raman spectroscopy. Here, we find that at room temperatures, upon compression to ~5 GPa, a linear-chain octadecane molecule transforms into a bent-chain configuration. Similar transitions from linear to a bent configuration in other hydrocarbons have been documented. We find a linear correlation between the transition pressure from linear to bent configuration, and the chain length of the alkane, that is, longer chain lengths, is likely to be less stable in the linear configuration under compression. These kinks in the bent-chain configuration are likely sites for the dissociation of the longer chain hydrocarbons to smaller hydrocarbons. The octadecane sample examined in this study did not undergo any additional transition to the highest pressure (~18 GPa) explored in this study.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A phytophotonic approach to enhanced photosynthesis

Photosynthesis is the dominant biotic carbon sink on earth and hence presents an opportunity for enhanced sequestration of CO 2 . If the average net carbon fixation efficiency of terrestrial plants could be increased by 3.3%, all anthropogenic CO 2 accumulating in the atmosphere could instead be reduced and incorporated into terrestrial biomass. Plants make inefficient use of the overly abundant sunlight available to them, a result of having evolved to be competitive and survive highly dynamic environmental conditions rather than maximize photosynthetic productivity. We explore herein a phytophotonic approach to enhanced photosynthesis, whereby sunlight is redistributed by means of luminescent or persistent luminescent (PersL) materials. Phytophotonics has potential at varied scales, ranging from photobioreactors to greenhouses all the way to crops in the field, the latter having the potential to impact planetary CO 2 levels. The approach is three-fold: a spectral redistribution to relieve high-light-stress at the top surface of leaves and increasingly drive photosynthesis deeper in leaves and canopies; a minute-scale temporal redistribution to bridge periods of intermittent shade and reduce shock associated with variable light conditions; and a multiple-hour temporal redistribution to shift a fraction of high-intensity midday lighting to evening hours. Based on simulations of photoluminescent materials and light quality experiments with a model algal system, it is shown that while lengthening daylight hours will require significant improvements in PersL materials, the other two approaches show more immediate promise. We demonstrate a means of concentrating PersL light from SrAl 2 O 4 :Eu,Dy, approaching levels needed to effectively bridge periods of natural shade, and outline the scientific questions and technical hurdles remaining to realize the benefits of the proposed spectral shift.

59 BASIC BIOLOGICAL SCIENCES↗

Exploring the High-Pressure Phases of Carbon through X-ray Diffraction of Dynamic Compression Experiments on Sandia’s Z Pulsed Power Facility

The carbon phase diagram is rich with polymorphs which possess very different physical and optical properties ideal for different scientific and engineering applications. An understanding of the dynamically driven phase transitions in carbon is particularly important for applications in inertial confinement fusion, as well as planetary and meteorite impact histories. Experiments on the Z Pulsed Power Facility at Sandia National Laboratories generate dynamically compressed high-pressure states of matter with exceptional uniformity, duration, and size that are ideal for investigations of fundamental material properties. X-ray diffraction (XRD) is an important material physics measurement because it enables direct observation of the strain and compression of the crystal lattice, and it enables the detection and identification of phase transitions. Several unique challenges of dynamic compression experiments on Z prevent using XRD systems typically utilized at other dynamic compression facilities, so novel XRD diagnostics have been designed and implemented. We performed experiments on Z to shock compress carbon (pyrolytic graphite) samples to pressures of 150–320 GPa. The Z-Beamlet Laser generated Mn-Heα (6.2 keV) X-rays to probe the shock-compressed carbon sample, and the new XRD diagnostics measured changes in the diffraction pattern as the carbon transformed into its high-pressure phases. Quantitative analysis of the dynamic XRD patterns in combination with continuum velocimetry information constrained the stability fields and melting of high-pressure carbon polymorphs.

