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NASA NTRS2018

Cross-Cutting Computational Modeling Project: Integrative Modeling Approach

A wide range of computational models and analyses have been applied to spaceflight risk assessment and countermeasure development. The benefits of using computational modeling to enhance Human Research Program (HRP) goals include the ability to mathematically represent physiological systems, integrate multiple, discrete experimental measures, span multiple temporal and spatial scales, determine important factors within the system and provide estimates of unmeasurable quantities. In the area of application, computational models provide a means of developing simulations to test hypotheses, determining key factors of the system to aid experimental design and bridging gaps in sparse data by mathematically simulating large populations. Specifically, computational models and their supporting analysis tools have the proven potential to integrate analyses of risk factors to enhance mission planning and preparation capabilities and to inform spacecraft design and countermeasure development. Appropriately applied, computational models may allow intelligent, unbiased physiological parameter assessment to enable hypothesis testing and model based design of experiments. HRP recently formed the Computational Modeling Project (CMP), managed out of Glenn Research Center, as a cross-cutting activity aimed at leveraging the growing power and acceptance of computational modeling in informing clinical, physiological, and biological studies. This presentation will provide an overview of the challenges and opportunities in implementing various forms of computational models in support of the HRPs path to risk reduction.

biomechanics↗

NASA NTRS2018

Long-Term Ozone Variability and Trends from Reanalyses

Stratospheric ozone has a profound impact on radiation and chemistry over various spatial and temporal scales. The evolution of stratospheric ozone over the 21st century, however, is not well understood, especially in the lower stratosphere. Highly vertically resolved ozone data from satellite-borne limb sounders have proved to be invaluable for studying ozone in the middle and upper stratosphere but it was not until recently that these measurements were successfully incorporated in atmospheric reanalyses. Validation and comparison studies have demonstrated that the addition of observations from the Microwave Limb Sounder (MLS) on EOS (Earth Observing System) Aura greatly improved the quality of ozone fields in MERRA-2 (Modern-Era Retrospective analysis for Research and Applications, Version 2) making these assimilated data sets more useful for scientific research. In this presentation we demonstrate that multidecadal lower-stratospheric ozone variability and trends can be derived from NASA's MERRA-2 reanalysis ozone. In particular, the reanalysis ozone bias-corrected using a chemistry model simulation as a transfer function agrees very well with recently reprocessed long ozonesonde records. Ozone trends in the lower stratosphere will be discussed in the context of recent findings (Ball et al., 2018) and interpreted in connection with long-term circulation changes in the lower stratosphere. Next, we show that the use of ozone data retrieved from the next generation OMPS (Ozone Mapping Profiler Suite) instruments, including the OMPS Limb Profiler, can successfully extend the reanalyses into the future allowing comprehensive monitoring of global ozone and interpretation of its evolution during the critical period of expected ozone recovery and climate change from increasing concentration of greenhouse gases.

ozone↗

NASA NTRS2018

Sea Surface Salinity Distribution in the Southern Ocean as Observed from Space

Large scale spatial and temporal variabilities of sea surface salinity (SSS) in the Southern Ocean from 2011 to 2017 were studied using products derived from microwave sensors on board Aquarius/SAC-D, Soil Moisture and Ocean Salinity (SMOS), and Soil Moisture Active and Passive (SMAP) satellites. Four products, three from Aquarius and one from SMOS, were evaluated and shown to be generally consistent within 0.3 to 0.6 psu and agree favorably with in situ measurements. However, although the Aquarius products show consistent seasonality of SSS with high values of 34.45 in October and low values of 33.40 in May, the SMOS and SMAP products lack such seasonal variations. This may be caused by larger uncertainties in the SMOS and SMAP data due in part to the lack of concurrent scatterometer measurements that is used to correct for roughness effects. The four products provide similar spatial distributions of SSS with root-mean-square-errors from 0.25 to 0.58 psu. Differences among Aquarius products are mainly due to varying salinity retrieval algorithms, smoothing, and masking of sea ice, while the SMOS product showed the highest SSS deviation that is likely due to the bias-adjustment done on the dataset. Our analyses show that SSS in the Southern Ocean region has significant meridional variations with the lowest SSS near the ice edge and highest at lower latitudes. The SSS is also lowest in summer indicating the predominant influence of sea ice and glacial melt, but it stays low near ice edges even during the growth season.