36 MATERIALS SCIENCE↗

NED_Asteroid_Energy_Deposition

In the event of a potentially catastrophic asteroid impact, with sufficient warning time, deploying a nuclear device remains a powerful option for planetary defense if a kinetic impactor proves insufficient. Predicting the effectiveness of a potential nuclear deflection or disruption mission depends on accurate multiphysics simulations of the device's x-ray energy deposition into the asteroid and the resulting material ablation. These simulations span many orders of magnitude, require a variety of different complex physics packages, and are computationally expensive. Having an efficient and accurate way of modeling this system is necessary for exploring a mission's sensitivity to the asteroid's range of physical properties. To expedite future simulations, we present a completed x-ray energy deposition model developed using the radiation-hydrodynamics code Kull which can be used to initiate a nuclear mitigation mission hydrocode. The model spans a wide variety of possible mission initial conditions: four different asteroid-like materials (Silicon Dioxide, Forsterite, Iron, and Ice), two different source spectra (1 and 2 keV blackbodies), and then a broad range of radiation fluences (0.0001 to 1 kt per square meter), source durations (10 to 100 ns), and asteroid porosities (0 to 80 percent). Using blowoff momentum as the primary metric, the modelinitiated simulation results match the full radiation-hydrodynamics results to within 10 percent. Please reference the journal article: Burkey et al., X-Ray Energy Deposition Model for Simulating Asteroid Response to a Nuclear Planetary Defense Mitigation Mission, Planetary Science Journal, (2023) for more information.

Managan, RobertA↗

Simulating Atmospheric Processes in Earth System Models and Quantifying Uncertainties With Deep Learning Multi‐Member and Stochastic Parameterizations

Abstract Deep learning is a powerful tool to represent subgrid processes in climate models, but many application cases have so far used idealized settings and deterministic approaches. Here, we develop stochastic parameterizations with calibrated uncertainty quantification to learn subgrid convective and turbulent processes and surface radiative fluxes of a superparameterization embedded in an Earth System Model (ESM). We explore three methods to construct stochastic parameterizations: (a) a single Deep Neural Network (DNN) with Monte Carlo Dropout; (b) a multi‐member parameterization; and (c) a Variational Encoder Decoder with latent space perturbation. We show that the multi‐member parameterization improves the representation of convective processes, especially in the planetary boundary layer, compared to individual DNNs. The respective uncertainty quantification illustrates that methods (b) and (c) are advantageous compared to a dropout‐based DNN parameterization regarding the spread of convective processes. Hybrid simulations with our best‐performing multi‐member parameterizations remained challenging and crash within the first days. Therefore, we develop a pragmatic partial coupling strategy relying on the superparameterization for condensate emulation. Partial coupling reduces the computational efficiency of hybrid Earth‐like simulations but enables model stability over 5 months with our multi‐member parameterizations. However, our hybrid simulations exhibit biases in thermodynamic fields and differences in precipitation patterns. Despite this, the multi‐member parameterizations enable improvements in reproducing tropical extreme precipitation compared to a traditional convection parameterization. Despite these challenges, our results indicate the potential of a new generation of multi‐member machine learning parameterizations leveraging uncertainty quantification to improve the representation of stochasticity of subgrid effects.

Behrens, Gunnar [Deutsches Zentrum für Luft‐ und R↗

JWST Noise Floor. I. Random Error Sources in JWST NIRCam Time Series

James Webb Space Telescope (JWST) transmission and emission spectra will provide invaluable glimpses of transiting exoplanet atmospheres, including possible biosignatures. This promising science from JWST, however, will require exquisite precision and understanding of systematic errors that can impact the time series of planets crossing in front of and behind their host stars. Here, we provide estimates of the random noise sources affecting JWST Near-Infrared Camera (NIRCam) time-series data on the integration-to-integration level. We find that 1/f noise can limit the precision of grism time series for two groups (230–1000 ppm depending on the extraction method and extraction parameters), but will average down like the square root of N frames/reads. The current NIRCam grism time-series mode is especially affected by 1/f noise because its GRISMR dispersion direction is parallel to the detector fast-read direction, but could be alleviated in the GRISMC direction. Care should be taken to include as many frames as possible per visit to reduce this 1/f noise source: thus, we recommend the smallest detector subarray sizes one can tolerate, four output channels, and readout modes that minimize the number of skipped frames (RAPID or BRIGHT2). We also describe a covariance-weighting scheme that can significantly lower the contributions from 1/f noise as compared to sum extraction. We evaluate the noise introduced by pre-amplifier offsets, random telegraph noise, and high dark current resistor capacitor (RC) pixels and find that these are correctable below 10 ppm once background subtraction and pixel masking are performed. We explore systematic error sources in a companion paper.

79 ASTRONOMY AND ASTROPHYSICS↗

The substantial role of May soil temperature over Central Asia for summer surface air temperature variation and prediction over Northeastern China

The slowly varying soil temperature can exert local and nonlocal influences on regional climate system, and may thus provide a critical source of subseasonal-to-seasonal climate prediction. In this study, we identify that soil temperature in May over the key region of Central Asia (42 °N–50 °N, 62 °E–80 °E, KRCA) from Noah, Mosaic, CLM and ERA-interim datasets is closely linked to variations of the surface air temperature, daily maximum temperature and hot days over Northeastern China in summer (June-July-August), with correlation coefficients of regional average detrended time series ranging from 0.42 to 0.54, and all significant at the 99% confidence level for the period of 1979-2018. The possible physical mechanism behind the substantial downstream impacts of soil temperature over Central Asia are explored via diagnostical analysis combined with regional climate model experiments. Warmer soil temperature in May over the KRCA tends to cause positive anomalies of geopotential height in summer over Northeastern China through the Rossby wave propagation, and associated stronger subsidence warming, less cloud cover, more solar radiation reaching the surface, higher planetary boundary layer, and stronger thermal advection at 850 hPa, which provide favorable conditions for warmer surface air temperature particularly in the daytime as well as more hot days. Here this study further reveals that soil temperature over Central Asia in May makes important contribution to prediction of summer surface air temperature, daily maximum temperature and hot days over Northeastern China in terms of regional average time series and spatial patterns. Our findings highlight the previously-unknown substantial role of antecedent soil temperature condition over Central Asia for summer surface air temperature variation and prediction over Northeastern China.

54 ENVIRONMENTAL SCIENCES↗

Catalog of Planetary Nebulae Detected by GALEX and Corollary Optical Surveys

Planetary nebulae (PNs) consist of an ionized envelope surrounding a hot central star (CSPN) that emits mostly at ultraviolet (UV) wavelengths. UV observations, therefore, provide important information on both the CSPN and the nebula. We have matched the PNs in the Hong Kong/Australian Astronomical Observatory/Strasbourg Hα catalog with the Galaxy Evolution Explorer (GALEX) UV sky surveys, the Sloan Digital Sky Survey (SDSS) data release 16, and the Panoramic Survey Telescope and Rapid Response System (Pan-STARRS) PS1 second release. A total of 671 PNs were observed by GALEX with the far-UV (FUV; 1344 Å–1786 Å) and/or the near-UV (NUV; 1771 Å–2831 Å) detectors on (GUVPNcat); 83 were observed by SDSS (PNcatxSDSSDR16) and 1819 by Pan-STARRS (PNcatxPS1MDS). We merged a distilled version of these matched catalogs into GUVPNcatxSDSSDR16xPS1MDS, which contains a total of 375 PNs with both UV and optical photometry over a total spectral coverage of ~1540 Å–9610 Å. We analyzed separately 170 PNs resolved in GALEX images and determined their UV radius by applying a flux profile analysis. The CSPN flux could be extracted separately from the PN emission for 8 and 50 objects with SDSS and Pan-STARRS counterparts, respectively. The multiband photometry was used to distinguish between compact and extended PNs and CSPNs (binary CSPNs) by color–color diagram analysis. We found that compact PN candidates could be identified by using the r - i < - 0.4 and -1 < FUV-NUV < 1 colors, whereas binary CSPN candidates in given T eff ranges (all with color r-i > -0.4) can be identified in the color region (FUV-NUV) ≤ 6(r-i)+1.3, -0.8 < FUV-NUV < 0.4, and r-i < 0.75.

79 ASTRONOMY AND ASTROPHYSICS↗

Ground-based temperature and humidity profiling: combining active and passive remote sensors

Abstract. Thermodynamic profiles in the planetary boundary layer (PBL) are important observations for a range of atmospheric research and operational needs. These profiles can be retrieved from passively sensed spectral infrared (IR) or microwave (MW) radiance observations or can be more directly measured by active remote sensors such as water vapor differential absorption lidars (DIALs). This paper explores the synergy of combining ground-based IR, MW, and DIAL observations using an optimal-estimation retrieval framework, quantifying the reduction in the uncertainty in the retrieved profiles and the increase in information content as additional observations are added to IR-only and MW-only retrievals. This study uses ground-based observations collected during the Perdigão field campaign in central Portugal in 2017 and during the DIAL demonstration campaign at the Atmospheric Radiation Measurement Southern Great Plains site in 2017. The results show that the information content in both temperature and water vapor is higher for the IR instrument relative to the MW instrument (thereby resulting in smaller uncertainties) and that the combined IR + MW retrieval is very similar to the IR-only retrieval below 1.5 km. However, including the partial profile of water vapor observed by the DIAL increases the information content in the combined IR + DIAL and MW + DIAL water vapor retrievals substantially, with the exact impact vertically depending on the characteristics of the DIAL instrument itself. Furthermore, there is a slight increase in the information content in the retrieved temperature profile using the IR + DIAL relative to the IR-only; this was not observed in the MW + DIAL retrieval.