SSS↗

NASA NTRS2018

NASA's Black Marble Product Suite: Validation Strategy

NASA's Black Marble nighttime lights product suite (VNP46) is available at 500m resolution since January 2012 with data fro the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) onboard the Suomi National Polar-orbiting Platform (SNPP). The retrieval algorithm, developed and implemented for routine global processing at NASA's Land Science Investigator-led Processing System (SIPS), utilizes all high-quality, cloud-free, atmospheric-terrain, vegetation, snow, lunar and stray light corrected radiances to estimate daily nighttime lights (NTL) and other intrinsic surface optical properties. Extensive benchmark tests at representative spatial and temporal scales were conducted on the VNP46 time series record to characterize the uncertainties stemming from upstream data sources. Current and planned validation activities under the Group on Earth Observations (GEO) Human Planet Initiative are aimed at evaluating the products at difference geographic locations and time periods representing the full range of retrieval conditions.

GEO Human Planet↗

NASA NTRS2018

Magnetospheric Constellation: Leveraging Space 2.0 for Big Science

Earth's magnetosphere is a large magnetic cavity formed through the interaction of the solar wind and Earth's intrinsic magnetic field. Solar wind energy enters this cavity through a boundary - the magnetopause - separating Earth's field from the solar wind. This energy leads to many forms of "space weather", including the aurora, geomagnetic storms, and energization of the Van Allen radiation belts. Despite decades of research, we still do not understand the extent of dayside reconnection sites, nor do we have a quantifiable understanding of how much energy enters the magnetosphere during different solar wind conditions - necessary for space weather prediction. On the nightside, impulsive flows at various spatial and temporal scales occur frequently during storms and substorms, and couple to the ionosphere through still unresolved physical mechanisms. Because the magnetosphere is so large, it has been understood since the dawn of the space age that a full understanding of this complex region could only be achieved with a large fleet of in situ spacecraft. NASA has studied one such constellation, the socalled "Magnetospheric Constellation" (MagCon), since the1990's, but it is deemed too expensive to implement using traditional approaches. The CubeSat/ SmallSat revolution represents a fundamental disruption to traditional mission architectures, and in this paper I will discuss how, by leveraging innovation in spacecraft subystems, advanced manufacturing, and access to space, we can finally realize this long-term vision of exploration and discovery. The proposed modular approach, utilizing rideshare and propulsive ESPAs, would also enable worldwide participation in the mission, and is applicable to any constellation mission, including Earth Science missions.

Kepko, Emil Larry↗

NASA NTRS2017

Observations, Modeling, and Predictions of Solar Activity From the Deep Interior to the Corona

Solar activity is a manifestation of magnetic self-organization processes that involve complex dynamical coupling of various layers of the Sun acting over a broad range of spatial and temporal scales. Synergy of observational, theoretical, and modeling efforts is key to understanding solar activity variation, dynamics, and evolution and to developing reliable physics-based forecasts of long-term solar cycles and short-term activity manifestations, “seasons of solar activity”, such as periods of enhanced flaring and CME activity. The session welcomes observers, modelers, and theoreticians to share their results and ideas and to discuss current challenges, development of emerging fields (such as data assimilation), and the analysis of historical and modern observational data using theoretical modeling, interpretations, and predictions.

Deep Interior↗

NASA NTRS2019

Revealing the Multiscale Nature of Turbulence in Space Plasmas with an Innovative Swarm of Spacecraft

Abstract: Turbulence is fundamentally a multiscale phenomena, with energy, mass, and momentum being transported across both spatial and temporal scales. In a magnetized collisionless plasma, there are unresolved questions about the structure of the turbulent transfer of energy, as well as how the energy is extracted from the cascade and dissipated as heat in the constituent charged particles. The plasma in the solar wind acts as an accessible natural laboratory to study these processes, and much progress has indeed been made since the dawn of the space age in understanding turbulence via in situ observations of turbulent plasmas near Earth. However, to date, these observations have been limited to a single, or at best, a tight cluster of points, leading to ambiguities in at what scales energy is contained, how it is transported, and by what mechanism it is dissipated. In this presentation, we describe a heliophysics mission concept aimed at understanding turbulence that is enabled by a swarm of small satellites. The proposed "HelioSwarm" mission will measure turbulent fields and flows and charged particles simultaneously at many points spanning size and time scales from the fluid to sub-ion regime. In doing so, we will be able to disentangle how the turbulence depends on time and space, directly observe the change in internal energy in the plasma, and definitively capture the dynamic relation between turbulence and structures. While the processes under examination are universal, arising throughout our solar system and universe, they are difficult to reproduce in either terrestrial laboratories or numerical simulations, meaning that the only a multipoint observatory in the near-Earth heliosphere will be able to study them in sufficient detail to discern the underlying physics. In this talk, we highlight the enabling role that small satellites play in providing closure on these long-standing but critically important science questions.