54 ENVIRONMENTAL SCIENCES↗

Predicting Biological Cleanliness: An Empirical Bayes Approach for Spacecraft Bioburden Accounting

To comply with the international planetary protection policy set forth by the Committee on Space Research and NASA Agency level requirements, spacecraft destined to biologically sensitive planetary bodies have to minimize terrestrial biological contamination. Analysis, testing and inspection are the standard forward verification activities that are used to demonstrate compliance with the biological contamination requirements. For testing of spacecraft surface areas, a swab or wipe sample is collected from surfaces prior to last access and subsequently processed in the lab using NASA Approved Planetary Protection Methods for Culture Based Assays. Raw data resulting from this assay is then statistically treated employing a mathematical paradigm stemming from the 1970’s Viking Lander Project to generate the bioburden density and total microbial bioburden present. This standard approach arbitrarily accounts for error and provides an upper conservative bound as it reports the maximum number of spores estimated to be present on flight hardware surfaces. A bioburden density estimate factors in the following variables: the observed bioburden count, representative volume processed, sampling efficiencies. Notably, to account for error in the approach, a 0 observed count is arbitrarily changed to a count of 1 for each hardware grouping. The data generated by spacecraft bioburden verification campaigns in the past have resulted in <80% of wipes and <90% of swabs containing a bioburden count of 0. As such, having a robust and well documented statistical approach for dealing with the probability of low incident rates is necessary to be able to estimate spacecraft bioburden. Being able to statistically describe the bioburden distribution and associated confidence level is a gamechanger for the development of bioburden allocations during mission design and will allow for tighter management of risk throughout spacecraft build. Thus, Empirical Bayes statistical approach was evaluated to estimate the microbial bioburden on spacecraft to mitigate the aforementioned mathematical concerns and provide a probabilistic bioburden distribution of the flight hardware surface. For application of this approach to performing bioburden calculations, a range of non-informative prior assumptions on hardware surfaces are explored for Bayesian analyses while informative priors using posterior distributions from prior assays are utilized for Empirical Bayes analyses. Several non-informative priors are currently under investigation to assess fitness including use of these priors to serve as a foundation to build off of NASA specification values or a basis of risk to account for unknowns during the integration and testing process. Informative priors under consideration are generated using sampled bioburden values from hardware originating within like processing environments (e.g. vendor cleaning process or similar assembly process), temporal spacecraft status events as a prediction for hardware cleanliness of future samples, and heritage system bioburden actuals to predict allocation for subsequent missions. Informative priors and probabilistic bioburden distributions are then validated using data sets from the Mars Exploration Rover, Mars Science Laboratory, and InSight missions. Using Empirical Bayes approach to generate a probabilistic bioburden distribution as demonstrated through mission use cases provides a valid approach for use in the end-to-end requirements verification process.

97 MATHEMATICS AND COMPUTING↗

Thermally induced structural competitiveness and metastability of body-centered-cubic iron under nonequilibrium conditions

The structure and stability of iron near melting at multi-megabar pressures are of significant interest in high pressure physics and earth and planetary sciences. While the body-centered cubic (BCC) phase is generally recognized as unstable at lower temperatures, its stability relative to the hexagonal close-packed (HCP) phase at high temperatures (approximately 0.5 eV) in the Earth’s inner core (IC) remains a topic of ongoing theoretical and experimental debate. Motivated by a series of studies attempting to understand the state of the IC and resulting in contradictory findings, we aim to explore the physical factors that may contribute to this confusion in a broader context. Our ab initio calculations show a significant drop in energy, the emergence of a plateau and a local minimum in the potential energy surface, and stabilization of all phonon modes of BCC iron at elevated electron temperatures (>1–1.5 eV). These effects increase the competition among the BCC, HCP, and the face-centered cubic (FCC) phases and lead to the metastability of the BCC structure. Furthermore, at pressure-temperature conditions relevant to the IC, we can expect substantial coexistence of FCC and HCP iron due to their similar free energies and low transition barrier (∼0.2 eV/atom), and the thermodynamic stability of BCC iron is enhanced by its substantial lattice vibration entropy. In conclusion, these findings provide a clear theoretical framework for understanding iron phase relations and solidification processes, both experimentally and in the IC.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Bayesian Framework for Bioburden Density Estimation in Planetary Protection