Spence, H. E.↗

NASA NTRS2019

Remote Sensing of Solar-Induced Chlorophyll Fluorescence (SIF) in Vegetation: 50 Years of Progress

Remote sensing of solar-induced chlorophyll fluorescence (SIF) is a rapidly advancing front in terrestrial vegetation science, with emerging capability in space-based methodologies and diverse application prospects. Although remote sensing of SIF – especially from space – is seen as a contemporary new specialty for terrestrial plants, it is founded upon a multi-decadal history of research, applications, and sensor developments in active and passive sensing of chlorophyll fluorescence. Current technical capabilities allow SIF to be measured across a range of biological, spatial, and temporal scales. As an optical signal, SIF may be assessed remotely using highly-resolved spectral sensors and state-of-the-art algorithms to distinguish the emission from reflected and/or scattered ambient light. Because the red to far-red SIF emission is detectable non-invasively, it may be sampled repeatedly to acquire spatio-temporally explicit information about photosynthetic light responses and steady-state behaviour in vegetation. Progress in this field is accelerating with innovative sensor developments, retrieval methods, and modelling advances. This review distills the historical and current developments spanning the last several decades. It highlights SIF heritage and complementarity within the broader field of fluorescence science, the maturation of physiological and radiative transfer modelling, SIF signal retrieval strategies, techniques for field and airborne sensing, advances in satellite-based systems, and applications of these capabilities in evaluation of photosynthesis and stress effects. Progress, challenges, and future directions are considered for this unique avenue of remote sensing.

Review↗

NASA NTRS2019

Numerical Reanalyses as a Gateway to Arctic Synthesis

Reanalyses are regularly gridded, retrospective depictions of the physical earth system, which are produced through the correction of a short-term forecast to available observations. In the Arctic, reanalyses are particularly well suited to marshal the sparse observing network to provide a plausible, multivariate representation of conditions. Atmospheric reanalyses such as MERRA-2 (NASA Modern-Era Retrospective analysis for Research and Applications, version 2) and ocean reanalyses such as SODA3 (Univ. Maryland Simple Ocean Data Assimilation version 3) are widely used in Arctic research for diagnostic studies of circulation, model evaluation, and as boundary conditions for a variety of process models. Here, we provide examples that illustrate the utility of reanalyses for providing information on the spatial and temporal scales of recent, rapid changes in the Arctic. Recent trends in Arctic surface temperatures, surface melt over Greenland and Arctic glaciers, and evolving freshwater conditions in the Arctic Ocean are examples where reanalyses can provide information that cannot easily be obtained via other means. These examples provide information on the scale, magnitude, and the uncertainty of recent Arctic change and provide a context for future scenarios. We further quantify uncertainties in key reanalyses variables and approaches for addressing these issues.

Arctic↗

NASA NTRSDate not supplied

TPSAS-NF1676L-10726-DND

The principal component radiative transfer model PCRTM (Xu 2006) simulates spectral longwave radiance at a 0.5cm-1 resolution over the wavelengths (50-2760cm-1) using 280 principal components. The CERES product SSF containing CERES field-of-view (FOV) cloud properties based on MODIS pixel information are used as inputs. NASA GMAO(Global Modeling and Assimilation Office)Geos-4 temperature and humidity profiles, as well as SMOBA (Stratosphere Monitoring Ozone Blended Analysis) ozone profiles allow computations for five years (Jan 2001- Dec 2006) of FOV nadir spectral radiance. The approximately twice daily FOV PCRTM simulations along with CERES broadband measurements are time-space averaged to 10deg zonal monthly data. Analysis of monthly seasonal and deseasonalized interannual variability in terms of brightness temperature are presented. Comparison of interannual variability in the portions of the spectrum seen by the AIRS instrument are shown. Comparisons of spectral integrated PCRTM simulations to CERES broadband longwave radiance measurements are made. In order to study the sensitivity of the spatially and temporally averaged TOA spectrum to various atmospheric properties, we perturbed atmospheric and surface temperatures, humidity, cloud height, cloud fraction, and particle size. The sensitivity of the spectrum to these properties depends on region and seasons. Month to month variability of the longwave spectra to these perturbations is 10 to 20% of the global monthly mean perturbation response. In addition, it depends on time period and size of the area used for averaging spectra. In this poster, the magnitude of sensitivity variability and how the sensitivity changes depending on temporal and spatial scale of averaging will be discussed.