To comply with the international planetary protection policy set forth by the Committee on Space Research and NASA Agency level requirements, spacecraft destined to biologically sensitive planetary bodies have to minimize terrestrial biological contamination. Analysis, testing and inspection are the standard forward verification activities that are used to demonstrate compliance with the biological contamination requirements. For testing of spacecraft surface areas, a swab or wipe sample is collected from surfaces prior to last access and subsequently processed in the lab using NASA Approved Planetary Protection Methods for Culture Based Assays. Raw data resulting from this assay is then statistically treated employing a mathematical paradigm stemming from the 1970’s Viking Lander Project to generate the bioburden density and total microbial bioburden present. This standard approach arbitrarily accounts for error and provides an upper conservative bound as it reports the maximum number of spores estimated to be present on flight hardware surfaces. A bioburden density estimate factors in the following variables: the observed bioburden count, representative volume processed, sampling efficiencies. Notably, to account for error in the approach, a 0 observed count is arbitrarily changed to a count of 1 for each hardware grouping. The data generated by spacecraft bioburden verification campaigns in the past have resulted in <80% of wipes and <90% of swabs containing a bioburden count of 0. As such, having a robust and well documented statistical approach for dealing with the probability of low incident rates is necessary to be able to estimate spacecraft bioburden. Being able to statistically describe the bioburden distribution and associated confidence level is a gamechanger for the development of bioburden allocations during mission design and will allow for tighter management of risk throughout spacecraft build. Thus, Empirical Bayes statistical approach was evaluated to estimate the microbial bioburden on spacecraft to mitigate the aforementioned mathematical concerns and provide a probabilistic bioburden distribution of the flight hardware surface. For application of this approach to performing bioburden calculations, a range of non-informative prior assumptions on hardware surfaces are explored for Bayesian analyses while informative priors using posterior distributions from prior assays are utilized for Empirical Bayes analyses. Several non-informative priors are currently under investigation to assess fitness including use of these priors to serve as a foundation to build off of NASA specification values or a basis of risk to account for unknowns during the integration and testing process. Informative priors under consideration are generated using sampled bioburden values from hardware originating within like processing environments (e.g. vendor cleaning process or similar assembly process), temporal spacecraft status events as a prediction for hardware cleanliness of future samples, and heritage system bioburden actuals to predict allocation for subsequent missions. Informative priors and probabilistic bioburden distributions are then validated using data sets from the Mars Exploration Rover, Mars Science Laboratory, and InSight missions. Using Empirical Bayes approach to generate a probabilistic bioburden distribution as demonstrated through mission use cases provides a valid approach for use in the end-to-end requirements verification process.

97 - MATHEMATICS AND COMPUTING↗

Probing Clustering Dynamics between Silicon and PAA or LiPAA Slurries under Processing Conditions

This work explores the complex interplay between slurry aggregation, agglomeration, and conformation (i.e., shape) of poly(acrylic acid) (PAA)- and lithiated PAA-based silicon slurries as a function of the shear rate and the resulting slurry homogeneity. These values were measured by small-angle neutron scattering (SANS) and rheology-coupled ultra-SANS at conditions relevant to battery electrode casting. Different binder solution preparation methods, either a ball milling (BM) process or a planetary centrifugal mixing (PCM) process, dramatically modify the resulting polymer dynamics and organization around a silicon material. This is due to the different energy profiles of mixing where the more violent and higher energy PCM causes extensive breakdown and reformation of the binder, which is now likely in a branched conformation, while the lower energy BM results in simply lower-molecular weight linear polymers. In conclusion, the breakdown and reorganization of the polymer structure affect silicon slurry homogeneity, which affects subsequent electrode architecture.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Exploring the Meteorological Impacts of Surface and Rooftop Heat Mitigation Strategies Over a Tropical City