Fred G. Rose↗

NASA NTRS2020

Synergistic Use of SMAP and OCO-2 Data in Assessing the Responses of Ecosystem Productivity to the 2018 U.S. Drought

Soil moisture and gross primary productivity (GPP) estimates from the Soil Moisture Active Passive (SMAP) and solar-induced chlorophyll fluorescence (SIF) from the Orbiting Carbon Observatory-2 (OCO-2) provide new opportunities for understanding the relationship between soil moisture and terrestrial photosynthesis over large regions. Here we explored the potential of the synergistic use of SMAP and OCO-2 based data for monitoring the responses of ecosystem productivity to drought. We used complementary observational information on root-zone soil moisture and GPP (9 km) from SMAP and fine-resolution SIF (0.05°; GOSIF) derived from OCO-2 SIF soundings. We compared the spatial pattern and temporal evolution of anomalies of these variables over the conterminous U.S. during the 2018 drought, and examined to what extent they could characterize the drought-induced variations of flux tower GPP and crop yield data. Our results showed that SMAP GPP and GOSIF could well capture the spatial extent and dynamics of drought indicated by the U.S. Drought Monitor maps and the SMAP root-zone soil moisture deficit. Over the U.S. Southwest, monthly anomalies of soil moisture showed significant positive correlations with those of SMAP GPP (R2=0.44, p<0.001) and GOSIF (R2=0.76, p<0.001), demonstrating strong water availability constraints on plant productivity across dryland ecosystems. We further found that SMAP GPP and GOSIF captured the impact of drought on tower GPP and crop yield. Our results suggest that synergistic use of SMAP and OCO-2 data products can reveal the drought evolution and its impact on ecosystem productivity and carbon uptake at multiple spatial and temporal scales, and demonstrate the value of SMAP and OCO-2 for studying ecosystem function, carbon cycling, and climate change.

Soil Moisture Active Passive↗

NASA NTRSDate not supplied

Presentation Summary: State of the AGN: Progress Toward Understanding Black Hole Accretion Processes

Accretion of plasma onto black holes power some of the most powerfulsystems in the cosmos. Supermassive black holes at the centers ofgalaxies represent the high-mass limit of these objects and so accountfor the most luminous accretors. As a result, their influence spansvast spatial and temporal scales of cosmic phenomena: intraclusterheating, intergalactic media, galactic feedback and star formation,kiloparsec-scale jets/outflows, variability over time scales of minutesto centuries, and luminous multi-wavelength electromagnetic emissionextending all the way down to its event horizon. Their intrigue isheightened by the fact that they lie at the intersection of variousphysical laws---e.g., general relativistic gravity,magnetohydrodynamics, radiation, high-energy particle physics,thermodynamics, and photo-ionization---which all must be reconciled toarrive at a fundamental understanding and probe for new physics, liketests of general relativity. These physics ingredients must beincorporated into simulations performed somehow on dynamical scalesranging from that of the event horizon to parsec-scales. Fortunately,new computational and theoretical techniques---such as GPU computing,radiation transport, and and novel gridding techniques---are enablingprogress to larger scales, more degrees of freedom, and even to binarysystems. Some of the topics we will survey include recent progress onsimulating the relationship between the disk-jet interaction, howtilted black holes behave, radiation-dominated flow, and how binaryAGN affect the standard picture of black hole accretion. Along theway, we will highlight how new technologies have enabled thesescientific rewards. Future directions and open questions will beprovided to inspire discussion and interaction during the session.