Different heat mitigation technologies have been developed to improve the thermal environment in cities. However, the regional impacts of such technologies, especially in the context of a tropical city, remain unclear. The deployment of heat mitigation technologies at city-scale can change the radiation balance, advective flow, and energy balance between urban areas and the overlying atmosphere. We used the mesoscale Weather Research and Forecasting model coupled with a physically based single-layer urban canopy model to assess the impacts of five different heat mitigation technologies on surface energy balance, standard surface meteorological fields, and planetary boundary layer (PBL) dynamics for premonsoon typical hot summer days over a tropical coastal city in the month of April in 2018, 2019, and 2020. Results indicate that the regional impacts of cool materials (CMs), super-cool broadband radiative coolers, green roofs (GRs), vegetation fraction change, and a combination of CMs and GRs (i.e., “Cool city (CC)”) on the lower atmosphere are different at diurnal scale. Results showed that super-cool materials have the maximum potential of ambient temperature reduction of 1.6°C during peak hour (14:00 LT) compared to other technologies in the study. During the daytime hours, the PBL height was considerably lower than the reference scenario with no implementation of strategies by 700 m for super-cool materials and 500 m for both CMs and CC cases; however, the green roofing system underwent nominal changes over the urban area. During the nighttime hours, the PBL height increased by CMs and the CC strategies compared to the reference scenario, but minimal changes were evident for super-cool materials. The changes of temperature on the vertical profile of the heat mitigation implemented city reveal a stable PBL over the urban domain and a reduction of the vertical mixing associated with a pollution dome. This would lead to crossover phenomena above the PBL due to the decrease in vertical wind speed. Therefore, assessing the coupled regional impact of urban heat mitigation over the lower atmosphere at city-scale is urgent for sustainable urban planning.

54 ENVIRONMENTAL SCIENCES↗

Standardized multi-omics of Earth’s microbiomes reveals microbial and metabolite diversity

Despite advances in sequencing, lack of standardization makes comparisons across studies challenging and hampers insights into the structure and function of microbial communities across multiple habitats on a planetary scale. Here we present a multi-omics analysis of a diverse set of 880 microbial community samples collected for the Earth Microbiome Project. We include amplicon (16S, 18S, ITS) and shotgun metagenomic sequence data, and untargeted metabolomics data (liquid chromatography-tandem mass spectrometry and gas chromatography mass spectrometry). We used standardized protocols and analytical methods to characterize microbial communities, focusing on relationships and co-occurrences of microbially related metabolites and microbial taxa across environments, thus allowing us to explore diversity at extraordinary scale. In addition to a reference database for metagenomic and metabolomic data, we provide a framework for incorporating additional studies, enabling the expansion of existing knowledge in the form of an evolving community resource. We demonstrate the utility of this database by testing the hypothesis that every microbe and metabolite is everywhere but the environment selects. Our results show that metabolite diversity exhibits turnover and nestedness related to both microbial communities and the environment, whereas the relative abundances of microbially related metabolites vary and co-occur with specific microbial consortia in a habitat-specific manner. We additionally show the power of certain chemistry, in particular terpenoids, in distinguishing Earth’s environments (for example, terrestrial plant surfaces and soils, freshwater and marine animal stool), as well as that of certain microbes including Conexibacter woesei (terrestrial soils), Haloquadratum walsbyi (marine deposits) and Pantoea dispersa (terrestrial plant detritus). This Resource provides insight into the taxa and metabolites within microbial communities from diverse habitats across Earth, informing both microbial and chemical ecology, and provides a foundation and methods for multi-omics microbiome studies of hosts and the environment.

59 BASIC BIOLOGICAL SCIENCES↗

X-Ray Energy Deposition Model for Simulating Asteroid Response to a Nuclear Planetary Defense Mitigation Mission

Abstract In the event of a potentially catastrophic asteroid impact, with sufficient warning time, deploying a nuclear device remains a powerful option for planetary defense if a kinetic impactor or other means of deflection proves insufficient. Predicting the effectiveness of a potential nuclear deflection or disruption mission depends on accurate multiphysics simulations of the device's X-ray energy deposition into the asteroid and the resulting material ablation. The relevant physics in these simulations span many orders of magnitude, require a variety of different complex physics packages, and are computationally expensive. Having an efficient and accurate way of modeling this system is necessary for exploring a mission's sensitivity to the asteroid's range of physical properties. To expedite future simulations, we present a completed X-ray energy deposition model developed using the radiation-hydrodynamics code Kull that can be used to initiate a nuclear mitigation mission calculation. The model spans a wide variety of possible mission initial conditions: four different asteroid-like materials at a range of porosities, two different source spectra, and a broad range of radiation fluences, source durations, and angles of incidence. Using blowoff momentum as the primary metric, the model-initiated simulation results match the full radiation-hydrodynamics results to within 10%.

79 ASTRONOMY AND ASTROPHYSICS↗