Black Holes↗

NASA NTRSDate not supplied

State of the AGN: Progress Toward Understanding Black Hole Accretion Processes

Accretion of plasma onto black holes power some of the most powerful systems in the cosmos. Supermassive black holes at the centers of galaxies represent the high-mass limit of these objects and so account for the most luminous accretors. As a result, their influence spans vast spatial and temporal scales of cosmic phenomena: intracluster heating, intergalactic media, galactic feedback and star formation, kiloparsec-scale jets/outflows, variability over time scales of minutes to centuries, and luminous multi-wavelength electromagnetic emission extending all the way down to its event horizon. Their intrigue is heightened by the fact that they lie at the intersection of various physical laws---e.g., general relativistic gravity, magnetohydrodynamics, radiation, high-energy particle physics, thermodynamics, and photo-ionization---which all must be reconciled to arrive at a fundamental understanding and probe for new physics, like tests of general relativity. These physics ingredients must be incorporated into simulations performed somehow on dynamical scales ranging from that of the event horizon to parsec-scales. Fortunately, new computational and theoretical techniques---such as GPU computing, radiation transport, and and novel gridding techniques---are enabling progress to larger scales, more degrees of freedom, and even to binary systems. Some of the topics we will survey include recent progress on simulating the relationship between the disk-jet interaction, how tilted black holes behave, radiation-dominated flow, and how binary AGN affect the standard picture of black hole accretion. Along the way, we will highlight how new technologies have enabled these scientific rewards. Future directions and open questions will be provided to inspire discussion and interaction during the session.

LISA↗

NASA NTRS2021

Sensing the Ocean Biological Carbon Pump from Space: A Review of Capabilities, Concepts, Research Gaps and Future Developments

The element carbon plays a central role in climate and life on Earth. It is capable of moving among the geosphere, cryosphere, atmosphere, biosphere and hydrosphere. This flow of carbon is referred to as the Earth's carbon cycle. It is also intimately linked to the cycling of other elements and compounds. The ocean plays a fundamental role in Earth's carbon cycle, helping to regulate atmospheric CO2 concentration. The ocean biological carbon pump (OBCP), defined as a set of processes that transfer organic carbon from the surface to the deep ocean, is at the heart of the ocean carbon cycle. Monitoring the OBCP is critical to understanding how the Earth's carbon cycle is changing. At present, satellite remote sensing is the only tool available for viewing the entire surface ocean at high temporal and spatial scales. In this paper, we review methods for monitoring the OBCP with a focus on satellites. We begin by providing an overview of the OBCP, defining and describing the pools of carbon in the ocean, and the processes controlling fluxes of carbon between the pools, from the surface to the deep ocean, and among ocean, land and atmosphere. We then examine how field measurements, from ship and autonomous platforms, complement satellite observations, provide validation points for satellite products and lead to a more complete view of the OBCP than would be possible from satellite observations alone. A thorough analysis is then provided on methods used for monitoring the OBCP from satellite platforms, covering current capabilities, concepts and gaps, and the requirement for uncertainties in satellite products. We finish by discussing the potential for producing a satellite-based carbon budget for the oceans, the advantages of integrating satellite-based observations with ecosystem models and field measurements, and future opportunities in space, all with a view towards bringing satellite observations into the limelight of ocean carbon research.

Robert J. W. Brewin↗

NASA NTRS2019

Fully-polarimetric millimeter-wave spectrometers for measurement of Earth's magnetic field

Earth’s ionosphere responds dynamically over a wide range of temporal and spatial scales to changes in the magnetosphere and solar wind from above, and to neutral atmospheric dynamics from below. Determining the dynamics and coupling of Earth's magnetosphere, ionosphere, and atmosphere by vector magnetic field measurements at all altitudes is essential, as the field plays a major role in controlling the distribution of ionospheric plasma. It is difficult to measure the magnetic B-field, either locally or globally, at the altitudes of the upper mesosphere and lower thermosphere (UMLT) where the transfer of energy and momentum between the plasma and neutral components of the system occur. The 118-GHz imaging magnetometer will measure all four Stokes parameters as a function of frequency about the Zeeman-split center of the 118-GHz molecular oxygen line. We are developing an array of fully-polarimetric millimeterwave radiometer/spectrometers operating near 118 GHz. These low cost, low power, low mass polarimetric 118 GHz millimeter-wave array receivers do not require cooling to meet the sensitivity requirements. With digital spectrometers we will be able to integrate the complete end-to-end system. This work will enable a second generation small satellite mission with an off-nadir viewing instrument comprised of 120 such receivers (arranged so that each spot on the Earth is observed simultaneously by four receivers each) that will globally map the magnetic field in the mesosphere at 42-76 km altitude at a horizontal resolution ~100 km with 1-sigma error of 40-120 nT, in typical mesospheric temperature conditions.

Mannucci, Anthony↗

NASA NTRS2021

Inter-comparison of snow depth over Arctic sea ice from reanalysis reconstructions and satellite retrieval

In this study, we compare eight recently developed snow depth products over Arctic sea ice, which use satellite observations, modeling, or a combination of satellite and modeling approaches. These products are further compared against various ground-truth observations, including those from ice mass balance observations and airborne measurements. Large mean snow depth discrepancies are observed over the Atlantic and Canadian Arctic sectors. The differences between climatology and the snow products early in winter could be in part a result of the delaying in Arctic ice formation that reduces early snow accumulation, leading to shallower snowpacks at the start of the freeze-up season. These differences persist through spring despite overall more winter snow accumulation in the reanalysis-based products than in the climatologies. Among the products evaluated, the University of Washington (UW) snow depth product produces the deepest spring (March–April) snowpacks, while the snow product from the Danish Meteorological Institute (DMI) provides the shallowest spring snow depths. Most snow products show significant correlation with snow depths retrieved from Operational IceBridge (OIB) while correlations are quite low against buoy measurements, with no correlation and very low variability from University of Bremen and DMI products. Inconsistencies in reconstructed snow depth among the products, as well as differences between these products and in situ and airborne observations, can be partially attributed to differences in effective footprint and spatial–temporal coverage, as well as insufficient observations for validation/bias adjustments. Our results highlight the need for more targeted Arctic surveys over different spatial and temporal scales to allow for a more systematic comparison and fusion of airborne, in situ and remote sensing observations.

Lu Zhou↗

NASA NTRS2022

The Effect of Solar Wind Turbulence on Parallel and Oblique Firehose Instabilities

We consider the firehose instability coexisting with the omnipresent ambient solar wind turbulence. The characteristic temporal and spatial scales of the turbulence are comparable to those of the instability. Therefore, turbulence may violate the common assumption of a uniform and stationary background used to describe instabilities and make the properties of the instabilities different. To investigate this effect, we perform threedimensional hybrid simulations with particle-in-cell ions and a quasi-neutralizing electron fluid. We find that the turbulence significantly reduces the growth rates and saturation levels of both instabilities. Comparing the cases with and without turbulence, the former results in a higher temperature anisotropy in the asymptotic marginally stable state at large times. In the former case, the distribution function averaged over the simulation box is also closer to the initial one.

S A Markovskii↗

NASA NTRSDate not supplied

Responses of Microbes to Modeled Space Radiation

The built environment of spaceships is host to a microbial community that affects crew and craft alike. While the static composition of this community has been characterized and its temporal dynamics examined, the mechanisms controlling its make-up and evolutionary trajectory are not understood. Systematic analyses of microbial diversity show consistent patterns in community composition and function. Understanding these patterns' ecological origins remains a significant challenge, as it requires connecting processes at varying temporal and spatial scales. However, it is clear that the state and trajectories of microbial communities are in-part determined by their physical environment. In this regard, the spaceflight environment includes numerous interacting factors that differentiate it from Earth environments, including an altered atmospheric composition, reduced gravity (and thus altered fluid dynamics), and increased ionizing radiation. These factors impart selective pressures on microbial communities that affect their evolutionary trajectories and thus the risks and benefits these communities represent to crew and craft. The radiation environment of space leads to chronic exposure to low doses and is difficult to mimic on Earth. Thus, little is known about how microbial communities in spacecraft will respond and evolve. Therefore, given the limitations of existing studies, we aim to empirically determine how exposure to low doses of ionizing radiation for thousands of cell divisions affects rates of mutation accumulation in bacteria and the trajectory of their evolution. In this way, we will provide a critical set of data for designing safe and robust space missions. Here we discuss our progress towards this aim, including the construction of exposure facilities, our culturing and analysis approach, and preliminary data.

radiation↗